diff --git "a/cropmodel-deadtrees_metadata.json" "b/cropmodel-deadtrees_metadata.json" new file mode 100644--- /dev/null +++ "b/cropmodel-deadtrees_metadata.json" @@ -0,0 +1,31 @@ +{ + "epoch": 40, + "global_step": 7161, + "pytorch-lightning_version": "1.5.10", + "state_dict": "OrderedDict({'model.conv1.weight': tensor([[[[ 1.7423e-02, 1.7370e-02, -1.3997e-02, ..., -4.1919e-02,\n -4.3347e-02, -6.9088e-02],\n [ 7.1121e-03, 6.7674e-03, 1.4364e-02, ..., 1.0979e-04,\n -2.1816e-02, -3.7354e-02],\n [ 2.3632e-02, 2.2722e-02, 1.3994e-02, ..., 1.0079e-01,\n 6.1910e-02, 5.3112e-02],\n ...,\n [-4.5380e-03, 2.3072e-02, -1.4565e-02, ..., -1.2890e-01,\n -7.6816e-02, 8.5470e-03],\n [-8.6062e-04, 4.2836e-02, 5.7355e-02, ..., 2.1883e-02,\n -3.4606e-02, -1.5829e-02],\n [-8.2720e-02, -3.5402e-02, -2.1170e-02, ..., 3.2448e-02,\n 2.0207e-02, -1.5618e-04]],\n\n [[-1.4875e-02, 1.3371e-02, 2.4230e-02, ..., 5.1390e-02,\n 4.2491e-02, -7.8635e-03],\n [-5.8244e-03, 1.8211e-02, 6.5439e-02, ..., 1.5501e-01,\n 1.4288e-01, 1.2009e-01],\n [-4.6395e-02, -7.9401e-02, -9.4662e-02, ..., 1.1578e-01,\n 1.6338e-01, 1.7566e-01],\n ...,\n [ 2.2661e-02, 5.8203e-03, -9.1607e-02, ..., -3.8614e-01,\n -3.0712e-01, -1.4055e-01],\n [ 7.5414e-02, 1.3004e-01, 1.4433e-01, ..., -1.0811e-02,\n -1.2782e-01, -1.3110e-01],\n [-1.2565e-02, 7.0969e-02, 1.3377e-01, ..., 1.7838e-01,\n 1.0663e-01, 2.0229e-02]],\n\n [[-1.5890e-02, -3.8928e-03, 8.7841e-03, ..., 2.4506e-02,\n 2.5698e-02, -2.7711e-03],\n [-7.5735e-03, 5.1739e-03, 4.8511e-02, ..., 1.2209e-01,\n 1.1834e-01, 1.1314e-01],\n [-6.2653e-02, -1.0250e-01, -1.0156e-01, ..., 1.0312e-01,\n 1.3804e-01, 1.5003e-01],\n ...,\n [ 2.1388e-02, 5.1374e-03, -8.0512e-02, ..., -3.1692e-01,\n -2.5648e-01, -1.2292e-01],\n [ 6.8269e-02, 1.0668e-01, 1.2594e-01, ..., -8.9066e-03,\n -1.2651e-01, -1.2429e-01],\n [-8.7121e-03, 6.4376e-02, 1.1933e-01, ..., 1.8877e-01,\n 1.1249e-01, 2.2275e-02]]],\n\n\n [[[ 7.3430e-02, 4.2992e-02, 5.6618e-02, ..., 2.8001e-02,\n 5.2057e-02, 6.8501e-02],\n [ 6.5587e-02, 2.2562e-02, 2.5222e-02, ..., -4.9152e-02,\n -2.0772e-02, -3.0064e-03],\n [ 6.0727e-02, 1.9524e-02, -3.1996e-03, ..., -1.2938e-01,\n -9.3858e-02, -5.5808e-02],\n ...,\n [ 2.5296e-02, -4.9696e-02, -1.0953e-01, ..., -2.5471e-01,\n -2.3896e-01, -2.0009e-01],\n [ 5.7729e-02, -1.9971e-02, -5.6444e-02, ..., -2.3550e-01,\n -1.9545e-01, -1.6158e-01],\n [ 6.1550e-02, 4.9567e-03, -4.7190e-02, ..., -1.5868e-01,\n -1.3994e-01, -9.7472e-02]],\n\n [[-9.4601e-02, -6.7234e-02, -7.0357e-02, ..., -3.6372e-02,\n -7.9327e-02, -8.4046e-02],\n [-6.7696e-02, -3.5407e-02, -8.3701e-03, ..., 5.8143e-02,\n 2.6254e-02, -1.1645e-02],\n [-9.0732e-02, -2.1020e-02, 3.4258e-02, ..., 2.0599e-01,\n 1.6162e-01, 8.8530e-02],\n ...,\n [-3.9135e-02, 6.6221e-02, 1.7249e-01, ..., 4.5838e-01,\n 3.7879e-01, 2.6062e-01],\n [-6.3747e-02, 1.5005e-02, 1.3270e-01, ..., 3.6834e-01,\n 3.2165e-01, 2.0698e-01],\n [-1.0289e-01, -2.6725e-02, 4.2138e-02, ..., 2.2918e-01,\n 1.8800e-01, 1.2154e-01]],\n\n [[ 4.4022e-02, 4.8726e-02, 1.7226e-02, ..., 3.3497e-02,\n 3.0300e-02, 4.6292e-02],\n [ 3.6207e-02, 3.4362e-02, -1.4973e-03, ..., 2.2331e-03,\n 4.4206e-03, 2.5600e-02],\n [ 2.3700e-02, 1.8004e-02, -1.4688e-02, ..., -7.5649e-02,\n -7.3812e-02, -2.4443e-02],\n ...,\n [ 2.7551e-02, 1.6011e-04, -8.1038e-02, ..., -1.8544e-01,\n -1.7324e-01, -6.3658e-02],\n [ 3.2957e-02, -1.1235e-02, -5.6409e-02, ..., -1.5320e-01,\n -1.2967e-01, -4.6528e-02],\n [ 5.2521e-02, 3.6159e-02, -1.3967e-02, ..., -4.5150e-02,\n -5.4028e-02, 2.0263e-04]]],\n\n\n [[[ 8.3269e-03, 1.6708e-02, 2.4774e-03, ..., -2.8923e-02,\n -2.9017e-02, -2.9015e-02],\n [ 7.8428e-03, 2.3590e-02, 1.2144e-02, ..., -7.5235e-03,\n -1.1780e-02, -3.1196e-02],\n [ 6.8515e-03, 3.0211e-02, 2.5150e-02, ..., 1.4913e-02,\n 2.7543e-03, -2.7594e-03],\n ...,\n [-6.1665e-05, 1.3197e-02, 3.0223e-04, ..., 3.7801e-02,\n 4.8027e-02, 7.4737e-02],\n [-1.2891e-02, 8.4314e-03, -1.4619e-03, ..., 4.1942e-03,\n 2.0213e-02, 7.3929e-02],\n [-1.6681e-02, 3.1067e-05, -5.4686e-03, ..., -1.2327e-03,\n 3.0831e-02, 8.7258e-02]],\n\n [[ 1.2349e-02, 8.9617e-03, 4.9161e-03, ..., 1.6767e-02,\n 3.7474e-02, 4.8172e-02],\n [ 1.1508e-02, 8.9820e-03, -3.2068e-03, ..., 2.9637e-02,\n 5.4333e-02, 4.0372e-02],\n [ 1.1583e-03, 2.7551e-03, -1.0432e-02, ..., 4.2679e-02,\n 5.7193e-02, 4.6712e-02],\n ...,\n [-1.6521e-02, -4.2786e-02, -8.5215e-02, ..., -4.9313e-02,\n -2.4213e-02, 6.2354e-04],\n [-8.3501e-04, -8.0220e-03, -4.8236e-02, ..., -8.6928e-02,\n -7.2460e-02, -2.5666e-02],\n [ 3.1781e-02, 2.5571e-02, -2.2853e-03, ..., -4.8432e-02,\n -3.7857e-02, -8.6870e-03]],\n\n [[ 9.4966e-03, -3.4626e-02, -2.8403e-02, ..., 7.3513e-03,\n 4.5188e-02, 4.5209e-02],\n [-1.6072e-02, -6.1474e-02, -6.3074e-02, ..., -1.4132e-02,\n 1.9797e-02, -4.8545e-03],\n [ 9.2336e-03, -3.8960e-02, -5.2791e-02, ..., 5.8548e-04,\n 1.1278e-02, -4.7385e-03],\n ...,\n [ 7.4635e-03, -5.4657e-02, -9.9695e-02, ..., -8.7201e-02,\n -9.7791e-02, -1.1151e-01],\n [ 2.0652e-02, -1.7371e-02, -5.5375e-02, ..., -1.1038e-01,\n -1.4238e-01, -1.4650e-01],\n [ 6.0446e-02, 1.7768e-02, -7.8140e-03, ..., -6.7596e-02,\n -1.0654e-01, -1.2524e-01]]],\n\n\n ...,\n\n\n [[[ 1.8896e-02, 2.0661e-02, 3.3691e-02, ..., 5.8899e-03,\n 4.5569e-02, -7.1463e-03],\n [-1.8771e-02, 5.7080e-02, 6.0451e-02, ..., -5.7159e-02,\n 8.5759e-02, -2.5616e-02],\n [-4.4024e-02, 1.0950e-01, 7.7987e-02, ..., -8.6644e-02,\n 1.5331e-01, -3.0070e-02],\n ...,\n [ 3.3058e-03, 1.2712e-01, -4.7450e-02, ..., 6.0374e-02,\n 1.5954e-01, -3.8973e-02],\n [ 5.7343e-03, 6.3007e-02, -5.8367e-02, ..., 4.8132e-02,\n 8.4208e-02, -4.4002e-02],\n [ 1.5908e-02, 5.3924e-03, -6.5587e-02, ..., 5.2903e-02,\n 4.9250e-02, -1.4116e-02]],\n\n [[ 1.3638e-02, 4.5322e-02, 5.1178e-04, ..., -6.7908e-02,\n 4.5383e-02, 4.8562e-02],\n [ 7.8524e-03, 1.3050e-01, 3.1334e-02, ..., -1.4652e-01,\n 1.4769e-01, 8.4441e-02],\n [ 9.2742e-03, 2.2090e-01, 3.4693e-02, ..., -1.7875e-01,\n 2.6272e-01, 9.6199e-02],\n ...,\n [ 4.8008e-02, 1.9671e-01, -1.3636e-01, ..., 4.4886e-02,\n 2.8747e-01, 5.3626e-02],\n [ 2.6285e-02, 9.5424e-02, -1.3510e-01, ..., 5.5676e-02,\n 1.5844e-01, -1.2105e-02],\n [ 1.5773e-02, 2.9138e-02, -1.0506e-01, ..., 7.3529e-02,\n 8.4518e-02, -8.1891e-03]],\n\n [[ 1.3020e-03, 1.9189e-02, 7.7214e-03, ..., -4.2918e-02,\n 5.9098e-03, 9.9404e-03],\n [-2.5975e-02, 7.4532e-02, 6.3130e-02, ..., -5.5890e-02,\n 7.6678e-02, 1.5331e-02],\n [-4.1582e-02, 1.2521e-01, 7.9715e-02, ..., -7.3005e-02,\n 1.3707e-01, -2.4824e-03],\n ...,\n [-4.2284e-03, 1.2260e-01, -4.8267e-02, ..., 4.0609e-02,\n 1.2848e-01, -2.5814e-02],\n [-5.8908e-03, 6.5694e-02, -5.0160e-02, ..., 3.7227e-02,\n 6.9522e-02, -4.2827e-02],\n [ 2.4446e-03, 3.1890e-02, -4.3880e-02, ..., 4.2656e-02,\n 3.3862e-02, -2.8787e-02]]],\n\n\n [[[ 4.0286e-02, 4.5570e-02, 3.6697e-02, ..., -3.9689e-02,\n -3.8607e-03, 8.7347e-03],\n [ 4.9105e-02, 4.8604e-02, 4.4186e-02, ..., -1.1997e-01,\n -8.9827e-02, -3.1905e-02],\n [ 8.8968e-02, 7.9026e-02, 6.8614e-02, ..., -2.1794e-01,\n -1.1710e-01, -2.3616e-02],\n ...,\n [ 3.5394e-02, 4.0068e-03, -1.4797e-01, ..., -2.5483e-01,\n -1.1369e-01, 4.1363e-02],\n [ 2.0551e-02, -2.6625e-02, -1.4642e-01, ..., -2.4816e-01,\n -2.8178e-02, 8.4261e-02],\n [-6.6820e-03, -5.7579e-02, -1.5126e-01, ..., -1.8630e-01,\n 1.2014e-02, 1.0187e-01]],\n\n [[-6.4620e-03, 8.4323e-03, 1.3344e-02, ..., 1.0995e-03,\n 2.3139e-03, -2.4625e-03],\n [ 1.7517e-02, 1.4860e-02, 3.4854e-02, ..., -5.2084e-03,\n -1.5112e-02, -7.7805e-03],\n [ 2.0823e-02, 1.4847e-02, 5.5040e-02, ..., -6.3476e-02,\n -6.9942e-03, 1.6063e-02],\n ...,\n [-6.4089e-03, 1.6636e-02, -3.5916e-02, ..., -4.5881e-02,\n -2.6389e-02, 4.6530e-02],\n [ 1.1896e-02, 1.6470e-02, -8.5888e-03, ..., -6.3729e-02,\n 1.3637e-02, 3.8382e-02],\n [ 1.2375e-02, 9.8441e-03, 3.6258e-03, ..., -2.8815e-02,\n 2.9565e-02, 3.3153e-02]],\n\n [[-4.3705e-02, -2.4073e-02, -2.2908e-02, ..., 1.4914e-02,\n 1.3241e-02, -2.0062e-02],\n [-2.9768e-02, -2.4631e-02, 3.5454e-03, ..., 4.5266e-02,\n 2.3629e-02, -4.5591e-03],\n [-3.7815e-02, -4.1441e-02, 1.9576e-02, ..., 3.5082e-02,\n 4.4664e-02, -5.8571e-03],\n ...,\n [-2.7588e-02, 1.1644e-02, 2.0002e-02, ..., 6.6457e-02,\n 8.4571e-03, -2.6714e-02],\n [-9.0928e-03, 1.9996e-02, 5.1682e-02, ..., 4.9328e-02,\n 3.0420e-02, -3.7907e-02],\n [-1.3657e-02, 9.9937e-03, 5.1298e-02, ..., 3.8106e-02,\n 1.8021e-02, -4.3264e-02]]],\n\n\n [[[ 1.4598e-02, -3.3817e-02, 5.5868e-02, ..., -5.7429e-02,\n 5.2747e-03, 1.5446e-04],\n [-5.0103e-02, 4.9528e-02, -3.1935e-02, ..., 1.3350e-02,\n -2.7653e-02, -1.7924e-02],\n [ 5.0754e-02, -4.8068e-02, -4.3133e-02, ..., -2.1932e-01,\n -7.2934e-03, 3.0930e-02],\n ...,\n [-3.4313e-02, 9.2640e-02, 1.1581e-01, ..., 5.2017e-01,\n -4.9485e-02, -6.1947e-02],\n [-9.9378e-03, 1.0036e-01, -2.0043e-01, ..., 2.2992e-01,\n -2.6669e-01, 1.2160e-01],\n [-1.2908e-02, 4.9417e-03, -7.6956e-02, ..., -6.0077e-02,\n 3.0109e-02, -3.6961e-02]],\n\n [[ 1.6478e-02, -4.2184e-02, 3.7397e-02, ..., -4.6173e-02,\n 2.3550e-02, -9.2604e-03],\n [-4.6685e-02, 6.0044e-02, -2.2951e-02, ..., 2.3048e-02,\n -2.8932e-03, -6.4245e-03],\n [ 3.6943e-02, -6.8452e-02, -2.6507e-02, ..., -2.6630e-01,\n 5.0869e-02, 3.4791e-02],\n ...,\n [-3.0239e-02, 1.3114e-01, 1.2162e-01, ..., 6.4871e-01,\n -1.9801e-02, -1.2524e-01],\n [-1.5060e-02, 1.2428e-01, -2.4909e-01, ..., 3.2819e-01,\n -3.2304e-01, 9.2470e-02],\n [ 6.2156e-03, 2.7530e-02, -8.2152e-02, ..., -7.1334e-02,\n 1.7640e-02, -1.7339e-02]],\n\n [[ 1.2585e-02, -3.9822e-02, 1.5856e-02, ..., -4.9154e-02,\n 2.4267e-02, 7.9401e-04],\n [-3.3055e-02, 7.3638e-02, -3.2115e-02, ..., 4.3057e-02,\n -1.0724e-02, -1.8203e-02],\n [ 6.2423e-02, -4.6217e-02, -1.3985e-01, ..., -1.3479e-01,\n 3.0507e-03, 1.2399e-02],\n ...,\n [-1.0786e-02, 9.9415e-03, 1.4551e-01, ..., 4.6289e-01,\n -1.6905e-01, -2.8713e-02],\n [-4.0803e-02, 3.9612e-02, -1.2468e-01, ..., 1.0443e-01,\n -2.7851e-01, 1.6612e-01],\n [ 1.4830e-02, 2.1806e-02, -1.3802e-02, ..., -1.1449e-01,\n 6.6131e-02, -7.6500e-03]]]]), 'model.bn1.weight': tensor([2.3385e-01, 2.9016e-01, 3.0658e-01, 2.7459e-01, 2.1334e-01, 3.1581e-01,\n 2.2771e-01, 2.2883e-01, 2.1365e-01, 2.9258e-01, 2.0320e-01, 3.3184e-01,\n 1.8086e-01, 1.1246e-08, 1.9625e-01, 2.0680e-01, 2.4543e-01, 2.1493e-01,\n 1.8654e-01, 3.1568e-01, 1.9772e-01, 2.2698e-01, 2.1431e-01, 2.1520e-01,\n 2.5119e-01, 3.0062e-01, 2.4289e-01, 2.0928e-01, 1.3899e-01, 3.2147e-01,\n 2.2886e-01, 8.2336e-02, 4.3495e-01, 2.0265e-01, 2.7876e-01, 3.4878e-01,\n 2.9830e-01, 2.5796e-01, 2.4204e-01, 2.1381e-01, 3.8588e-01, 2.0792e-01,\n 3.7640e-01, 3.3510e-01, 5.0407e-01, 1.9003e-01, 2.3887e-01, 2.7110e-01,\n 3.9128e-01, 1.8998e-01, 2.1021e-01, 2.6245e-01, 5.0382e-01, 2.3110e-01,\n 2.1211e-01, 2.6078e-01, 2.3693e-01, 1.6543e-01, 4.5454e-01, 1.6906e-01,\n 2.4740e-01, 2.4803e-01, 3.8772e-01, 1.9009e-01]), 'model.bn1.bias': tensor([ 2.1993e-01, 6.2183e-01, 1.2379e-02, 1.2887e-01, 1.6348e-01,\n 1.4390e-01, 1.5602e-01, 1.8563e-01, 2.1633e-01, 1.9617e-01,\n 1.2637e-01, -2.0073e-01, 1.6121e-01, -3.9217e-08, 2.5151e-01,\n 2.0790e-01, 5.4763e-01, 2.1790e-01, 2.2846e-01, 4.7369e-01,\n 2.5003e-01, 2.0099e-01, 2.1552e-01, 6.6213e-01, 2.3378e-01,\n 6.5980e-01, 1.9283e-01, 1.9750e-01, 1.1148e-01, 3.2275e-01,\n 1.1708e-01, 3.1975e-02, 7.7180e-01, 2.6145e-01, 3.3539e-01,\n 5.8465e-01, 1.4543e-01, 1.7586e-01, 2.0013e-01, 1.7351e-01,\n 8.0244e-01, 2.4375e-01, -4.2044e-01, 8.4956e-01, -3.7088e-01,\n 2.4415e-01, 1.8119e-01, 3.2131e-01, -2.7269e-01, 2.3657e-01,\n 2.7082e-01, 5.3020e-02, -4.9799e-01, 1.5498e-01, 1.8505e-01,\n 2.8712e-01, 4.1400e-01, -1.0650e-01, -3.1122e-01, -2.4879e-02,\n 9.3526e-02, 1.7754e-01, 8.2494e-01, 2.5704e-01]), 'model.bn1.running_mean': tensor([-1.4520e-01, 1.2603e+00, -3.7678e-01, 8.3902e-02, 2.2798e-02,\n 2.1165e-02, -1.6159e-02, -2.6231e-02, -5.9153e-02, -1.0745e-01,\n -3.1967e-02, -4.7975e-02, -2.3648e-02, 3.5683e-07, 2.3002e-02,\n -3.3673e-02, -4.7523e-02, 1.8248e-04, 6.3467e-02, 9.7352e-01,\n 1.6224e-03, -5.6854e-02, -2.7506e-02, -8.8085e-01, -7.2485e-02,\n -3.4302e-01, 6.3017e-03, -6.0989e-02, 4.8727e-02, -9.7606e-01,\n 6.3868e-02, -1.1763e-03, 6.9602e-01, 8.7695e-02, 6.0290e-01,\n -1.4772e+00, -1.8199e-02, 1.8632e-02, -1.5678e-02, -5.6249e-02,\n 3.8495e-01, 1.4944e-01, -6.1160e-02, -4.0895e-01, -6.6193e-01,\n 1.6886e-01, 3.7487e-02, -2.5112e-01, 4.1534e-01, 3.0326e-02,\n -7.8398e-02, 3.8408e-02, -3.4915e-01, -3.7936e-03, 5.9046e-02,\n 4.1466e-02, -6.0197e-01, 6.5984e-02, -6.6795e-01, 1.3837e-01,\n 6.0493e-02, -5.6205e-02, -2.3435e-01, -2.3528e-02]), 'model.bn1.running_var': tensor([4.5050e-01, 1.5653e+00, 9.0205e-01, 2.5418e+00, 1.1977e-01, 3.8435e+00,\n 1.4737e-01, 1.1366e-01, 1.0078e-01, 2.3350e+00, 1.9981e-01, 1.0517e+00,\n 1.8583e-01, 1.1350e-12, 4.2033e-02, 8.1119e-02, 6.6736e-01, 8.9722e-02,\n 5.8261e-02, 5.2584e+00, 2.9491e-02, 1.2638e-01, 5.1641e-02, 1.2665e+00,\n 4.0508e-01, 1.2017e+00, 1.3578e-01, 1.1837e-01, 1.7823e-01, 3.6359e+00,\n 7.2710e-01, 1.4111e-01, 3.1809e+00, 5.4360e-02, 2.3469e+00, 3.1897e+00,\n 3.2758e+00, 1.2464e+00, 1.6241e-01, 1.8627e-01, 6.6974e+00, 1.1172e-01,\n 7.9704e-01, 1.4092e+00, 3.2367e+00, 1.7656e-01, 1.2377e-01, 1.5984e+00,\n 1.4090e+00, 3.4823e-02, 1.9637e-01, 5.3290e-01, 2.2513e+00, 1.4368e-01,\n 2.3352e-01, 6.2779e-01, 6.0176e-01, 9.8054e-02, 3.9494e+00, 5.1127e-01,\n 5.2639e-01, 3.8728e-01, 5.4092e+00, 5.0303e-02]), 'model.bn1.num_batches_tracked': tensor(7160), 'model.layer1.0.conv1.weight': tensor([[[[-0.0013]],\n\n [[ 0.0351]],\n\n [[-0.0187]],\n\n ...,\n\n [[ 0.0911]],\n\n [[-0.2911]],\n\n [[-0.1610]]],\n\n\n [[[ 0.1077]],\n\n [[ 0.0058]],\n\n [[ 0.0328]],\n\n ...,\n\n [[ 0.0666]],\n\n [[-0.0916]],\n\n [[-0.1379]]],\n\n\n [[[-0.0095]],\n\n [[ 0.0124]],\n\n [[-0.0154]],\n\n ...,\n\n [[ 0.0798]],\n\n [[ 0.0774]],\n\n [[-0.0376]]],\n\n\n ...,\n\n\n [[[ 0.0027]],\n\n [[-0.0111]],\n\n [[ 0.0162]],\n\n ...,\n\n [[ 0.0145]],\n\n [[-0.0626]],\n\n [[ 0.0076]]],\n\n\n [[[-0.0601]],\n\n [[ 0.0111]],\n\n [[ 0.0328]],\n\n ...,\n\n [[-0.0250]],\n\n [[-0.0096]],\n\n [[ 0.0124]]],\n\n\n [[[-0.0545]],\n\n [[-0.1162]],\n\n [[ 0.0400]],\n\n ...,\n\n [[ 0.0535]],\n\n [[ 0.2453]],\n\n [[-0.0015]]]]), 'model.layer1.0.bn1.weight': tensor([2.2993e-01, 1.7672e-01, 1.3860e-01, 1.5243e-01, 1.3880e-01, 1.8358e-01,\n 1.5320e-01, 4.5110e-08, 1.5525e-01, 1.4040e-01, 2.3224e-01, 1.9086e-01,\n 1.8779e-01, 1.4427e-01, 1.3271e-01, 1.0483e-01, 3.7495e-01, 1.2541e-01,\n 3.1577e-01, 2.6881e-01, 2.5226e-01, 2.9888e-01, 1.8575e-01, 2.1088e-08,\n 3.3569e-01, 1.9941e-01, 3.0727e-01, 1.1805e-08, 1.5186e-01, 1.5859e-01,\n 1.4396e-01, 1.4311e-01, 1.1835e-01, 1.9015e-01, 1.4386e-01, 3.5263e-01,\n 1.5187e-01, 2.9250e-01, 2.5590e-01, 1.1185e-01, 2.6497e-01, 1.3658e-01,\n 1.1275e-01, 1.0725e-01, 2.8849e-01, 3.2215e-01, 1.3978e-01, 2.3577e-01,\n 3.3215e-01, 2.9119e-01, 1.2728e-01, 3.0518e-01, 1.0693e-01, 1.3096e-01,\n 2.0682e-01, 1.5850e-01, 2.6574e-08, 1.9726e-01, 2.8797e-08, 1.7765e-01,\n 3.0137e-01, 1.6473e-01, 2.7674e-01, 2.4443e-01]), 'model.layer1.0.bn1.bias': tensor([ 4.2852e-01, 5.0787e-02, -8.1387e-02, 7.1578e-02, 2.7892e-01,\n -5.9122e-03, 9.5093e-02, -1.0086e-07, -1.4815e-01, -5.4820e-02,\n 4.6692e-02, 2.1413e-01, 4.9796e-02, 1.2465e-01, 1.3774e-01,\n 1.3914e-01, -1.1324e-01, 1.5039e-01, -1.3044e-01, -5.4366e-02,\n -3.4564e-02, -1.6418e-02, 6.0456e-02, -6.5736e-08, -6.5690e-02,\n 7.0700e-02, -1.3131e-01, -6.4411e-08, -2.0813e-02, 1.0125e-01,\n 2.5444e-01, -8.2965e-02, -3.3498e-02, -1.6487e-01, 1.0052e-01,\n -1.0749e-01, 1.9903e-01, 2.1912e-02, -7.6569e-02, 9.2460e-02,\n 1.6274e-02, -3.5207e-02, 1.6210e-01, 1.1095e-01, 2.8488e-02,\n -1.0594e-01, -4.8784e-02, 4.9704e-01, -1.5140e-01, -1.0150e-01,\n 1.3420e-02, -6.4833e-02, -5.0822e-02, 1.1741e-01, -2.7427e-01,\n 2.7342e-03, -7.7156e-08, 7.8928e-02, -8.4474e-08, 2.2714e-01,\n -7.2317e-02, -1.6100e-01, -3.2962e-02, 5.2536e-01]), 'model.layer1.0.bn1.running_mean': tensor([-6.9368e-01, -3.9090e-01, 4.0074e-01, -2.5663e-01, -1.2186e-01,\n -3.4271e-01, -1.9568e-01, -1.4821e-07, 1.6884e-01, -4.5611e-01,\n -3.4338e-01, 1.2152e+00, -1.5331e-01, -2.7555e-01, -4.1979e-01,\n -4.0165e-02, -4.2778e-01, 8.0182e-01, -3.1685e-01, -3.3891e-01,\n -1.6509e-01, -3.4197e-02, -1.3131e-01, -1.0389e-08, -4.5980e-01,\n -1.8951e-01, -2.6420e-01, 9.7710e-10, -3.3818e-01, -2.7827e-01,\n -4.1369e-02, 1.5493e-01, -3.4250e-02, -1.5826e-01, -2.6422e-01,\n -4.4850e-01, -2.9098e-01, -2.6814e-01, -2.3782e-01, 3.3163e-01,\n -1.1007e-01, -1.2123e-01, -2.7279e-01, -5.3523e-01, -1.9164e-01,\n -3.4187e-01, -4.5975e-01, -3.1974e-01, -1.8213e-01, -4.2871e-01,\n -7.6328e-02, -3.6335e-01, 8.8403e-02, -4.0497e-01, -8.7680e-03,\n -6.9611e-01, -9.5807e-09, -2.3523e-01, -6.7049e-08, 1.1648e+00,\n 5.1154e-03, 4.9466e-02, -5.0438e-01, -7.5706e-02]), 'model.layer1.0.bn1.running_var': tensor([1.1744e-01, 1.6118e-02, 1.0355e-02, 1.5181e-02, 3.1851e-02, 1.2504e-02,\n 1.5169e-02, 2.8788e-15, 9.7345e-03, 2.0180e-02, 3.9226e-02, 1.1510e-01,\n 1.1711e-02, 8.8234e-03, 1.8740e-02, 6.7672e-03, 8.1154e-02, 5.3730e-02,\n 4.6299e-02, 5.6826e-02, 2.6576e-02, 3.7328e-02, 1.5577e-02, 5.4517e-16,\n 7.7153e-02, 3.1602e-02, 4.8766e-02, 6.1247e-16, 2.1589e-02, 1.6077e-02,\n 5.1534e-02, 9.2920e-03, 7.7222e-03, 2.9372e-02, 2.1801e-02, 8.0167e-02,\n 3.7515e-02, 6.4421e-02, 6.5180e-02, 2.6633e-02, 4.3020e-02, 1.1597e-02,\n 2.7667e-02, 9.0046e-03, 4.9602e-02, 7.5345e-02, 2.3218e-02, 2.7902e-01,\n 7.9585e-02, 4.9000e-02, 1.3696e-02, 7.4747e-02, 9.4011e-03, 1.0913e-02,\n 2.8421e-02, 2.9498e-02, 9.2546e-16, 1.9701e-02, 9.7502e-16, 1.0454e-01,\n 3.4100e-02, 1.8001e-02, 6.2885e-02, 2.5688e-01]), 'model.layer1.0.bn1.num_batches_tracked': tensor(7160), 'model.layer1.0.conv2.weight': tensor([[[[ 2.0919e-09, -1.4152e-09, 6.5850e-09],\n [ 4.7922e-09, 3.2819e-09, 9.4284e-10],\n [ 6.4763e-09, -3.0156e-09, -2.3958e-09]],\n\n [[ 1.1471e-08, 1.2815e-08, 1.3568e-08],\n [ 1.0737e-08, 4.9712e-09, 3.8516e-09],\n [ 1.0572e-08, 1.2153e-08, 6.9175e-09]],\n\n [[-6.8447e-09, -2.8470e-09, -1.5396e-09],\n [ 4.8804e-09, -3.0935e-09, 2.3919e-09],\n [ 5.2998e-09, -1.4133e-11, -7.5312e-09]],\n\n ...,\n\n [[-6.4828e-09, -7.6425e-09, -9.5572e-09],\n [-7.0080e-09, -4.0208e-09, -4.5819e-09],\n [-4.9349e-09, -5.4604e-10, -1.3119e-08]],\n\n [[-1.0458e-09, -6.9635e-09, -5.1090e-09],\n [-3.4306e-10, -4.2656e-09, -2.2703e-09],\n [-1.8570e-09, -4.8467e-09, -3.5571e-09]],\n\n [[ 1.8746e-09, 8.6741e-10, -5.5741e-10],\n [ 2.6233e-10, -5.0061e-09, 5.8350e-09],\n [ 2.4322e-10, 1.6342e-10, 3.3284e-09]]],\n\n\n [[[-2.9123e-02, -8.9639e-04, 2.4541e-02],\n [-3.7399e-03, -9.6462e-03, 1.6058e-02],\n [ 1.7717e-02, 1.7121e-02, -2.2063e-03]],\n\n [[-2.9638e-03, 4.7599e-03, 1.0888e-02],\n [ 1.7562e-02, 2.1370e-02, 1.7209e-02],\n [ 1.9383e-02, 1.9737e-02, -7.1393e-03]],\n\n [[ 9.5171e-04, -6.1962e-03, 1.2232e-02],\n [-1.4542e-03, -1.8858e-02, -1.0515e-02],\n [-2.7671e-04, -8.1750e-03, -1.9135e-02]],\n\n ...,\n\n [[ 1.9853e-03, 4.2481e-03, 8.4517e-03],\n [ 8.7366e-03, 4.5638e-03, 4.8403e-04],\n [ 1.5158e-02, 1.1159e-02, 4.7456e-03]],\n\n [[-5.8988e-03, -9.3484e-04, 7.2068e-03],\n [ 4.3430e-03, 8.6585e-02, 5.9759e-03],\n [-1.1858e-02, -1.1357e-02, 4.8535e-04]],\n\n [[-2.0126e-02, -3.4672e-03, -2.5906e-02],\n [-9.4510e-03, 2.0620e-02, 4.7318e-03],\n [-2.4712e-02, 1.1002e-02, 1.1281e-02]]],\n\n\n [[[ 4.6214e-02, 4.8295e-02, 2.6300e-02],\n [ 4.6956e-02, 5.6739e-02, 5.0466e-02],\n [ 5.0093e-02, 5.2526e-02, 3.4226e-02]],\n\n [[ 2.2587e-03, -7.0663e-03, 1.2653e-02],\n [ 1.0851e-02, 8.1221e-03, 1.8340e-02],\n [ 1.3817e-02, 1.8573e-02, 1.0262e-02]],\n\n [[ 3.0218e-03, -1.8700e-02, 6.4533e-03],\n [-2.7253e-02, -1.2406e-02, 2.6065e-02],\n [-6.6470e-03, -2.9249e-03, 2.0098e-02]],\n\n ...,\n\n [[ 2.9052e-02, 2.0336e-02, 3.3774e-02],\n [ 3.0709e-02, -7.8804e-03, 3.6706e-02],\n [ 3.0330e-02, 3.2190e-02, 4.2706e-02]],\n\n [[ 1.1355e-03, -1.8728e-02, 1.7115e-02],\n [-1.2277e-02, 1.8460e-03, 2.0013e-03],\n [ 2.4300e-03, -6.6539e-03, -1.8018e-03]],\n\n [[ 5.9674e-03, -2.4415e-02, -1.1262e-02],\n [-3.1812e-02, -3.9237e-02, -4.8997e-02],\n [-3.1275e-02, -3.1384e-02, -2.4815e-02]]],\n\n\n ...,\n\n\n [[[ 1.8211e-09, 2.9120e-09, -5.6310e-09],\n [ 4.3212e-09, -1.8635e-09, -3.3057e-09],\n [ 2.2608e-09, -1.2302e-09, 1.6536e-10]],\n\n [[ 1.9862e-09, -2.7085e-09, -1.5189e-08],\n [ 9.0284e-09, 2.6774e-09, -2.3783e-09],\n [ 5.4744e-09, 4.7255e-09, -5.1706e-09]],\n\n [[ 4.2245e-10, -6.2215e-09, -7.1381e-09],\n [-4.5743e-09, -8.9245e-09, -4.1074e-09],\n [-1.7179e-09, -1.4299e-10, -4.7585e-09]],\n\n ...,\n\n [[-1.6792e-09, 3.7950e-09, 5.4831e-10],\n [-4.9152e-09, -9.4884e-09, -6.3708e-09],\n [ 8.2731e-09, 3.9463e-09, 3.8983e-09]],\n\n [[ 4.0006e-09, -1.3585e-09, -2.7413e-12],\n [-1.2756e-09, 2.5309e-09, -4.6894e-09],\n [ 4.9880e-10, 3.3068e-09, -8.5953e-09]],\n\n [[ 2.7820e-09, 7.1263e-10, 3.2218e-09],\n [ 3.4826e-09, 5.6161e-09, -3.8766e-09],\n [ 2.3460e-09, 6.0292e-09, 4.8710e-10]]],\n\n\n [[[ 7.3070e-02, 4.9217e-02, 2.6744e-02],\n [ 2.9848e-02, -2.0091e-02, -3.9241e-02],\n [ 9.3575e-03, -4.2804e-02, -5.6395e-02]],\n\n [[-1.8695e-02, -8.3945e-05, -3.3161e-03],\n [ 1.0237e-02, 1.2117e-02, -1.1630e-03],\n [-3.5509e-03, -2.5768e-02, -3.0373e-02]],\n\n [[ 2.5803e-03, -1.3056e-02, -1.2358e-02],\n [-2.4735e-03, -1.5222e-02, 4.7467e-03],\n [-1.0714e-02, -2.1856e-02, 1.2783e-02]],\n\n ...,\n\n [[ 3.4517e-03, 5.5596e-04, -9.9613e-03],\n [-3.6187e-03, -1.7061e-02, -1.9763e-02],\n [-8.8637e-03, -1.9938e-02, -1.4074e-02]],\n\n [[ 1.0257e-02, 2.8173e-02, 6.8687e-03],\n [ 1.9947e-02, 3.9298e-02, 1.6358e-02],\n [-4.9443e-03, 2.2777e-02, 2.2537e-02]],\n\n [[-5.5587e-02, -1.7281e-02, 1.4792e-02],\n [-3.4586e-02, 3.7056e-02, 5.3105e-02],\n [ 2.9633e-03, 7.5818e-02, 6.9634e-02]]],\n\n\n [[[-4.1926e-02, -3.5742e-02, 1.0197e-01],\n [-1.7566e-01, 4.3271e-03, 2.8655e-01],\n [-1.0595e-01, -4.7502e-02, 1.4850e-01]],\n\n [[ 2.5422e-03, -2.6145e-03, 3.2524e-02],\n [-3.6397e-02, -2.2509e-02, 2.4138e-02],\n [-3.5005e-02, -9.4282e-03, 5.1171e-02]],\n\n [[-4.0658e-02, -5.3829e-02, -2.6803e-02],\n [-4.6819e-02, -1.0657e-01, -8.4326e-02],\n [-4.7794e-02, -6.1241e-02, -3.8802e-02]],\n\n ...,\n\n [[-2.2179e-02, -1.5321e-02, 8.5193e-03],\n [-5.4147e-02, 1.8593e-03, 6.3133e-02],\n [-1.1889e-02, 6.5377e-03, 3.0411e-02]],\n\n [[ 3.0924e-03, 1.2440e-02, 1.2624e-02],\n [-1.0628e-02, -7.4649e-03, 4.2225e-02],\n [-1.2168e-02, 1.8177e-03, 6.1114e-02]],\n\n [[ 1.9324e-01, -4.8932e-02, -1.4168e-01],\n [ 3.8003e-01, -1.5187e-02, -3.0844e-01],\n [ 2.4695e-01, -5.9076e-02, -1.9436e-01]]]]), 'model.layer1.0.bn2.weight': tensor([2.3224e-08, 1.3712e-01, 2.5342e-01, 1.2561e-01, 1.1012e-01, 1.9413e-01,\n 1.1534e-01, 1.3118e-01, 1.7347e-01, 1.2996e-01, 1.0116e-01, 1.7705e-01,\n 1.2818e-01, 1.4282e-01, 1.3586e-01, 1.2258e-01, 1.5261e-01, 1.3931e-01,\n 2.3603e-01, 4.6913e-07, 2.7308e-01, 1.6576e-01, 2.0555e-01, 2.1401e-01,\n 1.5197e-01, 1.7373e-01, 1.7115e-01, 1.7085e-01, 1.8140e-01, 1.8330e-01,\n 1.4676e-01, 1.3091e-01, 1.5575e-01, 2.3779e-01, 1.3608e-01, 1.3296e-01,\n 1.5727e-01, 1.6070e-01, 1.7666e-01, 2.2314e-01, 2.1516e-01, 2.2303e-01,\n 1.7866e-01, 1.0884e-01, 1.6788e-01, 2.0463e-01, 9.3744e-02, 2.5533e-01,\n 1.6492e-01, 1.3718e-01, 1.6685e-01, 1.7877e-01, 1.8793e-01, 1.1284e-01,\n 1.8132e-01, 1.7081e-01, 2.1263e-01, 1.2937e-01, 1.6516e-01, 5.9243e-04,\n 1.7153e-01, 9.5639e-09, 1.7823e-01, 2.3327e-01]), 'model.layer1.0.bn2.bias': tensor([-1.1646e-07, 3.2485e-02, 3.5804e-01, 1.2727e-01, 2.6396e-01,\n 3.5038e-01, 2.9373e-01, 1.6325e-01, -1.4787e-01, -9.7325e-02,\n -3.0915e-02, 3.1535e-01, 2.9476e-01, -4.0019e-02, -1.4030e-01,\n 2.8569e-01, 3.7776e-01, -1.0404e-01, 2.1628e-01, -1.4170e-06,\n 9.0395e-02, 1.2694e-01, -5.2809e-02, 4.2579e-01, 1.1113e-01,\n 1.8114e-01, 1.7128e-01, -3.3463e-02, -6.5607e-02, -2.5923e-02,\n 7.5371e-02, 3.2465e-01, 3.3772e-01, 5.2076e-01, -9.3282e-03,\n -1.0443e-01, 3.9320e-01, 1.7102e-01, 1.0319e-01, 1.0736e-01,\n 3.6893e-01, 7.7084e-02, 6.6106e-02, 2.3034e-01, -6.5082e-02,\n -5.7860e-02, 2.6036e-01, -2.3745e-01, 3.8408e-01, -3.7981e-02,\n 3.8223e-01, 1.3879e-01, 9.1681e-02, 1.6580e-01, 1.4754e-03,\n 3.0084e-02, -1.9890e-01, -5.3443e-02, -1.3641e-01, -7.6811e-03,\n -5.3994e-02, -4.7086e-08, -5.3690e-02, 9.7514e-02]), 'model.layer1.0.bn2.running_mean': tensor([ 5.2098e-08, 2.1046e-02, 1.2075e-01, -9.1728e-02, -2.3614e-02,\n -5.9569e-02, -7.7003e-02, 1.2295e-01, -3.7028e-03, 1.0349e-01,\n -1.1946e-01, -6.5572e-02, -4.9199e-02, 8.2149e-02, -1.2760e-02,\n 1.1370e-01, 2.2997e-02, 1.1328e-02, -2.5149e-01, 1.1379e-06,\n 1.9767e-01, 4.5983e-02, 2.0339e-01, 2.6261e-01, 1.0311e-01,\n 1.0850e-01, 5.1218e-01, 1.3532e-01, -1.3248e-01, 1.8202e-01,\n 4.9866e-03, 1.3977e-01, 1.2375e-01, 1.5103e-02, 4.7853e-02,\n -1.3417e-01, 1.3650e-01, 1.0016e-01, 1.1286e-01, 2.6573e-01,\n 2.1235e-01, 1.5603e-01, 1.6570e-01, 2.0265e-02, 2.9134e-01,\n 8.6548e-03, 1.3167e-01, -4.3021e-01, 4.7242e-02, -6.3516e-02,\n -5.5816e-02, 2.3659e-02, 2.9641e-01, -9.7500e-02, -3.6080e-01,\n -1.7773e-01, -6.3386e-01, -7.8339e-02, 4.1984e-03, -1.3804e-02,\n -1.5207e-01, -2.5913e-08, 3.2786e-01, 2.0436e-01]), 'model.layer1.0.bn2.running_var': tensor([1.1220e-15, 1.7706e-02, 1.5584e-01, 1.6109e-02, 4.3359e-02, 6.2412e-02,\n 3.3272e-02, 2.6645e-02, 8.3535e-03, 1.1635e-02, 2.2330e-02, 8.1895e-02,\n 7.4078e-02, 3.0054e-02, 1.7052e-02, 3.4464e-02, 4.7890e-02, 3.1586e-02,\n 1.2332e-01, 9.7974e-13, 1.6110e-01, 2.5511e-02, 3.4009e-02, 1.2360e-01,\n 3.4458e-02, 2.5263e-02, 2.2808e-02, 3.9228e-02, 2.4584e-02, 3.2979e-02,\n 4.8044e-02, 4.7393e-02, 1.0852e-01, 8.5848e-02, 1.2348e-02, 1.5512e-02,\n 1.6838e-01, 3.1914e-02, 2.3008e-02, 1.2371e-01, 9.4096e-02, 1.3059e-01,\n 5.0255e-02, 4.3577e-02, 3.4556e-02, 8.2057e-03, 2.6032e-02, 1.4893e-02,\n 4.2168e-02, 1.1824e-02, 9.4134e-02, 3.2504e-02, 5.3258e-02, 1.3536e-02,\n 3.9002e-02, 2.7707e-02, 1.2514e-02, 5.9668e-03, 1.7680e-02, 1.4064e-04,\n 2.9675e-02, 3.6976e-16, 3.1248e-02, 1.2479e-01]), 'model.layer1.0.bn2.num_batches_tracked': tensor(7160), 'model.layer1.0.conv3.weight': tensor([[[[-4.0119e-09]],\n\n [[ 1.8042e-02]],\n\n [[ 5.9963e-02]],\n\n ...,\n\n [[ 1.0813e-08]],\n\n [[-9.5301e-03]],\n\n [[-4.3819e-02]]],\n\n\n [[[ 5.7415e-09]],\n\n [[ 2.8870e-03]],\n\n [[ 1.8386e-03]],\n\n ...,\n\n [[ 2.3281e-09]],\n\n [[-1.7662e-03]],\n\n [[-1.1677e-03]]],\n\n\n [[[-2.2345e-09]],\n\n [[ 8.4034e-03]],\n\n [[-9.0477e-03]],\n\n ...,\n\n [[-3.2814e-09]],\n\n [[ 6.1659e-03]],\n\n [[-1.3667e-02]]],\n\n\n ...,\n\n\n [[[ 6.1314e-09]],\n\n [[-4.7092e-03]],\n\n [[ 3.7102e-03]],\n\n ...,\n\n [[-1.2589e-08]],\n\n [[ 8.9504e-03]],\n\n [[-9.6855e-04]]],\n\n\n [[[-7.4988e-09]],\n\n [[-5.6132e-03]],\n\n [[ 9.8312e-02]],\n\n ...,\n\n [[ 3.6372e-09]],\n\n [[-4.3602e-02]],\n\n [[-2.1142e-03]]],\n\n\n [[[ 1.4321e-09]],\n\n [[-1.5607e-02]],\n\n [[-1.9509e-02]],\n\n ...,\n\n [[ 6.1837e-09]],\n\n [[ 2.5106e-02]],\n\n [[-1.0734e-01]]]]), 'model.layer1.0.bn3.weight': tensor([ 6.2793e-02, -4.8633e-04, 3.8487e-02, 3.1521e-01, 5.1277e-02,\n 4.6770e-02, 1.1687e-01, 3.9311e-01, 9.8102e-02, 1.9138e-01,\n 2.7403e-01, 1.7946e-01, 2.1250e-01, 2.1054e-01, 2.3310e-01,\n 1.5945e-01, 2.2306e-01, 3.3955e-01, 7.8517e-02, 1.4840e-01,\n 1.3158e-01, 2.1257e-01, 1.1078e-06, 9.5138e-09, 1.7097e-01,\n 4.9364e-04, 7.5616e-03, 2.7314e-01, 2.1410e-01, 2.1349e-01,\n 1.7818e-01, 3.2866e-01, 2.4716e-01, 1.8115e-01, 1.3289e-01,\n 2.0466e-01, 1.3777e-01, 2.1720e-01, -5.4832e-04, 2.0631e-02,\n -1.3897e-02, 2.1647e-01, 1.8050e-01, 2.3615e-01, 1.1630e-01,\n 1.5954e-05, 8.5303e-02, 1.4693e-01, 8.9328e-02, 2.1431e-03,\n 2.1590e-01, 3.0577e-02, 1.6429e-07, 1.2692e-01, 6.3092e-02,\n 1.6454e-01, 2.0654e-03, 2.3049e-01, 1.8171e-01, 2.1221e-01,\n 1.6123e-01, 1.4651e-01, 1.7068e-01, 9.7683e-02, 7.8185e-08,\n -1.1145e-03, 8.4755e-02, 2.6592e-01, 1.6596e-01, 7.7360e-04,\n 3.0414e-02, -2.6206e-07, 2.6654e-01, 5.6842e-02, 3.2167e-01,\n 5.0668e-02, 1.1388e-03, 5.1784e-02, 2.8473e-01, 1.7423e-01,\n 2.1313e-01, 2.4346e-01, 1.6776e-01, -4.5969e-06, 2.4383e-01,\n 1.7763e-01, 1.4355e-01, 7.5519e-07, 1.7919e-01, 9.7360e-07,\n 1.5819e-03, 5.9668e-02, 5.9118e-03, 9.1770e-04, 1.2646e-02,\n 8.0623e-02, 2.0802e-01, 2.7940e-01, 9.8607e-02, 1.2599e-01,\n 2.6553e-01, 3.7739e-07, 2.7034e-01, 9.9929e-02, 2.5932e-01,\n 1.0395e-01, 2.1362e-01, 7.0997e-07, 1.9689e-02, 2.5750e-01,\n 8.6337e-02, 2.2112e-01, -5.9519e-03, -9.1908e-02, 2.4719e-01,\n 2.6185e-01, 2.8632e-01, 1.6807e-08, 2.2177e-01, 2.8553e-01,\n 1.8509e-01, 2.0108e-01, 2.8730e-01, 1.7130e-05, 7.4774e-02,\n 2.1046e-01, 1.9701e-01, 1.6825e-05, 7.1410e-02, 1.9853e-01,\n 1.9504e-01, 1.4566e-01, 1.6408e-01, 1.0848e-06, 1.0534e-06,\n 1.0080e-02, 1.3846e-01, 6.2744e-02, 2.2138e-01, 9.2431e-02,\n 6.5170e-02, 3.1105e-01, 8.0087e-02, 1.3029e-01, 4.9150e-02,\n 2.2998e-01, 2.5680e-01, 1.1617e-01, 5.6273e-02, 1.4954e-01,\n 6.8301e-02, 6.5142e-02, 7.8647e-02, -8.2498e-02, 1.3143e-01,\n 1.3633e-01, 1.3643e-01, 1.4960e-01, 2.2265e-01, -1.2118e-01,\n 2.8075e-01, 2.3023e-01, 2.2549e-01, -1.1295e-02, 2.9015e-02,\n 4.8021e-03, 3.2850e-02, 2.7183e-01, 1.5023e-01, 1.1105e-01,\n -1.8938e-02, 2.3728e-01, 1.2154e-01, 1.3541e-01, 1.1930e-05,\n 5.9672e-02, 2.5008e-01, 2.0258e-01, 1.7477e-01, 1.5510e-01,\n 1.6333e-01, 6.2256e-02, 1.4939e-01, 2.4209e-01, -1.8289e-02,\n -1.7191e-06, 1.6921e-01, 2.8301e-01, 2.4391e-01, -4.6018e-04,\n 1.0648e-01, 5.2570e-03, 8.5425e-02, 1.8989e-01, 4.2037e-04,\n 9.8877e-02, 1.4370e-01, 2.2155e-01, 2.0583e-01, 1.5927e-05,\n 2.6225e-01, 3.2999e-01, 9.0553e-07, 2.8728e-01, -4.3297e-08,\n -3.3592e-03, 1.4326e-01, -9.5168e-02, 1.3982e-01, 2.2323e-01,\n 1.5388e-01, -1.0719e-01, 9.5771e-02, 1.6035e-01, 8.0811e-07,\n 2.6281e-01, 1.8985e-01, 1.8080e-01, 2.0528e-01, 2.5111e-01,\n 2.6707e-03, 1.5055e-01, 7.7227e-02, 5.7712e-02, 7.5348e-02,\n 1.7678e-01, -7.1986e-04, 1.5423e-01, 1.1695e-03, 1.3511e-02,\n 1.5470e-01, 2.7522e-01, 3.1702e-02, 2.6761e-01, 2.1456e-01,\n 5.7166e-02, 1.6073e-01, -4.5976e-04, 6.2611e-02, 4.5880e-02,\n 1.0377e-01, -1.5192e-02, -7.3116e-05, 2.8735e-01, 1.7562e-01,\n 5.1017e-02, -1.5988e-05, 7.1619e-02, 1.1034e-01, 1.6189e-01,\n 2.1187e-01, 5.3046e-02, 2.6463e-01, -7.1645e-04, 2.9281e-01,\n 1.4139e-01]), 'model.layer1.0.bn3.bias': tensor([-9.5979e-03, 5.9533e-02, 2.3196e-02, 6.1058e-02, -4.8302e-02,\n 4.5096e-02, 7.0837e-02, 1.3649e-01, 1.0697e-01, 8.7079e-02,\n 5.4565e-02, 1.3588e-02, -5.8971e-03, 3.0777e-02, 6.4575e-02,\n 3.4837e-02, 1.2631e-01, 1.0387e-01, -8.1998e-02, 4.4319e-02,\n 6.2545e-02, 2.9247e-02, -2.0646e-06, -1.1174e-07, 1.0063e-01,\n -1.2143e-03, -1.0950e-01, -8.9310e-03, 4.3158e-02, 1.3342e-02,\n 3.2064e-02, 9.8939e-03, 4.0767e-02, -2.7455e-02, 6.4162e-02,\n -4.5047e-02, 1.3923e-02, 2.9443e-02, 1.7372e-02, 8.4337e-02,\n -1.4664e-02, 5.0641e-02, 6.1089e-03, 6.8188e-02, 3.6143e-02,\n -4.4509e-05, 3.6267e-02, 1.3665e-02, -1.1947e-01, 3.6692e-02,\n 1.2094e-01, 1.1169e-01, -3.6071e-07, 4.2791e-02, -4.6757e-02,\n 9.3142e-02, 1.4665e-01, 9.0121e-03, 2.2938e-02, -2.3806e-02,\n -4.5468e-02, 4.5434e-02, 4.6124e-02, 1.9794e-02, -1.4790e-07,\n 3.3339e-02, 3.1282e-04, 8.4840e-03, -1.4625e-02, 8.9681e-02,\n -5.1315e-02, -6.0294e-07, 2.1677e-01, 1.0266e-01, 1.8675e-02,\n 2.0500e-02, -3.5146e-03, -2.1426e-01, 4.4807e-02, 3.2196e-02,\n 6.2283e-02, 3.0386e-02, 1.0377e-01, -2.0677e-05, 1.5000e-01,\n 1.9023e-01, 3.3191e-02, -1.2605e-06, -7.9566e-03, -2.0082e-06,\n 9.3771e-02, -9.8182e-02, -4.0083e-02, -8.6359e-03, -3.2428e-02,\n 1.1327e-01, 1.5334e-01, 2.5980e-02, 4.9867e-02, -2.8695e-02,\n 3.5792e-02, -7.7537e-07, 7.6789e-03, 3.6915e-02, 7.9128e-02,\n 2.7267e-02, -1.3097e-01, -1.3511e-06, -7.6592e-02, 1.6880e-01,\n 7.7684e-02, 9.1958e-02, -4.1569e-02, 7.6345e-02, -4.1600e-03,\n 5.2164e-02, 4.6678e-02, -2.4410e-07, 1.5939e-01, 2.9205e-02,\n 2.4591e-02, -1.4741e-01, 9.1734e-02, -7.6240e-05, 1.0501e-01,\n 1.8492e-02, 6.0189e-02, -5.9870e-04, 2.1729e-02, 5.9630e-02,\n 1.6230e-01, -3.9407e-02, 6.3760e-02, -2.7045e-06, -3.3708e-06,\n 1.1172e-01, 4.7172e-02, -1.7036e-02, 4.3811e-02, -2.9359e-02,\n -2.0431e-02, 6.1058e-02, 6.4426e-02, 1.0956e-01, -2.4353e-01,\n 3.7320e-02, 1.8000e-01, 1.5991e-02, -3.1234e-01, 3.0354e-02,\n -2.2845e-01, 1.0207e-02, -4.7140e-03, 9.5463e-03, -6.6298e-02,\n 1.3481e-02, 1.9716e-02, -3.4244e-03, 1.2782e-02, -5.8222e-02,\n 5.1809e-02, 1.3731e-01, -1.7551e-02, 1.7710e-01, -3.1391e-02,\n 4.1953e-03, 2.7724e-02, 1.1236e-02, -9.9621e-04, 3.7918e-02,\n 8.9256e-02, -4.9890e-02, -2.6705e-02, -1.1142e-02, -1.8829e-05,\n 1.5684e-02, 3.3725e-02, 1.2976e-01, 7.6165e-02, -6.5642e-03,\n 2.4426e-02, -6.5646e-02, -1.7557e-02, -5.2649e-02, 1.9804e-02,\n -2.0810e-06, 1.4091e-02, 1.0042e-01, 7.2273e-02, 1.6599e-01,\n 3.4971e-02, -4.5338e-02, 2.9884e-02, 4.1305e-02, 2.8537e-02,\n 4.8590e-02, 3.0292e-02, 1.0425e-01, 2.8305e-02, -4.7313e-05,\n 8.1943e-02, 7.8172e-02, -2.0540e-06, 1.2355e-01, -2.4337e-07,\n 1.2079e-01, -7.9296e-03, -1.2318e-02, 8.7763e-02, 4.5041e-02,\n -2.4701e-02, -4.9069e-03, -2.6290e-02, 8.4358e-02, -2.9716e-06,\n 6.9435e-02, 4.2590e-02, 4.1136e-02, -5.8818e-02, 1.0195e-01,\n 1.1623e-01, -4.0657e-03, -4.6292e-02, 1.1820e-01, -5.6932e-02,\n -2.2315e-03, 5.9759e-02, 7.3227e-02, 5.8639e-02, 1.2491e-01,\n -4.8580e-02, 5.1834e-02, 2.4194e-02, 4.1919e-02, 1.9634e-01,\n 1.6744e-02, 6.8633e-02, 1.2080e-01, -2.6886e-03, -3.6851e-02,\n 4.9469e-02, 4.8096e-02, -9.1995e-03, 2.8372e-02, 1.9001e-01,\n 1.3320e-02, -4.0885e-04, 2.9009e-02, -4.3177e-02, 3.9360e-02,\n 7.7876e-02, 5.9795e-02, 1.2628e-01, 2.9211e-02, 1.9280e-01,\n 3.8492e-02]), 'model.layer1.0.bn3.running_mean': tensor([ 4.5994e-02, 5.6321e-03, -5.6799e-04, -7.5999e-02, 2.8015e-03,\n 1.7647e-02, -6.1503e-02, 3.7990e-02, 1.9027e-02, -6.3753e-02,\n -3.2934e-02, 1.0729e-02, 2.7577e-02, 5.8940e-02, 1.7811e-02,\n 9.8335e-03, -1.1428e-01, 2.8846e-02, 3.4025e-02, -6.0766e-03,\n -7.4366e-02, 1.1433e-01, 1.3541e-06, -1.1165e-07, -1.9388e-02,\n -7.5024e-05, 2.2109e-02, 4.6211e-02, -1.8873e-01, 7.2942e-02,\n -9.4448e-02, -2.5703e-03, -5.4311e-02, -3.7116e-02, -8.7232e-03,\n -1.4726e-02, -2.0771e-02, -2.3182e-02, -2.3450e-02, 6.4520e-03,\n -1.1450e-02, -3.2481e-02, -1.1116e-01, 1.2635e-02, -3.4652e-02,\n 1.6853e-05, 7.0162e-03, 1.6665e-02, -7.0034e-03, -1.0743e-02,\n -1.8696e-04, -7.5554e-03, -2.7120e-07, 3.4464e-02, 6.5905e-02,\n 7.3024e-02, -1.1200e-02, -1.0882e-01, 5.8644e-02, 6.3901e-02,\n 2.6668e-02, -5.9267e-02, -7.6411e-02, -2.1979e-02, -5.8558e-08,\n 3.5760e-03, 2.3628e-02, -5.2954e-02, 9.6742e-02, -1.3634e-02,\n -3.3515e-02, -1.4301e-07, -5.6173e-02, 8.0778e-02, 5.3909e-02,\n 3.8836e-02, 2.1100e-03, 1.0718e-02, 8.6296e-02, 5.6288e-02,\n 3.6118e-02, 1.8508e-01, -1.1668e-01, -1.1166e-05, 5.0105e-02,\n -6.1151e-02, -1.0492e-02, 7.4035e-07, -2.4770e-02, 8.5926e-07,\n -6.6014e-03, 3.3842e-02, -3.1291e-02, 1.5099e-03, -5.7618e-03,\n -1.0428e-02, -1.1501e-01, 7.2030e-02, 2.3396e-02, -1.5623e-02,\n 3.3230e-02, -7.2071e-07, -2.5998e-02, 1.9638e-03, -4.8329e-02,\n 1.4576e-02, -1.2339e-02, 3.5595e-07, 2.7454e-03, 1.8098e-02,\n 5.4411e-02, 2.5006e-02, -4.7208e-03, 8.8431e-03, 2.7817e-02,\n -2.4550e-02, 3.9276e-02, 2.8185e-08, -3.5655e-03, -1.3456e-02,\n -8.8147e-02, -1.9697e-02, -4.8779e-02, 5.0071e-05, 3.1166e-02,\n 3.3678e-02, 6.5041e-02, -8.9143e-05, -1.0418e-01, -3.0234e-03,\n -5.0910e-02, 8.3519e-02, -3.8094e-02, 5.2468e-08, 8.4451e-07,\n -1.9117e-03, 4.0601e-03, -3.0238e-02, 5.4810e-02, 1.5038e-02,\n -3.2508e-02, 3.0829e-02, -3.5697e-02, -4.7042e-02, -9.1108e-02,\n -4.3957e-02, -5.2565e-02, -3.8448e-02, -2.0036e-02, 1.8706e-02,\n 8.1113e-02, 4.8476e-02, 4.6526e-02, 2.9204e-03, 2.8627e-02,\n -4.4652e-03, 5.6934e-02, -5.3868e-02, -1.0491e-01, -2.9965e-02,\n 2.2083e-01, -4.1946e-02, -3.2184e-02, -1.5307e-02, 2.5110e-03,\n -2.0322e-02, -2.3285e-02, 1.9166e-01, -5.2125e-02, 2.3679e-02,\n -1.1148e-02, -7.8434e-02, -1.1885e-02, 6.2236e-02, -1.3492e-06,\n -4.7880e-02, -3.0135e-02, 9.5169e-02, 6.4108e-02, -8.5517e-03,\n 1.0193e-03, -3.4873e-02, 6.9795e-03, -9.1954e-03, 1.0264e-03,\n 6.9440e-07, 3.2798e-02, 2.3430e-02, -1.2793e-02, 1.6642e-03,\n -6.8671e-03, -2.6150e-02, 1.0450e-02, -7.7923e-02, -2.3737e-03,\n -1.7891e-02, -1.4876e-02, -1.7204e-01, -1.2740e-01, 1.8898e-05,\n -1.4062e-02, 5.9930e-02, 2.1484e-07, 1.9908e-01, -4.8128e-09,\n 5.4727e-03, 4.9669e-02, 9.3124e-03, -2.2344e-01, 5.0692e-02,\n 5.7448e-02, 4.0885e-02, 3.1112e-02, -8.2255e-02, -2.4215e-06,\n 1.1261e-01, -6.1810e-02, 8.2692e-02, 1.0330e-03, -1.1686e-02,\n -1.7176e-02, -4.9891e-02, 9.2898e-03, 4.8605e-03, 8.3078e-02,\n 1.3576e-02, -1.2193e-02, -1.7436e-02, -2.7521e-02, 1.5788e-02,\n -3.2135e-02, 2.2556e-01, 6.4713e-02, 6.4085e-03, 2.1988e-01,\n 1.8713e-04, 3.9285e-03, 1.3586e-02, 2.2043e-02, 3.7622e-02,\n -7.7021e-02, 3.2893e-02, 4.6344e-04, 3.3958e-02, -3.4378e-02,\n -2.4410e-02, -4.3248e-05, -2.1536e-02, 3.2184e-02, -3.0539e-03,\n -4.9654e-02, 4.1120e-02, -1.1972e-01, 9.6255e-03, -2.9693e-02,\n -4.4661e-02]), 'model.layer1.0.bn3.running_var': tensor([7.3279e-03, 4.3246e-04, 3.1994e-04, 2.5525e-02, 7.6365e-04, 3.1816e-03,\n 3.3359e-03, 3.7386e-02, 1.2398e-02, 8.3620e-03, 1.4496e-02, 7.2343e-03,\n 1.2009e-02, 3.1137e-02, 2.2565e-02, 4.4999e-03, 9.6978e-03, 2.2589e-02,\n 1.0654e-03, 2.2924e-02, 4.1347e-03, 4.2146e-03, 4.8732e-13, 2.1136e-14,\n 1.4540e-02, 2.5652e-07, 4.4625e-04, 7.1219e-03, 8.4116e-03, 6.7652e-03,\n 6.9655e-03, 1.7194e-02, 1.6241e-02, 3.9879e-03, 7.4073e-03, 1.0977e-02,\n 4.5828e-03, 9.6569e-03, 5.3465e-04, 3.6671e-03, 7.4306e-04, 1.5063e-02,\n 1.2911e-02, 1.6896e-02, 5.4342e-03, 4.0678e-11, 6.6783e-03, 3.8653e-03,\n 6.3040e-04, 2.0583e-04, 1.3117e-02, 1.3032e-03, 4.3647e-14, 4.2197e-03,\n 2.8782e-03, 1.9103e-02, 2.3405e-04, 8.4657e-03, 8.0715e-03, 1.2652e-02,\n 3.5475e-03, 3.8463e-03, 8.5541e-03, 3.9814e-03, 2.8169e-14, 3.5224e-04,\n 1.4256e-03, 7.2083e-03, 4.1554e-03, 2.4644e-04, 3.3125e-04, 9.6338e-14,\n 1.4120e-02, 1.3955e-02, 2.3463e-02, 1.5200e-03, 1.6710e-06, 2.0124e-03,\n 1.2295e-02, 5.5394e-03, 2.1074e-02, 1.0480e-02, 1.2498e-02, 5.2966e-11,\n 1.2077e-02, 1.3307e-02, 6.6223e-03, 2.7621e-13, 1.7504e-02, 1.7475e-13,\n 6.9015e-04, 7.8882e-04, 3.0592e-04, 4.0123e-06, 1.6884e-04, 3.8323e-03,\n 1.5648e-02, 9.4786e-03, 4.1738e-03, 5.5074e-03, 1.4772e-02, 1.1666e-13,\n 2.8479e-02, 7.1678e-03, 1.7100e-02, 1.0375e-02, 2.5692e-03, 4.3159e-13,\n 8.7567e-04, 2.2623e-02, 1.5808e-02, 6.0847e-03, 4.1644e-04, 5.7816e-03,\n 6.1208e-03, 1.9805e-02, 1.8207e-02, 1.3471e-14, 1.7970e-02, 2.2379e-02,\n 7.6398e-03, 3.0466e-03, 1.8686e-02, 8.3569e-09, 9.7759e-03, 8.9913e-03,\n 5.2729e-03, 8.3252e-08, 1.3128e-03, 1.1099e-02, 2.6971e-02, 3.0038e-03,\n 6.1210e-03, 1.4800e-12, 6.7073e-12, 4.0693e-04, 1.9342e-03, 1.0567e-03,\n 1.5974e-02, 9.3543e-04, 1.0336e-03, 1.9859e-02, 5.6559e-03, 5.6745e-03,\n 3.9663e-03, 1.8133e-02, 2.9145e-02, 4.5337e-03, 3.0309e-03, 5.2365e-03,\n 4.3536e-03, 1.0745e-03, 1.7232e-03, 7.6846e-04, 3.3288e-03, 5.9342e-03,\n 3.6951e-03, 2.1693e-03, 6.8729e-03, 3.4603e-03, 8.8351e-03, 1.7212e-02,\n 6.6366e-03, 8.4078e-04, 6.0174e-04, 1.9530e-04, 1.1774e-03, 1.8459e-02,\n 6.7784e-03, 6.5511e-03, 7.8939e-04, 6.0649e-03, 2.2128e-03, 1.3087e-03,\n 1.6376e-10, 9.8976e-04, 1.1303e-02, 2.6832e-02, 5.0509e-03, 7.3062e-03,\n 4.9983e-03, 1.7028e-03, 1.3876e-02, 3.8253e-03, 1.0107e-03, 1.4487e-12,\n 8.9172e-03, 3.2532e-02, 1.2130e-02, 5.2998e-04, 1.4842e-02, 2.7678e-04,\n 1.9382e-02, 6.4933e-03, 2.8007e-04, 9.8594e-03, 9.0702e-03, 8.3059e-03,\n 5.4259e-03, 9.1318e-10, 1.9896e-02, 2.3458e-02, 2.7189e-13, 3.1943e-02,\n 1.3293e-14, 5.5515e-04, 2.9658e-03, 1.7642e-03, 4.2241e-03, 1.1260e-02,\n 9.4366e-03, 3.4885e-03, 1.5910e-03, 4.3793e-03, 3.3399e-12, 2.0155e-02,\n 3.5951e-03, 5.3022e-03, 8.1649e-03, 1.4875e-02, 9.8312e-04, 3.2365e-03,\n 6.9129e-04, 1.4016e-02, 8.3931e-04, 9.0595e-03, 4.5025e-04, 4.6479e-03,\n 4.9001e-04, 9.4832e-04, 1.2430e-03, 2.0917e-02, 6.9416e-04, 2.8591e-02,\n 4.7580e-03, 9.3058e-04, 7.8207e-03, 1.0362e-03, 2.2570e-04, 1.0561e-03,\n 1.5970e-03, 6.8211e-04, 4.3241e-04, 1.9168e-02, 3.0544e-02, 2.7038e-03,\n 1.4718e-08, 1.5229e-03, 2.0817e-03, 3.9233e-03, 1.7735e-02, 1.4741e-02,\n 2.7381e-02, 2.8328e-04, 3.0644e-02, 4.3687e-03]), 'model.layer1.0.bn3.num_batches_tracked': tensor(7160), 'model.layer1.0.downsample.0.weight': tensor([[[[ 5.1320e-03]],\n\n [[-1.7141e-01]],\n\n [[ 1.0112e-02]],\n\n ...,\n\n [[-2.6192e-02]],\n\n [[ 3.4781e-02]],\n\n [[ 1.2500e-03]]],\n\n\n [[[ 1.7806e-02]],\n\n [[-1.2256e-02]],\n\n [[-2.0448e-02]],\n\n ...,\n\n [[-1.3706e-04]],\n\n [[ 2.2223e-02]],\n\n [[ 2.5119e-03]]],\n\n\n [[[-2.9618e-02]],\n\n [[ 2.0983e-02]],\n\n [[-2.6127e-02]],\n\n ...,\n\n [[ 5.6222e-02]],\n\n [[-1.0791e-02]],\n\n [[-4.7924e-03]]],\n\n\n ...,\n\n\n [[[-4.3132e-02]],\n\n [[-4.0139e-01]],\n\n [[ 6.8659e-02]],\n\n ...,\n\n [[-9.9012e-03]],\n\n [[ 1.0609e-01]],\n\n [[ 1.2337e-02]]],\n\n\n [[[ 3.3891e-03]],\n\n [[ 1.2044e-02]],\n\n [[ 7.1885e-02]],\n\n ...,\n\n [[-7.0875e-02]],\n\n [[ 1.5510e-01]],\n\n [[ 3.4049e-02]]],\n\n\n [[[ 1.3472e-02]],\n\n [[ 3.7534e-02]],\n\n [[-3.9483e-02]],\n\n ...,\n\n [[-1.1967e-01]],\n\n [[ 2.2417e-02]],\n\n [[-4.7771e-02]]]]), 'model.layer1.0.downsample.1.weight': tensor([ 2.5649e-01, 2.5405e-01, 1.3906e-01, 3.4369e-01, 2.7741e-02,\n 1.1261e-01, 2.1008e-01, 4.5121e-01, 1.7948e-01, 1.4926e-01,\n 3.5470e-01, 2.2247e-01, 2.6052e-01, 1.3505e-02, 4.0533e-01,\n 2.1481e-01, 9.9474e-02, 3.9884e-01, 1.8427e-01, 3.0514e-01,\n 2.4672e-01, 2.2927e-01, -1.0182e-08, 1.3827e-08, 3.1526e-01,\n 4.8934e-04, 2.5902e-01, 5.9800e-02, 1.9041e-01, 1.9697e-01,\n 1.6299e-01, 3.0947e-01, 3.5716e-01, 1.1979e-02, 3.0076e-01,\n 4.3283e-01, 2.6859e-01, 1.6177e-01, 2.9540e-01, 1.2635e-01,\n 6.5030e-02, 3.3602e-01, 3.4920e-01, 2.9235e-01, 2.7844e-01,\n 8.1415e-07, 3.5700e-01, 1.6428e-01, 2.2074e-01, 1.9208e-01,\n 2.9116e-01, 1.4676e-01, 2.0370e-07, 1.7167e-01, 2.2078e-01,\n 2.7810e-01, -3.7647e-03, 3.9423e-01, 2.5906e-01, 3.1911e-01,\n 3.4626e-01, 2.0475e-01, 2.3903e-01, 1.5897e-01, 2.0949e-08,\n 1.7767e-01, 1.9277e-01, 2.3679e-01, 1.6944e-01, 2.2554e-01,\n 1.8854e-01, 1.8148e-07, 1.9668e-01, 1.9006e-01, 3.1047e-01,\n 1.1652e-01, 1.9571e-03, 2.8439e-01, 2.9327e-01, 2.0702e-01,\n 2.9995e-01, 3.0325e-01, 3.0623e-01, 3.0339e-06, 2.5152e-01,\n 2.8140e-01, 2.2995e-01, -2.2464e-07, 9.2472e-02, 9.4888e-08,\n 2.2827e-01, 2.8262e-01, 2.5457e-01, 1.5075e-03, 1.6273e-02,\n 1.2599e-01, 2.5133e-01, 1.1075e-01, 2.0108e-01, 2.3767e-01,\n 2.3524e-01, 3.9112e-07, 4.3682e-01, 2.1114e-01, 3.2452e-01,\n 3.6081e-01, 1.6686e-01, 2.8431e-07, 2.3629e-01, 3.1635e-01,\n 2.0193e-01, 1.7552e-01, 2.4652e-01, 2.7143e-01, 2.3823e-02,\n 3.3126e-01, 2.8157e-01, 1.0910e-07, 3.2160e-01, 3.2273e-01,\n 1.7209e-01, 2.2235e-01, 2.2254e-01, 3.8821e-05, 2.1524e-01,\n 3.2440e-01, 2.1668e-01, 2.1191e-04, 2.4245e-01, 3.3027e-01,\n 3.5212e-01, 1.8687e-01, 2.3833e-01, 5.9542e-07, 2.1926e-06,\n 2.0110e-01, 1.9685e-01, 1.6048e-01, 3.1323e-01, 3.0452e-02,\n 1.5213e-01, 3.4198e-01, 2.2024e-01, 1.7783e-01, 2.9574e-01,\n 3.4543e-01, 3.2044e-01, 3.3072e-01, 3.0835e-01, 2.7302e-01,\n 3.3201e-01, 1.9682e-01, 1.5463e-01, 2.2950e-01, 1.2405e-01,\n 2.2542e-01, 7.7712e-02, 1.0741e-01, 3.3818e-01, 2.7966e-01,\n 3.2520e-01, 3.4062e-01, 2.7885e-01, 2.5204e-01, 7.7830e-02,\n 2.2279e-01, 1.2993e-01, 3.3122e-01, 3.7168e-01, 2.1216e-01,\n 7.3356e-02, 3.0585e-01, 5.3838e-02, 9.3193e-02, -3.7830e-06,\n 3.1186e-01, 2.3614e-01, 2.9975e-01, 1.6749e-01, 3.3863e-01,\n 2.2626e-01, 1.9095e-01, 3.4898e-01, 8.8529e-03, 1.9369e-01,\n 1.0625e-06, 3.7066e-01, 3.5308e-01, 2.0325e-01, 1.7515e-01,\n 4.0315e-01, 2.3564e-01, 2.3835e-01, 2.5256e-01, 3.9365e-02,\n 3.3978e-01, 3.4596e-01, -4.5056e-02, 1.7917e-01, -7.9278e-06,\n 2.8854e-01, 3.6811e-01, 1.4341e-07, 3.1075e-01, 7.5645e-08,\n 1.6157e-01, 1.6457e-01, 2.1962e-01, 2.7847e-01, 2.5764e-01,\n 2.8602e-01, 2.3765e-01, 8.2637e-02, 2.4565e-01, 6.3526e-07,\n 3.5799e-01, 2.4030e-01, 2.2463e-01, 3.1592e-01, 3.2121e-01,\n 2.5794e-01, 1.6665e-01, 6.7661e-02, 1.8643e-01, 1.7109e-01,\n 2.7718e-01, 1.9419e-01, 1.9357e-01, 2.1236e-01, 1.8157e-01,\n 1.5748e-02, 2.7220e-01, 1.4462e-01, 3.3992e-01, 1.8518e-01,\n 2.9366e-01, 2.7436e-01, 3.0138e-01, 1.3000e-01, 1.8559e-01,\n 1.2836e-01, 1.7893e-01, 3.2841e-01, 3.0601e-01, 2.9989e-01,\n 2.6225e-01, 7.0521e-05, 1.7048e-01, 2.4159e-01, 1.2561e-01,\n 3.5938e-01, 2.4819e-01, 3.7613e-01, 1.7073e-01, 3.6191e-01,\n 1.9065e-01]), 'model.layer1.0.downsample.1.bias': tensor([-9.5979e-03, 5.9533e-02, 2.3196e-02, 6.1058e-02, -4.8302e-02,\n 4.5096e-02, 7.0837e-02, 1.3649e-01, 1.0697e-01, 8.7079e-02,\n 5.4565e-02, 1.3588e-02, -5.8971e-03, 3.0777e-02, 6.4575e-02,\n 3.4837e-02, 1.2631e-01, 1.0387e-01, -8.1998e-02, 4.4319e-02,\n 6.2545e-02, 2.9247e-02, -2.0646e-06, -1.1174e-07, 1.0063e-01,\n -1.2143e-03, -1.0950e-01, -8.9310e-03, 4.3158e-02, 1.3342e-02,\n 3.2064e-02, 9.8939e-03, 4.0767e-02, -2.7455e-02, 6.4162e-02,\n -4.5047e-02, 1.3923e-02, 2.9443e-02, 1.7372e-02, 8.4337e-02,\n -1.4664e-02, 5.0641e-02, 6.1089e-03, 6.8188e-02, 3.6143e-02,\n -4.4509e-05, 3.6267e-02, 1.3665e-02, -1.1947e-01, 3.6692e-02,\n 1.2094e-01, 1.1169e-01, -3.6071e-07, 4.2791e-02, -4.6757e-02,\n 9.3142e-02, 1.4665e-01, 9.0121e-03, 2.2938e-02, -2.3806e-02,\n -4.5468e-02, 4.5434e-02, 4.6124e-02, 1.9794e-02, -1.4790e-07,\n 3.3339e-02, 3.1282e-04, 8.4840e-03, -1.4625e-02, 8.9681e-02,\n -5.1315e-02, -6.0294e-07, 2.1677e-01, 1.0266e-01, 1.8675e-02,\n 2.0500e-02, -3.5146e-03, -2.1426e-01, 4.4807e-02, 3.2196e-02,\n 6.2283e-02, 3.0386e-02, 1.0377e-01, -2.0677e-05, 1.5000e-01,\n 1.9023e-01, 3.3191e-02, -1.2605e-06, -7.9566e-03, -2.0082e-06,\n 9.3771e-02, -9.8182e-02, -4.0083e-02, -8.6359e-03, -3.2428e-02,\n 1.1327e-01, 1.5334e-01, 2.5980e-02, 4.9867e-02, -2.8695e-02,\n 3.5792e-02, -7.7537e-07, 7.6789e-03, 3.6915e-02, 7.9128e-02,\n 2.7267e-02, -1.3097e-01, -1.3511e-06, -7.6592e-02, 1.6880e-01,\n 7.7684e-02, 9.1958e-02, -4.1569e-02, 7.6345e-02, -4.1600e-03,\n 5.2164e-02, 4.6678e-02, -2.4410e-07, 1.5939e-01, 2.9205e-02,\n 2.4591e-02, -1.4741e-01, 9.1734e-02, -7.6240e-05, 1.0501e-01,\n 1.8492e-02, 6.0189e-02, -5.9870e-04, 2.1729e-02, 5.9630e-02,\n 1.6230e-01, -3.9407e-02, 6.3760e-02, -2.7045e-06, -3.3708e-06,\n 1.1172e-01, 4.7172e-02, -1.7036e-02, 4.3811e-02, -2.9359e-02,\n -2.0431e-02, 6.1058e-02, 6.4426e-02, 1.0956e-01, -2.4353e-01,\n 3.7320e-02, 1.8000e-01, 1.5991e-02, -3.1234e-01, 3.0354e-02,\n -2.2845e-01, 1.0207e-02, -4.7140e-03, 9.5463e-03, -6.6298e-02,\n 1.3481e-02, 1.9716e-02, -3.4244e-03, 1.2782e-02, -5.8222e-02,\n 5.1809e-02, 1.3731e-01, -1.7551e-02, 1.7710e-01, -3.1391e-02,\n 4.1953e-03, 2.7724e-02, 1.1236e-02, -9.9621e-04, 3.7918e-02,\n 8.9256e-02, -4.9890e-02, -2.6705e-02, -1.1142e-02, -1.8829e-05,\n 1.5684e-02, 3.3725e-02, 1.2976e-01, 7.6165e-02, -6.5642e-03,\n 2.4426e-02, -6.5646e-02, -1.7557e-02, -5.2649e-02, 1.9804e-02,\n -2.0810e-06, 1.4091e-02, 1.0042e-01, 7.2273e-02, 1.6599e-01,\n 3.4971e-02, -4.5338e-02, 2.9884e-02, 4.1305e-02, 2.8537e-02,\n 4.8590e-02, 3.0292e-02, 1.0425e-01, 2.8305e-02, -4.7313e-05,\n 8.1943e-02, 7.8172e-02, -2.0540e-06, 1.2355e-01, -2.4337e-07,\n 1.2079e-01, -7.9296e-03, -1.2318e-02, 8.7763e-02, 4.5041e-02,\n -2.4701e-02, -4.9069e-03, -2.6290e-02, 8.4358e-02, -2.9716e-06,\n 6.9435e-02, 4.2590e-02, 4.1136e-02, -5.8818e-02, 1.0195e-01,\n 1.1623e-01, -4.0657e-03, -4.6292e-02, 1.1820e-01, -5.6932e-02,\n -2.2315e-03, 5.9759e-02, 7.3227e-02, 5.8639e-02, 1.2491e-01,\n -4.8580e-02, 5.1834e-02, 2.4194e-02, 4.1919e-02, 1.9634e-01,\n 1.6744e-02, 6.8633e-02, 1.2080e-01, -2.6886e-03, -3.6851e-02,\n 4.9469e-02, 4.8096e-02, -9.1995e-03, 2.8372e-02, 1.9001e-01,\n 1.3320e-02, -4.0885e-04, 2.9009e-02, -4.3177e-02, 3.9360e-02,\n 7.7876e-02, 5.9795e-02, 1.2628e-01, 2.9211e-02, 1.9280e-01,\n 3.8492e-02]), 'model.layer1.0.downsample.1.running_mean': tensor([-3.5892e-01, 2.3005e-02, 5.9415e-02, -2.0991e-01, -7.1540e-02,\n -2.2700e-01, -2.6975e-01, 2.1663e-01, -7.4581e-01, -4.0236e-01,\n -5.3508e-01, 5.4625e-02, 8.9734e-02, 1.8225e-01, -1.5105e-01,\n -1.9944e-01, -3.1437e-01, 2.1560e-01, 3.5837e-01, -8.2092e-01,\n -3.0522e-01, 7.7663e-02, 1.3855e-06, 6.7490e-07, -2.3699e-02,\n -7.5915e-04, 2.9533e-01, -2.5106e-01, 5.2970e-02, 2.1346e-01,\n 5.2585e-02, -2.9960e-02, -7.1421e-03, -6.8597e-02, -4.4413e-01,\n -6.1577e-01, -6.2569e-01, 1.3391e-01, -6.4266e-01, -1.4805e-01,\n 2.2069e-02, -1.8526e-01, -2.3252e-01, -8.4073e-02, -1.8632e-01,\n 3.2602e-05, -4.2410e-01, -1.6131e-01, -6.2203e-02, -5.8875e-01,\n -4.0356e-01, 2.2236e-02, -1.3938e-06, 6.4924e-02, -3.0337e-01,\n -8.9464e-01, -1.6936e-01, 3.1781e-02, 2.0761e-01, -2.3989e-01,\n -6.6359e-01, -1.4588e-01, -2.1587e-01, -2.8371e-01, -7.6902e-07,\n -3.6729e-02, -2.2751e-01, -1.1870e-02, 6.4055e-03, -3.6392e-01,\n -1.3627e-01, -1.5142e-07, -7.7900e-01, -4.6688e-01, -1.4977e-01,\n 3.5527e-01, -1.0304e-02, 2.3507e-01, -4.0232e-01, 1.9804e-01,\n -4.0342e-01, 2.1703e-01, -3.8255e-01, 6.4990e-05, 7.8123e-01,\n 2.0854e-01, -3.2143e-01, -5.8381e-07, 1.6350e-01, -6.9679e-07,\n -4.6606e-01, -2.8865e-01, 4.1445e-02, 1.5936e-02, -4.0483e-02,\n -5.6196e-01, 2.4522e-01, 3.4775e-01, -4.0094e-02, -3.4275e-01,\n -2.1062e-01, -1.2843e-06, -2.3313e-01, -5.8029e-01, -2.2720e-01,\n -3.3089e-01, -1.4491e-02, -1.9518e-06, -4.3838e-02, -1.1181e-01,\n -3.4157e-01, 3.8708e-01, 5.5000e-02, -9.7195e-02, -1.7857e-01,\n -5.5570e-02, -3.1299e-01, -3.6926e-07, -4.8456e-02, -1.5078e-01,\n -3.8521e-01, -3.5381e-02, -3.6259e-01, -2.0591e-04, -4.3733e-01,\n -6.4529e-02, -3.8056e-01, 1.8657e-03, -1.7018e-02, 1.1243e-01,\n 5.1154e-03, -2.2820e-01, 1.4885e-01, -2.0308e-06, -1.5422e-05,\n -1.9714e-01, 4.4901e-02, -2.1689e-02, -2.6772e-01, -1.1448e-01,\n -1.6487e-01, -1.0973e-01, -6.8087e-02, -4.8357e-01, 1.3165e-02,\n -3.0906e-01, 1.6143e-02, -1.0403e-01, 3.7936e-02, -3.1902e-01,\n -2.7006e-01, -5.1550e-02, 1.4087e-01, 5.4539e-03, 1.6299e-01,\n -6.0989e-02, -6.0892e-02, 4.9997e-02, -1.3862e-01, -4.8353e-01,\n -2.5995e-01, 2.4781e-01, -1.8689e-01, 1.6262e+00, 1.2344e-02,\n -4.4301e-01, 4.8408e-02, -7.3572e-01, -1.4598e-01, -1.8613e-01,\n -5.3490e-02, -3.6540e-01, 9.5093e-02, -1.4810e-02, -3.6046e-05,\n 5.8225e-02, 2.4922e-01, 1.0131e+00, 4.2762e-01, -2.5794e-01,\n 2.0595e-01, 2.5604e-01, -3.5206e-01, -1.3127e-01, 5.3205e-02,\n -1.9172e-06, -7.4297e-01, -3.1609e-01, -1.1050e-01, 2.1247e-01,\n -3.2844e-01, 2.7732e-01, -1.8544e-01, -1.5106e-01, -8.8080e-02,\n -1.0989e+00, -2.0460e-01, 2.8485e-01, -1.3332e-01, 6.3812e-05,\n -3.3719e-01, 2.6610e-01, 7.1386e-07, -6.5280e-03, 6.7850e-08,\n -4.0129e-01, -7.2976e-02, -3.1098e-02, -2.6483e-01, -2.7097e-01,\n -2.5391e-01, 1.3919e-01, -3.8130e-02, -3.4445e-01, 2.4147e-06,\n -1.1815e-01, 1.4328e-01, 1.2098e-01, -2.6489e-01, 3.9863e-01,\n -2.1699e-01, 1.6624e-01, -5.3336e-02, -3.5181e-01, 1.2317e-01,\n -4.8942e-01, 1.4376e-01, -4.6735e-01, 9.4054e-02, 1.8471e-01,\n 6.7521e-03, -1.4772e-01, -3.8684e-01, 1.2314e-01, 4.1104e-01,\n -8.3530e-01, 3.7860e-01, 1.4559e-01, -2.7808e-01, -1.6556e-01,\n -2.0089e-01, -6.4639e-01, -4.2150e-01, -6.9228e-02, -7.5010e-02,\n -4.5362e-01, -2.4163e-04, 2.8540e-01, -3.2361e-01, 3.0626e-01,\n -1.6098e-01, -3.4835e-01, -1.0042e+00, 1.1221e-01, 2.1791e-01,\n 2.1290e-01]), 'model.layer1.0.downsample.1.running_var': tensor([4.4953e-02, 1.0355e-01, 7.6999e-03, 1.1795e-01, 2.1326e-03, 2.6688e-02,\n 2.8816e-02, 2.0457e-02, 3.3718e-02, 1.9406e-02, 4.7451e-02, 3.7285e-02,\n 3.2403e-02, 1.1528e-02, 3.9751e-02, 2.2919e-02, 2.2018e-02, 5.1446e-02,\n 1.8827e-02, 3.9665e-02, 1.9908e-02, 2.2934e-02, 5.4421e-13, 4.5877e-14,\n 5.1334e-02, 1.6879e-06, 4.9413e-02, 6.6007e-03, 3.3412e-02, 2.4071e-02,\n 2.8394e-02, 4.5200e-02, 6.1143e-02, 1.4709e-03, 4.4431e-02, 6.9253e-02,\n 4.1817e-02, 3.8040e-02, 1.0386e-01, 4.5055e-02, 2.8973e-03, 5.8914e-02,\n 6.2977e-02, 8.0219e-02, 3.0497e-02, 1.5852e-10, 5.0988e-02, 6.3953e-03,\n 6.0954e-03, 1.5682e-02, 3.9277e-02, 1.5601e-02, 2.1179e-13, 1.2420e-02,\n 2.3490e-02, 1.5506e-02, 2.8983e-03, 2.1856e-02, 5.3681e-02, 3.9535e-02,\n 1.1783e-02, 2.6344e-02, 2.0566e-02, 1.6766e-02, 1.7665e-13, 1.0171e-01,\n 2.0576e-02, 3.9163e-02, 1.0508e-02, 4.2343e-02, 3.2181e-03, 1.2160e-12,\n 5.8448e-02, 1.3146e-01, 1.0657e-01, 4.7739e-03, 2.4331e-05, 1.6862e-02,\n 6.1818e-02, 3.0550e-02, 6.2875e-02, 8.4099e-02, 6.1252e-02, 5.5546e-10,\n 7.1574e-02, 3.6952e-02, 3.1822e-02, 4.9172e-14, 3.1150e-02, 9.5628e-14,\n 1.0095e-01, 1.2507e-02, 4.1888e-02, 1.2691e-04, 1.0230e-03, 1.1545e-02,\n 2.6615e-02, 1.2750e-02, 1.2709e-02, 2.4427e-02, 4.7461e-02, 5.0575e-13,\n 3.7248e-02, 1.0177e-02, 5.5320e-02, 6.3547e-02, 7.0256e-03, 6.6266e-13,\n 4.9484e-02, 4.5796e-02, 5.9989e-02, 3.9775e-02, 6.7656e-02, 1.5566e-02,\n 5.0677e-03, 3.4589e-02, 6.3290e-02, 3.7618e-14, 3.6150e-02, 9.0490e-02,\n 3.1129e-02, 9.5473e-03, 7.2608e-02, 1.5376e-08, 3.6276e-02, 3.1026e-02,\n 2.3794e-02, 6.4353e-07, 1.5921e-02, 3.9649e-02, 5.6337e-02, 2.0634e-02,\n 4.3266e-02, 1.1901e-12, 1.4840e-11, 2.4201e-02, 2.4692e-02, 5.5973e-03,\n 9.2816e-02, 3.1673e-03, 6.3196e-03, 6.4882e-02, 1.5002e-02, 2.3148e-02,\n 1.8546e-02, 5.7284e-02, 2.9657e-02, 3.1707e-02, 2.8366e-02, 1.8107e-02,\n 3.7048e-02, 4.6600e-03, 2.0870e-02, 8.9399e-03, 1.4896e-02, 2.3162e-02,\n 6.2230e-03, 1.1659e-02, 2.6834e-02, 1.6688e-02, 6.7742e-02, 4.5970e-02,\n 8.6276e-03, 2.2645e-01, 5.4013e-03, 3.4232e-02, 1.2020e-02, 1.3129e-02,\n 7.3935e-02, 1.7003e-02, 8.9730e-03, 3.7635e-02, 3.6559e-03, 7.5759e-03,\n 1.5304e-10, 9.0985e-03, 5.7020e-02, 1.5228e-02, 3.7153e-02, 4.8612e-02,\n 2.2196e-02, 1.6622e-02, 5.0405e-02, 2.5960e-03, 7.7398e-02, 7.3837e-12,\n 4.2043e-02, 1.7473e-02, 5.0461e-02, 9.6278e-02, 1.0495e-01, 5.9498e-02,\n 1.1335e-01, 3.4499e-02, 3.7172e-03, 1.1338e-02, 6.1679e-02, 9.1966e-03,\n 2.5275e-02, 9.1299e-10, 7.5890e-02, 4.7725e-02, 1.0012e-13, 2.9560e-02,\n 1.1079e-13, 1.2843e-02, 1.7118e-02, 1.0382e-02, 2.0587e-02, 3.1524e-02,\n 3.9261e-02, 1.4925e-02, 2.8532e-03, 1.7211e-02, 3.1684e-12, 6.8206e-02,\n 3.1523e-02, 3.1019e-02, 3.1753e-02, 2.4866e-02, 3.0804e-01, 6.5936e-03,\n 2.8843e-03, 8.3814e-02, 9.4360e-03, 5.0218e-02, 8.4435e-02, 1.8361e-02,\n 3.7597e-02, 2.1522e-02, 1.5498e-03, 2.1778e-02, 2.0181e-02, 5.9260e-02,\n 2.8045e-02, 5.4537e-02, 4.3733e-02, 2.7338e-01, 7.4174e-03, 6.3420e-03,\n 9.9639e-03, 1.8706e-02, 1.4396e-01, 7.0821e-02, 4.2993e-02, 4.7345e-02,\n 7.0332e-08, 1.3892e-02, 2.8204e-02, 2.5292e-02, 4.5253e-02, 1.1483e-01,\n 2.2264e-02, 6.6646e-02, 6.8986e-02, 2.9963e-02]), 'model.layer1.0.downsample.1.num_batches_tracked': tensor(7160), 'model.layer1.1.conv1.weight': tensor([[[[ 0.0386]],\n\n [[ 0.0142]],\n\n [[ 0.0127]],\n\n ...,\n\n [[ 0.0129]],\n\n [[ 0.0225]],\n\n [[-0.0353]]],\n\n\n [[[ 0.0091]],\n\n [[ 0.0105]],\n\n [[-0.0071]],\n\n ...,\n\n [[-0.0133]],\n\n [[ 0.0320]],\n\n [[-0.0747]]],\n\n\n [[[-0.0020]],\n\n [[ 0.0069]],\n\n [[ 0.0226]],\n\n ...,\n\n [[-0.0041]],\n\n [[-0.0553]],\n\n [[ 0.0356]]],\n\n\n ...,\n\n\n [[[ 0.0030]],\n\n [[ 0.0155]],\n\n [[-0.0032]],\n\n ...,\n\n [[ 0.0112]],\n\n [[-0.0102]],\n\n [[-0.0551]]],\n\n\n [[[ 0.0504]],\n\n [[-0.0009]],\n\n [[-0.0147]],\n\n ...,\n\n [[ 0.0247]],\n\n [[ 0.0385]],\n\n [[-0.0259]]],\n\n\n [[[ 0.0149]],\n\n [[ 0.0296]],\n\n [[ 0.0159]],\n\n ...,\n\n [[ 0.0027]],\n\n [[-0.0199]],\n\n [[ 0.0640]]]]), 'model.layer1.1.bn1.weight': tensor([1.6927e-01, 3.2092e-01, 2.3994e-01, 2.0620e-01, 1.7239e-01, 1.8103e-01,\n 1.6215e-01, 2.4926e-01, 1.6876e-01, 3.1784e-01, 1.4325e-01, 1.9617e-01,\n 1.3244e-01, 1.2985e-09, 1.5507e-01, 1.8593e-01, 1.6448e-01, 1.9148e-01,\n 2.5287e-01, 1.7052e-01, 1.4617e-01, 1.7141e-01, 1.7597e-01, 1.2425e-01,\n 1.5912e-01, 1.0582e-01, 1.6503e-01, 1.5500e-01, 1.7386e-01, 2.3101e-01,\n 2.7820e-01, 2.1044e-01, 2.3985e-01, 1.8276e-01, 1.6419e-01, 1.5973e-01,\n 1.6807e-01, 2.4819e-01, 3.3578e-01, 1.3747e-01, 3.0460e-01, 2.9669e-01,\n 1.8158e-01, 2.8924e-01, 1.1781e-01, 4.6577e-07, 1.7349e-01, 1.4380e-08,\n 1.5815e-01, 1.8338e-01, 1.9670e-01, 2.1056e-01, 1.5188e-01, 2.4303e-01,\n 1.3356e-01, 2.9881e-01, 8.5831e-09, 1.7806e-01, 1.3872e-01, 1.5667e-01,\n 2.2360e-01, 1.3818e-01, 1.9050e-01, 1.8732e-01]), 'model.layer1.1.bn1.bias': tensor([ 6.1926e-02, -2.0984e-01, -1.1887e-01, -5.8621e-03, -5.3990e-02,\n -1.3508e-02, -8.0691e-03, -2.0602e-01, 1.3409e-02, -4.0462e-01,\n 2.1678e-02, -9.5836e-02, 1.0302e-01, -9.1670e-08, 4.5442e-03,\n -4.3987e-02, 5.9544e-02, 2.3764e-02, -1.4693e-01, -2.4228e-01,\n -5.3976e-04, 8.3240e-02, 8.1751e-03, 1.9749e-02, 1.0319e-01,\n 7.0648e-02, -1.4815e-02, 2.3621e-01, -5.0642e-02, -4.3683e-02,\n -1.8087e-01, -5.2920e-03, -1.0260e-01, -1.0352e-01, 1.5745e-02,\n -9.6596e-02, 2.8532e-01, -1.4199e-01, -2.3099e-01, 1.5172e-02,\n -1.9756e-01, -2.3497e-01, -9.1097e-02, -1.9510e-01, 3.0078e-01,\n -2.2354e-06, -1.2522e-01, -1.0213e-07, 9.8020e-02, -2.5489e-01,\n -6.1594e-02, -1.5090e-02, 1.4725e-01, -7.5203e-02, 2.9187e-01,\n -1.9195e-01, -6.0297e-08, 4.0168e-01, 9.3859e-02, 1.1821e-01,\n -9.7528e-03, 2.5260e-01, -1.5497e-01, 1.9963e-02]), 'model.layer1.1.bn1.running_mean': tensor([-1.1010e-03, 1.0792e-01, -9.9815e-03, 1.5380e-01, 1.8186e-01,\n 7.8607e-03, 8.4335e-02, 1.7228e-02, -1.7814e-01, 1.6476e-01,\n -3.1962e-01, 8.5684e-02, 2.7364e-01, 2.7551e-09, -8.3056e-02,\n 5.2380e-02, 5.9071e-02, -1.0982e-02, 2.1214e-02, 2.3931e-02,\n -7.9469e-02, -9.2043e-02, -1.7807e-01, 1.0245e-01, 3.6587e-02,\n 7.1407e-02, -4.5323e-02, -3.7531e-02, 1.6084e-02, 8.3836e-02,\n 7.3780e-02, 1.8761e-02, 1.7500e-01, 9.2852e-02, 6.9093e-02,\n 2.8512e-02, -9.5899e-02, 4.0381e-02, 6.4372e-02, 1.3343e-03,\n 1.5439e-01, -1.6829e-02, 5.0582e-02, 6.7305e-02, 2.2081e-02,\n -5.0206e-07, -1.7421e-01, 2.5626e-08, -6.8795e-02, -4.7895e-02,\n 1.0387e-01, 1.2167e-01, -1.3449e-01, 7.0074e-02, 3.2504e-02,\n -1.3614e-01, 1.2496e-08, 5.1316e-01, -2.2556e-01, 1.1770e-02,\n 3.7739e-02, -2.5499e-02, -5.1749e-02, -1.1650e-01]), 'model.layer1.1.bn1.running_var': tensor([1.3863e-02, 7.5030e-02, 3.1531e-02, 2.9037e-02, 3.1133e-02, 2.1560e-02,\n 1.4590e-02, 2.6931e-02, 2.4951e-02, 1.7458e-02, 1.3577e-02, 2.4710e-02,\n 3.3357e-02, 1.1231e-15, 1.6429e-02, 2.6842e-02, 4.9931e-02, 5.7131e-02,\n 2.5741e-02, 1.5055e-02, 2.5249e-02, 2.4704e-02, 3.7285e-02, 2.1464e-02,\n 2.2138e-02, 2.8122e-02, 3.9983e-02, 3.1830e-02, 1.6654e-02, 2.1361e-02,\n 7.1096e-02, 3.3143e-02, 1.0750e-02, 1.6992e-02, 4.4831e-02, 2.1671e-02,\n 4.9301e-02, 3.8709e-02, 3.7692e-02, 1.5305e-02, 8.4251e-02, 2.3392e-02,\n 1.6779e-02, 7.9266e-02, 1.7028e-02, 7.9360e-14, 1.0571e-02, 7.1381e-16,\n 2.8138e-02, 1.9315e-02, 1.3686e-02, 1.4114e-02, 1.4891e-02, 3.1680e-02,\n 2.1562e-02, 3.2163e-02, 5.5449e-16, 4.1868e-02, 2.1439e-02, 2.0498e-02,\n 3.1297e-02, 1.9448e-02, 2.6861e-02, 3.5104e-02]), 'model.layer1.1.bn1.num_batches_tracked': tensor(7160), 'model.layer1.1.conv2.weight': tensor([[[[ 0.0080, -0.0098, 0.0079],\n [-0.0013, -0.0215, -0.0179],\n [-0.0071, -0.0201, -0.0097]],\n\n [[-0.0053, 0.0025, -0.0045],\n [ 0.0164, 0.0368, 0.0480],\n [-0.0071, -0.0083, -0.0075]],\n\n [[ 0.0081, 0.0217, 0.0234],\n [ 0.0160, 0.0100, 0.0169],\n [ 0.0053, -0.0121, 0.0121]],\n\n ...,\n\n [[-0.0200, -0.0422, -0.0262],\n [ 0.0591, 0.0528, 0.0424],\n [-0.0282, -0.0588, -0.0331]],\n\n [[ 0.0078, 0.0282, 0.0115],\n [ 0.0153, 0.0130, 0.0158],\n [-0.0068, 0.0047, -0.0011]],\n\n [[-0.0025, -0.0144, 0.0015],\n [ 0.0181, -0.0122, -0.0130],\n [-0.0071, -0.0288, -0.0083]]],\n\n\n [[[-0.0080, -0.0021, 0.0095],\n [ 0.0169, -0.0077, -0.0010],\n [ 0.0077, -0.0048, -0.0069]],\n\n [[-0.0062, -0.0074, 0.0179],\n [ 0.0543, 0.0365, 0.0429],\n [ 0.0259, 0.0019, 0.0172]],\n\n [[ 0.0040, -0.0171, -0.0190],\n [ 0.0133, 0.0007, -0.0107],\n [-0.0003, 0.0090, 0.0019]],\n\n ...,\n\n [[ 0.0142, -0.0062, -0.0150],\n [ 0.0091, 0.0076, -0.0243],\n [ 0.0203, 0.0219, 0.0065]],\n\n [[-0.0079, -0.0296, -0.0430],\n [ 0.0143, -0.0217, -0.0511],\n [ 0.0277, 0.0149, -0.0302]],\n\n [[ 0.0029, 0.0047, -0.0060],\n [-0.0042, -0.0026, -0.0130],\n [ 0.0069, -0.0062, -0.0142]]],\n\n\n [[[-0.0295, 0.0121, 0.0140],\n [-0.0318, 0.0314, -0.0050],\n [-0.0215, 0.0090, 0.0120]],\n\n [[-0.0283, -0.0374, -0.0504],\n [-0.0483, -0.0620, -0.0384],\n [-0.0330, -0.0432, -0.0348]],\n\n [[ 0.0003, 0.0117, 0.0013],\n [-0.0017, -0.0174, 0.0228],\n [ 0.0035, -0.0232, 0.0062]],\n\n ...,\n\n [[-0.0068, 0.0069, -0.0342],\n [-0.0183, 0.0211, -0.0063],\n [-0.0034, 0.0058, -0.0106]],\n\n [[ 0.0239, -0.0129, -0.0094],\n [ 0.0233, -0.0069, -0.0177],\n [ 0.0063, -0.0039, -0.0111]],\n\n [[-0.0054, 0.0016, -0.0312],\n [ 0.0372, 0.0390, -0.0205],\n [-0.0067, 0.0049, -0.0319]]],\n\n\n ...,\n\n\n [[[ 0.0226, -0.0017, 0.0149],\n [ 0.0445, 0.0062, 0.0201],\n [ 0.0331, 0.0246, 0.0173]],\n\n [[ 0.0063, 0.0131, 0.0109],\n [ 0.0244, 0.0050, 0.0065],\n [ 0.0171, 0.0115, 0.0282]],\n\n [[ 0.0100, 0.0167, 0.0131],\n [ 0.0126, 0.0169, 0.0115],\n [ 0.0308, 0.0070, -0.0060]],\n\n ...,\n\n [[-0.0057, -0.0111, -0.0281],\n [ 0.0261, 0.0236, -0.0216],\n [-0.0305, -0.0274, -0.0482]],\n\n [[ 0.0124, -0.0024, -0.0199],\n [-0.0251, -0.0253, 0.0010],\n [-0.0107, 0.0089, -0.0008]],\n\n [[ 0.0141, -0.0209, 0.0003],\n [ 0.0219, -0.0353, -0.0010],\n [ 0.0098, 0.0102, 0.0435]]],\n\n\n [[[ 0.0478, 0.0379, 0.0169],\n [ 0.0259, 0.0095, -0.0142],\n [ 0.0143, -0.0187, -0.0064]],\n\n [[-0.0045, 0.0087, 0.0018],\n [-0.0073, -0.0038, 0.0059],\n [ 0.0016, 0.0091, 0.0035]],\n\n [[-0.0013, 0.0060, 0.0383],\n [ 0.0019, 0.0130, 0.0605],\n [ 0.0327, 0.0355, 0.0353]],\n\n ...,\n\n [[-0.0096, 0.0154, -0.0491],\n [ 0.0007, 0.0158, -0.0287],\n [-0.0242, 0.0547, -0.0214]],\n\n [[-0.0070, 0.0018, 0.0152],\n [-0.0107, 0.0029, 0.0321],\n [-0.0083, 0.0250, 0.0193]],\n\n [[ 0.0230, 0.0113, -0.0002],\n [ 0.0452, -0.0088, -0.0264],\n [-0.0109, -0.0260, -0.0095]]],\n\n\n [[[-0.0367, -0.0090, -0.0502],\n [-0.0002, -0.0864, -0.0083],\n [-0.0244, 0.0135, -0.0049]],\n\n [[-0.0367, 0.0172, -0.0067],\n [-0.0121, 0.0611, 0.0015],\n [-0.0236, -0.0029, -0.0187]],\n\n [[ 0.0187, 0.0244, 0.0063],\n [ 0.0159, 0.0077, 0.0141],\n [ 0.0220, 0.0124, 0.0110]],\n\n ...,\n\n [[ 0.0298, 0.0130, 0.0053],\n [ 0.0265, -0.0855, 0.0204],\n [ 0.0059, 0.0222, 0.0143]],\n\n [[ 0.0225, -0.0089, 0.0004],\n [-0.0075, -0.0909, 0.0136],\n [-0.0017, -0.0234, 0.0015]],\n\n [[ 0.0171, 0.0209, 0.0064],\n [ 0.0273, -0.0194, -0.0050],\n [ 0.0489, 0.0133, 0.0183]]]]), 'model.layer1.1.bn2.weight': tensor([0.3013, 0.1953, 0.1699, 0.1657, 0.2540, 0.1348, 0.1565, 0.1960, 0.1313,\n 0.1654, 0.1861, 0.2031, 0.2225, 0.1849, 0.1589, 0.1518, 0.2254, 0.2166,\n 0.1525, 0.2066, 0.1586, 0.1711, 0.1731, 0.1701, 0.1770, 0.2451, 0.1475,\n 0.1905, 0.1300, 0.1343, 0.2252, 0.2167, 0.2227, 0.1646, 0.1819, 0.2208,\n 0.1382, 0.2367, 0.1762, 0.2053, 0.1629, 0.1686, 0.2162, 0.1751, 0.1971,\n 0.1722, 0.1975, 0.1775, 0.1849, 0.1902, 0.1597, 0.2126, 0.1635, 0.1739,\n 0.1509, 0.2082, 0.1462, 0.1928, 0.2605, 0.1699, 0.1868, 0.1252, 0.1666,\n 0.1841]), 'model.layer1.1.bn2.bias': tensor([-0.3359, -0.0946, -0.0084, 0.0461, -0.0967, 0.3081, 0.0471, -0.0097,\n 0.2563, 0.1308, -0.1302, -0.0023, -0.1570, -0.0470, 0.1909, 0.0750,\n -0.0623, -0.1286, -0.0010, -0.1090, 0.0685, -0.1260, 0.0403, 0.0499,\n 0.0815, -0.2061, 0.2651, -0.1556, 0.2621, 0.2544, -0.0931, 0.0434,\n -0.0347, -0.0489, 0.0175, 0.0085, 0.1889, -0.0362, -0.0933, -0.0570,\n -0.2145, -0.0833, -0.0540, -0.0346, -0.0928, -0.0869, -0.1407, 0.0177,\n -0.1219, -0.1332, 0.0697, -0.0134, -0.0139, -0.0301, 0.3007, 0.0173,\n 0.1703, -0.0611, -0.1803, 0.1145, 0.0496, 0.1159, -0.0766, -0.0370]), 'model.layer1.1.bn2.running_mean': tensor([-0.1988, 0.0561, -0.0693, -0.1215, 0.1208, -0.0291, 0.0515, -0.1199,\n -0.0803, -0.0735, -0.0708, 0.1551, 0.1152, -0.0097, 0.0746, 0.0052,\n 0.0779, 0.0203, -0.3041, -0.1505, 0.0095, -0.0486, -0.1086, 0.0455,\n -0.0824, 0.0110, -0.0792, 0.0759, -0.0677, 0.1171, 0.1304, -0.0137,\n -0.0635, -0.2271, -0.0291, 0.0059, -0.1549, 0.1283, -0.0524, 0.0227,\n -0.1101, -0.0665, 0.0782, -0.1763, -0.0583, 0.1232, -0.0963, -0.0230,\n -0.0971, 0.0079, -0.0596, -0.0982, -0.2823, 0.0848, -0.0966, -0.0504,\n -0.1345, -0.0530, 0.1509, -0.0225, 0.0587, -0.0545, -0.0999, -0.0431]), 'model.layer1.1.bn2.running_var': tensor([0.0075, 0.0182, 0.0161, 0.0173, 0.0212, 0.0186, 0.0165, 0.0212, 0.0163,\n 0.0210, 0.0164, 0.0199, 0.0121, 0.0128, 0.0307, 0.0110, 0.0189, 0.0128,\n 0.0110, 0.0196, 0.0235, 0.0117, 0.0138, 0.0260, 0.0210, 0.0127, 0.0347,\n 0.0136, 0.0135, 0.0198, 0.0215, 0.0243, 0.0196, 0.0189, 0.0352, 0.0251,\n 0.0235, 0.0248, 0.0105, 0.0120, 0.0108, 0.0168, 0.0193, 0.0081, 0.0249,\n 0.0182, 0.0120, 0.0283, 0.0126, 0.0116, 0.0143, 0.0301, 0.0143, 0.0199,\n 0.0158, 0.0238, 0.0273, 0.0170, 0.0118, 0.0199, 0.0345, 0.0155, 0.0082,\n 0.0173]), 'model.layer1.1.bn2.num_batches_tracked': tensor(7160), 'model.layer1.1.conv3.weight': tensor([[[[ 0.0753]],\n\n [[-0.0050]],\n\n [[-0.0017]],\n\n ...,\n\n [[ 0.0018]],\n\n [[ 0.0022]],\n\n [[-0.0028]]],\n\n\n [[[ 0.1061]],\n\n [[ 0.0094]],\n\n [[ 0.0004]],\n\n ...,\n\n [[-0.0007]],\n\n [[-0.0039]],\n\n [[-0.0013]]],\n\n\n [[[ 0.0548]],\n\n [[-0.0198]],\n\n [[-0.0142]],\n\n ...,\n\n [[-0.0016]],\n\n [[-0.0030]],\n\n [[ 0.0210]]],\n\n\n ...,\n\n\n [[[ 0.0897]],\n\n [[-0.0068]],\n\n [[-0.0016]],\n\n ...,\n\n [[ 0.0039]],\n\n [[ 0.0078]],\n\n [[-0.0019]]],\n\n\n [[[-0.0160]],\n\n [[ 0.0106]],\n\n [[ 0.0214]],\n\n ...,\n\n [[ 0.0013]],\n\n [[-0.0056]],\n\n [[-0.0126]]],\n\n\n [[[ 0.0453]],\n\n [[-0.0482]],\n\n [[ 0.0003]],\n\n ...,\n\n [[ 0.0008]],\n\n [[-0.0111]],\n\n [[-0.0370]]]]), 'model.layer1.1.bn3.weight': tensor([-9.1331e-04, 3.2678e-04, 9.5888e-02, -3.5782e-03, 1.5008e-01,\n -8.0720e-04, 2.0485e-01, 1.3599e-02, 2.1615e-04, 1.1696e-01,\n 6.4282e-03, 1.5323e-01, -1.5722e-03, -1.5775e-03, 9.7623e-02,\n 1.5064e-01, 1.1122e-01, 1.7222e-02, 9.4802e-02, -2.0376e-03,\n 7.8805e-02, -1.8482e-04, 1.6092e-01, 2.8410e-01, 8.4786e-02,\n 1.2589e-01, -1.5281e-04, 1.4145e-01, -1.8060e-03, 5.2502e-02,\n 1.6936e-03, -2.4145e-03, 3.0466e-02, 1.1397e-01, 9.9802e-02,\n 7.6213e-02, 1.5283e-01, 8.2101e-02, 4.6795e-03, 2.0749e-04,\n 1.1435e-01, 5.8348e-02, 1.5193e-01, 8.3733e-02, 1.0078e-01,\n 5.3188e-02, 9.5475e-02, 1.5038e-01, 7.2377e-02, 2.3651e-02,\n -1.0057e-02, 1.7725e-01, 6.5325e-02, 1.4088e-01, 9.6957e-03,\n 1.4571e-02, 1.8799e-01, 7.2286e-02, 1.0962e-01, 1.1163e-01,\n 1.3478e-03, 8.1567e-02, 5.7434e-04, 1.5240e-01, 7.9670e-08,\n 1.0586e-03, 1.2557e-01, 3.5182e-02, 1.5801e-01, 3.1509e-02,\n 1.2130e-01, 6.9955e-06, 3.6828e-02, 9.1731e-05, 2.2850e-02,\n 1.4780e-01, 2.2151e-01, 1.0345e-01, 4.1334e-03, 1.2158e-01,\n 7.0923e-02, 4.0640e-02, 2.7021e-02, 5.2092e-02, 9.7534e-02,\n 6.3450e-02, 1.0542e-01, 7.0710e-02, 5.0712e-04, 3.2789e-04,\n -4.5818e-04, 1.1864e-01, -4.8852e-05, 1.0840e-01, 2.3112e-01,\n 1.6079e-01, 1.6724e-03, 1.1077e-01, 1.6377e-01, 1.4721e-01,\n 1.0225e-01, 1.9535e-06, 7.8711e-02, -6.2360e-04, 2.4008e-02,\n 1.2216e-01, 1.4072e-01, 1.0364e-01, -4.3513e-04, 6.1345e-02,\n -1.1039e-03, 5.6171e-02, -9.1920e-04, 4.6816e-02, 1.4128e-01,\n -3.0165e-03, 1.5681e-03, 1.5899e-01, 5.7623e-02, 1.3543e-04,\n 1.3786e-01, 1.8321e-01, 1.1943e-01, -2.3750e-05, 1.6626e-01,\n 5.5049e-02, 1.5782e-01, -4.7397e-05, 7.5145e-02, 5.3293e-02,\n 1.1733e-01, 1.5163e-01, 1.0848e-01, 1.4982e-01, 8.1973e-02,\n 1.2846e-01, 8.1095e-02, 1.4904e-01, 1.0884e-01, 1.5104e-01,\n 1.2394e-01, 1.6022e-03, 6.6987e-02, 1.0138e-01, 5.1852e-02,\n 7.5890e-02, -4.4102e-03, 1.2883e-01, -1.1088e-01, 7.9669e-02,\n 1.6454e-02, 7.7810e-02, 2.1628e-01, 6.6117e-02, 7.0572e-02,\n 1.9633e-01, 1.3462e-01, 2.0798e-01, -2.8854e-04, 3.3247e-04,\n -2.8387e-03, 6.8280e-02, 1.3172e-04, 1.2710e-03, 1.7755e-01,\n 1.8688e-01, 1.8056e-01, 2.1409e-03, 9.7601e-02, 1.0962e-01,\n 2.1195e-01, 1.3170e-02, 1.8888e-01, 1.4384e-01, 1.4909e-01,\n 9.0227e-02, 7.5596e-02, 9.7114e-04, 8.6789e-02, 1.4896e-01,\n -6.8329e-02, -9.3657e-04, 1.3527e-01, 2.0635e-01, -8.1323e-04,\n 2.1734e-06, -9.1002e-03, -5.9016e-04, 5.6265e-02, -1.1752e-04,\n 1.7097e-01, 3.0287e-03, -1.1804e-04, 2.3321e-02, 2.0346e-01,\n -5.1443e-04, 9.2140e-02, 8.2117e-02, 4.5362e-02, 1.5509e-01,\n 6.8066e-03, 6.7643e-02, 1.8972e-06, 1.7571e-02, 1.8305e-01,\n 1.0420e-03, 1.5937e-01, 5.4328e-02, 7.7009e-02, 9.4142e-02,\n 8.2763e-02, -5.8300e-02, 1.7615e-01, 1.1052e-01, 1.6207e-01,\n 2.4961e-02, 1.0852e-01, 1.0126e-01, 6.5492e-02, 6.7337e-02,\n 3.9191e-04, 8.5595e-02, 1.2980e-01, 6.7397e-04, 1.0305e-01,\n 1.1942e-01, -5.9911e-05, 4.8424e-02, 1.3340e-04, 1.5612e-01,\n 1.1780e-01, -8.6393e-04, 1.9234e-01, 6.2765e-03, 6.5450e-02,\n 7.4767e-03, 1.8290e-01, 8.0557e-05, 1.7037e-01, 3.1679e-02,\n 1.0368e-01, 1.9361e-01, 4.3913e-04, 7.9058e-02, 1.1168e-01,\n 1.7604e-01, 1.1558e-01, 1.8600e-01, 8.0448e-02, 1.5643e-01,\n 5.1649e-02, -2.5784e-04, -3.2045e-04, -2.1109e-04, 3.1007e-02,\n 2.1258e-01]), 'model.layer1.1.bn3.bias': tensor([-2.9638e-03, 8.6855e-03, -7.3696e-02, -1.6201e-03, -4.8818e-02,\n 9.4987e-03, 6.7300e-02, -4.4489e-03, 1.5294e-03, 4.6972e-02,\n -4.1718e-03, 1.0182e-01, 4.7999e-02, 1.2109e-03, -3.1889e-02,\n 2.3090e-02, -2.4323e-02, -2.5057e-03, -1.0815e-01, 7.9247e-03,\n 2.7059e-02, -1.3728e-03, 6.7317e-02, 2.4849e-02, -2.5379e-02,\n -5.5416e-02, -4.8938e-04, 9.4622e-03, 7.9362e-03, -3.0732e-02,\n -3.3607e-03, 1.0336e-02, 2.8580e-02, 1.1029e-01, 9.6091e-02,\n 1.0514e-01, -1.1674e-01, -2.6633e-02, -8.7265e-03, -8.0476e-03,\n -2.9254e-02, -1.8421e-02, -1.9816e-02, -6.6515e-02, 4.6083e-02,\n 5.1194e-02, 2.4187e-02, -6.4821e-02, -1.2277e-01, 5.6334e-02,\n 1.3503e-02, 9.0654e-02, -5.2730e-02, 6.6957e-03, 1.0900e-02,\n -6.5086e-04, 1.4728e-01, -4.6565e-02, -7.6439e-02, -4.3101e-03,\n 9.0400e-03, -4.2037e-02, 5.5112e-03, 5.9526e-02, -2.8872e-07,\n 7.9988e-03, -6.2872e-02, 3.1994e-02, -7.1147e-02, -1.2161e-03,\n -5.2347e-02, -5.9013e-05, 4.2808e-02, 4.5724e-03, -1.4176e-02,\n 6.7074e-02, 4.0730e-02, -5.1580e-02, 6.3705e-03, -2.6303e-02,\n 3.7072e-03, 5.4634e-02, 8.5585e-03, 9.6532e-02, 1.2326e-01,\n 9.7415e-02, 4.7163e-02, -2.1920e-02, 1.3624e-02, -2.7292e-03,\n 3.2575e-03, 1.6203e-02, 4.5157e-03, 1.3795e-02, 9.9654e-02,\n 5.9402e-02, 4.2113e-03, -5.4029e-02, 9.9462e-02, 1.4261e-01,\n 1.3952e-03, -3.7883e-05, 8.0331e-03, 2.7068e-03, 3.8325e-03,\n -2.7365e-02, -1.5690e-01, -1.9727e-02, 4.8514e-03, 1.8967e-02,\n -1.8836e-02, 1.0919e-01, 6.0169e-03, -2.5281e-03, 5.1729e-02,\n -4.3268e-03, 3.2047e-03, 8.6832e-04, 8.7328e-03, 1.2190e-02,\n -8.5171e-02, -1.3414e-01, -6.1807e-02, -5.2930e-04, -2.2781e-02,\n 4.4114e-02, 2.7817e-02, -7.7662e-04, -7.9066e-02, 7.4319e-03,\n -4.6442e-02, -8.3157e-03, 4.5401e-02, -2.2300e-02, -7.6587e-02,\n -2.8839e-02, -2.9096e-02, -5.5020e-02, 5.6329e-02, -1.1472e-01,\n -3.7919e-02, 5.5448e-03, -4.9121e-03, 2.5361e-02, -1.0750e-01,\n -5.1617e-02, 8.9678e-04, 2.3212e-02, -3.2841e-02, 7.8923e-03,\n -9.5893e-02, -4.1146e-02, -5.4458e-02, -2.0122e-03, 5.5422e-02,\n 5.5857e-02, -1.8428e-02, 8.2780e-03, 3.6913e-03, 9.3600e-03,\n -1.7881e-03, 4.8230e-03, 8.9931e-03, 1.0224e-02, 2.6115e-02,\n 3.0318e-02, -8.2535e-02, 8.1901e-03, -1.8899e-02, 2.9661e-02,\n 1.6324e-01, -2.6840e-03, -1.5077e-02, -3.3480e-02, -3.0824e-02,\n -1.0823e-01, -3.2462e-02, 1.0582e-02, 1.7111e-02, 1.0393e-01,\n 1.1556e-02, -1.5742e-02, 3.2784e-02, 4.4736e-02, 7.3579e-03,\n -3.3409e-06, -3.0555e-03, 5.0347e-02, -9.7009e-03, 1.0437e-02,\n -6.5392e-02, -4.8660e-03, 4.7889e-03, 4.9290e-03, 2.5889e-02,\n 6.1099e-03, -8.0221e-03, 9.0808e-03, -3.8963e-02, -4.5344e-02,\n -3.4873e-03, 4.0665e-03, -2.2053e-05, 1.2821e-02, -2.7410e-02,\n 3.5218e-03, -2.5082e-02, 5.8740e-02, 1.0302e-02, 1.3235e-01,\n 1.7820e-03, -7.2183e-02, 3.4267e-02, -1.3029e-02, -1.5743e-01,\n 1.2190e-02, -8.9407e-03, 1.7055e-02, 2.0984e-02, -2.9473e-02,\n 1.9603e-03, -4.5110e-02, 3.2766e-02, 4.0730e-03, 1.1601e-01,\n -3.9863e-02, 8.7819e-03, -1.2261e-02, 7.5687e-03, 5.7397e-02,\n -4.7361e-02, 1.0804e-02, 8.9083e-02, 2.1135e-03, 5.3514e-02,\n -2.1523e-03, -1.0374e-01, 9.7619e-03, 2.9890e-02, -2.1884e-02,\n -1.1063e-02, 1.1817e-01, 8.0786e-03, -4.3845e-02, 3.6391e-04,\n -3.5340e-02, -6.0003e-02, -8.0349e-02, -6.5354e-02, 5.6029e-03,\n 4.6616e-03, -1.0074e-02, -4.0020e-03, 2.8383e-03, 2.7619e-02,\n -6.8801e-02]), 'model.layer1.1.bn3.running_mean': tensor([ 9.6161e-04, 1.2023e-03, 3.0344e-03, 8.5014e-03, -1.3876e-02,\n -1.0926e-03, -3.4682e-02, 1.7525e-02, -2.1860e-03, 1.1286e-02,\n -4.7167e-03, 7.4020e-02, 1.0363e-03, 3.9487e-03, -6.7690e-03,\n 9.8688e-02, -5.3362e-02, 1.6484e-02, 2.0595e-02, 1.0178e-03,\n 1.0614e-02, 4.8325e-03, -9.7919e-03, 2.8677e-03, -2.4690e-02,\n 4.0830e-02, -3.5002e-03, 1.4753e-02, 7.3970e-03, 1.7438e-03,\n -1.6609e-03, 1.6398e-03, 1.4441e-02, -1.0769e-02, 1.1438e-01,\n -2.9248e-02, 4.5216e-02, -2.5238e-02, 1.3426e-02, 7.6692e-03,\n -2.7607e-02, 2.2575e-02, -4.4358e-02, -3.5704e-02, 1.4672e-02,\n -8.6538e-03, 1.5856e-03, 5.1741e-03, -1.6416e-02, -3.8029e-03,\n -1.8381e-02, 8.2106e-02, 1.1701e-02, -9.3041e-03, 1.8667e-03,\n -5.4864e-03, -5.8866e-02, 5.2340e-03, 9.0031e-03, -9.1174e-02,\n -2.9998e-03, 2.3903e-02, 6.5954e-04, 5.0002e-02, 7.2247e-08,\n -2.3157e-03, 3.5819e-03, 5.6565e-03, -1.4356e-02, 4.4469e-04,\n -3.2653e-03, -2.5697e-05, -2.0286e-02, -6.4515e-04, -3.0599e-02,\n -5.7680e-02, 3.7364e-03, -9.2547e-03, 1.0664e-02, 2.0554e-03,\n -2.3488e-02, -7.6919e-03, -1.1633e-02, 1.8361e-02, 7.3773e-03,\n -4.6763e-02, -3.9731e-02, -4.4232e-02, 7.5447e-03, 1.6110e-03,\n 2.7415e-04, 9.1666e-03, -2.4611e-03, -7.4530e-02, 6.8469e-02,\n 8.1680e-02, -4.0671e-04, 4.7438e-02, 6.0495e-02, 3.9206e-02,\n 1.6688e-02, 6.6863e-06, -6.8737e-02, 5.4598e-03, 1.3376e-03,\n 1.7210e-02, 9.5211e-02, 2.5385e-03, 1.8323e-03, -2.0058e-02,\n -3.8357e-03, -9.9236e-04, -4.9193e-03, -1.7243e-03, 8.0583e-02,\n 1.6215e-03, 6.0315e-03, 2.1220e-02, -2.7267e-02, -1.1678e-02,\n 1.4002e-02, 1.0758e-01, 5.3771e-02, 2.2540e-05, 2.4238e-02,\n 2.8326e-02, 2.3099e-02, -6.0360e-05, 3.9181e-02, -7.4373e-02,\n 2.3695e-02, -3.8652e-02, -2.7711e-02, -7.6424e-02, -2.8749e-03,\n 2.4922e-02, -7.2181e-03, 4.7763e-02, 3.5269e-02, -4.1026e-02,\n -3.7846e-02, -1.1596e-02, -3.3875e-02, 4.4611e-02, 1.3820e-03,\n 9.3090e-04, -2.7063e-02, -1.0248e-02, -9.0077e-02, -4.3081e-02,\n 1.3574e-02, -1.6923e-02, -2.9166e-02, -1.6757e-02, 2.9886e-02,\n -8.1642e-03, 4.4856e-02, -3.2801e-02, 9.7507e-04, 4.4586e-03,\n -2.7755e-03, -4.0092e-02, -1.1796e-02, 7.0033e-03, -6.4908e-02,\n -1.4000e-02, 2.6326e-02, 3.5729e-03, 3.5000e-02, 2.7121e-02,\n 2.9576e-03, -9.9206e-03, 9.5600e-02, 3.4811e-02, -4.9100e-02,\n -1.8219e-02, -1.6539e-02, -4.9792e-03, -4.1968e-02, -3.5208e-02,\n 3.3743e-02, -3.9789e-03, 7.3546e-03, -4.6546e-02, 6.3560e-03,\n -1.0144e-06, -3.3356e-03, -1.4870e-02, -1.7342e-02, -5.5588e-05,\n 6.3563e-02, 1.5756e-03, -1.7476e-03, -4.9532e-03, -1.0892e-01,\n 3.9961e-03, 5.2590e-03, 5.7019e-04, 4.8904e-02, 4.4529e-02,\n -9.1253e-03, -2.0574e-02, 4.5065e-06, 1.2398e-02, 5.3263e-02,\n -9.9884e-03, -1.9527e-02, -3.7605e-02, 9.8737e-03, -2.5320e-02,\n 4.4033e-02, 7.8718e-03, 6.0160e-03, -7.3258e-02, 8.7336e-03,\n 1.8977e-02, 5.8879e-02, -1.3217e-02, 1.0619e-02, -6.5762e-03,\n 2.0722e-03, -3.5110e-02, 1.4420e-02, -8.9375e-03, -2.4555e-02,\n 2.6842e-02, -3.0233e-04, 2.1720e-02, -2.2843e-03, 1.4147e-02,\n 1.1163e-02, 5.3231e-03, 1.2994e-02, -1.2303e-02, -6.6102e-02,\n -9.9616e-03, -2.7225e-02, -7.8722e-04, 2.5401e-02, 2.9698e-03,\n 2.4789e-03, 1.1436e-01, -6.1629e-03, 1.9780e-02, -2.7497e-03,\n 4.1375e-02, 1.3769e-02, -8.0218e-03, -4.7487e-02, 2.6710e-02,\n -7.0095e-03, 5.7778e-03, 5.6490e-03, -2.8467e-03, 1.9494e-02,\n -1.4092e-03]), 'model.layer1.1.bn3.running_var': tensor([2.1485e-04, 4.1779e-04, 6.7328e-04, 3.8642e-04, 2.3064e-03, 2.1060e-04,\n 5.5456e-03, 5.3085e-04, 3.3285e-04, 2.5157e-03, 2.5155e-04, 4.1611e-03,\n 2.5671e-04, 3.5557e-04, 2.2633e-03, 3.0406e-03, 2.4585e-03, 4.7263e-04,\n 1.6097e-03, 2.8361e-04, 1.0401e-03, 1.5059e-04, 3.0370e-03, 3.6542e-03,\n 3.3543e-03, 1.2935e-03, 1.5674e-04, 2.5374e-03, 2.3566e-04, 1.0697e-03,\n 2.7324e-04, 2.2692e-04, 5.5736e-04, 2.4224e-03, 1.8212e-03, 2.3059e-03,\n 4.6582e-03, 1.8505e-03, 4.5382e-04, 3.2381e-04, 1.4812e-03, 1.5990e-03,\n 2.7468e-03, 2.2447e-03, 2.0855e-03, 8.8943e-04, 2.0646e-03, 1.8053e-03,\n 4.2914e-04, 2.8766e-04, 2.9904e-04, 4.3226e-03, 5.9227e-04, 2.6946e-03,\n 1.7695e-04, 4.0421e-04, 5.3638e-03, 1.1987e-03, 1.9282e-03, 2.2542e-03,\n 2.0868e-04, 2.5126e-03, 1.3506e-04, 2.3419e-03, 6.8982e-15, 4.1531e-04,\n 1.8051e-03, 1.4354e-03, 1.5766e-03, 6.5882e-04, 8.3481e-04, 4.9833e-10,\n 1.5094e-03, 4.2996e-04, 6.4193e-04, 1.7949e-03, 4.4121e-03, 1.1191e-03,\n 2.1462e-04, 2.4744e-03, 1.9338e-03, 1.1240e-03, 7.7209e-04, 1.0323e-03,\n 2.5064e-03, 1.9084e-03, 1.9124e-03, 8.3847e-04, 3.6662e-04, 2.1722e-06,\n 6.6666e-04, 1.3786e-03, 2.4821e-04, 9.4888e-04, 3.4751e-03, 2.9772e-03,\n 1.7315e-04, 1.9721e-03, 2.6956e-03, 3.0141e-03, 2.0838e-03, 1.5036e-10,\n 1.0805e-03, 1.4095e-04, 6.0918e-04, 3.5492e-03, 1.0849e-03, 1.2267e-03,\n 1.7017e-04, 1.4363e-03, 3.8520e-04, 1.2601e-03, 2.7563e-04, 1.4516e-03,\n 2.5679e-03, 1.4493e-04, 2.5213e-04, 1.8789e-03, 1.9265e-03, 3.0659e-04,\n 2.5882e-03, 1.3544e-03, 2.7657e-03, 1.9057e-08, 7.0914e-03, 1.4058e-03,\n 2.1842e-03, 7.3985e-09, 1.4207e-03, 1.0822e-03, 6.2497e-03, 1.3249e-03,\n 1.6205e-03, 2.4578e-03, 6.5097e-04, 2.4811e-03, 1.2194e-03, 1.9211e-03,\n 3.4296e-03, 1.3142e-03, 1.6604e-03, 2.9751e-04, 6.2855e-04, 1.9503e-03,\n 4.9137e-04, 2.1557e-03, 2.4842e-04, 2.9651e-03, 1.8924e-03, 1.5252e-03,\n 2.2748e-04, 1.0521e-03, 3.0295e-03, 1.0527e-03, 1.3126e-03, 3.3776e-03,\n 3.4193e-03, 3.2457e-03, 1.9134e-04, 1.7117e-04, 2.7208e-04, 1.2491e-03,\n 2.0781e-04, 5.9325e-04, 2.1807e-03, 5.4089e-03, 3.6720e-03, 2.3490e-04,\n 2.1153e-03, 2.6767e-03, 4.9342e-03, 1.6292e-04, 2.6201e-03, 1.5021e-03,\n 1.6369e-03, 1.2723e-03, 1.6532e-03, 2.2580e-04, 1.9019e-03, 3.6680e-03,\n 7.4267e-04, 1.2331e-04, 2.6674e-03, 3.5901e-03, 2.3473e-04, 2.9453e-13,\n 2.5012e-04, 2.0227e-04, 1.4961e-03, 5.4681e-04, 5.1711e-03, 2.3279e-04,\n 4.4433e-04, 2.6734e-04, 3.2682e-03, 1.3702e-04, 1.9799e-03, 2.7860e-03,\n 7.0346e-04, 1.6553e-03, 5.9842e-04, 1.4652e-03, 5.7271e-11, 6.6504e-04,\n 2.7093e-03, 2.1794e-04, 2.1163e-03, 2.2295e-03, 1.2961e-03, 2.5939e-03,\n 1.9130e-03, 7.3248e-04, 1.8938e-03, 2.0252e-03, 6.4181e-04, 4.3723e-04,\n 1.7511e-03, 2.3058e-03, 1.0050e-03, 1.3469e-03, 1.0723e-03, 1.3525e-03,\n 1.7136e-03, 4.1198e-04, 2.0876e-03, 3.1477e-03, 4.3163e-04, 8.3212e-04,\n 3.3625e-04, 3.1799e-03, 1.2507e-03, 2.7612e-04, 6.0364e-03, 3.0243e-04,\n 1.1848e-03, 1.7490e-04, 3.2006e-03, 1.4233e-03, 2.1494e-03, 5.9966e-04,\n 1.7238e-03, 3.1119e-03, 5.4040e-04, 2.6250e-03, 5.0548e-03, 5.6484e-03,\n 1.2824e-03, 3.3323e-03, 1.0067e-03, 1.9412e-03, 9.4532e-04, 4.5970e-04,\n 2.1663e-04, 2.7977e-04, 6.2032e-04, 5.5386e-03]), 'model.layer1.1.bn3.num_batches_tracked': tensor(7160), 'model.layer1.2.conv1.weight': tensor([[[[ 0.0083]],\n\n [[-0.0006]],\n\n [[ 0.0004]],\n\n ...,\n\n [[ 0.0017]],\n\n [[-0.0525]],\n\n [[-0.0410]]],\n\n\n [[[-0.0041]],\n\n [[-0.0169]],\n\n [[ 0.0240]],\n\n ...,\n\n [[-0.0050]],\n\n [[-0.1177]],\n\n [[ 0.0715]]],\n\n\n [[[-0.0133]],\n\n [[ 0.0030]],\n\n [[ 0.0191]],\n\n ...,\n\n [[-0.0206]],\n\n [[-0.0203]],\n\n [[ 0.0136]]],\n\n\n ...,\n\n\n [[[ 0.0044]],\n\n [[ 0.0016]],\n\n [[-0.0038]],\n\n ...,\n\n [[ 0.0134]],\n\n [[-0.0134]],\n\n [[ 0.0171]]],\n\n\n [[[ 0.0014]],\n\n [[ 0.0057]],\n\n [[-0.0188]],\n\n ...,\n\n [[-0.0099]],\n\n [[ 0.0684]],\n\n [[-0.0199]]],\n\n\n [[[-0.0018]],\n\n [[ 0.0025]],\n\n [[-0.0314]],\n\n ...,\n\n [[-0.0043]],\n\n [[ 0.0334]],\n\n [[-0.0181]]]]), 'model.layer1.2.bn1.weight': tensor([0.1787, 0.1704, 0.0926, 0.1422, 0.2210, 0.2184, 0.1550, 0.1909, 0.1661,\n 0.1808, 0.2210, 0.1592, 0.1793, 0.2105, 0.2355, 0.1897, 0.2319, 0.1665,\n 0.1686, 0.1996, 0.1849, 0.1536, 0.1796, 0.2099, 0.2018, 0.1745, 0.1692,\n 0.2006, 0.1732, 0.2180, 0.1414, 0.1839, 0.1448, 0.2084, 0.1424, 0.2132,\n 0.1511, 0.2005, 0.1731, 0.1860, 0.1292, 0.2026, 0.2058, 0.1792, 0.1494,\n 0.1409, 0.2264, 0.1985, 0.1429, 0.1801, 0.1859, 0.1577, 0.2055, 0.1973,\n 0.2455, 0.1856, 0.1893, 0.1968, 0.1233, 0.2032, 0.1760, 0.1369, 0.2147,\n 0.1949]), 'model.layer1.2.bn1.bias': tensor([-0.0256, -0.0311, -0.0136, -0.1449, -0.1042, -0.0339, -0.0662, 0.0556,\n 0.0839, 0.1414, -0.1077, -0.2014, 0.0871, -0.0924, -0.1541, 0.0975,\n -0.1563, 0.1470, 0.0910, -0.0661, -0.0660, 0.1342, 0.0801, -0.1074,\n 0.0235, 0.0879, 0.0578, 0.0209, -0.0825, -0.1121, 0.0718, -0.0600,\n 0.1637, -0.0840, 0.1702, -0.0938, 0.1518, -0.0683, 0.0158, -0.1151,\n -0.0644, 0.0620, -0.0326, -0.0557, 0.0516, -0.0992, -0.1437, -0.0446,\n 0.0626, -0.1497, -0.0165, 0.1608, -0.1318, -0.0837, -0.1870, 0.0591,\n -0.0875, -0.0572, 0.0823, -0.1016, -0.0219, 0.0609, -0.1079, -0.0786]), 'model.layer1.2.bn1.running_mean': tensor([-0.1394, -0.1251, 0.0870, -0.0215, 0.1618, 0.0030, 0.0290, -0.0172,\n -0.2099, 0.1088, 0.0719, 0.0931, -0.0728, 0.0180, -0.0367, 0.0782,\n -0.5784, 0.0241, 0.0426, 0.1202, 0.1498, 0.0619, 0.0077, -0.0518,\n -0.0287, 0.2726, 0.0967, 0.0557, -0.0718, -0.0657, 0.1190, 0.0619,\n 0.0672, -0.0946, 0.1764, 0.0338, -0.0728, 0.0110, 0.1209, 0.1320,\n -0.0382, 0.0303, -0.1292, 0.0774, -0.0614, -0.0047, -0.1704, -0.0735,\n -0.2484, -0.0858, -0.0670, 0.0297, -0.0606, -0.1818, -0.0633, 0.1080,\n -0.0526, -0.0605, -0.2560, 0.1068, -0.0653, -0.0644, -0.0590, -0.0369]), 'model.layer1.2.bn1.running_var': tensor([0.0183, 0.0174, 0.0134, 0.0072, 0.0323, 0.0502, 0.0124, 0.0291, 0.0217,\n 0.0432, 0.0204, 0.0072, 0.0482, 0.0185, 0.0196, 0.0387, 0.0128, 0.0404,\n 0.0300, 0.0226, 0.0259, 0.0171, 0.0277, 0.0215, 0.0352, 0.0377, 0.0317,\n 0.0382, 0.0224, 0.0136, 0.0224, 0.0183, 0.0307, 0.0218, 0.0258, 0.0178,\n 0.0127, 0.0194, 0.0162, 0.0223, 0.0124, 0.0425, 0.0376, 0.0207, 0.0350,\n 0.0059, 0.0266, 0.0275, 0.0195, 0.0090, 0.0279, 0.0297, 0.0122, 0.0253,\n 0.0204, 0.0462, 0.0145, 0.0172, 0.0250, 0.0288, 0.0223, 0.0246, 0.0119,\n 0.0153]), 'model.layer1.2.bn1.num_batches_tracked': tensor(7160), 'model.layer1.2.conv2.weight': tensor([[[[ 3.2046e-02, -4.8372e-03, -3.2694e-02],\n [-7.5040e-03, -1.4202e-02, -1.8259e-02],\n [-5.8466e-02, 2.1640e-02, -1.8021e-02]],\n\n [[ 2.0169e-02, -6.0347e-02, -1.0521e-03],\n [ 2.5924e-02, -5.6206e-02, 6.5026e-03],\n [-2.0685e-02, 2.1882e-03, -1.9963e-02]],\n\n [[ 1.4686e-02, 5.7862e-03, 1.9413e-02],\n [ 1.7594e-03, -1.8504e-02, 1.5308e-02],\n [-3.1177e-03, -1.0239e-02, 8.5477e-03]],\n\n ...,\n\n [[ 1.1689e-02, -1.0471e-02, 1.5848e-04],\n [-7.4754e-03, -2.9988e-03, -1.9241e-02],\n [-2.5043e-02, 2.5717e-02, -1.3893e-02]],\n\n [[-4.5696e-02, 5.3513e-03, 1.3826e-02],\n [-4.5029e-02, 3.7288e-02, 2.6907e-02],\n [ 2.2829e-03, 8.8339e-03, -1.6406e-03]],\n\n [[ 5.0289e-03, -7.4572e-03, -2.4854e-02],\n [ 5.4640e-03, -1.1388e-02, -1.4124e-02],\n [ 5.5445e-04, -2.2475e-02, -9.3963e-03]]],\n\n\n [[[ 2.0442e-02, -2.0819e-02, -2.2581e-02],\n [-4.5874e-03, 1.6361e-02, -2.1565e-02],\n [ 4.4645e-02, 7.4890e-02, -5.6215e-02]],\n\n [[-3.4184e-02, 6.2040e-02, -3.4064e-02],\n [-6.3313e-02, 5.9188e-02, -3.2582e-02],\n [-8.9040e-03, -8.7303e-03, 2.2145e-03]],\n\n [[ 2.9078e-02, -3.7087e-03, 1.3142e-02],\n [-2.3837e-03, 1.0650e-03, -1.9156e-03],\n [-4.0026e-03, -7.5471e-03, 6.5568e-03]],\n\n ...,\n\n [[-2.1618e-02, 2.9594e-02, 8.3285e-03],\n [-2.0943e-03, 2.6594e-02, -7.6814e-03],\n [-1.2647e-02, 1.6600e-02, 2.7199e-02]],\n\n [[ 3.3396e-03, -1.9423e-02, -1.3757e-02],\n [ 1.9568e-02, -1.1212e-02, -4.5999e-03],\n [ 8.7628e-03, -4.5991e-03, 2.6997e-02]],\n\n [[-1.8809e-02, 2.0605e-02, -2.9849e-02],\n [ 3.3727e-03, 3.1017e-02, 1.3556e-02],\n [ 1.2995e-02, -1.9762e-03, -2.8305e-02]]],\n\n\n [[[-1.9207e-02, 5.7370e-03, -1.4616e-02],\n [ 5.9200e-04, -2.6530e-02, -2.1831e-02],\n [ 2.1125e-02, 1.7346e-02, -1.0602e-02]],\n\n [[ 9.2735e-03, 2.0057e-02, 3.5328e-02],\n [ 1.1136e-03, -6.2119e-02, 2.8993e-02],\n [ 2.9400e-02, -1.4755e-02, -3.1238e-02]],\n\n [[ 1.0487e-02, 4.7015e-03, -7.4954e-03],\n [ 1.1426e-02, -1.2309e-02, -5.4363e-03],\n [-6.1924e-03, -5.5202e-03, -7.0194e-03]],\n\n ...,\n\n [[-1.8089e-02, 1.8519e-02, 5.3282e-02],\n [-6.9878e-02, -3.7934e-03, 3.7150e-02],\n [-5.4417e-02, -6.4499e-02, 3.6834e-02]],\n\n [[ 2.4436e-03, -1.5511e-02, -1.5835e-02],\n [-3.4701e-02, 2.7640e-02, -8.9997e-02],\n [-1.3123e-02, 1.8059e-02, -2.1808e-04]],\n\n [[ 3.8819e-03, 2.5822e-02, -5.4563e-04],\n [ 1.1856e-02, -3.3579e-03, 2.2341e-02],\n [-1.3174e-02, 2.2700e-02, -3.2637e-03]]],\n\n\n ...,\n\n\n [[[-5.6541e-02, -5.3897e-03, 6.3732e-03],\n [-3.6325e-02, -3.3721e-03, 1.5594e-02],\n [-4.1830e-02, -7.6691e-04, -3.4736e-03]],\n\n [[-1.0480e-02, -2.2847e-02, 9.1475e-03],\n [-1.8888e-02, -4.5372e-02, 3.7344e-02],\n [-1.7431e-02, -2.5286e-02, 5.1056e-03]],\n\n [[ 2.5095e-02, 6.0275e-03, 9.3693e-03],\n [ 1.8271e-02, 1.2439e-03, -7.4266e-03],\n [ 2.7186e-02, 1.0659e-03, -9.5035e-03]],\n\n ...,\n\n [[-4.5836e-02, -3.3009e-02, 2.6155e-02],\n [-6.5028e-02, -4.1277e-02, 5.9219e-02],\n [-5.7619e-02, 2.8284e-02, 3.6091e-02]],\n\n [[ 5.5307e-02, 8.3789e-03, 5.3433e-04],\n [-2.4793e-02, -3.3724e-02, -3.2138e-02],\n [-2.6715e-02, -4.1081e-03, -1.7914e-02]],\n\n [[-2.8638e-02, -3.0509e-02, -1.0485e-02],\n [-4.5317e-02, -4.0770e-02, 6.4762e-02],\n [-4.7202e-02, -8.7156e-03, 3.5465e-02]]],\n\n\n [[[ 6.3752e-03, -9.5922e-03, 2.9673e-02],\n [ 2.2557e-02, -1.5895e-02, -3.4312e-03],\n [-7.0504e-03, -5.9594e-03, 8.9822e-03]],\n\n [[-6.4543e-03, 1.0917e-02, -3.9537e-02],\n [-1.3702e-02, 1.3231e-02, -3.4895e-02],\n [ 2.9550e-02, 1.0728e-02, -2.4550e-02]],\n\n [[ 3.6876e-02, 8.8374e-03, 1.4390e-02],\n [ 3.0957e-03, 6.4355e-05, -7.8478e-04],\n [ 9.1762e-03, -1.3871e-03, 1.1173e-02]],\n\n ...,\n\n [[-2.7830e-02, 1.0722e-02, 5.1852e-02],\n [-4.0680e-02, 3.5330e-02, 1.3394e-02],\n [-4.5330e-02, 3.2405e-02, -1.8880e-02]],\n\n [[-2.8077e-02, -1.8826e-02, -9.0260e-03],\n [-1.6381e-02, 4.4983e-03, 5.6013e-02],\n [ 1.3599e-03, 3.0312e-02, 8.9452e-03]],\n\n [[ 1.6043e-03, -7.4751e-04, 3.0208e-02],\n [ 1.6531e-02, 4.2029e-03, -1.6718e-02],\n [ 3.7882e-02, -3.0835e-04, -2.6396e-02]]],\n\n\n [[[ 5.6268e-03, 1.7579e-02, 1.0264e-02],\n [ 2.5936e-02, -3.4520e-02, 1.9605e-02],\n [-4.4064e-02, 1.3716e-02, -6.4702e-03]],\n\n [[ 2.4093e-03, -1.0439e-02, -1.3151e-02],\n [ 2.6368e-02, 2.4726e-02, 2.7653e-02],\n [-1.2495e-02, -1.1718e-02, 4.2321e-02]],\n\n [[ 1.0402e-02, 8.9669e-04, 1.2938e-06],\n [ 8.5959e-03, 2.5796e-02, 9.1019e-03],\n [-2.4373e-03, -4.9715e-03, 6.4720e-03]],\n\n ...,\n\n [[-3.3398e-02, -1.0840e-03, 1.2298e-02],\n [ 2.3346e-02, -2.4025e-02, -4.8750e-02],\n [ 1.5565e-02, 4.7763e-02, -1.7171e-02]],\n\n [[-1.0394e-02, -2.1192e-02, -2.2472e-03],\n [ 1.3852e-02, -3.7495e-02, -1.7198e-02],\n [-5.6988e-03, 3.0873e-02, -1.7169e-02]],\n\n [[-1.3318e-02, 2.0536e-02, 2.4401e-03],\n [-2.0161e-02, 1.2215e-02, 5.5129e-03],\n [ 2.6314e-02, -1.2296e-02, -1.0042e-02]]]]), 'model.layer1.2.bn2.weight': tensor([0.2146, 0.2510, 0.2343, 0.2264, 0.2124, 0.2114, 0.2250, 0.1544, 0.2060,\n 0.2233, 0.2403, 0.3186, 0.2353, 0.2409, 0.2301, 0.2117, 0.2331, 0.1881,\n 0.2278, 0.2414, 0.2426, 0.2317, 0.2341, 0.2083, 0.2399, 0.2386, 0.2253,\n 0.2228, 0.2284, 0.2174, 0.2253, 0.2444, 0.1566, 0.2474, 0.1922, 0.2021,\n 0.2347, 0.1839, 0.1136, 0.2457, 0.2403, 0.1844, 0.2238, 0.1852, 0.2239,\n 0.2298, 0.2446, 0.2223, 0.2233, 0.2359, 0.2322, 0.2168, 0.2045, 0.2227,\n 0.2279, 0.2224, 0.2582, 0.1962, 0.2091, 0.1958, 0.2017, 0.2379, 0.2196,\n 0.2424]), 'model.layer1.2.bn2.bias': tensor([-0.0296, -0.0955, -0.0367, -0.0703, -0.1139, -0.1087, -0.0143, -0.0088,\n -0.1251, -0.0378, -0.0736, -0.3432, -0.0751, -0.0505, -0.0503, -0.0520,\n -0.0668, 0.0431, -0.0644, -0.0713, -0.0257, -0.1283, -0.0150, -0.0369,\n -0.1336, -0.0478, -0.0542, -0.0227, -0.0450, -0.0160, -0.0912, -0.1045,\n 0.0943, -0.0790, 0.0012, -0.0290, -0.1564, 0.1009, 0.2642, -0.1261,\n -0.0650, 0.0608, -0.0658, 0.0316, -0.0428, -0.0860, -0.0780, -0.0471,\n -0.0119, -0.1007, -0.0190, -0.0786, -0.0118, -0.0733, -0.0820, -0.1035,\n -0.0557, -0.1042, 0.0040, 0.0201, -0.1026, -0.0461, -0.0591, -0.0762]), 'model.layer1.2.bn2.running_mean': tensor([-0.0234, -0.0523, -0.0879, -0.0431, -0.1249, 0.0056, -0.0351, -0.1826,\n -0.0540, 0.0465, 0.0013, -0.0894, -0.0396, -0.0422, -0.0480, -0.0639,\n -0.0006, -0.0419, -0.0402, 0.0079, -0.0531, -0.1397, -0.0219, -0.0043,\n -0.0712, -0.0666, -0.0768, -0.0300, -0.0330, -0.0303, -0.0027, -0.0486,\n -0.0296, -0.0447, -0.0571, -0.0543, -0.2239, -0.0296, 0.0021, -0.0166,\n -0.0552, -0.1722, 0.0695, -0.0295, -0.0398, -0.0337, -0.0814, -0.0531,\n 0.0146, -0.0821, -0.0915, -0.0373, -0.0900, -0.0669, 0.0030, -0.0503,\n -0.0208, -0.0090, -0.0081, -0.0041, 0.2462, -0.0009, -0.0294, -0.1442]), 'model.layer1.2.bn2.running_var': tensor([0.0309, 0.0390, 0.0190, 0.0204, 0.0128, 0.0143, 0.0174, 0.0102, 0.0222,\n 0.0287, 0.0159, 0.0067, 0.0261, 0.0289, 0.0294, 0.0343, 0.0260, 0.0243,\n 0.0168, 0.0293, 0.0348, 0.0157, 0.0192, 0.0410, 0.0129, 0.0271, 0.0339,\n 0.0263, 0.0295, 0.0207, 0.0256, 0.0250, 0.0114, 0.0357, 0.0229, 0.0162,\n 0.0183, 0.0158, 0.0156, 0.0141, 0.0398, 0.0113, 0.0224, 0.0131, 0.0427,\n 0.0254, 0.0288, 0.0241, 0.0314, 0.0189, 0.0262, 0.0216, 0.0352, 0.0229,\n 0.0252, 0.0161, 0.0276, 0.0114, 0.0172, 0.0181, 0.0120, 0.0217, 0.0272,\n 0.0147]), 'model.layer1.2.bn2.num_batches_tracked': tensor(7160), 'model.layer1.2.conv3.weight': tensor([[[[ 0.0175]],\n\n [[-0.0042]],\n\n [[-0.0143]],\n\n ...,\n\n [[ 0.0034]],\n\n [[ 0.0030]],\n\n [[-0.0051]]],\n\n\n [[[-0.0093]],\n\n [[ 0.0006]],\n\n [[ 0.0248]],\n\n ...,\n\n [[-0.0057]],\n\n [[ 0.0096]],\n\n [[ 0.0047]]],\n\n\n [[[-0.0286]],\n\n [[-0.0211]],\n\n [[-0.0649]],\n\n ...,\n\n [[-0.0206]],\n\n [[-0.0045]],\n\n [[-0.1197]]],\n\n\n ...,\n\n\n [[[ 0.0014]],\n\n [[-0.0083]],\n\n [[-0.0031]],\n\n ...,\n\n [[ 0.0043]],\n\n [[ 0.0046]],\n\n [[ 0.0076]]],\n\n\n [[[ 0.0063]],\n\n [[ 0.0057]],\n\n [[-0.0046]],\n\n ...,\n\n [[-0.0037]],\n\n [[-0.0039]],\n\n [[-0.0089]]],\n\n\n [[[-0.0481]],\n\n [[-0.0316]],\n\n [[ 0.0078]],\n\n ...,\n\n [[ 0.0103]],\n\n [[-0.0290]],\n\n [[-0.0309]]]]), 'model.layer1.2.bn3.weight': tensor([-7.9061e-03, 5.6443e-03, 2.3692e-01, 8.5153e-03, 2.0445e-01,\n -2.6013e-04, 1.2285e-01, 5.4562e-02, -1.3231e-03, -7.9332e-03,\n -5.4981e-03, 1.5122e-01, 2.1842e-01, -6.4736e-03, 1.3454e-01,\n 1.2102e-01, 4.9490e-03, 7.7644e-02, 1.4477e-03, -3.1772e-03,\n 1.3920e-01, 7.6462e-02, 1.7796e-01, 1.1027e-01, 8.9125e-02,\n 2.2948e-01, 3.0182e-03, 5.7621e-02, 8.8442e-04, -5.3445e-04,\n 8.4693e-03, 4.0266e-03, -1.2186e-03, 4.4877e-02, 1.2447e-01,\n -8.2497e-03, 6.1093e-03, 2.0265e-03, 1.1032e-03, 1.8519e-03,\n 3.4888e-01, 1.2742e-02, 1.4456e-01, 2.3747e-03, -1.0081e-02,\n 2.2290e-01, 1.2056e-03, 1.8394e-01, 2.4637e-01, 1.9842e-01,\n -1.3978e-02, 3.8369e-02, 2.3497e-01, 1.8644e-01, -7.8722e-04,\n 6.1458e-03, 1.5126e-03, 1.1957e-01, 2.4609e-03, 9.1841e-04,\n 1.2677e-02, 1.1365e-02, -7.2085e-04, 4.7374e-03, 3.7796e-01,\n -2.4629e-03, 2.1925e-01, 1.6775e-02, 6.6614e-02, -9.5618e-03,\n 1.4803e-01, 2.5850e-01, 6.0105e-02, -1.4834e-04, -8.1057e-04,\n 9.7142e-02, 1.2764e-01, 1.5890e-02, -7.8795e-05, 4.8102e-02,\n 5.2028e-03, 3.2142e-04, 3.1561e-03, 2.2626e-01, 1.0359e-01,\n 1.4103e-01, 1.8648e-01, 2.5510e-01, -3.1030e-03, 2.4956e-01,\n 3.9111e-04, 8.3024e-02, 1.8270e-03, 2.9306e-01, 1.4814e-01,\n 5.8667e-02, -1.8520e-04, 1.4367e-01, -4.6262e-03, 6.2213e-02,\n 2.7636e-02, 2.8242e-01, 1.4407e-01, 1.2802e-02, 6.8429e-02,\n 9.1346e-02, 1.2945e-01, 2.1599e-01, -2.5401e-04, -3.5122e-03,\n -1.4103e-03, 3.2914e-04, -6.9216e-04, 9.5041e-03, 7.1184e-02,\n 6.9098e-02, 7.9200e-03, 1.8534e-01, 1.5258e-01, -4.3160e-02,\n 3.2466e-02, -1.0653e-01, 1.0444e-02, 3.4509e-01, 3.4017e-04,\n 1.1765e-03, 1.2303e-01, 3.4986e-01, 1.4540e-01, 9.8441e-02,\n 1.4132e-01, 6.4668e-02, 1.3374e-01, 2.3543e-01, 1.7349e-01,\n -1.6882e-02, 1.2730e-01, 1.9043e-01, 1.6002e-02, 2.0092e-01,\n 1.8513e-01, -1.6378e-03, 4.2235e-02, 1.4323e-01, 3.9377e-03,\n 2.5708e-03, 1.5485e-02, 3.9535e-02, 5.4859e-02, 1.0781e-01,\n 1.0147e-02, 1.5447e-01, 1.8393e-01, 1.3033e-01, -1.3087e-03,\n 1.1714e-01, 6.0829e-03, 1.1093e-01, 4.5805e-03, -3.7681e-04,\n -1.2940e-02, 5.8971e-02, 3.1544e-03, 1.1259e-02, 1.9653e-01,\n 4.6420e-03, 1.2140e-01, -5.3098e-04, 5.7000e-02, 2.2607e-01,\n 7.0886e-02, 1.3401e-02, 1.6665e-01, 2.1873e-01, 2.0178e-01,\n 1.7136e-01, 6.0457e-02, 1.4317e-03, 1.1927e-01, 1.3298e-01,\n 2.1441e-01, 1.1534e-04, 6.6713e-02, 6.9755e-02, 4.4704e-03,\n 1.7457e-01, -4.7377e-04, 7.1506e-02, 3.3824e-04, 1.3408e-03,\n 5.9386e-03, 1.4532e-03, 1.6331e-04, -2.8883e-02, 1.6177e-01,\n 1.5748e-04, 7.5724e-02, 1.8724e-02, -1.1784e-02, 1.7658e-01,\n 2.3141e-02, 3.4853e-02, 2.3237e-01, 5.7834e-03, 2.0709e-01,\n 1.6854e-04, 1.6537e-01, 9.9472e-02, 4.1001e-02, 3.0186e-02,\n 1.1640e-01, 2.2439e-01, 1.3118e-01, 5.8414e-02, 5.7984e-02,\n 7.9386e-03, 1.7897e-01, 1.4650e-01, 1.0743e-01, 1.0620e-01,\n 8.4672e-04, 1.7157e-01, 1.8666e-01, 1.2536e-03, -1.4706e-04,\n 5.8125e-02, 9.0597e-04, 1.5901e-02, 1.3940e-03, 7.9726e-02,\n 2.4442e-01, 3.5395e-04, 5.3247e-02, 3.7704e-03, -6.7319e-03,\n 3.6209e-03, 1.1762e-01, -4.9121e-03, 3.9990e-02, 6.2540e-03,\n 9.2913e-02, 3.7026e-02, 4.5717e-04, -2.2658e-03, 2.0600e-02,\n -1.6430e-03, 2.4358e-01, 1.0638e-01, 1.7499e-01, 1.5549e-01,\n -1.0265e-03, 3.9684e-04, 3.2404e-04, 8.8836e-04, -1.2897e-02,\n 1.8132e-01]), 'model.layer1.2.bn3.bias': tensor([-5.0311e-03, 7.3956e-03, -6.2343e-03, 1.1248e-02, -8.1609e-02,\n 1.3699e-02, -2.1312e-02, -3.6910e-02, -2.8452e-03, -1.6995e-02,\n 1.2517e-02, -1.1071e-01, 5.0009e-02, -2.8540e-03, -8.3488e-02,\n 6.3926e-02, 6.0387e-03, -3.6276e-02, -7.0424e-02, 6.0516e-03,\n -3.3101e-02, -3.1956e-02, -5.1223e-02, -5.2233e-02, -4.9959e-02,\n -5.5009e-02, -5.7198e-03, 9.1940e-02, 4.5005e-03, 4.8769e-03,\n -1.6497e-02, 5.6470e-03, 6.6523e-03, 4.5381e-03, -5.9155e-03,\n 1.9444e-03, 4.0149e-03, 1.0403e-02, 7.7603e-03, -5.0509e-03,\n -2.4055e-02, 1.5505e-02, -1.2031e-01, 8.1998e-03, 1.2623e-04,\n 2.2452e-02, 7.2972e-03, -7.4154e-02, 4.2061e-04, 7.3855e-02,\n 8.4472e-04, 5.1382e-02, 1.3580e-01, -1.0091e-01, 7.6563e-03,\n 1.2495e-02, 6.2536e-03, 1.6549e-03, -6.7495e-03, 1.2580e-02,\n 1.5777e-03, -3.5085e-03, 3.8130e-03, 8.6525e-03, -3.0308e-02,\n 8.7376e-03, 1.9313e-02, 2.2251e-04, -9.7078e-02, 3.2097e-03,\n -4.4147e-02, 6.9577e-02, -4.1076e-03, 4.1993e-03, -2.3576e-03,\n -5.0395e-03, 1.5232e-01, -5.9040e-02, 9.2140e-04, -5.8507e-02,\n 3.3296e-03, 2.2580e-03, 1.2933e-02, 5.5897e-02, 5.4416e-02,\n 1.0453e-01, -4.6101e-02, 6.7890e-02, 1.0593e-02, 1.2681e-01,\n 6.4946e-03, -7.4916e-02, 5.4290e-03, -7.0334e-03, -1.0633e-01,\n -3.9848e-02, 4.6243e-03, -1.6778e-01, 4.3293e-03, 4.4100e-02,\n -1.4935e-02, 6.6078e-02, -1.1662e-01, 2.3919e-03, -5.1280e-02,\n -6.5178e-02, -2.3782e-02, 1.6918e-01, 7.1367e-03, 8.1535e-03,\n 4.7231e-03, 5.6430e-03, 6.1279e-03, 6.9210e-03, -1.2423e-01,\n -3.3309e-02, 1.3368e-02, 7.2205e-02, -5.5232e-02, 1.7107e-02,\n -4.7864e-02, -1.5260e-01, -1.0324e-03, 3.3114e-02, -7.8861e-03,\n 9.3471e-03, -1.2901e-01, 4.0645e-03, 1.7512e-01, -1.9375e-02,\n -1.3282e-01, -4.8944e-02, -1.8644e-02, -7.2960e-02, 1.4194e-01,\n -2.2631e-02, -2.5402e-02, 8.7248e-02, 1.0429e-02, 1.1704e-01,\n 1.6668e-02, 7.1017e-04, -5.1588e-02, -5.6461e-02, -4.0510e-02,\n 5.3741e-03, -5.3622e-03, -8.3569e-03, -7.1416e-02, 4.9305e-02,\n -4.9111e-03, -7.0523e-02, -7.4007e-02, 8.7457e-02, 9.1261e-03,\n -1.3749e-01, -1.1624e-03, -1.1204e-01, 4.5202e-03, 1.2525e-02,\n -6.5043e-03, -3.7100e-02, 2.2823e-03, 7.9974e-03, -4.7599e-02,\n -4.6034e-03, -1.5726e-01, 1.1114e-02, -5.3859e-02, -8.4106e-02,\n 4.8260e-02, 1.1174e-02, -1.2250e-01, -2.0554e-02, -1.1852e-02,\n 3.6319e-02, -6.6985e-02, 4.9237e-03, -8.0108e-02, -6.6195e-02,\n -7.4444e-02, -1.1837e-02, -7.3043e-02, -1.0358e-01, 5.8118e-03,\n 1.9970e-01, 1.7310e-03, 5.0495e-02, 3.1543e-03, 3.3405e-03,\n 9.1178e-03, 1.2488e-02, 2.7040e-03, -2.2796e-02, 9.2585e-02,\n 2.9183e-03, -7.0811e-02, 1.1822e-02, 6.5234e-03, -1.5377e-04,\n -2.7187e-03, -9.2866e-03, 1.3014e-01, 1.1727e-02, -7.3055e-02,\n 6.1087e-03, -4.6476e-02, 1.5420e-01, -4.8073e-02, 2.4421e-02,\n -6.3959e-02, 7.9421e-02, -5.3858e-02, 1.1425e-02, -1.0674e-01,\n 4.8188e-03, -7.7812e-02, -1.0879e-01, -6.8289e-02, -3.6993e-02,\n 2.9533e-03, -1.1338e-01, 2.3992e-02, 1.5772e-03, 4.5480e-03,\n -7.1925e-02, 6.7846e-03, -9.0350e-03, 1.1996e-03, 1.7780e-02,\n -1.2558e-01, 3.4264e-03, -1.5579e-02, -2.5444e-03, 1.2455e-02,\n 5.0313e-03, -1.6538e-01, 7.2891e-03, -3.9540e-02, -3.4028e-02,\n -1.6584e-02, 1.0451e-02, 5.9282e-03, 1.8190e-02, -5.2883e-02,\n 4.3035e-03, 1.0111e-02, -1.4420e-01, 2.5377e-02, -5.0836e-02,\n 7.8502e-03, -1.3426e-02, -5.9101e-03, 9.2283e-03, 2.7188e-03,\n -1.5074e-01]), 'model.layer1.2.bn3.running_mean': tensor([-6.5600e-03, 1.6597e-03, -9.8625e-02, -5.5417e-03, 5.3145e-02,\n 2.9978e-03, -2.8756e-02, -2.3361e-02, -5.9611e-03, 8.7601e-03,\n -6.0263e-03, -8.4720e-03, -5.8553e-02, 4.8203e-03, -5.6160e-02,\n 3.7889e-02, 5.5653e-04, -4.0768e-02, -8.1709e-04, -8.2491e-03,\n -3.2728e-02, -1.2979e-02, 1.4226e-02, 8.1089e-03, -4.8075e-02,\n -1.5475e-02, 4.0986e-03, -7.2311e-03, -1.3811e-03, -2.8367e-03,\n -6.0409e-03, -5.0952e-03, -5.3053e-05, 6.3575e-03, 3.6235e-02,\n -5.6361e-03, 3.6508e-03, -4.8601e-03, -5.4545e-03, -4.6564e-04,\n -4.8303e-02, 5.2674e-03, -4.9893e-02, -3.6259e-03, 5.7940e-04,\n -1.6141e-02, -5.6964e-04, -5.0257e-03, -1.1696e-02, 6.2715e-02,\n 1.9346e-03, 2.3732e-03, -6.8814e-02, -2.1473e-02, 1.2412e-03,\n -1.1897e-05, 1.0883e-03, -1.8558e-02, -7.3780e-03, -4.2219e-03,\n -1.4147e-02, -7.8114e-03, -2.0772e-03, 6.4873e-03, -1.3952e-01,\n 4.8267e-04, 2.6810e-02, -8.0424e-03, 2.0626e-02, 6.8923e-03,\n -5.2295e-02, -1.4992e-02, -6.9808e-02, 4.9690e-04, -2.3558e-04,\n -1.9115e-02, -3.0256e-02, 1.2390e-02, 1.9394e-03, 3.2004e-03,\n -5.1184e-03, 4.6883e-03, -6.0055e-03, -7.1172e-02, 3.5745e-02,\n -2.1556e-02, -1.8581e-02, -7.0488e-02, -5.6128e-05, 3.0861e-02,\n 7.9505e-03, -2.3743e-02, -2.9092e-03, -3.7493e-02, -1.1108e-02,\n 2.5881e-02, 1.4460e-03, 3.4766e-02, -5.8454e-03, -2.4897e-02,\n 1.2065e-02, -4.5622e-03, -4.2037e-02, 4.7941e-03, -1.0682e-02,\n -3.7932e-02, 2.7232e-02, -8.4084e-02, 6.8239e-04, -4.4356e-03,\n 4.3116e-03, 7.8970e-04, -9.2248e-03, 6.2398e-03, -1.2924e-02,\n -4.8350e-02, 1.1242e-03, -6.5077e-02, -5.0379e-02, -8.7913e-05,\n -9.5511e-03, -1.4787e-02, 1.1662e-02, -7.7249e-02, -3.7237e-04,\n 8.0572e-03, 1.1954e-02, -7.8838e-02, -1.7646e-02, -6.9774e-02,\n -6.9620e-02, -1.0836e-02, -4.0954e-02, -2.6809e-02, -4.5070e-02,\n -2.3662e-03, -5.4094e-02, 6.4801e-02, -2.7790e-03, -6.2203e-02,\n 2.9339e-02, 7.8541e-05, -2.1160e-02, -1.2922e-02, 6.5825e-03,\n -9.2531e-04, -4.4151e-03, -3.3948e-02, 3.1373e-02, 2.3220e-02,\n -2.1457e-03, 4.3349e-02, 4.6457e-02, 4.2672e-04, -1.9152e-03,\n -2.1196e-02, -3.7092e-03, -1.8133e-03, -6.2517e-03, -8.5368e-03,\n 5.1657e-03, -4.7731e-02, 7.6458e-03, -6.3121e-04, 1.8002e-02,\n 9.4180e-04, 2.4520e-02, -2.1162e-03, -2.4491e-02, -4.8786e-02,\n 8.7492e-03, -1.6741e-03, 1.6156e-02, 2.0466e-02, 1.4603e-02,\n -3.2394e-02, -3.5021e-02, 7.7743e-04, -3.5215e-03, -2.8562e-02,\n -6.0929e-02, -5.1667e-04, -3.2971e-02, 1.7670e-03, -1.9889e-03,\n 2.2350e-04, -7.6170e-04, 1.2073e-02, -3.0113e-04, -7.0470e-03,\n -2.9749e-03, -2.9785e-03, -3.7239e-03, 1.3426e-02, 3.1431e-04,\n 3.8400e-03, -1.9400e-02, -1.0541e-02, 6.7089e-03, 2.7891e-02,\n -3.3864e-03, -2.0024e-02, -3.2654e-02, 3.4689e-03, 2.6066e-02,\n 2.2200e-03, -1.8993e-02, -1.0987e-02, -2.4582e-03, -1.0934e-02,\n -2.5449e-02, -7.5787e-02, -7.3369e-03, -1.3497e-02, -1.3956e-02,\n 3.7684e-03, -1.1508e-02, -4.9302e-02, 5.5434e-03, -3.3495e-02,\n -8.1630e-03, -1.5429e-02, 2.8306e-02, 6.9035e-03, 5.2427e-03,\n -6.1003e-03, -7.0778e-03, -8.2524e-03, -7.2416e-03, -2.5507e-02,\n 2.7205e-02, 6.6192e-03, -6.0923e-02, -6.9713e-04, -1.3364e-02,\n -2.9859e-03, -2.2021e-02, -8.5086e-03, -1.1600e-02, -2.8204e-03,\n 3.7002e-03, 8.6208e-03, 5.2478e-03, -5.0893e-03, -1.4167e-02,\n -2.6712e-03, -6.6891e-03, -1.6009e-02, -6.5498e-03, 1.6719e-03,\n -2.8836e-03, -6.8487e-03, 7.6145e-04, -8.2335e-03, -1.6094e-04,\n -6.0876e-02]), 'model.layer1.2.bn3.running_var': tensor([2.6864e-04, 6.4563e-04, 2.5092e-03, 2.3332e-04, 1.7956e-03, 2.9989e-04,\n 2.2301e-03, 1.0951e-03, 3.5911e-04, 2.8494e-04, 2.8714e-04, 1.4712e-03,\n 3.5758e-03, 3.5436e-04, 1.9810e-03, 1.7183e-03, 1.6082e-04, 1.7187e-03,\n 1.0983e-04, 3.6914e-04, 1.3179e-03, 5.4514e-04, 2.0081e-03, 1.1093e-03,\n 1.3373e-03, 1.5947e-03, 2.2513e-04, 6.0339e-04, 2.3107e-04, 1.7261e-04,\n 1.8166e-04, 2.4137e-04, 2.1633e-04, 5.1411e-04, 1.3861e-03, 1.7617e-04,\n 2.3080e-04, 2.4250e-04, 5.9472e-04, 3.6263e-04, 5.4769e-03, 4.3273e-04,\n 1.3991e-03, 2.2891e-04, 1.3446e-04, 1.9410e-03, 1.6321e-04, 1.5755e-03,\n 2.6945e-03, 3.5462e-03, 2.6272e-04, 7.6203e-04, 2.3207e-03, 1.3743e-03,\n 1.9922e-04, 1.9933e-04, 1.8906e-04, 1.0447e-03, 2.0073e-04, 1.7528e-04,\n 2.2546e-04, 2.1856e-04, 1.6202e-04, 1.3097e-04, 3.3887e-03, 5.0899e-04,\n 2.8662e-03, 2.4837e-04, 3.9476e-04, 2.2300e-04, 1.2115e-03, 3.6674e-03,\n 1.1222e-03, 5.7939e-04, 2.3345e-04, 9.3906e-04, 2.4571e-03, 2.0656e-04,\n 1.4515e-04, 3.6171e-04, 1.7211e-04, 2.2525e-04, 2.3561e-04, 2.4045e-03,\n 1.2536e-03, 2.6014e-03, 1.9363e-03, 3.2939e-03, 3.0258e-04, 2.8534e-03,\n 8.8682e-04, 4.8644e-04, 2.5276e-04, 2.8449e-03, 1.3861e-03, 6.1859e-04,\n 2.2191e-04, 1.0939e-03, 1.3702e-04, 8.2984e-04, 3.9299e-04, 3.8932e-03,\n 1.6894e-03, 1.2413e-04, 7.7470e-04, 1.1589e-03, 1.5831e-03, 2.8388e-03,\n 1.9997e-04, 2.6661e-04, 4.8838e-04, 1.3667e-04, 3.1330e-04, 3.0252e-04,\n 5.3514e-04, 1.1275e-03, 3.2526e-04, 1.5455e-03, 3.2946e-03, 7.2435e-04,\n 5.1462e-04, 6.7410e-04, 2.3015e-04, 4.1799e-03, 2.1519e-04, 1.7821e-04,\n 1.0794e-03, 4.2041e-03, 2.3429e-03, 1.6338e-03, 3.1754e-03, 6.0333e-04,\n 2.0412e-03, 2.2073e-03, 2.1735e-03, 1.7809e-04, 1.1902e-03, 2.1764e-03,\n 2.1401e-04, 1.6724e-03, 1.5989e-03, 1.5942e-04, 6.0315e-04, 9.8068e-04,\n 1.7159e-04, 1.8983e-04, 2.5833e-04, 6.6113e-04, 5.4013e-04, 8.5024e-04,\n 2.7632e-04, 1.8676e-03, 2.1654e-03, 1.3840e-03, 1.2073e-04, 8.6902e-04,\n 1.9702e-04, 1.0314e-03, 1.7774e-04, 2.0875e-04, 2.1892e-04, 1.1695e-03,\n 1.6152e-04, 5.8988e-04, 1.2168e-03, 1.1820e-04, 1.0559e-03, 2.4292e-04,\n 1.0516e-03, 3.4653e-03, 1.2218e-03, 1.6232e-04, 1.3144e-03, 1.7406e-03,\n 1.3547e-03, 1.6528e-03, 6.7553e-04, 2.9827e-04, 9.0946e-04, 1.3978e-03,\n 1.9373e-03, 1.4320e-04, 5.9212e-04, 8.9718e-04, 2.4691e-04, 2.1513e-03,\n 2.0882e-04, 1.5114e-03, 1.4684e-04, 8.0947e-04, 2.9456e-04, 2.1365e-04,\n 5.7923e-04, 2.8512e-04, 1.7948e-03, 1.5025e-04, 1.1285e-03, 3.6489e-04,\n 1.2567e-04, 2.6468e-03, 2.9878e-04, 6.3771e-04, 2.6221e-03, 2.8260e-04,\n 2.3085e-03, 1.6497e-04, 1.5353e-03, 1.4133e-03, 3.5474e-04, 4.9659e-04,\n 1.4953e-03, 2.1713e-03, 9.2890e-04, 7.9060e-04, 2.8890e-04, 1.8102e-04,\n 1.2668e-03, 1.3522e-03, 1.0770e-03, 1.1422e-03, 1.4534e-03, 2.2690e-03,\n 1.9773e-03, 5.1935e-04, 9.2491e-05, 6.7682e-04, 5.4096e-04, 1.0883e-04,\n 4.0372e-04, 1.0118e-03, 2.6733e-03, 2.5352e-04, 6.9864e-04, 2.0290e-04,\n 1.7490e-04, 1.6640e-04, 1.1588e-03, 1.8594e-03, 2.3796e-04, 9.6199e-05,\n 6.9335e-04, 1.7999e-04, 5.2831e-04, 1.9358e-04, 3.8922e-04, 1.6260e-04,\n 3.3556e-03, 9.2080e-04, 1.8124e-03, 1.6947e-03, 1.6223e-04, 6.0433e-04,\n 3.7711e-04, 4.2880e-04, 4.1119e-04, 2.2263e-03]), 'model.layer1.2.bn3.num_batches_tracked': tensor(7160), 'model.layer2.0.conv1.weight': tensor([[[[ 0.0115]],\n\n [[ 0.0125]],\n\n [[ 0.0220]],\n\n ...,\n\n [[ 0.0144]],\n\n [[-0.0319]],\n\n [[-0.0027]]],\n\n\n [[[ 0.0161]],\n\n [[ 0.0141]],\n\n [[-0.0299]],\n\n ...,\n\n [[ 0.0129]],\n\n [[-0.0155]],\n\n [[-0.0779]]],\n\n\n [[[ 0.0290]],\n\n [[ 0.0057]],\n\n [[-0.0688]],\n\n ...,\n\n [[ 0.0095]],\n\n [[-0.0174]],\n\n [[-0.0012]]],\n\n\n ...,\n\n\n [[[-0.0080]],\n\n [[-0.0007]],\n\n [[ 0.0010]],\n\n ...,\n\n [[ 0.0082]],\n\n [[ 0.0157]],\n\n [[ 0.0086]]],\n\n\n [[[-0.0058]],\n\n [[-0.0060]],\n\n [[ 0.1278]],\n\n ...,\n\n [[-0.0092]],\n\n [[-0.0149]],\n\n [[ 0.0552]]],\n\n\n [[[ 0.0173]],\n\n [[ 0.0050]],\n\n [[-0.0124]],\n\n ...,\n\n [[ 0.0130]],\n\n [[ 0.0246]],\n\n [[-0.0604]]]]), 'model.layer2.0.bn1.weight': tensor([0.2607, 0.1859, 0.2010, 0.1921, 0.2007, 0.2148, 0.2177, 0.1763, 0.1761,\n 0.1746, 0.2401, 0.1540, 0.1933, 0.2542, 0.1961, 0.2117, 0.1919, 0.1515,\n 0.2132, 0.1365, 0.2081, 0.1708, 0.2436, 0.1701, 0.2584, 0.1279, 0.2286,\n 0.1500, 0.3144, 0.2455, 0.1815, 0.1723, 0.1646, 0.1837, 0.2321, 0.1929,\n 0.1665, 0.2016, 0.3596, 0.1878, 0.2369, 0.1534, 0.2426, 0.1501, 0.1735,\n 0.2231, 0.1891, 0.1816, 0.1397, 0.2411, 0.2026, 0.2460, 0.1914, 0.2082,\n 0.1036, 0.1806, 0.2234, 0.2295, 0.1904, 0.1872, 0.2257, 0.2043, 0.2181,\n 0.2203, 0.2140, 0.2118, 0.2563, 0.1242, 0.1833, 0.1800, 0.2307, 0.1975,\n 0.2015, 0.2195, 0.1756, 0.2110, 0.2174, 0.2170, 0.2475, 0.1538, 0.1554,\n 0.1989, 0.2124, 0.1976, 0.2095, 0.2640, 0.1997, 0.1649, 0.2135, 0.2979,\n 0.1864, 0.1895, 0.1611, 0.2231, 0.2003, 0.2259, 0.2083, 0.2389, 0.2064,\n 0.2338, 0.1483, 0.2161, 0.1922, 0.2200, 0.2181, 0.1810, 0.2304, 0.1817,\n 0.2462, 0.2235, 0.1964, 0.1711, 0.2251, 0.2003, 0.2221, 0.2047, 0.2346,\n 0.2046, 0.2277, 0.2236, 0.2865, 0.2127, 0.1785, 0.1446, 0.2121, 0.2522,\n 0.1903, 0.2941]), 'model.layer2.0.bn1.bias': tensor([-0.1608, -0.0983, -0.1869, -0.1083, -0.0293, -0.1178, -0.0786, -0.1067,\n -0.0674, 0.0922, -0.1658, 0.0642, -0.2100, -0.1573, -0.1038, -0.0239,\n -0.0863, 0.0889, -0.0728, 0.0628, -0.0224, 0.0419, -0.1920, 0.0805,\n -0.1478, 0.1243, -0.1262, 0.1188, -0.1294, -0.1734, 0.0679, 0.0388,\n -0.0322, 0.0233, -0.1350, 0.0537, 0.0887, -0.0803, -0.1931, 0.0927,\n -0.0892, 0.0809, -0.1366, 0.1024, 0.1000, -0.1399, 0.0438, 0.0260,\n 0.0939, -0.1644, -0.0846, -0.0944, -0.1312, -0.1802, -0.1077, -0.0312,\n -0.0866, -0.0752, -0.0918, -0.0093, -0.0690, -0.1069, -0.1090, -0.1680,\n -0.1019, -0.0901, -0.2639, 0.0437, -0.1403, 0.0659, -0.1843, 0.0631,\n -0.0296, -0.0696, 0.0643, -0.0617, -0.0320, -0.1183, -0.1832, 0.0454,\n 0.0273, -0.0967, -0.1374, -0.0638, -0.0596, -0.1637, -0.1146, 0.0054,\n -0.1093, -0.2504, -0.0193, -0.0150, -0.1584, 0.0264, 0.0262, -0.1180,\n -0.1031, -0.1370, -0.0889, -0.2309, 0.0303, -0.0908, -0.0342, -0.0112,\n -0.1383, 0.0059, -0.0974, 0.1191, -0.2095, -0.1430, -0.1647, 0.0215,\n -0.1809, -0.0731, -0.1482, -0.0568, -0.1355, -0.1398, -0.0905, -0.1104,\n -0.3018, -0.2258, -0.1313, 0.0419, -0.1234, -0.1522, 0.0265, -0.2530]), 'model.layer2.0.bn1.running_mean': tensor([-0.1239, -0.0606, -0.1473, -0.0308, 0.1471, 0.0177, -0.2035, -0.2068,\n -0.0036, 0.1490, -0.0602, -0.1110, 0.0318, -0.0154, -0.2234, -0.1234,\n -0.1841, -0.0748, -0.1762, 0.0082, -0.2599, -0.0466, 0.0735, 0.0722,\n 0.3805, -0.2792, 0.0740, 0.0332, -0.0249, 0.1215, 0.0851, -0.2312,\n -0.1162, 0.1010, -0.0872, -0.1797, -0.0372, -0.0534, -0.0489, 0.0291,\n -0.1073, -0.0109, -0.2104, -0.0458, 0.0885, -0.0831, -0.0256, -0.0743,\n -0.0333, 0.1440, -0.1640, -0.0200, -0.2911, 0.1060, 0.1763, -0.1191,\n -0.3886, -0.0609, -0.1177, -0.1609, -0.0614, -0.1312, 0.0918, -0.3072,\n -0.1151, -0.2065, -0.2502, -0.0353, -0.0730, -0.0055, -0.0669, 0.0301,\n 0.0256, -0.1682, 0.0354, -0.0750, -0.2876, -0.1029, 0.1089, -0.0915,\n 0.0398, -0.3402, -0.0855, -0.2242, 0.0358, 0.0119, -0.1827, -0.0868,\n -0.2870, -0.0840, -0.2299, 0.0296, 0.1784, 0.0335, -0.0731, -0.1450,\n -0.2459, -0.1242, 0.0369, -0.3310, -0.0640, -0.1392, -0.1944, -0.1892,\n -0.4376, 0.1309, -0.0931, 0.0106, -0.2462, -0.2257, -0.0769, -0.0504,\n -0.0135, -0.3751, -0.2797, -0.1293, -0.0918, -0.1641, -0.1011, -0.1012,\n -0.3538, -0.1977, -0.0520, 0.0645, -0.2053, -0.0460, -0.0086, -0.0878]), 'model.layer2.0.bn1.running_var': tensor([0.0540, 0.0217, 0.0243, 0.0212, 0.0353, 0.0178, 0.0326, 0.0149, 0.0246,\n 0.0232, 0.0300, 0.0173, 0.0079, 0.0246, 0.0214, 0.0423, 0.0157, 0.0252,\n 0.0461, 0.0165, 0.0401, 0.0199, 0.0333, 0.0311, 0.0353, 0.0303, 0.0345,\n 0.0289, 0.1219, 0.0208, 0.0297, 0.0187, 0.0360, 0.0604, 0.0225, 0.0385,\n 0.0322, 0.0304, 0.1195, 0.0643, 0.0484, 0.0401, 0.0381, 0.0194, 0.0532,\n 0.0192, 0.0176, 0.0301, 0.0216, 0.0307, 0.0229, 0.0361, 0.0192, 0.0108,\n 0.0054, 0.0462, 0.0459, 0.0590, 0.0374, 0.0306, 0.0495, 0.0249, 0.0308,\n 0.0167, 0.0399, 0.0381, 0.0330, 0.0210, 0.0123, 0.0293, 0.0286, 0.0565,\n 0.0373, 0.0397, 0.0398, 0.0273, 0.0225, 0.0304, 0.0312, 0.0159, 0.0385,\n 0.0389, 0.0335, 0.0445, 0.0283, 0.0353, 0.0291, 0.0177, 0.0368, 0.0225,\n 0.0171, 0.0363, 0.0070, 0.0531, 0.0475, 0.0566, 0.0317, 0.0224, 0.0249,\n 0.0204, 0.0230, 0.0293, 0.0244, 0.0496, 0.0387, 0.0481, 0.0684, 0.0335,\n 0.0216, 0.0264, 0.0116, 0.0477, 0.0175, 0.0266, 0.0397, 0.0293, 0.0645,\n 0.0220, 0.0317, 0.0269, 0.0328, 0.0174, 0.0122, 0.0223, 0.0406, 0.0317,\n 0.0310, 0.0407]), 'model.layer2.0.bn1.num_batches_tracked': tensor(7160), 'model.layer2.0.conv2.weight': tensor([[[[ 6.9168e-03, 6.0124e-03, 7.2581e-03],\n [ 3.4109e-03, 2.3616e-02, 2.1131e-03],\n [ 7.0380e-03, 1.9455e-02, 2.8738e-02]],\n\n [[-5.2995e-03, -2.0900e-02, -1.7880e-02],\n [ 1.6417e-03, 1.3684e-02, -7.2457e-04],\n [ 1.5399e-02, 1.4031e-02, 3.0630e-02]],\n\n [[ 8.9723e-03, -7.2626e-03, 2.0563e-03],\n [ 4.9210e-03, 3.4447e-03, -2.6109e-03],\n [ 1.7937e-02, 8.7013e-03, 8.5071e-03]],\n\n ...,\n\n [[-1.2321e-02, -1.3010e-02, -2.3341e-02],\n [-5.0884e-03, 3.9776e-04, -9.9807e-03],\n [ 3.4223e-03, -1.6830e-02, 1.7548e-02]],\n\n [[-5.1792e-02, -3.6824e-02, -2.3242e-02],\n [-3.2806e-02, -1.6044e-02, -2.0215e-02],\n [-3.1183e-02, -8.7157e-03, 1.6576e-02]],\n\n [[ 1.4615e-03, -8.1917e-05, -1.5195e-02],\n [ 7.6193e-03, 1.2358e-02, -2.0830e-02],\n [-2.0528e-02, -3.3036e-02, -2.2820e-02]]],\n\n\n [[[ 3.1364e-02, 1.5977e-02, 7.3294e-03],\n [ 1.1623e-02, 2.9759e-02, 2.5526e-02],\n [ 8.9961e-03, 2.5159e-02, 4.7256e-03]],\n\n [[ 5.5576e-03, 1.1506e-02, -1.8812e-02],\n [-1.2458e-02, 1.7566e-03, -1.0760e-03],\n [ 7.6758e-03, 6.7713e-03, -1.3550e-02]],\n\n [[-1.0409e-02, -1.5955e-02, 1.9369e-02],\n [-1.7607e-02, 1.3320e-02, 1.8161e-02],\n [-2.5506e-02, 3.2722e-03, 1.4223e-02]],\n\n ...,\n\n [[-1.2300e-03, -2.8931e-02, -3.3150e-02],\n [-2.5555e-02, -2.4103e-02, -2.8201e-02],\n [-2.2441e-02, -1.1374e-02, -1.1866e-02]],\n\n [[ 2.5213e-02, 4.2874e-02, 3.2649e-02],\n [ 2.0610e-02, -5.0971e-03, 2.5588e-02],\n [ 2.9987e-02, 4.9249e-02, 3.7965e-02]],\n\n [[ 2.0820e-02, 2.0771e-02, -8.7333e-03],\n [ 1.5728e-02, 4.7151e-02, 1.8586e-02],\n [ 1.1309e-02, 3.4455e-02, 1.7418e-02]]],\n\n\n [[[ 1.2227e-02, -9.6754e-03, -4.1864e-02],\n [ 1.8257e-02, 4.6623e-03, -2.9804e-02],\n [ 1.2608e-02, -9.8799e-03, -3.9089e-02]],\n\n [[-1.8439e-02, -1.4471e-02, 1.7391e-02],\n [-7.4081e-04, 1.8495e-03, -6.4943e-03],\n [-5.8632e-04, -7.9632e-03, -1.1863e-03]],\n\n [[-1.2130e-02, 1.8550e-02, 3.9605e-02],\n [-2.5508e-02, 1.2627e-02, 3.5600e-02],\n [-2.9737e-02, -1.4700e-02, 1.9359e-02]],\n\n ...,\n\n [[-1.2773e-02, -4.6814e-03, 7.7809e-03],\n [ 2.3805e-02, -6.2465e-03, 1.0715e-02],\n [-1.2798e-03, -2.0953e-02, 5.7496e-03]],\n\n [[ 5.1240e-02, 4.7005e-02, 1.2931e-02],\n [ 2.4174e-02, 9.9326e-03, 7.3686e-03],\n [ 7.7504e-03, 3.1407e-02, 2.4152e-03]],\n\n [[-1.7258e-02, -1.5668e-02, -3.5679e-02],\n [-3.5871e-03, -1.5856e-03, -5.0341e-02],\n [-1.8034e-02, -2.0462e-02, -4.4504e-02]]],\n\n\n ...,\n\n\n [[[-1.1409e-02, -2.5789e-02, -2.0874e-02],\n [-2.3106e-02, 5.7798e-04, -3.1347e-02],\n [-1.7374e-02, -3.0979e-02, -4.5451e-02]],\n\n [[-7.3907e-03, -8.2560e-03, -7.8785e-03],\n [-5.4224e-04, 3.6777e-03, -1.2417e-02],\n [-1.1758e-02, -1.4145e-02, -2.4272e-02]],\n\n [[-3.1376e-02, -1.9850e-02, 1.0617e-02],\n [-3.4972e-02, -1.8478e-02, 3.0636e-02],\n [ 7.7072e-03, 1.7517e-02, 6.4302e-02]],\n\n ...,\n\n [[-1.6030e-02, 5.5710e-03, 3.1158e-03],\n [ 1.1375e-02, -3.2733e-03, 3.2397e-03],\n [ 2.7894e-03, -1.1574e-02, -2.2190e-02]],\n\n [[-6.0425e-03, 3.0529e-02, 1.8353e-02],\n [-8.5483e-03, 1.5013e-02, 8.4444e-03],\n [-3.6726e-02, -1.3993e-02, -1.9764e-02]],\n\n [[-1.0216e-02, -5.3996e-03, -1.1715e-02],\n [-1.6047e-03, 4.0247e-04, -1.3775e-02],\n [-3.1403e-03, -1.0091e-02, -1.5260e-02]]],\n\n\n [[[ 1.2243e-02, 3.9953e-03, -2.8384e-02],\n [ 1.6756e-02, -2.2114e-03, 3.3715e-03],\n [-1.7652e-02, 2.5144e-03, 1.8340e-02]],\n\n [[ 1.0028e-03, -6.7814e-03, 3.5964e-02],\n [-2.2472e-02, 2.8155e-03, 2.5371e-02],\n [-1.6687e-02, -1.9749e-03, -1.7783e-02]],\n\n [[-5.0492e-03, 1.0221e-02, 6.9792e-03],\n [ 8.3911e-03, 1.4930e-03, -3.3210e-03],\n [ 9.4828e-03, 4.6928e-03, -3.7848e-03]],\n\n ...,\n\n [[ 4.5604e-03, 3.5710e-03, 1.6761e-02],\n [-4.0118e-04, -2.0628e-03, -5.7992e-03],\n [-1.2118e-02, 2.7178e-02, -2.1269e-02]],\n\n [[ 4.0919e-02, -8.8907e-03, -2.3504e-02],\n [ 8.1058e-03, -5.7943e-03, -3.1722e-02],\n [ 2.4379e-02, -2.3327e-02, 1.7741e-02]],\n\n [[-1.5084e-02, -1.2485e-02, -1.8112e-02],\n [-2.0355e-02, -2.0287e-02, 1.1061e-02],\n [-2.2897e-02, -1.1918e-02, 1.3194e-03]]],\n\n\n [[[-2.7470e-02, -3.4897e-02, 8.0972e-03],\n [-1.3457e-02, -1.8333e-02, -1.8038e-02],\n [-2.6980e-02, -2.2258e-02, -3.1595e-02]],\n\n [[ 1.2637e-02, 1.9370e-02, 2.1781e-02],\n [ 3.1733e-02, 1.2722e-02, 3.1147e-02],\n [-8.4746e-04, 2.0278e-02, 1.6848e-02]],\n\n [[-2.4709e-03, -1.6890e-02, -3.3594e-03],\n [ 2.1978e-02, -6.0085e-03, -1.3348e-02],\n [ 7.0362e-03, 3.8039e-02, 1.8817e-02]],\n\n ...,\n\n [[ 3.1038e-02, -5.8873e-04, -1.1846e-02],\n [ 2.3978e-02, 1.9876e-02, -1.3144e-02],\n [-1.0316e-02, 1.5720e-02, 4.5532e-03]],\n\n [[-1.5406e-03, 2.5970e-02, 2.4279e-02],\n [-2.1069e-02, 2.2888e-02, -8.6526e-03],\n [ 1.5454e-02, -2.4635e-02, -2.5354e-02]],\n\n [[-2.1221e-02, -1.4223e-02, 7.3357e-03],\n [ 1.3374e-02, -1.1409e-02, -1.0236e-02],\n [ 9.4244e-03, -1.5842e-03, -5.5748e-03]]]]), 'model.layer2.0.bn2.weight': tensor([0.2223, 0.1855, 0.1549, 0.2479, 0.2225, 0.2327, 0.1864, 0.1741, 0.1983,\n 0.2079, 0.2771, 0.1911, 0.1967, 0.2161, 0.1778, 0.1766, 0.1532, 0.2382,\n 0.2091, 0.2290, 0.3002, 0.2072, 0.2050, 0.2008, 0.1878, 0.1997, 0.1919,\n 0.2145, 0.2264, 0.1867, 0.1967, 0.1434, 0.2163, 0.2726, 0.2043, 0.2661,\n 0.2408, 0.2354, 0.1852, 0.1466, 0.2400, 0.2435, 0.2621, 0.1864, 0.1885,\n 0.1828, 0.2002, 0.1981, 0.1704, 0.2438, 0.1547, 0.2085, 0.1599, 0.2131,\n 0.2267, 0.1967, 0.1697, 0.2597, 0.2270, 0.1715, 0.2104, 0.2319, 0.1514,\n 0.2082, 0.1764, 0.1613, 0.2256, 0.1894, 0.1545, 0.2065, 0.1695, 0.1418,\n 0.2272, 0.2737, 0.2185, 0.1899, 0.1976, 0.2176, 0.2044, 0.1535, 0.2118,\n 0.2038, 0.1704, 0.2194, 0.2067, 0.1480, 0.2305, 0.2154, 0.2161, 0.1865,\n 0.2652, 0.1962, 0.2188, 0.1574, 0.1629, 0.1866, 0.2540, 0.2190, 0.2077,\n 0.1721, 0.2185, 0.2470, 0.1532, 0.1750, 0.1718, 0.2031, 0.2211, 0.2357,\n 0.1682, 0.2196, 0.2037, 0.1624, 0.1804, 0.1987, 0.2070, 0.2436, 0.1552,\n 0.2037, 0.1617, 0.1978, 0.2111, 0.1948, 0.2292, 0.1844, 0.1924, 0.1621,\n 0.2202, 0.1729]), 'model.layer2.0.bn2.bias': tensor([-6.4613e-02, 1.5500e-01, 1.5214e-01, -5.7497e-02, -7.3616e-02,\n -1.0275e-01, 6.6493e-02, 1.0573e-02, -2.7941e-03, -3.8143e-02,\n -3.7022e-02, 2.3569e-03, -4.2948e-02, 1.8371e-02, -2.4369e-02,\n 1.5403e-01, 8.6409e-02, -3.1838e-02, -2.7692e-02, -2.1025e-02,\n -2.8074e-02, 7.2167e-02, -5.1871e-02, 1.1114e-02, 5.2308e-02,\n -2.4563e-02, -2.4945e-02, -1.2720e-02, -3.3838e-02, -3.6698e-02,\n -3.1716e-02, 1.2455e-01, -6.8709e-02, -4.6247e-02, 3.3910e-03,\n -1.5966e-01, 1.2178e-02, 2.0642e-03, -2.0594e-02, 1.7120e-01,\n -2.9755e-02, -8.8599e-02, -1.0972e-01, -1.4690e-02, 2.2598e-02,\n 1.1811e-01, -3.5539e-02, -7.0981e-02, 1.6699e-01, -4.4844e-02,\n 1.4829e-01, -1.2105e-02, 2.4651e-01, -7.0786e-02, -9.8554e-02,\n 6.3107e-02, 1.9981e-01, -4.7306e-02, 1.5680e-02, 5.2955e-02,\n -1.9409e-02, -3.3017e-02, 2.3351e-01, 2.3955e-02, 5.4127e-02,\n 5.6124e-02, -5.8938e-02, -8.6897e-03, 2.2247e-01, -1.7164e-02,\n 2.1100e-01, 1.4695e-01, -5.8233e-02, -1.1127e-01, -4.3789e-02,\n 6.8444e-03, 9.0411e-02, -3.1704e-02, -3.3315e-03, 1.9729e-01,\n -2.2331e-02, -8.4929e-03, 1.4001e-01, -6.7232e-02, -8.7632e-05,\n 1.0813e-01, -5.4178e-02, -1.0954e-02, -5.7520e-02, 6.1170e-03,\n -3.1645e-01, 6.4796e-02, 1.6376e-02, 6.3080e-03, 4.6874e-02,\n 1.6134e-01, -4.3168e-02, 4.0466e-02, 1.0814e-01, -1.0172e-02,\n -7.2261e-02, -1.0032e-01, 2.6503e-01, -5.1000e-02, 1.0701e-01,\n 8.3905e-03, -2.4408e-02, -3.8112e-02, 2.0187e-01, -3.3428e-02,\n -6.2251e-02, 3.7042e-02, 4.9573e-02, 3.5280e-03, -3.3673e-02,\n -1.1423e-01, 1.0796e-01, -3.5622e-04, 1.7088e-01, 7.0510e-02,\n 1.6285e-02, 1.2550e-01, -3.5396e-02, 1.2627e-02, 9.1127e-02,\n 1.5204e-01, -5.0727e-02, 4.5031e-02]), 'model.layer2.0.bn2.running_mean': tensor([-0.1630, -0.1752, 0.0015, -0.0769, -0.0953, 0.0408, -0.0845, -0.0920,\n -0.0774, -0.0508, -0.2582, -0.0041, -0.0763, -0.0447, -0.2162, -0.1669,\n -0.1134, -0.0972, 0.0322, 0.0087, -0.0971, -0.0396, -0.0499, -0.1806,\n -0.0118, 0.0304, -0.0652, -0.0309, -0.0650, -0.1268, 0.0048, 0.0345,\n -0.0321, -0.2514, -0.0540, -0.2463, -0.0111, -0.1077, -0.0344, -0.0476,\n -0.1032, -0.1358, -0.0868, 0.4252, -0.0661, 0.0054, -0.0160, -0.1493,\n 0.0235, -0.2092, -0.0230, -0.0687, 0.0087, -0.2208, -0.1995, -0.0542,\n 0.1349, -0.1062, 0.0199, -0.1060, -0.1135, -0.1443, 0.0431, 0.0358,\n -0.0588, 0.0028, 0.0705, -0.0299, -0.0752, -0.0810, 0.1106, 0.0355,\n -0.0685, -0.0839, -0.0340, -0.0062, -0.0013, -0.1143, -0.0638, -0.0103,\n -0.0482, 0.0282, 0.0130, -0.1496, -0.0684, 0.0182, -0.1152, 0.0390,\n -0.0844, 0.0483, -0.2445, -0.0258, -0.0577, -0.0573, -0.0194, -0.0855,\n 0.0012, -0.0446, 0.0054, 0.2028, -0.0736, -0.1151, 0.0317, -0.1152,\n -0.0820, -0.0712, -0.0887, -0.0694, 0.0515, -0.0425, -0.0553, -0.0816,\n -0.0697, -0.2458, -0.2131, -0.2210, -0.1140, -0.0706, 0.0006, -0.0332,\n -0.0010, 0.0377, -0.1411, -0.0988, 0.0105, -0.0539, 0.0704, -0.0412]), 'model.layer2.0.bn2.running_var': tensor([0.0341, 0.0559, 0.0245, 0.0311, 0.0379, 0.0286, 0.0485, 0.0234, 0.0239,\n 0.0280, 0.0341, 0.0309, 0.0184, 0.0343, 0.0191, 0.0520, 0.0173, 0.0353,\n 0.0307, 0.0381, 0.0361, 0.0328, 0.0269, 0.0286, 0.0265, 0.0284, 0.0289,\n 0.0224, 0.0395, 0.0237, 0.0289, 0.0315, 0.0316, 0.0430, 0.0421, 0.0258,\n 0.0532, 0.0358, 0.0253, 0.0295, 0.0517, 0.0282, 0.0375, 0.0165, 0.0420,\n 0.0598, 0.0279, 0.0312, 0.0361, 0.0500, 0.0192, 0.0296, 0.0354, 0.0310,\n 0.0290, 0.0462, 0.0356, 0.0489, 0.0459, 0.0253, 0.0235, 0.0436, 0.0356,\n 0.0313, 0.0425, 0.0206, 0.0380, 0.0274, 0.0334, 0.0228, 0.0359, 0.0239,\n 0.0397, 0.0254, 0.0316, 0.0266, 0.0281, 0.0255, 0.0333, 0.0259, 0.0199,\n 0.0289, 0.0328, 0.0419, 0.0308, 0.0262, 0.0382, 0.0299, 0.0317, 0.0395,\n 0.0135, 0.0377, 0.0349, 0.0257, 0.0210, 0.0520, 0.0418, 0.0448, 0.0322,\n 0.0212, 0.0267, 0.0273, 0.0325, 0.0226, 0.0283, 0.0418, 0.0264, 0.0541,\n 0.0331, 0.0188, 0.0331, 0.0276, 0.0252, 0.0301, 0.0199, 0.0381, 0.0194,\n 0.0364, 0.0240, 0.0475, 0.0345, 0.0344, 0.0392, 0.0273, 0.0290, 0.0225,\n 0.0335, 0.0421]), 'model.layer2.0.bn2.num_batches_tracked': tensor(7160), 'model.layer2.0.conv3.weight': tensor([[[[ 8.3712e-03]],\n\n [[-2.9944e-03]],\n\n [[ 1.4515e-02]],\n\n ...,\n\n [[ 7.4280e-03]],\n\n [[-1.9975e-02]],\n\n [[-1.2452e-03]]],\n\n\n [[[-2.7036e-02]],\n\n [[-1.0812e-02]],\n\n [[ 1.6438e-02]],\n\n ...,\n\n [[-2.4220e-03]],\n\n [[-1.2264e-02]],\n\n [[ 6.9713e-02]]],\n\n\n [[[-3.4495e-03]],\n\n [[ 6.7101e-04]],\n\n [[-2.1707e-03]],\n\n ...,\n\n [[-2.2451e-03]],\n\n [[-2.6142e-03]],\n\n [[-2.3594e-03]]],\n\n\n ...,\n\n\n [[[ 1.1697e-07]],\n\n [[ 3.4833e-07]],\n\n [[-1.7422e-07]],\n\n ...,\n\n [[-1.8790e-07]],\n\n [[-8.5461e-08]],\n\n [[ 2.0189e-07]]],\n\n\n [[[ 3.7859e-02]],\n\n [[-1.2937e-01]],\n\n [[-4.4423e-02]],\n\n ...,\n\n [[ 1.1859e-01]],\n\n [[ 5.2828e-02]],\n\n [[-1.7553e-02]]],\n\n\n [[[ 2.9864e-03]],\n\n [[-1.6215e-02]],\n\n [[ 6.0349e-03]],\n\n ...,\n\n [[ 1.2780e-02]],\n\n [[ 1.0187e-03]],\n\n [[ 7.2724e-03]]]]), 'model.layer2.0.bn3.weight': tensor([-1.9536e-03, 2.1198e-01, 1.1381e-03, 1.4151e-01, -1.5050e-03,\n -2.0702e-06, 2.0753e-01, 1.1380e-02, 2.6256e-03, 2.0922e-02,\n 8.5108e-02, 1.0714e-01, 1.1229e-01, 4.8445e-02, 4.5550e-06,\n 1.3134e-01, 2.9966e-01, -1.8129e-02, 1.3066e-01, 9.4527e-02,\n 8.3597e-02, -1.8412e-03, 2.0046e-01, 1.5372e-07, 1.5391e-01,\n -8.8025e-03, 1.1844e-01, 1.5473e-01, 6.6282e-06, 1.8172e-01,\n 3.1369e-01, -2.1027e-03, 4.3207e-02, 1.4959e-01, 8.5977e-02,\n 1.8994e-01, 7.5675e-02, 1.9319e-01, 1.1779e-03, 2.2510e-01,\n 2.3500e-01, 1.8279e-01, 5.7092e-02, -1.9156e-03, -6.7198e-03,\n 2.1987e-01, 1.4564e-02, 2.0025e-01, 1.5535e-01, 2.0835e-01,\n -3.2646e-03, -5.9155e-04, 6.8811e-02, 1.0054e-01, 3.2551e-03,\n 2.0447e-01, 4.9828e-02, 8.9463e-02, 2.0561e-01, -7.7076e-08,\n -2.3954e-04, 1.4148e-01, 1.3955e-01, -2.8433e-03, 1.5824e-01,\n 1.6034e-01, 6.9573e-02, 1.9015e-01, -1.0229e-06, 2.2883e-01,\n 2.3895e-01, 1.4091e-01, 2.5603e-01, 1.6529e-01, 3.2133e-01,\n 1.0347e-02, 2.4605e-01, -6.1768e-03, 1.7618e-01, 1.9273e-01,\n 2.3189e-01, 1.3646e-01, -6.9054e-03, 2.1327e-01, 1.0735e-01,\n 1.9633e-01, 1.7669e-01, 6.8525e-03, 4.0672e-03, 2.3814e-06,\n 6.4092e-07, 2.2547e-01, 1.6914e-01, 1.0721e-02, 2.6848e-08,\n 1.8315e-01, 1.9406e-01, -3.2643e-02, 1.6296e-01, 3.7790e-04,\n 1.2872e-01, 1.7676e-01, 1.0465e-02, 1.8672e-01, 2.2735e-03,\n -1.9165e-04, 1.6642e-01, 1.9044e-01, 1.4409e-01, 5.4172e-02,\n 1.2111e-01, 1.5339e-01, -1.0824e-07, 1.5783e-01, 5.0360e-03,\n 1.2267e-01, 1.8536e-01, 1.4190e-01, 1.9956e-01, 6.8567e-02,\n 1.0022e-01, 1.2605e-01, 7.0132e-02, 1.0259e-01, 8.9288e-02,\n -4.0429e-04, 2.4928e-01, 5.6875e-02, 7.0892e-02, 1.6392e-01,\n 1.7119e-01, 1.4228e-01, 1.0957e-01, 1.7668e-06, 8.9635e-02,\n 8.9525e-02, 1.5497e-01, 1.8757e-01, 4.5771e-07, 1.7903e-01,\n 1.2131e-01, 1.3435e-01, 2.0952e-01, 1.6595e-04, -2.5550e-02,\n -1.8625e-02, 6.4338e-03, 1.9398e-01, 2.6457e-01, 1.7863e-01,\n 2.2521e-01, 4.0949e-02, 8.4070e-02, -5.9602e-06, -2.7400e-03,\n 1.2719e-01, -6.9892e-04, 2.2609e-06, 1.6050e-01, 1.2716e-01,\n 1.9524e-01, 5.7366e-04, 1.8046e-01, 1.1893e-01, 2.0747e-01,\n 2.6753e-04, 1.1138e-01, 1.4851e-01, 1.9880e-01, 1.0473e-01,\n 2.5308e-08, 1.8989e-01, 2.4397e-01, -1.8081e-03, 1.4885e-06,\n 2.7617e-01, 6.4678e-02, 2.5984e-01, -4.8197e-04, 1.4877e-01,\n 2.5496e-01, 1.4775e-01, 2.1442e-01, 5.7131e-03, 1.2388e-01,\n -3.5100e-04, -2.8465e-07, 1.1955e-01, 4.6141e-03, 1.0667e-01,\n 2.1701e-01, 1.7348e-01, 1.0793e-01, 6.6470e-02, 2.6819e-03,\n 1.9104e-01, 2.5171e-08, 2.2789e-01, 4.2786e-02, -1.0556e-02,\n 2.6809e-06, 1.5658e-01, 2.4329e-01, 2.4119e-03, -2.5157e-08,\n 1.7257e-01, 1.4399e-01, 1.5156e-01, 8.7173e-03, 7.7896e-03,\n 8.7723e-02, 2.1184e-01, 1.1250e-01, 1.4455e-06, 7.5847e-02,\n 2.3478e-01, 1.0279e-01, -1.4769e-03, 1.7182e-02, 2.6397e-01,\n 4.5007e-02, 1.1820e-01, -4.7809e-09, 1.6240e-01, 1.3509e-01,\n 1.9850e-01, 1.2483e-01, 1.6104e-03, 1.9146e-01, 2.2756e-01,\n 1.7724e-01, 8.1856e-02, -3.6785e-03, 4.8969e-02, -5.9956e-09,\n 1.8870e-01, 3.2006e-06, 1.9846e-01, 2.4094e-01, 1.7710e-01,\n -9.5735e-06, 8.1718e-03, 2.0082e-01, -1.3453e-02, 1.3658e-01,\n 1.6137e-01, 1.1891e-01, 2.5447e-01, 1.8142e-01, -7.9333e-03,\n 1.8141e-01, 2.9386e-03, 1.8553e-01, 1.5559e-01, 1.2095e-01,\n -2.4218e-03, 2.2330e-01, 1.4843e-01, 1.8448e-01, 1.9448e-01,\n 1.1131e-01, 2.5336e-01, 2.2701e-01, -1.7206e-02, 2.1376e-01,\n 1.9733e-02, 6.9354e-02, 1.3722e-02, -7.4758e-03, -3.3250e-03,\n -8.4383e-07, 1.5921e-01, -3.3189e-07, 9.9339e-02, 1.9969e-01,\n -4.7148e-03, 7.3247e-02, 8.9003e-03, 1.7627e-01, 2.0863e-01,\n 1.5816e-01, 7.5597e-03, 1.9273e-01, 3.1256e-04, -3.5289e-03,\n -9.4862e-04, 2.0858e-01, 2.0164e-01, 2.1179e-01, 1.5794e-01,\n 1.6118e-02, 1.3520e-04, 2.1115e-01, 2.3660e-01, 2.0776e-01,\n 2.3532e-01, 1.9084e-01, 8.8419e-06, -1.9972e-02, 2.9771e-04,\n 1.7044e-01, 1.5924e-01, 1.1752e-01, 1.1090e-01, 1.4953e-01,\n 1.2061e-01, 9.9554e-02, 9.0683e-02, 7.1548e-02, -7.1196e-03,\n 1.9990e-01, -1.4600e-06, 4.6740e-08, 6.2084e-07, -1.1251e-02,\n 6.4855e-02, 1.8926e-01, 4.1565e-03, 7.9060e-08, -8.9178e-03,\n 1.8756e-01, 1.5228e-01, 1.1230e-01, 8.7468e-02, 2.1883e-01,\n 2.5915e-08, 1.6811e-01, 1.1626e-01, 1.2059e-01, 8.3458e-02,\n 1.7759e-01, 2.5912e-01, 1.5983e-07, -3.2177e-03, 1.1802e-01,\n 8.3591e-02, 2.3023e-01, -4.6494e-03, 2.0505e-01, 6.3930e-02,\n -3.3223e-04, 1.7201e-01, 2.2167e-02, 2.5699e-01, 1.1481e-03,\n 1.9518e-01, 8.0938e-08, 1.4443e-02, 1.3937e-01, 1.9977e-02,\n 1.3345e-01, 2.2334e-03, 2.2607e-01, -3.5765e-03, 1.4275e-03,\n 1.3462e-01, 1.2582e-01, 1.8838e-03, 1.6636e-01, 2.0374e-01,\n 1.3778e-01, 1.2720e-01, 1.2012e-01, -6.3868e-03, 1.1730e-05,\n 2.3155e-01, 1.0777e-01, 2.4584e-01, 1.5801e-01, 1.4153e-01,\n 1.4868e-07, 5.0456e-03, 1.6131e-01, 1.6824e-01, 2.5045e-01,\n 2.7347e-01, 1.1029e-01, 1.7194e-01, 9.9998e-02, 2.5366e-03,\n 3.0619e-01, 1.7556e-01, 1.4603e-03, 1.0279e-01, 2.2909e-01,\n 1.4553e-01, 1.4255e-06, -2.9262e-03, 1.0140e-01, 2.2615e-01,\n 2.2418e-01, 2.2961e-01, -3.1527e-05, 7.2833e-02, 2.1879e-01,\n 5.7369e-04, 8.5396e-03, 1.0637e-01, 1.4737e-01, 5.0695e-02,\n -2.0379e-07, -1.2920e-03, 2.7650e-01, 9.9434e-02, 2.6341e-01,\n 2.0880e-01, 4.4456e-02, 9.1532e-02, 1.5481e-01, -3.0899e-10,\n 1.7618e-01, 2.0046e-01, -2.8324e-03, 6.9877e-08, 8.3268e-02,\n 2.0012e-01, 3.1972e-02, 2.5690e-01, 1.4864e-03, 1.2443e-01,\n 1.8248e-01, 3.8845e-02, 1.1607e-01, 1.3251e-01, 8.9622e-02,\n 9.6921e-02, -4.1332e-07, 3.6670e-02, 1.7157e-01, 9.6171e-02,\n 1.6147e-06, 9.1408e-02, 1.9816e-01, 1.6818e-06, 3.2439e-01,\n 1.9281e-01, 2.0485e-01, 2.5191e-01, 1.2909e-01, 2.2357e-01,\n 1.0247e-01, 6.8850e-04, 6.7161e-02, 1.3464e-02, 3.0665e-02,\n 1.5136e-01, 6.0822e-07, 2.2342e-01, 2.2127e-01, 6.4698e-05,\n 1.5606e-01, 2.5414e-07, 1.9498e-08, 1.8767e-01, 1.0366e-03,\n 1.0932e-01, 1.8675e-01, 1.9290e-01, -5.3873e-03, 1.1822e-01,\n 1.4215e-01, 1.7422e-01, 5.2772e-02, 1.2171e-01, 7.4911e-04,\n 2.0730e-01, 1.1106e-01, 4.4404e-08, -1.5845e-02, 1.9845e-01,\n 1.5821e-01, 1.2517e-02, -4.5107e-08, -1.4433e-03, 1.3236e-03,\n 1.3902e-01, 4.1671e-02, 3.3078e-02, 1.8196e-01, 2.9826e-01,\n 5.9726e-02, 1.6500e-01, 2.5572e-02, 1.9811e-01, 2.2920e-01,\n 1.2735e-01, 5.8267e-06, 1.4823e-01, 2.4450e-03, 7.4062e-02,\n 1.9134e-01, 1.4295e-01, -1.4381e-02, 2.2046e-01, -3.3928e-03,\n 1.2585e-01, 2.0783e-01, 7.5199e-02, 9.7573e-09, 1.6815e-01,\n 1.2660e-02, 1.1730e-01, 1.9976e-01, 5.6735e-02, 1.3749e-01,\n 2.1932e-02, -4.2584e-04, 8.3552e-02, 1.5455e-01, 1.4837e-07,\n 1.5731e-01, 4.7550e-03]), 'model.layer2.0.bn3.bias': tensor([ 5.0834e-02, -4.9077e-02, -6.7327e-03, 1.9894e-02, 3.7655e-02,\n -7.9189e-06, 1.1055e-02, 8.4496e-02, 3.3037e-02, 6.3673e-02,\n -8.4341e-05, -2.9828e-02, 6.7897e-03, 8.3709e-02, -1.7023e-05,\n -2.0068e-02, -3.3362e-02, 3.7563e-02, 4.3028e-02, -1.8203e-03,\n 4.4003e-02, 6.7282e-02, -1.4415e-02, -8.6219e-07, 1.7616e-02,\n 6.2465e-02, 2.3539e-03, -2.6935e-02, -3.1902e-05, 5.3920e-02,\n -9.6259e-02, 6.9395e-02, 3.2581e-02, -1.2491e-02, 5.1481e-03,\n -2.9016e-02, 9.1588e-02, 4.8823e-02, -5.4377e-03, 7.2925e-02,\n -3.9511e-02, 1.8236e-02, -2.4880e-02, 3.5841e-02, 6.7832e-03,\n -5.7434e-02, 7.2637e-02, -3.6747e-02, 6.7101e-02, -5.5490e-02,\n 9.2174e-02, -1.5524e-03, 5.6394e-02, 4.2435e-02, 8.8194e-02,\n 1.0468e-02, -4.6608e-03, -3.1827e-03, 8.3859e-03, -4.0713e-06,\n 4.3254e-02, -8.6418e-03, -1.2451e-03, -1.6065e-04, -8.1947e-03,\n 8.9926e-03, -1.0028e-01, 4.3496e-02, -7.8888e-06, -6.8866e-04,\n 6.4236e-03, 2.5530e-02, -9.8615e-03, -5.5630e-03, -4.2850e-02,\n 4.7188e-02, -2.1013e-02, 9.8083e-02, 1.9405e-02, -5.6787e-02,\n 7.8191e-03, 1.8706e-02, -2.5680e-02, 2.6439e-02, -1.7403e-03,\n 4.6873e-02, 5.8927e-02, -2.6867e-03, 8.3420e-02, -1.0144e-05,\n -7.6508e-06, -4.7262e-02, -5.6446e-02, 4.2935e-02, -1.5890e-07,\n -1.8265e-02, 1.4940e-02, 3.3675e-02, -8.1817e-03, -2.1246e-02,\n -4.6000e-03, -3.2776e-02, 8.8999e-02, 2.4027e-02, 1.1350e-01,\n -8.9958e-04, 3.8284e-02, -4.0489e-02, -5.3689e-03, -2.1906e-02,\n 7.6661e-02, 5.4796e-02, -2.8526e-06, -2.1416e-02, 1.0094e-01,\n 6.5590e-02, -3.6022e-03, -1.2144e-02, 3.3670e-02, 5.0224e-02,\n -1.9256e-02, 3.5518e-02, 7.7969e-02, 1.1642e-03, -4.2843e-02,\n 1.6325e-01, -3.5453e-02, 5.6190e-02, -1.2538e-03, -3.8911e-02,\n -1.3372e-02, 1.7887e-02, 2.5722e-02, -7.1322e-06, 9.3343e-02,\n -6.3560e-03, 1.5494e-03, 1.3458e-02, -1.4194e-06, -2.9466e-04,\n 9.6760e-03, -2.5608e-02, -1.9833e-02, -4.8029e-04, -4.0123e-02,\n 5.3387e-03, 5.1415e-02, -2.2941e-02, 2.2118e-02, -2.2908e-02,\n -1.7613e-03, 3.2486e-02, 6.6462e-02, -6.2677e-05, 1.1092e-01,\n 2.6414e-02, 8.9002e-02, -9.1733e-06, 3.3761e-02, -6.4337e-03,\n -1.4307e-02, 1.1110e-01, 3.2314e-02, 3.1876e-02, 5.9272e-02,\n -1.3884e-03, -2.0293e-02, -3.5694e-02, -4.0915e-02, -1.4256e-02,\n -1.3500e-06, -2.2835e-03, 9.0950e-02, 1.5382e-01, -2.7238e-05,\n -5.3157e-02, 9.7019e-02, -4.0202e-02, 5.5121e-02, -2.0945e-02,\n -4.2598e-02, -6.8659e-03, 1.5319e-02, 3.8783e-02, 8.0118e-03,\n 1.2944e-01, -2.8239e-06, 1.3769e-02, 7.1490e-02, -3.2435e-02,\n 1.7839e-03, -1.8380e-02, 2.2649e-02, 1.1004e-01, 1.5524e-01,\n 4.9853e-03, -1.1732e-07, -2.6311e-02, 3.9022e-03, 2.5377e-03,\n -6.2902e-06, 4.7875e-02, -5.3681e-03, 4.1534e-02, -7.1198e-07,\n -4.4762e-02, 1.9327e-02, 3.7311e-02, 4.3841e-02, -1.3019e-02,\n -7.6676e-03, 7.6830e-02, 4.5697e-02, -1.0135e-05, -2.3555e-02,\n -2.1732e-02, -1.3449e-02, 1.3110e-01, 1.6816e-02, 2.0754e-02,\n 5.1336e-02, -8.8543e-03, -1.2968e-07, -2.6250e-02, 3.1023e-02,\n 2.2531e-02, 5.4253e-02, 1.9927e-01, 1.5372e-02, 6.7338e-03,\n -2.6483e-03, 7.6939e-02, 1.0131e-01, -3.5332e-02, -1.1165e-07,\n 4.6136e-02, -2.7389e-05, -1.8186e-02, 4.4463e-02, -4.6612e-03,\n -1.8436e-04, 1.8990e-01, 2.9364e-02, 8.5756e-02, 1.1440e-02,\n -4.5376e-02, 2.0764e-02, -1.9064e-03, -4.4344e-02, 4.2163e-02,\n 3.4994e-02, 1.4637e-01, -2.4943e-03, 4.4574e-03, 2.5483e-02,\n 6.9906e-02, -3.1308e-02, -1.3978e-02, 3.2223e-02, -6.0031e-04,\n -4.6819e-02, 2.3282e-02, 2.4065e-03, 6.6848e-02, 5.4479e-03,\n 1.0452e-01, 2.8558e-02, 1.6056e-02, 6.2350e-02, 4.1735e-02,\n -1.2237e-04, -2.2317e-02, -3.2690e-06, 6.3187e-02, 1.0923e-02,\n 4.5637e-02, 2.4988e-03, 6.5815e-02, -1.5194e-02, -4.6845e-02,\n -1.4582e-02, 1.1561e-02, -1.7258e-02, 4.9623e-02, 8.4348e-02,\n -3.3495e-02, 1.2883e-02, -7.6839e-03, -3.1304e-02, -4.7099e-02,\n -1.3767e-02, -9.8877e-04, -4.5615e-02, -5.3457e-02, -8.2705e-02,\n 2.0353e-03, 3.9430e-02, -9.5408e-05, 2.7815e-02, -1.2186e-03,\n 1.1368e-02, -2.4319e-02, 5.8323e-03, 4.0933e-02, -1.7825e-02,\n -8.5407e-03, -4.6759e-02, 1.8576e-02, 1.3593e-02, -5.7132e-02,\n -2.7901e-02, -1.7975e-05, -2.4256e-07, -2.3200e-06, 8.8974e-02,\n -2.0184e-02, -3.6667e-03, 1.4330e-01, -5.4095e-07, 8.1132e-02,\n 2.1760e-02, 6.0346e-03, 1.4534e-02, 1.1589e-04, 3.7186e-02,\n -1.5115e-07, -6.7433e-02, -1.3699e-02, 3.0056e-03, 3.8657e-02,\n 7.2264e-02, -6.7452e-04, -6.0793e-07, -6.9888e-02, 1.4458e-03,\n 2.6498e-02, -2.1198e-02, 7.2501e-02, -2.9475e-02, -3.0987e-02,\n 8.9529e-02, 7.2748e-03, 1.1690e-01, -3.0943e-02, 1.1331e-01,\n 1.3392e-02, -1.8967e-07, 8.5637e-02, 5.5860e-03, 1.4101e-01,\n -5.0247e-03, -9.8680e-02, -1.9396e-02, 3.0411e-02, 1.4446e-01,\n -3.5790e-03, 3.3711e-02, 1.4874e-01, 1.8345e-02, -2.8280e-02,\n 2.5847e-02, 3.2509e-02, -4.7404e-03, -4.0921e-02, -6.7543e-05,\n -3.7236e-02, 1.2577e-03, -1.5731e-02, 5.9471e-02, -3.2187e-02,\n -5.0082e-06, 1.0503e-01, 2.7247e-02, 1.3641e-02, 7.1566e-02,\n -3.4105e-02, -3.1445e-02, 4.1694e-03, -1.6897e-02, 6.1689e-02,\n -2.6501e-02, -1.0475e-02, 1.2626e-01, 4.1497e-02, -5.9193e-03,\n 1.1730e-02, -5.9827e-05, 8.4875e-02, 5.6433e-02, -1.7832e-02,\n 1.0870e-03, 1.5394e-02, 7.1454e-02, -4.9118e-02, -1.0158e-02,\n 1.3767e-01, 8.3597e-02, -5.8024e-02, 9.3476e-03, 3.0341e-02,\n -1.9198e-06, -2.4033e-02, -1.5026e-02, 7.4188e-03, -6.8561e-02,\n -6.1679e-02, 2.8765e-02, 1.6927e-03, 7.8538e-03, -9.6343e-07,\n 5.6390e-03, 2.5071e-03, 1.1709e-01, -2.4052e-07, 3.5965e-03,\n -2.9915e-02, 6.3756e-04, -2.4417e-02, -2.1534e-02, 1.7838e-02,\n -1.4226e-02, -4.9004e-02, 1.5733e-03, -1.6215e-02, -4.5628e-03,\n -2.2838e-02, -1.9253e-06, 4.4060e-03, -1.0329e-02, -1.1512e-03,\n -8.7646e-06, 4.7309e-02, 8.8067e-02, -8.0243e-06, -1.7264e-01,\n -1.5183e-02, -4.1436e-02, -5.1695e-02, -3.6572e-03, 8.5591e-03,\n 1.0878e-02, 5.7972e-02, -6.6692e-02, 1.6173e-01, 6.3349e-02,\n -2.8691e-02, -2.3525e-06, 4.4352e-03, -1.1629e-02, -1.6837e-04,\n -2.0481e-02, -2.3380e-06, -4.7066e-07, 3.3126e-02, -4.4317e-03,\n 7.6798e-03, 6.7975e-02, -2.7854e-02, 9.1272e-02, 1.1165e-01,\n -1.0632e-02, 6.0867e-02, -2.5826e-02, 3.4329e-02, 1.6916e-01,\n 1.3250e-02, -1.9785e-02, -3.8024e-07, 4.9826e-02, -1.5098e-02,\n -2.7743e-02, 1.4274e-01, -1.0422e-07, 6.1897e-02, 8.5070e-02,\n 1.3790e-02, 6.8949e-02, -2.4559e-03, -3.1927e-03, -5.6222e-02,\n -8.7371e-03, 4.5338e-03, 1.7333e-02, -3.6611e-02, -1.2728e-02,\n -1.3143e-02, -1.6550e-05, 3.3299e-02, 7.5311e-02, -1.0978e-02,\n -3.3621e-02, -5.9845e-02, 5.5580e-02, 4.0376e-02, 9.9984e-02,\n -4.7201e-02, -1.4597e-02, -5.5442e-02, -6.0001e-08, 9.6936e-03,\n 5.9480e-02, -1.0083e-01, -2.4799e-02, 1.2643e-03, 1.2939e-02,\n 7.4288e-02, 2.9965e-02, -1.6249e-02, -4.2799e-02, -8.7138e-07,\n 7.5978e-02, 1.6202e-01]), 'model.layer2.0.bn3.running_mean': tensor([-3.5428e-03, 6.6526e-02, -4.9051e-03, 1.7877e-02, 2.1593e-02,\n 1.4349e-06, -4.4761e-02, 2.2132e-03, -4.2479e-03, -2.9522e-04,\n -1.1225e-02, -3.6555e-03, -3.9158e-02, 1.4824e-02, -4.7704e-06,\n -7.3194e-02, -7.3894e-02, 9.1159e-03, -7.1883e-02, -2.1029e-02,\n -1.9776e-02, 2.5438e-02, -3.2472e-02, -1.9366e-07, 8.6787e-02,\n -9.7815e-03, -2.3230e-02, 9.8006e-02, 1.4467e-05, 4.3712e-02,\n -9.8949e-03, -2.0999e-02, -2.1776e-02, 8.6743e-02, 2.9344e-02,\n -4.5899e-02, -5.2583e-02, -5.1188e-02, 3.4694e-03, 7.9893e-02,\n -4.8479e-04, 5.4227e-02, -1.9925e-02, -1.8658e-02, -1.6769e-02,\n -2.7905e-02, -3.6108e-03, -2.7234e-02, -4.1205e-02, -3.9487e-02,\n 2.0642e-02, -8.9385e-05, 3.8094e-02, 1.6833e-03, 1.7788e-02,\n -1.0686e-01, -2.1550e-02, 2.5988e-02, 5.6474e-02, 7.5733e-07,\n -4.5422e-04, 1.0488e-02, -2.6818e-02, 2.8629e-03, 6.5382e-02,\n 1.3211e-02, 2.2080e-03, 1.1047e-02, -1.3229e-06, 4.9185e-02,\n 4.1100e-02, -2.3698e-02, -5.9971e-02, 6.8208e-02, -2.4770e-02,\n -4.8092e-02, 9.6954e-02, 1.3023e-02, -6.6402e-02, -2.3224e-03,\n 1.3336e-02, 1.5989e-02, -1.1337e-02, -9.6759e-02, -3.1691e-02,\n 8.3116e-02, -6.0237e-02, 6.4229e-03, 6.0544e-03, 1.9759e-06,\n 1.3753e-06, 1.5318e-02, -2.6131e-02, 2.3552e-02, 2.3577e-08,\n -3.4847e-03, 2.4897e-02, -4.9973e-02, 8.8006e-02, 6.9985e-03,\n 7.5724e-02, 5.0062e-02, -1.4267e-02, 8.3840e-03, 7.6477e-03,\n -3.6709e-04, 6.4608e-02, -5.7783e-02, 6.5807e-02, -2.5716e-02,\n 1.0826e-02, 4.9714e-02, 4.6233e-07, -8.6801e-04, 3.1038e-03,\n 9.1391e-02, 8.8501e-02, -2.2427e-03, -5.8231e-02, -4.7095e-02,\n -7.6403e-03, -1.2470e-02, 6.0932e-02, -1.9628e-02, 1.2081e-02,\n 1.3800e-02, -4.8977e-02, 1.8457e-02, -3.7663e-02, 4.2840e-02,\n 6.0210e-03, 3.4281e-02, -4.3822e-02, -3.8221e-06, -6.5325e-02,\n -3.8701e-02, -8.7054e-04, -3.9228e-02, 5.7139e-07, -8.2593e-03,\n 2.4711e-03, -3.7198e-03, 2.4068e-02, -1.5034e-04, -9.3916e-03,\n -3.1715e-02, -6.1526e-03, 2.5736e-02, -3.0661e-01, 9.9563e-02,\n 7.0042e-03, -4.4411e-02, -8.9528e-03, -9.8123e-06, 4.3417e-03,\n -2.6709e-02, -4.4175e-03, -1.1772e-06, 1.7320e-02, -2.7842e-02,\n 1.1069e-02, -3.6229e-02, 3.5374e-02, 1.1531e-01, 1.1721e-02,\n -5.3280e-04, 1.1249e-01, 3.2086e-02, 6.6821e-02, 5.1368e-02,\n 1.2416e-07, 4.0340e-02, 1.7527e-01, -1.7667e-02, 2.3217e-06,\n -2.7688e-02, 8.5533e-02, 3.2845e-03, 3.0737e-03, 3.3817e-02,\n -5.9373e-02, -6.3349e-02, -3.5366e-02, 1.2571e-02, 5.7388e-02,\n -4.3961e-02, -1.2388e-06, 1.7488e-02, 6.4132e-03, 1.1141e-01,\n -1.6808e-02, -1.4955e-02, 2.7055e-02, -1.4394e-01, 1.8151e-02,\n 2.4069e-02, -4.5681e-08, 3.7824e-02, 1.0521e-02, -2.2298e-02,\n 4.9612e-07, 2.4959e-02, 1.0560e-01, -1.1576e-02, -3.6703e-07,\n -5.3762e-02, 7.0478e-02, 2.4102e-02, -4.4608e-02, -1.3956e-02,\n -7.5925e-02, 1.0267e-03, -1.0626e-01, 1.5806e-06, -7.8572e-03,\n -6.0471e-03, -6.1796e-02, 3.1033e-02, -1.8997e-02, -1.0878e-01,\n 1.9317e-02, 2.3745e-02, -5.6959e-08, -3.6224e-03, 2.9755e-02,\n 4.1757e-02, -2.9707e-04, 2.2289e-02, 3.0859e-02, -2.1415e-01,\n 7.4001e-02, -3.7974e-02, -3.4548e-03, 4.1408e-03, -5.9153e-08,\n 1.4198e-03, 1.1805e-05, 3.0258e-02, 4.6502e-02, -2.0136e-02,\n 1.4067e-05, 1.5883e-02, 5.4585e-02, -3.3480e-02, -1.3829e-02,\n -4.3963e-02, 1.3836e-02, -9.4576e-02, 6.0971e-02, -6.5222e-03,\n -1.1771e-02, -3.9480e-02, -3.0931e-03, -3.9252e-02, 1.6127e-02,\n -2.0086e-03, 2.4527e-02, 5.2367e-02, -2.1744e-02, -5.8630e-02,\n 1.5045e-02, 3.2966e-03, 2.3629e-02, -2.6147e-02, 4.7939e-02,\n -1.1089e-03, -5.2137e-02, -1.3636e-02, -1.5805e-02, -1.1728e-02,\n -7.7229e-06, -3.0284e-02, -8.8973e-07, -4.8371e-02, -6.1431e-02,\n -9.9898e-03, -7.0391e-02, -2.9598e-03, 3.6204e-02, 8.7882e-02,\n 9.1201e-02, -1.1454e-02, 1.2147e-02, -6.6008e-03, -3.2658e-02,\n 1.3838e-02, -2.0199e-02, -1.0437e-04, 1.0726e-01, 3.5871e-03,\n 1.4503e-02, 1.7124e-04, 2.3277e-03, 1.3637e-02, -7.2386e-02,\n -1.1690e-01, -1.9331e-02, -2.0744e-06, -3.8467e-04, 1.6087e-03,\n -4.5883e-02, 2.2607e-03, -7.8971e-03, -2.1419e-02, -2.8057e-03,\n -1.4449e-01, -4.4166e-04, -5.9486e-02, 1.7834e-02, -6.7727e-03,\n 3.6630e-02, 6.3450e-07, 1.9852e-08, 1.2912e-06, 1.5809e-03,\n -1.3057e-02, -2.2131e-03, 5.9551e-03, 2.8077e-07, -2.0990e-03,\n 1.2805e-01, -4.5348e-02, 4.1413e-02, -1.4872e-02, -1.0735e-01,\n 1.5005e-08, -5.7664e-02, 7.9241e-03, -6.0590e-02, 3.7193e-02,\n -6.0372e-02, 1.3191e-01, -1.1775e-07, -1.7721e-02, -4.8639e-02,\n 5.5501e-02, -7.8442e-02, 5.1371e-03, 1.8944e-02, 1.0658e-02,\n -1.1316e-02, -1.7209e-02, -2.6832e-02, -9.0897e-03, 2.8120e-03,\n -7.2481e-03, -4.0921e-08, -1.0243e-04, -1.9110e-02, 1.7015e-02,\n 8.2144e-02, 2.0249e-02, -1.2641e-01, 3.3683e-03, 8.5099e-03,\n -2.2955e-02, 2.1135e-02, 1.2075e-03, -1.2190e-01, -4.3818e-03,\n -6.8938e-02, 1.9088e-02, 1.5294e-02, -4.3781e-03, -1.2561e-05,\n -3.4326e-02, 4.3307e-02, -1.1986e-01, -1.1483e-01, -6.0739e-02,\n 6.2136e-07, 7.8275e-03, -5.9818e-02, -3.1772e-02, -2.4800e-02,\n -1.3265e-01, 7.1143e-03, 5.8493e-04, 1.2324e-02, -1.0527e-02,\n -1.7109e-02, 1.8169e-02, -9.7378e-03, -6.4357e-02, 1.4922e-02,\n 4.1986e-02, 9.4468e-06, -7.3104e-03, -1.9160e-02, -1.3882e-02,\n 5.2448e-03, 3.1423e-02, -6.4863e-03, -1.2251e-04, 2.2310e-02,\n 7.8373e-03, 1.0230e-02, -3.2889e-02, 4.3333e-03, 1.2662e-02,\n 2.6310e-07, -1.1259e-02, -3.9007e-03, -1.5885e-02, -2.2522e-02,\n 1.9027e-01, 1.1028e-02, -2.5435e-02, -7.1892e-02, 1.2835e-07,\n -6.2390e-02, 1.0915e-02, 7.2141e-03, -9.7804e-08, 2.5545e-02,\n -1.1160e-02, -1.0955e-02, -1.7228e-02, 6.1631e-03, -1.6626e-02,\n -5.2369e-03, -1.1121e-03, 5.7386e-02, -2.5765e-02, 8.5948e-02,\n 4.5594e-02, -1.3915e-10, 1.0865e-02, -2.3699e-02, -2.0637e-02,\n -3.3166e-06, -1.3107e-01, -1.1174e-01, 4.2642e-06, 1.0511e-01,\n -2.9477e-02, 8.2548e-03, -2.1801e-02, 9.2672e-02, 3.0196e-02,\n 2.2319e-02, 4.5303e-03, -2.3416e-02, 1.1478e-02, -2.0937e-02,\n -3.6433e-02, 1.0321e-06, 1.8225e-02, -4.3157e-02, 3.5439e-05,\n 1.8816e-01, 1.1494e-07, 8.5276e-08, -3.7483e-03, -4.7998e-05,\n -6.9038e-02, 4.2104e-03, 4.9151e-02, 1.2861e-02, -3.1221e-02,\n -6.2561e-02, 5.8173e-02, -5.8892e-03, -1.1697e-02, 1.2467e-02,\n -2.1257e-02, 8.0093e-02, -1.3343e-07, -8.7298e-03, -2.8814e-02,\n 1.8482e-02, 1.0504e-02, -7.9849e-09, 3.9378e-03, 1.4988e-03,\n -2.5803e-02, -1.0124e-02, 1.4756e-02, -7.3346e-02, -1.8551e-02,\n 1.7915e-02, 1.4446e-02, -9.1208e-03, -5.1820e-02, -1.9470e-02,\n 2.7955e-02, -7.9987e-06, -2.5183e-02, 7.2206e-03, 7.7121e-03,\n 2.1003e-02, 1.1062e-01, 5.4380e-03, -1.3676e-01, -1.9305e-02,\n -7.7144e-03, -5.6113e-02, 3.6525e-02, 2.8639e-08, 3.6044e-03,\n 1.1195e-02, -6.5483e-03, 2.9995e-02, -5.2178e-02, 7.2564e-03,\n 5.7930e-02, 1.4188e-03, 2.7457e-02, 1.1168e-02, 1.2070e-08,\n -1.1511e-02, -1.6048e-02]), 'model.layer2.0.bn3.running_var': tensor([4.5781e-04, 2.4038e-03, 2.0799e-05, 2.4998e-03, 3.2603e-04, 1.0679e-11,\n 4.6242e-03, 5.8062e-04, 2.7351e-04, 7.8915e-04, 1.0945e-03, 1.7357e-03,\n 2.8539e-03, 5.8537e-04, 3.8723e-11, 2.0934e-03, 7.5086e-03, 3.4924e-04,\n 3.7531e-03, 1.3454e-03, 1.7868e-03, 4.4279e-04, 5.6531e-03, 6.2258e-14,\n 3.9533e-03, 3.6899e-04, 1.7747e-03, 3.0868e-03, 2.1728e-10, 6.2775e-03,\n 3.7747e-03, 3.4288e-04, 1.9962e-03, 2.3971e-03, 1.5374e-03, 5.4800e-03,\n 4.9370e-03, 5.4910e-03, 5.6583e-06, 1.0378e-02, 4.5324e-03, 5.9211e-03,\n 1.0956e-03, 4.4981e-04, 3.2337e-04, 3.9797e-03, 4.6497e-04, 2.9700e-03,\n 3.9149e-03, 2.8600e-03, 3.3563e-04, 6.2630e-08, 2.7788e-03, 2.1800e-03,\n 5.2959e-04, 5.1657e-03, 8.8854e-04, 9.8513e-04, 4.8839e-03, 1.4458e-12,\n 3.0098e-04, 2.7617e-03, 2.7221e-03, 2.2740e-04, 2.1554e-03, 2.3229e-03,\n 7.6968e-04, 3.9981e-03, 1.4540e-11, 3.1821e-03, 5.5664e-03, 4.6713e-03,\n 4.1726e-03, 2.7541e-03, 6.5036e-03, 4.8542e-04, 4.4652e-03, 5.5690e-04,\n 6.2447e-03, 2.7492e-03, 6.6020e-03, 2.4162e-03, 2.3795e-04, 4.0298e-03,\n 2.5361e-03, 5.0212e-03, 4.7706e-03, 4.6252e-04, 7.8536e-04, 1.8437e-11,\n 5.4895e-12, 3.9680e-03, 1.4044e-03, 3.3716e-04, 2.4126e-15, 2.1493e-03,\n 3.5155e-03, 7.6318e-04, 2.6825e-03, 7.2415e-04, 2.8043e-03, 1.9243e-03,\n 5.5736e-04, 3.5789e-03, 4.8216e-04, 2.1584e-07, 4.2090e-03, 2.5443e-03,\n 4.8188e-03, 5.7330e-04, 3.2889e-03, 5.1928e-03, 2.5579e-13, 4.5109e-03,\n 5.5817e-04, 5.4629e-03, 2.6597e-03, 3.5796e-03, 3.7301e-03, 2.2022e-03,\n 2.9688e-03, 2.6188e-03, 2.4170e-03, 2.8615e-03, 1.3563e-03, 7.7091e-04,\n 5.1733e-03, 2.1175e-03, 1.0193e-03, 2.7298e-03, 4.6312e-03, 2.6408e-03,\n 3.2285e-03, 1.8114e-11, 3.5097e-03, 1.5631e-03, 3.4413e-03, 3.3078e-03,\n 1.9401e-13, 2.5975e-03, 3.7672e-03, 3.4786e-03, 3.8980e-03, 4.9656e-08,\n 5.8402e-04, 3.8778e-04, 3.6595e-04, 2.5312e-03, 5.1997e-03, 2.8023e-03,\n 7.1128e-03, 2.0314e-03, 1.9691e-03, 3.7770e-10, 4.5277e-04, 3.0726e-03,\n 5.0068e-04, 1.7099e-11, 4.8611e-03, 1.9594e-03, 6.0072e-03, 7.4517e-04,\n 6.6497e-03, 2.3554e-03, 2.7227e-03, 2.2206e-07, 2.8423e-03, 2.0094e-03,\n 2.7146e-03, 1.5351e-03, 9.4528e-14, 1.1841e-02, 1.7061e-02, 7.4617e-04,\n 3.8117e-11, 6.0437e-03, 1.9892e-03, 5.8020e-03, 3.1083e-04, 2.4542e-03,\n 2.7955e-03, 4.9276e-03, 5.5680e-03, 5.9025e-04, 2.2297e-03, 5.2556e-04,\n 1.0297e-12, 2.9124e-03, 4.9752e-04, 1.7703e-03, 7.1435e-03, 2.5098e-03,\n 2.0678e-03, 2.5298e-03, 9.2805e-04, 4.0257e-03, 1.3894e-15, 4.5296e-03,\n 6.9012e-04, 5.6032e-04, 4.7315e-12, 3.9851e-03, 4.2578e-03, 1.8415e-04,\n 1.4322e-13, 1.7109e-03, 2.0471e-03, 3.1558e-03, 8.9577e-04, 9.2319e-05,\n 2.1007e-03, 8.1485e-03, 7.4547e-03, 2.2852e-11, 8.3123e-04, 6.1492e-03,\n 2.1753e-03, 9.6653e-04, 5.8828e-04, 5.0937e-03, 1.7403e-03, 2.1477e-03,\n 9.1444e-16, 1.4750e-03, 4.1636e-03, 4.7347e-03, 2.6243e-03, 6.8345e-04,\n 4.9531e-03, 8.6628e-03, 2.8347e-03, 1.8084e-03, 6.0550e-04, 7.1276e-04,\n 2.5162e-15, 6.2396e-03, 2.9215e-10, 4.8689e-03, 8.5282e-03, 2.9879e-03,\n 1.6631e-09, 9.7823e-04, 3.9826e-03, 7.1266e-04, 2.1383e-03, 2.8601e-03,\n 2.2124e-03, 8.1376e-03, 3.9262e-03, 4.1096e-04, 6.0679e-03, 7.9462e-04,\n 3.7562e-03, 4.5780e-03, 2.8114e-03, 4.0686e-04, 3.3592e-03, 3.4237e-03,\n 7.8263e-03, 7.7132e-03, 1.7133e-03, 5.8901e-03, 6.4906e-03, 6.2439e-04,\n 4.0613e-03, 1.7059e-03, 1.5267e-03, 3.4912e-04, 9.9514e-04, 3.7959e-04,\n 1.4370e-09, 2.6523e-03, 4.5625e-13, 3.8823e-03, 4.7528e-03, 5.2494e-04,\n 1.5182e-03, 3.7067e-04, 2.7685e-03, 4.9043e-03, 3.4305e-03, 4.3955e-04,\n 3.7426e-03, 2.9678e-04, 4.9216e-04, 3.9772e-04, 5.4049e-03, 4.0949e-03,\n 5.1048e-03, 2.3026e-03, 3.7601e-04, 7.6288e-08, 3.3318e-03, 4.8612e-03,\n 1.6136e-03, 5.5027e-03, 6.3007e-03, 1.1834e-09, 3.5683e-04, 6.6811e-07,\n 3.1873e-03, 2.0110e-03, 1.1759e-03, 1.8011e-03, 1.7783e-03, 2.7682e-03,\n 8.9110e-04, 1.7707e-03, 1.2452e-03, 4.8318e-04, 3.6099e-03, 9.2558e-12,\n 2.6762e-14, 9.6290e-13, 5.4745e-04, 1.4706e-03, 4.6186e-03, 6.1739e-04,\n 6.0980e-14, 5.0715e-04, 5.5747e-03, 4.7234e-03, 3.0301e-03, 1.1596e-03,\n 6.2469e-03, 1.7981e-15, 1.9571e-03, 3.0234e-03, 3.5981e-03, 2.5663e-03,\n 5.1737e-03, 7.3743e-03, 7.0056e-14, 2.1314e-04, 1.8759e-03, 1.8144e-03,\n 3.4012e-03, 6.1884e-04, 4.3963e-03, 1.5704e-03, 6.2718e-04, 4.6104e-03,\n 5.0919e-04, 3.6157e-03, 6.8929e-04, 6.0195e-03, 5.7071e-15, 7.7956e-04,\n 2.9474e-03, 9.3425e-04, 2.6797e-03, 3.5535e-04, 5.6806e-03, 3.7437e-04,\n 8.0700e-04, 4.1917e-03, 2.6133e-03, 6.1979e-04, 2.4572e-03, 3.6673e-03,\n 3.3634e-03, 2.8365e-03, 1.9498e-03, 5.7976e-04, 6.5691e-10, 5.6446e-03,\n 2.2665e-03, 3.6097e-03, 2.9993e-03, 2.3891e-03, 2.8563e-12, 5.2599e-04,\n 5.9363e-03, 4.4545e-03, 9.9123e-03, 6.3730e-03, 1.7260e-03, 6.5569e-03,\n 1.2342e-03, 3.0376e-04, 7.1924e-03, 2.9885e-03, 3.0295e-04, 1.8526e-03,\n 4.9150e-03, 3.0956e-03, 4.7228e-10, 3.4940e-04, 3.5461e-03, 4.5122e-03,\n 5.4541e-03, 4.8535e-03, 5.9117e-04, 5.1320e-04, 6.6226e-03, 8.1265e-04,\n 5.8706e-04, 2.4162e-03, 5.9589e-03, 1.5471e-03, 1.2724e-13, 4.7002e-04,\n 7.2802e-03, 2.0361e-03, 4.7752e-03, 6.7738e-03, 1.2407e-03, 1.8922e-03,\n 2.0842e-03, 1.1989e-13, 3.8972e-03, 6.2489e-03, 6.0345e-04, 7.6480e-15,\n 2.6924e-03, 2.1987e-03, 3.5471e-04, 7.7366e-03, 6.2037e-04, 3.8321e-03,\n 4.9955e-03, 8.6777e-04, 1.4754e-03, 2.8987e-03, 1.7935e-03, 1.0822e-03,\n 1.1558e-13, 1.3859e-03, 4.9842e-03, 1.4056e-03, 2.9517e-12, 1.5650e-03,\n 5.1015e-03, 2.1300e-11, 4.7290e-03, 2.6298e-03, 3.3122e-03, 4.5566e-03,\n 2.3756e-03, 4.9533e-03, 1.5219e-03, 6.0633e-04, 1.7369e-03, 1.0052e-03,\n 7.0954e-04, 3.7181e-03, 1.5845e-12, 6.4901e-03, 7.9832e-03, 8.9221e-09,\n 3.7468e-03, 2.5466e-13, 4.2390e-14, 5.6439e-03, 2.7670e-06, 2.7016e-03,\n 3.6898e-03, 2.6135e-03, 9.6647e-04, 5.6398e-03, 1.7303e-03, 4.6258e-03,\n 6.0451e-04, 3.1486e-03, 8.3017e-04, 5.2683e-03, 9.5172e-04, 2.3843e-14,\n 4.9227e-04, 3.4622e-03, 2.2689e-03, 8.6186e-04, 9.3075e-16, 5.3814e-04,\n 7.5544e-04, 3.3146e-03, 1.3618e-03, 6.3441e-04, 5.3682e-03, 4.2463e-03,\n 7.5545e-04, 4.0102e-03, 5.4563e-04, 3.9965e-03, 5.4376e-03, 2.0468e-03,\n 5.7327e-11, 4.5217e-03, 4.7004e-04, 2.1630e-03, 4.3066e-03, 2.0396e-03,\n 5.3821e-04, 5.1954e-03, 8.2631e-04, 2.3149e-03, 3.9605e-03, 1.0611e-03,\n 5.9448e-16, 5.2116e-03, 3.2181e-04, 1.4770e-03, 3.2259e-03, 1.3128e-03,\n 2.7519e-03, 8.3614e-04, 3.0208e-04, 1.0520e-03, 2.4579e-03, 1.0765e-13,\n 5.0680e-03, 4.2715e-04]), 'model.layer2.0.bn3.num_batches_tracked': tensor(7160), 'model.layer2.0.downsample.0.weight': tensor([[[[ 7.1089e-02]],\n\n [[ 3.8419e-03]],\n\n [[ 1.5302e-02]],\n\n ...,\n\n [[ 1.8444e-01]],\n\n [[-6.9004e-03]],\n\n [[ 7.9494e-03]]],\n\n\n [[[-2.0584e-02]],\n\n [[-1.1064e-02]],\n\n [[ 2.3433e-02]],\n\n ...,\n\n [[-6.4582e-03]],\n\n [[-5.2245e-02]],\n\n [[-4.2363e-03]]],\n\n\n [[[-8.6989e-04]],\n\n [[-7.8696e-04]],\n\n [[ 4.1695e-03]],\n\n ...,\n\n [[-1.2266e-03]],\n\n [[ 7.4750e-04]],\n\n [[ 1.8342e-03]]],\n\n\n ...,\n\n\n [[[ 1.0406e-07]],\n\n [[ 5.3282e-08]],\n\n [[ 9.3874e-08]],\n\n ...,\n\n [[-3.8367e-08]],\n\n [[-1.5700e-07]],\n\n [[ 1.0596e-07]]],\n\n\n [[[ 1.0145e-02]],\n\n [[ 8.8368e-04]],\n\n [[-3.6216e-02]],\n\n ...,\n\n [[ 1.5663e-02]],\n\n [[ 2.0082e-02]],\n\n [[ 2.1405e-02]]],\n\n\n [[[ 1.0137e-02]],\n\n [[-4.4088e-02]],\n\n [[-4.5361e-02]],\n\n ...,\n\n [[ 2.0704e-02]],\n\n [[-5.0108e-02]],\n\n [[ 1.8505e-02]]]]), 'model.layer2.0.downsample.1.weight': tensor([ 2.4960e-01, 1.1328e-01, 7.5449e-04, 1.0229e-01, 1.4736e-01,\n 2.2900e-06, 1.2622e-01, 2.6069e-01, 1.7780e-01, 2.9830e-02,\n 9.4326e-02, 2.2701e-01, 1.9688e-01, 2.1882e-01, -2.7017e-06,\n 1.2220e-01, 7.5014e-02, 1.2832e-01, 8.5417e-02, 1.6291e-01,\n 8.4596e-02, 1.9402e-01, 1.6017e-01, 3.6475e-07, 2.3727e-01,\n 9.6206e-02, 9.8700e-02, 1.0533e-01, -4.4109e-06, 6.2882e-02,\n 1.9133e-01, 1.5387e-01, 1.0403e-01, 1.6535e-01, 2.1686e-01,\n 1.4239e-01, 2.2955e-01, 1.5080e-01, -1.2674e-03, 1.3902e-01,\n 8.5259e-02, 3.4642e-02, 9.9039e-02, 2.4904e-01, 6.9841e-02,\n 8.3124e-02, 2.4294e-01, 1.4483e-01, 3.1757e-02, 1.1015e-01,\n 1.4036e-01, 3.1919e-04, 2.6469e-02, 2.1261e-01, 3.1144e-01,\n 3.8289e-02, 1.4501e-01, 7.5515e-02, 1.2624e-01, 8.4435e-07,\n 1.5350e-01, 1.4073e-01, 6.1724e-02, 2.2941e-01, 2.5614e-02,\n 1.0534e-01, 2.6670e-01, 5.9685e-02, 2.8428e-06, 6.3810e-02,\n 2.3985e-03, 1.3340e-01, 8.8923e-02, 1.1278e-01, 2.0682e-02,\n 2.7739e-01, 5.5902e-02, 2.1307e-01, 1.7146e-01, 7.7722e-02,\n 6.7209e-02, 1.1543e-01, 4.6488e-02, 7.6764e-02, 1.3236e-01,\n 1.2145e-01, 1.1983e-01, 7.4065e-02, 2.9635e-01, -1.7493e-06,\n 1.9132e-06, 9.8736e-02, 6.0385e-02, 2.2797e-01, 5.8966e-09,\n 2.5619e-02, 1.6748e-01, 2.1671e-01, 2.2459e-01, 3.6150e-01,\n 2.8499e-01, 5.5654e-02, 2.7252e-01, 7.2379e-02, 2.1270e-01,\n 1.2923e-04, 8.3425e-02, 1.0576e-01, 1.6487e-01, 1.7846e-01,\n 1.8283e-01, 8.8660e-02, 7.1795e-07, 9.0984e-02, 1.9297e-01,\n 1.5472e-01, 8.5600e-02, 1.7427e-01, 1.1005e-01, 1.7787e-01,\n 9.2511e-02, 1.4382e-01, 1.8540e-01, 2.0488e-01, 1.0983e-01,\n 2.8291e-01, 1.0290e-01, 2.0830e-01, 1.1883e-01, 1.0847e-01,\n 1.0995e-01, 5.9085e-02, 1.4754e-01, 1.5151e-06, 2.1499e-01,\n 9.7562e-02, 1.3178e-01, 1.8838e-01, -1.3624e-07, 1.0629e-01,\n 1.6661e-01, 7.8254e-02, 9.3795e-02, 8.6764e-05, 9.8791e-02,\n 3.4343e-01, 3.0137e-01, 1.3332e-01, 3.7465e-02, 2.5121e-01,\n 1.1898e-01, 5.3422e-02, 2.1665e-01, 9.4354e-06, 2.4696e-01,\n 2.0986e-01, 2.5194e-01, 2.0311e-06, 1.9968e-01, 1.2404e-01,\n 6.6729e-02, 2.1871e-01, 7.7020e-02, 2.7100e-01, 6.7304e-02,\n 3.1770e-04, 2.3104e-01, 1.1025e-01, 4.5252e-02, 6.8790e-02,\n 5.0323e-07, 1.8729e-01, 1.9567e-02, 1.7832e-01, 9.1058e-06,\n -1.1478e-02, 1.3999e-01, 1.1835e-01, 1.4631e-01, 2.2847e-01,\n 1.0294e-01, 1.4038e-01, 6.6081e-02, 2.4701e-01, 2.4612e-01,\n 3.1893e-01, 9.3287e-07, 1.7977e-01, 2.7202e-01, 1.1103e-01,\n 2.0467e-01, 1.3426e-01, 2.1761e-01, 2.4957e-01, 2.9877e-01,\n 1.1854e-01, -2.1788e-08, 3.7019e-02, 9.7481e-02, 2.8520e-01,\n -1.1039e-06, 4.2144e-02, 2.0087e-01, 9.6810e-02, 2.5079e-07,\n 8.4145e-02, 4.5465e-02, 1.5436e-01, 2.2429e-01, -2.2714e-03,\n 2.0405e-01, 8.1799e-02, 1.7233e-01, 2.9152e-06, 6.0585e-02,\n 8.2246e-02, 1.6369e-01, 2.6506e-01, 4.3962e-02, 5.7825e-02,\n 1.6734e-01, 7.4994e-02, 4.3876e-08, 6.2260e-02, 1.8669e-01,\n 5.3609e-02, 9.8477e-02, 2.8263e-01, 9.5169e-02, 6.4151e-02,\n 2.5783e-02, 2.1409e-01, 1.7208e-02, 5.0337e-02, 4.3892e-08,\n 6.2156e-02, 7.5510e-06, 5.8744e-02, 4.6921e-02, 2.0314e-01,\n 6.1390e-05, 3.1272e-01, 5.0435e-02, 2.2654e-01, 4.6576e-02,\n 1.5671e-01, 2.7796e-01, 1.0143e-01, 7.7886e-02, 1.9232e-01,\n 4.6385e-02, 2.2279e-01, 7.2706e-02, 1.2879e-01, 4.1680e-02,\n 1.9123e-01, 4.8767e-02, 1.2984e-01, 3.6433e-02, 1.3312e-01,\n 1.1975e-01, 4.8339e-02, 5.1418e-02, 2.2925e-01, 6.6953e-02,\n 2.4234e-01, 2.8563e-02, 3.0139e-01, 2.3045e-01, 2.3291e-01,\n 4.6171e-05, 9.0080e-02, 8.7562e-07, 1.4014e-01, 4.8940e-02,\n 2.1190e-01, 1.2955e-01, 8.6879e-02, 6.3741e-02, 1.3162e-01,\n 1.6884e-01, 1.8746e-01, 7.7271e-02, 1.5858e-01, 1.7510e-01,\n 3.2000e-01, 2.8692e-02, 1.3079e-01, 1.1904e-01, 1.0042e-01,\n 2.8212e-01, 3.5598e-04, 5.7799e-02, 8.5295e-02, 1.4939e-01,\n 1.1860e-01, 3.9204e-02, 4.2354e-05, 2.3282e-01, -7.8637e-06,\n 8.1989e-02, 1.4976e-01, 5.8519e-02, 1.1507e-01, 1.5949e-01,\n 1.2652e-01, 6.5645e-02, 1.3944e-01, 1.5968e-01, 3.4834e-01,\n 8.3482e-02, 2.7767e-06, 6.0657e-08, -2.3011e-07, 2.5447e-01,\n 9.5803e-02, 4.6457e-02, 3.4183e-01, 2.0945e-07, 1.5123e-01,\n 5.7456e-02, 2.1479e-01, 9.1830e-02, 8.2543e-02, 1.5812e-01,\n -2.9826e-08, 1.3071e-01, 1.7724e-01, 1.8948e-01, 1.0188e-01,\n 9.4392e-02, 7.0258e-02, 1.5887e-07, 3.3889e-01, 8.6709e-02,\n 1.7729e-01, 1.0908e-01, 2.3407e-01, 6.0903e-02, 1.7340e-01,\n 2.2216e-01, 1.0164e-01, 2.6807e-01, 3.0605e-02, 2.5506e-01,\n 1.9174e-01, 1.1581e-08, 1.7566e-01, 6.8024e-02, 2.1692e-01,\n 2.1478e-01, 2.1097e-01, 1.5198e-01, 2.8608e-01, 2.0977e-01,\n 1.3812e-01, 1.4606e-01, 2.2817e-01, 2.0661e-01, 5.4122e-02,\n 1.5023e-01, 2.0152e-01, 1.0224e-01, 3.2730e-01, 1.3787e-05,\n 1.6877e-01, 8.7145e-02, 1.0302e-01, 1.9743e-01, 1.6231e-01,\n 1.7920e-06, 2.0808e-01, 1.4886e-01, 1.3305e-01, 1.9893e-02,\n 9.5783e-02, 1.3257e-01, 8.8533e-02, 4.6299e-02, 2.1269e-01,\n -1.3488e-02, 1.1509e-01, 1.9692e-01, 1.5157e-01, 8.8719e-02,\n 5.8094e-02, 2.2648e-05, 2.5804e-01, 2.2469e-01, 1.0589e-01,\n 2.6049e-02, 4.2041e-02, 1.5114e-01, 1.0736e-01, 1.2608e-01,\n 3.1654e-01, 3.6467e-01, 1.5305e-01, 1.4385e-01, 5.6045e-02,\n 4.6438e-07, 3.4942e-01, 2.1350e-02, 2.1010e-01, 2.4005e-01,\n 1.9154e-01, 2.6363e-01, 1.1007e-01, 1.1057e-01, 3.3806e-07,\n 1.2993e-01, 7.7208e-02, 1.7599e-01, 5.9839e-08, 1.0211e-01,\n 4.3633e-02, 9.0415e-02, 9.0694e-03, 2.5682e-01, 1.3450e-01,\n 9.6971e-02, 6.2193e-02, 8.3240e-02, 1.9054e-01, 2.2685e-01,\n 5.3872e-02, 2.9870e-07, 7.7488e-02, 1.6893e-01, 1.2898e-01,\n 2.2102e-06, 6.6114e-02, 3.8978e-02, 1.4840e-06, 3.7466e-01,\n 8.1198e-02, 3.5721e-02, 1.2506e-01, 1.3209e-01, 5.3634e-02,\n 8.7965e-02, 2.3550e-01, 2.7244e-01, 2.7956e-01, 1.0065e-01,\n 8.5840e-02, -2.4200e-07, 8.0170e-02, 1.7799e-01, -2.7752e-05,\n 6.3721e-02, 5.6049e-07, 1.0697e-07, 5.9467e-02, 9.6309e-04,\n 2.4954e-01, 5.7962e-02, 1.0379e-01, 3.5687e-01, 2.6085e-01,\n 4.3701e-02, 2.4195e-02, 2.7597e-02, 2.0601e-01, 2.4514e-01,\n 9.3253e-02, 2.1202e-02, 7.8078e-08, 2.5881e-01, 6.0697e-02,\n 1.1231e-01, 3.3074e-01, 1.4187e-08, 2.1977e-01, 1.7850e-01,\n 1.2060e-01, 2.1658e-01, 1.3639e-01, 1.3979e-01, 2.5539e-02,\n 1.0469e-01, 1.3676e-01, 9.8885e-02, 1.3933e-01, 7.5356e-02,\n 1.0392e-01, -1.2151e-06, 1.6287e-01, 1.8783e-01, 2.6180e-01,\n 4.4862e-02, 8.1100e-02, 1.4853e-01, 8.6906e-02, 2.9029e-01,\n 2.3909e-01, 9.2808e-02, 1.9357e-01, 1.5000e-08, 1.2966e-01,\n 1.4273e-01, 1.9589e-01, 5.3727e-02, 1.5235e-01, 7.8051e-02,\n 2.7537e-01, 2.4821e-01, 1.4319e-01, 1.5251e-01, 1.8631e-07,\n 7.2372e-02, 2.5942e-01]), 'model.layer2.0.downsample.1.bias': tensor([ 5.0834e-02, -4.9077e-02, -6.7327e-03, 1.9894e-02, 3.7655e-02,\n -7.9189e-06, 1.1055e-02, 8.4496e-02, 3.3037e-02, 6.3673e-02,\n -8.4341e-05, -2.9828e-02, 6.7897e-03, 8.3709e-02, -1.7023e-05,\n -2.0068e-02, -3.3362e-02, 3.7563e-02, 4.3028e-02, -1.8203e-03,\n 4.4003e-02, 6.7282e-02, -1.4415e-02, -8.6219e-07, 1.7616e-02,\n 6.2465e-02, 2.3539e-03, -2.6935e-02, -3.1902e-05, 5.3920e-02,\n -9.6259e-02, 6.9395e-02, 3.2581e-02, -1.2491e-02, 5.1481e-03,\n -2.9016e-02, 9.1588e-02, 4.8823e-02, -5.4377e-03, 7.2925e-02,\n -3.9511e-02, 1.8236e-02, -2.4880e-02, 3.5841e-02, 6.7832e-03,\n -5.7434e-02, 7.2637e-02, -3.6747e-02, 6.7101e-02, -5.5490e-02,\n 9.2174e-02, -1.5524e-03, 5.6394e-02, 4.2435e-02, 8.8194e-02,\n 1.0468e-02, -4.6608e-03, -3.1827e-03, 8.3859e-03, -4.0713e-06,\n 4.3254e-02, -8.6418e-03, -1.2451e-03, -1.6065e-04, -8.1947e-03,\n 8.9926e-03, -1.0028e-01, 4.3496e-02, -7.8888e-06, -6.8866e-04,\n 6.4236e-03, 2.5530e-02, -9.8615e-03, -5.5630e-03, -4.2850e-02,\n 4.7188e-02, -2.1013e-02, 9.8083e-02, 1.9405e-02, -5.6787e-02,\n 7.8191e-03, 1.8706e-02, -2.5680e-02, 2.6439e-02, -1.7403e-03,\n 4.6873e-02, 5.8927e-02, -2.6867e-03, 8.3420e-02, -1.0144e-05,\n -7.6508e-06, -4.7262e-02, -5.6446e-02, 4.2935e-02, -1.5890e-07,\n -1.8265e-02, 1.4940e-02, 3.3675e-02, -8.1817e-03, -2.1246e-02,\n -4.6000e-03, -3.2776e-02, 8.8999e-02, 2.4027e-02, 1.1350e-01,\n -8.9958e-04, 3.8284e-02, -4.0489e-02, -5.3689e-03, -2.1906e-02,\n 7.6661e-02, 5.4796e-02, -2.8526e-06, -2.1416e-02, 1.0094e-01,\n 6.5590e-02, -3.6022e-03, -1.2144e-02, 3.3670e-02, 5.0224e-02,\n -1.9256e-02, 3.5518e-02, 7.7969e-02, 1.1642e-03, -4.2843e-02,\n 1.6325e-01, -3.5453e-02, 5.6190e-02, -1.2538e-03, -3.8911e-02,\n -1.3372e-02, 1.7887e-02, 2.5722e-02, -7.1322e-06, 9.3343e-02,\n -6.3560e-03, 1.5494e-03, 1.3458e-02, -1.4194e-06, -2.9466e-04,\n 9.6760e-03, -2.5608e-02, -1.9833e-02, -4.8029e-04, -4.0123e-02,\n 5.3387e-03, 5.1415e-02, -2.2941e-02, 2.2118e-02, -2.2908e-02,\n -1.7613e-03, 3.2486e-02, 6.6462e-02, -6.2677e-05, 1.1092e-01,\n 2.6414e-02, 8.9002e-02, -9.1733e-06, 3.3761e-02, -6.4337e-03,\n -1.4307e-02, 1.1110e-01, 3.2314e-02, 3.1876e-02, 5.9272e-02,\n -1.3884e-03, -2.0293e-02, -3.5694e-02, -4.0915e-02, -1.4256e-02,\n -1.3500e-06, -2.2835e-03, 9.0950e-02, 1.5382e-01, -2.7238e-05,\n -5.3157e-02, 9.7019e-02, -4.0202e-02, 5.5121e-02, -2.0945e-02,\n -4.2598e-02, -6.8659e-03, 1.5319e-02, 3.8783e-02, 8.0118e-03,\n 1.2944e-01, -2.8239e-06, 1.3769e-02, 7.1490e-02, -3.2435e-02,\n 1.7839e-03, -1.8380e-02, 2.2649e-02, 1.1004e-01, 1.5524e-01,\n 4.9853e-03, -1.1732e-07, -2.6311e-02, 3.9022e-03, 2.5377e-03,\n -6.2902e-06, 4.7875e-02, -5.3681e-03, 4.1534e-02, -7.1198e-07,\n -4.4762e-02, 1.9327e-02, 3.7311e-02, 4.3841e-02, -1.3019e-02,\n -7.6676e-03, 7.6830e-02, 4.5697e-02, -1.0135e-05, -2.3555e-02,\n -2.1732e-02, -1.3449e-02, 1.3110e-01, 1.6816e-02, 2.0754e-02,\n 5.1336e-02, -8.8543e-03, -1.2968e-07, -2.6250e-02, 3.1023e-02,\n 2.2531e-02, 5.4253e-02, 1.9927e-01, 1.5372e-02, 6.7338e-03,\n -2.6483e-03, 7.6939e-02, 1.0131e-01, -3.5332e-02, -1.1165e-07,\n 4.6136e-02, -2.7389e-05, -1.8186e-02, 4.4463e-02, -4.6612e-03,\n -1.8436e-04, 1.8990e-01, 2.9364e-02, 8.5756e-02, 1.1440e-02,\n -4.5376e-02, 2.0764e-02, -1.9064e-03, -4.4344e-02, 4.2163e-02,\n 3.4994e-02, 1.4637e-01, -2.4943e-03, 4.4574e-03, 2.5483e-02,\n 6.9906e-02, -3.1308e-02, -1.3978e-02, 3.2223e-02, -6.0031e-04,\n -4.6819e-02, 2.3282e-02, 2.4065e-03, 6.6848e-02, 5.4479e-03,\n 1.0452e-01, 2.8558e-02, 1.6056e-02, 6.2350e-02, 4.1735e-02,\n -1.2237e-04, -2.2317e-02, -3.2690e-06, 6.3187e-02, 1.0923e-02,\n 4.5637e-02, 2.4988e-03, 6.5815e-02, -1.5194e-02, -4.6845e-02,\n -1.4582e-02, 1.1561e-02, -1.7258e-02, 4.9623e-02, 8.4348e-02,\n -3.3495e-02, 1.2883e-02, -7.6839e-03, -3.1304e-02, -4.7099e-02,\n -1.3767e-02, -9.8877e-04, -4.5615e-02, -5.3457e-02, -8.2705e-02,\n 2.0353e-03, 3.9430e-02, -9.5408e-05, 2.7815e-02, -1.2186e-03,\n 1.1368e-02, -2.4319e-02, 5.8323e-03, 4.0933e-02, -1.7825e-02,\n -8.5407e-03, -4.6759e-02, 1.8576e-02, 1.3593e-02, -5.7132e-02,\n -2.7901e-02, -1.7975e-05, -2.4256e-07, -2.3200e-06, 8.8974e-02,\n -2.0184e-02, -3.6667e-03, 1.4330e-01, -5.4095e-07, 8.1132e-02,\n 2.1760e-02, 6.0346e-03, 1.4534e-02, 1.1589e-04, 3.7186e-02,\n -1.5115e-07, -6.7433e-02, -1.3699e-02, 3.0056e-03, 3.8657e-02,\n 7.2264e-02, -6.7452e-04, -6.0793e-07, -6.9888e-02, 1.4458e-03,\n 2.6498e-02, -2.1198e-02, 7.2501e-02, -2.9475e-02, -3.0987e-02,\n 8.9529e-02, 7.2748e-03, 1.1690e-01, -3.0943e-02, 1.1331e-01,\n 1.3392e-02, -1.8967e-07, 8.5637e-02, 5.5860e-03, 1.4101e-01,\n -5.0247e-03, -9.8680e-02, -1.9396e-02, 3.0411e-02, 1.4446e-01,\n -3.5790e-03, 3.3711e-02, 1.4874e-01, 1.8345e-02, -2.8280e-02,\n 2.5847e-02, 3.2509e-02, -4.7404e-03, -4.0921e-02, -6.7543e-05,\n -3.7236e-02, 1.2577e-03, -1.5731e-02, 5.9471e-02, -3.2187e-02,\n -5.0082e-06, 1.0503e-01, 2.7247e-02, 1.3641e-02, 7.1566e-02,\n -3.4105e-02, -3.1445e-02, 4.1694e-03, -1.6897e-02, 6.1689e-02,\n -2.6501e-02, -1.0475e-02, 1.2626e-01, 4.1497e-02, -5.9193e-03,\n 1.1730e-02, -5.9827e-05, 8.4875e-02, 5.6433e-02, -1.7832e-02,\n 1.0870e-03, 1.5394e-02, 7.1454e-02, -4.9118e-02, -1.0158e-02,\n 1.3767e-01, 8.3597e-02, -5.8024e-02, 9.3476e-03, 3.0341e-02,\n -1.9198e-06, -2.4033e-02, -1.5026e-02, 7.4188e-03, -6.8561e-02,\n -6.1679e-02, 2.8765e-02, 1.6927e-03, 7.8538e-03, -9.6343e-07,\n 5.6390e-03, 2.5071e-03, 1.1709e-01, -2.4052e-07, 3.5965e-03,\n -2.9915e-02, 6.3756e-04, -2.4417e-02, -2.1534e-02, 1.7838e-02,\n -1.4226e-02, -4.9004e-02, 1.5733e-03, -1.6215e-02, -4.5628e-03,\n -2.2838e-02, -1.9253e-06, 4.4060e-03, -1.0329e-02, -1.1512e-03,\n -8.7646e-06, 4.7309e-02, 8.8067e-02, -8.0243e-06, -1.7264e-01,\n -1.5183e-02, -4.1436e-02, -5.1695e-02, -3.6572e-03, 8.5591e-03,\n 1.0878e-02, 5.7972e-02, -6.6692e-02, 1.6173e-01, 6.3349e-02,\n -2.8691e-02, -2.3525e-06, 4.4352e-03, -1.1629e-02, -1.6837e-04,\n -2.0481e-02, -2.3380e-06, -4.7066e-07, 3.3126e-02, -4.4317e-03,\n 7.6798e-03, 6.7975e-02, -2.7854e-02, 9.1272e-02, 1.1165e-01,\n -1.0632e-02, 6.0867e-02, -2.5826e-02, 3.4329e-02, 1.6916e-01,\n 1.3250e-02, -1.9785e-02, -3.8024e-07, 4.9826e-02, -1.5098e-02,\n -2.7743e-02, 1.4274e-01, -1.0422e-07, 6.1897e-02, 8.5070e-02,\n 1.3790e-02, 6.8949e-02, -2.4559e-03, -3.1927e-03, -5.6222e-02,\n -8.7371e-03, 4.5338e-03, 1.7333e-02, -3.6611e-02, -1.2728e-02,\n -1.3143e-02, -1.6550e-05, 3.3299e-02, 7.5311e-02, -1.0978e-02,\n -3.3621e-02, -5.9845e-02, 5.5580e-02, 4.0376e-02, 9.9984e-02,\n -4.7201e-02, -1.4597e-02, -5.5442e-02, -6.0001e-08, 9.6936e-03,\n 5.9480e-02, -1.0083e-01, -2.4799e-02, 1.2643e-03, 1.2939e-02,\n 7.4288e-02, 2.9965e-02, -1.6249e-02, -4.2799e-02, -8.7138e-07,\n 7.5978e-02, 1.6202e-01]), 'model.layer2.0.downsample.1.running_mean': tensor([-5.1494e-02, -3.4200e-02, 1.5244e-02, 9.9552e-02, 3.0875e-02,\n -9.5126e-06, -7.4565e-02, -2.9151e-02, 1.3913e-01, -3.1685e-02,\n 3.9955e-02, -7.3408e-02, -9.7464e-02, -2.8860e-02, -5.9779e-06,\n -8.5015e-02, 1.2746e-01, 1.1992e-01, -4.0742e-02, 1.5534e-02,\n -2.8876e-02, -5.6134e-02, -9.3357e-02, -6.0939e-07, 3.2722e-02,\n -7.8473e-02, 2.0565e-02, -2.4481e-02, 1.5274e-05, -6.9021e-02,\n 1.0172e-03, -2.3125e-01, 1.0290e-02, -2.1377e-01, 1.0227e-01,\n 2.8100e-02, -1.1899e-01, -1.9452e-02, -5.3655e-03, -5.3225e-02,\n -1.3558e-02, -6.5388e-03, -1.1410e-01, -1.1632e-01, 8.6672e-02,\n 1.5987e-03, 3.2145e-01, -1.4395e-02, 1.4354e-02, 3.9411e-02,\n 1.2270e-03, 2.4547e-03, 6.1737e-02, -1.5356e-01, -7.7385e-02,\n 2.1861e-02, -5.3690e-03, -8.6291e-03, -1.8018e-01, 3.2186e-06,\n 1.7535e-01, 1.6793e-02, -1.5368e-02, 2.9967e-01, 9.8743e-02,\n -4.0577e-03, -3.1102e-02, -1.3835e-01, 9.8944e-06, -2.1008e-02,\n -9.2743e-02, -2.0274e-02, -1.4976e-01, -4.7787e-02, -3.1984e-02,\n -4.1896e-01, -4.8994e-02, -3.6580e-02, -9.6157e-02, 5.7637e-02,\n 6.9121e-02, 4.0654e-02, -5.3441e-02, 3.8249e-02, -1.5450e-01,\n -1.4380e-01, -1.4130e-01, -3.4571e-02, 1.2586e-01, 4.7157e-06,\n -8.8239e-06, -4.6050e-03, -1.6682e-02, 1.5990e-01, 1.4460e-07,\n -2.5262e-02, 2.0516e-01, 2.6793e-01, 2.8471e-01, 2.0728e-01,\n 5.9970e-02, -3.3379e-02, 7.8618e-02, 9.5349e-02, -4.5227e-02,\n -4.4244e-04, 7.2037e-02, -9.3071e-02, 5.2790e-02, -4.9935e-02,\n -4.0144e-01, 7.3325e-02, -2.2793e-06, -1.0787e-01, -9.3281e-02,\n 1.1547e-01, 1.1470e-01, -1.9383e-01, -6.9215e-02, -6.8437e-02,\n -8.9409e-02, -5.1472e-02, -1.4683e-03, -5.6333e-03, -1.9213e-02,\n -1.5533e-01, -1.0694e-01, -1.2464e-01, -1.0615e-01, -1.2645e-01,\n -8.9637e-02, 1.0236e-02, -7.8950e-03, 4.7539e-06, -8.8186e-02,\n -1.0535e-01, -7.8422e-02, -1.0059e-01, 1.8397e-06, -1.7196e-02,\n -7.0751e-02, -6.6775e-02, -4.8048e-02, -5.4936e-05, 9.2941e-04,\n -2.4341e-01, 7.8635e-03, -6.7531e-02, 5.9265e-04, -1.1725e-01,\n 6.3332e-02, -6.8120e-02, -9.9978e-02, 5.8937e-05, 7.9082e-02,\n -5.2833e-02, 1.2625e-01, -3.1564e-06, 9.4257e-02, 6.9458e-02,\n 7.0997e-02, -2.5035e-01, 6.0399e-03, 3.0550e-03, -5.9067e-02,\n 1.4415e-03, -3.3051e-02, -4.7765e-02, 5.0178e-02, 5.1502e-03,\n 2.5458e-07, -5.6236e-02, -7.9061e-02, -4.9046e-02, -2.5835e-05,\n 1.4821e-02, -1.2499e-01, -8.9138e-02, 1.2298e-01, -1.5778e-02,\n 1.4793e-01, -5.8426e-02, -5.4780e-02, 1.5189e-01, -4.1092e-02,\n -1.2049e-01, -4.8331e-06, -4.5806e-02, -5.9576e-02, 1.9365e-01,\n -1.3244e-01, 3.4717e-02, 1.5543e-02, -1.4416e-01, 7.2557e-02,\n -7.1049e-02, 2.3511e-08, -1.6318e-03, -1.0574e-01, 2.6456e-01,\n 3.4350e-06, -2.4238e-03, -1.0138e-02, -5.5122e-02, -7.7622e-07,\n -7.0377e-02, -4.3843e-02, -1.4770e-01, -1.2912e-01, -2.0321e-02,\n 7.4068e-02, 3.4340e-04, -2.5603e-01, -1.0122e-05, -3.7011e-02,\n 1.4616e-02, -9.4595e-02, -1.2611e-01, -7.8900e-02, -8.5303e-02,\n 2.4116e-02, -3.4063e-02, -2.3451e-07, -7.7975e-02, -4.2487e-02,\n -2.0526e-02, 3.4307e-02, -1.0794e-01, 2.6745e-02, -1.1022e-01,\n 6.0726e-03, 5.1916e-02, -6.0559e-02, -2.3276e-02, -1.1830e-07,\n 8.1495e-02, -4.1710e-05, -5.1419e-02, -7.0356e-02, -1.7159e-01,\n -7.4798e-05, -2.4341e-01, 4.4122e-02, -1.0517e-01, -7.6906e-02,\n -9.4440e-02, 1.2953e-01, -7.9873e-02, -5.8268e-02, 3.3151e-02,\n 8.6216e-03, -2.3912e-01, -6.8335e-02, -7.7786e-02, -3.0963e-02,\n 1.3942e-01, 7.9495e-02, -2.1287e-02, 2.0102e-02, -1.9002e-01,\n -3.9216e-02, 1.0049e-01, -4.7711e-02, -2.2911e-01, 1.6710e-02,\n -5.6067e-02, -4.9242e-02, -1.3610e-01, 3.6339e-02, 6.7277e-02,\n 2.3815e-04, -2.3254e-02, -6.5055e-08, 3.7634e-03, -1.8258e-02,\n -1.1410e-01, 1.4320e-02, -3.3789e-02, -6.3791e-02, -2.4148e-02,\n -3.7206e-02, -1.2796e-01, 1.2008e-02, 1.1259e-01, -7.3402e-02,\n 6.3834e-02, -6.9279e-02, 4.8657e-02, -8.8376e-02, -5.6269e-02,\n 7.5044e-02, -1.4919e-03, 7.2122e-05, 6.3626e-02, 4.4883e-03,\n -1.4006e-02, 3.1468e-03, 1.0584e-05, 9.3481e-02, 2.9683e-04,\n 4.0994e-02, -1.5514e-01, -3.6478e-02, -1.1323e-01, -2.1093e-01,\n -1.1583e-01, -6.2612e-03, -9.8456e-02, 7.0785e-02, 1.7377e-01,\n -4.8519e-02, -2.6506e-06, -3.4384e-07, 1.2361e-06, -8.1221e-03,\n 9.2822e-02, -3.1319e-02, -1.4969e-01, -1.7925e-07, 1.0613e-01,\n -3.8450e-02, 1.2934e-01, 7.1560e-02, -1.1351e-01, -5.3256e-02,\n 1.2374e-07, -1.6676e-01, -1.4126e-02, -2.8358e-02, -1.8973e-02,\n -1.1192e-01, 6.7761e-02, -2.1485e-06, -5.4737e-03, -1.3424e-01,\n -8.5759e-02, 7.1261e-02, 1.6633e-02, 7.7866e-02, 7.0906e-02,\n -5.9297e-02, 1.2769e-01, -4.7684e-01, -2.8294e-02, 1.0238e-01,\n -1.3284e-02, -6.2213e-08, -3.2179e-01, -1.9865e-02, 2.5758e-01,\n 2.2382e-02, -1.0474e-02, -3.9884e-02, -4.2099e-02, -1.5500e-01,\n -1.0262e-01, 3.1960e-02, -2.9903e-01, -8.5342e-02, 1.1899e-03,\n -1.3985e-01, -8.6824e-02, -8.5617e-02, 5.3615e-02, -1.2432e-04,\n 2.0587e-02, -8.5178e-02, 4.0394e-02, 6.0847e-02, -1.2978e-01,\n 2.0457e-06, -2.7623e-01, 5.7551e-02, 1.4730e-01, 3.9564e-02,\n 2.2296e-01, 1.0716e-01, -5.4350e-02, -2.5503e-02, -7.8661e-02,\n 4.7257e-02, -1.7208e-02, -2.3454e-01, 9.7573e-02, -3.4692e-02,\n 1.4882e-02, -4.2898e-05, 5.1740e-02, -1.5613e-01, -1.6091e-01,\n -2.4320e-03, -9.0669e-02, 1.0613e-01, 1.3265e-01, -5.8577e-02,\n 1.0569e-02, -9.5271e-03, 4.0287e-02, -6.4316e-02, 1.2627e-03,\n 8.7915e-07, -9.5728e-02, 1.8258e-02, -1.1543e-01, -1.1213e-01,\n -3.8751e-02, -6.8220e-02, -1.9392e-02, -3.1073e-02, 2.0723e-06,\n -1.0835e-01, -2.2189e-01, -2.2050e-01, -1.7649e-07, 4.8899e-02,\n -4.5984e-03, -7.7331e-03, -6.5538e-03, -1.0198e-01, -9.3513e-02,\n -4.7175e-03, -4.1204e-02, -1.1459e-02, -1.1549e-01, -3.2389e-02,\n -1.3938e-02, -9.7627e-07, -8.3975e-02, -3.5227e-03, -1.1286e-01,\n -7.0237e-06, -1.2664e-01, -7.9236e-02, -2.6279e-06, 1.4914e-01,\n 5.7039e-03, -8.8592e-04, -4.7614e-02, -6.6155e-02, -3.0336e-02,\n -3.4918e-02, -2.2736e-03, 4.4817e-02, -1.4666e-01, -5.3723e-03,\n -1.0448e-01, -1.0190e-06, 3.5251e-02, -5.9295e-02, 5.0465e-05,\n 1.2428e-01, 4.2824e-07, 9.2233e-08, -6.3308e-02, -3.8271e-03,\n -2.8248e-03, -6.1434e-02, 4.8685e-02, 2.8634e-01, -3.2100e-01,\n 2.5677e-02, 5.5749e-03, -9.4098e-02, -6.1421e-02, -3.3226e-02,\n -2.6313e-02, -7.3888e-03, 6.9471e-10, -1.2029e-01, 4.4325e-02,\n -2.3904e-02, -8.7518e-02, 5.4222e-08, 1.5282e-01, -6.3052e-02,\n -6.6893e-02, -1.8875e-01, 4.5119e-02, 7.5942e-02, 1.9861e-02,\n 1.0094e-01, -1.7717e-01, 1.9425e-01, -8.2651e-02, -1.2596e-01,\n 1.2080e-01, -1.3713e-05, -4.8514e-02, -2.1563e-01, -2.4228e-01,\n 2.5554e-02, 1.0412e-01, -2.6581e-02, 9.8107e-03, -1.7702e-01,\n -6.8835e-02, -4.1259e-02, 4.9592e-02, 1.6342e-09, -2.1512e-01,\n -1.7377e-02, -1.5371e-02, 4.8003e-02, 1.1801e-02, 9.0497e-03,\n -7.5383e-03, 1.1011e-01, -8.5890e-02, 4.8695e-02, -4.1990e-07,\n 5.0467e-02, -2.7258e-01]), 'model.layer2.0.downsample.1.running_var': tensor([4.0108e-02, 5.9022e-03, 1.9758e-04, 1.1750e-02, 1.8898e-02, 7.6707e-11,\n 1.1231e-02, 4.6329e-02, 2.7251e-02, 4.5001e-03, 4.2267e-03, 1.1909e-02,\n 2.2178e-02, 4.1602e-02, 4.0086e-11, 7.0469e-03, 9.4003e-03, 1.1912e-02,\n 1.0040e-02, 1.1718e-02, 1.0532e-02, 1.6382e-02, 1.6058e-02, 1.8147e-12,\n 1.9796e-02, 7.5455e-03, 6.4640e-03, 9.1774e-03, 2.0381e-10, 6.2323e-03,\n 1.2584e-02, 2.1563e-02, 1.4579e-02, 6.7111e-03, 1.0543e-02, 1.1221e-02,\n 5.5487e-02, 1.4509e-02, 1.5498e-05, 2.6282e-02, 7.4251e-03, 4.8472e-03,\n 4.4860e-03, 1.4650e-02, 5.3030e-03, 5.0246e-03, 7.4990e-03, 1.1456e-02,\n 4.6799e-03, 6.8461e-03, 2.5500e-02, 1.9955e-06, 5.9086e-03, 1.7941e-02,\n 4.6160e-02, 4.9382e-03, 9.2217e-03, 4.0137e-03, 1.7223e-02, 3.1763e-11,\n 2.3454e-02, 1.6756e-02, 4.2170e-03, 1.4039e-02, 2.6245e-03, 5.5266e-03,\n 1.1048e-02, 7.5043e-03, 1.4115e-10, 3.6541e-03, 1.8464e-03, 1.8337e-02,\n 7.6409e-03, 5.7093e-03, 4.2871e-03, 1.6457e-02, 3.0123e-03, 2.8361e-02,\n 3.3375e-02, 6.4739e-03, 6.9558e-03, 7.8341e-03, 3.4899e-03, 7.3748e-03,\n 1.3685e-02, 1.1679e-02, 9.8388e-03, 8.3112e-03, 6.3684e-02, 2.4334e-11,\n 7.6123e-11, 5.7267e-03, 3.7715e-03, 2.3362e-02, 7.9169e-15, 5.1006e-03,\n 1.5994e-02, 2.0457e-02, 1.5393e-02, 8.1003e-02, 1.8582e-02, 2.7796e-03,\n 5.0151e-02, 5.9074e-03, 4.6512e-02, 1.0857e-06, 8.4133e-03, 5.2448e-03,\n 1.7981e-02, 1.1735e-02, 1.7322e-02, 1.3828e-02, 4.4758e-12, 7.7755e-03,\n 1.7450e-02, 3.2944e-02, 6.8834e-03, 1.5271e-02, 9.4238e-03, 2.3891e-02,\n 7.3869e-03, 2.1917e-02, 3.0049e-02, 2.5507e-02, 7.0788e-03, 7.9102e-02,\n 1.3183e-02, 1.9995e-02, 9.1243e-03, 7.1698e-03, 1.6053e-02, 7.1020e-03,\n 1.7030e-02, 1.9297e-10, 3.0996e-02, 5.5069e-03, 1.1372e-02, 1.2701e-02,\n 4.6677e-13, 4.5256e-03, 2.9357e-02, 5.8541e-03, 5.0191e-03, 5.3028e-08,\n 4.8056e-03, 3.0222e-02, 1.5977e-02, 1.2170e-02, 4.4752e-03, 1.7961e-02,\n 1.1032e-02, 1.0086e-02, 2.1112e-02, 2.7429e-09, 4.6146e-02, 2.5225e-02,\n 4.1311e-02, 5.6025e-11, 1.6580e-02, 8.4484e-03, 6.8792e-03, 1.4554e-02,\n 1.4448e-02, 1.9588e-02, 4.0559e-03, 3.9662e-06, 2.0957e-02, 6.9433e-03,\n 4.0750e-03, 4.9251e-03, 1.8914e-12, 3.3303e-02, 5.0937e-03, 2.8188e-02,\n 7.9882e-10, 2.0607e-03, 2.3508e-02, 1.0387e-02, 1.4808e-02, 1.4209e-02,\n 5.2674e-03, 2.3322e-02, 8.5391e-03, 3.8543e-02, 1.9092e-02, 3.3705e-02,\n 1.8850e-11, 2.6005e-02, 4.2245e-02, 7.2634e-03, 4.4754e-02, 1.2972e-02,\n 1.3073e-02, 4.2765e-02, 8.4765e-02, 1.4100e-02, 3.5516e-15, 2.7700e-03,\n 8.3742e-03, 5.2579e-02, 3.9345e-12, 6.4790e-03, 1.8289e-02, 8.4780e-03,\n 1.2532e-12, 2.5235e-03, 3.3381e-03, 1.1462e-02, 6.5645e-02, 1.7948e-04,\n 1.0641e-02, 1.4229e-02, 3.9101e-02, 8.5117e-11, 3.9166e-03, 5.7764e-03,\n 1.7393e-02, 7.2899e-02, 7.3749e-03, 7.0937e-03, 2.3119e-02, 5.8676e-03,\n 7.5054e-15, 4.0042e-03, 3.3743e-02, 5.1534e-03, 8.9095e-03, 9.6275e-02,\n 1.1718e-02, 7.1739e-03, 3.7180e-03, 2.1800e-02, 3.0599e-03, 1.2640e-03,\n 1.6048e-14, 1.4569e-02, 2.2806e-09, 6.3714e-03, 5.8556e-03, 1.1582e-02,\n 1.5058e-08, 1.0255e-01, 4.9627e-03, 3.2192e-02, 5.6889e-03, 1.5644e-02,\n 1.2141e-02, 7.9325e-03, 4.8865e-03, 1.3180e-02, 2.6635e-03, 4.9325e-02,\n 4.9905e-03, 1.6956e-02, 4.9197e-03, 2.0845e-02, 4.4053e-03, 2.1105e-02,\n 3.9544e-03, 2.0867e-02, 5.2946e-03, 6.6504e-03, 7.7558e-03, 4.5953e-02,\n 7.5627e-03, 2.6599e-02, 3.7907e-03, 2.2974e-02, 3.4155e-02, 2.0341e-02,\n 2.1043e-08, 5.8011e-03, 9.1324e-12, 2.8863e-02, 5.7450e-03, 4.6773e-02,\n 1.0770e-02, 1.0097e-02, 5.7286e-03, 1.0623e-02, 1.1081e-02, 1.1425e-02,\n 5.6954e-03, 2.2208e-02, 4.0948e-02, 2.8968e-02, 6.1700e-03, 1.1263e-02,\n 8.0074e-03, 4.7704e-03, 3.2938e-02, 6.5867e-07, 3.9369e-03, 6.5243e-03,\n 6.2089e-03, 1.0588e-02, 7.2726e-03, 1.0563e-08, 2.1555e-02, 8.4442e-07,\n 9.1624e-03, 1.2380e-02, 3.2667e-03, 6.2799e-03, 8.2279e-03, 8.2997e-03,\n 2.5481e-03, 6.7048e-03, 1.3142e-02, 3.5099e-02, 6.4991e-03, 1.5075e-10,\n 1.6299e-13, 5.2938e-13, 2.5273e-02, 9.8461e-03, 6.9722e-03, 4.5871e-02,\n 6.6234e-13, 1.7216e-02, 7.7591e-03, 4.0651e-02, 7.9649e-03, 5.0947e-03,\n 1.9004e-02, 3.2217e-15, 7.4167e-03, 2.6613e-02, 2.4887e-02, 1.8719e-02,\n 1.5186e-02, 8.3486e-03, 5.8134e-13, 2.3335e-02, 5.8005e-03, 1.2276e-02,\n 6.8865e-03, 2.4106e-02, 6.1154e-03, 1.1789e-02, 4.1170e-02, 1.1382e-02,\n 2.8129e-02, 3.3656e-03, 5.6108e-02, 3.8962e-02, 1.0149e-14, 1.9409e-02,\n 5.3416e-03, 4.1821e-02, 2.6221e-02, 1.0779e-02, 1.7584e-02, 2.7974e-02,\n 5.8485e-02, 1.1996e-02, 2.0558e-02, 4.1314e-02, 1.6077e-02, 3.5219e-03,\n 1.8028e-02, 1.9238e-02, 1.0860e-02, 4.0010e-02, 1.8171e-09, 1.2630e-02,\n 6.8163e-03, 5.4125e-03, 3.0787e-02, 1.0820e-02, 2.2871e-11, 2.0710e-02,\n 1.7023e-02, 1.4118e-02, 4.2585e-03, 8.6494e-03, 1.0022e-02, 9.3197e-03,\n 4.0051e-03, 2.8197e-02, 2.1347e-03, 9.5634e-03, 1.8450e-02, 1.0896e-02,\n 9.9629e-03, 5.7616e-03, 5.8486e-09, 4.4991e-02, 2.8465e-02, 7.6301e-03,\n 4.6009e-03, 4.1795e-03, 2.5524e-02, 3.5220e-03, 2.8559e-02, 9.6070e-02,\n 1.8841e-02, 8.5170e-03, 1.6350e-02, 8.6296e-03, 1.8948e-12, 4.1053e-02,\n 2.3594e-03, 1.1217e-02, 1.0403e-02, 1.6333e-02, 3.3128e-02, 1.4701e-02,\n 4.4597e-03, 7.9827e-13, 9.0481e-03, 8.3619e-03, 2.4073e-02, 1.9202e-14,\n 1.4766e-02, 1.8754e-03, 5.3685e-03, 1.7824e-03, 1.5752e-02, 3.2000e-02,\n 1.1554e-02, 3.5065e-03, 6.0218e-03, 3.2324e-02, 7.8774e-03, 4.8347e-03,\n 3.0184e-12, 7.3819e-03, 2.8272e-02, 7.1594e-03, 6.8424e-11, 5.3134e-03,\n 7.3182e-03, 5.0282e-11, 1.8210e-02, 4.5767e-03, 3.7676e-03, 8.0150e-03,\n 1.1794e-02, 3.7702e-03, 5.1505e-03, 3.2827e-02, 2.4580e-02, 1.3691e-01,\n 9.2217e-03, 1.0614e-02, 2.7633e-12, 9.4216e-03, 3.6578e-02, 4.1641e-08,\n 5.9897e-03, 4.4326e-12, 6.6778e-14, 5.9967e-03, 1.6353e-05, 4.2815e-02,\n 5.9243e-03, 5.1016e-03, 7.4039e-02, 3.3095e-02, 3.3083e-03, 7.0826e-03,\n 2.2721e-03, 3.1245e-02, 6.3295e-02, 7.3038e-03, 1.9498e-03, 1.0919e-13,\n 2.8405e-02, 5.1835e-03, 8.4422e-03, 1.1439e-01, 1.3715e-14, 2.8552e-02,\n 1.4836e-02, 1.1564e-02, 1.9696e-02, 3.9060e-03, 1.4313e-02, 3.1320e-03,\n 4.5995e-03, 1.1412e-02, 9.6281e-03, 1.3761e-02, 6.3437e-03, 7.3657e-03,\n 1.6457e-10, 1.9925e-02, 3.6221e-02, 2.3281e-02, 5.3451e-03, 8.1319e-03,\n 2.4187e-02, 1.2475e-02, 4.4540e-02, 1.5588e-02, 1.0321e-02, 1.1104e-02,\n 1.1835e-15, 1.5742e-02, 1.2606e-02, 7.8369e-03, 5.2505e-03, 1.1295e-02,\n 5.7751e-03, 1.7448e-02, 2.2761e-02, 1.0751e-02, 1.3395e-02, 1.3356e-13,\n 1.2496e-02, 3.1548e-02]), 'model.layer2.0.downsample.1.num_batches_tracked': tensor(7160), 'model.layer2.1.conv1.weight': tensor([[[[ 3.4852e-02]],\n\n [[ 5.6791e-03]],\n\n [[-7.3805e-04]],\n\n ...,\n\n [[-4.9786e-09]],\n\n [[-7.8674e-03]],\n\n [[ 6.1202e-02]]],\n\n\n [[[-6.8279e-03]],\n\n [[-6.6493e-03]],\n\n [[-4.6118e-04]],\n\n ...,\n\n [[ 3.6587e-09]],\n\n [[ 5.1035e-03]],\n\n [[-7.2080e-02]]],\n\n\n [[[-6.6098e-02]],\n\n [[-1.1080e-02]],\n\n [[ 4.3583e-05]],\n\n ...,\n\n [[-1.7033e-08]],\n\n [[ 3.1989e-03]],\n\n [[-3.4813e-02]]],\n\n\n ...,\n\n\n [[[ 2.6281e-02]],\n\n [[ 1.8157e-02]],\n\n [[ 1.4917e-03]],\n\n ...,\n\n [[ 5.4477e-08]],\n\n [[ 1.0077e-02]],\n\n [[-5.2985e-03]]],\n\n\n [[[-4.9629e-02]],\n\n [[-1.8374e-02]],\n\n [[-4.8183e-04]],\n\n ...,\n\n [[ 3.8903e-09]],\n\n [[-3.0356e-03]],\n\n [[ 1.7453e-02]]],\n\n\n [[[ 1.4627e-02]],\n\n [[ 2.0944e-02]],\n\n [[ 2.3914e-06]],\n\n ...,\n\n [[ 2.5520e-08]],\n\n [[ 1.0829e-02]],\n\n [[ 2.8182e-02]]]]), 'model.layer2.1.bn1.weight': tensor([0.1134, 0.0877, 0.0825, 0.1014, 0.1049, 0.1376, 0.0919, 0.1195, 0.1315,\n 0.0927, 0.1061, 0.1466, 0.1051, 0.1562, 0.0649, 0.1009, 0.0839, 0.1192,\n 0.0715, 0.0649, 0.1426, 0.0912, 0.1099, 0.1124, 0.2030, 0.0912, 0.1425,\n 0.1300, 0.1159, 0.2195, 0.0806, 0.1205, 0.0856, 0.1093, 0.1341, 0.1397,\n 0.1170, 0.1377, 0.2025, 0.1491, 0.1029, 0.0923, 0.0685, 0.1006, 0.1486,\n 0.1779, 0.0907, 0.0750, 0.1340, 0.1268, 0.1385, 0.1055, 0.1758, 0.1071,\n 0.0910, 0.1100, 0.1330, 0.0874, 0.1261, 0.1232, 0.1102, 0.1333, 0.1375,\n 0.0851, 0.1018, 0.0383, 0.0906, 0.0931, 0.0918, 0.0712, 0.1083, 0.1029,\n 0.1308, 0.1124, 0.0972, 0.1075, 0.1264, 0.1165, 0.0635, 0.1119, 0.1222,\n 0.1391, 0.1056, 0.1085, 0.0604, 0.1313, 0.1083, 0.1460, 0.0813, 0.1171,\n 0.1132, 0.1250, 0.2001, 0.1211, 0.0969, 0.0987, 0.0781, 0.1420, 0.1216,\n 0.0916, 0.1145, 0.1310, 0.1380, 0.1456, 0.1449, 0.1469, 0.1148, 0.1536,\n 0.0944, 0.1113, 0.1300, 0.0568, 0.1074, 0.1269, 0.1132, 0.0948, 0.0800,\n 0.1005, 0.1309, 0.1017, 0.1095, 0.0771, 0.1469, 0.0953, 0.1394, 0.0991,\n 0.1533, 0.1317]), 'model.layer2.1.bn1.bias': tensor([ 0.0633, 0.1382, 0.0951, 0.0337, -0.0480, 0.0582, 0.1160, 0.0029,\n -0.0473, 0.2315, 0.2399, 0.3078, 0.0673, -0.0679, 0.1050, 0.0044,\n 0.0847, 0.0628, 0.0710, 0.0993, -0.0300, 0.1521, 0.0280, -0.0654,\n -0.0308, 0.1988, -0.0720, -0.0440, 0.0023, -0.1868, -0.0043, 0.0461,\n 0.1728, 0.0698, -0.0776, 0.2440, -0.0257, -0.0901, -0.1050, -0.0027,\n 0.0310, 0.0217, 0.0053, -0.0406, -0.0189, -0.1961, 0.2076, 0.2075,\n -0.0853, -0.0385, -0.0389, 0.2097, -0.0708, -0.0185, -0.0401, 0.0459,\n -0.0413, 0.1661, -0.0622, -0.0085, 0.0308, -0.0502, -0.1022, 0.0127,\n 0.1640, 0.0755, 0.1325, -0.0287, 0.2604, 0.0027, 0.0730, 0.0253,\n -0.0168, 0.1188, -0.0407, 0.0718, 0.1694, -0.0294, 0.0593, 0.0314,\n 0.0290, -0.0170, 0.0116, 0.0230, 0.0898, -0.0529, 0.0829, -0.0629,\n 0.1227, 0.1768, -0.0689, -0.0130, 0.3842, 0.1079, 0.0968, 0.1910,\n 0.0175, -0.0016, 0.0585, -0.0475, -0.0274, 0.0138, -0.0530, -0.0895,\n 0.3840, -0.0179, 0.0497, -0.0565, 0.0254, 0.0150, -0.0669, 0.0417,\n 0.1967, 0.0566, 0.0618, -0.0261, 0.0575, 0.0428, -0.1035, 0.0388,\n 0.0212, 0.0636, -0.0608, 0.0272, -0.0428, 0.2389, 0.2599, -0.0752]), 'model.layer2.1.bn1.running_mean': tensor([ 0.2538, -0.0370, -0.0545, -0.0976, -0.1073, -0.0148, 0.1195, 0.0951,\n -0.0956, 0.1144, -0.1689, -0.2124, 0.1226, 0.0210, -0.0450, -0.0103,\n 0.0928, -0.1732, -0.0149, 0.0616, -0.0150, -0.0122, 0.0753, -0.0578,\n -0.1171, 0.0952, 0.0274, 0.0239, -0.0957, -0.0518, -0.0078, -0.0387,\n 0.1547, 0.0604, -0.0096, 0.2480, -0.1329, 0.1918, -0.0879, -0.1254,\n 0.0201, 0.0289, 0.1101, 0.1219, 0.1208, -0.2027, -0.0809, -0.1096,\n 0.0543, 0.0909, -0.0004, -0.1173, 0.0678, -0.0291, 0.0029, 0.0496,\n -0.0783, 0.1640, -0.1129, 0.0406, -0.1095, -0.1617, 0.0792, -0.0135,\n 0.1375, 0.0421, 0.1809, 0.0714, -0.1363, -0.0231, 0.0991, -0.0409,\n 0.0237, 0.2428, 0.0242, 0.0519, 0.0794, -0.0546, -0.0426, -0.0905,\n -0.0145, -0.0677, -0.0489, -0.1037, 0.0524, -0.0996, -0.0512, -0.0160,\n -0.0514, -0.0693, 0.0521, 0.1785, 0.3243, -0.0211, 0.0989, -0.0897,\n 0.0562, 0.0614, 0.1585, 0.0464, 0.0549, -0.0449, 0.0036, 0.0923,\n -0.3505, 0.0678, 0.0805, 0.0200, 0.0043, -0.1514, -0.2075, -0.0747,\n -0.2897, 0.0506, -0.0655, 0.1800, -0.0108, 0.0568, 0.1576, 0.1015,\n -0.0525, 0.0126, 0.0757, 0.0012, 0.0463, -0.1391, 0.0894, 0.0247]), 'model.layer2.1.bn1.running_var': tensor([0.1277, 0.0533, 0.0474, 0.0152, 0.0141, 0.0410, 0.1101, 0.0549, 0.0139,\n 0.0657, 0.0381, 0.1595, 0.0931, 0.0447, 0.0160, 0.0349, 0.0326, 0.0251,\n 0.0167, 0.0287, 0.0197, 0.0557, 0.0345, 0.0132, 0.0962, 0.1024, 0.0124,\n 0.0078, 0.0308, 0.0421, 0.0217, 0.0560, 0.1245, 0.0817, 0.0123, 0.2713,\n 0.0259, 0.0254, 0.0296, 0.0279, 0.0365, 0.0343, 0.0138, 0.0111, 0.0177,\n 0.0249, 0.0926, 0.0660, 0.0143, 0.0268, 0.0268, 0.0402, 0.0180, 0.0102,\n 0.0273, 0.0538, 0.0446, 0.1393, 0.0387, 0.0330, 0.0212, 0.0181, 0.0452,\n 0.0229, 0.0265, 0.0302, 0.1077, 0.0213, 0.1059, 0.0129, 0.0414, 0.0262,\n 0.0289, 0.0436, 0.0284, 0.0376, 0.0270, 0.0562, 0.0311, 0.0301, 0.0317,\n 0.0929, 0.0127, 0.0183, 0.0361, 0.0135, 0.0315, 0.0123, 0.0418, 0.1412,\n 0.0106, 0.0140, 0.4522, 0.0242, 0.0911, 0.0791, 0.0354, 0.0373, 0.0877,\n 0.0052, 0.0194, 0.0426, 0.0551, 0.0380, 0.2857, 0.0198, 0.1117, 0.0190,\n 0.0301, 0.0431, 0.0313, 0.0307, 0.0504, 0.1134, 0.0281, 0.0160, 0.0649,\n 0.0135, 0.0329, 0.0411, 0.0194, 0.0186, 0.0215, 0.0676, 0.0307, 0.1908,\n 0.2532, 0.0271]), 'model.layer2.1.bn1.num_batches_tracked': tensor(7160), 'model.layer2.1.conv2.weight': tensor([[[[-2.9449e-02, -4.2878e-02, -2.2652e-02],\n [-3.6452e-02, -7.8070e-03, -3.3627e-02],\n [-3.4823e-02, -3.7785e-02, -3.2083e-02]],\n\n [[ 2.5856e-03, 3.8393e-03, 2.2831e-04],\n [ 4.2873e-03, 1.5389e-02, 1.7554e-04],\n [ 6.3191e-03, 1.1151e-02, 8.4535e-03]],\n\n [[ 9.6038e-03, 2.3265e-02, 1.2359e-02],\n [ 2.6252e-02, -3.8545e-02, 2.4417e-02],\n [ 2.3389e-02, 2.7451e-02, 2.2812e-02]],\n\n ...,\n\n [[ 1.4541e-03, 7.0364e-04, 9.4004e-04],\n [-1.1366e-03, -2.4213e-02, -3.7518e-03],\n [ 7.6501e-03, 2.9514e-03, -1.7097e-03]],\n\n [[ 4.3779e-04, 1.7109e-02, 9.0890e-03],\n [ 1.6029e-02, 1.0388e-02, 1.9057e-02],\n [ 1.4539e-02, 2.8889e-02, 1.7098e-02]],\n\n [[ 1.4323e-02, 1.2092e-02, 1.9529e-02],\n [ 2.5923e-03, -2.9038e-02, -6.0629e-04],\n [ 1.8995e-02, 1.5984e-02, 5.8482e-03]]],\n\n\n [[[ 1.4911e-02, 1.2273e-02, 1.2127e-02],\n [ 1.7952e-02, -4.5700e-02, 1.4789e-02],\n [ 9.6127e-03, 1.6139e-02, 1.9232e-02]],\n\n [[ 1.9188e-03, 8.8606e-03, 1.2366e-03],\n [ 9.0152e-03, 6.9561e-03, -7.9063e-03],\n [-7.2299e-03, -8.6111e-03, -1.5122e-02]],\n\n [[-8.8627e-03, -4.1148e-03, -1.4983e-03],\n [-1.6147e-02, -1.0115e-02, -1.3534e-02],\n [-1.1869e-02, -1.4026e-02, -1.1418e-02]],\n\n ...,\n\n [[-3.9241e-03, -8.1247e-04, -5.7673e-03],\n [ 1.0939e-02, -2.8038e-02, 9.3079e-03],\n [-3.1506e-03, 1.6006e-02, -1.7261e-03]],\n\n [[-4.8816e-03, -1.1077e-02, -9.0006e-03],\n [-1.9569e-02, 6.4565e-02, -3.2164e-02],\n [-1.4456e-02, -3.3793e-02, -2.8323e-02]],\n\n [[ 1.7427e-02, 2.2175e-02, 1.6268e-02],\n [ 8.0874e-03, -4.8383e-02, 4.8777e-03],\n [ 7.5091e-03, 1.7483e-02, -1.8778e-03]]],\n\n\n [[[ 5.3477e-03, -1.8310e-02, -5.7154e-03],\n [-7.7336e-03, 8.9927e-04, -6.0886e-03],\n [ 1.6448e-02, 3.9997e-02, 2.0619e-02]],\n\n [[ 1.0091e-02, 2.8225e-02, 2.0580e-02],\n [-1.0825e-02, -1.1642e-02, -1.1065e-02],\n [ 3.0934e-03, 6.8456e-03, 6.2208e-03]],\n\n [[ 1.1139e-02, 1.4302e-02, 6.0766e-03],\n [ 4.7331e-04, -1.0357e-02, -1.0268e-02],\n [-1.2849e-02, -1.6313e-02, -1.5298e-02]],\n\n ...,\n\n [[-3.6616e-02, -1.1584e-01, -6.2247e-02],\n [-2.6155e-02, 6.1589e-03, -2.3672e-02],\n [ 5.3270e-02, 1.4144e-01, 8.6781e-02]],\n\n [[ 7.8554e-02, 2.1438e-01, 1.1422e-01],\n [ 8.1675e-03, -2.6416e-02, -1.1034e-02],\n [-5.1324e-02, -1.7064e-01, -1.1195e-01]],\n\n [[-2.4299e-02, -4.5382e-02, -2.7452e-02],\n [-1.1414e-02, 6.2480e-03, -1.3134e-02],\n [ 2.2362e-02, 5.7740e-02, 3.6743e-02]]],\n\n\n ...,\n\n\n [[[-1.5258e-02, -4.5267e-02, -1.2541e-02],\n [-6.7815e-03, 6.0479e-02, -1.3859e-04],\n [ 8.6685e-04, 2.5291e-02, 7.8575e-05]],\n\n [[ 4.2581e-03, 7.1402e-03, 5.9544e-03],\n [-1.5136e-02, 2.3607e-02, -9.0026e-03],\n [-2.1982e-02, 6.6799e-04, -9.2078e-03]],\n\n [[ 1.9741e-02, 7.0707e-02, 4.3101e-02],\n [-1.5984e-02, -6.9152e-02, -5.1644e-03],\n [-1.4617e-02, -4.8219e-02, -1.0093e-02]],\n\n ...,\n\n [[ 3.1356e-02, 8.2815e-02, 4.6814e-02],\n [-1.4440e-02, -7.3168e-02, -7.6690e-03],\n [-1.9531e-02, -4.4348e-02, -2.1651e-02]],\n\n [[ 2.7185e-02, 3.8521e-02, 2.9902e-02],\n [ 2.7282e-03, 3.3194e-02, 3.7600e-03],\n [-9.4882e-03, 1.8543e-02, 5.1541e-03]],\n\n [[ 4.9527e-03, 8.9511e-03, 1.5685e-02],\n [-4.6069e-03, -4.1452e-02, 2.1970e-03],\n [-1.2852e-02, -1.4924e-02, -6.3124e-03]]],\n\n\n [[[-8.1570e-03, -7.1536e-03, -4.1329e-03],\n [-1.0386e-02, 2.8918e-02, 6.9929e-03],\n [-1.4302e-02, -4.3978e-03, -4.0522e-03]],\n\n [[-2.5996e-03, -2.6601e-03, -5.8479e-03],\n [ 4.2480e-03, 4.9111e-03, -4.6492e-04],\n [ 1.2494e-03, 3.3628e-03, -8.1392e-03]],\n\n [[-6.4070e-03, -8.3938e-03, -7.8072e-03],\n [-4.5914e-04, -1.9537e-02, -1.2476e-02],\n [-4.2001e-03, -8.6976e-03, -1.2116e-02]],\n\n ...,\n\n [[ 6.8064e-03, 1.5708e-02, 6.0387e-03],\n [ 1.4691e-02, -2.1424e-02, 7.4906e-03],\n [ 2.4571e-03, 4.1060e-03, 2.9926e-03]],\n\n [[ 6.1388e-03, -3.3643e-03, -8.9091e-03],\n [ 2.3703e-03, 9.2271e-03, -1.8485e-02],\n [-4.8962e-03, -2.1477e-02, -2.6680e-02]],\n\n [[ 1.4551e-03, 1.2552e-02, 8.6264e-03],\n [ 8.6750e-03, 1.4969e-03, 1.1774e-02],\n [ 4.9355e-03, 1.6606e-02, 1.0804e-02]]],\n\n\n [[[ 1.2908e-02, 8.3751e-03, -9.4053e-03],\n [ 1.2400e-02, -1.6998e-03, -2.1157e-02],\n [ 2.0678e-02, 1.5659e-03, -1.4635e-02]],\n\n [[ 1.0541e-02, -1.1440e-02, -6.9819e-03],\n [-4.3455e-03, 3.5730e-03, -1.3227e-02],\n [-3.8006e-04, -1.5967e-02, -8.2004e-03]],\n\n [[-1.2073e-03, -6.6526e-03, -7.7049e-04],\n [ 2.0330e-02, 3.0093e-03, -1.2804e-02],\n [ 5.9635e-04, -1.7162e-03, -1.0718e-02]],\n\n ...,\n\n [[ 2.2265e-03, -9.3266e-03, 2.2201e-02],\n [ 1.5913e-02, 1.7355e-03, 3.3828e-02],\n [-7.3491e-03, -1.2799e-02, 1.5358e-02]],\n\n [[-3.0969e-03, -1.8737e-02, 5.2690e-03],\n [ 3.7768e-03, -7.2968e-03, 1.5832e-02],\n [-8.7544e-03, -1.7933e-02, 7.3376e-03]],\n\n [[ 8.6833e-03, 1.6002e-02, -4.7220e-03],\n [ 5.7563e-03, 1.4887e-03, -1.9430e-02],\n [ 1.9259e-03, 7.0727e-03, -1.1467e-02]]]]), 'model.layer2.1.bn2.weight': tensor([0.1783, 0.1251, 0.1951, 0.2086, 0.1826, 0.1405, 0.1541, 0.1213, 0.0854,\n 0.2030, 0.1556, 0.1504, 0.1705, 0.1211, 0.1246, 0.1771, 0.1426, 0.1578,\n 0.1476, 0.2053, 0.1232, 0.1566, 0.2224, 0.1219, 0.1785, 0.1828, 0.1407,\n 0.1290, 0.1543, 0.2400, 0.2150, 0.2271, 0.0795, 0.2216, 0.1381, 0.2073,\n 0.1539, 0.1932, 0.0774, 0.1541, 0.1386, 0.1710, 0.1457, 0.1400, 0.1409,\n 0.1629, 0.1688, 0.1980, 0.1663, 0.1538, 0.1578, 0.1616, 0.1763, 0.1975,\n 0.1274, 0.1157, 0.1228, 0.1508, 0.1337, 0.1509, 0.1625, 0.2509, 0.1885,\n 0.1847, 0.1503, 0.1557, 0.2941, 0.1181, 0.2565, 0.1897, 0.1892, 0.1233,\n 0.1465, 0.1699, 0.1595, 0.1747, 0.1317, 0.1053, 0.1690, 0.1741, 0.1719,\n 0.1370, 0.1578, 0.1736, 0.0819, 0.1342, 0.1260, 0.2031, 0.1052, 0.1740,\n 0.1378, 0.1404, 0.1619, 0.2041, 0.1526, 0.2006, 0.1120, 0.1539, 0.1641,\n 0.1117, 0.1229, 0.1697, 0.1830, 0.1740, 0.1924, 0.2270, 0.1674, 0.0955,\n 0.1537, 0.1289, 0.1798, 0.1389, 0.1612, 0.1883, 0.1755, 0.1828, 0.1774,\n 0.1450, 0.2011, 0.1613, 0.1739, 0.2223, 0.1435, 0.1959, 0.1565, 0.1528,\n 0.1084, 0.2167]), 'model.layer2.1.bn2.bias': tensor([-0.0180, 0.0451, 0.0756, 0.1088, -0.0113, 0.0557, 0.0276, 0.0728,\n 0.0374, -0.1546, -0.0774, -0.0314, 0.1223, 0.0229, -0.0247, 0.0333,\n 0.0412, -0.1232, -0.0948, 0.0917, -0.0879, 0.1598, 0.0798, 0.0221,\n 0.0650, 0.0186, -0.0584, -0.0053, -0.0065, -0.1327, -0.1887, 0.0534,\n 0.0743, 0.0838, -0.0066, 0.0275, -0.0420, 0.0874, -0.0448, 0.0265,\n 0.0603, 0.1395, -0.0772, 0.1414, -0.0634, 0.0714, -0.0981, -0.0544,\n -0.1411, 0.1464, -0.1633, 0.1683, 0.0741, 0.0748, 0.0164, -0.0305,\n -0.0038, -0.0125, 0.0577, -0.0285, 0.0753, -0.1311, -0.1538, -0.0437,\n 0.0819, 0.0655, -0.1750, 0.0346, -0.1371, 0.0443, -0.1223, 0.0514,\n 0.0076, 0.0647, 0.0679, 0.0003, -0.0725, 0.0211, 0.0661, 0.0334,\n 0.0859, 0.0186, 0.0413, 0.0189, -0.0479, -0.1141, -0.0071, 0.0587,\n 0.0779, 0.0702, -0.0503, -0.0214, 0.0536, -0.1452, -0.0824, 0.0519,\n 0.0366, 0.0871, -0.0577, -0.0345, 0.0120, -0.0209, -0.0637, 0.1864,\n 0.0959, -0.1276, 0.0616, 0.0621, 0.0252, -0.0237, 0.1392, -0.0160,\n -0.0858, -0.1147, -0.0406, -0.0223, 0.2015, -0.0460, 0.0894, -0.0565,\n -0.0972, -0.1355, -0.0403, -0.0590, 0.0709, 0.0709, 0.0150, -0.0445]), 'model.layer2.1.bn2.running_mean': tensor([ 0.0957, -0.1800, 0.2171, 0.1666, -0.3646, 0.0928, 0.2105, 0.0949,\n -0.1397, -0.1449, -0.0256, -0.0116, 0.0381, 0.1024, -0.0981, 0.1283,\n 0.0644, -0.1745, -0.0776, 0.1348, 0.0370, 0.2630, 0.2531, 0.0212,\n 0.3088, 0.1226, 0.0170, -0.2734, 0.0677, -0.1645, -0.2124, 0.2284,\n -0.4079, 0.2587, -0.1776, -0.3539, 0.0163, 0.2599, -0.1411, -0.0661,\n 0.1302, 0.3505, -0.0960, 0.2666, -0.1172, 0.2059, 0.0080, -0.0996,\n -0.1739, 0.2291, -0.2251, 0.1567, 0.1148, 0.3808, 0.0327, 0.0115,\n -0.0158, 0.1178, 0.2058, -0.0046, 0.2008, -0.1314, -0.3296, -0.0042,\n 0.0925, 0.0901, -0.6906, 0.2889, -0.7857, 0.2612, 0.0133, -0.1983,\n -0.0254, 0.0446, 0.1280, -0.0634, -0.0696, 0.0877, 0.1632, 0.2659,\n 0.2850, 0.0793, 0.0578, -0.0113, -0.0825, 0.0946, -0.1322, 0.0903,\n 0.0144, 0.0867, -0.0154, -0.0302, 0.3053, 0.0347, -0.1663, 0.3207,\n 0.0180, 0.2271, 0.0602, 0.0221, 0.0558, -0.0587, -0.1456, 0.3817,\n 0.3879, -0.1200, 0.1018, -0.1077, 0.1433, 0.0265, 0.1930, -0.1970,\n -0.0874, -0.5113, -0.2510, -0.0809, 0.5083, -0.0066, 0.3719, -0.1612,\n -0.0148, -0.0906, -0.2645, -0.0602, 0.1323, 0.2095, -0.0684, 0.0075]), 'model.layer2.1.bn2.running_var': tensor([0.0584, 0.0220, 0.0949, 0.0401, 0.0215, 0.0203, 0.0308, 0.0213, 0.0458,\n 0.0234, 0.0641, 0.0236, 0.0243, 0.0166, 0.0393, 0.0363, 0.0312, 0.0143,\n 0.0201, 0.0877, 0.0289, 0.0256, 0.0795, 0.0174, 0.0395, 0.0350, 0.0148,\n 0.0194, 0.0222, 0.0207, 0.0850, 0.0825, 0.0215, 0.0427, 0.0232, 0.0281,\n 0.0241, 0.0873, 0.0193, 0.0111, 0.0192, 0.0349, 0.0270, 0.0345, 0.0169,\n 0.0285, 0.0103, 0.0306, 0.0372, 0.0314, 0.0110, 0.0289, 0.0419, 0.0501,\n 0.0231, 0.0195, 0.0164, 0.0307, 0.0212, 0.0178, 0.0381, 0.0554, 0.0295,\n 0.0187, 0.0301, 0.0327, 0.0264, 0.0175, 0.0252, 0.0496, 0.0493, 0.0260,\n 0.0222, 0.0332, 0.0301, 0.0174, 0.0477, 0.0191, 0.0538, 0.0363, 0.0498,\n 0.0162, 0.0298, 0.0373, 0.0298, 0.0224, 0.0463, 0.0316, 0.0222, 0.0418,\n 0.0104, 0.0313, 0.0530, 0.0336, 0.0187, 0.0707, 0.0504, 0.0252, 0.0209,\n 0.0272, 0.0620, 0.0452, 0.0192, 0.0312, 0.0374, 0.0343, 0.0474, 0.0344,\n 0.0213, 0.0241, 0.0243, 0.0233, 0.0320, 0.0147, 0.0308, 0.0249, 0.0316,\n 0.0170, 0.0403, 0.0834, 0.0409, 0.0838, 0.0277, 0.0225, 0.0523, 0.0279,\n 0.0223, 0.0279]), 'model.layer2.1.bn2.num_batches_tracked': tensor(7160), 'model.layer2.1.conv3.weight': tensor([[[[-0.0325]],\n\n [[ 0.0143]],\n\n [[-0.0007]],\n\n ...,\n\n [[-0.0080]],\n\n [[-0.0230]],\n\n [[ 0.0251]]],\n\n\n [[[ 0.0054]],\n\n [[ 0.0008]],\n\n [[ 0.0121]],\n\n ...,\n\n [[ 0.0003]],\n\n [[ 0.0119]],\n\n [[-0.0070]]],\n\n\n [[[-0.0268]],\n\n [[-0.0045]],\n\n [[-0.1670]],\n\n ...,\n\n [[-0.0088]],\n\n [[ 0.0013]],\n\n [[ 0.0061]]],\n\n\n ...,\n\n\n [[[ 0.0002]],\n\n [[-0.0318]],\n\n [[-0.0108]],\n\n ...,\n\n [[ 0.0354]],\n\n [[ 0.0543]],\n\n [[ 0.0933]]],\n\n\n [[[ 0.0005]],\n\n [[-0.0023]],\n\n [[-0.0147]],\n\n ...,\n\n [[ 0.0067]],\n\n [[ 0.0007]],\n\n [[ 0.0178]]],\n\n\n [[[ 0.0665]],\n\n [[-0.0023]],\n\n [[ 0.0045]],\n\n ...,\n\n [[ 0.0241]],\n\n [[ 0.0535]],\n\n [[ 0.0058]]]]), 'model.layer2.1.bn3.weight': tensor([ 1.3216e-01, -1.0111e-02, 2.4772e-01, 1.8054e-02, 1.3705e-01,\n 1.9221e-01, -1.3065e-03, 2.8174e-01, 1.3173e-01, 1.8933e-01,\n 2.2119e-01, 2.4162e-02, 7.9400e-02, 1.3046e-01, 2.5668e-01,\n 3.0583e-03, -3.1915e-03, 1.0745e-01, 1.0502e-01, 2.3730e-02,\n 4.2253e-04, 2.5390e-02, -6.9590e-03, 2.6446e-01, -7.6447e-04,\n 1.6186e-01, 1.7480e-01, 1.1011e-02, 2.3832e-01, 1.4917e-03,\n 8.6012e-03, 1.0641e-03, 2.4378e-01, 5.4452e-02, 6.5134e-02,\n -1.1205e-02, 6.5574e-04, 7.2744e-03, -5.4507e-04, 2.1929e-03,\n -5.1371e-03, 1.0331e-03, 2.0844e-01, 1.0618e-01, 2.3452e-01,\n 9.6990e-03, 1.3263e-01, -1.9252e-03, -1.1501e-03, 4.9683e-02,\n 2.2324e-01, 8.2780e-05, 1.0562e-03, -2.3062e-02, 1.8433e-01,\n 4.3367e-04, 1.3524e-02, 4.4269e-02, -3.9934e-03, 1.1608e-01,\n 2.3412e-01, 9.9685e-03, 1.2498e-03, 8.0008e-03, 3.6845e-02,\n 2.8188e-02, 4.1215e-02, 4.9958e-03, 3.3143e-05, 1.3406e-03,\n 1.4421e-02, -2.1080e-03, 3.1808e-02, 2.1421e-02, 5.6838e-03,\n 5.4498e-02, -2.1525e-02, 2.4923e-03, 7.9648e-02, 1.6360e-02,\n 7.2091e-03, 4.6771e-07, 2.5426e-01, -9.1372e-04, -5.0867e-04,\n 5.8722e-03, 2.3881e-02, 2.4328e-01, 2.2863e-01, 1.9443e-01,\n 2.4190e-01, 6.4076e-03, 1.4603e-02, 1.3160e-01, 2.4971e-01,\n 1.1295e-03, 3.6948e-03, 4.8757e-02, 2.6430e-02, 2.0272e-01,\n 6.5320e-02, 1.0142e-02, 1.9382e-01, 7.2801e-04, 1.9127e-01,\n 1.9130e-01, 1.1728e-03, 4.3032e-03, -3.1307e-04, 1.0805e-01,\n -6.5770e-03, 3.6964e-03, 1.0567e-01, 5.4259e-02, 8.0337e-02,\n 2.9832e-03, -4.5167e-03, 5.9376e-03, 2.0458e-03, 5.3040e-02,\n 4.8449e-02, 5.8511e-02, 1.0291e-01, 3.7544e-03, 5.3446e-03,\n 2.6123e-01, -3.5804e-03, -2.2934e-02, 9.7823e-02, 3.5725e-03,\n 9.3746e-03, -7.6282e-03, 1.8318e-02, 1.4506e-01, 1.0437e-02,\n 8.3876e-02, 2.7543e-03, -9.5595e-03, 2.8593e-01, 4.4023e-02,\n -2.4258e-02, 1.7623e-01, -1.0655e-02, 2.5612e-01, 1.7438e-01,\n 1.2012e-01, 1.1972e-01, 2.4370e-02, 5.4958e-04, 3.7032e-02,\n -1.9311e-03, 1.6790e-01, -5.2397e-03, 3.0061e-01, 1.8732e-01,\n 1.2513e-02, 1.3177e-01, 2.7740e-01, 3.4973e-03, 1.2872e-01,\n 1.0823e-02, 3.2252e-02, -2.7173e-05, 3.3819e-02, 1.0689e-03,\n 1.1343e-01, 3.9731e-02, 4.7830e-02, 9.2405e-04, 1.0386e-01,\n 2.3820e-01, 2.7905e-03, 4.1678e-04, 9.9301e-04, 1.2310e-01,\n -2.1266e-03, 1.6549e-01, -7.4427e-04, 1.2520e-01, 3.2970e-02,\n -4.0369e-02, 2.0928e-03, -6.1907e-03, 2.2482e-01, 2.2916e-02,\n 1.5058e-01, 2.8149e-01, 2.9866e-02, 1.9072e-01, 7.3744e-02,\n 2.6977e-02, 1.1392e-02, 7.7647e-02, -1.2313e-03, 2.8190e-01,\n -7.8482e-04, 2.6041e-01, -5.5404e-03, 2.4133e-01, 1.7513e-01,\n 1.7509e-06, -2.2572e-03, 7.3166e-04, 1.1809e-01, 2.7830e-01,\n 1.3975e-02, 1.1277e-01, 1.1459e-02, 1.5210e-03, -8.6595e-03,\n 2.1552e-02, 1.0491e-03, 4.1739e-03, 2.8765e-01, 2.2481e-01,\n -3.1530e-03, 1.2083e-02, -1.3201e-02, 2.9132e-01, -1.1724e-02,\n 1.4448e-01, 2.7113e-02, 2.5536e-01, 1.4917e-02, -1.6091e-03,\n 1.9179e-03, 1.1230e-02, 2.8162e-01, -2.4424e-03, -9.2042e-03,\n 1.1048e-02, -1.0498e-02, 2.6617e-01, 1.4768e-01, 2.9574e-01,\n -2.9849e-04, 2.8565e-01, 1.1755e-03, -6.2101e-03, 1.1711e-02,\n 2.5396e-01, 3.3822e-01, 7.5140e-03, 5.3766e-02, 3.5843e-03,\n -1.0474e-03, 9.6387e-02, 1.3802e-02, 4.1450e-03, 1.5275e-01,\n -3.0095e-03, 5.1747e-02, 2.7797e-03, -1.0900e-02, -1.5690e-03,\n 1.6758e-01, 3.1681e-04, 5.7048e-02, -4.3026e-03, 1.3082e-03,\n 3.3681e-02, 4.6398e-03, 1.1470e-03, 1.3859e-01, 3.7881e-03,\n 2.7264e-02, 5.4628e-05, 6.4847e-02, 3.6130e-02, 3.1294e-02,\n 1.5508e-01, 2.7261e-02, 1.9402e-01, 1.4808e-01, 3.6300e-03,\n 2.1762e-01, 9.6969e-02, 1.0375e-01, 6.4472e-03, 2.5007e-03,\n -3.3740e-03, 1.4280e-01, -7.1890e-04, 1.4071e-01, 2.1000e-01,\n 1.3736e-01, 1.9047e-03, -1.7429e-02, 2.3939e-02, -3.4405e-02,\n 1.2680e-01, 9.4632e-02, -7.9040e-04, -1.3974e-03, 3.7268e-03,\n -2.9807e-03, -9.6421e-04, 2.5784e-01, 1.8822e-01, 2.5783e-05,\n -2.4686e-02, 3.6049e-04, 1.1035e-01, 2.3800e-02, 1.5734e-03,\n 1.0257e-02, 3.0602e-02, 8.2572e-02, 1.5851e-02, 7.2581e-02,\n -4.3003e-03, 2.0987e-01, 2.9393e-01, 1.9551e-01, 2.4064e-01,\n 2.7698e-01, -3.3273e-03, 1.7697e-01, 3.2306e-01, 1.5980e-01,\n 5.0475e-03, -1.2652e-02, 1.3207e-03, 6.4159e-02, -9.4835e-04,\n 3.4771e-01, 7.4830e-02, 1.9677e-02, 6.3403e-03, 2.4386e-01,\n -5.5625e-03, 1.1209e-02, 3.4114e-01, 7.4548e-02, 1.0894e-03,\n 9.4521e-02, 1.7402e-03, 5.4905e-02, -1.0906e-03, 4.5073e-02,\n 1.8157e-01, 1.6578e-02, 2.1089e-01, -9.8872e-05, 2.3293e-01,\n 7.1117e-03, 2.6109e-01, 3.0103e-02, 1.2056e-02, -2.9117e-02,\n 2.2169e-03, 8.0927e-02, 1.2099e-03, 1.3235e-01, 2.5190e-01,\n 9.7535e-03, 1.1923e-02, 4.0705e-02, 2.2248e-02, 1.4743e-03,\n 1.3839e-01, -1.5372e-02, 8.1091e-02, 5.3232e-02, 2.3006e-01,\n -2.5365e-03, 5.3122e-03, -4.4537e-03, 2.0171e-02, -1.2028e-03,\n 2.6771e-01, 6.6527e-03, -2.3827e-03, 1.5998e-02, -9.4333e-05,\n 7.6806e-03, 5.3367e-02, 2.2846e-03, 3.9305e-02, 1.3425e-01,\n 4.6727e-03, -1.0440e-02, 1.6300e-01, -1.1103e-03, -3.4106e-04,\n -1.9733e-03, 2.4769e-01, 1.3566e-01, 1.1629e-01, 2.8975e-03,\n -4.1457e-04, -6.1697e-03, 9.8896e-02, 3.5008e-02, 2.2931e-02,\n 2.8990e-01, 1.4096e-01, 9.6605e-02, -1.1882e-03, 2.2945e-01,\n 3.4239e-01, 1.5681e-01, 5.4589e-03, -3.7798e-04, 1.2813e-01,\n 3.9941e-02, -2.2976e-02, 2.0354e-02, 8.7188e-02, 1.8827e-01,\n 4.3766e-03, -9.0020e-03, -1.0673e-03, 1.3118e-01, 2.6218e-01,\n -4.2653e-04, 8.9669e-02, -1.5689e-03, -5.8323e-02, 9.1875e-02,\n 2.6899e-02, 3.0000e-01, 1.1749e-02, 7.2157e-03, 1.0536e-01,\n 5.9561e-02, 2.9385e-01, 2.6555e-01, 2.6874e-02, 1.1832e-02,\n 2.7020e-01, 2.9418e-02, 6.8307e-05, 2.8475e-01, -6.1139e-02,\n -7.6225e-04, -4.9499e-04, 4.5114e-03, 9.2743e-03, -5.6995e-03,\n 9.0001e-04, 1.1979e-01, 1.1559e-01, 2.5959e-01, 5.3557e-02,\n 2.2076e-03, 2.5962e-01, 3.5195e-03, 4.7937e-04, 1.9700e-01,\n 3.9217e-01, -2.5558e-06, 2.3448e-01, 3.1861e-04, 2.6258e-01,\n 3.6450e-02, 2.2528e-03, 1.2656e-02, 2.4080e-01, 8.6388e-03,\n 9.0848e-03, -1.9510e-04, 2.2458e-02, -1.8914e-04, 2.3019e-01,\n -3.5669e-03, 1.6559e-02, 2.7831e-01, 5.8645e-02, -1.3312e-02,\n 1.7662e-02, 2.8826e-01, 2.9468e-01, 1.7956e-01, 9.9795e-04,\n -1.0045e-02, -2.1479e-02, 1.0065e-01, -2.1074e-03, 2.3063e-03,\n 4.7179e-02, 6.1856e-04, 1.6193e-01, 2.8915e-03, 6.4051e-03,\n 1.0515e-01, 2.8007e-01, -4.3540e-03, 1.8368e-01, -3.0619e-02,\n -1.4611e-03, 2.6020e-02, 1.7179e-01, 3.1001e-02, 1.0829e-01,\n 1.6150e-01, 1.2648e-02, 7.9153e-02, 2.6779e-01, 3.4882e-04,\n 1.5072e-01, 9.9721e-02, -1.3717e-04, 1.1658e-01, 4.3776e-03,\n 4.6684e-02, 3.4810e-02, 2.4196e-02, -8.3876e-03, 2.0221e-01,\n -3.5410e-03, 1.8625e-01]), 'model.layer2.1.bn3.bias': tensor([-1.4986e-01, -3.8732e-02, 1.0457e-01, -2.5660e-03, -6.5047e-02,\n 2.0199e-02, 9.5826e-04, -1.1934e-01, -1.0407e-01, 6.8223e-02,\n -7.5510e-02, -9.3884e-03, -2.3470e-02, -7.5310e-02, 1.6889e-02,\n -5.1691e-03, 3.4255e-03, 8.2400e-04, -2.5528e-02, -3.0343e-02,\n -7.8874e-04, -4.3599e-02, -2.8302e-03, 5.5368e-02, 8.5529e-03,\n -1.6798e-02, -8.6696e-02, 5.6218e-02, 2.6629e-02, 7.5073e-03,\n -2.6903e-02, -8.1596e-02, 1.2188e-02, -1.7905e-02, -1.0178e-01,\n -2.7344e-02, 1.6820e-02, 2.6225e-03, -7.3959e-03, 8.7908e-03,\n -1.7105e-02, 1.9487e-03, -4.2557e-02, -1.1110e-01, -4.1240e-02,\n -4.1959e-02, -1.3874e-01, -1.2968e-02, 4.1544e-03, -1.2506e-02,\n -6.0709e-02, -3.0088e-03, 3.6583e-02, 2.9316e-03, -2.0125e-01,\n -4.3403e-03, 2.7353e-02, -4.6091e-02, -6.3358e-03, 4.8157e-02,\n -7.3833e-02, -2.8902e-02, -4.3767e-03, -1.1625e-01, -1.5556e-02,\n -2.0985e-02, -1.5706e-01, 1.5404e-02, -3.7539e-04, -1.7308e-03,\n -5.7231e-03, 1.0308e-02, -2.6123e-02, -3.1095e-02, -9.3011e-03,\n -3.6677e-02, -3.5538e-04, 3.1522e-03, -8.1146e-02, -4.6586e-02,\n -3.5957e-03, -5.4730e-03, -4.3898e-02, -3.2515e-03, -1.0195e-02,\n -5.5557e-03, 5.9307e-03, 2.1591e-02, -3.9165e-02, -2.1620e-02,\n 1.1540e-02, -1.6619e-02, -3.0364e-02, -8.3649e-02, 2.8416e-02,\n -1.4808e-02, 2.6336e-03, -8.5365e-02, -6.5936e-03, 8.1320e-02,\n -9.0313e-02, -3.4431e-02, -6.8675e-02, -6.4725e-03, -6.2224e-02,\n 1.0628e-01, 3.0031e-03, -1.4026e-02, 1.8101e-02, 3.8955e-02,\n 7.1004e-04, -4.6924e-03, 8.6068e-03, -5.2327e-02, -1.0037e-01,\n -7.1642e-03, 4.3960e-03, -8.9255e-03, 6.3641e-03, -4.2804e-02,\n -1.1409e-02, -3.6720e-02, -8.2005e-02, -1.0931e-02, -5.7884e-02,\n -1.4202e-01, -3.2566e-03, -8.9366e-02, -1.4584e-02, -4.5933e-03,\n -1.6912e-02, -1.1510e-02, -1.4323e-02, 1.1869e-01, -1.7724e-02,\n -2.0364e-02, -2.3877e-03, 3.9268e-03, 2.1531e-02, -1.7191e-02,\n -4.7059e-03, -2.5499e-03, -1.8653e-03, -2.0774e-02, 4.4436e-02,\n -1.1270e-01, -1.7277e-01, -1.4624e-02, -1.2082e-03, -2.9079e-02,\n -5.9770e-03, -7.3789e-05, -6.4235e-03, 4.8799e-03, -9.2206e-02,\n -2.3724e-02, -1.5661e-01, -3.4757e-02, -5.3052e-03, -2.7086e-02,\n 9.0081e-03, -5.9913e-03, -5.3139e-03, -3.7418e-02, 1.2877e-02,\n 6.7476e-02, -5.7603e-02, -5.9848e-02, -2.2649e-02, 3.6202e-03,\n -1.4275e-02, -8.4312e-03, 1.5294e-02, 1.3401e-02, 8.4953e-02,\n -3.3706e-03, -9.2608e-02, -1.9881e-03, -3.3470e-02, -3.0509e-02,\n -4.0703e-02, -1.4683e-02, 2.1491e-03, 7.4073e-03, -1.2933e-02,\n -1.9383e-01, 6.7653e-02, -7.8821e-03, -1.3979e-01, 1.5624e-01,\n -3.7695e-02, -1.3638e-02, -6.5658e-02, -7.7324e-03, -6.1986e-02,\n -4.0728e-03, 6.9729e-03, -8.9266e-03, -6.5596e-02, 8.0932e-02,\n -8.8769e-06, -5.2807e-03, 1.0288e-02, -7.3818e-02, 8.8537e-02,\n -4.0063e-02, 5.5634e-03, 1.0941e-02, -6.3927e-03, -1.6203e-02,\n -2.6611e-02, 2.1018e-03, -3.8044e-03, 4.8065e-02, 2.2236e-02,\n 4.3921e-03, -3.1326e-02, -9.1720e-02, 3.4529e-02, -3.5950e-03,\n -6.0908e-02, -9.5869e-03, 3.2311e-02, -2.3029e-02, 9.6587e-03,\n 5.2074e-04, -7.8142e-03, -1.2974e-01, 1.3303e-02, -7.9309e-03,\n -2.0781e-03, -8.4812e-05, 1.0144e-01, -1.7826e-03, 5.0746e-02,\n 2.4879e-02, 3.0010e-03, -1.5786e-03, -7.1852e-03, -5.9403e-03,\n 7.4164e-02, -1.4619e-01, -2.5201e-03, -1.0592e-01, 1.6628e-03,\n -2.6114e-02, -1.2379e-01, -1.0347e-02, -1.5025e-02, 6.6880e-02,\n 3.3387e-03, -1.1878e-01, 4.3490e-03, -8.4047e-03, -1.7995e-03,\n -1.4666e-01, -2.7843e-03, -2.3299e-02, 1.1137e-02, 3.3008e-03,\n -5.1130e-02, 1.8366e-03, -8.4004e-03, -1.0575e-01, -2.5044e-03,\n -1.2974e-01, 1.9992e-02, -1.2710e-01, -8.0433e-02, -9.8666e-02,\n 1.1008e-01, -4.1473e-02, 5.8162e-02, -6.8418e-02, -1.3340e-03,\n 6.5894e-02, -6.1234e-02, 3.9047e-03, -2.0406e-02, -2.2234e-02,\n -1.1630e-02, -8.2685e-02, -1.1640e-02, -3.6403e-02, -3.2041e-02,\n 2.3088e-02, -1.1988e-02, -3.1522e-02, -2.9685e-02, -4.6087e-02,\n 1.0141e-01, 1.3024e-02, -8.7566e-03, -1.2988e-02, -4.6937e-02,\n -5.1432e-03, 1.5705e-02, 5.8781e-02, -8.9718e-02, -1.8058e-03,\n -6.9385e-03, -8.3323e-03, -2.3002e-02, -9.4833e-03, -7.5916e-03,\n 1.0278e-02, -5.1069e-02, 1.4418e-02, 1.2552e-02, -1.7128e-01,\n -1.9456e-03, 8.5267e-02, 5.9670e-02, 1.8871e-02, -7.0389e-02,\n -6.8160e-03, -7.8241e-03, -2.3426e-01, 4.3032e-02, 5.6777e-03,\n 1.1633e-02, -1.8696e-02, 1.0056e-01, -5.0870e-02, 7.3137e-03,\n 1.1731e-01, -9.4240e-02, -4.7063e-03, -1.6083e-03, -2.7877e-02,\n -1.1562e-03, -3.0806e-03, 4.4421e-02, -1.6376e-01, -1.2055e-02,\n -7.3459e-02, -1.1554e-02, -1.7422e-01, -7.3807e-03, -2.5705e-02,\n -1.0125e-01, 8.1064e-03, -1.7548e-01, -1.8824e-02, -6.5405e-02,\n -1.0338e-02, 3.5024e-02, -5.2693e-02, 5.5526e-02, -1.2546e-01,\n -1.0340e-02, 8.2551e-02, -1.1595e-02, -8.2431e-02, -1.1581e-01,\n -5.5666e-03, -1.9307e-02, -8.4366e-02, -1.0201e-02, -1.4434e-02,\n -1.6523e-02, 8.1590e-03, -3.0820e-02, -1.2199e-01, -2.4444e-02,\n -1.6773e-03, 9.4512e-02, -9.8308e-03, -9.0989e-04, -1.3261e-02,\n 2.1622e-02, -1.1778e-01, -3.1170e-03, -1.3213e-02, -2.8969e-04,\n -8.4195e-03, -4.6532e-02, -8.7321e-04, -1.9775e-02, -2.5945e-02,\n -6.7538e-03, -3.0345e-03, -9.9218e-02, -9.2459e-03, -2.9509e-02,\n -7.9473e-03, 1.0836e-03, -1.3382e-01, 9.6597e-02, 2.0548e-03,\n -2.8656e-03, 1.1191e-02, -3.8715e-02, -7.0898e-02, -3.9072e-02,\n -6.6409e-02, -1.7226e-01, -4.2877e-02, -6.5421e-03, -3.1335e-02,\n 4.4376e-02, 8.8140e-02, 3.5968e-03, -6.4005e-03, -1.6295e-01,\n -6.0877e-02, -8.2383e-02, 9.4329e-03, -4.4164e-02, 3.2696e-02,\n -1.5381e-02, -1.0761e-02, -1.2925e-03, -1.2866e-02, -5.0059e-02,\n -1.8387e-02, -6.9078e-02, -1.1444e-02, -8.0777e-02, 1.7713e-03,\n -1.0655e-02, -9.4189e-03, -1.6117e-02, -1.8331e-02, -6.0671e-02,\n -1.0876e-02, -1.1088e-02, -1.1837e-02, -1.0883e-02, -5.5836e-04,\n 9.9478e-03, 4.6073e-02, 3.5624e-03, 1.2786e-02, -9.5998e-02,\n -1.5723e-02, -1.9520e-02, -1.3815e-02, 6.1687e-03, 1.1558e-02,\n -1.1337e-02, -1.7036e-01, -1.1297e-01, -1.0165e-01, 2.8914e-02,\n 2.5690e-02, 4.6551e-02, 4.7597e-04, -1.6136e-03, -4.7614e-02,\n -7.9677e-02, -7.5211e-05, 7.0974e-02, 1.0395e-02, 3.1176e-02,\n -5.8417e-02, 4.5185e-03, -1.0690e-02, -3.6599e-02, -1.1042e-02,\n -9.0658e-03, 4.6242e-03, -3.0880e-02, -1.7770e-02, -1.9000e-01,\n -1.2054e-04, -2.7755e-02, 4.6585e-02, -8.0122e-02, -3.0527e-03,\n -2.7525e-02, -9.1495e-02, 4.5098e-02, -1.2219e-01, -4.9850e-02,\n -5.2894e-04, -5.9260e-02, -8.9141e-02, 2.8879e-02, -8.5407e-03,\n -3.5107e-02, -7.9348e-03, 4.6034e-02, -9.1334e-03, -2.2695e-03,\n -8.3442e-02, -1.0862e-03, -3.5895e-03, -4.8142e-02, -3.3222e-02,\n -1.0862e-02, 1.3278e-01, -5.7134e-02, 1.6281e-02, -1.8676e-01,\n -1.4764e-01, -9.7668e-03, 2.9782e-02, -1.5886e-02, 2.2901e-03,\n -9.0490e-02, 6.9336e-02, -1.8071e-02, -2.1740e-02, -4.1260e-03,\n -1.8192e-01, -1.3600e-01, -7.3430e-02, -2.1452e-02, 8.9087e-02,\n 2.5859e-03, -1.3685e-01]), 'model.layer2.1.bn3.running_mean': tensor([-6.1630e-02, 7.8898e-03, -6.8463e-02, -4.0615e-03, -2.0940e-02,\n -5.2389e-02, 4.1778e-03, -4.2783e-02, -4.8211e-02, -7.3387e-02,\n 7.7051e-02, -3.0653e-02, -2.9909e-02, 3.9787e-03, -5.1158e-03,\n -1.0077e-02, 9.3577e-03, 1.6489e-02, 7.3144e-03, 8.2574e-03,\n 4.9383e-03, -5.8181e-03, 1.9042e-03, -4.7098e-02, -8.9470e-03,\n -5.1385e-03, 1.3488e-01, 5.0005e-03, -8.0987e-03, -1.1535e-02,\n 2.3052e-03, 1.1496e-02, -4.6659e-02, -4.2374e-03, 2.5063e-03,\n -9.4499e-03, 3.0783e-03, -1.2660e-02, -6.4423e-04, -3.3392e-02,\n 1.7310e-02, 5.0484e-03, 1.0378e-02, 7.2709e-02, 4.4299e-04,\n -8.5599e-06, -1.5631e-02, 7.6560e-04, -7.5397e-03, -4.6380e-02,\n -3.4924e-02, -2.0968e-04, 1.7877e-02, -4.1185e-03, 3.8800e-02,\n 2.6329e-03, 3.7522e-02, 5.4329e-03, -1.3509e-02, -5.5511e-02,\n -2.4763e-02, 1.5802e-02, -9.6190e-03, 2.1284e-03, -5.3953e-03,\n -1.8433e-02, -5.4729e-03, 1.0860e-02, -1.6562e-04, 2.8953e-04,\n 3.2827e-02, 5.1624e-03, -2.1482e-02, -1.1542e-02, 6.3514e-03,\n -7.4282e-02, 1.2306e-03, 7.6909e-03, 9.3903e-03, 7.0557e-03,\n -4.3946e-03, 2.5615e-03, -1.3336e-02, 6.9100e-03, 1.0147e-02,\n -8.9329e-03, -1.2872e-03, -4.2205e-03, 1.1613e-03, -2.3522e-02,\n -6.8272e-02, 1.5585e-02, 4.3389e-03, -1.6738e-02, -5.5895e-02,\n 1.7507e-03, -8.8688e-03, 4.5883e-02, 1.3863e-02, 5.1703e-02,\n 2.0327e-02, -2.8059e-02, -1.7091e-02, -1.3373e-03, -5.6000e-02,\n -9.5969e-02, 1.5131e-02, 3.2701e-03, 1.4930e-02, -2.9852e-02,\n -9.1878e-03, -1.7458e-03, -5.2006e-02, 2.6626e-03, 1.9617e-02,\n -1.6251e-02, 1.0088e-02, 1.6144e-02, 1.0992e-02, -1.1090e-02,\n -3.9310e-03, -4.0084e-03, 1.9568e-02, 1.1106e-03, -2.4542e-04,\n -4.5500e-02, 4.2185e-03, 7.5864e-03, -4.5815e-02, -1.3214e-02,\n 3.3050e-03, 4.6969e-05, -1.5216e-02, -1.7732e-01, 4.0980e-03,\n -2.4941e-02, -2.3979e-03, 3.1712e-02, -8.2215e-02, 1.4124e-02,\n -9.1984e-03, -3.1579e-03, 1.0447e-02, -5.1968e-04, -7.9636e-02,\n -3.4668e-02, -7.9006e-02, 3.1355e-04, -4.4395e-03, 6.4086e-03,\n -2.8759e-03, -5.3743e-03, 1.1212e-02, -3.6664e-02, -3.4687e-02,\n 1.0767e-03, 1.3392e-02, -4.3481e-02, 7.2764e-03, -4.3983e-02,\n -5.8604e-03, -8.1720e-03, 1.5224e-02, 1.4569e-02, 1.0180e-03,\n -5.8773e-03, -3.0904e-02, -9.9513e-03, -3.0087e-03, -2.5371e-02,\n -4.6890e-02, -1.3767e-02, -8.3521e-03, -6.0951e-03, -4.2716e-02,\n 4.2298e-03, -6.4789e-02, 8.3204e-03, -3.3539e-02, -8.1747e-03,\n -1.6034e-03, 4.4256e-03, 3.0430e-03, -1.2637e-01, 1.1695e-02,\n -3.6034e-02, -4.9500e-02, -6.6025e-03, 6.2927e-02, 4.5905e-02,\n 7.2890e-03, 1.6046e-02, -9.6045e-03, -2.5571e-02, -6.8812e-02,\n 1.6483e-03, -4.2887e-02, -5.5329e-03, 2.1942e-02, -6.4416e-02,\n -6.1739e-07, -1.5200e-03, 4.7759e-03, -4.8074e-03, -9.9970e-02,\n -1.7930e-02, -1.2537e-01, -3.4271e-03, -8.6723e-03, 2.8293e-03,\n -5.9878e-03, -2.9844e-03, 1.2775e-02, -7.6634e-02, 4.0469e-03,\n 4.1017e-03, -1.5039e-02, -1.3255e-02, -8.6220e-02, 7.9114e-04,\n 4.3030e-02, 2.5302e-03, -6.6981e-02, -4.2069e-02, -5.6601e-03,\n 1.8664e-03, -8.1262e-03, -9.9750e-02, 3.8353e-03, -5.6272e-03,\n -1.0854e-02, -2.0883e-02, -1.0455e-01, -2.2141e-02, -6.4585e-02,\n 9.2637e-03, 4.0492e-02, -2.5520e-03, 8.5156e-03, -3.1104e-03,\n -1.8872e-02, 6.9918e-03, -1.1267e-02, 1.3446e-02, -2.6576e-02,\n -9.1320e-04, 6.1323e-02, 1.9384e-02, -1.4955e-02, -9.9953e-03,\n 6.5828e-03, -2.7891e-02, -8.6911e-04, 5.5979e-03, -1.1868e-02,\n -1.3515e-02, -5.5000e-03, -9.6853e-03, 9.6386e-03, -1.6099e-02,\n -1.1465e-02, 3.8778e-03, 1.1142e-03, -2.4062e-02, -1.6078e-03,\n 9.8328e-03, -3.4726e-03, 7.1425e-02, -1.2264e-02, 3.1697e-02,\n -8.7609e-02, -1.6841e-02, -2.6483e-02, -1.9274e-02, -1.9159e-03,\n -3.5544e-02, -1.4055e-02, 4.3487e-03, 5.8251e-03, 2.4357e-02,\n -3.0987e-03, -2.8345e-03, -7.7594e-03, 5.8795e-03, -4.4351e-02,\n 2.1466e-02, 1.2086e-02, -1.3661e-03, 2.1465e-02, -2.4152e-02,\n 5.7035e-02, -2.4888e-02, -1.9105e-03, -2.9938e-03, -1.5110e-03,\n 7.3743e-03, 1.7191e-02, -6.7035e-02, -4.8055e-02, 4.4078e-04,\n -1.4219e-03, 1.0214e-04, -5.5811e-02, 1.0600e-03, 3.8770e-03,\n 1.4943e-02, -1.6769e-02, 5.5453e-03, -1.3033e-02, 6.8728e-03,\n -1.6300e-02, -1.4063e-01, -6.6008e-02, -5.3088e-02, -8.0929e-02,\n -5.9954e-02, 1.3846e-02, 2.9028e-03, -8.2858e-02, -1.2248e-02,\n 3.2485e-03, 1.3091e-02, 4.6037e-03, -2.9172e-02, 4.9192e-03,\n -8.3659e-02, 2.4556e-02, 3.1274e-03, -5.3652e-03, -5.1219e-02,\n -1.6464e-02, -1.0791e-02, -7.0808e-02, 2.9549e-02, 6.9030e-04,\n -2.9106e-02, -1.1347e-02, 1.6326e-02, 1.3698e-03, 1.3335e-02,\n -3.9990e-03, -4.8042e-03, -5.2860e-02, -1.6299e-03, -2.6169e-02,\n -5.6785e-03, -3.3729e-02, 1.0976e-02, 5.1164e-03, -2.6874e-02,\n 5.1960e-03, 1.2626e-02, 1.1067e-02, -1.8997e-02, -3.6983e-02,\n -2.5380e-03, -1.9672e-04, 1.0955e-03, -3.2291e-02, -1.5087e-02,\n -4.6826e-03, -2.5902e-02, -2.8765e-02, -4.3274e-02, -2.7452e-02,\n -5.7329e-03, -7.6371e-03, -1.2433e-02, 1.4679e-02, -8.5813e-03,\n 2.1212e-02, -1.6630e-02, 7.4735e-03, -9.3315e-03, 7.0437e-04,\n 1.7084e-02, 1.3524e-02, 5.6563e-05, -3.4659e-02, -2.6073e-02,\n 9.8773e-03, -1.1403e-03, 9.1698e-02, 1.7817e-02, 2.6938e-03,\n -8.7298e-04, -9.2135e-02, -4.3346e-02, -1.0723e-02, -7.5214e-03,\n -1.2788e-03, -3.9181e-03, -4.6781e-02, -3.2087e-02, -1.5007e-02,\n 2.9794e-03, 4.2723e-03, -9.6649e-02, -7.9658e-03, -3.8589e-02,\n -5.7007e-02, 1.6767e-02, -6.0047e-03, 1.7973e-03, 8.1394e-02,\n 7.4284e-04, -1.2377e-02, -7.0904e-03, 8.9645e-03, -5.1067e-02,\n 4.0284e-03, -8.8110e-03, 1.0760e-02, -4.3777e-02, -1.3485e-02,\n 8.4750e-03, -8.1178e-03, 2.1983e-02, 1.9817e-02, -2.0361e-02,\n 1.5264e-03, 2.9585e-02, -3.3826e-03, -1.8662e-02, -5.0871e-03,\n -4.1761e-03, -1.3352e-02, -4.9291e-02, -2.9667e-03, -4.1657e-03,\n -1.4125e-02, -2.4925e-02, -7.3262e-03, -4.0821e-02, -3.6844e-02,\n -5.3588e-03, 9.2700e-03, 1.8525e-02, -1.3093e-02, 7.2922e-03,\n 7.1852e-03, -7.5654e-02, -1.0676e-02, -6.3917e-02, 4.6733e-02,\n -1.5944e-03, -5.2311e-02, -3.7182e-03, -1.9856e-02, 2.1777e-02,\n -1.4162e-02, -8.3385e-05, -2.2257e-01, -1.2121e-02, -4.2986e-02,\n -3.9699e-02, -3.7553e-03, -2.2272e-03, -7.1096e-02, 1.0558e-02,\n 1.9630e-02, 2.4908e-03, -7.2540e-03, 4.7527e-03, -3.0557e-02,\n -8.5595e-03, -1.8454e-02, -6.0614e-02, -3.4699e-02, 2.3420e-03,\n 3.5810e-02, -6.4762e-02, -5.1684e-02, -2.1636e-02, 7.0214e-03,\n -1.3586e-02, -1.1692e-02, -2.0307e-02, 1.2550e-02, 1.7285e-02,\n 9.2390e-04, 1.4152e-02, -1.7813e-01, 1.7881e-02, 4.1880e-03,\n 2.0321e-02, -2.3866e-02, 8.5750e-04, -2.2717e-02, -4.2261e-02,\n -9.0707e-03, 6.9524e-03, -5.6845e-02, -2.5175e-02, -8.1115e-02,\n -1.4048e-01, -8.1095e-03, -7.7608e-03, -5.0151e-02, -3.9404e-03,\n -4.6484e-02, -2.9829e-03, 1.3489e-02, -1.1030e-02, -1.1541e-02,\n -5.9611e-03, 4.5289e-03, -1.5657e-02, -2.9575e-03, -8.7919e-03,\n -5.9538e-04, -1.9329e-02]), 'model.layer2.1.bn3.running_var': tensor([1.7722e-03, 3.7489e-04, 8.9415e-03, 7.9895e-04, 2.7932e-03, 4.7943e-03,\n 4.4163e-04, 6.4332e-03, 1.5337e-03, 3.5603e-03, 2.9310e-03, 6.5410e-04,\n 1.6204e-03, 3.8992e-03, 6.7960e-03, 3.0421e-04, 6.9624e-04, 1.4156e-03,\n 1.6159e-03, 1.0017e-03, 2.4373e-04, 3.9101e-04, 4.2060e-04, 7.2590e-03,\n 3.8729e-04, 4.2717e-03, 2.6183e-03, 5.6728e-04, 4.3168e-03, 4.3345e-04,\n 2.8463e-04, 4.2409e-04, 1.0830e-02, 1.1280e-03, 7.7212e-04, 5.2769e-04,\n 1.1233e-03, 5.9297e-04, 5.5509e-06, 9.2085e-04, 2.9367e-04, 3.2187e-04,\n 4.4839e-03, 1.2600e-03, 6.8725e-03, 4.3274e-04, 1.1991e-03, 3.3406e-04,\n 4.8652e-04, 9.7240e-04, 3.8223e-03, 1.4626e-07, 5.1031e-04, 5.0951e-04,\n 2.4134e-03, 2.4087e-04, 7.0195e-04, 1.0624e-03, 6.3734e-04, 2.2500e-03,\n 5.1447e-03, 4.6994e-04, 3.3674e-04, 3.3856e-04, 4.4630e-04, 5.8738e-04,\n 2.0578e-04, 4.2203e-04, 4.2287e-08, 2.3295e-04, 4.2962e-04, 3.9027e-04,\n 4.8760e-04, 5.8572e-04, 5.8569e-04, 9.5545e-04, 6.2687e-04, 4.9329e-04,\n 2.1523e-03, 5.0391e-04, 5.5099e-04, 3.1403e-04, 3.4108e-03, 4.8254e-04,\n 2.7043e-04, 5.6379e-04, 6.3274e-04, 5.9257e-03, 3.6194e-03, 2.3822e-03,\n 7.0945e-03, 3.3670e-04, 2.7516e-04, 8.4447e-04, 9.6291e-03, 2.7816e-04,\n 5.1718e-04, 1.4944e-03, 4.5110e-04, 5.7848e-03, 8.3654e-04, 3.4197e-04,\n 3.1431e-03, 4.5424e-04, 4.9538e-03, 3.0210e-03, 3.1333e-04, 3.2304e-04,\n 5.5784e-04, 2.3421e-03, 4.7462e-04, 5.0025e-04, 2.7489e-03, 6.4608e-04,\n 9.7667e-04, 5.4873e-04, 3.9001e-04, 4.2513e-04, 4.7050e-04, 8.9737e-04,\n 7.1849e-04, 8.9107e-04, 1.5903e-03, 2.6499e-04, 2.7113e-04, 9.3409e-03,\n 5.9548e-04, 5.0821e-04, 1.4499e-03, 3.4145e-04, 4.7755e-04, 8.7987e-04,\n 4.7277e-04, 2.7551e-03, 7.8925e-04, 1.8411e-03, 3.5124e-04, 5.6225e-04,\n 1.2528e-02, 7.7117e-04, 6.0538e-04, 3.8570e-03, 3.7249e-04, 7.0843e-03,\n 2.6287e-03, 1.6247e-03, 1.1291e-03, 6.1116e-04, 3.3048e-04, 8.9690e-04,\n 4.1891e-04, 8.4356e-03, 5.3626e-04, 8.3460e-03, 2.4896e-03, 6.6484e-04,\n 2.0754e-03, 8.0224e-03, 3.8925e-04, 1.8526e-03, 5.4166e-04, 8.4322e-04,\n 5.3054e-04, 5.4099e-04, 5.4298e-04, 2.2038e-03, 5.6571e-04, 1.3745e-03,\n 2.6713e-04, 1.4877e-03, 8.2104e-03, 9.4251e-04, 9.9462e-04, 5.9279e-04,\n 3.1793e-03, 3.5222e-04, 2.0273e-03, 4.6696e-04, 1.6114e-03, 4.7598e-04,\n 4.2770e-04, 4.7224e-04, 4.3005e-04, 3.9372e-03, 5.7123e-04, 1.6215e-03,\n 1.0857e-02, 1.1035e-03, 3.3479e-03, 2.0187e-03, 8.3588e-04, 3.3559e-04,\n 1.4027e-03, 5.5524e-04, 6.2873e-03, 3.8234e-04, 4.2909e-03, 5.0139e-04,\n 6.0130e-03, 3.8440e-03, 6.0963e-13, 4.7638e-04, 3.2804e-04, 2.5365e-03,\n 9.3688e-03, 2.4409e-04, 1.2428e-03, 5.6374e-04, 9.7949e-04, 1.2018e-04,\n 4.8911e-04, 4.1871e-04, 7.8379e-04, 8.1278e-03, 4.1711e-03, 2.2942e-04,\n 6.1922e-04, 5.7014e-04, 1.0305e-02, 4.0900e-04, 1.6163e-03, 3.3220e-04,\n 4.7057e-03, 2.0138e-04, 5.7709e-04, 5.1277e-04, 5.1558e-04, 9.3180e-03,\n 3.9267e-04, 6.3184e-04, 3.6291e-04, 3.8963e-04, 6.0374e-03, 2.1467e-03,\n 1.5924e-02, 3.4514e-04, 9.2560e-03, 3.7026e-04, 5.0576e-04, 4.2282e-04,\n 7.9145e-03, 6.6135e-03, 5.7397e-04, 6.5902e-04, 3.1661e-04, 3.7954e-04,\n 1.4223e-03, 4.9878e-04, 4.0559e-04, 4.2545e-03, 4.8743e-04, 2.0969e-03,\n 4.9092e-04, 4.5998e-04, 3.9429e-04, 1.5460e-03, 3.2250e-04, 1.1180e-03,\n 3.8874e-04, 5.3455e-04, 8.4939e-04, 3.7391e-04, 4.4140e-04, 3.4349e-03,\n 6.2467e-04, 5.4517e-04, 3.1942e-04, 6.8625e-04, 1.1834e-03, 4.2608e-04,\n 4.9806e-03, 3.4489e-04, 5.5896e-03, 4.0756e-03, 3.6872e-04, 3.6407e-03,\n 1.6913e-03, 1.3179e-03, 3.6646e-04, 5.4444e-04, 2.8425e-04, 2.3251e-03,\n 2.9822e-04, 3.0059e-03, 5.1789e-03, 2.2357e-03, 4.5775e-04, 5.9676e-04,\n 5.4450e-04, 2.1836e-04, 4.0193e-03, 1.5523e-03, 2.1445e-04, 3.1683e-04,\n 3.5699e-04, 2.6858e-04, 3.5522e-04, 9.6699e-03, 1.1055e-03, 1.7681e-07,\n 5.9175e-04, 2.1674e-04, 1.5502e-03, 4.6328e-04, 2.8919e-04, 5.3081e-04,\n 3.3816e-04, 1.5535e-03, 4.5573e-04, 6.3266e-04, 3.1465e-04, 5.1166e-03,\n 8.9968e-03, 4.9058e-03, 2.7768e-03, 8.4133e-03, 3.8104e-04, 1.3948e-03,\n 1.4335e-02, 3.5704e-03, 3.0210e-04, 3.4484e-04, 5.8360e-04, 1.4558e-03,\n 5.4878e-04, 1.3311e-02, 5.6903e-04, 5.3376e-04, 3.4830e-04, 6.3211e-03,\n 6.1925e-04, 3.9842e-04, 7.8910e-03, 8.0119e-04, 2.6102e-04, 1.0268e-03,\n 3.5184e-04, 4.5329e-04, 2.8406e-04, 9.1161e-04, 4.5357e-03, 4.0787e-04,\n 3.0818e-03, 3.3322e-04, 7.4244e-03, 7.1693e-04, 7.1747e-03, 6.2522e-04,\n 4.9498e-04, 9.9778e-04, 6.4956e-04, 1.6965e-03, 4.7488e-04, 2.6312e-03,\n 9.3089e-03, 4.0281e-04, 4.2081e-04, 1.0088e-03, 4.0832e-04, 3.0809e-04,\n 1.5040e-03, 6.0776e-04, 1.8630e-03, 6.2271e-04, 3.4448e-03, 4.4320e-04,\n 5.0169e-04, 4.0477e-04, 5.1174e-04, 2.8797e-04, 6.6290e-03, 3.2876e-04,\n 6.0360e-04, 5.1379e-04, 5.9975e-04, 3.3811e-04, 5.2605e-04, 2.5335e-04,\n 4.8613e-04, 1.9688e-03, 4.5398e-04, 4.5958e-04, 2.2103e-03, 3.3574e-04,\n 3.1829e-04, 2.7412e-04, 5.0645e-03, 3.1492e-03, 3.0951e-03, 4.4955e-04,\n 3.0829e-04, 5.5580e-04, 2.2345e-03, 2.1864e-04, 1.5193e-03, 6.3939e-03,\n 2.2752e-03, 1.2239e-03, 3.6956e-04, 3.5456e-03, 1.1048e-02, 3.7842e-03,\n 5.5431e-04, 3.0960e-04, 8.8471e-04, 7.4001e-04, 3.1152e-04, 5.4756e-04,\n 1.4985e-03, 3.9097e-03, 3.8055e-04, 3.9859e-04, 4.6407e-04, 2.2067e-03,\n 7.6721e-03, 3.0660e-04, 6.2631e-04, 2.9286e-04, 3.7713e-04, 3.8416e-03,\n 3.6981e-04, 1.0275e-02, 2.0089e-04, 3.6599e-04, 7.4046e-04, 7.5739e-04,\n 4.6482e-03, 8.5539e-03, 7.3173e-04, 4.5245e-04, 3.3978e-03, 7.0290e-04,\n 4.7800e-04, 3.8433e-03, 7.3364e-04, 3.3704e-04, 2.9371e-04, 2.9388e-04,\n 4.3646e-04, 4.3216e-04, 2.6743e-04, 1.0773e-03, 6.9993e-04, 1.0167e-02,\n 1.0960e-03, 4.3254e-04, 9.6444e-03, 5.6731e-04, 5.0299e-04, 3.3398e-03,\n 1.2002e-02, 2.2136e-09, 2.5375e-03, 3.3271e-04, 5.6762e-03, 9.3208e-04,\n 5.6217e-04, 3.2318e-04, 5.0955e-03, 7.3001e-04, 3.2252e-04, 3.1582e-04,\n 2.4303e-04, 3.2663e-04, 8.2659e-03, 4.8449e-04, 2.6013e-04, 1.0443e-02,\n 1.3333e-03, 3.3159e-04, 3.1621e-04, 1.4900e-02, 1.2927e-02, 2.1890e-03,\n 2.5784e-04, 5.0037e-04, 4.6124e-04, 6.1742e-04, 5.3782e-04, 4.6817e-04,\n 7.4277e-04, 4.7429e-04, 2.1580e-03, 3.5350e-04, 4.7847e-04, 8.3337e-04,\n 4.5079e-03, 5.6095e-04, 2.7611e-03, 5.2061e-04, 2.3819e-04, 8.6924e-04,\n 2.9582e-03, 8.5180e-04, 1.2413e-03, 1.4509e-03, 5.7622e-04, 1.9052e-03,\n 1.2466e-02, 4.0383e-04, 2.2183e-03, 1.3653e-03, 2.9453e-04, 3.8469e-03,\n 4.8301e-04, 7.5992e-04, 3.0742e-04, 9.8982e-04, 5.7186e-04, 3.2481e-03,\n 4.6708e-04, 5.6997e-03]), 'model.layer2.1.bn3.num_batches_tracked': tensor(7160), 'model.layer2.2.conv1.weight': tensor([[[[ 0.0149]],\n\n [[ 0.0085]],\n\n [[-0.0233]],\n\n ...,\n\n [[ 0.0246]],\n\n [[ 0.0060]],\n\n [[ 0.0187]]],\n\n\n [[[ 0.0051]],\n\n [[-0.0327]],\n\n [[-0.0288]],\n\n ...,\n\n [[ 0.0054]],\n\n [[ 0.0155]],\n\n [[-0.0238]]],\n\n\n [[[ 0.0068]],\n\n [[-0.0297]],\n\n [[ 0.0153]],\n\n ...,\n\n [[ 0.0253]],\n\n [[-0.0438]],\n\n [[-0.0024]]],\n\n\n ...,\n\n\n [[[ 0.0027]],\n\n [[-0.0081]],\n\n [[-0.0015]],\n\n ...,\n\n [[ 0.0432]],\n\n [[ 0.0100]],\n\n [[ 0.0572]]],\n\n\n [[[ 0.0152]],\n\n [[ 0.0019]],\n\n [[-0.0070]],\n\n ...,\n\n [[ 0.0473]],\n\n [[ 0.0235]],\n\n [[-0.0105]]],\n\n\n [[[ 0.0256]],\n\n [[ 0.0069]],\n\n [[ 0.0548]],\n\n ...,\n\n [[-0.0109]],\n\n [[ 0.0127]],\n\n [[-0.0294]]]]), 'model.layer2.2.bn1.weight': tensor([0.1022, 0.1252, 0.2063, 0.2030, 0.1154, 0.1629, 0.1585, 0.1330, 0.2265,\n 0.1661, 0.1901, 0.1905, 0.1636, 0.1529, 0.1966, 0.1398, 0.1872, 0.1363,\n 0.1255, 0.1821, 0.1899, 0.1770, 0.1933, 0.2187, 0.1547, 0.1730, 0.2064,\n 0.1415, 0.1521, 0.1355, 0.2305, 0.1722, 0.1328, 0.1370, 0.1942, 0.1184,\n 0.1109, 0.1073, 0.2037, 0.1199, 0.1918, 0.2435, 0.1453, 0.1341, 0.2075,\n 0.1899, 0.1980, 0.1315, 0.2155, 0.1758, 0.1574, 0.1592, 0.1812, 0.1692,\n 0.1881, 0.2219, 0.1686, 0.1567, 0.1451, 0.1809, 0.1459, 0.1549, 0.1938,\n 0.1658, 0.2051, 0.1780, 0.1973, 0.1703, 0.1796, 0.1439, 0.2131, 0.2181,\n 0.1308, 0.1922, 0.2175, 0.1344, 0.2069, 0.2031, 0.1938, 0.1654, 0.1987,\n 0.1781, 0.2025, 0.2079, 0.1924, 0.1687, 0.1085, 0.2028, 0.1194, 0.1846,\n 0.1972, 0.1320, 0.1219, 0.1637, 0.1562, 0.1673, 0.2020, 0.1240, 0.2057,\n 0.1455, 0.1676, 0.1179, 0.2363, 0.2088, 0.2102, 0.2344, 0.1557, 0.1783,\n 0.1891, 0.1795, 0.1589, 0.1706, 0.1635, 0.1482, 0.1577, 0.1522, 0.1294,\n 0.1541, 0.2109, 0.1382, 0.1505, 0.1696, 0.1937, 0.1351, 0.2144, 0.1308,\n 0.1380, 0.1480]), 'model.layer2.2.bn1.bias': tensor([ 1.4192e-01, 1.9469e-02, -6.9439e-02, 1.5894e-02, 9.1295e-02,\n 6.3164e-02, -4.2766e-02, 6.3045e-02, -9.2423e-02, 8.5756e-02,\n -7.2815e-02, -3.8910e-02, -4.5498e-02, 2.7792e-02, -7.1431e-03,\n 2.6234e-01, 6.8596e-02, 1.8803e-04, 7.5382e-02, -5.6723e-02,\n 5.9016e-02, -1.3837e-02, -4.5084e-03, -7.0244e-02, -8.7606e-02,\n -7.4552e-02, 5.4945e-02, 4.9428e-02, 2.4072e-02, 8.4577e-02,\n -3.2678e-02, 2.6507e-03, 2.6461e-02, 1.9004e-02, 7.0424e-02,\n 1.8218e-01, 7.1981e-02, 1.3488e-01, -1.3121e-01, 2.1184e-01,\n -1.1548e-01, -4.2505e-02, 4.1664e-02, 9.1184e-03, -7.6632e-02,\n -4.1060e-02, -6.1442e-02, 2.8644e-02, 6.7599e-02, -4.5591e-02,\n 2.0009e-02, -3.6326e-02, 3.6177e-02, -3.5273e-03, -3.3395e-02,\n 2.9628e-02, 1.3728e-02, 3.8422e-02, -6.3300e-02, 5.9309e-03,\n 7.2742e-02, 6.7135e-02, -4.5221e-02, -8.3974e-02, 3.0804e-02,\n -3.8921e-02, -2.3215e-02, -7.5018e-02, -2.5045e-02, 5.4205e-02,\n -7.6879e-02, 5.6720e-03, 2.5908e-01, 6.6457e-02, -2.0883e-01,\n 1.2910e-02, -5.7912e-02, -1.0956e-02, -4.8829e-02, -3.7243e-02,\n 2.3501e-02, 4.9559e-03, 2.2173e-03, -9.9589e-02, 3.1624e-03,\n 1.7382e-02, 4.7187e-02, -6.4608e-02, 3.0114e-02, -5.6408e-03,\n -4.8470e-02, 8.7462e-02, 9.4938e-02, 3.9828e-02, 4.1404e-02,\n -1.5601e-02, -2.6407e-02, 7.5909e-02, -1.0495e-01, -8.5456e-02,\n 3.5825e-02, 8.5103e-02, -1.2696e-01, -5.3326e-02, -1.0948e-01,\n -6.6306e-02, 6.6270e-02, 2.1369e-03, -8.2931e-02, 1.9423e-03,\n 2.8276e-03, -2.5195e-02, -3.5793e-02, 3.0759e-03, -1.1221e-02,\n -4.6781e-02, 1.0966e-01, 3.4090e-02, -4.7476e-02, 4.3113e-02,\n -4.0748e-02, 2.3362e-02, -1.4581e-01, 4.5093e-04, -1.2424e-01,\n 8.3169e-02, 4.2764e-02, 1.4469e-02]), 'model.layer2.2.bn1.running_mean': tensor([-6.8105e-02, -1.2630e-01, -3.8148e-02, 6.2514e-02, -2.6517e-01,\n -1.2291e-01, -7.5748e-02, -1.5825e-01, -4.7607e-02, -3.2059e-01,\n -9.1099e-02, 2.9784e-02, -4.4436e-03, 1.3953e-01, 1.0291e-01,\n -1.3339e-01, -1.5793e-01, -1.0611e-01, 1.1685e-02, 6.4526e-02,\n -2.1747e-01, -7.5630e-03, -8.7825e-02, -2.5191e-02, -1.4013e-01,\n 8.9983e-02, -1.0614e-01, 1.3710e-01, -6.6756e-03, -8.2611e-02,\n -6.2877e-02, -2.3241e-02, 2.2913e-02, -6.6717e-02, -1.1871e-01,\n -9.6377e-02, 4.9936e-02, 1.2030e-01, -2.4429e-02, -1.0950e-01,\n 2.5397e-02, -2.0978e-01, -1.6745e-02, 5.3781e-02, 3.8179e-03,\n -7.1525e-02, 5.0311e-02, 1.4554e-01, -1.4108e-01, 1.1258e-01,\n -1.1563e-01, -1.6922e-01, -3.0928e-02, 9.3868e-03, -7.3661e-02,\n 1.3312e-02, 4.2543e-02, 7.6193e-02, 2.2586e-01, -8.2156e-02,\n -1.9266e-01, -1.6402e-01, -1.4945e-01, -2.7239e-03, -2.6149e-01,\n -1.8937e-01, 1.2290e-01, -1.3483e-01, 3.5938e-02, -2.6698e-02,\n -3.5451e-01, -2.3422e-01, -6.9086e-02, -3.2637e-02, -1.2613e-01,\n 1.1687e-02, -2.0347e-02, -1.7048e-02, -5.5581e-02, 1.1996e-01,\n 1.3489e-01, 7.9576e-02, -1.2019e-01, -8.4362e-02, -2.4376e-01,\n 6.7535e-02, 1.7417e-01, 4.1067e-01, 2.7336e-03, 7.6368e-02,\n -1.0981e-01, 5.8580e-02, -2.0146e-01, -1.1700e-01, -3.0579e-03,\n -1.6814e-01, -3.3618e-02, 1.5868e-02, -3.8261e-02, -5.0983e-02,\n -9.0261e-02, -1.1737e-01, 2.9446e-02, -9.7820e-02, -5.5806e-02,\n -7.4953e-02, -4.8407e-02, -8.7281e-02, 7.6404e-02, -1.9234e-01,\n -5.5370e-02, -7.4705e-02, 2.2224e-01, 2.0182e-01, -1.3712e-04,\n -4.2777e-02, 1.2122e-01, 1.5138e-02, -1.1301e-01, -2.0692e-01,\n -4.1191e-02, -1.5081e-01, -6.4672e-02, -1.3631e-01, 2.0813e-02,\n 1.2749e-01, -7.9523e-03, -3.4183e-02]), 'model.layer2.2.bn1.running_var': tensor([0.0303, 0.0253, 0.0235, 0.0352, 0.0212, 0.0509, 0.0182, 0.0201, 0.0296,\n 0.0438, 0.0174, 0.0376, 0.0180, 0.0289, 0.0321, 0.0966, 0.0536, 0.0114,\n 0.0265, 0.0236, 0.0459, 0.0304, 0.0438, 0.0320, 0.0124, 0.0200, 0.0457,\n 0.0275, 0.0302, 0.0475, 0.0458, 0.0353, 0.0263, 0.0335, 0.0552, 0.0531,\n 0.0168, 0.0219, 0.0236, 0.0705, 0.0191, 0.0465, 0.0282, 0.0258, 0.0311,\n 0.0204, 0.0331, 0.0217, 0.0454, 0.0157, 0.0302, 0.0178, 0.0262, 0.0200,\n 0.0306, 0.0608, 0.0350, 0.0265, 0.0245, 0.0259, 0.0302, 0.0394, 0.0360,\n 0.0176, 0.0760, 0.0234, 0.0318, 0.0188, 0.0244, 0.0258, 0.0240, 0.0476,\n 0.1052, 0.0477, 0.0217, 0.0189, 0.0215, 0.0356, 0.0207, 0.0187, 0.0392,\n 0.0289, 0.0431, 0.0325, 0.0324, 0.0318, 0.0196, 0.0234, 0.0175, 0.0363,\n 0.0230, 0.0363, 0.0153, 0.0255, 0.0301, 0.0241, 0.0285, 0.0369, 0.0252,\n 0.0195, 0.0386, 0.0250, 0.0286, 0.0364, 0.0276, 0.0458, 0.0380, 0.0260,\n 0.0237, 0.0417, 0.0256, 0.0167, 0.0207, 0.0192, 0.0287, 0.0269, 0.0399,\n 0.0200, 0.0282, 0.0296, 0.0172, 0.0354, 0.0173, 0.0262, 0.0219, 0.0251,\n 0.0206, 0.0215]), 'model.layer2.2.bn1.num_batches_tracked': tensor(7160), 'model.layer2.2.conv2.weight': tensor([[[[ 0.0014, -0.0002, -0.0037],\n [ 0.0150, -0.0038, 0.0081],\n [ 0.0053, -0.0098, 0.0033]],\n\n [[ 0.0178, 0.0089, 0.0112],\n [ 0.0154, 0.0116, -0.0022],\n [ 0.0119, 0.0145, 0.0132]],\n\n [[ 0.0080, 0.0152, 0.0020],\n [ 0.0086, 0.0077, 0.0326],\n [-0.0047, -0.0028, -0.0069]],\n\n ...,\n\n [[ 0.0032, -0.0036, -0.0040],\n [-0.0091, -0.0125, -0.0088],\n [-0.0202, -0.0025, -0.0002]],\n\n [[-0.0265, -0.0104, 0.0138],\n [-0.0161, 0.0130, 0.0245],\n [-0.0136, 0.0030, 0.0119]],\n\n [[ 0.0187, 0.0164, 0.0087],\n [ 0.0266, 0.0145, 0.0353],\n [ 0.0131, 0.0095, 0.0179]]],\n\n\n [[[-0.0045, 0.0149, 0.0008],\n [ 0.0099, 0.0354, -0.0054],\n [-0.0275, -0.0609, -0.0384]],\n\n [[-0.0091, -0.0093, 0.0046],\n [ 0.0043, 0.0012, 0.0072],\n [ 0.0075, -0.0027, 0.0104]],\n\n [[ 0.0144, 0.0119, -0.0061],\n [-0.0065, -0.0215, -0.0265],\n [-0.0045, 0.0008, -0.0093]],\n\n ...,\n\n [[-0.0188, -0.0136, -0.0246],\n [-0.0037, -0.0012, -0.0170],\n [-0.0017, 0.0009, 0.0281]],\n\n [[ 0.0085, 0.0040, -0.0058],\n [ 0.0225, 0.0040, -0.0138],\n [ 0.0016, -0.0111, -0.0104]],\n\n [[-0.0116, -0.0034, -0.0122],\n [-0.0097, 0.0097, 0.0021],\n [-0.0087, 0.0034, 0.0021]]],\n\n\n [[[-0.0133, -0.0152, -0.0112],\n [-0.0027, 0.0100, 0.0072],\n [-0.0045, -0.0031, 0.0032]],\n\n [[-0.0123, -0.0081, -0.0067],\n [-0.0107, -0.0092, 0.0051],\n [ 0.0137, 0.0243, -0.0044]],\n\n [[ 0.0050, 0.0172, 0.0153],\n [-0.0121, -0.0297, -0.0147],\n [ 0.0073, 0.0082, -0.0075]],\n\n ...,\n\n [[-0.0061, -0.0093, 0.0129],\n [ 0.0309, -0.0368, -0.0018],\n [ 0.0252, 0.0602, -0.0086]],\n\n [[-0.0126, -0.0114, 0.0033],\n [-0.0095, 0.0284, 0.0071],\n [-0.0349, -0.0042, 0.0203]],\n\n [[-0.0187, -0.0343, -0.0138],\n [ 0.0518, 0.0126, 0.0283],\n [ 0.0249, 0.0144, 0.0470]]],\n\n\n ...,\n\n\n [[[-0.0232, -0.0137, -0.0163],\n [-0.0195, -0.0026, -0.0161],\n [-0.0355, 0.0484, 0.0132]],\n\n [[-0.0145, -0.0207, -0.0124],\n [-0.0093, -0.0080, 0.0032],\n [-0.0253, 0.0461, 0.0547]],\n\n [[-0.0304, -0.0150, -0.0158],\n [-0.0296, -0.0199, -0.0228],\n [ 0.0035, 0.0108, 0.0201]],\n\n ...,\n\n [[ 0.0049, 0.0175, -0.0021],\n [-0.0011, -0.0088, 0.0023],\n [-0.0025, -0.0185, -0.0043]],\n\n [[ 0.0032, -0.0089, 0.0031],\n [-0.0188, -0.0347, -0.0274],\n [-0.0117, -0.0261, -0.0200]],\n\n [[ 0.0238, 0.0139, -0.0046],\n [ 0.0226, 0.0194, -0.0177],\n [ 0.0172, -0.0167, -0.0541]]],\n\n\n [[[ 0.0143, 0.0109, 0.0023],\n [ 0.0169, -0.0124, -0.0118],\n [ 0.0022, 0.0137, -0.0095]],\n\n [[-0.0012, -0.0103, -0.0005],\n [ 0.0036, 0.0058, -0.0075],\n [-0.0013, 0.0292, 0.0163]],\n\n [[ 0.0098, -0.0214, -0.0179],\n [ 0.0934, 0.0049, -0.1201],\n [ 0.0208, -0.0226, -0.0262]],\n\n ...,\n\n [[ 0.0021, -0.0170, -0.0173],\n [-0.0122, 0.0064, 0.0347],\n [-0.0079, 0.0017, 0.0048]],\n\n [[ 0.0197, 0.0006, -0.0141],\n [-0.0165, -0.0171, -0.0370],\n [-0.0161, -0.0270, -0.0248]],\n\n [[-0.0020, 0.0089, 0.0029],\n [-0.0431, 0.0096, 0.0197],\n [ 0.0029, 0.0148, 0.0262]]],\n\n\n [[[-0.0040, -0.0209, -0.0163],\n [ 0.0039, 0.0001, 0.0108],\n [ 0.0183, 0.0248, 0.0213]],\n\n [[-0.0151, -0.0469, -0.0111],\n [-0.0097, 0.0173, 0.0057],\n [-0.0013, -0.0123, 0.0142]],\n\n [[ 0.0037, -0.0062, -0.0022],\n [ 0.0033, -0.0131, -0.0171],\n [ 0.0084, 0.0208, 0.0278]],\n\n ...,\n\n [[-0.0359, -0.0631, -0.0288],\n [-0.0766, 0.0210, -0.0158],\n [-0.0125, -0.0121, 0.0186]],\n\n [[ 0.0070, 0.0272, 0.0067],\n [ 0.0160, -0.0204, 0.0026],\n [-0.0181, 0.0176, 0.0020]],\n\n [[-0.0134, 0.0117, 0.0040],\n [-0.0256, -0.0066, -0.0244],\n [ 0.0146, 0.0237, 0.0054]]]]), 'model.layer2.2.bn2.weight': tensor([0.2212, 0.1788, 0.2093, 0.2000, 0.1697, 0.2141, 0.1836, 0.2188, 0.1561,\n 0.1384, 0.1204, 0.1843, 0.1320, 0.1297, 0.2270, 0.2045, 0.2066, 0.1383,\n 0.1548, 0.2103, 0.1333, 0.1862, 0.1612, 0.1895, 0.2153, 0.1897, 0.1606,\n 0.1722, 0.1357, 0.2009, 0.1208, 0.2124, 0.2163, 0.1579, 0.1554, 0.2347,\n 0.1994, 0.1672, 0.1600, 0.1518, 0.2202, 0.1960, 0.1601, 0.2258, 0.1727,\n 0.1916, 0.1872, 0.2009, 0.2022, 0.2031, 0.1893, 0.2103, 0.2076, 0.1048,\n 0.2145, 0.1428, 0.2069, 0.1563, 0.1118, 0.2183, 0.1998, 0.2074, 0.1943,\n 0.1953, 0.1953, 0.1843, 0.1503, 0.1265, 0.1786, 0.2154, 0.2092, 0.1787,\n 0.1438, 0.1618, 0.1143, 0.2007, 0.2211, 0.1843, 0.1145, 0.1778, 0.2177,\n 0.1765, 0.1896, 0.1290, 0.1446, 0.1994, 0.1806, 0.1854, 0.1630, 0.2542,\n 0.2254, 0.2173, 0.1529, 0.2169, 0.1734, 0.1181, 0.1942, 0.2209, 0.1525,\n 0.1389, 0.2195, 0.2118, 0.1757, 0.2213, 0.1716, 0.1506, 0.1601, 0.1679,\n 0.1965, 0.2079, 0.1709, 0.2161, 0.2022, 0.1842, 0.1227, 0.2184, 0.1964,\n 0.2163, 0.2026, 0.1246, 0.2104, 0.1771, 0.1630, 0.1985, 0.1846, 0.2117,\n 0.2105, 0.1287]), 'model.layer2.2.bn2.bias': tensor([-7.3118e-02, -3.0055e-02, -8.1645e-02, -2.7631e-02, -2.9997e-02,\n -6.5979e-02, 5.0920e-03, 8.6834e-03, -2.5513e-02, 2.1131e-01,\n 1.4256e-01, -8.2810e-02, 1.3672e-02, 1.4762e-01, -4.1234e-02,\n -1.6727e-02, -9.2056e-02, 5.1055e-03, -3.8254e-02, -7.8387e-02,\n 4.9463e-02, -3.8345e-02, -2.7647e-02, -3.9597e-02, -5.3561e-02,\n 1.1101e-01, 6.8672e-02, 1.2413e-01, 7.2285e-02, -1.0986e-01,\n 1.8567e-01, -4.2524e-02, -4.8332e-02, 1.5732e-02, -4.3358e-02,\n -7.4067e-02, -1.6550e-02, 7.9331e-02, -2.9865e-02, -3.1419e-03,\n -6.8786e-02, -8.2095e-05, 3.0153e-02, -5.4517e-02, 3.6648e-02,\n -4.3953e-02, -3.3252e-02, -1.6633e-01, -3.4004e-02, -5.4942e-02,\n -4.9473e-02, -7.1178e-02, -1.2870e-02, 2.5586e-02, -1.1377e-01,\n -3.3676e-02, -1.2154e-01, 8.5426e-02, 2.1546e-01, -2.4526e-02,\n -5.8373e-02, -3.9107e-02, -5.7994e-02, -1.6968e-01, -7.6703e-02,\n 3.8944e-02, 8.8565e-02, 2.8714e-01, -1.6229e-02, -8.0385e-02,\n 8.3646e-03, -1.1079e-02, 1.4076e-02, -4.9011e-02, 1.1276e-01,\n -9.5059e-02, -6.9944e-02, 5.7922e-02, 1.5682e-01, 6.5796e-02,\n -3.8576e-02, -4.5985e-02, -7.7482e-02, 1.3242e-01, 1.4879e-01,\n -3.5992e-02, -4.6274e-02, -3.2921e-02, 7.6635e-02, -1.6672e-01,\n -1.2065e-01, -5.6025e-02, -1.5827e-02, 6.1845e-02, 4.9333e-02,\n 6.9471e-02, -8.4281e-02, -1.1529e-01, 2.7987e-02, 1.0180e-01,\n 2.5351e-03, -1.2132e-01, -3.0077e-02, -8.8971e-02, -6.6298e-03,\n 1.0986e-01, 9.9913e-02, 7.2074e-02, 3.5081e-02, 5.9574e-02,\n -8.4321e-02, -8.0417e-02, -7.4359e-02, 6.0067e-02, 7.4843e-02,\n -1.7193e-01, 8.1602e-02, -1.0030e-01, -2.6405e-02, 9.8145e-03,\n -1.5544e-01, 9.8196e-02, 4.6701e-02, -9.9269e-02, -8.5910e-02,\n -1.0161e-01, -5.1338e-02, 2.0456e-01]), 'model.layer2.2.bn2.running_mean': tensor([-0.0981, 0.0521, -0.0228, 0.0339, -0.0342, -0.1671, 0.1892, -0.0078,\n -0.0342, 0.0267, 0.1289, -0.2443, -0.1169, 0.0624, 0.1765, 0.0305,\n -0.0764, 0.0334, -0.2296, -0.0637, -0.0749, -0.0974, -0.0438, 0.1301,\n -0.0937, 0.1331, 0.1978, 0.2481, -0.0506, -0.1148, -0.3675, 0.1015,\n -0.1132, -0.0319, -0.2340, -0.0656, 0.0421, -0.0534, -0.0379, -0.0426,\n 0.1097, 0.0895, -0.0600, -0.0049, 0.1098, 0.0715, 0.0173, -0.1783,\n 0.1138, -0.0578, -0.0929, 0.0359, 0.0838, -0.1960, -0.1491, 0.1007,\n -0.0737, 0.0649, 0.0780, 0.0800, -0.1551, -0.1926, -0.0158, 0.0171,\n -0.0981, 0.1975, 0.0727, -0.1458, 0.1021, -0.1191, -0.1206, -0.0935,\n -0.0964, 0.1447, -0.0599, -0.0678, -0.1767, 0.0157, -0.1182, 0.1123,\n 0.1061, -0.0383, -0.1027, 0.1834, 0.1196, -0.1474, -0.1086, -0.0493,\n 0.1838, 0.0014, -0.1033, -0.0884, 0.0687, 0.1235, 0.1817, -0.2198,\n -0.1233, 0.0066, -0.4165, -0.1371, 0.0025, 0.0152, 0.0902, -0.0885,\n -0.0770, 0.1532, 0.1240, 0.2215, 0.1429, 0.1303, -0.1714, -0.0653,\n -0.1268, -0.1914, -0.1664, 0.1468, 0.0806, -0.0144, 0.1064, 0.0489,\n -0.2521, 0.2150, -0.1953, -0.1755, -0.0205, 0.0202, 0.0558, -0.1587]), 'model.layer2.2.bn2.running_var': tensor([0.0577, 0.0211, 0.0295, 0.0328, 0.0256, 0.0472, 0.0220, 0.0276, 0.0186,\n 0.0298, 0.0181, 0.0164, 0.0160, 0.0207, 0.0376, 0.0325, 0.0282, 0.0117,\n 0.0134, 0.0252, 0.0158, 0.0251, 0.0150, 0.0193, 0.0477, 0.0433, 0.0246,\n 0.0489, 0.0275, 0.0221, 0.0199, 0.0279, 0.0480, 0.0279, 0.0164, 0.0578,\n 0.0280, 0.0207, 0.0135, 0.0195, 0.0287, 0.0213, 0.0374, 0.0339, 0.0305,\n 0.0210, 0.0148, 0.0156, 0.0298, 0.0285, 0.0175, 0.0151, 0.0292, 0.0133,\n 0.0278, 0.0163, 0.0276, 0.0313, 0.0178, 0.0328, 0.0371, 0.0439, 0.0185,\n 0.0121, 0.0177, 0.0362, 0.0228, 0.0322, 0.0173, 0.0312, 0.0415, 0.0264,\n 0.0381, 0.0153, 0.0207, 0.0142, 0.0443, 0.0273, 0.0165, 0.0258, 0.0273,\n 0.0163, 0.0168, 0.0263, 0.0282, 0.0502, 0.0167, 0.0225, 0.0324, 0.0129,\n 0.0248, 0.0341, 0.0202, 0.0438, 0.0270, 0.0302, 0.0250, 0.0279, 0.0195,\n 0.0213, 0.0312, 0.0259, 0.0244, 0.0351, 0.0235, 0.0283, 0.0230, 0.0346,\n 0.0272, 0.0495, 0.0154, 0.0305, 0.0267, 0.0336, 0.0248, 0.0126, 0.0414,\n 0.0180, 0.0188, 0.0193, 0.0150, 0.0291, 0.0235, 0.0142, 0.0142, 0.0180,\n 0.0293, 0.0303]), 'model.layer2.2.bn2.num_batches_tracked': tensor(7160), 'model.layer2.2.conv3.weight': tensor([[[[-0.0179]],\n\n [[ 0.0361]],\n\n [[ 0.0041]],\n\n ...,\n\n [[-0.0083]],\n\n [[ 0.0023]],\n\n [[ 0.0058]]],\n\n\n [[[ 0.0045]],\n\n [[-0.0131]],\n\n [[ 0.0014]],\n\n ...,\n\n [[ 0.0314]],\n\n [[-0.0138]],\n\n [[-0.0165]]],\n\n\n [[[-0.0271]],\n\n [[-0.0031]],\n\n [[ 0.0172]],\n\n ...,\n\n [[-0.0096]],\n\n [[ 0.0003]],\n\n [[ 0.0020]]],\n\n\n ...,\n\n\n [[[ 0.0211]],\n\n [[-0.0228]],\n\n [[-0.0133]],\n\n ...,\n\n [[ 0.0102]],\n\n [[ 0.0133]],\n\n [[ 0.0118]]],\n\n\n [[[ 0.0083]],\n\n [[ 0.0089]],\n\n [[ 0.0149]],\n\n ...,\n\n [[-0.0121]],\n\n [[ 0.0028]],\n\n [[ 0.0057]]],\n\n\n [[[ 0.0009]],\n\n [[ 0.0009]],\n\n [[ 0.0113]],\n\n ...,\n\n [[-0.0107]],\n\n [[-0.0108]],\n\n [[ 0.0017]]]]), 'model.layer2.2.bn3.weight': tensor([ 7.0880e-02, 4.8990e-02, 6.7883e-02, 1.9827e-01, 2.1363e-01,\n 1.1423e-01, -7.3334e-03, 1.8445e-01, 1.1367e-01, 1.1421e-01,\n 1.1508e-01, 8.2101e-02, 7.3928e-02, 6.5504e-02, 1.7343e-01,\n 7.8929e-02, 6.0328e-02, 1.9154e-01, 9.2523e-02, 1.8450e-01,\n 4.2989e-02, 1.0161e-01, 3.9014e-02, 1.3769e-01, 5.8623e-02,\n 2.0317e-01, 1.7715e-01, 1.6471e-01, 1.4592e-01, 1.4455e-01,\n 4.4182e-02, 1.8064e-01, 4.7497e-02, 1.0353e-01, 9.7094e-02,\n 2.6780e-02, -8.2968e-04, 7.5665e-02, 2.1463e-01, 2.7380e-03,\n 8.6878e-02, 9.8774e-02, 2.2139e-01, 7.4470e-02, 1.3884e-01,\n 1.0549e-01, 9.5112e-02, 1.0290e-01, 6.2445e-02, 8.1120e-02,\n 1.0305e-01, 1.0772e-01, 2.6102e-01, 8.9281e-02, 6.5506e-02,\n 5.3358e-02, 1.2693e-01, 1.0852e-01, -1.3202e-03, 2.1255e-01,\n 9.5898e-02, 6.4735e-02, 1.8091e-01, 1.0100e-01, 8.4465e-02,\n 1.2700e-01, 1.0211e-01, 7.0666e-02, 6.1994e-02, 5.5363e-02,\n 6.0169e-02, 1.1955e-01, 4.8800e-02, 1.7858e-01, 2.4491e-03,\n 9.9050e-02, 2.1961e-02, 1.0027e-02, 6.8055e-02, 8.1232e-02,\n 2.7258e-02, 6.8274e-02, 5.0009e-02, 1.1468e-01, 1.7042e-01,\n 4.9465e-02, 7.2666e-02, 9.6299e-02, 4.9005e-02, 2.1203e-01,\n 8.8144e-02, 4.7633e-02, 4.9286e-02, 1.0405e-01, 1.5380e-01,\n 1.0972e-01, 5.2554e-02, 6.2831e-02, 5.3858e-02, 5.2736e-02,\n 1.1790e-01, 6.9973e-02, -2.1002e-02, -3.5732e-04, 2.7402e-01,\n 1.0363e-01, 1.1785e-01, 9.0917e-02, 3.6701e-02, 1.2083e-01,\n 3.5377e-02, 1.7731e-01, 2.5287e-01, 1.3651e-01, 9.4070e-02,\n 2.2419e-03, 8.2615e-02, 4.1185e-02, 2.7215e-02, 1.2387e-01,\n 1.8660e-01, 1.0999e-01, 8.4045e-02, 1.2024e-01, 2.6747e-01,\n 1.8359e-01, 4.9384e-04, 2.9876e-02, 1.6317e-01, 1.2517e-01,\n 1.0220e-01, 1.2240e-01, 1.4029e-01, 7.6801e-02, -7.6162e-04,\n 2.7782e-01, 7.3239e-02, 1.3424e-01, 1.4291e-01, 1.3090e-01,\n 5.4300e-02, 1.5318e-01, 1.0936e-01, 1.9470e-01, 4.2611e-02,\n 8.5907e-02, 8.5646e-02, 5.9918e-02, 5.1022e-02, 1.0022e-01,\n 3.0121e-02, 1.5103e-01, 1.2940e-01, 1.7996e-01, 1.6661e-01,\n 1.2810e-02, 1.4215e-01, 9.0324e-02, 9.9468e-02, 1.1999e-01,\n 1.5398e-01, 5.0350e-02, 1.2841e-02, 7.4253e-02, 4.6748e-02,\n 2.3153e-01, 1.7548e-02, 2.1728e-01, 6.3284e-02, 1.3252e-01,\n 1.4800e-01, 5.4903e-04, 3.0713e-03, -2.6697e-02, 1.2650e-01,\n 6.0365e-02, 9.7148e-02, 3.6510e-02, 1.8347e-01, 7.8034e-02,\n 1.2061e-01, 9.8481e-02, 4.1030e-02, 7.7922e-02, 9.6178e-02,\n 7.7159e-02, 1.1289e-01, 5.0782e-02, 5.6003e-02, 1.4251e-01,\n 2.8814e-02, 8.3414e-02, 1.6942e-01, 1.1054e-01, 1.6210e-01,\n 6.2943e-02, 7.9925e-02, 7.4118e-02, 1.8681e-01, 4.5214e-02,\n 3.3742e-01, 1.0922e-01, 8.0003e-02, 2.2658e-01, 1.2502e-01,\n 1.2988e-01, 1.1316e-01, 4.2340e-02, 1.9783e-02, 3.2424e-01,\n 8.2989e-02, 3.5270e-02, 1.7885e-02, 1.3931e-01, 1.1830e-01,\n 9.5040e-02, 2.0393e-01, 5.3793e-03, 7.2929e-02, 8.6800e-02,\n 9.9946e-02, 1.8978e-01, 8.0339e-02, 1.2657e-01, 9.7142e-03,\n 1.6104e-01, 6.8044e-02, 1.3956e-01, 8.0345e-02, 3.0657e-02,\n 1.2391e-01, 1.2600e-01, 1.3784e-01, 1.9843e-01, 1.5018e-01,\n 1.1406e-01, 7.6623e-02, -3.0017e-03, -3.8198e-03, 1.1726e-01,\n 7.5878e-02, 1.6275e-01, 7.0431e-02, 4.1159e-02, 1.7144e-01,\n 8.4888e-02, 5.4058e-02, 1.9347e-02, 1.0384e-01, 1.3534e-01,\n 1.6422e-01, 1.1979e-01, 1.1153e-01, 6.4891e-02, 1.2325e-01,\n 1.4919e-01, -7.6633e-03, 6.2322e-02, 1.1594e-01, 6.0394e-03,\n 1.1519e-01, 1.7779e-02, 4.7501e-02, -7.2849e-03, 1.4238e-01,\n -6.7033e-03, 3.1840e-01, 6.1153e-02, 6.6808e-03, 8.4727e-02,\n 1.1658e-01, 1.8121e-01, 1.8158e-01, 8.9811e-02, 1.4836e-01,\n 7.4639e-02, 1.3515e-01, 1.4471e-01, 1.1900e-01, 1.3479e-01,\n 7.6569e-02, 2.2974e-01, 8.9857e-02, 1.8186e-01, 1.1183e-01,\n 7.2941e-02, 1.1947e-01, 7.7452e-02, 5.0029e-02, 1.0997e-01,\n 2.6918e-02, 2.8365e-01, 8.3601e-02, 5.7666e-02, 6.5126e-02,\n 3.1783e-03, 1.1451e-01, 1.1460e-01, 1.3234e-01, 1.2777e-01,\n 1.6046e-01, 4.5248e-02, 1.1162e-01, 1.6663e-01, 5.9254e-02,\n 9.1519e-02, 2.4341e-01, 1.9197e-01, 1.3842e-01, 8.3369e-02,\n 9.7386e-02, 4.9651e-02, 1.0447e-01, 1.6487e-01, 1.6657e-01,\n 3.6960e-02, 1.5602e-01, 1.8778e-01, 1.0255e-01, 1.5566e-01,\n 9.1748e-02, 8.4432e-02, 1.7541e-01, 2.7272e-01, 6.7934e-03,\n 1.3124e-01, 1.4636e-01, 1.2563e-01, 1.0989e-01, 1.2546e-01,\n 6.4016e-03, 4.4568e-02, 1.0023e-01, 1.2279e-01, 1.3035e-01,\n 1.2772e-01, 7.9668e-02, 3.9896e-02, 5.6010e-02, 1.2937e-01,\n 1.3818e-01, 1.9157e-01, 1.0998e-01, 1.1931e-01, 1.0349e-01,\n 5.7175e-02, 1.3493e-01, 5.1319e-02, 1.4652e-01, -9.8962e-03,\n 7.5421e-02, 1.4240e-01, 6.8477e-02, 8.2498e-02, 1.6229e-01,\n 9.5533e-02, 1.0956e-01, 1.0604e-01, 9.1472e-02, 1.0987e-01,\n 7.9516e-02, 4.6210e-02, 1.6483e-01, 7.4189e-02, 1.6369e-01,\n 5.4138e-02, 1.5579e-01, -3.8557e-02, 4.0346e-02, 4.4466e-02,\n 6.7443e-02, 5.7561e-02, 9.5390e-02, 2.0200e-02, 4.1572e-03,\n 3.4289e-02, 1.4141e-01, 1.2439e-01, 2.1772e-01, 6.7795e-02,\n -7.0932e-05, 4.4310e-02, 4.2315e-02, 1.7640e-01, 3.8005e-02,\n 1.5139e-01, 1.3000e-01, 6.4518e-02, 4.2030e-02, 9.2117e-02,\n 6.0178e-02, 5.0806e-02, 8.9881e-02, 9.2819e-02, 2.6407e-02,\n 1.5038e-01, 7.5128e-02, 1.2113e-01, 8.5075e-02, 1.0293e-01,\n 1.2012e-01, 1.2593e-02, 1.8090e-02, 1.0197e-01, 1.9406e-01,\n 7.4084e-02, 4.3324e-02, 1.1180e-01, 1.7802e-01, 2.3818e-01,\n 8.1177e-03, 8.1181e-02, 1.7338e-01, 2.1991e-01, 2.4977e-02,\n 6.1576e-02, 2.2050e-01, 5.2216e-02, 1.1960e-01, 1.6874e-01,\n 1.2597e-01, 1.9532e-02, 6.1486e-02, 6.9581e-02, 1.6091e-01,\n 2.1858e-01, 5.3833e-02, 3.9921e-02, 8.6775e-02, 1.0303e-01,\n 6.9261e-02, 1.4892e-01, 5.5291e-02, 4.4500e-02, 1.3671e-01,\n 7.2777e-02, 9.3604e-02, 3.8112e-02, 1.4312e-01, 1.5810e-01,\n 1.4432e-01, 5.7964e-02, 9.6953e-02, 1.6444e-01, 1.9782e-01,\n 5.2416e-02, 1.5045e-01, 9.6676e-02, 1.3156e-02, 1.7633e-01,\n 1.6842e-01, 2.4041e-01, 1.7004e-01, 5.8743e-02, 1.5320e-01,\n 1.1495e-01, 7.0968e-02, 7.2105e-02, 7.1746e-02, 6.9276e-02,\n 7.7078e-02, 1.4441e-02, 1.7159e-01, 9.3543e-02, 2.1105e-01,\n 8.8974e-02, 7.6350e-02, 7.1781e-02, 4.2142e-02, 5.0972e-02,\n 1.1042e-01, 8.0776e-02, 1.2845e-01, 9.0495e-02, 1.7513e-01,\n 8.5687e-02, -6.8641e-02, 1.4563e-01, 3.6284e-02, 5.0113e-02,\n 9.9660e-02, 1.1253e-01, 1.3830e-01, 7.7544e-02, 3.4092e-02,\n 1.5867e-01, 5.2468e-02, 6.2029e-02, 1.2404e-01, 5.1561e-02,\n 7.6773e-02, 1.6401e-01, 1.2735e-01, 8.7418e-02, 5.9692e-02,\n 1.0122e-01, 7.8861e-02, 1.1307e-01, 1.6527e-01, 2.6166e-03,\n 1.3877e-01, 3.5829e-02, 1.2912e-01, 1.5601e-01, 1.1339e-01,\n 9.0850e-02, 5.9655e-02, 2.3116e-01, 7.1540e-02, 4.8444e-02,\n 4.0296e-02, 7.8776e-02]), 'model.layer2.2.bn3.bias': tensor([-6.9073e-02, 6.0049e-02, -1.0832e-01, -5.4798e-02, -1.2807e-01,\n 6.8513e-02, -1.2747e-02, -2.0686e-01, -1.2161e-01, -9.6315e-02,\n -9.4741e-02, -6.2726e-02, -1.3170e-01, 5.3169e-02, -6.2918e-02,\n -5.4291e-02, 5.7022e-02, -4.2604e-02, -6.1113e-02, 8.0424e-03,\n -1.9595e-03, -9.6569e-02, -4.1977e-02, -1.2965e-01, -5.9376e-02,\n -1.0049e-01, -9.7369e-02, 6.9868e-02, -9.7489e-02, -6.8856e-02,\n -2.9538e-02, -1.2904e-01, -2.6910e-02, -1.1263e-01, -9.6117e-02,\n -7.4872e-03, 7.7858e-04, -4.5742e-02, 7.5881e-02, -7.3457e-03,\n -8.1839e-02, -3.7391e-02, -6.4651e-03, -1.2686e-01, -5.1199e-02,\n -5.0767e-02, -1.2696e-01, -8.6121e-02, -2.3192e-02, 1.1481e-02,\n -1.4310e-01, 2.7440e-02, 3.2008e-02, -7.3804e-02, -1.0692e-01,\n 1.2696e-02, 3.1913e-02, 7.5218e-02, -1.3663e-02, -5.3250e-02,\n -1.0830e-01, -5.2421e-02, -4.0876e-02, -1.6245e-01, -1.7149e-02,\n -4.3928e-02, -3.7709e-02, -1.1701e-02, 1.7482e-02, -4.5160e-02,\n -4.5875e-02, -7.5213e-03, -4.4529e-02, -3.2956e-02, 9.1221e-04,\n -1.2056e-01, -2.6560e-02, -1.6116e-01, -1.0346e-01, -9.5560e-02,\n -2.4650e-02, -2.1150e-02, -7.5706e-02, -3.4450e-02, -5.7368e-02,\n -3.9763e-02, -4.2934e-02, -9.3645e-02, -8.3131e-02, -5.3881e-02,\n -4.8462e-02, -4.4791e-02, -2.5181e-02, -1.2364e-01, -1.4861e-01,\n -4.8954e-02, -4.3055e-02, -8.9181e-02, -2.7019e-02, 1.5771e-02,\n -1.2947e-01, -5.0997e-02, -7.5464e-02, -2.5824e-03, -2.0575e-01,\n 5.2076e-03, -4.6510e-02, -2.3281e-02, 3.4519e-03, -2.0185e-02,\n -3.3912e-02, -2.3792e-02, 4.7022e-03, -9.2581e-02, -9.9632e-02,\n -3.3897e-02, -4.4998e-02, -2.5673e-02, -2.2495e-02, -7.4826e-02,\n -4.8273e-02, -9.3323e-02, -9.1759e-02, -5.6599e-02, -4.4478e-02,\n -2.4301e-01, -8.9391e-03, -5.3327e-03, -1.2639e-01, 2.4269e-03,\n -8.6716e-03, -3.3928e-02, -4.1841e-02, -1.5013e-02, 8.3139e-03,\n -4.5331e-02, -7.3796e-03, -1.2309e-01, -8.8993e-02, -8.0715e-02,\n -6.9618e-02, 4.2639e-03, -1.0047e-01, -8.1277e-02, 6.3655e-02,\n -1.1649e-01, -7.7149e-02, -4.7095e-02, -6.5466e-02, -8.7416e-02,\n -1.4812e-02, -1.2417e-01, -4.7939e-02, -3.8502e-02, -1.6277e-01,\n -1.3073e-02, -1.8645e-01, -1.8129e-02, -1.1319e-01, -5.9699e-02,\n -2.6718e-02, -5.0820e-02, -8.8948e-03, -1.1038e-01, -1.4658e-02,\n -3.5180e-02, -3.6385e-02, -1.7177e-02, -6.5882e-02, -3.6917e-02,\n -1.1680e-01, 4.3485e-03, 8.2944e-03, 1.1019e-02, 1.5412e-02,\n -6.5567e-02, -1.4307e-01, -1.5768e-02, -9.5915e-02, -6.4657e-02,\n -1.2081e-01, -4.8654e-02, -2.5106e-02, -1.0513e-01, -8.6517e-02,\n -1.1340e-01, -1.2362e-01, -4.1259e-02, -1.1086e-01, 1.6065e-01,\n -2.3026e-02, -8.5169e-02, -1.9184e-01, -1.7803e-01, -9.2594e-02,\n -2.4313e-02, -7.6196e-02, -4.0404e-02, -9.4903e-02, -1.5916e-02,\n 2.7516e-02, -1.0821e-01, -6.7290e-02, -1.2396e-01, -1.8125e-01,\n -3.0688e-02, -7.0909e-02, -3.6210e-02, 1.8511e-03, 2.3747e-02,\n -1.6514e-02, -2.6917e-02, -3.2165e-02, -1.3532e-01, 3.2752e-02,\n -8.1504e-02, -6.8639e-02, -1.7278e-02, -1.2872e-01, -3.6229e-02,\n -9.9996e-02, -3.3211e-02, -9.6104e-02, -3.5034e-02, -8.4246e-03,\n -6.4632e-02, -5.0014e-02, -1.2919e-01, -2.0924e-02, -2.5216e-02,\n -5.3334e-02, -1.4820e-01, -1.1557e-01, -2.0280e-02, -1.4055e-01,\n 1.6309e-02, -6.8283e-02, -1.1488e-02, -1.0923e-02, -6.2223e-02,\n -1.1083e-01, -2.6498e-01, -2.3390e-02, -7.9808e-02, -2.8411e-02,\n -8.4372e-02, -5.7377e-02, -6.6449e-03, -5.2035e-02, -5.8482e-02,\n -8.6250e-02, -1.2274e-01, -5.8614e-02, -4.9710e-02, -1.5359e-02,\n -1.0155e-01, -8.3871e-03, -6.7651e-02, 1.1642e-02, -8.9057e-03,\n -9.5358e-02, -2.6833e-03, -2.7964e-02, -4.9011e-02, -8.0019e-02,\n -1.3235e-02, 1.6761e-02, -1.1841e-01, -1.4217e-02, -9.4186e-02,\n 6.5918e-02, -5.7879e-02, -6.9068e-02, -7.2576e-02, -5.1694e-02,\n -2.6538e-02, -6.8820e-02, -3.3535e-02, -4.2025e-02, -3.8372e-02,\n -6.2551e-02, -8.3532e-02, 2.8225e-03, -6.3834e-02, -8.2686e-02,\n -8.8125e-02, -2.4184e-02, -6.3377e-02, -2.5959e-03, -7.0287e-02,\n 4.2831e-02, -1.0164e-01, -8.5600e-02, -8.3558e-02, -5.5066e-02,\n -1.1914e-02, -1.4797e-04, -1.1905e-01, -1.3523e-01, 3.9681e-02,\n -1.2083e-01, -6.1048e-02, -3.0199e-02, -6.9483e-02, -7.0606e-02,\n -1.7416e-02, -1.9265e-02, -9.0177e-02, 4.3991e-02, -1.3806e-01,\n -1.0192e-01, -2.7584e-02, -1.2798e-01, -1.3600e-01, -1.5407e-01,\n -8.2758e-02, 1.0364e-02, -2.3144e-01, -1.3638e-01, -2.2775e-02,\n 2.7094e-03, -7.7172e-02, 1.1111e-01, -4.7157e-02, -7.7349e-03,\n -2.6987e-01, -1.1391e-01, -3.4818e-02, -5.5141e-02, -1.1346e-01,\n -1.5215e-02, -1.6374e-02, -1.6970e-01, -1.0697e-01, -8.0811e-02,\n -5.0347e-02, -3.8200e-02, -7.2004e-02, 1.1351e-02, -7.0107e-03,\n -1.6040e-01, 3.3946e-02, -1.2953e-01, -9.6317e-02, -1.1391e-01,\n -3.3970e-02, -1.3595e-01, -6.9510e-02, 4.7054e-02, -7.0648e-02,\n -5.8742e-02, 3.6916e-02, -6.4222e-02, -1.0406e-01, -2.3315e-01,\n -8.4132e-02, -9.9668e-02, -9.6829e-02, -5.4386e-02, -3.4676e-02,\n -5.2547e-02, -3.1863e-02, -9.4289e-02, -1.1535e-01, 5.6789e-03,\n -5.2646e-02, 1.0002e-01, -2.9732e-02, -3.6308e-02, -2.6594e-02,\n -4.0978e-03, -7.5206e-02, -6.5830e-02, -2.2467e-02, -9.0052e-03,\n -3.3023e-02, -7.6451e-02, -4.8988e-02, 4.9719e-03, -7.3242e-02,\n 1.3798e-02, -1.6950e-02, -1.0348e-01, -1.3521e-01, -1.9560e-02,\n -7.2304e-02, -7.4703e-02, -1.1042e-01, 3.6493e-02, -8.2302e-02,\n -3.6257e-02, -2.7066e-02, -1.0195e-01, -7.8323e-02, -3.5451e-02,\n -4.6487e-02, -1.1534e-01, -4.8127e-02, -2.3611e-02, -7.7038e-02,\n -1.4157e-01, -5.2516e-02, -2.4982e-02, -7.8070e-02, -2.1581e-01,\n -4.2204e-02, -8.7860e-02, 1.5165e-02, -6.2199e-02, -5.4442e-02,\n -1.6436e-02, -6.2121e-02, -1.5879e-01, -5.3981e-02, -5.4418e-02,\n -3.2451e-02, -3.4571e-02, -1.2503e-02, -1.5418e-01, -9.4191e-02,\n -7.6824e-02, -4.3471e-02, -7.0911e-02, -7.3815e-02, -1.4321e-01,\n -8.6274e-02, -1.0145e-01, -5.6710e-02, -8.3910e-02, -4.8037e-02,\n -1.2495e-01, 2.3500e-02, -3.3713e-02, -6.3922e-02, -1.5161e-01,\n -4.5555e-02, -1.0808e-01, 4.0843e-02, -2.0168e-02, -6.2799e-02,\n 2.3363e-02, -7.7171e-02, -1.4101e-01, -2.1847e-02, 2.8880e-02,\n 5.1335e-02, -1.5604e-01, -9.1447e-02, 9.1186e-03, -9.6333e-02,\n -1.9606e-01, 2.1455e-02, -6.1667e-02, 8.8612e-03, -7.5655e-02,\n -7.0651e-02, -4.1767e-02, -8.5822e-02, -2.9226e-02, -1.1728e-01,\n -6.3663e-02, -9.7300e-03, 5.9556e-02, -8.4239e-02, -2.4076e-01,\n -6.2236e-02, 1.1046e-02, -7.3514e-02, -9.9459e-02, -1.1217e-02,\n -7.8414e-02, -1.3849e-01, -1.6752e-01, -8.9435e-02, -1.1104e-01,\n -3.4093e-02, -7.4910e-02, -1.9733e-02, 3.0782e-03, -6.4200e-02,\n 4.1187e-02, -7.8648e-02, -3.0870e-02, -8.6545e-02, -3.9709e-02,\n -1.1710e-01, -8.0857e-02, -4.5806e-02, -1.1060e-01, -1.1009e-01,\n 9.6615e-03, 1.3969e-01, -5.6019e-02, -4.4889e-02, -1.0778e-01,\n -7.1354e-02, -5.1243e-02, -5.1953e-02, -1.0249e-01, 5.6771e-04,\n -1.0209e-01, -4.4347e-02, -1.2007e-01, -5.4944e-02, -8.0438e-02,\n -1.4170e-01, -9.9055e-02, -1.2377e-02, 4.3605e-02, -2.7088e-02,\n -2.5916e-02, -1.3038e-01]), 'model.layer2.2.bn3.running_mean': tensor([-2.4917e-03, -1.4562e-02, -9.4891e-03, -4.6039e-02, -2.2374e-02,\n 3.9764e-02, -6.9371e-03, -4.5419e-03, 7.9151e-03, 5.0955e-03,\n -2.5674e-02, -6.7639e-02, -4.2284e-02, 8.8559e-03, -5.1236e-02,\n -2.5406e-02, 4.0457e-02, -3.3398e-03, 2.3504e-02, -1.2550e-02,\n 1.1349e-02, 1.7597e-02, 9.3236e-03, 2.0994e-03, -4.5680e-02,\n -2.3550e-03, 2.7095e-02, -7.6893e-03, 5.8179e-03, -5.2545e-02,\n -1.4530e-02, 5.6541e-02, -2.1269e-03, 6.0856e-02, 9.9132e-03,\n -5.9349e-03, -8.8510e-03, -1.3220e-02, 2.9107e-02, -1.8524e-02,\n 1.7490e-03, -2.2026e-02, -2.8499e-02, 8.6007e-04, 4.2791e-04,\n -2.8400e-02, 4.6806e-03, -2.2122e-02, 8.9756e-03, -2.6008e-02,\n -1.8909e-03, -3.3654e-02, 4.0198e-02, -1.8472e-02, 5.0537e-03,\n 2.2264e-02, -5.9301e-02, -3.1817e-02, -4.4404e-03, -1.4422e-02,\n -1.1542e-02, -1.3107e-02, -3.5013e-02, 1.1223e-02, 3.9559e-03,\n -2.2066e-02, 4.6324e-02, -2.3762e-02, 2.3602e-02, -2.2094e-02,\n 3.9966e-02, -4.0665e-02, 2.8482e-02, 1.5419e-02, 6.4022e-03,\n 5.1173e-02, 1.3463e-02, 7.9775e-03, 5.5494e-03, 2.4275e-02,\n 2.2130e-02, 1.8057e-02, 1.6165e-02, -2.3341e-03, -2.0221e-02,\n -1.0897e-02, 2.1391e-02, 5.2007e-02, -8.7821e-03, 6.2515e-03,\n -1.5492e-02, -6.2605e-03, 2.6019e-03, 4.5949e-02, 4.8743e-02,\n -2.2809e-02, 1.3190e-02, 1.9609e-02, -1.8004e-02, -8.9622e-03,\n 2.5000e-02, -2.7693e-02, 6.4760e-04, 6.0185e-03, -1.5049e-02,\n -1.4186e-02, 1.9899e-02, -3.7617e-02, -1.6793e-02, -5.1596e-03,\n 3.3974e-02, 1.5799e-03, -2.8518e-02, -5.9943e-02, 3.1022e-02,\n 6.6258e-03, 5.9223e-02, -8.1320e-03, 1.9187e-02, -4.8151e-02,\n -1.6609e-02, -8.8043e-03, 2.5172e-03, 1.8644e-02, 3.9209e-03,\n 3.7488e-02, 4.5486e-03, 3.8914e-02, 1.2256e-02, 4.8492e-02,\n -4.2589e-02, 2.1529e-02, -5.6897e-02, 1.0053e-02, -2.5496e-02,\n -4.6995e-04, -1.6161e-02, 1.0062e-01, 5.2515e-03, -1.2840e-02,\n -5.5365e-04, 9.5375e-03, -9.9691e-03, 8.6888e-03, 9.4457e-03,\n 3.4893e-02, -4.8048e-03, -4.2671e-02, 4.6293e-02, -1.0753e-02,\n 2.1245e-02, 1.3494e-02, 2.6117e-02, -5.4029e-03, 3.0922e-02,\n -9.9945e-03, 4.1323e-02, 5.9149e-02, 3.1705e-02, 1.0535e-02,\n -1.5166e-02, 5.0873e-03, -1.3252e-02, 3.9845e-02, 4.2968e-02,\n 4.0126e-02, -2.6266e-02, -3.2788e-03, 2.2386e-02, 2.2152e-02,\n 1.3704e-02, -1.0357e-03, -6.8528e-03, -8.3966e-03, 7.6878e-02,\n 3.7548e-05, -5.0276e-02, 5.6302e-03, -3.0108e-02, 1.3241e-02,\n 3.8399e-02, 4.7883e-03, 2.2641e-02, 3.6738e-02, 2.2519e-03,\n 2.9874e-02, 1.4302e-02, -6.8648e-04, 4.8789e-02, 5.1160e-02,\n 6.0040e-03, -9.8700e-03, -2.9916e-02, 5.3039e-02, 9.3847e-03,\n -4.6180e-02, -1.6632e-02, 1.1765e-02, -3.9646e-02, 1.4712e-02,\n -2.9140e-02, -8.6269e-03, 9.5358e-03, 4.6327e-02, 1.8010e-02,\n -2.6721e-02, -3.9405e-02, -2.7276e-02, -1.1922e-04, -2.4108e-03,\n -2.4397e-02, 2.3367e-02, 2.2242e-02, 2.1760e-03, 1.5808e-02,\n -5.5669e-02, -2.4718e-02, 1.1021e-03, 3.2331e-02, -1.8206e-02,\n -1.4892e-02, 6.6613e-03, -6.1857e-03, -1.0602e-02, 1.7186e-02,\n 5.5426e-03, -5.5779e-03, 1.3784e-02, -7.2343e-03, 3.2243e-02,\n 1.0941e-02, -1.4870e-02, -1.6207e-02, -1.0081e-02, -1.3476e-03,\n -4.3468e-02, -5.1466e-04, 1.1758e-02, -1.3772e-02, 9.7067e-03,\n 8.0712e-03, 6.2305e-02, 2.6037e-02, 1.2913e-02, 1.2911e-02,\n -5.5900e-02, 4.5590e-02, 1.2531e-02, -3.2710e-02, -7.7957e-02,\n -2.0590e-02, 4.6396e-02, -3.9356e-03, -1.0133e-02, 3.9268e-03,\n 1.4378e-02, -2.2940e-03, -1.1004e-02, -4.1183e-02, -1.9565e-02,\n -6.5068e-02, -1.7485e-02, 6.9522e-03, -1.5113e-02, -3.6653e-03,\n -1.0388e-02, 3.7049e-02, 2.8467e-02, -1.6816e-02, -3.0887e-02,\n 2.8205e-02, -3.7468e-02, 1.0150e-02, 3.1993e-03, -2.9544e-02,\n -3.2119e-03, 2.3167e-02, 4.1077e-02, -3.4351e-02, -2.7997e-02,\n -4.0040e-03, 3.3318e-02, -6.2778e-03, 2.9097e-03, -2.8575e-02,\n 4.3155e-02, -2.2370e-02, -2.5186e-02, 2.4095e-02, -3.3127e-02,\n -3.5497e-03, 4.3613e-02, -2.7064e-02, 1.6116e-02, 1.0050e-02,\n -2.1564e-02, -3.1383e-02, -1.1608e-02, 3.1717e-02, -2.1935e-03,\n 6.8612e-03, -2.1835e-02, -2.8305e-02, -3.4488e-02, -5.0848e-02,\n -1.2550e-02, -2.1814e-02, 7.3624e-02, 2.7430e-02, -2.9671e-03,\n -2.0323e-02, 3.7872e-02, -7.7486e-03, 3.0261e-02, 7.2505e-04,\n 1.0866e-02, -9.5450e-03, 1.1420e-02, 1.1959e-02, -2.5701e-02,\n -4.0735e-02, -1.5497e-02, 4.5863e-02, 4.0377e-03, -6.8597e-03,\n 1.8396e-02, -7.2778e-03, -2.0753e-02, -2.3284e-02, -2.2612e-02,\n 1.6354e-02, 3.6169e-02, -1.0145e-02, -1.8552e-02, 3.7889e-02,\n -1.0055e-03, -1.1705e-02, 4.7596e-03, -1.4251e-02, 1.6387e-02,\n 1.8321e-02, -2.1860e-02, -1.1481e-03, -2.7587e-02, -1.7646e-02,\n -1.7529e-02, 2.0406e-02, -1.2984e-02, 1.1941e-02, 7.5924e-02,\n -2.0264e-02, 8.7545e-02, -1.4319e-02, -2.0210e-02, 3.7686e-02,\n -9.8364e-03, 8.1133e-03, 1.5976e-02, -1.2787e-02, -3.6165e-02,\n -9.7961e-03, -2.6025e-02, -2.6910e-02, 1.4385e-02, -4.5371e-02,\n 9.5248e-03, 3.9192e-02, 6.2232e-03, 2.6859e-02, 1.3374e-02,\n 3.0917e-02, 2.5641e-02, -3.0434e-02, 1.0323e-03, 4.3021e-03,\n 3.7804e-02, -8.8496e-03, 3.1122e-02, 9.6732e-03, -2.5496e-02,\n -1.0281e-04, -4.0822e-02, -1.2101e-02, 3.6553e-02, -2.0242e-02,\n -2.0702e-02, -6.1364e-03, -4.2640e-02, 4.9288e-03, -4.6812e-04,\n -1.2714e-02, -3.8228e-03, 6.9023e-02, -2.7440e-02, 1.8387e-04,\n -7.1636e-02, 3.2006e-02, -6.2753e-02, -1.8560e-02, -7.9545e-03,\n 9.4830e-03, 1.2842e-02, 2.0890e-02, 3.4963e-02, 3.9436e-02,\n 4.5967e-02, -8.0907e-03, -1.4271e-02, 8.4443e-02, -5.9004e-03,\n -5.3650e-03, -1.5788e-02, -5.0279e-02, -5.7962e-03, 7.8246e-03,\n 1.5333e-02, -5.5933e-02, -3.7550e-02, 6.2041e-02, -2.1274e-03,\n 6.2233e-03, -8.8381e-03, 1.3842e-02, -3.7126e-02, -3.4739e-02,\n 2.3499e-03, 2.8593e-02, 4.2755e-03, -1.0023e-02, -7.2885e-02,\n -1.7003e-02, 6.7177e-02, 4.8511e-02, 6.1011e-03, 1.6881e-02,\n -2.1295e-02, -1.8655e-02, 2.0161e-02, 4.5004e-02, -8.4207e-04,\n -3.6771e-02, 1.2005e-02, -1.4289e-02, 8.7210e-03, -5.1792e-02,\n -2.2427e-02, -1.9201e-03, 7.0765e-03, 2.9399e-03, -2.7107e-02,\n 1.0085e-01, -1.2043e-02, -9.6625e-02, 3.5944e-02, -1.6692e-02,\n -4.2978e-02, 6.3889e-03, -1.7227e-02, 1.0131e-02, 2.9324e-02,\n 2.6743e-03, -7.7861e-03, -4.5000e-02, -5.9619e-02, 1.4466e-02,\n 4.2319e-02, -3.1458e-02, 8.0687e-03, -4.8439e-03, 3.0068e-03,\n -2.5550e-02, -4.4740e-02, 8.5766e-03, -3.8246e-03, -3.6000e-02,\n -2.0779e-02, -8.8806e-02, -1.6270e-02, -4.6865e-02, 1.6866e-02,\n -3.1715e-02, -2.8640e-02, 4.3669e-02, -7.1950e-03, 1.7248e-02,\n 5.3438e-02, 3.1591e-02, -1.9105e-02, 2.2914e-02, 3.3010e-02,\n 1.4248e-03, -3.4385e-02, 9.4513e-05, -2.6438e-02, -3.6927e-02,\n -3.5205e-02, -3.0762e-02, 6.6416e-02, -2.6882e-04, 3.2027e-03,\n -3.2216e-02, 1.3250e-02, -1.1155e-03, -4.9710e-02, 1.0476e-02,\n -6.7438e-02, -4.4612e-02, -7.3124e-03, -1.7998e-02, 3.9955e-02,\n 9.2986e-03, 5.1643e-02]), 'model.layer2.2.bn3.running_var': tensor([0.0009, 0.0013, 0.0007, 0.0057, 0.0027, 0.0019, 0.0005, 0.0018, 0.0010,\n 0.0016, 0.0009, 0.0013, 0.0014, 0.0011, 0.0044, 0.0012, 0.0017, 0.0022,\n 0.0014, 0.0050, 0.0006, 0.0013, 0.0005, 0.0032, 0.0010, 0.0040, 0.0021,\n 0.0045, 0.0024, 0.0047, 0.0005, 0.0049, 0.0012, 0.0010, 0.0008, 0.0005,\n 0.0006, 0.0015, 0.0027, 0.0006, 0.0012, 0.0018, 0.0046, 0.0007, 0.0039,\n 0.0016, 0.0008, 0.0010, 0.0015, 0.0014, 0.0017, 0.0013, 0.0120, 0.0013,\n 0.0009, 0.0009, 0.0014, 0.0018, 0.0005, 0.0041, 0.0009, 0.0006, 0.0050,\n 0.0010, 0.0012, 0.0025, 0.0014, 0.0014, 0.0009, 0.0006, 0.0009, 0.0024,\n 0.0009, 0.0039, 0.0004, 0.0013, 0.0006, 0.0004, 0.0011, 0.0007, 0.0006,\n 0.0011, 0.0006, 0.0025, 0.0028, 0.0010, 0.0011, 0.0016, 0.0007, 0.0044,\n 0.0021, 0.0006, 0.0006, 0.0008, 0.0033, 0.0023, 0.0010, 0.0007, 0.0007,\n 0.0009, 0.0020, 0.0007, 0.0003, 0.0003, 0.0075, 0.0016, 0.0034, 0.0010,\n 0.0012, 0.0019, 0.0009, 0.0070, 0.0070, 0.0021, 0.0016, 0.0005, 0.0010,\n 0.0003, 0.0011, 0.0013, 0.0034, 0.0023, 0.0012, 0.0032, 0.0086, 0.0042,\n 0.0003, 0.0008, 0.0022, 0.0026, 0.0023, 0.0018, 0.0018, 0.0009, 0.0004,\n 0.0069, 0.0013, 0.0016, 0.0026, 0.0023, 0.0008, 0.0049, 0.0016, 0.0045,\n 0.0010, 0.0010, 0.0008, 0.0007, 0.0010, 0.0012, 0.0007, 0.0040, 0.0026,\n 0.0037, 0.0031, 0.0004, 0.0024, 0.0013, 0.0022, 0.0024, 0.0032, 0.0014,\n 0.0004, 0.0009, 0.0004, 0.0054, 0.0004, 0.0056, 0.0008, 0.0016, 0.0018,\n 0.0005, 0.0007, 0.0009, 0.0027, 0.0011, 0.0019, 0.0006, 0.0018, 0.0009,\n 0.0014, 0.0019, 0.0006, 0.0013, 0.0011, 0.0011, 0.0017, 0.0006, 0.0008,\n 0.0023, 0.0006, 0.0018, 0.0032, 0.0013, 0.0029, 0.0014, 0.0017, 0.0011,\n 0.0040, 0.0007, 0.0115, 0.0040, 0.0013, 0.0031, 0.0015, 0.0018, 0.0014,\n 0.0010, 0.0009, 0.0135, 0.0012, 0.0009, 0.0009, 0.0025, 0.0020, 0.0011,\n 0.0063, 0.0008, 0.0013, 0.0009, 0.0013, 0.0057, 0.0009, 0.0015, 0.0003,\n 0.0055, 0.0009, 0.0027, 0.0011, 0.0008, 0.0025, 0.0016, 0.0027, 0.0034,\n 0.0033, 0.0021, 0.0007, 0.0003, 0.0004, 0.0018, 0.0012, 0.0039, 0.0008,\n 0.0007, 0.0024, 0.0008, 0.0005, 0.0005, 0.0013, 0.0022, 0.0045, 0.0028,\n 0.0016, 0.0009, 0.0024, 0.0022, 0.0003, 0.0008, 0.0023, 0.0006, 0.0014,\n 0.0005, 0.0007, 0.0004, 0.0036, 0.0005, 0.0135, 0.0005, 0.0004, 0.0007,\n 0.0018, 0.0037, 0.0036, 0.0018, 0.0034, 0.0013, 0.0023, 0.0013, 0.0015,\n 0.0026, 0.0009, 0.0035, 0.0011, 0.0029, 0.0011, 0.0009, 0.0023, 0.0014,\n 0.0010, 0.0014, 0.0010, 0.0056, 0.0010, 0.0013, 0.0008, 0.0003, 0.0022,\n 0.0023, 0.0012, 0.0015, 0.0030, 0.0005, 0.0009, 0.0020, 0.0006, 0.0017,\n 0.0051, 0.0020, 0.0019, 0.0007, 0.0008, 0.0010, 0.0013, 0.0027, 0.0017,\n 0.0008, 0.0034, 0.0045, 0.0016, 0.0020, 0.0023, 0.0010, 0.0029, 0.0052,\n 0.0004, 0.0017, 0.0017, 0.0029, 0.0018, 0.0026, 0.0004, 0.0007, 0.0012,\n 0.0012, 0.0012, 0.0024, 0.0009, 0.0005, 0.0006, 0.0030, 0.0026, 0.0077,\n 0.0018, 0.0016, 0.0017, 0.0007, 0.0022, 0.0013, 0.0041, 0.0010, 0.0010,\n 0.0043, 0.0009, 0.0008, 0.0035, 0.0013, 0.0019, 0.0025, 0.0012, 0.0022,\n 0.0011, 0.0010, 0.0020, 0.0009, 0.0049, 0.0010, 0.0031, 0.0003, 0.0012,\n 0.0007, 0.0020, 0.0010, 0.0019, 0.0005, 0.0006, 0.0004, 0.0021, 0.0031,\n 0.0030, 0.0009, 0.0004, 0.0008, 0.0006, 0.0040, 0.0008, 0.0022, 0.0025,\n 0.0012, 0.0017, 0.0014, 0.0012, 0.0008, 0.0011, 0.0009, 0.0006, 0.0026,\n 0.0011, 0.0011, 0.0022, 0.0021, 0.0020, 0.0006, 0.0006, 0.0015, 0.0025,\n 0.0016, 0.0009, 0.0021, 0.0025, 0.0054, 0.0003, 0.0014, 0.0037, 0.0059,\n 0.0009, 0.0007, 0.0022, 0.0013, 0.0008, 0.0034, 0.0017, 0.0005, 0.0006,\n 0.0005, 0.0016, 0.0058, 0.0008, 0.0010, 0.0012, 0.0011, 0.0010, 0.0020,\n 0.0010, 0.0005, 0.0014, 0.0007, 0.0014, 0.0008, 0.0024, 0.0032, 0.0029,\n 0.0009, 0.0010, 0.0035, 0.0036, 0.0020, 0.0024, 0.0025, 0.0005, 0.0025,\n 0.0016, 0.0064, 0.0020, 0.0010, 0.0027, 0.0020, 0.0010, 0.0006, 0.0015,\n 0.0017, 0.0006, 0.0005, 0.0022, 0.0013, 0.0048, 0.0016, 0.0010, 0.0014,\n 0.0006, 0.0006, 0.0013, 0.0013, 0.0021, 0.0013, 0.0022, 0.0013, 0.0019,\n 0.0015, 0.0007, 0.0009, 0.0012, 0.0019, 0.0016, 0.0011, 0.0006, 0.0022,\n 0.0007, 0.0008, 0.0014, 0.0010, 0.0011, 0.0033, 0.0016, 0.0014, 0.0020,\n 0.0010, 0.0011, 0.0015, 0.0040, 0.0003, 0.0016, 0.0005, 0.0026, 0.0038,\n 0.0020, 0.0011, 0.0007, 0.0067, 0.0012, 0.0008, 0.0006, 0.0016]), 'model.layer2.2.bn3.num_batches_tracked': tensor(7160), 'model.layer2.3.conv1.weight': tensor([[[[ 0.0061]],\n\n [[-0.0274]],\n\n [[ 0.0208]],\n\n ...,\n\n [[ 0.0104]],\n\n [[ 0.0264]],\n\n [[-0.0006]]],\n\n\n [[[ 0.0227]],\n\n [[-0.0192]],\n\n [[-0.0145]],\n\n ...,\n\n [[ 0.0163]],\n\n [[ 0.0262]],\n\n [[ 0.0013]]],\n\n\n [[[-0.0125]],\n\n [[-0.0104]],\n\n [[ 0.0138]],\n\n ...,\n\n [[ 0.0155]],\n\n [[ 0.0465]],\n\n [[ 0.0023]]],\n\n\n ...,\n\n\n [[[ 0.0176]],\n\n [[-0.0335]],\n\n [[-0.0128]],\n\n ...,\n\n [[-0.0233]],\n\n [[ 0.0172]],\n\n [[ 0.0073]]],\n\n\n [[[ 0.0024]],\n\n [[-0.0068]],\n\n [[-0.0014]],\n\n ...,\n\n [[-0.0109]],\n\n [[-0.0068]],\n\n [[ 0.0202]]],\n\n\n [[[ 0.0120]],\n\n [[-0.0243]],\n\n [[-0.0075]],\n\n ...,\n\n [[-0.0101]],\n\n [[ 0.0018]],\n\n [[-0.0153]]]]), 'model.layer2.3.bn1.weight': tensor([0.1997, 0.1767, 0.1959, 0.1333, 0.1991, 0.1709, 0.1126, 0.1500, 0.1498,\n 0.1859, 0.1732, 0.1793, 0.1297, 0.1971, 0.1440, 0.2075, 0.1687, 0.2230,\n 0.2259, 0.1827, 0.1657, 0.1554, 0.1674, 0.1580, 0.1808, 0.1616, 0.1959,\n 0.1872, 0.1134, 0.1888, 0.1598, 0.1620, 0.1482, 0.1982, 0.1514, 0.1660,\n 0.1366, 0.1791, 0.1654, 0.1853, 0.1450, 0.1958, 0.1722, 0.1662, 0.1763,\n 0.1629, 0.1686, 0.1977, 0.1265, 0.1747, 0.1940, 0.1585, 0.1707, 0.1543,\n 0.1365, 0.1695, 0.1864, 0.1633, 0.1984, 0.1169, 0.1690, 0.1280, 0.2126,\n 0.1260, 0.1573, 0.1988, 0.1684, 0.1633, 0.2094, 0.1857, 0.1855, 0.1345,\n 0.1883, 0.1681, 0.1803, 0.1321, 0.1637, 0.1348, 0.1421, 0.1713, 0.1321,\n 0.1407, 0.1552, 0.1550, 0.1429, 0.1528, 0.1885, 0.1696, 0.1563, 0.1867,\n 0.1481, 0.1937, 0.1687, 0.1828, 0.1700, 0.1743, 0.1799, 0.1934, 0.2077,\n 0.1620, 0.1720, 0.1701, 0.1731, 0.2002, 0.1473, 0.1701, 0.1508, 0.1791,\n 0.1523, 0.1758, 0.1990, 0.1913, 0.1552, 0.1715, 0.2270, 0.1730, 0.2305,\n 0.1624, 0.1512, 0.2023, 0.2066, 0.1569, 0.1877, 0.1273, 0.1557, 0.1627,\n 0.1594, 0.1718]), 'model.layer2.3.bn1.bias': tensor([-0.1195, -0.0077, -0.1106, 0.0343, -0.0888, -0.0453, 0.0079, 0.0254,\n 0.0571, -0.1152, 0.0393, 0.0192, 0.0572, -0.1145, 0.1097, -0.1056,\n -0.0493, -0.1103, -0.1749, -0.0722, 0.0202, 0.0254, -0.0743, -0.1078,\n -0.0113, -0.0317, -0.0314, -0.0503, 0.0924, -0.1281, -0.0567, -0.0416,\n -0.0028, -0.1105, 0.0341, 0.0163, -0.0147, -0.0964, 0.0268, -0.1621,\n 0.0406, -0.2293, -0.0466, 0.0702, -0.0576, -0.0483, 0.0493, -0.0340,\n -0.0333, -0.0744, -0.0353, -0.0071, -0.1031, 0.0265, -0.0063, -0.0060,\n -0.0027, 0.0467, -0.1187, 0.0718, -0.0590, 0.0136, -0.1338, 0.0509,\n 0.0650, -0.0365, -0.0436, 0.0025, -0.1206, -0.1015, -0.0200, 0.0019,\n -0.1007, 0.0280, -0.1096, -0.0096, 0.0435, 0.0739, -0.0358, -0.1246,\n 0.1180, 0.0573, 0.1215, 0.0338, 0.0311, 0.0358, -0.0363, -0.0183,\n 0.0289, 0.0144, 0.0326, -0.1252, -0.0066, -0.0117, 0.0431, -0.0729,\n -0.0680, -0.0901, -0.0935, -0.0025, -0.0312, -0.0035, -0.0800, -0.1158,\n 0.0309, -0.0737, 0.0332, 0.0066, 0.0523, -0.0032, 0.0354, -0.0385,\n -0.0943, 0.0007, -0.1458, -0.0735, -0.2415, 0.0223, 0.0420, -0.1342,\n -0.1289, -0.0164, -0.0788, 0.0667, 0.0598, 0.0561, -0.0028, -0.0656]), 'model.layer2.3.bn1.running_mean': tensor([-0.0613, -0.0901, 0.0503, -0.2252, 0.0105, 0.0456, 0.0094, -0.1239,\n -0.0752, 0.1090, 0.0212, 0.0087, -0.1065, -0.0137, 0.1721, -0.1304,\n 0.0753, -0.1012, -0.1268, 0.0834, -0.0578, -0.1409, -0.0713, 0.0543,\n -0.2727, -0.1774, -0.0977, -0.0016, 0.0155, 0.1279, -0.0369, 0.0133,\n -0.0707, -0.0034, -0.1536, -0.1690, 0.0813, -0.0124, -0.0966, -0.0129,\n -0.2193, -0.1067, 0.0009, -0.1597, 0.0877, 0.0464, -0.2960, -0.0834,\n 0.0286, -0.0352, -0.0460, -0.0332, 0.1544, -0.1934, -0.1411, -0.0552,\n -0.0435, -0.2555, -0.1442, 0.0645, 0.0074, -0.1264, -0.0958, -0.1424,\n -0.1646, -0.1225, 0.0956, -0.0495, -0.0633, 0.0689, -0.0832, 0.0596,\n -0.0324, -0.2245, 0.0318, -0.1397, -0.1098, -0.1294, 0.1071, -0.0479,\n 0.0384, -0.1169, -0.0899, -0.0281, -0.0964, -0.2644, 0.0382, -0.0568,\n -0.2362, -0.0629, -0.0965, 0.0744, -0.0929, -0.1488, -0.1558, 0.0365,\n -0.2568, -0.0269, 0.1440, -0.0934, -0.0567, -0.2156, 0.1238, -0.0407,\n -0.2633, -0.0151, 0.0053, -0.1416, -0.1235, -0.0660, -0.2899, 0.0867,\n 0.0675, -0.0994, -0.0660, -0.0987, -0.1272, -0.1353, 0.0874, -0.1757,\n -0.0905, -0.0664, 0.0330, -0.0877, -0.1534, -0.1204, -0.1765, -0.0603]), 'model.layer2.3.bn1.running_var': tensor([0.0150, 0.0318, 0.0217, 0.0206, 0.0221, 0.0198, 0.0175, 0.0329, 0.0460,\n 0.0205, 0.0517, 0.0368, 0.0173, 0.0203, 0.0410, 0.0254, 0.0180, 0.0276,\n 0.0288, 0.0367, 0.0254, 0.0326, 0.0288, 0.0156, 0.0235, 0.0262, 0.0330,\n 0.0350, 0.0286, 0.0198, 0.0233, 0.0360, 0.0313, 0.0234, 0.0204, 0.0289,\n 0.0182, 0.0211, 0.0306, 0.0121, 0.0325, 0.0159, 0.0317, 0.0506, 0.0314,\n 0.0290, 0.0423, 0.0423, 0.0131, 0.0260, 0.0325, 0.0306, 0.0236, 0.0320,\n 0.0264, 0.0296, 0.0433, 0.0562, 0.0268, 0.0171, 0.0254, 0.0301, 0.0253,\n 0.0334, 0.0398, 0.0400, 0.0414, 0.0433, 0.0221, 0.0308, 0.0302, 0.0230,\n 0.0225, 0.0340, 0.0254, 0.0294, 0.0434, 0.0397, 0.0303, 0.0174, 0.0309,\n 0.0302, 0.0435, 0.0312, 0.0273, 0.0304, 0.0362, 0.0265, 0.0457, 0.0313,\n 0.0292, 0.0214, 0.0221, 0.0407, 0.0425, 0.0214, 0.0244, 0.0236, 0.0244,\n 0.0260, 0.0244, 0.0328, 0.0260, 0.0200, 0.0255, 0.0265, 0.0286, 0.0430,\n 0.0336, 0.0320, 0.0372, 0.0207, 0.0276, 0.0446, 0.0320, 0.0222, 0.0220,\n 0.0225, 0.0336, 0.0237, 0.0206, 0.0277, 0.0291, 0.0339, 0.0402, 0.0302,\n 0.0321, 0.0294]), 'model.layer2.3.bn1.num_batches_tracked': tensor(7160), 'model.layer2.3.conv2.weight': tensor([[[[-1.5782e-03, 7.2184e-03, -1.2262e-02],\n [-2.5783e-03, 8.7497e-03, 4.9707e-03],\n [ 1.8498e-02, 1.4492e-02, -7.3724e-03]],\n\n [[-2.5747e-03, 7.7807e-03, 1.4414e-02],\n [-7.0019e-03, 2.9371e-03, 9.8466e-03],\n [-8.8274e-03, -2.2813e-03, 8.1007e-03]],\n\n [[ 2.3918e-02, 3.9625e-02, 2.2022e-02],\n [ 2.0769e-02, 1.4540e-02, 1.8989e-02],\n [ 2.6048e-02, 1.1040e-02, -6.6231e-03]],\n\n ...,\n\n [[ 4.2458e-02, 1.1165e-02, -1.1186e-02],\n [ 3.5812e-02, -1.5502e-02, -4.1353e-02],\n [ 3.2811e-02, -8.1229e-03, -3.3586e-02]],\n\n [[ 2.9052e-02, 2.7246e-02, -1.5804e-02],\n [ 2.0362e-02, 1.8498e-02, 4.9830e-03],\n [ 3.2481e-02, 2.7741e-02, -3.1927e-02]],\n\n [[-1.7921e-02, -5.7531e-03, 1.4353e-02],\n [-3.0244e-02, -1.5544e-02, 1.4712e-02],\n [-2.0840e-02, 5.2558e-03, 4.2492e-02]]],\n\n\n [[[-5.6067e-03, 1.9097e-02, 2.6041e-02],\n [ 8.2940e-03, -9.5501e-03, -3.0818e-03],\n [ 1.8504e-02, -6.9878e-03, -3.3673e-02]],\n\n [[ 3.7200e-03, -1.1277e-02, 2.4859e-02],\n [ 2.1035e-02, -3.6702e-02, 3.8909e-02],\n [ 3.9214e-02, 3.6186e-02, 2.1953e-02]],\n\n [[-9.8517e-03, -1.4155e-02, -3.2639e-02],\n [ 5.7588e-02, -2.5757e-02, -3.5267e-02],\n [ 2.4816e-02, 9.3350e-02, 4.8376e-02]],\n\n ...,\n\n [[ 3.6296e-02, 2.8738e-02, 2.2600e-03],\n [ 1.7616e-02, 1.3521e-02, 9.2879e-03],\n [ 6.9364e-03, -2.6318e-02, -1.6339e-02]],\n\n [[ 3.4935e-03, 1.1731e-03, 1.3539e-02],\n [ 1.3847e-02, -3.0816e-02, 1.2677e-02],\n [ 2.0321e-02, -1.8540e-02, -4.6574e-02]],\n\n [[-1.6025e-02, -1.4924e-02, -2.4953e-02],\n [-6.7712e-03, -2.7343e-02, 1.2459e-02],\n [ 2.5764e-02, 2.1451e-02, 1.0021e-02]]],\n\n\n [[[-1.4247e-02, -1.5271e-02, 1.8215e-02],\n [-1.9702e-02, -4.1149e-02, -2.4292e-02],\n [-8.7653e-03, -7.9829e-03, -1.0835e-02]],\n\n [[ 5.6757e-03, 8.6302e-03, 2.5473e-03],\n [-2.3788e-02, -8.8400e-04, 2.9282e-03],\n [-1.9056e-02, -2.1611e-02, -2.2737e-02]],\n\n [[ 2.1868e-02, -1.3729e-02, -6.6415e-03],\n [-4.1939e-04, -4.8188e-03, -9.2146e-03],\n [ 9.4939e-03, 2.2827e-02, 3.9707e-02]],\n\n ...,\n\n [[-1.5143e-02, 3.8039e-03, 3.7732e-03],\n [-1.3390e-02, -8.1918e-03, -1.4910e-02],\n [-1.9824e-02, 1.1575e-02, 2.7901e-02]],\n\n [[-1.8648e-02, -2.3032e-02, -2.3484e-02],\n [ 4.1025e-02, 1.3420e-02, -3.2202e-02],\n [-1.4240e-02, -3.1045e-03, 2.0841e-02]],\n\n [[-2.7671e-03, -8.5409e-03, -2.3361e-02],\n [-1.8164e-02, -1.2083e-03, 1.6118e-02],\n [ 2.4914e-02, 1.9322e-02, 2.1054e-02]]],\n\n\n ...,\n\n\n [[[-5.6867e-02, 4.7784e-03, -9.5672e-03],\n [-4.1312e-02, -6.1247e-03, 1.9626e-02],\n [-5.7993e-03, -6.6742e-02, -2.4230e-02]],\n\n [[-4.1848e-03, -1.5532e-02, -1.2427e-02],\n [-2.5141e-02, 3.4233e-02, -2.1457e-02],\n [-1.3795e-02, 2.1103e-02, -1.4926e-02]],\n\n [[ 2.8156e-02, -5.0919e-03, 4.9827e-04],\n [ 1.8866e-03, 5.1854e-02, -7.9564e-02],\n [-1.8480e-02, 2.7534e-02, -3.5233e-02]],\n\n ...,\n\n [[ 1.8511e-02, 1.1305e-02, 8.0286e-03],\n [ 1.9809e-02, -4.6371e-03, 2.2720e-02],\n [-1.0248e-02, -3.4119e-02, 1.6840e-02]],\n\n [[-2.1603e-02, -2.1082e-02, -2.1119e-02],\n [-7.0949e-03, -1.8875e-02, -1.6897e-02],\n [-1.7367e-02, 8.2991e-03, 9.2758e-03]],\n\n [[ 3.1282e-02, -3.3910e-02, 4.2922e-02],\n [ 4.8142e-02, -5.8272e-03, -4.0094e-02],\n [ 9.1953e-03, -1.4709e-02, -4.2420e-02]]],\n\n\n [[[-1.8364e-02, 2.7982e-03, -1.8279e-02],\n [-6.5072e-03, -1.3272e-02, -8.4444e-03],\n [ 1.2537e-02, 6.3999e-03, -6.5167e-03]],\n\n [[-2.5874e-03, 2.3414e-02, -1.7368e-02],\n [-5.0576e-02, -1.4841e-02, 3.0625e-02],\n [-1.3203e-02, -1.3496e-02, -2.5919e-03]],\n\n [[ 6.4718e-02, -8.6517e-03, -4.3068e-02],\n [ 9.3716e-05, 2.4989e-02, 6.6636e-02],\n [-7.6368e-03, -5.4342e-03, -9.2356e-03]],\n\n ...,\n\n [[-1.7919e-02, 1.1647e-02, 6.5627e-03],\n [-2.9045e-02, -1.9268e-02, 7.3064e-03],\n [ 4.1338e-03, -5.6853e-03, -2.5515e-02]],\n\n [[ 2.3654e-02, 5.4097e-03, 1.0490e-02],\n [ 2.6271e-02, 1.0854e-02, -5.0306e-02],\n [ 4.0695e-03, 5.6038e-03, -1.8334e-03]],\n\n [[ 4.9428e-03, 7.9565e-03, 4.8875e-03],\n [-1.9802e-02, -5.9035e-03, 4.8900e-03],\n [-1.3847e-03, 5.0813e-03, 1.7112e-03]]],\n\n\n [[[ 7.2624e-03, -1.9830e-02, -2.1968e-02],\n [ 2.9670e-02, 1.0189e-03, -2.8692e-02],\n [-1.6590e-02, -2.1603e-02, -3.9941e-02]],\n\n [[-1.4734e-02, -2.0594e-02, -4.4209e-02],\n [-4.0197e-02, -1.3676e-02, 3.2549e-03],\n [-4.6767e-02, -2.4640e-02, -9.1068e-03]],\n\n [[ 4.8460e-03, -1.3009e-02, 3.7309e-03],\n [ 2.3541e-02, 8.1119e-02, 3.6955e-02],\n [ 6.9893e-03, 4.8079e-02, -4.8691e-03]],\n\n ...,\n\n [[ 1.6409e-03, -4.0241e-02, -3.7602e-02],\n [ 6.6933e-03, -3.0880e-02, 8.8354e-03],\n [-7.7744e-03, -1.3349e-02, 1.5739e-02]],\n\n [[-3.6662e-03, -1.3771e-02, -2.1714e-02],\n [-4.4028e-03, -1.5841e-02, 3.2988e-03],\n [-1.2143e-02, -6.3537e-03, -1.0816e-02]],\n\n [[ 6.1634e-03, 1.3182e-02, 8.7462e-03],\n [-2.4221e-02, -4.7398e-03, 3.4440e-02],\n [ 5.4882e-03, -1.1910e-02, -2.3304e-03]]]]), 'model.layer2.3.bn2.weight': tensor([0.2079, 0.2512, 0.1646, 0.2484, 0.2057, 0.2098, 0.2316, 0.2045, 0.2050,\n 0.2314, 0.2174, 0.1502, 0.2053, 0.2103, 0.2050, 0.2139, 0.1971, 0.1771,\n 0.1950, 0.2394, 0.2159, 0.1949, 0.2330, 0.2174, 0.2169, 0.1664, 0.1994,\n 0.2140, 0.1872, 0.2307, 0.1463, 0.1885, 0.1990, 0.1946, 0.2472, 0.1932,\n 0.1665, 0.1733, 0.1715, 0.2208, 0.2052, 0.1822, 0.2440, 0.2402, 0.2085,\n 0.2289, 0.2464, 0.1563, 0.2018, 0.2182, 0.1799, 0.2458, 0.2297, 0.2619,\n 0.2195, 0.2235, 0.1565, 0.2014, 0.1802, 0.1661, 0.2225, 0.2447, 0.1936,\n 0.2490, 0.2371, 0.1870, 0.2195, 0.2117, 0.2056, 0.1664, 0.2000, 0.1900,\n 0.1614, 0.2290, 0.2054, 0.1440, 0.2027, 0.1847, 0.1744, 0.1832, 0.2044,\n 0.1156, 0.1871, 0.1697, 0.1929, 0.2349, 0.1265, 0.1481, 0.2054, 0.2387,\n 0.2005, 0.2172, 0.1118, 0.2364, 0.1628, 0.2186, 0.1725, 0.1720, 0.2146,\n 0.1835, 0.1609, 0.1752, 0.2043, 0.1894, 0.2021, 0.2341, 0.2239, 0.2423,\n 0.2044, 0.2460, 0.2263, 0.2410, 0.2155, 0.1988, 0.2025, 0.2512, 0.2106,\n 0.1957, 0.2010, 0.2162, 0.1877, 0.1902, 0.1934, 0.1894, 0.2237, 0.2032,\n 0.1763, 0.2330]), 'model.layer2.3.bn2.bias': tensor([-0.0663, -0.1605, -0.0375, -0.1173, -0.0768, -0.0289, -0.1220, -0.1136,\n -0.1282, -0.1058, -0.1029, 0.0819, -0.0134, -0.1133, -0.1353, -0.0372,\n -0.0311, -0.0923, -0.0632, -0.0883, -0.1269, -0.0895, -0.1359, -0.0865,\n -0.0849, -0.0514, -0.0703, -0.0772, -0.0950, -0.1321, 0.0802, -0.0460,\n -0.0461, -0.0682, -0.1523, -0.0675, -0.0411, -0.0724, 0.0222, -0.0861,\n -0.0743, -0.0674, -0.1661, -0.1612, -0.1340, -0.1667, -0.1569, 0.0215,\n -0.0310, -0.0618, -0.0861, -0.1591, -0.1040, -0.1673, -0.0965, -0.0927,\n 0.0362, -0.0389, -0.0350, -0.0021, -0.0618, -0.1592, -0.0804, -0.1394,\n -0.0576, -0.0403, -0.0700, -0.2313, -0.0565, -0.0408, -0.0369, -0.0884,\n 0.0014, -0.1205, -0.0503, 0.0709, -0.1108, -0.0598, 0.0558, -0.0545,\n -0.0400, 0.1778, -0.0672, -0.0711, -0.0364, -0.0991, 0.2570, 0.1560,\n -0.0859, -0.0894, -0.0626, -0.0894, 0.2702, -0.0817, 0.0485, -0.1261,\n -0.0058, -0.0188, -0.0785, -0.0627, -0.0290, -0.0937, -0.0051, 0.1320,\n -0.0544, -0.1700, -0.1467, -0.1169, -0.0871, -0.1512, -0.1519, -0.1666,\n -0.1210, -0.0881, -0.0685, -0.1671, -0.0425, -0.0848, -0.0450, -0.0591,\n -0.0583, -0.0372, -0.0485, 0.0022, -0.1289, -0.0133, -0.0737, -0.1599]), 'model.layer2.3.bn2.running_mean': tensor([-1.8871e-01, 2.4540e-02, -9.6055e-02, -1.7321e-02, -9.7265e-03,\n 3.8140e-02, -2.7809e-02, -8.4010e-02, -4.1708e-02, -8.9813e-02,\n -1.1589e-01, 1.0343e-01, 7.6272e-04, -9.6880e-02, -9.3868e-02,\n -9.3320e-02, -8.0854e-02, -1.4722e-01, 4.5584e-01, -7.5556e-02,\n -3.1129e-02, -3.5341e-02, -4.1270e-02, -9.7493e-02, 1.1686e-02,\n -8.1565e-02, -6.0740e-02, -4.6242e-02, -6.9427e-02, 3.2403e-03,\n -1.4263e-01, -2.9909e-02, -1.5970e-01, 6.2643e-03, -7.9254e-02,\n -9.8850e-02, -1.7813e-01, -5.1989e-02, -1.0592e-02, -1.2641e-01,\n -1.4498e-01, -6.6281e-02, -8.7792e-02, -6.2327e-02, 7.6498e-02,\n -2.2790e-02, -5.6993e-02, -1.1488e-01, -4.4076e-02, -8.7929e-02,\n -1.4150e-01, -4.1701e-02, -1.0824e-01, -4.5569e-02, -3.9014e-02,\n -1.1827e-01, 1.5744e-03, -6.7095e-02, -9.9252e-02, -2.7385e-02,\n -2.6479e-02, -7.3859e-02, -2.3525e-02, -3.2196e-02, -6.9984e-02,\n -1.1243e-01, -1.5118e-02, 1.7632e-01, -6.2368e-02, -3.4000e-02,\n 5.2916e-03, -9.5152e-02, -5.8327e-03, 2.3396e-03, -7.3730e-02,\n -3.9345e-02, -6.9266e-02, -3.1844e-02, 1.1035e-01, -2.3981e-02,\n -3.1418e-02, -8.3911e-02, 1.9503e-04, -3.2032e-02, -3.7985e-02,\n -1.0187e-01, -9.7445e-02, 1.3661e-02, -4.9292e-02, -1.5719e-01,\n -1.8325e-02, -6.0778e-02, -1.8966e-01, -2.7545e-02, 1.0552e-01,\n 1.9408e-03, -3.5373e-02, -3.0091e-02, 3.3456e-03, -3.7843e-02,\n -1.1377e-01, -1.1780e-01, -9.0249e-02, -8.7710e-02, -9.5474e-02,\n -6.7701e-02, -1.6877e-01, -6.8672e-02, -1.3514e-01, -7.9762e-02,\n -1.3837e-01, -9.3543e-02, -4.9114e-02, 1.1633e-02, -7.4325e-02,\n -2.4844e-02, -2.8759e-02, -4.2335e-02, -7.3951e-02, -1.1766e-01,\n -5.7450e-02, 9.6737e-02, -9.6028e-02, -3.0891e-02, -4.5065e-02,\n -1.1466e-01, -1.3367e-01, 1.3305e-01]), 'model.layer2.3.bn2.running_var': tensor([0.0245, 0.0124, 0.0153, 0.0218, 0.0182, 0.0254, 0.0227, 0.0141, 0.0165,\n 0.0189, 0.0216, 0.0181, 0.0258, 0.0119, 0.0193, 0.0254, 0.0218, 0.0118,\n 0.0181, 0.0190, 0.0171, 0.0151, 0.0166, 0.0286, 0.0318, 0.0175, 0.0260,\n 0.0200, 0.0141, 0.0144, 0.0135, 0.0258, 0.0210, 0.0164, 0.0296, 0.0162,\n 0.0188, 0.0119, 0.0117, 0.0200, 0.0200, 0.0239, 0.0181, 0.0165, 0.0154,\n 0.0138, 0.0155, 0.0182, 0.0294, 0.0360, 0.0145, 0.0181, 0.0248, 0.0159,\n 0.0236, 0.0225, 0.0241, 0.0178, 0.0207, 0.0155, 0.0201, 0.0181, 0.0155,\n 0.0240, 0.0235, 0.0248, 0.0227, 0.0101, 0.0234, 0.0160, 0.0194, 0.0219,\n 0.0149, 0.0220, 0.0254, 0.0237, 0.0150, 0.0149, 0.0146, 0.0167, 0.0149,\n 0.0132, 0.0232, 0.0142, 0.0210, 0.0263, 0.0189, 0.0263, 0.0284, 0.0311,\n 0.0252, 0.0292, 0.0198, 0.0330, 0.0266, 0.0161, 0.0164, 0.0211, 0.0204,\n 0.0193, 0.0233, 0.0102, 0.0299, 0.0348, 0.0189, 0.0142, 0.0187, 0.0193,\n 0.0153, 0.0245, 0.0195, 0.0162, 0.0139, 0.0155, 0.0207, 0.0204, 0.0258,\n 0.0141, 0.0334, 0.0214, 0.0178, 0.0252, 0.0227, 0.0186, 0.0163, 0.0283,\n 0.0151, 0.0266]), 'model.layer2.3.bn2.num_batches_tracked': tensor(7160), 'model.layer2.3.conv3.weight': tensor([[[[ 0.0149]],\n\n [[-0.0200]],\n\n [[-0.0322]],\n\n ...,\n\n [[-0.0172]],\n\n [[ 0.0086]],\n\n [[-0.0033]]],\n\n\n [[[-0.0046]],\n\n [[ 0.0275]],\n\n [[ 0.0226]],\n\n ...,\n\n [[-0.0147]],\n\n [[ 0.0496]],\n\n [[-0.0410]]],\n\n\n [[[-0.0014]],\n\n [[ 0.0058]],\n\n [[-0.0030]],\n\n ...,\n\n [[ 0.0015]],\n\n [[-0.0125]],\n\n [[-0.0018]]],\n\n\n ...,\n\n\n [[[-0.0175]],\n\n [[ 0.0031]],\n\n [[ 0.0007]],\n\n ...,\n\n [[ 0.0012]],\n\n [[-0.0068]],\n\n [[-0.0066]]],\n\n\n [[[ 0.0208]],\n\n [[ 0.0048]],\n\n [[-0.0314]],\n\n ...,\n\n [[-0.0025]],\n\n [[ 0.0306]],\n\n [[ 0.0010]]],\n\n\n [[[-0.0062]],\n\n [[-0.0148]],\n\n [[-0.0036]],\n\n ...,\n\n [[-0.0199]],\n\n [[ 0.0122]],\n\n [[ 0.0250]]]]), 'model.layer2.3.bn3.weight': tensor([ 1.9509e-02, 1.2068e-01, 2.7900e-03, 1.0565e-01, 7.8115e-02,\n 2.3188e-03, 9.5906e-03, 4.4283e-02, 1.9444e-01, 1.4871e-01,\n 1.1457e-01, 5.8996e-02, 5.8427e-02, 1.2914e-02, 6.3908e-02,\n 2.1388e-01, 5.4805e-02, 1.4895e-01, 1.1672e-01, 8.6077e-02,\n 1.9852e-01, 4.3500e-02, 5.7372e-02, 3.2329e-02, 1.0839e-01,\n 9.4289e-02, 1.7338e-01, 1.4985e-01, 3.1018e-02, 1.6489e-01,\n 7.6094e-02, -2.6419e-03, 4.7237e-02, 8.9674e-02, 4.9617e-02,\n 3.3515e-02, -4.9925e-04, 9.6149e-02, 3.9020e-02, 6.7487e-02,\n 1.4154e-01, 1.4598e-01, 1.4685e-01, -3.2368e-02, 3.4589e-02,\n 1.9898e-01, 2.7474e-02, 1.5420e-01, 1.9040e-01, 1.1211e-01,\n 8.0438e-02, 2.6063e-01, 1.0133e-01, 6.5878e-02, 4.6493e-02,\n 1.2891e-01, 1.4722e-01, 2.1767e-01, -3.2924e-03, 7.4860e-02,\n 1.3607e-02, 1.9339e-01, 1.5855e-01, 1.4686e-02, 2.0854e-01,\n 1.1313e-01, -1.1815e-02, 1.0804e-01, 2.1618e-01, 1.4743e-01,\n 7.8409e-02, 1.9500e-01, 1.3644e-01, 1.2116e-01, 9.7346e-02,\n 4.4484e-02, 8.6750e-02, 9.0717e-02, 1.2937e-01, 2.1066e-01,\n 2.7347e-02, 1.9271e-01, 1.1960e-02, 9.4937e-02, 1.5307e-01,\n 9.9645e-02, 1.1061e-01, -1.5138e-02, 1.8881e-02, 5.8302e-02,\n 4.6349e-02, 1.9346e-01, 1.5588e-01, 4.8633e-02, 3.6943e-02,\n 1.8210e-01, 7.9120e-02, -1.5880e-03, 8.6341e-02, -9.4993e-03,\n 9.3147e-02, 1.8745e-01, 5.2614e-03, 9.3302e-02, 3.4785e-02,\n 5.3935e-04, 1.4719e-01, 1.8121e-01, 5.7186e-02, 8.5452e-02,\n 4.2840e-02, 1.7356e-01, 8.9649e-02, 1.5486e-01, -2.7263e-04,\n 1.1261e-02, 1.5062e-01, 3.9441e-02, 8.1197e-02, 1.2475e-01,\n 6.7837e-02, 1.5745e-01, 5.9042e-02, 9.8284e-02, 8.1686e-02,\n 3.6922e-02, 4.1356e-02, 8.9695e-03, 1.7667e-01, 1.5564e-01,\n 1.2796e-01, 1.3461e-01, 1.4593e-01, -1.0102e-03, -1.7819e-02,\n 2.2719e-02, 1.3044e-01, 1.4618e-01, 4.7036e-03, 1.0674e-01,\n 1.2858e-01, 7.2340e-02, 1.4159e-01, 5.9030e-02, 3.6210e-03,\n 7.2602e-02, 3.4645e-02, 1.0030e-01, 1.1132e-01, 5.1251e-02,\n 2.2300e-02, 4.0990e-02, 9.2882e-02, 7.6853e-03, 4.0904e-02,\n 1.2511e-02, -4.9223e-02, 4.0480e-02, 6.9544e-02, 1.0244e-01,\n 1.5589e-01, 3.8058e-03, 5.7375e-02, -2.0862e-02, 6.9858e-02,\n -3.6570e-05, 1.4175e-02, 1.2675e-01, 1.9620e-01, 9.7913e-02,\n 6.3258e-03, 6.0386e-02, 1.9079e-03, 2.8369e-03, 6.4645e-02,\n 1.8208e-01, 2.1975e-02, 1.2022e-01, 5.7857e-02, 1.4727e-01,\n 2.2120e-01, 1.8117e-01, 4.1651e-02, 1.6138e-02, 7.6880e-02,\n 3.5614e-02, 9.1415e-03, 2.7058e-01, -1.8838e-02, 6.7465e-02,\n 7.1171e-02, 1.6502e-01, 5.6099e-02, 1.0999e-01, 1.0632e-03,\n 1.0141e-01, 3.4899e-02, 2.1072e-01, 1.1340e-01, 3.3092e-04,\n 7.0750e-02, 1.6576e-01, 5.3089e-02, 4.6124e-02, 2.1647e-02,\n 2.1024e-01, 1.3802e-01, 4.4765e-02, -3.6188e-03, 9.7181e-02,\n 5.5448e-02, 8.3098e-02, 1.4552e-02, 3.2520e-02, 1.0828e-01,\n 1.2683e-01, 7.8057e-02, -6.5341e-03, 8.2354e-03, 1.1218e-01,\n 1.0824e-01, 1.2008e-01, -1.7704e-02, 2.7495e-01, 6.2629e-02,\n 1.6004e-01, 2.0368e-01, 1.1135e-02, 1.2457e-01, 6.0462e-02,\n 1.9177e-01, 1.0308e-01, 1.2298e-01, 8.0206e-02, 1.0807e-03,\n 1.1765e-01, 3.4929e-02, 3.5104e-02, 1.3606e-01, 5.2410e-02,\n 4.3888e-02, 4.1452e-02, 1.2437e-01, 1.5086e-02, 2.3013e-01,\n 1.5128e-01, 4.4074e-02, 5.1580e-02, 1.5277e-01, 2.7046e-02,\n 1.2328e-01, 5.0347e-03, 1.9872e-01, 1.4110e-01, 2.3051e-01,\n 1.0758e-01, 1.2289e-01, 1.1115e-01, 1.1695e-01, 3.7402e-03,\n 2.4651e-01, 8.4824e-02, 1.3709e-01, 1.1524e-02, 1.5160e-01,\n 6.9168e-04, 7.2901e-02, 4.3426e-02, -1.1351e-02, 4.2191e-02,\n -2.0392e-03, 1.3633e-01, 2.7696e-02, 6.8351e-02, 1.7855e-01,\n 3.0583e-03, 1.6988e-01, 1.5527e-01, 1.4399e-01, 7.8179e-02,\n 9.1038e-02, 6.9841e-02, 1.0005e-01, 9.5947e-02, 4.0935e-02,\n 2.8652e-03, 1.5015e-01, 9.9978e-02, 5.7254e-02, 2.0132e-01,\n -8.4209e-03, 7.1213e-03, 1.9616e-01, 1.4768e-01, 2.3240e-01,\n 9.7776e-02, 1.3365e-01, 3.1625e-02, 5.9813e-02, 2.5462e-01,\n 1.1383e-01, 5.7506e-02, 2.3896e-01, 1.1243e-01, 1.5285e-01,\n 1.8735e-01, 1.1649e-01, 1.4264e-01, 2.0432e-01, 2.3519e-02,\n 2.0034e-01, -4.2882e-03, -1.5394e-04, 2.8154e-02, 3.5668e-02,\n 5.8531e-02, 1.6465e-01, 4.5714e-03, -1.3587e-02, 1.2327e-02,\n 1.1909e-01, 1.0416e-01, 4.3146e-02, 8.9131e-02, -3.7126e-03,\n 5.4779e-03, 1.6189e-01, 1.5786e-01, 5.8507e-02, 6.3646e-02,\n 1.8744e-02, 5.7396e-02, -7.8985e-03, 4.3222e-02, 1.9335e-01,\n 6.7201e-02, 2.1757e-01, 2.3214e-02, 1.0195e-01, 7.9701e-02,\n 3.3814e-02, 8.7225e-02, 4.5147e-02, 1.5026e-01, 1.6420e-02,\n 6.9692e-02, 1.8593e-02, -2.9549e-03, 1.7909e-01, 1.9095e-03,\n 8.6095e-02, 1.6899e-02, 6.1780e-02, 8.1563e-02, 2.5820e-02,\n 1.0011e-01, 1.3768e-01, -6.2900e-03, 1.0210e-01, 2.1719e-01,\n 9.6077e-02, 6.6609e-02, 1.2081e-01, -2.8363e-02, 5.7468e-02,\n 4.0546e-02, 5.6087e-02, 1.8532e-01, 2.8930e-02, 5.8003e-02,\n 4.0013e-02, -9.4103e-03, 8.9244e-02, 5.8294e-02, 1.4041e-02,\n 1.9200e-01, 1.1103e-01, 1.3775e-01, 1.5435e-01, 6.6660e-02,\n 1.4711e-01, 6.4717e-02, 8.0234e-05, 1.2763e-01, 8.4709e-02,\n 1.6747e-01, 1.1833e-02, 1.8511e-02, 1.1207e-02, 1.4676e-01,\n 1.2634e-01, 1.5813e-01, 1.7188e-02, 2.6247e-01, 9.4000e-02,\n -3.6951e-03, 3.7788e-02, 1.7699e-01, 1.1940e-01, 8.9676e-02,\n 1.8979e-02, -4.6982e-03, 1.7236e-01, 7.7824e-02, 7.5365e-02,\n -4.4843e-03, -1.8556e-02, 1.1631e-01, 9.3385e-02, 5.5670e-02,\n 1.9137e-01, 1.3348e-01, 2.8434e-02, 3.8557e-02, 8.1444e-02,\n 2.2518e-01, 1.0536e-01, 1.9261e-01, 5.8404e-04, 7.9257e-02,\n 7.0582e-02, 4.5665e-02, 2.6959e-01, 1.1225e-01, 9.9613e-02,\n 1.6104e-01, 1.1493e-02, 3.4384e-02, 9.9797e-02, 1.7024e-01,\n 3.3818e-02, 7.2957e-02, 1.0080e-01, 3.3102e-02, 8.6305e-02,\n 2.6746e-01, 1.8659e-01, 1.4193e-01, 7.5845e-02, 1.3285e-01,\n 1.1208e-01, -9.3924e-03, 4.3963e-02, 2.8947e-04, 7.6066e-02,\n 1.9654e-01, 2.3392e-02, 1.6657e-01, 3.4220e-02, 2.1208e-01,\n 1.0441e-01, 1.3257e-01, 6.1205e-02, 9.1782e-02, 5.8149e-02,\n 5.3822e-02, 1.3941e-01, 1.6724e-01, 9.0943e-03, 5.8889e-02,\n 3.2101e-01, 1.1914e-01, 5.2162e-02, 9.1571e-02, 2.2049e-02,\n 9.1670e-02, 2.2609e-01, 4.7597e-02, -1.3806e-02, 2.0500e-01,\n 1.8695e-01, 1.0369e-02, 1.0849e-02, 3.6321e-02, 5.9064e-02,\n 1.5055e-01, 6.0216e-03, 1.6935e-01, 1.1479e-01, 1.3769e-01,\n 2.3151e-01, 1.1065e-01, -4.8216e-03, 1.2501e-01, 1.4674e-01,\n 1.0817e-01, 1.5372e-02, 6.3256e-02, 5.5337e-02, 6.6935e-03,\n 1.9285e-01, 6.3768e-02, 8.1425e-02, 6.2178e-02, 9.4410e-03,\n 6.9121e-02, 1.4357e-01, 7.2777e-02, -3.8647e-03, 4.7887e-02,\n 5.7002e-02, 8.2180e-03, 1.7953e-01, 7.7592e-02, 1.3762e-01,\n 5.4110e-02, 2.5230e-02, 6.3522e-02, 1.1038e-01, -4.4912e-03,\n 9.8029e-02, 4.9463e-02]), 'model.layer2.3.bn3.bias': tensor([-8.0311e-03, 1.3321e-01, 2.5480e-02, -1.4687e-01, -1.0298e-01,\n 1.4761e-02, -9.4533e-03, -9.1417e-02, -6.7944e-02, -1.7974e-01,\n -8.9363e-02, -6.1534e-02, 6.7991e-02, -1.9379e-03, -5.9050e-02,\n -7.9792e-02, 3.8916e-02, -7.6423e-02, -7.5641e-02, -1.3537e-01,\n 2.7219e-03, -2.5054e-02, -1.0572e-01, 4.9481e-02, -1.6399e-01,\n -1.1943e-01, -1.8672e-01, -4.5544e-02, 5.6497e-02, -4.4419e-02,\n -1.1653e-01, 1.3067e-02, -6.2764e-02, -1.0900e-01, -1.0274e-01,\n 1.2140e-02, 9.4152e-03, -1.2122e-01, 6.0889e-02, -4.4210e-02,\n -1.4425e-01, -9.4985e-02, -1.0019e-01, -2.5528e-02, 3.3105e-03,\n -1.3414e-01, -2.3652e-02, -1.0446e-01, -1.4443e-01, -6.3351e-02,\n -1.3989e-01, 6.0006e-02, -1.3488e-01, -7.7855e-02, -8.3889e-02,\n 7.6640e-03, -1.5932e-02, 1.3662e-02, 2.0886e-02, -9.8811e-02,\n -3.0377e-02, 1.5494e-02, -1.0141e-01, -6.8979e-02, -7.5565e-02,\n -1.2741e-01, -1.0441e-02, -9.0778e-02, 9.7140e-02, -1.1658e-01,\n -1.3077e-01, -1.9417e-01, -1.2877e-01, -9.2788e-02, -7.0833e-02,\n -8.0419e-02, -7.3194e-02, -1.2012e-01, 5.3331e-02, 9.1272e-02,\n -1.0010e-02, -9.0070e-02, -3.7516e-02, -7.1719e-02, -9.3360e-02,\n -1.4759e-01, -1.0914e-01, -5.3514e-02, -2.7789e-02, 6.1761e-02,\n 8.8755e-02, -3.0985e-02, 4.0984e-02, 2.7039e-02, 2.2180e-02,\n 8.3246e-03, -1.1317e-01, -2.7804e-02, -1.0164e-01, 5.7840e-03,\n -1.1514e-01, 1.5325e-02, 2.6607e-03, -1.3027e-02, -5.4505e-02,\n 1.2541e-02, -1.8018e-01, -9.1343e-02, -1.3111e-02, -2.9196e-02,\n -7.8166e-02, -1.6903e-01, -1.0260e-01, 5.7173e-02, 1.1425e-02,\n 4.6740e-03, -6.7175e-02, -7.8791e-02, -9.4932e-02, -3.0734e-02,\n -4.4585e-02, 6.0400e-02, -1.0738e-01, -1.8604e-01, -2.1430e-02,\n -7.5665e-02, 3.6656e-02, 2.8037e-02, -6.5022e-02, 3.6963e-02,\n -1.0051e-01, -1.4140e-01, -1.6312e-01, 9.0301e-03, 3.6678e-03,\n 1.3247e-02, -1.4997e-01, 9.1211e-02, -1.1101e-03, -9.4847e-03,\n -9.4441e-02, -1.4566e-01, -1.5556e-01, -8.0949e-02, 1.2184e-02,\n -1.4223e-01, -5.2138e-02, -1.1858e-01, -1.2141e-01, -1.2071e-01,\n -7.7488e-03, -6.2799e-02, -1.5869e-01, -4.1524e-02, -1.2096e-01,\n 4.3347e-03, -1.0281e-01, 4.2472e-02, -8.5999e-02, -3.6711e-02,\n -1.7079e-01, 9.5715e-03, 3.3953e-03, -4.6336e-02, -3.1364e-02,\n -3.8837e-03, 8.4888e-03, -1.1663e-01, 1.3879e-04, -9.2520e-02,\n -1.1416e-02, -2.9020e-02, -8.7499e-03, 1.7373e-02, -1.7191e-02,\n -2.4105e-02, -3.6465e-02, -1.4134e-01, -7.0804e-02, -4.9350e-02,\n -1.2017e-01, -1.0069e-01, -5.4241e-02, -6.2134e-03, -1.4340e-01,\n -8.3742e-02, -7.5960e-04, -1.4584e-01, 1.9397e-02, 4.9849e-02,\n -1.2286e-01, -8.6397e-02, -1.4174e-01, -2.1595e-01, -5.4293e-03,\n -3.8680e-02, 3.5060e-02, -3.3168e-02, -6.5964e-02, 1.0687e-02,\n -7.6697e-02, -5.9429e-02, -5.9950e-02, -4.9808e-02, -2.9750e-02,\n -3.9336e-02, -3.5895e-02, -2.9295e-02, -9.6040e-03, -9.5449e-02,\n 8.7392e-02, -8.1633e-02, 3.6369e-02, -5.5173e-02, -3.3028e-02,\n -7.1480e-02, 7.2094e-02, -1.4871e-02, -1.1592e-02, -9.2173e-02,\n -1.3505e-01, 6.8610e-02, -4.2891e-02, -2.1952e-02, -2.0084e-01,\n -1.5150e-01, -9.6567e-02, -3.7398e-02, -1.2583e-01, -9.3578e-02,\n -1.7518e-01, -1.2330e-01, -1.4780e-01, -1.1596e-01, 1.1810e-02,\n -1.7461e-01, 2.7164e-02, -1.9475e-02, -1.6923e-01, -9.5115e-02,\n 2.3394e-02, -8.5379e-02, -1.0696e-01, -6.7294e-04, -1.4571e-01,\n -3.4448e-02, -5.1618e-02, -7.3989e-02, 2.7807e-02, -6.6390e-02,\n -1.8935e-01, 1.9334e-02, -1.0070e-02, -1.4390e-01, -1.9689e-01,\n -1.1232e-01, -1.8690e-02, -1.0948e-01, -1.8734e-01, -2.7741e-03,\n -1.4087e-01, -7.5083e-02, -6.9070e-02, 1.0485e-02, -1.5661e-01,\n 7.1048e-03, -7.6661e-02, -5.4706e-02, 2.5478e-02, -5.7970e-02,\n 1.2966e-03, -7.2993e-02, -6.3252e-02, -1.2965e-01, -1.2887e-01,\n 1.1002e-02, -2.8364e-02, -7.0622e-02, -1.2268e-01, -7.0747e-02,\n -1.1060e-01, -8.7729e-02, -2.1095e-02, -6.4946e-02, -4.0111e-02,\n 9.3366e-03, -8.2777e-02, -1.0579e-01, 3.3117e-02, -3.2249e-02,\n 1.3491e-02, -2.6397e-02, -1.1640e-01, -1.2333e-01, -2.8802e-02,\n -1.1359e-01, -1.8793e-01, 5.2236e-02, -8.3032e-02, -8.1026e-02,\n 4.6271e-02, -1.2763e-02, -1.3508e-01, -1.3255e-01, -3.4075e-02,\n -1.4483e-02, -2.8797e-02, -7.7820e-02, -5.5294e-02, -7.1072e-02,\n -5.9631e-02, 1.1646e-03, -2.9849e-02, -3.6559e-02, -6.2954e-02,\n 9.6331e-02, -1.4376e-01, -1.0487e-01, -8.4850e-03, -1.1833e-02,\n -1.0863e-01, -1.7691e-01, 5.4515e-02, -7.0280e-02, 1.5970e-02,\n -3.2215e-02, -1.6301e-01, -1.8124e-01, -1.4173e-01, 7.4218e-02,\n -2.6749e-02, -6.9194e-02, -1.6636e-02, -6.5389e-02, 4.4011e-02,\n -7.7073e-02, -1.7128e-01, -3.7993e-02, -4.1986e-02, -1.2000e-01,\n -6.1315e-02, -1.4458e-01, -9.5289e-02, 3.1452e-02, -1.9275e-02,\n -1.5184e-01, -2.1721e-02, -1.1478e-02, -6.5692e-02, 5.3385e-03,\n -1.1746e-01, 3.0066e-02, -1.2135e-01, -9.7670e-02, -8.6288e-02,\n -1.4258e-01, -1.4535e-01, 4.1736e-03, -3.1352e-02, -1.3901e-01,\n -1.3273e-01, -6.5581e-02, -1.2473e-01, -4.3993e-02, -6.9778e-02,\n -8.6932e-02, -3.8913e-03, -1.4660e-01, -6.3903e-02, -6.7467e-02,\n 7.9769e-02, 1.2902e-02, -1.4612e-01, -8.5373e-02, -2.8777e-02,\n -1.1403e-01, -5.5524e-02, -1.5030e-01, -1.1069e-01, -7.3003e-02,\n -5.6670e-02, -7.3735e-02, -1.8352e-02, -6.1544e-02, -4.6895e-02,\n -1.3690e-01, -1.6323e-02, -3.0153e-02, -1.0627e-02, -1.8037e-02,\n -2.8183e-02, -7.6225e-02, 1.7247e-02, -6.0416e-02, 6.4815e-02,\n 4.8033e-03, -5.8666e-02, 5.0026e-04, -1.2974e-01, -8.4783e-02,\n 4.9395e-02, 7.9961e-03, -7.9979e-02, -9.2508e-02, -1.8324e-01,\n 1.8989e-02, -3.6303e-03, 5.7638e-02, -6.8394e-02, 8.9056e-03,\n -1.1619e-01, -1.4662e-01, -6.8728e-02, 5.2169e-02, 6.3127e-02,\n -1.2425e-01, 7.8923e-03, -1.1428e-01, -2.3618e-02, 7.2560e-02,\n 3.1795e-02, 4.9077e-02, -3.9114e-02, 6.5974e-03, -1.7900e-01,\n -4.7722e-02, 5.8274e-04, 3.2056e-02, -1.3812e-01, -4.5266e-02,\n 2.0717e-02, -4.8140e-02, -8.0183e-02, 5.2730e-02, 2.2245e-02,\n -1.7910e-01, 2.9329e-02, -2.7873e-02, -7.8172e-02, -1.7244e-01,\n 3.2144e-02, 3.4657e-02, 1.2881e-02, 5.5859e-03, -3.4753e-02,\n -6.4252e-02, -3.6839e-02, -1.9047e-01, -1.0405e-01, -1.1038e-01,\n -1.7894e-01, -1.1648e-01, -1.2432e-01, -8.0982e-02, -7.4476e-02,\n -1.9365e-01, -2.0010e-02, -1.4538e-02, 2.4634e-03, -1.2154e-01,\n -1.7793e-01, -5.7760e-02, -3.0288e-03, -1.2226e-01, -4.8088e-02,\n -1.2358e-01, 4.0069e-02, 7.0287e-02, -9.5735e-03, -1.3008e-01,\n 9.2914e-02, -5.7828e-03, 1.6435e-03, -4.2021e-02, -8.4716e-02,\n -1.3682e-01, 1.8479e-02, -5.9173e-02, -1.4148e-01, -3.1581e-02,\n 1.1891e-01, -1.5211e-01, 1.0661e-02, -5.4842e-02, -7.8874e-03,\n -1.5291e-01, 1.4619e-02, -1.3447e-01, -7.1869e-02, -9.5183e-03,\n -9.6482e-03, 5.6763e-02, -1.5416e-01, -6.7456e-02, 8.8170e-03,\n -7.5047e-02, -9.9851e-02, -3.8724e-02, -2.5248e-03, -3.0197e-02,\n -1.0594e-01, -7.6940e-04, -8.4415e-02, -1.0497e-01, -1.3482e-01,\n -5.5224e-02, -3.2331e-02, 5.1440e-02, -9.8266e-03, -4.4944e-03,\n -1.2275e-01, -7.9217e-02]), 'model.layer2.3.bn3.running_mean': tensor([-9.5600e-03, 7.1885e-03, 8.0626e-04, -3.3389e-02, -1.4586e-02,\n 1.5738e-03, -3.1977e-03, -1.2045e-02, -2.2185e-02, -2.5944e-02,\n -4.7764e-02, -7.2624e-03, 3.3940e-02, 3.2356e-03, 7.8418e-03,\n -3.3690e-03, 3.1941e-02, -7.7782e-03, -3.3786e-02, 3.3311e-03,\n -1.3994e-02, 3.8140e-03, 2.6549e-02, 6.7152e-03, 2.9177e-02,\n 5.8263e-03, 6.0987e-03, -6.8513e-02, -1.4033e-02, 3.8368e-03,\n 5.0747e-02, 1.2016e-02, -2.7797e-02, 1.6974e-02, 1.6124e-02,\n -7.4974e-03, -9.8516e-03, 6.1202e-02, -5.1882e-02, -1.2648e-02,\n -1.0130e-02, -1.6334e-02, -2.2730e-02, -6.8119e-03, -1.1004e-02,\n -1.5084e-02, -6.6244e-03, -1.5767e-03, -4.7240e-02, 8.4744e-03,\n -1.5915e-02, -7.8520e-03, -2.9292e-02, 3.6438e-02, 1.5014e-02,\n -2.7344e-02, 3.1595e-02, -3.1754e-02, -3.0494e-03, -1.9529e-02,\n -2.6319e-02, -6.2900e-02, 1.0369e-02, 5.9693e-03, -1.0062e-01,\n 1.5915e-02, -1.8353e-02, 2.1468e-02, 3.1398e-03, -1.9953e-02,\n 4.4329e-03, -1.5898e-02, -3.7092e-03, 8.3909e-03, 2.5038e-03,\n 1.9262e-02, -3.0694e-02, 1.0480e-02, 1.4637e-02, -2.5312e-02,\n -3.7121e-03, 1.7634e-02, -6.5895e-03, -3.1831e-03, 1.7270e-02,\n 1.3088e-02, 1.7967e-02, 4.5273e-03, -7.2193e-03, -3.5720e-02,\n 1.3800e-02, -2.9991e-02, -1.6660e-02, -4.7806e-02, -6.8822e-03,\n 4.9467e-03, 2.7773e-02, 1.1377e-03, 6.6764e-03, 1.5837e-03,\n 4.9814e-02, -1.7659e-02, -1.7443e-04, -8.8620e-03, -1.7874e-02,\n 2.6540e-03, -4.3822e-03, -1.7226e-02, -1.3866e-02, -8.2522e-03,\n 4.7248e-02, -2.6280e-02, -6.8213e-03, -6.9233e-02, 7.1500e-03,\n 1.3906e-03, -1.8805e-02, -5.7315e-03, -5.3086e-03, -7.3449e-03,\n 1.1130e-02, -4.0635e-03, 1.1603e-02, -1.1524e-02, -6.8810e-03,\n 6.6081e-03, -7.3187e-03, 1.2387e-02, -1.9397e-02, -2.0531e-02,\n -5.4290e-03, 2.8384e-03, -5.5051e-03, -4.4665e-03, 9.4642e-03,\n -2.4208e-03, -9.6085e-03, 4.4410e-02, -8.9839e-03, 1.4870e-02,\n 3.5199e-02, -3.4657e-02, 6.1248e-03, -8.4982e-03, -1.0412e-03,\n 1.1365e-02, 1.6366e-02, -1.3110e-02, 3.7477e-02, -3.7519e-03,\n -3.9597e-03, -1.2900e-02, -4.2950e-03, -3.0275e-03, 3.2573e-04,\n 3.3507e-03, 4.2296e-03, -2.9255e-02, 5.2691e-02, 3.4491e-03,\n -2.1695e-03, -3.8535e-04, -2.5422e-02, -4.0677e-03, 9.4353e-03,\n -4.7400e-03, -9.5729e-03, -1.1009e-02, -4.9561e-02, -3.1504e-02,\n -1.5052e-03, -4.6490e-04, 4.2077e-03, 6.9206e-03, -7.1285e-03,\n -3.9220e-02, 4.1769e-04, -3.3361e-03, 6.9011e-03, 7.1193e-02,\n 4.3215e-02, 1.8603e-02, 1.8449e-02, 1.5609e-02, 8.2931e-03,\n 5.4954e-02, -3.1758e-03, -6.4575e-03, 1.3004e-04, 2.8802e-03,\n 6.4943e-03, 2.6177e-02, 1.6621e-02, 9.4886e-02, 1.3244e-04,\n 9.8145e-03, 1.1145e-02, 1.2195e-03, -2.1129e-02, -1.8965e-03,\n -3.3104e-03, 3.3565e-02, -8.4340e-03, -1.5222e-02, -9.9479e-03,\n 3.8054e-03, 1.2655e-02, -1.3727e-02, -7.5648e-04, -2.2001e-02,\n -1.3838e-03, 6.9573e-02, 9.4018e-03, -3.0624e-02, -1.8263e-02,\n -2.9802e-03, 1.5213e-02, 1.1915e-02, 2.5430e-03, 1.7625e-02,\n 1.7099e-02, -2.0746e-02, 1.2226e-02, -3.8398e-02, 1.2407e-02,\n -2.9183e-02, -2.1615e-02, 4.3889e-03, -1.4773e-02, 2.4192e-02,\n 3.8953e-02, 3.3437e-02, -1.1092e-02, 8.2619e-03, -9.2275e-03,\n -3.7707e-04, -4.4437e-03, -1.4023e-02, -1.6998e-02, 1.6289e-02,\n -4.5602e-03, -1.6340e-02, -1.3573e-02, 2.8301e-03, 3.0200e-02,\n 2.3960e-03, -1.4575e-02, 3.0291e-02, -6.5044e-02, -7.4092e-03,\n 1.5762e-02, -1.1318e-02, -3.8853e-02, -2.4755e-02, -1.4275e-03,\n -1.5036e-02, -2.0342e-02, 4.4723e-03, 1.0953e-02, 7.6468e-03,\n -2.5756e-02, -1.0181e-02, -2.6408e-02, 6.4576e-03, -1.2173e-02,\n 3.3259e-03, -2.2915e-02, 1.5447e-02, 7.0798e-03, 3.2901e-03,\n -1.5823e-03, -1.8555e-02, 2.1139e-05, 1.3103e-04, -1.7602e-04,\n 1.0114e-02, 4.7527e-03, -2.8355e-02, -1.4929e-02, -1.4077e-02,\n 1.9224e-02, -1.5473e-02, -4.9599e-02, 9.3977e-03, 1.6066e-02,\n 3.5248e-03, -1.7141e-02, 1.0774e-03, -3.3143e-02, -7.0035e-02,\n -1.1797e-02, -1.8263e-03, -4.1720e-03, -3.8533e-02, -1.4294e-01,\n -1.8224e-02, -3.0294e-02, -9.4199e-03, -1.9225e-02, -7.4997e-02,\n 4.9832e-02, -4.6733e-02, -7.9757e-02, 2.2179e-02, -5.4695e-02,\n 2.2764e-02, 4.6476e-02, 8.4831e-02, -1.1353e-01, -2.8118e-03,\n -2.9515e-02, -3.7200e-03, 8.6315e-03, -1.3842e-03, -2.4931e-03,\n -7.3919e-03, -8.5029e-03, -6.9091e-03, 9.3416e-03, 6.0132e-03,\n -3.6804e-02, -1.4215e-02, 7.7158e-04, -2.5713e-02, -6.4543e-03,\n -1.5578e-02, 4.2784e-03, 5.9097e-03, -1.3780e-02, 1.6272e-03,\n 1.3740e-02, -1.3121e-02, 1.8437e-02, -1.9512e-02, -7.4717e-02,\n -6.3464e-03, -8.1407e-02, -7.7770e-03, -1.0048e-02, -6.5892e-03,\n 2.2420e-03, 5.3531e-03, -4.0176e-02, 2.1053e-03, -1.0880e-02,\n 2.2279e-02, -8.1221e-03, 3.2899e-03, -8.4280e-02, -6.1269e-03,\n 7.3640e-03, -1.5147e-03, 2.4665e-02, -1.5094e-03, -5.9271e-03,\n 3.9024e-02, 9.6729e-03, 2.4620e-03, 3.1577e-02, -7.2844e-04,\n -2.8576e-02, -1.2071e-02, -7.6817e-04, -4.5253e-03, -2.9135e-02,\n 9.2410e-03, -1.4355e-02, -3.2211e-02, 5.0486e-02, 8.0943e-03,\n -9.5575e-03, -2.9896e-04, -8.8284e-03, 2.5336e-02, 1.3900e-03,\n -6.4492e-02, 1.0728e-02, 1.6283e-03, -3.3553e-03, -1.1665e-03,\n 1.8871e-02, -6.1743e-04, -1.3835e-03, 2.1081e-02, -8.2806e-03,\n -1.9669e-02, -3.4386e-03, -7.1128e-03, 1.5483e-02, 1.4793e-02,\n -1.0720e-02, 9.7682e-03, -3.2992e-05, -6.3334e-02, 1.7956e-02,\n 9.2656e-03, 6.1824e-03, 3.4557e-02, 3.7646e-02, -1.5838e-02,\n 4.7435e-03, -3.2154e-03, -2.1289e-02, 1.6679e-02, 4.3056e-02,\n 2.1262e-03, 1.8346e-02, -4.6449e-02, 1.4773e-02, -1.4090e-02,\n -7.4824e-02, 1.1621e-02, 1.5678e-02, 4.9522e-03, -2.4100e-03,\n 2.0951e-02, -1.2447e-02, 3.1811e-04, 3.4319e-03, -2.5482e-02,\n 1.9682e-02, 9.2132e-04, -1.1206e-01, -4.4543e-03, 5.4325e-02,\n 1.6414e-02, -4.0208e-03, 1.4682e-03, 1.7898e-02, 1.1144e-04,\n -3.6727e-02, 3.2687e-02, 3.4212e-03, -1.3113e-03, -2.3072e-02,\n -8.7600e-02, -9.2536e-03, -4.1998e-02, 4.3890e-02, -2.4853e-02,\n -1.3262e-02, 7.9389e-03, 1.7403e-02, -1.1623e-03, 4.1739e-02,\n -1.8020e-02, -1.1707e-02, -1.4988e-02, -1.4804e-02, -8.6657e-03,\n 4.7714e-02, -5.8454e-03, -1.7636e-02, 9.3129e-04, -1.5031e-02,\n 2.2873e-02, -1.0626e-02, -7.1283e-02, 1.3842e-02, 7.3561e-02,\n -9.8737e-02, -4.5709e-02, 5.1533e-03, -8.8308e-04, 1.0106e-02,\n -2.1122e-02, -1.8847e-02, 8.5754e-03, -5.2147e-04, -3.5663e-02,\n -1.9228e-02, -5.7754e-03, -9.4540e-03, -9.8061e-04, -2.6096e-02,\n -2.4714e-02, 1.7623e-02, -5.2172e-03, -1.8395e-02, -1.5521e-02,\n -8.4313e-02, 1.2049e-02, 3.9975e-03, 1.3861e-03, -4.3796e-02,\n -1.8915e-03, 5.6458e-04, 5.0042e-03, -1.5137e-02, -1.6588e-03,\n -2.4143e-02, -1.1179e-02, -2.7827e-03, 3.2592e-03, 1.1136e-03,\n -2.6610e-02, 2.3551e-02, 7.6561e-03, 5.4634e-04, -2.0025e-02,\n 1.8470e-03, -5.2601e-03, -3.0151e-02, -1.3668e-02, 5.2405e-02,\n -1.9350e-02, -3.8106e-03, 1.0851e-02, -1.2494e-02, 1.1025e-03,\n 4.9087e-02, -1.3142e-02]), 'model.layer2.3.bn3.running_var': tensor([0.0002, 0.0016, 0.0004, 0.0007, 0.0005, 0.0002, 0.0003, 0.0004, 0.0018,\n 0.0014, 0.0007, 0.0004, 0.0012, 0.0003, 0.0005, 0.0028, 0.0012, 0.0014,\n 0.0011, 0.0009, 0.0021, 0.0006, 0.0006, 0.0006, 0.0019, 0.0008, 0.0012,\n 0.0018, 0.0005, 0.0024, 0.0008, 0.0003, 0.0005, 0.0005, 0.0004, 0.0006,\n 0.0006, 0.0019, 0.0007, 0.0014, 0.0017, 0.0017, 0.0013, 0.0004, 0.0005,\n 0.0023, 0.0004, 0.0013, 0.0021, 0.0009, 0.0006, 0.0036, 0.0012, 0.0009,\n 0.0004, 0.0018, 0.0016, 0.0036, 0.0003, 0.0008, 0.0002, 0.0018, 0.0023,\n 0.0002, 0.0017, 0.0009, 0.0001, 0.0016, 0.0034, 0.0014, 0.0009, 0.0026,\n 0.0010, 0.0014, 0.0015, 0.0006, 0.0009, 0.0015, 0.0020, 0.0034, 0.0005,\n 0.0021, 0.0002, 0.0009, 0.0013, 0.0016, 0.0015, 0.0003, 0.0003, 0.0010,\n 0.0011, 0.0017, 0.0016, 0.0006, 0.0004, 0.0026, 0.0010, 0.0002, 0.0006,\n 0.0003, 0.0009, 0.0017, 0.0002, 0.0011, 0.0004, 0.0003, 0.0016, 0.0024,\n 0.0009, 0.0010, 0.0007, 0.0031, 0.0006, 0.0019, 0.0002, 0.0004, 0.0016,\n 0.0005, 0.0015, 0.0011, 0.0012, 0.0016, 0.0006, 0.0008, 0.0011, 0.0004,\n 0.0009, 0.0004, 0.0016, 0.0018, 0.0015, 0.0014, 0.0010, 0.0002, 0.0003,\n 0.0004, 0.0014, 0.0027, 0.0003, 0.0014, 0.0012, 0.0008, 0.0011, 0.0005,\n 0.0002, 0.0006, 0.0003, 0.0009, 0.0016, 0.0006, 0.0004, 0.0004, 0.0014,\n 0.0003, 0.0005, 0.0004, 0.0004, 0.0008, 0.0005, 0.0011, 0.0013, 0.0004,\n 0.0010, 0.0002, 0.0011, 0.0002, 0.0004, 0.0012, 0.0026, 0.0006, 0.0002,\n 0.0012, 0.0004, 0.0004, 0.0009, 0.0028, 0.0002, 0.0013, 0.0004, 0.0022,\n 0.0020, 0.0030, 0.0005, 0.0003, 0.0007, 0.0008, 0.0003, 0.0019, 0.0003,\n 0.0013, 0.0006, 0.0020, 0.0007, 0.0017, 0.0002, 0.0018, 0.0006, 0.0027,\n 0.0013, 0.0003, 0.0009, 0.0023, 0.0004, 0.0005, 0.0003, 0.0023, 0.0012,\n 0.0005, 0.0005, 0.0011, 0.0012, 0.0013, 0.0011, 0.0004, 0.0013, 0.0018,\n 0.0011, 0.0005, 0.0002, 0.0015, 0.0009, 0.0013, 0.0002, 0.0030, 0.0005,\n 0.0017, 0.0019, 0.0003, 0.0012, 0.0015, 0.0025, 0.0012, 0.0012, 0.0008,\n 0.0002, 0.0012, 0.0006, 0.0007, 0.0021, 0.0005, 0.0007, 0.0004, 0.0016,\n 0.0003, 0.0022, 0.0019, 0.0006, 0.0009, 0.0018, 0.0003, 0.0016, 0.0005,\n 0.0026, 0.0018, 0.0020, 0.0011, 0.0012, 0.0007, 0.0014, 0.0003, 0.0020,\n 0.0013, 0.0012, 0.0003, 0.0017, 0.0003, 0.0007, 0.0003, 0.0004, 0.0003,\n 0.0002, 0.0012, 0.0002, 0.0009, 0.0019, 0.0002, 0.0026, 0.0016, 0.0010,\n 0.0006, 0.0010, 0.0006, 0.0014, 0.0007, 0.0003, 0.0002, 0.0020, 0.0011,\n 0.0010, 0.0032, 0.0003, 0.0003, 0.0021, 0.0015, 0.0025, 0.0015, 0.0015,\n 0.0009, 0.0005, 0.0034, 0.0011, 0.0007, 0.0021, 0.0007, 0.0013, 0.0018,\n 0.0014, 0.0019, 0.0019, 0.0002, 0.0027, 0.0002, 0.0002, 0.0003, 0.0003,\n 0.0014, 0.0016, 0.0002, 0.0003, 0.0002, 0.0015, 0.0010, 0.0007, 0.0007,\n 0.0003, 0.0003, 0.0015, 0.0012, 0.0005, 0.0018, 0.0005, 0.0008, 0.0002,\n 0.0004, 0.0019, 0.0009, 0.0020, 0.0002, 0.0010, 0.0006, 0.0006, 0.0010,\n 0.0005, 0.0018, 0.0003, 0.0010, 0.0002, 0.0002, 0.0015, 0.0005, 0.0010,\n 0.0003, 0.0010, 0.0007, 0.0004, 0.0011, 0.0010, 0.0003, 0.0013, 0.0021,\n 0.0010, 0.0015, 0.0009, 0.0002, 0.0006, 0.0007, 0.0006, 0.0016, 0.0006,\n 0.0006, 0.0014, 0.0003, 0.0010, 0.0008, 0.0003, 0.0021, 0.0010, 0.0022,\n 0.0012, 0.0005, 0.0028, 0.0009, 0.0002, 0.0015, 0.0015, 0.0013, 0.0002,\n 0.0003, 0.0004, 0.0026, 0.0015, 0.0018, 0.0002, 0.0019, 0.0017, 0.0003,\n 0.0005, 0.0018, 0.0009, 0.0010, 0.0006, 0.0003, 0.0032, 0.0007, 0.0005,\n 0.0003, 0.0002, 0.0012, 0.0006, 0.0010, 0.0020, 0.0014, 0.0004, 0.0007,\n 0.0015, 0.0025, 0.0009, 0.0026, 0.0002, 0.0021, 0.0009, 0.0009, 0.0029,\n 0.0012, 0.0009, 0.0017, 0.0004, 0.0009, 0.0008, 0.0018, 0.0007, 0.0013,\n 0.0016, 0.0006, 0.0013, 0.0028, 0.0022, 0.0017, 0.0011, 0.0012, 0.0014,\n 0.0002, 0.0006, 0.0002, 0.0009, 0.0024, 0.0002, 0.0028, 0.0006, 0.0015,\n 0.0009, 0.0013, 0.0007, 0.0009, 0.0004, 0.0004, 0.0018, 0.0017, 0.0002,\n 0.0011, 0.0030, 0.0019, 0.0003, 0.0007, 0.0003, 0.0010, 0.0023, 0.0008,\n 0.0002, 0.0024, 0.0020, 0.0002, 0.0004, 0.0002, 0.0006, 0.0012, 0.0003,\n 0.0023, 0.0011, 0.0020, 0.0030, 0.0015, 0.0003, 0.0030, 0.0019, 0.0012,\n 0.0005, 0.0011, 0.0004, 0.0003, 0.0019, 0.0007, 0.0005, 0.0008, 0.0003,\n 0.0005, 0.0015, 0.0007, 0.0002, 0.0008, 0.0006, 0.0003, 0.0026, 0.0007,\n 0.0016, 0.0004, 0.0004, 0.0010, 0.0014, 0.0003, 0.0016, 0.0006]), 'model.layer2.3.bn3.num_batches_tracked': tensor(7160), 'model.layer3.0.conv1.weight': tensor([[[[ 0.0077]],\n\n [[ 0.0163]],\n\n [[ 0.0101]],\n\n ...,\n\n [[ 0.0002]],\n\n [[-0.0168]],\n\n [[ 0.0039]]],\n\n\n [[[-0.0091]],\n\n [[ 0.0058]],\n\n [[ 0.0149]],\n\n ...,\n\n [[ 0.0135]],\n\n [[ 0.0840]],\n\n [[-0.0049]]],\n\n\n [[[ 0.0196]],\n\n [[-0.0370]],\n\n [[ 0.0114]],\n\n ...,\n\n [[ 0.0149]],\n\n [[-0.0059]],\n\n [[-0.0276]]],\n\n\n ...,\n\n\n [[[ 0.0026]],\n\n [[ 0.0108]],\n\n [[-0.0261]],\n\n ...,\n\n [[-0.0211]],\n\n [[-0.0288]],\n\n [[ 0.0247]]],\n\n\n [[[-0.0094]],\n\n [[-0.0620]],\n\n [[ 0.0052]],\n\n ...,\n\n [[ 0.0036]],\n\n [[ 0.0157]],\n\n [[ 0.0317]]],\n\n\n [[[ 0.0113]],\n\n [[-0.0288]],\n\n [[ 0.0016]],\n\n ...,\n\n [[ 0.0119]],\n\n [[-0.0519]],\n\n [[ 0.0057]]]]), 'model.layer3.0.bn1.weight': tensor([0.1996, 0.2572, 0.2030, 0.1657, 0.2131, 0.1928, 0.2679, 0.2512, 0.2341,\n 0.2082, 0.2084, 0.2460, 0.2824, 0.2594, 0.2432, 0.2775, 0.1739, 0.2631,\n 0.2379, 0.1915, 0.2724, 0.2516, 0.2783, 0.2718, 0.2717, 0.2798, 0.2705,\n 0.2119, 0.2277, 0.2042, 0.2679, 0.2272, 0.2077, 0.2150, 0.1731, 0.2204,\n 0.2221, 0.2260, 0.2374, 0.2171, 0.2033, 0.2233, 0.2013, 0.2086, 0.2039,\n 0.2008, 0.2860, 0.2286, 0.2114, 0.1729, 0.2788, 0.2381, 0.3132, 0.2431,\n 0.2444, 0.2193, 0.1956, 0.2301, 0.2330, 0.2318, 0.2754, 0.1635, 0.2870,\n 0.2334, 0.2052, 0.3017, 0.2105, 0.2246, 0.1957, 0.2825, 0.2181, 0.2280,\n 0.2311, 0.2178, 0.2950, 0.2514, 0.2436, 0.2728, 0.2305, 0.2224, 0.2819,\n 0.1978, 0.2158, 0.2284, 0.2002, 0.2553, 0.2609, 0.2712, 0.2342, 0.2206,\n 0.2321, 0.2220, 0.1957, 0.2202, 0.1855, 0.2661, 0.1618, 0.2663, 0.2195,\n 0.1743, 0.2485, 0.2516, 0.1582, 0.2572, 0.2542, 0.2525, 0.1858, 0.2029,\n 0.1604, 0.2645, 0.2169, 0.1954, 0.2426, 0.1849, 0.2360, 0.2443, 0.2237,\n 0.2250, 0.2384, 0.2262, 0.2178, 0.2393, 0.1625, 0.2808, 0.2876, 0.3037,\n 0.2143, 0.1846, 0.2427, 0.2162, 0.2598, 0.2354, 0.2264, 0.1836, 0.3012,\n 0.2191, 0.2269, 0.2960, 0.2523, 0.2448, 0.2268, 0.2258, 0.1884, 0.2184,\n 0.2337, 0.1963, 0.2342, 0.2749, 0.2305, 0.2690, 0.2319, 0.2227, 0.2907,\n 0.2850, 0.3134, 0.2010, 0.2368, 0.2619, 0.2065, 0.2562, 0.2512, 0.1893,\n 0.2392, 0.1992, 0.2129, 0.2057, 0.2240, 0.2888, 0.2428, 0.1651, 0.2572,\n 0.2748, 0.2651, 0.2254, 0.2371, 0.1324, 0.2361, 0.2216, 0.2330, 0.2461,\n 0.1797, 0.2157, 0.1692, 0.2008, 0.2816, 0.2593, 0.2216, 0.2527, 0.2475,\n 0.2269, 0.2288, 0.2478, 0.3201, 0.2541, 0.2314, 0.2620, 0.2380, 0.2189,\n 0.1623, 0.2404, 0.2005, 0.2549, 0.2096, 0.1950, 0.2849, 0.2639, 0.1959,\n 0.2046, 0.2169, 0.2559, 0.2851, 0.2545, 0.2054, 0.2360, 0.2596, 0.2706,\n 0.3198, 0.2573, 0.1731, 0.2591, 0.2843, 0.1809, 0.2076, 0.2057, 0.2420,\n 0.2306, 0.1845, 0.2027, 0.2345, 0.2609, 0.2319, 0.2800, 0.2348, 0.2170,\n 0.2542, 0.2574, 0.1972, 0.2252, 0.2480, 0.2249, 0.2932, 0.2322, 0.1742,\n 0.2357, 0.2193, 0.2339, 0.2529, 0.1968, 0.1914, 0.2151, 0.2652, 0.1772,\n 0.2113, 0.2451, 0.2214, 0.2444]), 'model.layer3.0.bn1.bias': tensor([-7.4663e-02, -2.1475e-01, -8.4732e-02, 1.4074e-02, -1.7141e-01,\n -3.2331e-02, -2.5180e-01, -1.1293e-01, -1.5964e-01, -2.5341e-02,\n -1.6118e-01, -2.2788e-01, -1.7207e-01, -1.9385e-01, -1.4324e-01,\n -2.5177e-01, -1.2828e-02, -1.5004e-01, -1.9041e-01, -9.2309e-02,\n -1.3251e-01, -1.0044e-01, -2.1440e-01, -1.9099e-01, -2.2901e-01,\n -2.3108e-01, -1.6459e-01, -1.5062e-01, -1.5656e-02, -8.3009e-02,\n -1.3654e-01, -1.0786e-01, -5.2090e-02, -1.2285e-01, 1.5943e-02,\n -8.4096e-02, -1.1887e-01, -1.2056e-01, -1.6464e-01, -8.3180e-02,\n -4.7511e-02, -6.2659e-02, -1.4096e-01, -1.0008e-02, -9.0942e-02,\n -4.6594e-02, -1.5886e-01, -2.2119e-02, -1.7101e-01, -9.4944e-02,\n -2.2468e-01, -7.4620e-02, -1.6971e-01, -9.8435e-02, -1.3533e-01,\n -1.7667e-01, -7.4877e-02, -8.6128e-02, -1.1253e-01, -4.7411e-02,\n -2.4517e-01, 7.9683e-02, -2.9690e-01, -1.6872e-01, -2.6726e-02,\n -3.7993e-01, -1.1420e-01, -9.5942e-02, -1.3428e-02, -2.4442e-01,\n -1.5184e-01, -1.0973e-01, -2.0903e-01, -8.7546e-02, -3.4243e-01,\n -7.9348e-02, -1.3946e-01, -2.4043e-01, -1.4348e-02, -1.4326e-01,\n -3.3366e-01, -6.2219e-02, -1.0003e-01, -1.2400e-01, -4.7453e-02,\n -1.7993e-01, -2.5464e-01, -1.4617e-01, -1.1887e-01, -1.3775e-01,\n -1.2526e-01, -1.1645e-01, -1.0909e-01, -1.5020e-01, 1.0124e-04,\n -2.1849e-01, -7.1999e-02, -2.1313e-01, -7.1217e-02, -8.7269e-02,\n -9.4976e-02, -2.4057e-01, 7.2222e-02, -1.8792e-01, -1.7745e-01,\n -2.6438e-01, -6.9111e-02, -7.3449e-02, 1.0577e-01, -1.5762e-01,\n -2.0579e-01, -9.1914e-02, -1.2657e-01, -7.0333e-02, -1.1769e-01,\n -1.3833e-01, -1.7811e-02, -1.2776e-01, -4.4564e-02, -1.1616e-01,\n -5.8508e-02, -8.8177e-02, -1.8656e-03, -1.6456e-01, -1.5528e-01,\n -3.7492e-01, -1.7534e-01, -5.2057e-03, -1.0833e-01, -1.4083e-01,\n -1.4103e-01, -1.0805e-01, -1.1684e-01, -4.0722e-02, -3.6454e-01,\n -1.3134e-01, -9.6145e-02, -1.7029e-01, -2.2325e-01, -1.3077e-01,\n -8.9478e-02, -1.3456e-01, -6.7213e-02, -5.9339e-02, -1.4281e-01,\n -1.2037e-01, -1.1367e-01, -3.3053e-01, -1.8959e-01, -2.7428e-01,\n -2.0684e-01, -1.4262e-01, -3.7782e-01, -2.2417e-01, -3.0412e-01,\n -8.5495e-02, -2.2139e-01, -1.4909e-01, -1.2040e-01, -1.4401e-01,\n -1.4784e-01, -8.5301e-02, -1.4910e-01, -6.7129e-02, -5.8512e-02,\n -1.3770e-01, -1.4962e-01, -1.5837e-01, -1.0334e-01, -5.6283e-02,\n -1.4649e-01, -2.2810e-01, -2.0903e-01, -1.3165e-01, -1.1458e-01,\n 1.0026e-01, -9.9472e-02, 5.2288e-03, -1.3887e-01, -1.3596e-01,\n 1.6850e-02, -1.5024e-02, 4.9090e-03, -8.2711e-02, -1.1244e-01,\n -8.1976e-02, -1.0654e-01, -1.6406e-01, -2.0038e-01, -1.2967e-01,\n -1.3884e-01, -1.6930e-01, -2.8907e-01, -1.9975e-01, -2.0617e-01,\n -1.3628e-01, -1.5535e-01, -1.3823e-01, 2.8583e-02, -9.9201e-02,\n -6.8989e-02, -1.3427e-01, -5.0402e-02, -3.7316e-02, -1.1610e-01,\n -2.6046e-01, -1.0458e-01, -1.6448e-01, -4.4129e-02, -1.7667e-01,\n -1.8229e-01, -2.0951e-01, -1.6216e-01, -1.7146e-01, -1.1560e-01,\n -9.1469e-02, -1.5777e-01, -2.2750e-01, -3.9473e-02, -1.2581e-01,\n -2.5115e-01, -3.0991e-03, -1.1463e-01, -2.8083e-02, -1.7420e-01,\n -1.9414e-01, -1.2846e-02, -1.0127e-02, -1.7005e-01, -3.5109e-01,\n -1.5949e-01, -2.3101e-01, -1.5148e-01, -6.1844e-02, -1.2843e-01,\n -3.3184e-01, -1.1005e-01, -1.6622e-01, -1.6838e-01, -1.3230e-01,\n -2.3995e-01, -1.5721e-01, -5.1260e-02, -1.5225e-01, -1.2978e-01,\n -1.1998e-01, -1.7321e-01, -1.0516e-01, -4.2166e-02, -6.6027e-02,\n -1.4511e-01, -5.0708e-02, -9.5407e-02, -1.5015e-01, -2.2862e-01,\n -1.7446e-01]), 'model.layer3.0.bn1.running_mean': tensor([-0.0576, -0.1022, -0.0586, -0.0043, -0.1208, -0.0109, -0.0164, -0.0494,\n -0.1709, 0.0499, -0.1562, -0.1524, -0.2368, -0.3639, -0.0646, -0.0979,\n 0.0798, -0.0539, -0.1362, -0.0682, -0.3461, -0.1973, -0.1509, -0.1309,\n -0.0632, -0.0858, 0.0434, -0.0578, -0.1979, -0.0199, -0.1134, -0.1609,\n -0.0946, 0.0064, -0.1118, 0.0748, -0.0359, 0.0417, -0.1004, -0.0369,\n 0.0217, -0.1229, -0.0269, -0.0679, -0.0502, -0.3548, -0.1034, 0.0019,\n -0.1270, -0.0619, -0.0911, -0.1318, -0.0709, -0.0640, -0.0779, -0.0224,\n -0.2237, -0.2853, -0.1649, -0.1275, -0.1051, -0.1374, -0.1753, -0.0523,\n -0.0111, -0.0791, -0.1300, -0.1332, -0.1849, -0.1051, -0.0375, -0.2262,\n -0.2826, -0.0994, 0.1197, -0.2744, -0.1278, -0.0884, -0.2414, -0.2462,\n 0.0486, -0.1017, -0.1389, -0.0499, -0.1940, 0.0385, -0.0453, 0.0527,\n 0.1645, -0.0727, -0.0115, -0.0445, 0.1417, -0.1244, -0.0405, 0.0705,\n -0.1193, -0.2009, -0.0426, 0.0289, -0.2381, -0.0296, -0.1317, 0.1104,\n -0.2395, 0.2547, -0.1119, -0.0241, 0.0962, -0.0323, -0.0190, -0.2003,\n 0.0574, -0.0864, -0.2076, 0.0962, -0.1073, -0.1883, -0.2966, 0.1030,\n -0.1551, -0.0016, -0.1133, -0.0121, -0.0235, -0.2527, -0.0607, -0.0231,\n -0.0907, 0.0193, -0.0041, 0.0153, -0.0084, -0.1429, -0.0734, 0.0072,\n -0.0210, -0.1890, -0.0801, -0.1626, -0.0471, 0.0622, -0.2528, -0.0156,\n 0.1804, -0.0505, -0.2134, 0.3196, -0.1699, 0.1339, -0.0728, -0.1140,\n -0.1954, -0.0346, -0.2287, -0.1753, -0.1062, -0.0804, -0.0613, -0.1367,\n -0.1780, -0.1119, -0.1247, -0.1191, -0.0582, -0.0594, -0.1103, -0.1099,\n -0.1462, 0.0326, -0.0476, -0.0311, -0.1599, -0.0547, -0.4025, -0.0594,\n -0.0165, -0.1934, -0.0827, 0.0074, -0.1017, -0.3274, 0.0148, -0.0728,\n -0.1731, -0.1811, 0.0263, -0.1613, -0.1003, -0.2381, -0.1234, -0.1313,\n -0.0799, -0.1572, 0.0671, -0.1385, -0.2871, 0.0400, 0.0440, -0.1020,\n -0.0041, -0.1735, -0.0584, -0.2650, -0.0458, -0.0553, -0.0068, -0.0960,\n 0.1665, 0.0204, -0.0881, -0.1896, 0.0113, -0.1833, -0.1450, -0.1439,\n 0.0122, -0.0752, 0.0151, -0.0134, -0.0466, -0.0590, -0.0651, -0.0920,\n 0.0110, -0.0365, 0.0113, -0.2822, -0.1209, -0.1553, -0.0238, -0.1249,\n 0.0748, -0.0842, -0.2790, -0.1302, -0.1030, 0.0779, -0.2246, -0.1901,\n -0.2124, -0.1756, -0.0765, 0.0323, -0.1488, -0.0927, -0.0127, -0.1659,\n -0.0652, -0.0827, -0.1197, -0.1860, -0.0813, -0.0864, -0.0422, -0.1167]), 'model.layer3.0.bn1.running_var': tensor([0.0265, 0.0281, 0.0429, 0.0284, 0.0184, 0.0381, 0.0347, 0.0361, 0.0224,\n 0.0354, 0.0237, 0.0269, 0.0369, 0.0274, 0.0295, 0.0352, 0.0295, 0.0384,\n 0.0340, 0.0197, 0.0392, 0.0575, 0.0340, 0.0564, 0.0285, 0.0360, 0.0521,\n 0.0274, 0.0463, 0.0266, 0.0445, 0.0438, 0.0328, 0.0253, 0.0369, 0.0313,\n 0.0241, 0.0300, 0.0425, 0.0291, 0.0507, 0.0494, 0.0196, 0.0642, 0.0260,\n 0.0386, 0.0513, 0.0429, 0.0287, 0.0251, 0.0272, 0.0474, 0.0293, 0.0416,\n 0.0305, 0.0267, 0.0522, 0.0454, 0.0330, 0.0477, 0.0418, 0.0351, 0.0269,\n 0.0256, 0.0366, 0.0172, 0.0290, 0.0285, 0.0357, 0.0323, 0.0362, 0.0440,\n 0.0285, 0.0419, 0.0338, 0.0408, 0.0334, 0.0291, 0.0462, 0.0230, 0.0292,\n 0.0229, 0.0224, 0.0263, 0.0284, 0.0314, 0.0239, 0.0331, 0.0429, 0.0236,\n 0.0403, 0.0400, 0.0339, 0.0394, 0.0423, 0.0266, 0.0203, 0.0374, 0.0534,\n 0.0221, 0.0343, 0.0153, 0.0390, 0.0350, 0.0287, 0.0211, 0.0278, 0.0263,\n 0.0436, 0.0387, 0.0282, 0.0236, 0.0287, 0.0257, 0.0372, 0.0299, 0.0810,\n 0.0247, 0.0463, 0.0348, 0.0576, 0.0518, 0.0276, 0.0666, 0.0634, 0.0249,\n 0.0256, 0.0372, 0.0503, 0.0243, 0.0466, 0.0414, 0.0308, 0.0346, 0.0305,\n 0.0206, 0.0318, 0.0684, 0.0244, 0.0391, 0.0505, 0.0376, 0.0391, 0.0278,\n 0.0259, 0.0309, 0.0577, 0.0234, 0.0356, 0.0346, 0.0462, 0.0152, 0.0387,\n 0.0391, 0.0455, 0.0308, 0.0277, 0.0508, 0.0264, 0.0340, 0.0308, 0.0185,\n 0.0337, 0.0345, 0.0376, 0.0252, 0.0225, 0.0604, 0.0355, 0.0332, 0.0323,\n 0.0330, 0.0335, 0.0358, 0.0567, 0.0286, 0.0310, 0.0859, 0.0305, 0.0362,\n 0.0302, 0.0490, 0.0217, 0.0196, 0.0782, 0.0398, 0.0271, 0.0321, 0.0291,\n 0.0434, 0.0285, 0.0426, 0.0377, 0.0307, 0.0225, 0.0472, 0.0451, 0.0214,\n 0.0363, 0.0623, 0.0276, 0.0427, 0.0212, 0.0472, 0.0570, 0.0310, 0.0242,\n 0.0165, 0.0393, 0.0365, 0.0404, 0.0334, 0.0175, 0.0537, 0.0387, 0.0557,\n 0.0731, 0.0179, 0.0274, 0.0585, 0.0341, 0.0283, 0.0270, 0.0554, 0.0277,\n 0.0390, 0.0281, 0.0600, 0.0216, 0.0370, 0.0316, 0.0359, 0.0359, 0.0356,\n 0.0431, 0.0295, 0.0355, 0.0338, 0.0435, 0.0331, 0.0382, 0.0315, 0.0171,\n 0.0349, 0.0252, 0.0425, 0.0471, 0.0193, 0.0293, 0.0415, 0.0506, 0.0392,\n 0.0311, 0.0307, 0.0300, 0.0328]), 'model.layer3.0.bn1.num_batches_tracked': tensor(7160), 'model.layer3.0.conv2.weight': tensor([[[[-0.0362, -0.0428, -0.0388],\n [-0.0234, -0.0094, -0.0330],\n [-0.0293, -0.0453, -0.0448]],\n\n [[-0.0064, -0.0333, -0.0007],\n [-0.0092, -0.0182, -0.0243],\n [-0.0293, -0.0177, -0.0339]],\n\n [[ 0.0126, -0.0007, 0.0257],\n [-0.0225, -0.0042, -0.0151],\n [-0.0125, -0.0221, -0.0082]],\n\n ...,\n\n [[ 0.0360, 0.0640, 0.0380],\n [ 0.0604, 0.0384, 0.0551],\n [ 0.0363, 0.0475, 0.0299]],\n\n [[-0.0064, 0.0220, -0.0188],\n [ 0.0090, -0.0023, -0.0041],\n [-0.0049, 0.0087, 0.0150]],\n\n [[-0.0138, -0.0136, -0.0168],\n [ 0.0243, 0.0167, 0.0334],\n [ 0.0116, 0.0316, 0.0133]]],\n\n\n [[[-0.0155, -0.0058, 0.0017],\n [-0.0039, 0.0024, 0.0021],\n [-0.0129, -0.0172, 0.0259]],\n\n [[-0.0120, -0.0032, -0.0203],\n [ 0.0030, -0.0112, -0.0213],\n [-0.0140, 0.0002, -0.0178]],\n\n [[-0.0192, -0.0191, -0.0117],\n [-0.0041, -0.0124, -0.0171],\n [-0.0132, -0.0031, 0.0013]],\n\n ...,\n\n [[-0.0023, 0.0122, -0.0071],\n [ 0.0097, 0.0028, 0.0094],\n [-0.0042, -0.0056, -0.0104]],\n\n [[ 0.0080, 0.0107, 0.0189],\n [ 0.0109, 0.0099, 0.0306],\n [ 0.0075, 0.0117, 0.0210]],\n\n [[-0.0085, -0.0259, -0.0130],\n [-0.0127, -0.0131, -0.0103],\n [-0.0274, -0.0219, 0.0078]]],\n\n\n [[[-0.0109, -0.0079, 0.0187],\n [ 0.0215, 0.0136, 0.0180],\n [ 0.0065, 0.0051, 0.0122]],\n\n [[-0.0011, -0.0018, -0.0017],\n [-0.0124, -0.0304, -0.0216],\n [-0.0007, -0.0152, -0.0078]],\n\n [[ 0.0044, 0.0086, -0.0018],\n [ 0.0148, -0.0079, -0.0043],\n [ 0.0191, 0.0190, 0.0267]],\n\n ...,\n\n [[-0.0093, 0.0169, 0.0106],\n [-0.0004, 0.0408, 0.0075],\n [-0.0107, 0.0142, 0.0066]],\n\n [[-0.0115, 0.0032, -0.0065],\n [ 0.0169, -0.0049, -0.0028],\n [ 0.0001, 0.0060, -0.0041]],\n\n [[ 0.0003, -0.0041, 0.0183],\n [ 0.0137, 0.0316, 0.0216],\n [ 0.0044, 0.0252, 0.0214]]],\n\n\n ...,\n\n\n [[[ 0.0003, 0.0205, 0.0088],\n [-0.0089, -0.0220, 0.0006],\n [-0.0016, -0.0123, -0.0041]],\n\n [[ 0.0002, 0.0292, 0.0316],\n [ 0.0019, -0.0032, -0.0210],\n [ 0.0196, 0.0136, 0.0155]],\n\n [[-0.0054, -0.0049, -0.0041],\n [-0.0083, -0.0201, -0.0202],\n [ 0.0040, 0.0083, 0.0141]],\n\n ...,\n\n [[-0.0142, 0.0092, -0.0040],\n [ 0.0047, -0.0069, -0.0162],\n [-0.0032, 0.0095, 0.0235]],\n\n [[ 0.0202, -0.0012, 0.0024],\n [-0.0112, -0.0289, -0.0037],\n [ 0.0288, 0.0155, -0.0018]],\n\n [[-0.0013, -0.0107, 0.0048],\n [-0.0139, -0.0069, 0.0087],\n [ 0.0032, -0.0002, -0.0111]]],\n\n\n [[[ 0.0187, -0.0002, -0.0043],\n [ 0.0099, 0.0041, -0.0008],\n [ 0.0267, 0.0025, 0.0128]],\n\n [[-0.0105, -0.0242, -0.0142],\n [-0.0172, -0.0128, -0.0229],\n [-0.0139, -0.0231, -0.0225]],\n\n [[ 0.0200, 0.0162, 0.0218],\n [ 0.0222, 0.0122, 0.0104],\n [ 0.0062, -0.0106, -0.0147]],\n\n ...,\n\n [[-0.0099, 0.0062, 0.0045],\n [-0.0172, 0.0065, 0.0053],\n [-0.0006, 0.0093, 0.0172]],\n\n [[-0.0072, -0.0187, -0.0058],\n [ 0.0102, 0.0158, 0.0074],\n [-0.0018, 0.0200, 0.0020]],\n\n [[-0.0198, -0.0333, -0.0205],\n [-0.0112, 0.0064, -0.0164],\n [ 0.0106, 0.0194, 0.0095]]],\n\n\n [[[ 0.0081, -0.0005, -0.0009],\n [ 0.0096, -0.0009, -0.0225],\n [ 0.0288, -0.0024, -0.0136]],\n\n [[-0.0017, 0.0109, 0.0056],\n [ 0.0041, 0.0090, 0.0155],\n [-0.0028, 0.0095, 0.0086]],\n\n [[-0.0013, 0.0076, -0.0186],\n [ 0.0076, -0.0059, 0.0041],\n [-0.0065, 0.0015, 0.0100]],\n\n ...,\n\n [[ 0.0001, 0.0066, 0.0227],\n [-0.0009, 0.0138, 0.0177],\n [-0.0126, 0.0089, 0.0105]],\n\n [[ 0.0101, -0.0026, -0.0030],\n [ 0.0054, 0.0092, 0.0201],\n [ 0.0051, -0.0056, 0.0188]],\n\n [[-0.0121, 0.0056, 0.0290],\n [ 0.0041, 0.0003, 0.0250],\n [-0.0322, 0.0012, 0.0377]]]]), 'model.layer3.0.bn2.weight': tensor([0.1795, 0.2359, 0.1783, 0.1530, 0.1626, 0.1457, 0.1596, 0.1399, 0.1746,\n 0.1899, 0.1673, 0.2350, 0.1572, 0.1790, 0.1825, 0.1699, 0.1622, 0.1669,\n 0.1736, 0.1691, 0.1571, 0.1717, 0.1936, 0.1549, 0.2260, 0.1863, 0.2294,\n 0.1979, 0.1674, 0.1785, 0.1441, 0.1575, 0.1771, 0.1547, 0.1390, 0.2216,\n 0.1768, 0.2219, 0.1776, 0.1830, 0.1440, 0.2837, 0.2129, 0.1859, 0.1651,\n 0.1787, 0.1412, 0.1648, 0.1422, 0.2333, 0.1489, 0.2219, 0.2017, 0.1564,\n 0.1771, 0.1895, 0.2377, 0.1785, 0.1686, 0.1755, 0.1863, 0.2004, 0.1505,\n 0.1397, 0.2049, 0.1522, 0.1403, 0.1204, 0.1791, 0.2168, 0.1560, 0.2108,\n 0.1334, 0.1516, 0.1700, 0.2016, 0.1881, 0.1892, 0.1506, 0.1975, 0.1545,\n 0.2234, 0.1806, 0.1477, 0.1978, 0.3322, 0.2311, 0.1818, 0.1352, 0.1850,\n 0.2386, 0.1733, 0.1451, 0.1979, 0.1919, 0.1672, 0.1952, 0.2191, 0.2005,\n 0.1679, 0.2450, 0.1871, 0.2063, 0.1424, 0.1779, 0.2178, 0.1668, 0.1487,\n 0.1901, 0.1953, 0.2303, 0.1828, 0.2206, 0.1846, 0.1731, 0.2006, 0.1811,\n 0.2097, 0.1611, 0.1648, 0.1792, 0.1940, 0.1737, 0.1690, 0.1630, 0.1541,\n 0.2076, 0.2004, 0.1560, 0.1344, 0.1976, 0.1950, 0.2449, 0.1624, 0.2336,\n 0.2279, 0.1990, 0.1592, 0.1901, 0.1567, 0.1346, 0.1680, 0.1830, 0.1866,\n 0.1516, 0.1389, 0.1373, 0.1854, 0.2219, 0.1700, 0.1781, 0.1674, 0.1669,\n 0.1957, 0.1764, 0.1613, 0.1974, 0.1880, 0.1590, 0.2127, 0.1751, 0.1374,\n 0.1475, 0.1495, 0.1320, 0.1997, 0.1622, 0.2120, 0.1788, 0.1899, 0.1456,\n 0.1677, 0.2135, 0.1791, 0.1492, 0.2135, 0.1401, 0.1898, 0.1642, 0.1993,\n 0.1426, 0.1500, 0.1712, 0.1912, 0.1641, 0.1765, 0.1991, 0.1777, 0.1675,\n 0.1509, 0.1744, 0.2088, 0.1604, 0.1467, 0.1866, 0.1545, 0.1723, 0.2098,\n 0.1693, 0.2651, 0.1650, 0.1549, 0.1641, 0.1396, 0.1839, 0.2549, 0.2004,\n 0.1568, 0.1996, 0.1800, 0.1959, 0.2078, 0.2310, 0.1774, 0.1902, 0.2490,\n 0.1966, 0.1310, 0.1527, 0.1900, 0.1578, 0.1725, 0.2120, 0.1989, 0.2119,\n 0.2069, 0.1675, 0.2048, 0.1812, 0.1756, 0.1561, 0.2450, 0.2099, 0.2276,\n 0.2035, 0.1369, 0.1764, 0.1900, 0.1934, 0.1402, 0.2113, 0.1812, 0.2204,\n 0.1692, 0.1737, 0.1975, 0.1957, 0.1776, 0.1909, 0.1883, 0.1801, 0.1873,\n 0.2149, 0.2144, 0.1486, 0.2094]), 'model.layer3.0.bn2.bias': tensor([ 0.0829, -0.0521, -0.0067, 0.1445, -0.0289, 0.0900, 0.0128, 0.1356,\n 0.0219, 0.0389, 0.1814, -0.0834, 0.0878, -0.0630, -0.0311, 0.0571,\n 0.0210, -0.0019, 0.1635, 0.0658, 0.2627, 0.0868, 0.0009, 0.1193,\n -0.0713, -0.0722, -0.0082, -0.0356, 0.0181, 0.1100, 0.2302, 0.1265,\n 0.0562, 0.1822, 0.1750, -0.0255, -0.0101, -0.0565, -0.0098, -0.0109,\n 0.1158, -0.1898, -0.0037, -0.0179, 0.0263, 0.0645, 0.1927, 0.0220,\n 0.1792, -0.0286, 0.0972, 0.0759, -0.0757, 0.1176, 0.0073, -0.0293,\n -0.0467, 0.0316, -0.0230, 0.0099, -0.0070, -0.0263, 0.1248, 0.1403,\n 0.0052, 0.1423, 0.1815, 0.1575, 0.0437, -0.0328, 0.0777, 0.1537,\n 0.1640, 0.0499, -0.0335, -0.0672, 0.0410, 0.0007, 0.0644, -0.0174,\n 0.0672, 0.0421, 0.0266, 0.1302, -0.0263, -0.1209, 0.0741, -0.0379,\n 0.1604, -0.1115, -0.0241, 0.0589, 0.1078, 0.0245, 0.0268, -0.0348,\n 0.0349, 0.0266, -0.0570, -0.0147, -0.0941, 0.0243, -0.0559, 0.1157,\n -0.0802, 0.0526, -0.0262, 0.0389, 0.0330, 0.0289, -0.1128, -0.0226,\n -0.0279, -0.1038, 0.1415, -0.1150, -0.0267, -0.0229, 0.0241, 0.0569,\n 0.0320, -0.0203, 0.0290, 0.0620, 0.1271, 0.0785, -0.0538, -0.0756,\n 0.0446, 0.1532, 0.1014, 0.1368, -0.0260, 0.0558, -0.0336, -0.0819,\n -0.0122, 0.0678, -0.0131, 0.0773, 0.1114, -0.0123, -0.0075, 0.0419,\n 0.1026, 0.0816, 0.0425, -0.0077, -0.0662, 0.0287, -0.0411, 0.0450,\n -0.0009, 0.1063, -0.0039, 0.0961, -0.0679, -0.0078, 0.0122, -0.0514,\n -0.0025, 0.1212, 0.1302, 0.2282, 0.1011, -0.0318, 0.1348, -0.0449,\n 0.0550, -0.0312, 0.1168, 0.0672, -0.0012, 0.0028, 0.1958, -0.0113,\n 0.1668, 0.0357, 0.0460, 0.0601, 0.1985, 0.1589, -0.0456, -0.0074,\n 0.0553, 0.0870, -0.0361, 0.1295, 0.0041, 0.2427, 0.1360, -0.0549,\n 0.1174, 0.1306, -0.0811, 0.0423, 0.0241, -0.0530, 0.1195, -0.1562,\n 0.1606, 0.0463, 0.0886, 0.2315, -0.0184, -0.0254, -0.0227, -0.0302,\n -0.0372, -0.0859, 0.0065, -0.0780, -0.0368, 0.1297, 0.0952, -0.0675,\n 0.0099, 0.1729, 0.1287, -0.0466, 0.0694, -0.0452, -0.0901, -0.0487,\n 0.0349, 0.0531, 0.0806, -0.0018, 0.1130, 0.0620, 0.1055, -0.0166,\n -0.0299, -0.0880, -0.0307, 0.1609, -0.0157, 0.1340, 0.0082, 0.1139,\n -0.0407, 0.0667, 0.0074, 0.0627, -0.0375, -0.0992, -0.0029, -0.0778,\n -0.0093, -0.0088, -0.0424, -0.0013, 0.0540, -0.1318, 0.0123, -0.0455]), 'model.layer3.0.bn2.running_mean': tensor([ 0.0188, -0.1004, -0.0198, -0.1182, -0.1067, -0.0591, -0.0861, 0.0758,\n 0.0195, -0.0203, 0.1951, -0.1578, -0.0383, 0.1024, 0.0163, 0.0159,\n 0.0140, -0.0899, 0.0080, -0.1499, 0.0122, -0.2265, -0.0809, 0.0691,\n -0.2222, -0.1120, 0.0259, -0.0208, -0.0717, 0.1638, -0.0570, 0.0389,\n -0.0350, -0.1431, -0.0336, -0.0143, 0.0109, 0.0090, -0.0693, -0.0017,\n -0.1101, -0.2356, -0.1300, -0.0759, -0.0120, 0.0595, -0.0176, 0.0055,\n 0.0256, -0.2232, -0.0656, 0.0097, 0.0372, -0.1418, 0.2196, 0.0310,\n -0.1938, 0.0105, -0.0389, -0.0060, -0.0901, -0.1167, -0.0926, -0.1250,\n -0.0761, 0.1197, -0.0978, 0.1981, 0.0627, -0.1268, -0.0556, -0.0030,\n 0.0327, 0.1486, -0.0327, -0.1637, -0.0526, -0.0914, 0.0644, -0.0490,\n 0.0739, -0.0948, -0.1158, 0.0337, -0.0474, -0.1430, -0.0375, -0.1220,\n 0.0831, -0.0742, -0.2497, -0.0138, 0.0473, 0.0119, -0.0691, -0.0859,\n -0.0003, -0.0879, 0.0422, -0.1182, -0.0677, 0.0178, 0.0260, -0.0486,\n 0.0305, -0.0450, -0.0682, -0.0010, -0.2236, -0.0816, -0.1865, -0.0929,\n 0.0149, -0.0394, -0.0070, -0.0083, 0.0729, -0.0275, -0.1048, -0.1112,\n -0.1058, 0.0401, -0.0318, -0.0610, 0.0964, 0.0477, -0.1051, 0.0114,\n -0.0806, -0.1240, -0.1735, 0.0242, -0.0390, -0.1172, -0.2743, -0.1063,\n -0.0134, -0.0609, -0.0955, 0.0021, -0.0334, -0.0699, 0.0460, -0.0603,\n 0.1008, 0.0104, 0.0187, -0.2084, -0.0527, 0.0681, -0.0609, -0.0794,\n 0.0677, 0.0772, -0.2234, 0.0326, -0.0927, -0.0862, -0.1039, -0.1041,\n 0.1417, -0.1143, -0.0399, -0.0448, 0.0069, 0.0603, -0.2450, -0.1102,\n -0.1366, -0.0417, 0.2057, -0.1104, -0.1715, -0.0482, 0.0143, -0.1728,\n -0.0571, -0.0624, -0.1533, -0.1767, -0.0731, 0.1102, -0.0421, -0.0976,\n -0.0492, 0.0339, -0.0653, 0.0988, 0.1555, -0.0171, -0.0163, -0.0477,\n 0.0071, -0.1300, -0.0980, 0.1510, -0.0981, -0.1549, 0.0042, -0.2458,\n -0.0637, 0.0383, -0.0590, 0.0453, 0.0058, 0.0619, 0.0405, 0.0342,\n -0.0847, -0.0913, -0.0465, -0.1196, 0.0591, -0.0070, -0.0043, -0.2548,\n -0.0879, 0.0080, 0.1089, -0.0676, -0.0321, -0.0818, -0.1084, 0.0318,\n -0.1550, -0.1985, -0.0214, -0.0591, 0.0241, -0.0488, -0.0549, -0.0894,\n 0.0917, -0.0732, -0.0904, 0.0343, -0.0245, 0.0446, -0.1021, -0.0078,\n 0.1176, -0.0457, 0.0326, -0.1519, -0.0397, -0.0531, -0.1131, -0.0694,\n -0.0369, -0.0883, -0.0049, 0.0030, 0.0279, -0.1840, 0.0276, 0.0295]), 'model.layer3.0.bn2.running_var': tensor([0.0227, 0.0409, 0.0288, 0.0252, 0.0181, 0.0416, 0.0192, 0.0202, 0.0278,\n 0.0269, 0.0297, 0.0372, 0.0316, 0.0210, 0.0247, 0.0240, 0.0192, 0.0213,\n 0.0271, 0.0369, 0.0277, 0.0241, 0.0188, 0.0247, 0.0235, 0.0261, 0.0287,\n 0.0250, 0.0349, 0.0258, 0.0183, 0.0251, 0.0312, 0.0269, 0.0228, 0.0379,\n 0.0290, 0.0244, 0.0282, 0.0249, 0.0257, 0.0458, 0.0386, 0.0232, 0.0223,\n 0.0319, 0.0208, 0.0249, 0.0317, 0.0347, 0.0284, 0.0280, 0.0290, 0.0280,\n 0.0275, 0.0284, 0.0294, 0.0294, 0.0204, 0.0253, 0.0239, 0.0295, 0.0259,\n 0.0293, 0.0337, 0.0204, 0.0200, 0.0189, 0.0280, 0.0262, 0.0224, 0.0320,\n 0.0264, 0.0199, 0.0177, 0.0264, 0.0266, 0.0290, 0.0197, 0.0273, 0.0242,\n 0.0312, 0.0257, 0.0245, 0.0285, 0.0331, 0.0466, 0.0234, 0.0212, 0.0195,\n 0.0230, 0.0238, 0.0300, 0.0280, 0.0204, 0.0184, 0.0284, 0.0563, 0.0189,\n 0.0233, 0.0329, 0.0237, 0.0293, 0.0362, 0.0181, 0.0294, 0.0179, 0.0231,\n 0.0262, 0.0343, 0.0244, 0.0261, 0.0435, 0.0226, 0.0233, 0.0241, 0.0216,\n 0.0346, 0.0270, 0.0225, 0.0286, 0.0325, 0.0219, 0.0354, 0.0352, 0.0253,\n 0.0167, 0.0285, 0.0156, 0.0242, 0.0310, 0.0418, 0.0514, 0.0237, 0.0521,\n 0.0208, 0.0311, 0.0201, 0.0243, 0.0247, 0.0355, 0.0288, 0.0298, 0.0250,\n 0.0328, 0.0298, 0.0219, 0.0211, 0.0223, 0.0300, 0.0209, 0.0254, 0.0306,\n 0.0359, 0.0286, 0.0183, 0.0235, 0.0194, 0.0338, 0.0321, 0.0295, 0.0221,\n 0.0176, 0.0296, 0.0195, 0.0181, 0.0208, 0.0281, 0.0309, 0.0185, 0.0210,\n 0.0195, 0.0199, 0.0196, 0.0234, 0.0358, 0.0245, 0.0332, 0.0163, 0.0504,\n 0.0219, 0.0194, 0.0224, 0.0210, 0.0248, 0.0302, 0.0279, 0.0402, 0.0286,\n 0.0220, 0.0335, 0.0267, 0.0388, 0.0255, 0.0177, 0.0163, 0.0174, 0.0224,\n 0.0607, 0.0319, 0.0209, 0.0269, 0.0349, 0.0259, 0.0219, 0.0375, 0.0216,\n 0.0161, 0.0201, 0.0226, 0.0286, 0.0349, 0.0392, 0.0325, 0.0300, 0.0298,\n 0.0213, 0.0233, 0.0268, 0.0213, 0.0189, 0.0174, 0.0319, 0.0226, 0.0265,\n 0.0292, 0.0248, 0.0223, 0.0382, 0.0190, 0.0246, 0.0621, 0.0259, 0.0357,\n 0.0249, 0.0222, 0.0189, 0.0409, 0.0227, 0.0177, 0.0349, 0.0300, 0.0245,\n 0.0254, 0.0227, 0.0190, 0.0193, 0.0269, 0.0292, 0.0275, 0.0241, 0.0182,\n 0.0302, 0.0197, 0.0211, 0.0249]), 'model.layer3.0.bn2.num_batches_tracked': tensor(7160), 'model.layer3.0.conv3.weight': tensor([[[[-0.0067]],\n\n [[ 0.0222]],\n\n [[ 0.0465]],\n\n ...,\n\n [[-0.0096]],\n\n [[-0.0166]],\n\n [[-0.0234]]],\n\n\n [[[ 0.0090]],\n\n [[-0.0042]],\n\n [[ 0.0029]],\n\n ...,\n\n [[-0.0076]],\n\n [[-0.0018]],\n\n [[ 0.0002]]],\n\n\n [[[-0.0009]],\n\n [[-0.0044]],\n\n [[-0.0096]],\n\n ...,\n\n [[ 0.0033]],\n\n [[-0.0153]],\n\n [[ 0.0316]]],\n\n\n ...,\n\n\n [[[-0.0124]],\n\n [[-0.0074]],\n\n [[-0.0104]],\n\n ...,\n\n [[-0.0159]],\n\n [[-0.0247]],\n\n [[ 0.0269]]],\n\n\n [[[ 0.0311]],\n\n [[-0.0027]],\n\n [[-0.0054]],\n\n ...,\n\n [[-0.0101]],\n\n [[-0.0076]],\n\n [[-0.0205]]],\n\n\n [[[-0.0251]],\n\n [[-0.0022]],\n\n [[-0.0313]],\n\n ...,\n\n [[ 0.0019]],\n\n [[ 0.0009]],\n\n [[-0.0188]]]]), 'model.layer3.0.bn3.weight': tensor([0.1668, 0.1144, 0.0920, ..., 0.1058, 0.1779, 0.1454]), 'model.layer3.0.bn3.bias': tensor([-0.0111, -0.0266, -0.0258, ..., 0.0115, -0.0056, -0.0002]), 'model.layer3.0.bn3.running_mean': tensor([-0.0045, -0.0372, 0.0016, ..., -0.0550, -0.0258, 0.0240]), 'model.layer3.0.bn3.running_var': tensor([0.0047, 0.0022, 0.0015, ..., 0.0025, 0.0058, 0.0055]), 'model.layer3.0.bn3.num_batches_tracked': tensor(7160), 'model.layer3.0.downsample.0.weight': tensor([[[[ 0.0326]],\n\n [[ 0.0161]],\n\n [[ 0.0053]],\n\n ...,\n\n [[ 0.0163]],\n\n [[ 0.0358]],\n\n [[-0.0270]]],\n\n\n [[[-0.0074]],\n\n [[-0.0101]],\n\n [[-0.0099]],\n\n ...,\n\n [[ 0.0112]],\n\n [[-0.0248]],\n\n [[-0.0012]]],\n\n\n [[[ 0.0342]],\n\n [[-0.0200]],\n\n [[ 0.0013]],\n\n ...,\n\n [[-0.0071]],\n\n [[ 0.0053]],\n\n [[ 0.0112]]],\n\n\n ...,\n\n\n [[[-0.0041]],\n\n [[-0.0074]],\n\n [[-0.0054]],\n\n ...,\n\n [[-0.0081]],\n\n [[ 0.0229]],\n\n [[ 0.0485]]],\n\n\n [[[ 0.0278]],\n\n [[-0.0117]],\n\n [[-0.0162]],\n\n ...,\n\n [[ 0.0003]],\n\n [[ 0.0258]],\n\n [[ 0.0669]]],\n\n\n [[[-0.0405]],\n\n [[-0.0118]],\n\n [[ 0.0453]],\n\n ...,\n\n [[ 0.0040]],\n\n [[ 0.0086]],\n\n [[ 0.0175]]]]), 'model.layer3.0.downsample.1.weight': tensor([0.1150, 0.1030, 0.0686, ..., 0.0953, 0.0828, 0.1845]), 'model.layer3.0.downsample.1.bias': tensor([-0.0111, -0.0266, -0.0258, ..., 0.0115, -0.0056, -0.0002]), 'model.layer3.0.downsample.1.running_mean': tensor([ 0.0821, 0.0200, 0.0145, ..., -0.1365, 0.0340, 0.0695]), 'model.layer3.0.downsample.1.running_var': tensor([0.0104, 0.0070, 0.0043, ..., 0.0060, 0.0080, 0.0242]), 'model.layer3.0.downsample.1.num_batches_tracked': tensor(7160), 'model.layer3.1.conv1.weight': tensor([[[[ 0.0146]],\n\n [[-0.0106]],\n\n [[ 0.0049]],\n\n ...,\n\n [[ 0.0169]],\n\n [[-0.0047]],\n\n [[ 0.0140]]],\n\n\n [[[-0.0001]],\n\n [[-0.0343]],\n\n [[-0.0004]],\n\n ...,\n\n [[-0.0056]],\n\n [[-0.0139]],\n\n [[-0.0121]]],\n\n\n [[[-0.0010]],\n\n [[ 0.0181]],\n\n [[-0.0066]],\n\n ...,\n\n [[-0.0197]],\n\n [[ 0.0088]],\n\n [[-0.0162]]],\n\n\n ...,\n\n\n [[[-0.0068]],\n\n [[-0.0136]],\n\n [[-0.0109]],\n\n ...,\n\n [[ 0.0179]],\n\n [[-0.0016]],\n\n [[ 0.0034]]],\n\n\n [[[-0.0062]],\n\n [[-0.0058]],\n\n [[-0.0021]],\n\n ...,\n\n [[ 0.0050]],\n\n [[-0.0131]],\n\n [[ 0.0287]]],\n\n\n [[[ 0.0030]],\n\n [[-0.0005]],\n\n [[ 0.0017]],\n\n ...,\n\n [[-0.0115]],\n\n [[-0.0076]],\n\n [[ 0.0077]]]]), 'model.layer3.1.bn1.weight': tensor([0.1181, 0.1111, 0.1092, 0.1135, 0.1391, 0.1201, 0.1467, 0.1700, 0.1538,\n 0.0894, 0.1607, 0.1531, 0.1460, 0.1482, 0.1255, 0.1650, 0.2247, 0.1401,\n 0.1722, 0.1375, 0.1425, 0.1784, 0.1391, 0.1473, 0.1298, 0.1384, 0.0979,\n 0.1190, 0.1908, 0.1318, 0.1129, 0.1774, 0.1215, 0.1314, 0.1799, 0.1726,\n 0.1500, 0.1440, 0.1640, 0.1813, 0.1791, 0.1895, 0.1259, 0.1785, 0.1734,\n 0.1688, 0.1527, 0.1291, 0.1370, 0.1440, 0.1496, 0.1614, 0.1434, 0.1283,\n 0.1319, 0.1666, 0.1982, 0.1657, 0.1573, 0.1300, 0.2242, 0.2130, 0.1849,\n 0.1181, 0.1342, 0.1649, 0.1211, 0.1622, 0.1197, 0.1697, 0.1275, 0.1369,\n 0.1806, 0.1567, 0.1321, 0.1232, 0.1939, 0.1599, 0.1757, 0.2032, 0.1641,\n 0.1307, 0.2498, 0.1615, 0.1867, 0.1992, 0.1491, 0.1622, 0.1259, 0.1684,\n 0.2284, 0.1624, 0.1395, 0.1612, 0.1962, 0.1782, 0.1009, 0.1734, 0.1624,\n 0.1863, 0.1432, 0.1470, 0.1400, 0.2203, 0.1221, 0.1130, 0.1374, 0.2009,\n 0.2238, 0.1399, 0.1733, 0.2263, 0.1306, 0.1827, 0.1392, 0.1919, 0.1567,\n 0.1972, 0.1462, 0.1606, 0.1293, 0.1636, 0.1409, 0.1529, 0.1436, 0.1674,\n 0.1682, 0.1706, 0.1209, 0.1906, 0.1605, 0.1478, 0.1503, 0.1278, 0.1705,\n 0.1346, 0.1782, 0.1411, 0.1510, 0.1574, 0.1985, 0.1478, 0.1247, 0.1461,\n 0.1581, 0.1203, 0.1907, 0.1076, 0.1438, 0.1706, 0.1770, 0.1757, 0.1870,\n 0.1271, 0.1232, 0.1903, 0.1927, 0.1507, 0.1567, 0.1215, 0.1796, 0.1507,\n 0.1842, 0.1863, 0.1703, 0.1551, 0.1757, 0.1458, 0.2083, 0.1996, 0.1632,\n 0.2238, 0.1466, 0.1513, 0.1501, 0.1610, 0.1181, 0.1351, 0.1501, 0.1409,\n 0.1388, 0.1522, 0.1603, 0.1185, 0.1091, 0.1361, 0.1925, 0.1645, 0.1792,\n 0.1340, 0.1610, 0.1799, 0.1685, 0.1335, 0.1124, 0.1123, 0.1443, 0.1710,\n 0.1547, 0.1436, 0.1659, 0.1663, 0.1397, 0.1515, 0.3063, 0.1385, 0.1259,\n 0.1785, 0.1172, 0.1449, 0.1203, 0.1838, 0.1388, 0.1217, 0.1906, 0.1870,\n 0.1539, 0.1536, 0.1751, 0.0980, 0.1660, 0.1524, 0.1997, 0.1659, 0.1519,\n 0.2070, 0.1152, 0.1429, 0.1556, 0.1373, 0.1647, 0.1452, 0.1566, 0.1466,\n 0.1996, 0.1884, 0.1553, 0.1545, 0.1272, 0.1221, 0.1298, 0.1443, 0.1559,\n 0.1802, 0.1287, 0.1233, 0.1653, 0.2099, 0.1436, 0.1731, 0.1224, 0.1679,\n 0.1642, 0.1592, 0.1419, 0.1519]), 'model.layer3.1.bn1.bias': tensor([ 1.2477e-01, 9.0379e-02, 4.7476e-02, 3.5605e-02, -2.1310e-02,\n 3.8097e-02, -9.5971e-03, -2.4738e-02, -4.7894e-02, 1.2564e-01,\n 2.9976e-02, -1.4310e-01, 9.6276e-03, -3.9079e-02, 1.3874e-02,\n -4.3575e-02, -1.1567e-01, -1.0819e-02, -2.6815e-02, -1.0325e-02,\n -3.8853e-02, -7.4345e-02, 6.0770e-02, 1.0677e-02, 7.0770e-02,\n -3.0363e-02, 1.2625e-01, 3.5211e-02, -9.6358e-02, 7.4453e-02,\n 3.4420e-03, -1.7757e-02, 1.8873e-02, 5.8177e-02, -4.8830e-02,\n -7.0872e-03, -1.0112e-02, 9.2423e-03, -3.3701e-03, -2.4705e-02,\n 2.9319e-04, -1.3221e-02, 3.9207e-02, -6.6112e-02, -8.4611e-02,\n -6.8526e-02, 2.7495e-02, 6.0598e-02, 7.0951e-03, 7.4694e-02,\n -1.1805e-02, -1.3860e-03, 1.5583e-02, 7.9448e-02, -1.1446e-02,\n -1.2641e-02, -9.7128e-02, -4.3370e-02, 3.3182e-02, 1.8584e-02,\n -9.9564e-02, -1.2967e-01, -1.3595e-02, 8.3781e-03, 2.4632e-04,\n -1.0223e-01, 1.6432e-02, 3.2804e-02, -2.9343e-02, -5.1382e-02,\n 1.9189e-02, 1.2632e-02, -1.8794e-02, -6.9781e-02, -2.6150e-02,\n -1.1282e-02, -1.2784e-01, -7.3852e-02, -8.2515e-02, -1.0813e-01,\n -3.2660e-02, -3.9814e-03, -1.0201e-01, -4.9451e-03, -3.6636e-02,\n -1.0405e-01, -1.4435e-02, -9.4155e-02, -1.1126e-02, 3.1873e-02,\n -1.0590e-01, -4.9556e-02, -2.4913e-02, -7.9982e-02, -4.3768e-02,\n -6.3941e-02, 9.2711e-02, -9.6670e-02, -7.0805e-02, -1.0750e-01,\n 6.1020e-02, 2.5659e-03, -5.4657e-02, -1.4643e-01, 4.5769e-02,\n 5.1020e-02, -4.4553e-03, -1.6280e-02, -1.2731e-01, 6.4696e-03,\n -4.8715e-02, -8.1562e-02, 7.9984e-03, -3.7544e-02, -1.6608e-02,\n -8.8018e-02, 7.2094e-02, -1.0055e-01, -2.0848e-03, -2.2095e-02,\n 3.2706e-02, -3.6574e-02, -2.3093e-02, -4.4401e-02, 3.7247e-02,\n 1.0731e-02, -1.0179e-02, -3.1460e-02, 3.7255e-02, -9.4197e-02,\n -3.8552e-02, -1.3879e-04, -2.3723e-03, 2.9293e-02, -2.7839e-03,\n 2.3633e-02, -5.2422e-02, 3.7305e-02, -2.1002e-02, 5.6986e-03,\n -3.8184e-02, 3.2434e-02, 6.7573e-03, 3.9374e-02, -2.4150e-02,\n 1.9009e-01, -6.1619e-02, 5.3994e-02, 6.3960e-02, -3.6135e-02,\n -1.2017e-02, -5.7252e-02, -1.4143e-01, 5.3078e-02, 8.4490e-02,\n 6.4830e-03, -7.0987e-02, -1.6369e-03, -3.5278e-02, 4.5124e-02,\n -1.1461e-01, 9.4125e-04, -3.1322e-02, -7.0355e-02, -5.4468e-02,\n -1.0861e-02, -6.5011e-02, -2.6068e-02, -1.2995e-01, -6.2051e-02,\n 1.0693e-02, -1.2949e-01, -5.3735e-02, -1.9248e-02, 4.3665e-03,\n 1.6765e-02, 6.0936e-02, 1.4359e-01, 2.3380e-02, -1.2193e-02,\n 1.1672e-02, -6.1524e-02, 2.8713e-02, 7.7973e-02, 3.0845e-02,\n -8.3428e-03, -7.1111e-02, -5.2926e-02, -1.1416e-01, 4.3397e-02,\n -4.9602e-02, -4.3490e-02, -4.0343e-02, 3.8287e-02, 5.3008e-02,\n 6.1444e-02, 4.5144e-02, -4.5972e-02, 2.6272e-02, -8.4462e-02,\n -1.5775e-02, -5.3823e-02, 7.5367e-02, 2.1618e-02, -1.6296e-01,\n 5.2209e-02, 7.7785e-02, -4.8165e-03, 1.0814e-01, 4.9651e-02,\n 5.9534e-02, -1.2853e-01, 1.8728e-02, 1.4561e-02, -5.8825e-02,\n -7.9962e-02, -3.3144e-02, -3.8100e-02, -4.8130e-02, 1.6949e-01,\n -6.8020e-02, -4.5457e-02, -4.5146e-02, -4.3297e-02, 4.2796e-02,\n -1.0812e-01, 3.8301e-02, -2.4852e-02, -4.2482e-02, -9.0035e-03,\n -6.0175e-02, -2.1729e-02, 8.2503e-03, -1.8657e-02, -1.1472e-01,\n -1.0627e-01, -5.6636e-02, -3.0586e-02, -1.1102e-03, 9.3588e-02,\n 3.7927e-02, 5.7885e-03, -5.9712e-02, -1.3086e-02, 8.3599e-03,\n 1.4519e-02, 5.0918e-03, -1.1307e-01, -2.0293e-02, -4.5010e-02,\n 6.2975e-02, -4.8579e-02, -5.8286e-02, -5.5335e-02, 1.2247e-02,\n 4.0836e-03]), 'model.layer3.1.bn1.running_mean': tensor([-1.5440e-01, -1.8807e-01, -1.0605e-01, -4.8685e-02, -1.3989e-01,\n -6.1058e-02, -1.9306e-01, 7.0026e-02, -9.8406e-02, -2.6905e-01,\n -7.2063e-02, -1.5654e-01, -1.9535e-01, -8.6402e-02, -7.6519e-02,\n 6.7864e-02, -2.2697e-01, -5.2870e-02, 3.8258e-02, -3.9445e-02,\n -2.3417e-01, -4.6506e-02, -5.7560e-02, -2.4568e-02, 5.5304e-01,\n -3.5476e-02, 1.6028e-02, -5.9498e-04, 1.0475e-02, -5.1251e-02,\n -1.5507e-01, -4.5925e-03, -6.7461e-02, -8.5999e-02, 1.0186e-01,\n -3.1177e-02, -2.5520e-02, -1.6977e-02, -3.5810e-02, 6.8676e-02,\n -7.8797e-02, -7.5943e-02, -1.8104e-01, 2.6389e-01, 7.9854e-02,\n -7.5956e-02, -3.6472e-02, 1.2320e-01, 1.7784e-01, -1.2844e-01,\n -7.6120e-02, -9.7535e-02, 1.6814e-02, -1.7937e-01, 7.7788e-02,\n -7.8034e-02, -1.4748e-01, -1.3856e-01, -7.1998e-02, 4.5994e-02,\n -1.2065e-01, -3.8930e-02, -4.3978e-01, -3.2313e-01, -1.5484e-01,\n -1.1033e-01, -2.1855e-02, -1.1619e-02, -2.3753e-01, -5.3309e-02,\n 3.0074e-02, -1.6548e-02, -1.5969e-01, -1.5708e-05, -3.7479e-02,\n -7.2788e-02, -1.3588e-01, -2.8835e-02, -1.2843e-01, 8.4163e-02,\n -9.5331e-02, 8.5773e-02, -2.2488e-01, -1.5894e-01, -6.7546e-02,\n -1.1078e-01, 3.3550e-02, -6.4857e-02, -1.2435e-01, -6.7883e-02,\n -4.2583e-02, 9.1524e-03, -2.8782e-02, -6.7465e-02, -6.7643e-02,\n -1.5639e-02, 2.0372e-02, -3.1936e-02, 2.0348e-02, -2.6939e-01,\n -3.3756e-02, -3.5434e-02, 5.8263e-02, 6.8712e-02, -1.0368e-01,\n -2.5502e-03, -4.8477e-01, -6.3414e-02, -5.8054e-02, 5.3321e-02,\n 2.4119e-01, -4.7558e-02, -3.6627e-02, -3.1943e-02, -9.4505e-02,\n -1.1210e-01, 7.9152e-02, -1.0601e-01, 2.5304e-02, -1.0121e-01,\n -5.1700e-02, -1.0120e-01, -2.2131e-01, 2.1847e-01, -5.3846e-02,\n -6.4646e-02, -3.9831e-02, -9.5727e-02, -2.2223e-01, -9.0852e-02,\n 2.9367e-02, -2.4363e-01, -2.7785e-02, 8.3490e-02, -1.8594e-01,\n 1.4642e-01, -2.5415e-01, -1.5756e-01, -1.3463e-01, -2.6757e-02,\n -1.1059e-01, -1.7632e-01, -1.0650e-01, -5.8628e-03, 1.4167e-01,\n -8.6912e-01, -6.2778e-02, -7.6209e-02, -4.1650e-01, -7.5511e-02,\n -4.7857e-02, -1.4955e-02, -1.5809e-01, 6.0209e-02, 3.0756e-02,\n -2.8646e-02, 7.3404e-03, -9.8062e-02, -2.0692e-02, -3.1255e-01,\n -2.3693e-02, -1.3153e-01, -2.1554e-01, 8.3598e-02, -9.9536e-03,\n 9.7380e-03, 5.2469e-02, -2.6219e-01, 5.3548e-02, 2.0394e-01,\n -9.7504e-03, -7.2595e-02, 2.2675e-01, -5.8423e-02, -8.6632e-02,\n -2.0114e-02, 1.1208e-01, 1.2046e-01, -3.4267e-02, -3.2992e-02,\n -1.3091e-02, -5.5556e-02, -3.6398e-02, -1.9889e-01, -6.1390e-02,\n 2.0617e-01, -8.8920e-02, 2.0429e-02, -4.8516e-02, -6.6250e-02,\n 7.3096e-02, 5.6853e-02, -1.1782e-02, 7.5434e-02, -1.8271e-01,\n -1.5887e-01, 1.1028e-01, -1.1503e-01, 6.9469e-02, 1.5614e-01,\n 4.2921e-02, 5.6486e-02, -1.6162e-01, 9.6869e-02, 1.9038e-01,\n -2.0336e-01, 1.5405e-02, -5.2644e-02, -9.8064e-02, -4.2672e-02,\n 5.6233e-02, 1.0709e-01, 7.5015e-02, -1.2760e-01, 1.8332e-01,\n -7.6127e-03, -2.0775e-02, -6.1970e-02, 6.2894e-02, -4.7301e-01,\n 1.6421e-03, -9.5084e-02, 1.2345e-01, -3.2540e-02, 2.8587e-02,\n 2.0706e-01, -7.0143e-01, -1.0035e-01, 6.1342e-02, 2.0252e-02,\n 3.6331e-02, -9.0209e-02, -1.4322e-01, -4.9489e-02, -7.7317e-02,\n -3.9801e-02, 4.8505e-04, 4.6852e-02, -1.0994e-01, -1.3940e-01,\n -1.9917e-02, 1.8771e-02, -9.2462e-02, 1.0885e-01, 8.2741e-02,\n -8.4839e-02, -2.1290e-01, -1.0819e-01, -6.3084e-02, 1.4973e-01,\n 1.1325e-01, -1.0975e-02, 2.7676e-02, -8.9407e-02, -4.8052e-02,\n 2.3875e-02]), 'model.layer3.1.bn1.running_var': tensor([0.0446, 0.0388, 0.0234, 0.0320, 0.0169, 0.0159, 0.0376, 0.0746, 0.0287,\n 0.0312, 0.0248, 0.0120, 0.0270, 0.0309, 0.0205, 0.0168, 0.0247, 0.0225,\n 0.0213, 0.0253, 0.0240, 0.0290, 0.0463, 0.0363, 0.0447, 0.0185, 0.0268,\n 0.0285, 0.0183, 0.0437, 0.0341, 0.0255, 0.0323, 0.0386, 0.0288, 0.0296,\n 0.0229, 0.0260, 0.0241, 0.0261, 0.0384, 0.0304, 0.0215, 0.0311, 0.0303,\n 0.0296, 0.0304, 0.0251, 0.0402, 0.0320, 0.0319, 0.0224, 0.0393, 0.0373,\n 0.0206, 0.0295, 0.0270, 0.0233, 0.0406, 0.0263, 0.0254, 0.0144, 0.0969,\n 0.0266, 0.0260, 0.0186, 0.0346, 0.0432, 0.0239, 0.0260, 0.0122, 0.0325,\n 0.0225, 0.0139, 0.0239, 0.0240, 0.0217, 0.0205, 0.0251, 0.0340, 0.0254,\n 0.0247, 0.0243, 0.0407, 0.0201, 0.0257, 0.0221, 0.0257, 0.0298, 0.0471,\n 0.0244, 0.0151, 0.0273, 0.0195, 0.0194, 0.0242, 0.0227, 0.0225, 0.0127,\n 0.0285, 0.0333, 0.0213, 0.0216, 0.0201, 0.0155, 0.0192, 0.0328, 0.0393,\n 0.0236, 0.0200, 0.0271, 0.0402, 0.0301, 0.0247, 0.0262, 0.0242, 0.0386,\n 0.0247, 0.0325, 0.0215, 0.0561, 0.0273, 0.0287, 0.0365, 0.0403, 0.0356,\n 0.0326, 0.0289, 0.0294, 0.0353, 0.0181, 0.0280, 0.0212, 0.0268, 0.0352,\n 0.0329, 0.0172, 0.0197, 0.0194, 0.0251, 0.0378, 0.0241, 0.0287, 0.0274,\n 0.0254, 0.0989, 0.0398, 0.0263, 0.0470, 0.0428, 0.0329, 0.0187, 0.0187,\n 0.0264, 0.0278, 0.0341, 0.0381, 0.0245, 0.0155, 0.0290, 0.0223, 0.0249,\n 0.0452, 0.0120, 0.0246, 0.0160, 0.0194, 0.0223, 0.0198, 0.0263, 0.0333,\n 0.0293, 0.0385, 0.0234, 0.0234, 0.0270, 0.0342, 0.0317, 0.0339, 0.0163,\n 0.0230, 0.0249, 0.0286, 0.0244, 0.0250, 0.0341, 0.0215, 0.0186, 0.0236,\n 0.0247, 0.0259, 0.0261, 0.0168, 0.0201, 0.0316, 0.0376, 0.0376, 0.0268,\n 0.0427, 0.0178, 0.0269, 0.0200, 0.0364, 0.0302, 0.0705, 0.0470, 0.0509,\n 0.0330, 0.0473, 0.0263, 0.0301, 0.0332, 0.0290, 0.0246, 0.0341, 0.0148,\n 0.0192, 0.0228, 0.0204, 0.0448, 0.0176, 0.0123, 0.0331, 0.0193, 0.0443,\n 0.0288, 0.0526, 0.0228, 0.0205, 0.0271, 0.0138, 0.0227, 0.0229, 0.0214,\n 0.0215, 0.0188, 0.0172, 0.0328, 0.0185, 0.0394, 0.0211, 0.0284, 0.0202,\n 0.0276, 0.0270, 0.0350, 0.0315, 0.0198, 0.0337, 0.0191, 0.0308, 0.0219,\n 0.0301, 0.0189, 0.0179, 0.0326]), 'model.layer3.1.bn1.num_batches_tracked': tensor(7160), 'model.layer3.1.conv2.weight': tensor([[[[-7.4665e-03, 8.9739e-03, -1.6352e-03],\n [-3.5747e-03, 8.7583e-03, 1.5872e-02],\n [ 3.7158e-03, 1.1544e-02, 4.0914e-03]],\n\n [[ 3.0740e-02, 3.5466e-02, 1.0893e-02],\n [ 1.0650e-02, 3.2397e-03, -5.7164e-03],\n [-8.1763e-03, -2.4877e-02, -8.2806e-03]],\n\n [[-3.2623e-03, 2.3360e-03, -2.1355e-03],\n [-9.2390e-03, -1.8247e-03, -3.0660e-03],\n [ 1.5006e-02, 1.9534e-02, 1.4484e-02]],\n\n ...,\n\n [[ 1.1062e-02, 9.0799e-03, 1.3065e-02],\n [-2.0632e-02, -9.5494e-03, 6.0611e-03],\n [ 6.2753e-03, 7.7204e-03, 1.2038e-02]],\n\n [[ 2.5211e-03, 3.4092e-03, 1.7101e-03],\n [ 8.2942e-03, 1.1622e-02, 5.1155e-03],\n [ 3.6868e-03, 7.7453e-03, 5.7696e-03]],\n\n [[-3.2292e-02, -3.2309e-02, -1.8263e-02],\n [-1.7967e-02, 4.8524e-04, 1.0607e-03],\n [ 1.4855e-02, 2.9793e-02, 1.3734e-02]]],\n\n\n [[[-9.0749e-04, -2.6324e-03, -8.2063e-03],\n [ 6.1415e-03, -2.2074e-03, -3.6337e-05],\n [-2.0016e-02, -2.7049e-02, -1.4625e-02]],\n\n [[ 4.7201e-03, 2.4853e-02, -6.2205e-03],\n [-1.6661e-03, 1.8346e-02, 4.4904e-03],\n [-7.0739e-03, 3.7813e-04, 1.3738e-02]],\n\n [[-5.9349e-03, -1.7261e-02, -1.7120e-02],\n [ 7.5477e-03, 1.0225e-02, -1.3207e-02],\n [-8.4025e-04, 1.2941e-02, 2.8338e-03]],\n\n ...,\n\n [[ 7.9856e-03, -2.2875e-02, 1.4476e-04],\n [ 1.7212e-02, 6.2747e-03, 7.7383e-03],\n [ 1.0891e-02, 1.8005e-02, 1.9355e-02]],\n\n [[ 8.1587e-03, 1.4589e-02, 2.6335e-02],\n [ 4.5132e-03, 6.7285e-03, 2.1630e-02],\n [-7.4162e-03, -1.2900e-03, 2.1020e-02]],\n\n [[-1.3779e-02, -1.8718e-02, -3.1152e-02],\n [-3.1625e-02, -4.0738e-02, -4.3149e-02],\n [-4.2914e-02, -7.8571e-02, -6.0270e-02]]],\n\n\n [[[-3.7094e-03, -2.7850e-02, -3.0655e-02],\n [ 1.6664e-02, 1.0635e-02, 1.0879e-02],\n [ 5.4870e-02, 6.2190e-02, 5.8135e-02]],\n\n [[ 4.2645e-03, 2.6514e-02, 1.8530e-02],\n [-6.4703e-03, 1.6106e-02, 1.5355e-02],\n [-9.4679e-03, -1.1050e-02, 1.8515e-04]],\n\n [[ 2.3785e-02, 1.5853e-02, 9.4358e-03],\n [ 9.4293e-03, 7.8658e-03, 4.0947e-03],\n [-3.4348e-03, -2.2844e-02, -9.5661e-03]],\n\n ...,\n\n [[ 2.4202e-02, 3.8547e-02, 3.4739e-02],\n [-5.1845e-03, 2.9916e-03, 1.0268e-03],\n [-2.5667e-02, -2.9442e-02, -8.9681e-03]],\n\n [[ 5.6276e-03, 9.3444e-03, 2.0814e-02],\n [-9.3926e-03, 3.1091e-03, 6.4551e-03],\n [-1.2051e-02, -4.7429e-03, -5.1828e-03]],\n\n [[-6.9407e-03, -1.6315e-02, -1.0969e-02],\n [ 6.3078e-03, 1.0324e-03, 1.6330e-03],\n [ 3.5943e-03, -7.4056e-03, -2.5285e-03]]],\n\n\n ...,\n\n\n [[[-9.0751e-03, -2.7273e-03, -1.0529e-02],\n [ 6.4750e-03, 9.7608e-03, -4.0464e-03],\n [ 3.9436e-03, 1.3666e-02, 7.7466e-05]],\n\n [[-8.0531e-03, -6.3497e-04, -3.6812e-03],\n [-1.6370e-02, -1.8252e-02, -1.6030e-03],\n [ 3.2574e-03, 8.5227e-03, -3.2988e-04]],\n\n [[ 6.9912e-03, 1.9981e-03, 6.6482e-03],\n [ 2.2599e-02, 7.0881e-03, -6.1672e-03],\n [ 3.0242e-02, 1.5534e-02, 3.0014e-03]],\n\n ...,\n\n [[-1.5941e-02, 3.7402e-04, -7.5098e-03],\n [ 5.7461e-03, 9.4695e-03, 1.1331e-02],\n [-1.3687e-02, -2.0098e-02, -1.4362e-02]],\n\n [[ 2.1312e-02, 1.1065e-02, -2.1016e-03],\n [-1.4691e-03, 8.4659e-03, -8.1167e-03],\n [ 8.8587e-03, 1.0674e-02, -1.2994e-02]],\n\n [[ 5.5273e-03, -2.6810e-04, 6.6620e-03],\n [-1.7589e-02, -1.1790e-02, -6.3873e-03],\n [ 2.5803e-02, 2.1591e-02, -4.7453e-03]]],\n\n\n [[[ 1.0165e-02, 1.1344e-02, 1.6442e-02],\n [-1.1534e-02, -1.4600e-03, -1.7651e-03],\n [ 7.3339e-05, 1.5105e-03, 5.0454e-03]],\n\n [[ 1.3724e-02, 2.9303e-03, -6.2250e-03],\n [-1.0723e-02, -3.7298e-02, -1.7638e-02],\n [ 1.8614e-02, -2.9164e-03, 1.2221e-02]],\n\n [[-1.5211e-02, -1.0190e-02, 2.8298e-03],\n [ 3.5463e-03, -1.3505e-02, 2.3221e-03],\n [ 1.9992e-02, 2.2686e-02, 2.5065e-02]],\n\n ...,\n\n [[ 1.2458e-02, -5.7351e-03, 2.4632e-02],\n [ 1.1275e-02, -1.1772e-02, 6.0785e-03],\n [ 1.0423e-02, 1.1442e-02, 5.5747e-03]],\n\n [[-6.0866e-03, -2.6276e-02, -2.1030e-02],\n [-2.3607e-03, -1.4978e-02, -2.0726e-02],\n [ 1.1131e-02, -2.3465e-02, -8.6126e-03]],\n\n [[ 2.9787e-03, 1.6957e-02, 1.7787e-02],\n [ 2.7656e-03, 3.4410e-02, 2.0509e-02],\n [-1.4950e-02, -8.4597e-04, -2.4731e-02]]],\n\n\n [[[ 2.9105e-03, 4.7481e-03, 7.1366e-04],\n [ 7.5474e-04, 2.5411e-02, 9.5093e-03],\n [-3.0082e-03, 1.0890e-02, -1.4152e-02]],\n\n [[ 1.5011e-02, 3.9916e-03, 2.7990e-03],\n [ 4.8147e-02, 2.6052e-03, -1.1474e-02],\n [ 3.5510e-02, 5.5926e-04, 8.4040e-06]],\n\n [[-3.1188e-03, -4.8316e-03, -2.4018e-03],\n [-1.0678e-02, -4.8008e-03, 1.4353e-02],\n [ 8.8155e-03, 9.4821e-03, 2.6415e-02]],\n\n ...,\n\n [[ 1.4960e-02, -1.9044e-02, -1.6153e-02],\n [ 5.8615e-02, -1.1964e-02, -4.2605e-02],\n [ 2.7551e-02, -9.6880e-03, -2.3314e-02]],\n\n [[-6.9956e-03, 4.0385e-03, 1.5729e-02],\n [-2.7747e-03, -6.0225e-03, 1.5815e-02],\n [-5.7219e-03, -1.7471e-03, 1.1294e-02]],\n\n [[-3.7736e-03, -1.1602e-02, -1.6294e-02],\n [ 2.2633e-02, -6.8019e-04, -9.0224e-03],\n [ 1.0897e-02, -2.5016e-03, 2.4365e-03]]]]), 'model.layer3.1.bn2.weight': tensor([0.1744, 0.2047, 0.1787, 0.1692, 0.1732, 0.1437, 0.1995, 0.1834, 0.2390,\n 0.1942, 0.1691, 0.4125, 0.1540, 0.1727, 0.2216, 0.1926, 0.1607, 0.1654,\n 0.1615, 0.2013, 0.2216, 0.2120, 0.1864, 0.1921, 0.1789, 0.1765, 0.1984,\n 0.1889, 0.3543, 0.2356, 0.1440, 0.2100, 0.1910, 0.2307, 0.1999, 0.1349,\n 0.1533, 0.1497, 0.2194, 0.2123, 0.1890, 0.1976, 0.1972, 0.2087, 0.2011,\n 0.2072, 0.2048, 0.2238, 0.1715, 0.1622, 0.1723, 0.2013, 0.1949, 0.2002,\n 0.2164, 0.4219, 0.1663, 0.1828, 0.1497, 0.1184, 0.1821, 0.1173, 0.1910,\n 0.1766, 0.2259, 0.2397, 0.1334, 0.1618, 0.1655, 0.1803, 0.1339, 0.1959,\n 0.2041, 0.1696, 0.2169, 0.2035, 0.1541, 0.1418, 0.1760, 0.1606, 0.1861,\n 0.1778, 0.1725, 0.1494, 0.3022, 0.2316, 0.1671, 0.2153, 0.1785, 0.1602,\n 0.1734, 0.2091, 0.2223, 0.1213, 0.1311, 0.1703, 0.2094, 0.2088, 0.1956,\n 0.1695, 0.1877, 0.1979, 0.1855, 0.2085, 0.2131, 0.2152, 0.1976, 0.1660,\n 0.2028, 0.1787, 0.1295, 0.1904, 0.2215, 0.2095, 0.1530, 0.1620, 0.1045,\n 0.1576, 0.1654, 0.1973, 0.1953, 0.1459, 0.1525, 0.1920, 0.1385, 0.2938,\n 0.1751, 0.2242, 0.1109, 0.2037, 0.1934, 0.1740, 0.1779, 0.1968, 0.1630,\n 0.1608, 0.1793, 0.3127, 0.1628, 0.1907, 0.1695, 0.1239, 0.1646, 0.1863,\n 0.1565, 0.1572, 0.1945, 0.2071, 0.1810, 0.1797, 0.1552, 0.1630, 0.1720,\n 0.1673, 0.1784, 0.1577, 0.1750, 0.1511, 0.1522, 0.1696, 0.1973, 0.1485,\n 0.2653, 0.2000, 0.1774, 0.2205, 0.1987, 0.2177, 0.1135, 0.1851, 0.1847,\n 0.1777, 0.1768, 0.1725, 0.2128, 0.1937, 0.1692, 0.1521, 0.1612, 0.1844,\n 0.2770, 0.1395, 0.1828, 0.1990, 0.2002, 0.1886, 0.1510, 0.2230, 0.1467,\n 0.1412, 0.1140, 0.1470, 0.2198, 0.1531, 0.1966, 0.1647, 0.1872, 0.1660,\n 0.1367, 0.1193, 0.2069, 0.2016, 0.2283, 0.2377, 0.1685, 0.1669, 0.1879,\n 0.1466, 0.1897, 0.1884, 0.1910, 0.1888, 0.1815, 0.2056, 0.1938, 0.2093,\n 0.2052, 0.1081, 0.2122, 0.1341, 0.1316, 0.2022, 0.1718, 0.1810, 0.1903,\n 0.1884, 0.1457, 0.2478, 0.1946, 0.1800, 0.2227, 0.1682, 0.1156, 0.1797,\n 0.1875, 0.1849, 0.1735, 0.2065, 0.1792, 0.1714, 0.1260, 0.1522, 0.1691,\n 0.1633, 0.2015, 0.1435, 0.1589, 0.1749, 0.2069, 0.1772, 0.1986, 0.2314,\n 0.1562, 0.2765, 0.1979, 0.2092]), 'model.layer3.1.bn2.bias': tensor([-0.0677, -0.0953, -0.0477, -0.0314, -0.0911, 0.1264, -0.1112, -0.0844,\n -0.2370, -0.0996, -0.0229, -0.3609, -0.0299, -0.0441, -0.0530, -0.0026,\n -0.0146, -0.0563, -0.0802, -0.0680, -0.0670, -0.0856, -0.0941, -0.0783,\n -0.0849, 0.0052, -0.0735, -0.0119, -0.3260, -0.0526, 0.0885, -0.0842,\n -0.0977, -0.0967, -0.0990, 0.0799, -0.0076, -0.0465, -0.0764, -0.1182,\n -0.0489, -0.0707, -0.0894, -0.0923, -0.1040, -0.1140, -0.0961, -0.1782,\n -0.1137, 0.0291, 0.0541, -0.0878, -0.0547, -0.0290, -0.0988, -0.3846,\n -0.1075, -0.1278, -0.0074, -0.0248, -0.1077, 0.0609, 0.0190, -0.0230,\n -0.1422, -0.0981, 0.0063, -0.0073, 0.0213, -0.0542, 0.0095, -0.0974,\n -0.0971, -0.0285, -0.1307, -0.0402, -0.0052, 0.0893, -0.0223, 0.0672,\n -0.0391, -0.0334, -0.0978, 0.0151, -0.1843, -0.0124, 0.0748, -0.1154,\n -0.1035, 0.0583, -0.0707, -0.1902, -0.1018, 0.0305, 0.0343, -0.1052,\n -0.1041, -0.1147, -0.0565, -0.0100, -0.0771, -0.0736, -0.0982, -0.0887,\n -0.1119, -0.1125, -0.1040, -0.0380, -0.1647, -0.0465, 0.0025, -0.0805,\n -0.1162, -0.0943, 0.0342, -0.0795, 0.1316, 0.2064, 0.0232, -0.0490,\n -0.0568, -0.0519, -0.0172, -0.0867, 0.0226, -0.2923, -0.0809, -0.1289,\n 0.0928, -0.1316, -0.1208, -0.0799, -0.1128, -0.1418, -0.0559, -0.0749,\n -0.0321, -0.2416, -0.0514, -0.0464, 0.0107, 0.1467, -0.0538, -0.0783,\n 0.0029, 0.0619, -0.0980, -0.0721, 0.0279, -0.0923, -0.0323, -0.0998,\n 0.0168, -0.0656, -0.0297, -0.0687, 0.0801, 0.0033, -0.0082, 0.0674,\n -0.0800, 0.0940, -0.2243, -0.0849, -0.0801, -0.1361, -0.0604, -0.1898,\n 0.0559, -0.0882, -0.0451, -0.0341, -0.0401, -0.0150, -0.0699, -0.1050,\n -0.1301, 0.0670, -0.0344, -0.0347, -0.0551, -0.0167, -0.0555, -0.0834,\n -0.1135, -0.1645, -0.0155, -0.0873, -0.0282, 0.0061, 0.1676, -0.0420,\n -0.1173, -0.0301, -0.0428, -0.0588, -0.1312, 0.0350, 0.0688, 0.1039,\n -0.0860, -0.1337, -0.1148, -0.0885, -0.0079, -0.0702, -0.0689, 0.0102,\n -0.1076, -0.1303, -0.0989, -0.0527, -0.0938, -0.1278, -0.1129, -0.0947,\n -0.0819, 0.0307, -0.1039, 0.0618, 0.0073, -0.1070, -0.0568, 0.0028,\n -0.0930, -0.0902, -0.0158, -0.1388, -0.0898, -0.1094, -0.0746, -0.0189,\n 0.0953, -0.0825, -0.0838, -0.0993, -0.0998, -0.0664, -0.1018, -0.0962,\n 0.0534, -0.0081, -0.0366, 0.0072, -0.1003, 0.0805, -0.0108, -0.0275,\n -0.0835, -0.0535, -0.0994, -0.1626, 0.0256, -0.2284, -0.0865, -0.1003]), 'model.layer3.1.bn2.running_mean': tensor([ 1.8636e-01, -8.0598e-02, 1.0825e-01, -1.5215e-01, 5.0626e-02,\n 1.4351e-01, -1.2812e-01, 5.3008e-01, -1.1056e-01, -7.4893e-02,\n 1.5579e-02, -2.9905e-02, 8.0134e-02, 1.0439e-01, 7.2134e-02,\n -3.8511e-02, 1.6032e-01, 1.8689e-02, 6.2281e-02, -3.1742e-01,\n -8.5657e-03, -5.9451e-03, -6.3930e-02, -4.7970e-02, -1.1501e-01,\n 1.6228e-01, -2.3853e-01, -7.6440e-02, -4.4659e-02, -9.0392e-01,\n 2.1074e-01, 3.7036e-02, -4.3734e-03, -8.5678e-03, 1.5339e-01,\n 3.0522e-01, -2.9242e-02, -2.1756e-01, -4.1976e-01, -7.9989e-02,\n -5.5573e-02, -8.5154e-02, -3.7316e-02, -8.2076e-02, -7.9770e-02,\n 8.7046e-02, 5.6433e-02, -3.2092e-02, -2.3196e-01, 9.0082e-02,\n 1.4069e-01, -1.2237e-02, 1.8392e-01, -1.0771e-01, -1.3860e-01,\n -3.3491e-01, -6.1907e-02, 1.5596e-02, -2.3207e-02, -3.9693e-03,\n -2.7838e-02, -1.0254e-02, 8.6599e-02, 5.5833e-02, -2.8851e-02,\n -1.0695e-01, 1.0893e-01, 1.9309e-02, 1.3172e-02, -3.5943e-04,\n -7.3730e-03, 1.8335e-02, -9.7880e-02, -1.4495e-01, 3.1805e-02,\n -5.8455e-03, 1.5898e-01, 1.3198e-01, 6.8674e-02, 2.5499e-01,\n 3.0975e-03, 1.2257e-01, -8.2309e-02, -3.5052e-01, -3.6289e-02,\n -7.6523e-03, 1.8553e-01, -1.0245e-03, -2.8006e-01, 4.7236e-02,\n 3.0880e-02, 1.8765e-01, 1.3057e-02, 1.8870e-01, -1.1175e-01,\n 7.7410e-02, -8.0222e-02, -2.6706e-01, 5.8090e-03, -5.6770e-02,\n 1.8051e-02, -1.1108e-02, -1.2067e-01, -1.1512e-01, -1.0961e-02,\n -6.7948e-02, -5.8566e-02, -1.2202e-01, 1.7261e-01, 1.4531e-01,\n -1.1204e-01, -9.9870e-02, -3.0182e-01, -5.5411e-02, 1.5188e-02,\n -1.9819e-02, 7.2458e-01, -3.8398e-01, 1.2038e-01, -3.7166e-02,\n -7.6266e-04, -1.2913e-01, 3.9060e-02, -1.9657e-01, -3.3384e-01,\n -2.7184e-01, 2.5109e-02, -9.4578e-02, -2.0452e-01, -1.6459e-01,\n -2.3008e-01, 3.6522e-02, 1.1833e-01, -1.1536e-01, -2.4180e-01,\n -1.2249e-01, 5.2061e-02, -3.0878e-01, 1.4029e-01, -2.7503e-01,\n 6.3931e-02, 4.5893e-01, 3.6654e-02, -6.5552e-02, 9.0589e-02,\n 1.0536e-01, -1.8367e-01, -3.8578e-01, -1.5113e-01, -2.0195e-01,\n 9.2704e-02, -4.9952e-02, 1.3968e-01, 1.0018e-01, 1.0586e-01,\n -9.7845e-02, -1.1892e-01, -2.6055e-01, -1.2570e-01, -1.4941e-01,\n -9.7882e-02, -1.3750e-01, 3.9528e-02, -7.6001e-02, -8.7162e-02,\n -3.5491e-01, -5.1265e-02, 6.5837e-02, -5.3985e-02, 1.9335e-01,\n 2.1154e-02, 4.4133e-03, 2.3294e-02, 7.6035e-02, -1.7924e-01,\n -1.9341e-04, -2.5232e-01, -1.6411e-01, -6.9563e-03, 9.3801e-02,\n -9.1713e-01, -2.7100e-01, -1.4011e-01, -7.5408e-03, -1.6080e-03,\n 2.0174e-01, -2.1005e-01, -4.4537e-02, -1.6552e-02, -2.3684e-01,\n 1.6365e-01, -1.0563e-02, -1.7386e-02, -1.2004e-01, -2.9457e-02,\n -1.3703e-01, -3.6244e-02, -6.7439e-02, -8.4194e-02, 4.6271e-02,\n -1.5037e-01, -1.2679e-01, 2.6856e-02, 4.6063e-02, -7.2557e-02,\n 2.8627e-02, -3.9469e-02, 5.5324e-02, 2.3338e-02, -8.0623e-02,\n 2.1677e-03, 1.1045e-02, -3.3737e-02, 8.5640e-02, -5.8316e-02,\n 1.9291e-02, -2.6860e-02, -1.2454e-01, -6.6734e-02, 5.7379e-02,\n -9.3804e-02, -1.2844e-01, -1.7150e-02, -1.3005e-01, -3.8329e-03,\n -8.5719e-02, 3.7858e-02, -4.5513e-02, -1.4194e-01, 1.0611e-01,\n -1.6096e-01, -1.1392e-01, 2.2073e-01, 2.6964e-02, -2.8859e-01,\n -9.5760e-02, -9.2319e-02, 9.3859e-02, -9.3763e-02, -1.2068e-01,\n -1.9413e-01, -4.8938e-02, -1.5013e-01, -8.2048e-02, 3.3760e-02,\n -4.7596e-02, -7.8928e-02, 1.0952e-01, -1.9862e-01, 1.2989e-01,\n 6.1954e-02, -2.9768e-01, 5.0627e-02, -7.5438e-02, 6.1928e-02,\n 1.1901e-01]), 'model.layer3.1.bn2.running_var': tensor([0.0209, 0.0384, 0.0237, 0.0233, 0.0267, 0.0503, 0.0243, 0.0323, 0.0291,\n 0.0229, 0.0313, 0.0689, 0.0260, 0.0251, 0.0454, 0.0347, 0.0215, 0.0194,\n 0.0241, 0.0238, 0.0432, 0.0341, 0.0171, 0.0199, 0.0215, 0.0333, 0.0383,\n 0.0373, 0.1027, 0.0786, 0.0567, 0.0321, 0.0212, 0.0302, 0.0308, 0.0431,\n 0.0166, 0.0161, 0.0354, 0.0160, 0.0418, 0.0311, 0.0258, 0.0393, 0.0207,\n 0.0245, 0.0192, 0.0212, 0.0182, 0.0250, 0.0516, 0.0235, 0.0287, 0.0207,\n 0.0388, 0.0835, 0.0232, 0.0240, 0.0258, 0.0151, 0.0149, 0.0193, 0.0321,\n 0.0206, 0.0199, 0.0532, 0.0172, 0.0408, 0.0513, 0.0166, 0.0206, 0.0228,\n 0.0168, 0.0425, 0.0252, 0.0356, 0.0247, 0.0422, 0.0332, 0.0385, 0.0346,\n 0.0338, 0.0261, 0.0318, 0.0281, 0.0710, 0.0550, 0.0286, 0.0399, 0.0473,\n 0.0270, 0.0232, 0.0314, 0.0147, 0.0246, 0.0249, 0.0252, 0.0216, 0.0236,\n 0.0275, 0.0196, 0.0238, 0.0263, 0.0355, 0.0360, 0.0355, 0.0338, 0.0315,\n 0.0262, 0.0151, 0.0237, 0.0186, 0.0202, 0.0352, 0.0350, 0.0160, 0.0272,\n 0.0605, 0.0389, 0.0303, 0.0251, 0.0139, 0.0234, 0.0223, 0.0235, 0.0276,\n 0.0248, 0.0358, 0.0174, 0.0223, 0.0328, 0.0151, 0.0249, 0.0270, 0.0204,\n 0.0166, 0.0250, 0.0279, 0.0430, 0.0245, 0.0282, 0.0331, 0.0252, 0.0354,\n 0.0239, 0.0340, 0.0186, 0.0365, 0.0274, 0.0202, 0.0227, 0.0173, 0.0294,\n 0.0205, 0.0345, 0.0256, 0.0420, 0.0194, 0.0224, 0.0338, 0.0366, 0.0356,\n 0.0238, 0.0249, 0.0291, 0.0248, 0.0338, 0.0192, 0.0262, 0.0322, 0.0238,\n 0.0343, 0.0300, 0.0294, 0.0175, 0.0248, 0.0183, 0.0281, 0.0233, 0.0247,\n 0.0763, 0.0209, 0.0116, 0.0556, 0.0185, 0.0240, 0.0239, 0.0373, 0.0281,\n 0.0169, 0.0215, 0.0179, 0.0278, 0.0205, 0.0304, 0.0209, 0.0241, 0.0310,\n 0.0250, 0.0213, 0.0379, 0.0286, 0.0493, 0.0554, 0.0264, 0.0217, 0.0231,\n 0.0169, 0.0247, 0.0228, 0.0402, 0.0274, 0.0277, 0.0197, 0.0207, 0.0355,\n 0.0192, 0.0177, 0.0206, 0.0280, 0.0241, 0.0207, 0.0152, 0.0379, 0.0265,\n 0.0274, 0.0206, 0.0414, 0.0188, 0.0196, 0.0439, 0.0224, 0.0366, 0.0246,\n 0.0216, 0.0238, 0.0205, 0.0214, 0.0217, 0.0171, 0.0267, 0.0238, 0.0271,\n 0.0224, 0.0265, 0.0402, 0.0137, 0.0344, 0.0285, 0.0144, 0.0301, 0.0228,\n 0.0358, 0.0462, 0.0175, 0.0279]), 'model.layer3.1.bn2.num_batches_tracked': tensor(7160), 'model.layer3.1.conv3.weight': tensor([[[[-9.4853e-03]],\n\n [[ 2.7828e-02]],\n\n [[ 1.7823e-03]],\n\n ...,\n\n [[ 7.6452e-03]],\n\n [[ 8.2779e-03]],\n\n [[-1.0612e-02]]],\n\n\n [[[-1.0210e-02]],\n\n [[ 9.7746e-03]],\n\n [[-1.6107e-02]],\n\n ...,\n\n [[ 6.5137e-03]],\n\n [[-5.1248e-03]],\n\n [[ 2.5105e-02]]],\n\n\n [[[ 1.2220e-05]],\n\n [[-2.6587e-03]],\n\n [[ 7.5165e-03]],\n\n ...,\n\n [[ 7.4858e-03]],\n\n [[ 1.3632e-02]],\n\n [[ 7.1421e-03]]],\n\n\n ...,\n\n\n [[[ 3.6933e-02]],\n\n [[-1.8959e-02]],\n\n [[ 2.3098e-02]],\n\n ...,\n\n [[ 3.4098e-02]],\n\n [[-9.2754e-03]],\n\n [[ 4.3309e-02]]],\n\n\n [[[ 1.0250e-02]],\n\n [[-1.8664e-03]],\n\n [[-7.7583e-03]],\n\n ...,\n\n [[-1.0148e-02]],\n\n [[-2.1041e-03]],\n\n [[-1.4775e-02]]],\n\n\n [[[-6.7134e-03]],\n\n [[ 2.1495e-02]],\n\n [[ 7.5845e-03]],\n\n ...,\n\n [[-1.5975e-02]],\n\n [[-2.5066e-03]],\n\n [[-7.0459e-04]]]]), 'model.layer3.1.bn3.weight': tensor([0.0390, 0.0836, 0.1079, ..., 0.1326, 0.1006, 0.1129]), 'model.layer3.1.bn3.bias': tensor([-0.0628, -0.0264, -0.0140, ..., -0.0214, -0.0714, -0.0830]), 'model.layer3.1.bn3.running_mean': tensor([-0.0400, -0.0201, 0.0283, ..., 0.0055, 0.0257, -0.0577]), 'model.layer3.1.bn3.running_var': tensor([0.0016, 0.0013, 0.0024, ..., 0.0030, 0.0033, 0.0037]), 'model.layer3.1.bn3.num_batches_tracked': tensor(7160), 'model.layer3.2.conv1.weight': tensor([[[[ 0.0015]],\n\n [[-0.0224]],\n\n [[-0.0011]],\n\n ...,\n\n [[-0.0436]],\n\n [[-0.0313]],\n\n [[-0.0063]]],\n\n\n [[[-0.0129]],\n\n [[-0.0023]],\n\n [[ 0.0171]],\n\n ...,\n\n [[ 0.0433]],\n\n [[-0.0092]],\n\n [[ 0.0296]]],\n\n\n [[[-0.0020]],\n\n [[-0.0314]],\n\n [[ 0.0143]],\n\n ...,\n\n [[-0.0023]],\n\n [[-0.0305]],\n\n [[ 0.0093]]],\n\n\n ...,\n\n\n [[[ 0.0073]],\n\n [[ 0.0003]],\n\n [[ 0.0043]],\n\n ...,\n\n [[-0.0190]],\n\n [[-0.0090]],\n\n [[ 0.0094]]],\n\n\n [[[ 0.0086]],\n\n [[-0.0206]],\n\n [[-0.0128]],\n\n ...,\n\n [[-0.0125]],\n\n [[-0.0251]],\n\n [[ 0.0275]]],\n\n\n [[[ 0.0172]],\n\n [[ 0.0193]],\n\n [[ 0.0099]],\n\n ...,\n\n [[-0.0039]],\n\n [[ 0.0082]],\n\n [[-0.0101]]]]), 'model.layer3.2.bn1.weight': tensor([0.2249, 0.1765, 0.1147, 0.1385, 0.1681, 0.1719, 0.1910, 0.1915, 0.1513,\n 0.1679, 0.1409, 0.1621, 0.0940, 0.0980, 0.1931, 0.1266, 0.1771, 0.1811,\n 0.1275, 0.1742, 0.1443, 0.1938, 0.1254, 0.1675, 0.2446, 0.2306, 0.1568,\n 0.1385, 0.1416, 0.2100, 0.1583, 0.1349, 0.1028, 0.1414, 0.1691, 0.1191,\n 0.1665, 0.1330, 0.1691, 0.1713, 0.1300, 0.1976, 0.1052, 0.1525, 0.1560,\n 0.1582, 0.1779, 0.1918, 0.1250, 0.1228, 0.1647, 0.2006, 0.1498, 0.2134,\n 0.1300, 0.1511, 0.1533, 0.1086, 0.1784, 0.1521, 0.1588, 0.1513, 0.1552,\n 0.1553, 0.1927, 0.1117, 0.1026, 0.1492, 0.1459, 0.1722, 0.1457, 0.2282,\n 0.1705, 0.1555, 0.1624, 0.1728, 0.1605, 0.1354, 0.1818, 0.1657, 0.1624,\n 0.1429, 0.1919, 0.1314, 0.1477, 0.1525, 0.1893, 0.1146, 0.1669, 0.2438,\n 0.1374, 0.1512, 0.1777, 0.1406, 0.1684, 0.1470, 0.1241, 0.1758, 0.1422,\n 0.2111, 0.1855, 0.1448, 0.1595, 0.1645, 0.1487, 0.2156, 0.1518, 0.1019,\n 0.1458, 0.1699, 0.1552, 0.1832, 0.1258, 0.0961, 0.1880, 0.1513, 0.1715,\n 0.0914, 0.1180, 0.1344, 0.1585, 0.1548, 0.1305, 0.1471, 0.1468, 0.1186,\n 0.1237, 0.1514, 0.1394, 0.1463, 0.1584, 0.1578, 0.1382, 0.1504, 0.1491,\n 0.1604, 0.1516, 0.1466, 0.1466, 0.1666, 0.1522, 0.1942, 0.1318, 0.1655,\n 0.1619, 0.1233, 0.1605, 0.1710, 0.1816, 0.1236, 0.1466, 0.1262, 0.1328,\n 0.1948, 0.1349, 0.1603, 0.1599, 0.1505, 0.1877, 0.1313, 0.1310, 0.1909,\n 0.1442, 0.1399, 0.1519, 0.1867, 0.1627, 0.2023, 0.1511, 0.1425, 0.1201,\n 0.1358, 0.1978, 0.1673, 0.1286, 0.1295, 0.1634, 0.1526, 0.1275, 0.1528,\n 0.1833, 0.1357, 0.1859, 0.1297, 0.1792, 0.1276, 0.1971, 0.1543, 0.1541,\n 0.1634, 0.1568, 0.1456, 0.1531, 0.1307, 0.1688, 0.1452, 0.1883, 0.1202,\n 0.1595, 0.2157, 0.1349, 0.1143, 0.1416, 0.1906, 0.1277, 0.1694, 0.1509,\n 0.1555, 0.1898, 0.1447, 0.2141, 0.1166, 0.1501, 0.1262, 0.1437, 0.1262,\n 0.1881, 0.1184, 0.1938, 0.1229, 0.1642, 0.1353, 0.1241, 0.1358, 0.1348,\n 0.1810, 0.1597, 0.1178, 0.1646, 0.1094, 0.1218, 0.1741, 0.1179, 0.1282,\n 0.1821, 0.1216, 0.1585, 0.1728, 0.1755, 0.1675, 0.1339, 0.1874, 0.1565,\n 0.1543, 0.2041, 0.1728, 0.1118, 0.1817, 0.1487, 0.1097, 0.1446, 0.1715,\n 0.1569, 0.1626, 0.1535, 0.1415]), 'model.layer3.2.bn1.bias': tensor([-0.1168, -0.2114, 0.0675, 0.0433, -0.1055, -0.1091, -0.0911, -0.1021,\n -0.0120, -0.0844, -0.0518, -0.0563, 0.1117, 0.0588, -0.0434, 0.0059,\n -0.0865, -0.1174, -0.0083, -0.0646, -0.0610, -0.1090, 0.0057, -0.0678,\n -0.1726, -0.1624, -0.0695, -0.0138, -0.0278, -0.1552, -0.1255, -0.0261,\n 0.0960, -0.0169, -0.0421, 0.0218, -0.0460, 0.0346, -0.1142, -0.0195,\n 0.0378, -0.1152, 0.0551, -0.0735, -0.0542, 0.0166, -0.0575, -0.1491,\n 0.0416, -0.0008, -0.0535, -0.0894, -0.1372, -0.1163, 0.0314, 0.0195,\n -0.1059, 0.1324, -0.0867, -0.0773, -0.0472, -0.0434, -0.0889, -0.0096,\n -0.0064, 0.0255, 0.0962, -0.0446, -0.0435, -0.1197, -0.0047, -0.2342,\n -0.0493, -0.0520, -0.0249, -0.1110, -0.0204, -0.0306, -0.0679, -0.0110,\n -0.0395, 0.0203, -0.0060, 0.0212, -0.0985, 0.0199, -0.1367, 0.0544,\n -0.0261, -0.0839, 0.0090, -0.0612, -0.0479, -0.0327, -0.1125, -0.0841,\n -0.0120, -0.1365, -0.0433, -0.1323, -0.1191, -0.0593, -0.0867, -0.0781,\n 0.0036, -0.2013, 0.0168, 0.0322, -0.0266, -0.0622, -0.0327, -0.1158,\n 0.0314, 0.0768, -0.0889, -0.0461, -0.0836, 0.1007, 0.0803, -0.0197,\n -0.0616, -0.0479, -0.0014, -0.0243, -0.0260, -0.0075, 0.0152, -0.0753,\n -0.0452, -0.0679, -0.0746, -0.0287, 0.0172, -0.0637, -0.0383, -0.0684,\n -0.0855, -0.0051, -0.0420, -0.0919, -0.0310, -0.0960, -0.0167, -0.0808,\n -0.0707, 0.0192, -0.0643, -0.0933, -0.1303, 0.0236, -0.0123, -0.0212,\n -0.0108, -0.1117, -0.0103, -0.1302, -0.0667, -0.0394, -0.0785, -0.0437,\n 0.0305, -0.1388, -0.0845, -0.0469, -0.1517, -0.1304, -0.0565, -0.1515,\n -0.0152, 0.0147, 0.0466, -0.0267, -0.1146, -0.0111, 0.0101, -0.0227,\n -0.0464, -0.1104, 0.0415, -0.0177, -0.0891, -0.0514, -0.0953, -0.0272,\n -0.0510, -0.0235, -0.1124, -0.0540, -0.0879, -0.0780, -0.0755, -0.0419,\n -0.0974, -0.0429, -0.0903, -0.0314, -0.1753, 0.0251, 0.0568, -0.1322,\n -0.0779, 0.0281, -0.0159, -0.1211, -0.0881, -0.0692, -0.0582, -0.0362,\n -0.1338, -0.0163, -0.1442, -0.0295, -0.1190, -0.0134, -0.0610, -0.0749,\n -0.1512, 0.0153, -0.1154, 0.0472, -0.0541, -0.0446, 0.0347, -0.0181,\n 0.1242, -0.0596, -0.0364, -0.0206, -0.0711, 0.0411, 0.0294, -0.1164,\n 0.0263, -0.0318, -0.1040, 0.0424, -0.0768, -0.1016, -0.0601, -0.0810,\n -0.0244, -0.1049, -0.0193, -0.0574, -0.1196, -0.0111, 0.0060, -0.0868,\n -0.0315, 0.0672, -0.0774, -0.0720, 0.0397, -0.0637, -0.0081, -0.0541]), 'model.layer3.2.bn1.running_mean': tensor([-0.1129, 0.0273, -0.0442, 0.0492, -0.0716, -0.0281, -0.0754, -0.0648,\n -0.0777, -0.0421, 0.0363, -0.0269, -0.0727, -0.2676, -0.0895, -0.1175,\n -0.1909, -0.0370, -0.0806, -0.1343, -0.0375, -0.1126, -0.0290, -0.0837,\n -0.2018, 0.0137, -0.1411, -0.0979, -0.0754, -0.0576, 0.0280, -0.0410,\n -0.1008, -0.0420, -0.0241, -0.0277, -0.0694, -0.0575, 0.0100, -0.0179,\n -0.0122, -0.0795, -0.0581, -0.0141, -0.0653, -0.1269, -0.0526, 0.1205,\n -0.1384, -0.0490, -0.0950, -0.0705, -0.0465, -0.0547, 0.0036, -0.0119,\n -0.0278, -0.0596, 0.0530, 0.0537, 0.0731, 0.0129, -0.0586, 0.0179,\n 0.1357, -0.0730, -0.2494, -0.0347, 0.0244, -0.0690, 0.0016, -0.0495,\n -0.0199, -0.1165, -0.0577, -0.0926, -0.1105, -0.0638, -0.0675, -0.1041,\n -0.0737, 0.1135, -0.1205, 0.0853, 0.0220, -0.0547, -0.0888, -0.0223,\n -0.0366, -0.0112, -0.1022, 0.0093, -0.0333, -0.0791, -0.0978, -0.0551,\n -0.0968, -0.0480, 0.0326, -0.1281, -0.0698, 0.0046, 0.0641, -0.0808,\n -0.0256, -0.0633, -0.0245, -0.2078, -0.0151, 0.0655, -0.1217, -0.1010,\n -0.0881, 0.0242, -0.0059, -0.0078, 0.0296, -0.2104, -0.0401, -0.0459,\n -0.0518, 0.0132, -0.1605, 0.0081, -0.0839, -0.1384, -0.1683, -0.0074,\n -0.0279, -0.0347, 0.0924, -0.0705, 0.0401, 0.0596, 0.0112, 0.1657,\n -0.0708, -0.1436, -0.0452, -0.0999, -0.0977, -0.0173, 0.0058, 0.0429,\n 0.0595, -0.1449, -0.0273, 0.0587, 0.1189, 0.0007, -0.1221, 0.0223,\n 0.0378, -0.0862, -0.0906, -0.0231, 0.0509, 0.0416, -0.0227, -0.0861,\n -0.0156, -0.0797, -0.1531, -0.0544, -0.0593, -0.0661, -0.0896, 0.0351,\n -0.0138, -0.2141, 0.0782, 0.0252, -0.1152, -0.0166, -0.0033, -0.0415,\n -0.1225, 0.0839, 0.0152, -0.2145, -0.0881, -0.0494, 0.0103, -0.0305,\n 0.0112, 0.0090, -0.1179, -0.0144, -0.1038, -0.1282, -0.0731, -0.0884,\n 0.0558, -0.1124, -0.0793, -0.1152, 0.0614, -0.0121, -0.0067, 0.0361,\n -0.0114, -0.1736, -0.0846, -0.1098, 0.0163, -0.0478, -0.0386, -0.1630,\n -0.1756, 0.0078, -0.1429, -0.1908, 0.0269, -0.0348, -0.0704, -0.0571,\n 0.0171, -0.1455, -0.1258, -0.0850, -0.0895, -0.0247, 0.0899, 0.0124,\n 0.0367, -0.0690, 0.0731, 0.0505, -0.0220, -0.0474, -0.0475, -0.0913,\n -0.0134, -0.0574, 0.2503, -0.0720, -0.0138, -0.0614, -0.2199, -0.0872,\n -0.0939, -0.0955, -0.0893, -0.1023, -0.0831, -0.1308, -0.1625, -0.0418,\n -0.0706, -0.0931, -0.0740, -0.1157, -0.1449, -0.0426, -0.1022, -0.0528]), 'model.layer3.2.bn1.running_var': tensor([0.0264, 0.0101, 0.0222, 0.0314, 0.0271, 0.0131, 0.0298, 0.0209, 0.0215,\n 0.0166, 0.0230, 0.0158, 0.0265, 0.0193, 0.0408, 0.0230, 0.0226, 0.0148,\n 0.0222, 0.0168, 0.0133, 0.0208, 0.0210, 0.0142, 0.0221, 0.0152, 0.0212,\n 0.0239, 0.0316, 0.0224, 0.0138, 0.0236, 0.0237, 0.0205, 0.0277, 0.0246,\n 0.0215, 0.0213, 0.0195, 0.0265, 0.0354, 0.0320, 0.0268, 0.0183, 0.0196,\n 0.0274, 0.0240, 0.0140, 0.0249, 0.0174, 0.0245, 0.0186, 0.0137, 0.0379,\n 0.0255, 0.0366, 0.0143, 0.0251, 0.0274, 0.0238, 0.0296, 0.0298, 0.0149,\n 0.0331, 0.0434, 0.0251, 0.0249, 0.0255, 0.0226, 0.0216, 0.0271, 0.0243,\n 0.0283, 0.0213, 0.0258, 0.0130, 0.0217, 0.0228, 0.0304, 0.0271, 0.0228,\n 0.0307, 0.0524, 0.0221, 0.0161, 0.0356, 0.0196, 0.0353, 0.0317, 0.0388,\n 0.0232, 0.0176, 0.0253, 0.0239, 0.0178, 0.0179, 0.0161, 0.0123, 0.0230,\n 0.0240, 0.0218, 0.0256, 0.0243, 0.0211, 0.0346, 0.0208, 0.0330, 0.0163,\n 0.0259, 0.0228, 0.0266, 0.0176, 0.0288, 0.0253, 0.0184, 0.0180, 0.0235,\n 0.0175, 0.0394, 0.0322, 0.0260, 0.0248, 0.0229, 0.0324, 0.0243, 0.0199,\n 0.0208, 0.0215, 0.0139, 0.0170, 0.0151, 0.0242, 0.0283, 0.0211, 0.0167,\n 0.0264, 0.0217, 0.0212, 0.0140, 0.0276, 0.0188, 0.0181, 0.0191, 0.0206,\n 0.0253, 0.0121, 0.0187, 0.0163, 0.0284, 0.0239, 0.0307, 0.0289, 0.0138,\n 0.0191, 0.0271, 0.0275, 0.0272, 0.0217, 0.0264, 0.0231, 0.0260, 0.0179,\n 0.0169, 0.0202, 0.0133, 0.0180, 0.0232, 0.0245, 0.0251, 0.0230, 0.0265,\n 0.0208, 0.0214, 0.0295, 0.0314, 0.0228, 0.0176, 0.0120, 0.0216, 0.0211,\n 0.0236, 0.0162, 0.0213, 0.0208, 0.0296, 0.0193, 0.0255, 0.0158, 0.0118,\n 0.0181, 0.0252, 0.0256, 0.0202, 0.0197, 0.0204, 0.0183, 0.0189, 0.0209,\n 0.0469, 0.0414, 0.0131, 0.0225, 0.0211, 0.0178, 0.0157, 0.0269, 0.0171,\n 0.0268, 0.0131, 0.0219, 0.0286, 0.0148, 0.0137, 0.0219, 0.0186, 0.0113,\n 0.0250, 0.0215, 0.0157, 0.0229, 0.0238, 0.0230, 0.0272, 0.0236, 0.0320,\n 0.0256, 0.0251, 0.0191, 0.0237, 0.0173, 0.0276, 0.0142, 0.0300, 0.0183,\n 0.0483, 0.0381, 0.0225, 0.0231, 0.0219, 0.0232, 0.0212, 0.0199, 0.0197,\n 0.0208, 0.0269, 0.0334, 0.0227, 0.0204, 0.0265, 0.0214, 0.0145, 0.0218,\n 0.0476, 0.0215, 0.0171, 0.0173]), 'model.layer3.2.bn1.num_batches_tracked': tensor(7160), 'model.layer3.2.conv2.weight': tensor([[[[-0.0007, -0.0112, 0.0044],\n [ 0.0125, 0.0251, 0.0114],\n [ 0.0190, 0.0298, 0.0298]],\n\n [[ 0.0066, -0.0018, 0.0035],\n [ 0.0029, 0.0330, 0.0124],\n [-0.0041, 0.0120, -0.0005]],\n\n [[ 0.0205, 0.0177, 0.0029],\n [-0.0214, -0.0358, -0.0150],\n [ 0.0091, 0.0341, 0.0118]],\n\n ...,\n\n [[-0.0211, -0.0194, -0.0155],\n [-0.0164, -0.0084, 0.0153],\n [ 0.0058, 0.0482, 0.0143]],\n\n [[-0.0032, 0.0145, 0.0186],\n [-0.0100, -0.0037, 0.0171],\n [-0.0226, -0.0166, 0.0103]],\n\n [[ 0.0621, 0.0317, -0.0436],\n [ 0.0849, 0.0086, -0.0851],\n [ 0.0646, -0.0014, -0.0571]]],\n\n\n [[[ 0.0019, 0.0032, -0.0065],\n [ 0.0023, 0.0447, 0.0099],\n [-0.0124, 0.0020, -0.0034]],\n\n [[-0.0139, 0.0012, 0.0148],\n [-0.0235, 0.0030, -0.0025],\n [-0.0159, -0.0157, 0.0009]],\n\n [[-0.0010, 0.0083, 0.0077],\n [ 0.0020, 0.0036, 0.0125],\n [ 0.0032, 0.0080, 0.0042]],\n\n ...,\n\n [[-0.0027, -0.0152, -0.0105],\n [-0.0062, 0.0002, -0.0105],\n [-0.0150, -0.0113, -0.0169]],\n\n [[ 0.0157, 0.0142, 0.0116],\n [ 0.0413, 0.0247, 0.0335],\n [ 0.0212, 0.0197, 0.0097]],\n\n [[ 0.0157, 0.0044, -0.0137],\n [ 0.0060, -0.0005, -0.0221],\n [ 0.0128, -0.0048, -0.0233]]],\n\n\n [[[ 0.0038, -0.0164, -0.0085],\n [ 0.0133, -0.0191, 0.0012],\n [ 0.0075, -0.0036, 0.0168]],\n\n [[-0.0062, -0.0159, -0.0083],\n [-0.0077, -0.0093, -0.0103],\n [-0.0056, 0.0097, -0.0015]],\n\n [[-0.0015, -0.0100, 0.0011],\n [-0.0083, -0.0126, 0.0020],\n [-0.0289, -0.0151, -0.0062]],\n\n ...,\n\n [[ 0.0223, 0.0242, -0.0098],\n [ 0.0035, 0.0156, -0.0017],\n [-0.0296, -0.0117, 0.0155]],\n\n [[-0.0097, 0.0004, 0.0009],\n [-0.0172, -0.0045, -0.0042],\n [-0.0036, -0.0005, 0.0099]],\n\n [[ 0.0006, 0.0020, -0.0020],\n [-0.0027, 0.0038, 0.0117],\n [ 0.0011, 0.0133, 0.0188]]],\n\n\n ...,\n\n\n [[[ 0.0126, -0.0148, -0.0038],\n [ 0.0135, -0.0269, 0.0093],\n [ 0.0105, -0.0139, 0.0045]],\n\n [[ 0.0011, -0.0106, -0.0096],\n [ 0.0218, 0.0128, 0.0086],\n [ 0.0014, 0.0002, -0.0008]],\n\n [[ 0.0024, -0.0153, 0.0047],\n [ 0.0006, -0.0227, -0.0019],\n [ 0.0028, -0.0100, -0.0093]],\n\n ...,\n\n [[ 0.0076, -0.0438, -0.0059],\n [ 0.0001, -0.0198, -0.0028],\n [-0.0064, -0.0180, -0.0024]],\n\n [[ 0.0250, -0.0353, 0.0025],\n [ 0.0027, -0.0280, 0.0013],\n [ 0.0204, -0.0102, 0.0115]],\n\n [[-0.0154, -0.0126, 0.0127],\n [-0.0188, -0.0092, 0.0173],\n [-0.0060, -0.0122, 0.0034]]],\n\n\n [[[ 0.0304, 0.0264, 0.0223],\n [ 0.0317, 0.0130, 0.0068],\n [ 0.0047, 0.0062, -0.0096]],\n\n [[-0.0232, -0.0102, 0.0129],\n [-0.0412, -0.0325, 0.0252],\n [-0.0357, -0.0571, -0.0234]],\n\n [[-0.0074, 0.0017, 0.0112],\n [-0.0228, -0.0114, 0.0270],\n [-0.0076, -0.0093, 0.0065]],\n\n ...,\n\n [[-0.0143, -0.0102, -0.0101],\n [-0.0033, 0.0048, -0.0021],\n [-0.0133, -0.0047, 0.0192]],\n\n [[-0.0008, -0.0046, -0.0249],\n [ 0.0045, -0.0033, -0.0121],\n [-0.0053, -0.0091, -0.0086]],\n\n [[-0.0141, -0.0003, 0.0180],\n [-0.0073, -0.0058, 0.0099],\n [-0.0075, -0.0121, -0.0073]]],\n\n\n [[[-0.0145, -0.0211, -0.0129],\n [ 0.0038, -0.0196, 0.0090],\n [ 0.0119, -0.0122, -0.0008]],\n\n [[-0.0209, -0.0162, -0.0110],\n [-0.0280, -0.0192, -0.0133],\n [-0.0177, -0.0165, -0.0160]],\n\n [[-0.0214, -0.0201, -0.0072],\n [-0.0205, -0.0057, 0.0186],\n [-0.0143, 0.0113, 0.0212]],\n\n ...,\n\n [[ 0.0156, 0.0143, -0.0141],\n [-0.0042, -0.0046, -0.0134],\n [-0.0185, -0.0223, -0.0027]],\n\n [[-0.0081, 0.0033, -0.0264],\n [-0.0317, 0.0101, -0.0275],\n [-0.0254, 0.0083, -0.0002]],\n\n [[-0.0065, 0.0041, 0.0149],\n [-0.0056, -0.0171, 0.0085],\n [ 0.0045, -0.0052, 0.0162]]]]), 'model.layer3.2.bn2.weight': tensor([0.1091, 0.1762, 0.1975, 0.1596, 0.2196, 0.2109, 0.1487, 0.1857, 0.1338,\n 0.1859, 0.1652, 0.1688, 0.2257, 0.1224, 0.1929, 0.1769, 0.2044, 0.2013,\n 0.2193, 0.1551, 0.1960, 0.2047, 0.1361, 0.1341, 0.1767, 0.2268, 0.1870,\n 0.1829, 0.1348, 0.2015, 0.1790, 0.2237, 0.2138, 0.2500, 0.2064, 0.2023,\n 0.1982, 0.1368, 0.1526, 0.2290, 0.1913, 0.2047, 0.1776, 0.1900, 0.2017,\n 0.1927, 0.2337, 0.2011, 0.2092, 0.1377, 0.1339, 0.1602, 0.1932, 0.1606,\n 0.1978, 0.1853, 0.1915, 0.1805, 0.1814, 0.1318, 0.1984, 0.1748, 0.1530,\n 0.1440, 0.1254, 0.1336, 0.2186, 0.1556, 0.1733, 0.1871, 0.2095, 0.1680,\n 0.1542, 0.1679, 0.1872, 0.2064, 0.2067, 0.2331, 0.1830, 0.1949, 0.1333,\n 0.1365, 0.2173, 0.2019, 0.1850, 0.1366, 0.1714, 0.1954, 0.1942, 0.2036,\n 0.2120, 0.2198, 0.2315, 0.1829, 0.1506, 0.1851, 0.2038, 0.2249, 0.1634,\n 0.1641, 0.1656, 0.2049, 0.1711, 0.1801, 0.2101, 0.2187, 0.1984, 0.2014,\n 0.1658, 0.2019, 0.2373, 0.1667, 0.1874, 0.1720, 0.1261, 0.1175, 0.2290,\n 0.2052, 0.1160, 0.1899, 0.2331, 0.2205, 0.1627, 0.1663, 0.1800, 0.1321,\n 0.2015, 0.1389, 0.1556, 0.1876, 0.1937, 0.2422, 0.1691, 0.2224, 0.1521,\n 0.1190, 0.1811, 0.2029, 0.1497, 0.2197, 0.1802, 0.1772, 0.1894, 0.1100,\n 0.1764, 0.1998, 0.1860, 0.1446, 0.2037, 0.1844, 0.1826, 0.2190, 0.1985,\n 0.1856, 0.1821, 0.1838, 0.1974, 0.1720, 0.1753, 0.2165, 0.2478, 0.1677,\n 0.1773, 0.1640, 0.1933, 0.1733, 0.1901, 0.2003, 0.1903, 0.1738, 0.1893,\n 0.1981, 0.1867, 0.2033, 0.1923, 0.1554, 0.1897, 0.1527, 0.1792, 0.1626,\n 0.1945, 0.1968, 0.1917, 0.1421, 0.1853, 0.1849, 0.1972, 0.1919, 0.1318,\n 0.2027, 0.1888, 0.1258, 0.1850, 0.1586, 0.1324, 0.2220, 0.2176, 0.1960,\n 0.1748, 0.1784, 0.2084, 0.2382, 0.1666, 0.1720, 0.1432, 0.1298, 0.1424,\n 0.2178, 0.2131, 0.1342, 0.1177, 0.1810, 0.1353, 0.1316, 0.1499, 0.2163,\n 0.2149, 0.2316, 0.2066, 0.1736, 0.1651, 0.2021, 0.1933, 0.1968, 0.1613,\n 0.1645, 0.2221, 0.1509, 0.1772, 0.2019, 0.1838, 0.2068, 0.2364, 0.1990,\n 0.1987, 0.2189, 0.2055, 0.1762, 0.1354, 0.3121, 0.2004, 0.2033, 0.1895,\n 0.1612, 0.1939, 0.2073, 0.1829, 0.2214, 0.2039, 0.2072, 0.1511, 0.1333,\n 0.1337, 0.2149, 0.1717, 0.1515]), 'model.layer3.2.bn2.bias': tensor([ 0.1243, -0.0674, -0.1534, -0.0506, -0.1128, -0.1285, 0.1061, -0.0273,\n -0.0151, -0.0834, -0.0590, -0.0818, -0.1213, -0.0183, -0.1172, -0.0558,\n -0.1540, -0.1138, -0.1368, -0.0592, -0.0933, -0.1162, 0.0587, 0.0426,\n -0.0927, -0.1443, -0.0665, -0.0679, 0.0570, -0.1149, -0.1100, -0.1072,\n -0.1555, -0.1555, -0.1199, -0.1648, -0.0868, -0.0074, 0.0132, -0.1064,\n -0.0583, -0.1323, -0.0630, -0.1316, -0.1212, -0.0927, -0.1373, -0.1414,\n -0.1372, 0.0190, -0.0018, -0.1064, -0.1024, -0.0410, -0.0869, -0.0107,\n -0.1733, -0.0519, -0.0664, 0.0627, -0.1174, -0.0702, 0.0049, 0.0772,\n 0.1043, 0.0151, -0.1482, -0.0180, -0.0900, -0.0887, -0.1556, -0.0925,\n -0.0705, -0.0432, -0.1087, -0.1019, -0.1128, -0.1747, -0.0355, -0.1098,\n 0.0684, 0.0240, -0.1674, -0.0663, -0.1184, 0.1139, -0.0432, -0.1745,\n -0.1057, -0.1538, -0.1611, -0.2075, -0.1511, -0.0734, 0.0678, -0.0579,\n -0.1192, -0.0895, 0.0039, -0.0554, -0.0899, -0.0644, -0.0782, -0.0429,\n -0.0868, -0.1128, -0.1463, -0.1212, -0.1385, -0.1451, -0.1533, -0.0808,\n -0.0991, -0.0878, 0.1737, 0.1780, -0.1297, -0.1703, 0.0530, -0.0673,\n -0.1305, -0.1632, -0.0708, -0.1190, -0.1252, 0.0663, -0.0455, 0.0381,\n -0.0508, -0.0815, -0.1153, -0.1395, -0.0867, -0.0772, 0.0434, 0.0842,\n -0.0351, -0.0656, -0.0053, -0.1692, -0.0988, -0.0317, -0.0690, 0.1048,\n -0.0701, -0.1522, -0.0938, 0.0937, -0.1083, -0.0860, -0.0249, -0.1465,\n -0.0874, -0.1124, -0.0869, -0.1387, -0.1208, -0.1039, -0.0512, -0.1140,\n -0.1353, -0.1086, -0.0494, -0.0556, -0.1514, -0.1139, -0.0830, -0.1012,\n -0.0883, -0.0811, -0.1372, -0.0875, -0.1009, -0.1343, -0.0484, -0.0283,\n -0.0710, 0.0158, -0.0461, -0.0144, -0.0690, -0.0911, -0.1451, -0.0427,\n -0.1004, -0.0730, -0.1366, -0.0800, 0.1171, -0.1342, -0.1161, 0.0801,\n -0.1344, -0.0286, -0.0189, -0.1015, -0.1588, -0.1415, -0.0936, -0.0756,\n -0.0636, -0.1418, -0.0909, -0.0654, 0.0012, 0.0595, 0.0497, -0.1091,\n -0.1360, 0.0614, 0.2268, -0.1173, 0.0153, 0.0270, 0.0193, -0.1112,\n -0.1305, -0.0983, -0.0925, -0.1362, -0.0373, -0.1451, -0.1003, -0.0581,\n -0.0250, -0.0284, -0.1233, -0.0063, -0.0878, -0.1060, -0.1017, -0.1033,\n -0.0544, -0.1201, -0.1487, -0.1180, -0.1119, -0.0196, 0.0073, -0.2275,\n -0.1573, -0.1212, -0.1042, -0.0472, -0.0418, -0.1876, -0.0743, -0.1033,\n -0.0979, -0.0970, 0.0060, 0.0298, 0.0906, -0.0998, -0.0587, -0.0184]), 'model.layer3.2.bn2.running_mean': tensor([ 0.0578, -0.1882, -0.0419, -0.0847, -0.1718, -0.0894, -0.1799, -0.0751,\n -0.1805, -0.0297, 0.1182, -0.0787, -0.0586, -0.0822, -0.0723, -0.0506,\n -0.0548, 0.1783, -0.0499, -0.0402, -0.1630, -0.0115, -0.0904, -0.1016,\n -0.0977, -0.1412, -0.1164, -0.1403, -0.1602, -0.0369, -0.0904, -0.1127,\n -0.0783, -0.2883, -0.0597, 0.2117, -0.0203, -0.0962, -0.0214, -0.2736,\n -0.1037, -0.0221, -0.1248, -0.1534, -0.1025, 0.0193, -0.2075, -0.0893,\n -0.1763, -0.0134, -0.2072, 0.0792, -0.1168, -0.0550, -0.0771, -0.0851,\n -0.0417, -0.0466, -0.1254, -0.0981, 0.0195, -0.0815, 0.0593, 0.0010,\n -0.0164, -0.0603, -0.0909, 0.0008, -0.0448, -0.1283, -0.1042, -0.1236,\n -0.0592, 0.0393, -0.0627, 0.0050, -0.0406, -0.4904, 0.0227, 0.2982,\n 0.0319, -0.0195, -0.1290, -0.1157, -0.0813, -0.1411, -0.0487, -0.0159,\n -0.1719, -0.0748, -0.0790, -0.0775, -0.0409, -0.0076, 0.0576, -0.1186,\n -0.0107, -0.0224, 0.0012, 0.0029, 0.0376, -0.0043, -0.0946, -0.1245,\n -0.0059, 0.0487, -0.0804, 0.0311, 0.0036, -0.1367, -0.0051, -0.0636,\n -0.0589, 0.0559, -0.1085, 0.1091, -0.0016, -0.1136, -0.0883, -0.0993,\n -0.1811, -0.0465, -0.0440, 0.0252, -0.0117, -0.1709, -0.1221, 0.0343,\n -0.0255, -0.1504, -0.1003, -0.1502, -0.0929, -0.0763, 0.1147, -0.1272,\n 0.0077, -0.2855, 0.0426, -0.0468, -0.1319, -0.0666, -0.1291, 0.1708,\n -0.0107, -0.0343, -0.0394, -0.1614, -0.1045, -0.1011, -0.0803, -0.0708,\n -0.0392, -0.0655, -0.0593, -0.1838, -0.1275, -0.0975, 0.0681, 0.0232,\n -0.0678, -0.1275, -0.0022, -0.1083, -0.0274, -0.0899, -0.0780, -0.0820,\n -0.1051, -0.0316, -0.0723, -0.0726, -0.1603, -0.1253, -0.0870, 0.0292,\n -0.0970, 0.0180, -0.0314, -0.0426, -0.0097, -0.0402, -0.2213, 0.0030,\n -0.0402, -0.1071, -0.0474, 0.0272, 0.0800, -0.1688, 0.0801, 0.0368,\n -0.1131, -0.0120, -0.0366, -0.0768, -0.0492, -0.0270, -0.1210, -0.1159,\n 0.0160, -0.0739, -0.0371, -0.1172, -0.0744, -0.0538, -0.0378, -0.0468,\n -0.0455, 0.0189, 0.3834, -0.0809, 0.0184, -0.0876, -0.1256, -0.0084,\n 0.0005, -0.2695, -0.0821, -0.1020, -0.0063, -0.1038, -0.1869, -0.0199,\n 0.0055, -0.1401, -0.1303, -0.1250, -0.0782, 0.0256, -0.0353, -0.0636,\n -0.1507, -0.0458, -0.0501, -0.1421, -0.1441, -0.0515, -0.0035, -0.2482,\n -0.1008, -0.1152, -0.1105, 0.0816, -0.1049, -0.0535, -0.0836, -0.1418,\n -0.1016, 0.0125, -0.0233, -0.1405, -0.1218, -0.0680, -0.0174, -0.0031]), 'model.layer3.2.bn2.running_var': tensor([0.0142, 0.0113, 0.0183, 0.0131, 0.0218, 0.0197, 0.0232, 0.0150, 0.0114,\n 0.0173, 0.0172, 0.0178, 0.0203, 0.0114, 0.0143, 0.0190, 0.0163, 0.0130,\n 0.0211, 0.0140, 0.0261, 0.0204, 0.0173, 0.0168, 0.0175, 0.0219, 0.0139,\n 0.0129, 0.0252, 0.0152, 0.0156, 0.0287, 0.0181, 0.0363, 0.0212, 0.0189,\n 0.0245, 0.0160, 0.0240, 0.0327, 0.0234, 0.0192, 0.0144, 0.0177, 0.0100,\n 0.0222, 0.0260, 0.0157, 0.0197, 0.0162, 0.0175, 0.0097, 0.0127, 0.0176,\n 0.0148, 0.0299, 0.0164, 0.0170, 0.0170, 0.0166, 0.0198, 0.0116, 0.0147,\n 0.0173, 0.0277, 0.0129, 0.0235, 0.0115, 0.0135, 0.0162, 0.0163, 0.0144,\n 0.0158, 0.0169, 0.0206, 0.0241, 0.0185, 0.0309, 0.0235, 0.0158, 0.0239,\n 0.0126, 0.0187, 0.0167, 0.0156, 0.0249, 0.0162, 0.0145, 0.0232, 0.0124,\n 0.0168, 0.0122, 0.0240, 0.0205, 0.0340, 0.0138, 0.0115, 0.0208, 0.0174,\n 0.0145, 0.0163, 0.0203, 0.0147, 0.0194, 0.0221, 0.0141, 0.0195, 0.0134,\n 0.0100, 0.0215, 0.0218, 0.0160, 0.0156, 0.0124, 0.0167, 0.0316, 0.0210,\n 0.0220, 0.0190, 0.0184, 0.0272, 0.0133, 0.0168, 0.0107, 0.0131, 0.0166,\n 0.0190, 0.0168, 0.0163, 0.0171, 0.0251, 0.0230, 0.0098, 0.0175, 0.0191,\n 0.0168, 0.0173, 0.0226, 0.0155, 0.0239, 0.0166, 0.0264, 0.0216, 0.0159,\n 0.0146, 0.0201, 0.0141, 0.0221, 0.0171, 0.0147, 0.0356, 0.0173, 0.0284,\n 0.0133, 0.0150, 0.0136, 0.0279, 0.0148, 0.0169, 0.0218, 0.0346, 0.0175,\n 0.0174, 0.0146, 0.0125, 0.0154, 0.0197, 0.0251, 0.0209, 0.0163, 0.0150,\n 0.0218, 0.0115, 0.0187, 0.0213, 0.0178, 0.0294, 0.0194, 0.0197, 0.0177,\n 0.0163, 0.0175, 0.0198, 0.0135, 0.0209, 0.0148, 0.0153, 0.0142, 0.0436,\n 0.0156, 0.0125, 0.0199, 0.0176, 0.0132, 0.0099, 0.0322, 0.0151, 0.0195,\n 0.0133, 0.0171, 0.0291, 0.0236, 0.0188, 0.0189, 0.0143, 0.0193, 0.0217,\n 0.0297, 0.0221, 0.0185, 0.0234, 0.0142, 0.0240, 0.0201, 0.0178, 0.0151,\n 0.0242, 0.0347, 0.0237, 0.0138, 0.0198, 0.0162, 0.0132, 0.0227, 0.0176,\n 0.0125, 0.0223, 0.0142, 0.0126, 0.0202, 0.0143, 0.0217, 0.0325, 0.0157,\n 0.0143, 0.0214, 0.0230, 0.0196, 0.0157, 0.0352, 0.0176, 0.0146, 0.0155,\n 0.0113, 0.0230, 0.0174, 0.0256, 0.0229, 0.0173, 0.0192, 0.0207, 0.0182,\n 0.0168, 0.0184, 0.0204, 0.0281]), 'model.layer3.2.bn2.num_batches_tracked': tensor(7160), 'model.layer3.2.conv3.weight': tensor([[[[-0.0190]],\n\n [[ 0.0131]],\n\n [[ 0.0199]],\n\n ...,\n\n [[-0.0411]],\n\n [[ 0.0090]],\n\n [[-0.0071]]],\n\n\n [[[-0.0158]],\n\n [[-0.0097]],\n\n [[-0.0082]],\n\n ...,\n\n [[ 0.0301]],\n\n [[-0.0097]],\n\n [[-0.0150]]],\n\n\n [[[ 0.0147]],\n\n [[ 0.0045]],\n\n [[-0.0190]],\n\n ...,\n\n [[-0.0184]],\n\n [[ 0.0137]],\n\n [[ 0.0242]]],\n\n\n ...,\n\n\n [[[-0.0344]],\n\n [[ 0.0478]],\n\n [[ 0.0119]],\n\n ...,\n\n [[-0.0138]],\n\n [[ 0.0103]],\n\n [[ 0.0331]]],\n\n\n [[[-0.0149]],\n\n [[-0.0374]],\n\n [[-0.0077]],\n\n ...,\n\n [[-0.0006]],\n\n [[-0.0105]],\n\n [[ 0.0189]]],\n\n\n [[[ 0.0216]],\n\n [[ 0.0045]],\n\n [[-0.0096]],\n\n ...,\n\n [[ 0.0164]],\n\n [[ 0.0006]],\n\n [[-0.0269]]]]), 'model.layer3.2.bn3.weight': tensor([0.0845, 0.0824, 0.1260, ..., 0.0980, 0.0470, 0.0347]), 'model.layer3.2.bn3.bias': tensor([ 0.0713, -0.0604, -0.0162, ..., -0.0551, -0.0700, -0.0191]), 'model.layer3.2.bn3.running_mean': tensor([ 0.0163, -0.0305, 0.0036, ..., 0.0275, -0.0351, -0.0248]), 'model.layer3.2.bn3.running_var': tensor([0.0020, 0.0007, 0.0014, ..., 0.0013, 0.0006, 0.0009]), 'model.layer3.2.bn3.num_batches_tracked': tensor(7160), 'model.layer3.3.conv1.weight': tensor([[[[-1.4748e-02]],\n\n [[-1.1505e-02]],\n\n [[ 7.3245e-04]],\n\n ...,\n\n [[-2.9082e-02]],\n\n [[ 1.9636e-02]],\n\n [[-2.1509e-02]]],\n\n\n [[[ 2.9671e-03]],\n\n [[-1.0272e-02]],\n\n [[ 5.3477e-03]],\n\n ...,\n\n [[-7.4352e-03]],\n\n [[-2.9809e-02]],\n\n [[ 7.4780e-03]]],\n\n\n [[[-1.1603e-05]],\n\n [[-2.6583e-03]],\n\n [[ 4.2660e-04]],\n\n ...,\n\n [[-4.3425e-03]],\n\n [[-1.5210e-02]],\n\n [[-9.6861e-03]]],\n\n\n ...,\n\n\n [[[-1.3291e-02]],\n\n [[-6.5603e-03]],\n\n [[ 4.7479e-02]],\n\n ...,\n\n [[ 3.7532e-02]],\n\n [[-6.9250e-03]],\n\n [[ 3.4381e-02]]],\n\n\n [[[-9.9679e-03]],\n\n [[-8.8720e-03]],\n\n [[ 2.5375e-02]],\n\n ...,\n\n [[-6.6345e-03]],\n\n [[-1.1369e-02]],\n\n [[-6.1739e-03]]],\n\n\n [[[ 1.3063e-02]],\n\n [[ 1.4979e-02]],\n\n [[ 3.4726e-03]],\n\n ...,\n\n [[ 5.2537e-03]],\n\n [[-6.4699e-03]],\n\n [[-7.5372e-04]]]]), 'model.layer3.3.bn1.weight': tensor([0.2230, 0.1771, 0.1851, 0.1687, 0.2091, 0.2045, 0.1909, 0.1764, 0.1909,\n 0.1765, 0.1954, 0.1256, 0.1714, 0.2070, 0.1507, 0.1388, 0.1384, 0.1819,\n 0.1587, 0.1692, 0.1593, 0.1952, 0.0934, 0.1619, 0.1580, 0.1984, 0.2093,\n 0.1670, 0.1423, 0.1813, 0.1492, 0.1752, 0.1511, 0.1512, 0.1163, 0.1553,\n 0.1236, 0.1603, 0.0968, 0.1426, 0.1945, 0.1903, 0.1606, 0.1309, 0.2022,\n 0.1866, 0.2110, 0.1404, 0.1372, 0.1230, 0.2123, 0.1276, 0.1562, 0.1833,\n 0.1463, 0.1626, 0.1479, 0.1321, 0.1745, 0.1852, 0.1622, 0.1464, 0.1093,\n 0.1853, 0.1173, 0.1476, 0.1841, 0.1019, 0.2074, 0.1314, 0.1614, 0.1856,\n 0.1722, 0.1510, 0.1692, 0.1855, 0.1442, 0.1325, 0.1686, 0.1614, 0.1663,\n 0.1443, 0.1641, 0.1958, 0.1684, 0.1356, 0.1732, 0.1142, 0.2089, 0.1868,\n 0.1836, 0.1494, 0.1132, 0.1500, 0.1992, 0.1733, 0.1723, 0.1082, 0.1794,\n 0.1806, 0.1985, 0.1818, 0.1722, 0.1693, 0.1177, 0.2021, 0.1176, 0.1466,\n 0.1634, 0.1806, 0.2295, 0.1537, 0.1753, 0.1314, 0.2172, 0.1478, 0.1087,\n 0.1561, 0.1653, 0.1277, 0.1701, 0.1972, 0.1784, 0.1986, 0.1653, 0.1445,\n 0.1739, 0.1653, 0.1749, 0.1818, 0.1832, 0.1781, 0.1536, 0.1186, 0.1362,\n 0.1880, 0.1478, 0.1831, 0.1605, 0.1774, 0.1822, 0.1389, 0.1175, 0.1343,\n 0.1232, 0.1464, 0.1960, 0.1790, 0.1780, 0.1527, 0.1550, 0.1637, 0.2051,\n 0.1372, 0.1660, 0.1519, 0.1313, 0.1432, 0.1531, 0.2279, 0.2070, 0.1596,\n 0.0944, 0.1861, 0.1878, 0.1229, 0.1742, 0.2189, 0.1091, 0.1912, 0.1644,\n 0.1642, 0.1854, 0.2110, 0.1548, 0.1545, 0.1148, 0.1589, 0.1688, 0.1740,\n 0.1824, 0.1677, 0.1445, 0.2033, 0.1344, 0.1872, 0.1904, 0.2266, 0.1302,\n 0.1421, 0.1608, 0.1562, 0.1618, 0.1642, 0.1688, 0.1808, 0.1856, 0.1822,\n 0.1808, 0.1527, 0.1286, 0.1491, 0.1247, 0.1448, 0.1309, 0.1645, 0.1617,\n 0.1689, 0.2238, 0.1546, 0.1704, 0.2274, 0.1423, 0.1718, 0.2248, 0.1538,\n 0.1305, 0.1852, 0.1391, 0.2100, 0.2056, 0.1471, 0.1649, 0.1294, 0.1480,\n 0.1428, 0.1732, 0.1874, 0.1725, 0.1928, 0.1723, 0.1843, 0.2377, 0.1468,\n 0.1410, 0.0990, 0.1677, 0.1432, 0.1764, 0.1187, 0.1804, 0.1392, 0.1226,\n 0.1084, 0.1551, 0.1628, 0.2486, 0.1922, 0.1956, 0.1330, 0.1692, 0.1159,\n 0.1437, 0.1767, 0.1635, 0.1667]), 'model.layer3.3.bn1.bias': tensor([-0.1521, -0.1046, -0.1337, -0.1307, -0.1559, -0.1693, -0.1126, -0.1195,\n -0.1022, -0.0493, -0.1797, 0.0472, -0.0743, -0.1899, -0.0827, -0.0518,\n -0.0314, -0.1336, -0.0741, -0.0714, -0.0879, -0.1659, 0.0709, -0.1174,\n -0.1530, -0.1279, -0.1603, -0.1089, -0.0283, -0.1911, 0.0003, -0.1515,\n -0.0479, -0.0578, -0.0173, -0.0329, -0.0108, -0.0831, 0.0612, -0.0321,\n -0.1559, -0.1705, -0.0558, -0.0306, -0.1769, -0.1211, -0.1469, -0.0111,\n 0.0306, -0.0099, -0.0919, -0.0419, -0.0477, -0.1170, -0.0523, -0.0944,\n -0.0528, 0.0032, -0.1471, -0.1152, -0.1142, -0.0350, 0.0364, -0.1285,\n 0.0444, -0.0240, -0.1001, 0.0235, -0.1100, 0.0008, -0.1058, -0.1163,\n -0.0638, -0.0697, -0.0744, -0.1292, -0.0409, 0.0039, -0.0885, -0.1356,\n -0.1171, -0.0480, -0.0406, -0.1703, -0.0866, -0.0066, -0.0790, 0.0057,\n -0.0400, -0.1475, -0.1430, -0.0083, 0.0290, -0.0209, -0.1243, -0.1308,\n -0.0827, 0.0948, -0.1177, -0.0777, -0.1856, -0.0918, -0.0682, -0.0758,\n -0.0070, -0.1306, -0.0005, -0.0201, -0.1204, -0.0591, -0.1940, -0.0378,\n -0.0878, 0.0662, -0.2446, -0.0060, 0.0841, -0.1264, -0.1367, -0.0305,\n -0.1564, -0.1094, -0.1223, -0.1630, -0.1138, -0.0112, -0.0775, -0.0945,\n -0.0475, -0.1004, -0.0702, -0.1302, -0.0646, 0.0081, 0.0098, -0.1098,\n -0.0924, -0.1349, -0.0961, -0.1068, -0.1023, 0.0148, 0.0392, -0.0453,\n 0.0150, -0.0673, -0.2044, -0.0637, -0.0916, -0.0863, -0.0732, -0.0832,\n -0.2283, -0.0421, -0.0608, -0.0902, -0.0122, -0.0080, -0.1204, -0.2222,\n -0.2343, -0.0430, 0.0686, -0.1021, -0.1214, 0.0406, -0.0761, -0.2643,\n 0.0737, -0.1689, -0.1090, -0.0763, -0.1101, -0.1675, -0.0869, -0.0687,\n 0.0590, -0.0309, -0.1208, -0.1201, -0.1133, -0.1199, -0.0385, -0.2012,\n 0.0555, -0.0843, -0.1240, -0.1176, -0.0082, -0.0518, -0.1042, -0.0908,\n -0.0747, -0.0847, -0.1340, -0.1412, -0.0981, -0.1408, -0.1267, -0.0635,\n -0.0749, -0.0468, -0.0632, -0.0833, 0.0041, -0.1232, -0.0968, -0.0406,\n -0.1405, -0.0995, -0.0665, -0.2578, -0.0477, -0.1512, -0.1639, -0.0389,\n -0.0404, -0.1484, -0.0264, -0.1487, -0.2500, -0.0101, -0.0876, 0.0208,\n -0.0763, 0.0221, -0.1159, -0.1705, -0.1351, -0.1263, -0.1713, -0.1680,\n -0.1107, -0.0184, -0.0120, 0.0976, -0.1104, 0.0016, -0.1037, 0.0285,\n -0.1459, 0.0485, -0.0194, -0.0045, -0.0953, -0.0659, -0.2020, -0.0874,\n -0.1377, 0.1371, -0.1093, 0.0451, -0.1390, -0.0888, -0.1741, -0.0806]), 'model.layer3.3.bn1.running_mean': tensor([-2.0994e-01, -1.7017e-02, -1.8777e-01, -1.4549e-02, 1.6976e-03,\n 1.5225e-02, -1.1168e-01, -5.8104e-02, -1.7863e-02, -1.2443e-01,\n -8.3952e-02, -1.4578e-01, -4.3441e-02, -1.4516e-02, -1.0781e-01,\n -1.2927e-01, -2.0768e-02, -1.1622e-01, -7.7563e-02, -3.8356e-02,\n -2.4538e-02, -9.8626e-03, -1.6425e-01, -8.9123e-02, -3.3558e-02,\n 3.7517e-02, -1.4362e-01, -7.6755e-02, -9.9911e-02, 3.7584e-02,\n -1.9686e-01, 6.8028e-03, -4.7946e-02, -8.3725e-02, -1.2201e-01,\n -7.5749e-02, -6.6004e-02, -5.5867e-02, -2.1954e-02, -9.2815e-02,\n 2.2383e-02, 5.5853e-02, -1.6485e-02, -7.7501e-02, -8.5913e-02,\n 2.0891e-02, -8.8119e-02, -1.1880e-01, -1.8731e-01, -8.1871e-02,\n 6.2424e-03, -6.9299e-02, -1.8406e-02, -9.1085e-02, -4.1212e-02,\n -1.0293e-01, -5.1964e-02, -6.2360e-02, -9.2388e-02, -9.8250e-02,\n -6.2444e-02, -1.6084e-02, -2.0068e-02, -4.0856e-02, -4.1856e-02,\n -8.7391e-02, -2.1869e-01, -1.3481e-02, -2.1664e-01, -6.7760e-02,\n -7.3026e-02, -4.9729e-02, -5.3162e-02, 2.4753e-02, 1.6386e-01,\n -5.8194e-02, -3.1337e-03, -4.7780e-02, -3.7436e-02, -5.0130e-02,\n 5.2752e-02, -4.2576e-02, -5.1188e-02, -8.4672e-02, -4.1499e-02,\n -1.5912e-01, -1.3182e-01, -1.1867e-01, -1.9282e-01, -1.9171e-01,\n -4.6347e-02, -9.6401e-02, -1.4754e-01, -1.5113e-01, -1.3396e-01,\n -7.4984e-02, -3.5931e-03, 7.0416e-03, -9.6945e-02, -1.0502e-01,\n -8.6613e-03, -7.8221e-02, -8.1605e-02, -2.4143e-02, -6.3758e-02,\n -1.9403e-01, 7.0240e-05, -1.3542e-01, -1.2331e-01, -2.1742e-02,\n 1.1809e-01, -4.3927e-03, -6.3989e-02, 1.0988e-02, -1.3040e-01,\n -5.8706e-02, -6.3204e-02, -2.3737e-02, -8.6001e-02, -4.1259e-02,\n -5.9971e-02, -1.3425e-01, -6.5866e-02, -7.0258e-02, -1.8860e-04,\n -2.3928e-02, 1.4353e-01, 1.0490e-02, -3.0257e-02, -1.3700e-01,\n -9.2700e-02, -5.7785e-02, -1.7856e-01, -4.2441e-02, -1.0634e-01,\n -6.9131e-02, -5.7655e-02, 8.2801e-03, -1.2430e-01, -1.3875e-01,\n -6.1067e-02, -1.3111e-02, -3.7281e-02, -4.4426e-03, -7.6528e-02,\n 1.8822e-02, -8.1393e-02, -4.7143e-02, -7.8277e-02, -4.9122e-02,\n -3.6563e-02, -6.6624e-02, -6.1109e-02, 7.5402e-03, 1.8981e-02,\n 2.5346e-02, -5.7557e-02, 1.6601e-02, -4.4523e-02, 7.5034e-02,\n -4.2467e-02, -2.5253e-02, -1.4761e-01, -4.9911e-02, -6.7154e-02,\n -1.9534e-01, -1.1974e-02, -4.4894e-02, -8.6933e-02, -9.2509e-02,\n -1.1038e-01, 4.1586e-02, -8.9247e-02, -1.0075e-01, -2.8303e-02,\n -4.7039e-02, -6.6748e-02, -1.5820e-01, -2.8402e-02, -6.5652e-02,\n -3.1098e-02, 1.8184e-02, -1.1681e-02, -2.0322e-02, -1.0131e-01,\n -7.2304e-02, -5.7962e-02, -6.4334e-02, -1.2199e-01, -2.1278e-02,\n -7.4468e-02, -5.6926e-02, -1.3558e-01, -6.9798e-02, 2.6943e-02,\n 4.9680e-02, -1.6797e-01, -9.3198e-02, -4.2223e-02, 1.2281e-02,\n -4.7707e-02, -2.0603e-02, 3.6221e-03, -7.1412e-02, -2.5432e-02,\n -1.9389e-01, 6.4551e-02, 3.7614e-02, -2.0644e-01, -5.4203e-02,\n -1.3032e-01, 4.4911e-02, -6.0575e-02, -7.3366e-02, -3.2163e-02,\n -5.8144e-02, 1.0998e-02, -6.5652e-02, -1.4475e-01, -1.5265e-01,\n -9.1352e-02, -4.3609e-02, 2.8141e-02, -6.1721e-02, -9.0328e-02,\n -5.6840e-02, 4.9744e-02, -7.3142e-02, -4.1434e-02, 4.2591e-02,\n 4.4700e-02, -9.6153e-02, 4.2078e-02, -1.4260e-01, -2.4038e-02,\n -3.5264e-02, -3.3413e-02, 4.0140e-03, -2.2800e-02, -1.8500e-01,\n -3.1972e-02, -6.9361e-02, -1.1710e-01, 4.4737e-03, -4.0703e-02,\n -1.3392e-02, -1.9104e-02, -7.1219e-02, -1.2047e-01, -4.2012e-02,\n -7.6491e-02, -5.4312e-02, -5.7382e-02, 1.1160e-01, -8.2298e-02,\n -5.0604e-02]), 'model.layer3.3.bn1.running_var': tensor([0.0156, 0.0164, 0.0203, 0.0162, 0.0296, 0.0207, 0.0218, 0.0307, 0.0465,\n 0.0221, 0.0165, 0.0251, 0.0247, 0.0164, 0.0144, 0.0222, 0.0120, 0.0154,\n 0.0165, 0.0153, 0.0220, 0.0241, 0.0309, 0.0165, 0.0138, 0.0329, 0.0196,\n 0.0114, 0.0258, 0.0281, 0.0233, 0.0137, 0.0184, 0.0186, 0.0149, 0.0229,\n 0.0145, 0.0193, 0.0247, 0.0203, 0.0142, 0.0243, 0.0174, 0.0137, 0.0157,\n 0.0170, 0.0150, 0.0224, 0.0326, 0.0187, 0.0601, 0.0146, 0.0254, 0.0170,\n 0.0156, 0.0195, 0.0221, 0.0193, 0.0158, 0.0151, 0.0156, 0.0240, 0.0229,\n 0.0214, 0.0268, 0.0213, 0.0294, 0.0164, 0.0259, 0.0237, 0.0224, 0.0171,\n 0.0301, 0.0174, 0.0264, 0.0128, 0.0219, 0.0187, 0.0186, 0.0161, 0.0129,\n 0.0157, 0.0220, 0.0227, 0.0175, 0.0225, 0.0205, 0.0155, 0.0295, 0.0215,\n 0.0116, 0.0223, 0.0252, 0.0244, 0.0203, 0.0177, 0.0197, 0.0265, 0.0149,\n 0.0207, 0.0249, 0.0209, 0.0265, 0.0219, 0.0135, 0.0185, 0.0187, 0.0147,\n 0.0204, 0.0341, 0.0290, 0.0222, 0.0141, 0.0383, 0.0133, 0.0254, 0.0222,\n 0.0117, 0.0209, 0.0180, 0.0113, 0.0226, 0.0171, 0.0197, 0.0163, 0.0218,\n 0.0221, 0.0163, 0.0168, 0.0159, 0.0342, 0.0279, 0.0177, 0.0203, 0.0223,\n 0.0217, 0.0168, 0.0260, 0.0155, 0.0194, 0.0355, 0.0166, 0.0282, 0.0198,\n 0.0194, 0.0149, 0.0122, 0.0163, 0.0187, 0.0171, 0.0254, 0.0192, 0.0177,\n 0.0138, 0.0209, 0.0165, 0.0221, 0.0276, 0.0168, 0.0387, 0.0175, 0.0182,\n 0.0174, 0.0217, 0.0191, 0.0168, 0.0165, 0.0150, 0.0265, 0.0173, 0.0154,\n 0.0170, 0.0136, 0.0181, 0.0179, 0.0173, 0.0238, 0.0182, 0.0147, 0.0192,\n 0.0155, 0.0126, 0.0202, 0.0093, 0.0375, 0.0472, 0.0256, 0.0308, 0.0169,\n 0.0162, 0.0189, 0.0217, 0.0276, 0.0214, 0.0149, 0.0188, 0.0250, 0.0148,\n 0.0179, 0.0202, 0.0140, 0.0206, 0.0145, 0.0149, 0.0172, 0.0191, 0.0206,\n 0.0169, 0.0173, 0.0150, 0.0195, 0.0184, 0.0168, 0.0124, 0.0084, 0.0177,\n 0.0142, 0.0205, 0.0202, 0.0193, 0.0140, 0.0237, 0.0131, 0.0202, 0.0168,\n 0.0211, 0.0117, 0.0137, 0.0159, 0.0296, 0.0239, 0.0127, 0.0497, 0.0137,\n 0.0149, 0.0321, 0.0139, 0.0239, 0.0199, 0.0224, 0.0133, 0.0405, 0.0204,\n 0.0199, 0.0192, 0.0176, 0.0231, 0.0214, 0.0148, 0.0641, 0.0171, 0.0193,\n 0.0130, 0.0312, 0.0165, 0.0159]), 'model.layer3.3.bn1.num_batches_tracked': tensor(7160), 'model.layer3.3.conv2.weight': tensor([[[[-3.1331e-02, -1.8715e-02, -2.7718e-02],\n [ 9.8236e-03, 3.4269e-02, 3.8114e-03],\n [-1.2395e-03, 2.1366e-02, 1.6281e-02]],\n\n [[-5.2711e-04, -2.1085e-02, -2.2934e-02],\n [-3.0657e-02, -3.1927e-02, -2.9223e-02],\n [-6.0701e-03, -3.0766e-02, -1.6632e-02]],\n\n [[-2.0010e-02, -2.4492e-02, -1.6116e-02],\n [-3.9567e-02, -2.6315e-02, 8.9784e-03],\n [-3.9538e-02, -3.9675e-02, 4.7809e-03]],\n\n ...,\n\n [[ 1.8792e-02, -1.8121e-03, 1.2338e-02],\n [-2.6748e-03, -1.4203e-02, -8.4663e-03],\n [-1.9101e-02, 2.0241e-02, -9.9877e-03]],\n\n [[-4.4267e-03, -9.9311e-03, -7.4826e-03],\n [-1.1726e-02, -8.4689e-03, -1.9819e-02],\n [ 2.6708e-03, 1.1296e-02, 1.6388e-03]],\n\n [[-7.4953e-03, -1.2406e-02, -1.5981e-02],\n [ 6.2670e-03, 1.3663e-03, -6.5698e-03],\n [ 1.4895e-02, 1.6250e-02, 1.1057e-02]]],\n\n\n [[[ 1.1312e-02, 2.2892e-02, 1.6327e-02],\n [-1.6783e-03, -3.2349e-03, 8.1633e-03],\n [-7.2072e-03, 1.0239e-02, 8.8935e-03]],\n\n [[-7.1156e-03, 3.6572e-03, 3.7485e-03],\n [ 6.9458e-03, 1.3660e-02, 1.5479e-02],\n [ 1.3668e-02, 1.3920e-02, 1.3553e-02]],\n\n [[ 2.4006e-03, 1.2653e-02, 1.0310e-02],\n [-1.5488e-03, 1.1477e-02, 1.8001e-02],\n [ 7.4584e-06, 7.9493e-03, 2.1277e-02]],\n\n ...,\n\n [[ 2.2767e-02, 5.3878e-02, 2.9870e-02],\n [ 3.5167e-03, -6.2672e-03, 6.2767e-03],\n [ 1.0765e-02, 1.3425e-02, 9.8281e-03]],\n\n [[-4.8974e-03, 2.0566e-02, 4.8253e-03],\n [-2.1751e-02, -1.9436e-02, -2.9716e-02],\n [-2.0757e-02, -2.6020e-02, -3.3166e-02]],\n\n [[-7.7381e-03, 2.9021e-03, -1.9051e-02],\n [-7.8912e-03, 2.6272e-02, -6.7302e-03],\n [-3.7173e-03, 3.7112e-03, -2.1971e-03]]],\n\n\n [[[ 9.1578e-03, 1.7036e-02, 5.7084e-03],\n [ 1.4496e-02, 1.1287e-02, -9.6969e-03],\n [-2.1141e-02, -2.5885e-02, -1.9025e-02]],\n\n [[-2.4777e-03, 1.3374e-02, -1.8411e-02],\n [ 8.6692e-04, 3.6528e-02, 1.6353e-03],\n [ 6.6738e-03, 1.5757e-02, -2.5163e-03]],\n\n [[ 2.5805e-03, -1.8246e-02, -3.1836e-02],\n [ 2.8876e-02, 2.7580e-02, -2.8498e-02],\n [-4.6805e-02, 3.1571e-02, 2.0666e-02]],\n\n ...,\n\n [[ 2.3283e-02, 2.4631e-02, 3.0100e-02],\n [ 2.0125e-02, -1.1327e-02, 1.4842e-02],\n [ 7.8862e-03, 5.0839e-03, -1.4554e-02]],\n\n [[-2.1567e-03, -4.6093e-04, 2.8822e-03],\n [-6.8318e-03, -3.5493e-03, -7.4119e-03],\n [-9.7986e-03, 4.8692e-03, -2.5393e-03]],\n\n [[ 1.3471e-03, -2.8637e-02, -6.5650e-03],\n [ 2.1205e-02, 3.2294e-02, 1.8393e-02],\n [ 1.4187e-02, 2.1916e-02, 1.1835e-02]]],\n\n\n ...,\n\n\n [[[ 3.9392e-03, 1.6087e-02, -9.8092e-03],\n [ 3.7981e-03, 1.3331e-02, -4.6766e-03],\n [-6.2335e-03, -1.6187e-03, -1.6636e-03]],\n\n [[-2.1576e-02, 9.4926e-03, 1.6733e-02],\n [ 2.5413e-02, 1.4385e-02, -1.0274e-02],\n [-2.8736e-03, -4.9533e-03, 8.4318e-03]],\n\n [[-2.5225e-02, 5.6688e-05, -1.4045e-02],\n [ 1.7526e-03, 4.3885e-04, 5.1353e-03],\n [ 7.4111e-03, 1.7880e-02, 1.0899e-02]],\n\n ...,\n\n [[ 1.0222e-02, 2.9590e-03, -1.3333e-02],\n [ 6.9976e-03, 1.9710e-02, -1.9716e-03],\n [ 6.4712e-05, 1.8693e-02, 3.0995e-02]],\n\n [[-9.8212e-03, -1.3951e-02, 5.1785e-03],\n [-4.3857e-03, -7.5492e-03, 1.3771e-02],\n [ 3.7444e-03, -1.0056e-02, -5.6159e-03]],\n\n [[ 7.4526e-03, -1.7778e-02, -1.1627e-02],\n [-1.8985e-02, -3.7321e-03, -6.2049e-04],\n [-7.3062e-03, -1.3635e-02, 6.1755e-03]]],\n\n\n [[[-1.4693e-02, -1.5463e-02, -1.4546e-02],\n [ 2.7727e-03, 1.7193e-03, -4.1141e-03],\n [ 1.2364e-02, -2.7759e-03, 2.3282e-03]],\n\n [[-5.4895e-03, -9.2234e-03, -1.8805e-02],\n [-1.0013e-02, -6.1178e-03, -1.0872e-02],\n [-1.0582e-03, 1.6569e-02, -5.3309e-03]],\n\n [[ 4.9018e-02, 8.7841e-03, -3.1071e-03],\n [ 2.4552e-02, 2.0851e-02, -1.1446e-02],\n [-8.8797e-03, -1.5200e-02, -2.6953e-02]],\n\n ...,\n\n [[ 1.5694e-02, 1.0961e-02, 1.0489e-02],\n [-4.2155e-03, 1.4291e-03, 1.4888e-02],\n [ 1.7123e-02, 3.3396e-02, 1.7221e-02]],\n\n [[-1.3751e-03, -8.2527e-03, -5.7071e-03],\n [-3.6276e-03, 1.0816e-03, 8.1855e-03],\n [-1.2234e-02, 7.5269e-03, -4.7416e-03]],\n\n [[-1.8575e-02, -1.4999e-02, -1.4652e-02],\n [-1.7099e-02, -8.8370e-03, -8.3645e-03],\n [ 4.4669e-03, 1.8526e-02, 2.1490e-03]]],\n\n\n [[[ 9.5108e-06, -2.6314e-02, 2.3612e-03],\n [ 2.4634e-03, -2.8208e-02, -5.0757e-03],\n [ 4.9386e-03, -1.5689e-02, 1.7642e-03]],\n\n [[-3.1788e-02, -2.2664e-02, -1.0704e-02],\n [-3.0826e-03, 1.0506e-02, -1.2678e-02],\n [ 5.3900e-03, -9.3914e-03, 3.1283e-03]],\n\n [[-2.4059e-03, -3.1932e-04, 2.8315e-02],\n [ 9.4020e-03, -9.3391e-03, 2.0109e-02],\n [ 3.0090e-03, -3.3906e-02, -1.9049e-02]],\n\n ...,\n\n [[ 4.4066e-04, -2.2272e-03, 3.7070e-03],\n [-4.5664e-03, -1.3327e-02, -1.1584e-02],\n [ 5.5896e-03, -3.3969e-03, -5.2814e-04]],\n\n [[-1.5602e-03, -3.9242e-03, -7.8692e-03],\n [-9.3419e-03, 4.5063e-03, 2.6920e-03],\n [-7.7899e-03, 9.7994e-03, 4.2765e-03]],\n\n [[ 4.9827e-03, 4.8096e-03, 8.6380e-04],\n [-6.8730e-03, -3.4426e-03, -1.9905e-03],\n [-8.0675e-04, 6.9949e-03, 1.1157e-02]]]]), 'model.layer3.3.bn2.weight': tensor([0.1194, 0.1590, 0.1085, 0.1931, 0.1269, 0.1685, 0.2110, 0.1183, 0.2008,\n 0.1686, 0.1325, 0.1839, 0.1705, 0.1207, 0.2141, 0.1686, 0.1543, 0.1768,\n 0.1867, 0.1724, 0.2026, 0.1782, 0.1922, 0.2131, 0.2020, 0.1707, 0.1602,\n 0.1771, 0.1179, 0.1680, 0.1452, 0.1921, 0.1915, 0.1707, 0.1924, 0.1769,\n 0.1399, 0.1527, 0.2000, 0.1653, 0.1600, 0.1876, 0.1281, 0.1450, 0.1690,\n 0.1702, 0.1498, 0.1267, 0.1852, 0.1640, 0.2055, 0.1074, 0.1657, 0.1976,\n 0.1605, 0.1716, 0.1891, 0.1930, 0.1639, 0.1986, 0.2063, 0.2155, 0.1999,\n 0.1665, 0.1793, 0.1209, 0.1881, 0.1755, 0.1884, 0.1831, 0.1709, 0.1560,\n 0.1644, 0.2010, 0.1924, 0.1637, 0.1455, 0.1118, 0.1988, 0.1410, 0.1966,\n 0.1667, 0.1661, 0.1028, 0.1762, 0.1856, 0.2235, 0.1700, 0.2289, 0.1733,\n 0.1831, 0.1361, 0.1610, 0.1657, 0.1193, 0.1152, 0.1058, 0.1284, 0.1670,\n 0.1925, 0.1643, 0.1977, 0.1501, 0.1630, 0.1742, 0.2315, 0.1751, 0.2403,\n 0.1652, 0.1802, 0.1938, 0.1605, 0.1782, 0.2137, 0.1562, 0.2547, 0.1789,\n 0.1786, 0.1733, 0.1797, 0.1333, 0.1695, 0.1382, 0.1371, 0.1494, 0.1687,\n 0.1739, 0.1679, 0.1827, 0.1887, 0.1916, 0.2107, 0.1695, 0.1808, 0.1438,\n 0.1786, 0.1776, 0.1347, 0.1795, 0.1462, 0.1573, 0.1700, 0.1337, 0.1923,\n 0.1373, 0.1328, 0.1805, 0.1381, 0.1980, 0.1730, 0.1511, 0.1655, 0.1833,\n 0.1864, 0.1850, 0.1921, 0.1621, 0.2100, 0.1766, 0.2088, 0.1085, 0.1657,\n 0.1551, 0.1723, 0.1537, 0.1649, 0.1352, 0.1508, 0.1807, 0.1801, 0.1668,\n 0.1800, 0.2189, 0.1736, 0.1477, 0.1697, 0.1267, 0.1750, 0.1586, 0.1707,\n 0.1602, 0.1884, 0.1928, 0.1821, 0.1464, 0.2378, 0.1648, 0.1514, 0.1917,\n 0.1967, 0.1945, 0.1329, 0.1542, 0.2106, 0.1702, 0.1135, 0.1949, 0.1750,\n 0.1978, 0.1762, 0.1757, 0.2126, 0.1430, 0.1691, 0.1896, 0.2097, 0.1671,\n 0.1646, 0.1736, 0.2175, 0.1888, 0.1443, 0.2009, 0.1791, 0.2017, 0.1984,\n 0.1503, 0.1438, 0.1890, 0.1403, 0.1689, 0.1592, 0.1785, 0.2641, 0.1755,\n 0.1705, 0.1558, 0.1928, 0.2036, 0.1315, 0.1817, 0.1697, 0.1520, 0.1587,\n 0.1966, 0.0948, 0.1844, 0.1154, 0.1839, 0.1356, 0.1662, 0.1989, 0.1874,\n 0.1741, 0.1914, 0.1302, 0.1519, 0.2163, 0.1759, 0.1771, 0.1900, 0.1644,\n 0.2614, 0.1840, 0.1964, 0.1814]), 'model.layer3.3.bn2.bias': tensor([ 0.0423, 0.0191, 0.0567, -0.1064, -0.0148, -0.0825, -0.1413, 0.0230,\n -0.0754, -0.0698, -0.0591, -0.0486, -0.0564, 0.0220, -0.1215, -0.0983,\n -0.0532, -0.0935, -0.0412, -0.0822, -0.1636, -0.0785, -0.0849, -0.1572,\n -0.0908, -0.1296, -0.0494, -0.0758, 0.0594, -0.0468, -0.0445, -0.1196,\n -0.0974, -0.0795, -0.1758, -0.0880, -0.0241, -0.0527, -0.1259, -0.0655,\n -0.0199, -0.0879, 0.0608, -0.0639, -0.0602, -0.0685, -0.0508, 0.0371,\n -0.1302, -0.0818, -0.1167, 0.0791, -0.1231, -0.1117, -0.0670, -0.1027,\n -0.0386, -0.1168, -0.0662, -0.1557, -0.1774, -0.1848, -0.0720, -0.0477,\n -0.0983, 0.0442, -0.1224, -0.1169, -0.0884, -0.0708, -0.1129, -0.1109,\n -0.0854, -0.0964, -0.1188, -0.0507, -0.0713, 0.0752, -0.1227, 0.0614,\n -0.0970, -0.0900, -0.0702, 0.1144, -0.0068, -0.0837, -0.1024, -0.0709,\n -0.0725, -0.0376, -0.0910, 0.0717, -0.0695, -0.0286, 0.0283, 0.1729,\n 0.0945, 0.0004, -0.0457, -0.0776, -0.0445, -0.1226, -0.0826, -0.0771,\n -0.0623, -0.0949, -0.0804, -0.0671, -0.0861, -0.0259, -0.1162, -0.1166,\n -0.0974, -0.1224, -0.0283, -0.1543, -0.1240, -0.0831, -0.0480, -0.1101,\n -0.0395, -0.0843, -0.0111, 0.0066, -0.0146, -0.0953, -0.1000, -0.0879,\n -0.1542, -0.1101, -0.1160, -0.1235, -0.0807, -0.0833, -0.0341, -0.0270,\n -0.1067, -0.0036, -0.1331, -0.0499, -0.0327, -0.0646, 0.0109, -0.1302,\n -0.0169, 0.0061, -0.0701, 0.0130, -0.1204, -0.0508, -0.0452, -0.0881,\n -0.1477, -0.1224, -0.0895, -0.1152, -0.1073, -0.1619, -0.0898, -0.0971,\n 0.1530, -0.0891, -0.0768, -0.1036, -0.0143, -0.0523, -0.0421, -0.0532,\n -0.1186, -0.0404, -0.0124, -0.1177, -0.0445, -0.0887, -0.0104, -0.1111,\n 0.1740, -0.0821, -0.1111, -0.0766, -0.0920, -0.1511, -0.1204, -0.0717,\n 0.0509, -0.1277, -0.0502, -0.0396, -0.0902, -0.1054, -0.1529, 0.0133,\n -0.0592, -0.1390, -0.1268, 0.0263, -0.0671, -0.0998, -0.2170, -0.0615,\n -0.1063, -0.0993, -0.0377, -0.0764, -0.1051, -0.0731, -0.0980, -0.1031,\n -0.0665, -0.1265, -0.1138, -0.0417, -0.1039, -0.1413, -0.1607, -0.1054,\n -0.0751, -0.0384, -0.1363, -0.0288, -0.0948, -0.0579, -0.0180, -0.1744,\n -0.1157, -0.0758, -0.0324, -0.0509, -0.1177, 0.1113, -0.1099, -0.1122,\n -0.0520, -0.0586, -0.0574, 0.1542, -0.1087, 0.0966, -0.1400, 0.0110,\n -0.0541, -0.1251, -0.1234, -0.0849, -0.1301, 0.0920, 0.0121, -0.1403,\n -0.0840, -0.0812, -0.0715, -0.0606, -0.1046, -0.0982, -0.1221, -0.1338]), 'model.layer3.3.bn2.running_mean': tensor([-5.1873e-02, -6.6369e-02, 1.1622e-02, -1.1689e-01, -7.1524e-02,\n -1.0917e-01, 5.5118e-02, 3.7443e-03, -8.8932e-02, -3.5182e-02,\n -1.1216e-01, -1.1369e-02, -6.4455e-03, -4.0261e-02, -6.4704e-02,\n -6.2793e-03, -8.9413e-02, -2.2292e-02, 1.7134e-02, -4.9229e-02,\n -6.1379e-02, -1.6901e-01, -5.5771e-02, -1.1429e-01, -1.6287e-01,\n -6.9383e-02, -5.4070e-02, -1.6421e-01, -6.7734e-02, -1.2998e-01,\n -5.2622e-02, -7.2890e-02, -5.0496e-02, -3.9140e-02, 1.4318e-02,\n 1.1283e-01, 2.1215e-02, 2.8079e-02, -1.0195e-01, -2.0062e-02,\n -8.5592e-02, -7.2247e-02, 1.0684e-01, -2.3283e-02, -1.3020e-02,\n 1.3392e-02, -1.1510e-01, 9.9121e-03, -2.0963e-02, -7.2127e-03,\n -1.1395e-01, 7.5302e-02, -4.6491e-02, -4.4804e-02, -9.3830e-02,\n -7.1347e-02, -6.9317e-02, -1.4551e-01, -6.1717e-02, -9.4379e-02,\n -1.3596e-01, -1.1756e-01, -8.6015e-02, 2.6347e-02, -9.1603e-02,\n 4.5116e-02, -4.9254e-02, -1.4005e-01, -7.6442e-02, -1.2555e-01,\n -6.5776e-02, -1.6245e-01, -7.8489e-02, -1.6175e-01, -1.4177e-01,\n 3.0219e-02, 3.2408e-02, 8.7985e-03, -1.1273e-02, -6.1654e-02,\n -1.0995e-01, -8.0552e-02, 1.7116e-01, 1.6725e-01, 8.9135e-03,\n -2.4086e-02, -1.7132e-01, -1.4414e-01, -8.8753e-02, -1.4457e-01,\n 6.0375e-03, 2.9481e-03, 2.7784e-02, -2.2672e-02, -6.3902e-02,\n 3.1684e-02, -1.0686e-01, -1.0509e-01, 5.8325e-03, -5.6847e-02,\n -4.1341e-02, -1.0282e-01, -4.6515e-02, -1.0707e-01, -1.3017e-01,\n -3.5042e-02, -5.9135e-02, -1.0199e-01, -7.9892e-02, 3.3459e-02,\n 3.4673e-04, -1.1669e-01, -3.3151e-02, 1.8532e-02, -1.1218e-01,\n 6.2800e-02, -1.2978e-01, 5.6782e-02, -2.3459e-02, 1.0364e-01,\n -5.1710e-02, -1.2124e-01, -1.6659e-02, -1.0655e-01, 4.8388e-02,\n -6.5504e-03, -8.8006e-02, 3.9415e-01, -1.6173e-02, -7.5004e-02,\n -1.0140e-01, -5.2301e-02, -7.4440e-02, -8.5791e-02, -1.7308e-01,\n 2.4193e-02, -3.2698e-02, -9.7651e-03, -6.8653e-02, -7.3553e-03,\n -7.5897e-02, -3.2931e-02, -5.9310e-02, 2.9499e-02, 6.0093e-02,\n -1.1524e-01, 4.0822e-02, -1.6018e-01, -4.0417e-02, -1.4140e-01,\n 3.6706e-03, -7.3187e-02, -5.4697e-02, -3.2743e-02, -8.9897e-02,\n -1.6513e-01, -6.0078e-02, -9.5500e-02, -1.0580e-01, -1.2680e-01,\n 6.7102e-02, 9.0303e-02, -6.7219e-02, -8.8425e-02, -3.7223e-02,\n 1.5360e-02, -2.8172e-02, -8.9768e-02, -1.2452e-02, 6.8743e-03,\n -8.8396e-02, -5.0100e-02, -9.9978e-02, -4.6776e-02, -1.1756e-01,\n -1.2389e-01, -1.0174e-01, -4.6471e-02, 2.6683e-03, -9.2664e-02,\n -3.5653e-02, -1.2835e-01, -4.0357e-02, -1.2106e-01, -1.0782e-01,\n -1.0054e-01, -1.0284e-01, -3.4341e-02, -3.0674e-02, -2.3580e-02,\n 1.5843e-01, -4.8470e-02, -1.3029e-01, -7.3551e-02, -4.4362e-02,\n -5.9819e-03, -1.8960e-02, -5.6322e-02, -8.3084e-02, -4.1870e-02,\n -6.4657e-02, -8.7466e-02, 2.4253e-02, 3.1761e-03, -1.8305e-01,\n -6.2150e-02, -2.6378e-02, -2.8306e-02, -5.9731e-02, 5.4533e-02,\n -3.3735e-02, -5.9574e-02, -9.9987e-02, -1.0205e-02, -2.2382e-02,\n -5.7927e-02, -1.1076e-01, 6.6406e-03, -6.6683e-02, -7.2671e-02,\n -8.9736e-02, 2.0933e-03, -1.2087e-01, -1.8363e-02, -9.8306e-02,\n -6.5535e-02, -9.1239e-02, -3.3566e-03, -1.2702e-01, 9.8216e-02,\n -5.1643e-02, -2.7968e-02, -1.0655e-01, -1.5508e-01, -4.0503e-02,\n 2.3746e-02, -1.2227e-01, -4.3544e-02, -4.3579e-02, -4.1443e-02,\n -2.9448e-02, -1.4360e-02, -8.1390e-02, 9.7566e-03, -1.0489e-01,\n 9.1270e-02, -6.9815e-02, -1.9057e-03, -8.1744e-02, 7.9392e-03,\n -2.9366e-02, -1.1107e-01, -4.0137e-02, -9.7140e-02, -3.3128e-02,\n -1.8862e-02]), 'model.layer3.3.bn2.running_var': tensor([0.0110, 0.0191, 0.0142, 0.0094, 0.0150, 0.0136, 0.0254, 0.0135, 0.0180,\n 0.0082, 0.0119, 0.0166, 0.0088, 0.0105, 0.0112, 0.0115, 0.0082, 0.0114,\n 0.0097, 0.0141, 0.0140, 0.0129, 0.0145, 0.0106, 0.0088, 0.0073, 0.0121,\n 0.0140, 0.0108, 0.0106, 0.0218, 0.0098, 0.0136, 0.0082, 0.0116, 0.0089,\n 0.0166, 0.0122, 0.0087, 0.0112, 0.0105, 0.0178, 0.0250, 0.0109, 0.0205,\n 0.0089, 0.0110, 0.0141, 0.0078, 0.0063, 0.0104, 0.0171, 0.0076, 0.0097,\n 0.0087, 0.0083, 0.0167, 0.0117, 0.0084, 0.0138, 0.0111, 0.0107, 0.0173,\n 0.0085, 0.0135, 0.0316, 0.0155, 0.0100, 0.0120, 0.0086, 0.0104, 0.0092,\n 0.0071, 0.0138, 0.0122, 0.0097, 0.0085, 0.0099, 0.0104, 0.0143, 0.0139,\n 0.0110, 0.0133, 0.0145, 0.0119, 0.0090, 0.0113, 0.0128, 0.0240, 0.0188,\n 0.0125, 0.0160, 0.0089, 0.0117, 0.0173, 0.0196, 0.0116, 0.0115, 0.0137,\n 0.0094, 0.0092, 0.0080, 0.0231, 0.0085, 0.0110, 0.0281, 0.0145, 0.0377,\n 0.0113, 0.0160, 0.0099, 0.0094, 0.0118, 0.0118, 0.0101, 0.0328, 0.0108,\n 0.0117, 0.0093, 0.0115, 0.0091, 0.0149, 0.0152, 0.0106, 0.0116, 0.0111,\n 0.0103, 0.0202, 0.0089, 0.0089, 0.0096, 0.0127, 0.0124, 0.0123, 0.0103,\n 0.0175, 0.0084, 0.0120, 0.0096, 0.0113, 0.0095, 0.0119, 0.0097, 0.0070,\n 0.0236, 0.0135, 0.0129, 0.0120, 0.0119, 0.0105, 0.0138, 0.0104, 0.0114,\n 0.0099, 0.0161, 0.0114, 0.0093, 0.0106, 0.0115, 0.0405, 0.0335, 0.0264,\n 0.0094, 0.0117, 0.0132, 0.0114, 0.0116, 0.0084, 0.0148, 0.0141, 0.0135,\n 0.0104, 0.0329, 0.0076, 0.0107, 0.0102, 0.0143, 0.0109, 0.0126, 0.0086,\n 0.0073, 0.0113, 0.0104, 0.0143, 0.0126, 0.0076, 0.0134, 0.0081, 0.0148,\n 0.0062, 0.0149, 0.0116, 0.0207, 0.0138, 0.0114, 0.0261, 0.0208, 0.0175,\n 0.0090, 0.0148, 0.0123, 0.0143, 0.0122, 0.0091, 0.0144, 0.0135, 0.0083,\n 0.0113, 0.0191, 0.0243, 0.0130, 0.0210, 0.0154, 0.0094, 0.0118, 0.0088,\n 0.0155, 0.0161, 0.0076, 0.0102, 0.0094, 0.0097, 0.0109, 0.0191, 0.0101,\n 0.0094, 0.0096, 0.0139, 0.0099, 0.0175, 0.0202, 0.0092, 0.0102, 0.0118,\n 0.0159, 0.0127, 0.0104, 0.0183, 0.0078, 0.0095, 0.0140, 0.0118, 0.0123,\n 0.0096, 0.0106, 0.0343, 0.0117, 0.0174, 0.0123, 0.0118, 0.0152, 0.0146,\n 0.0336, 0.0141, 0.0182, 0.0100]), 'model.layer3.3.bn2.num_batches_tracked': tensor(7160), 'model.layer3.3.conv3.weight': tensor([[[[ 3.3246e-05]],\n\n [[ 1.1131e-02]],\n\n [[-4.6239e-02]],\n\n ...,\n\n [[-7.3855e-03]],\n\n [[ 1.8520e-02]],\n\n [[-1.6319e-02]]],\n\n\n [[[-8.7212e-03]],\n\n [[ 3.0983e-02]],\n\n [[-2.5206e-02]],\n\n ...,\n\n [[ 2.8159e-02]],\n\n [[-2.5655e-02]],\n\n [[ 7.2692e-04]]],\n\n\n [[[-5.8591e-03]],\n\n [[-5.9408e-03]],\n\n [[ 1.3496e-02]],\n\n ...,\n\n [[ 2.7617e-02]],\n\n [[ 1.0018e-02]],\n\n [[ 3.3522e-03]]],\n\n\n ...,\n\n\n [[[ 1.5026e-02]],\n\n [[-3.4176e-02]],\n\n [[-2.5060e-03]],\n\n ...,\n\n [[ 3.8331e-03]],\n\n [[-3.0710e-02]],\n\n [[ 1.1094e-02]]],\n\n\n [[[ 3.0897e-03]],\n\n [[ 1.9267e-02]],\n\n [[-4.0650e-02]],\n\n ...,\n\n [[-7.3639e-03]],\n\n [[ 8.7486e-03]],\n\n [[-1.1630e-02]]],\n\n\n [[[-1.0613e-02]],\n\n [[-3.2397e-03]],\n\n [[-4.9836e-03]],\n\n ...,\n\n [[-5.0900e-04]],\n\n [[-5.3537e-03]],\n\n [[-7.4171e-03]]]]), 'model.layer3.3.bn3.weight': tensor([0.0318, 0.1313, 0.0991, ..., 0.1117, 0.0537, 0.0146]), 'model.layer3.3.bn3.bias': tensor([ 0.0062, -0.0517, -0.0944, ..., -0.0821, -0.0255, -0.0050]), 'model.layer3.3.bn3.running_mean': tensor([-0.0201, -0.0387, -0.0247, ..., -0.0247, 0.0089, -0.0002]), 'model.layer3.3.bn3.running_var': tensor([0.0009, 0.0014, 0.0014, ..., 0.0010, 0.0010, 0.0008]), 'model.layer3.3.bn3.num_batches_tracked': tensor(7160), 'model.layer3.4.conv1.weight': tensor([[[[-0.0369]],\n\n [[ 0.0313]],\n\n [[-0.0222]],\n\n ...,\n\n [[ 0.0092]],\n\n [[ 0.0150]],\n\n [[-0.0033]]],\n\n\n [[[ 0.0086]],\n\n [[-0.0089]],\n\n [[-0.0103]],\n\n ...,\n\n [[ 0.0116]],\n\n [[ 0.0045]],\n\n [[-0.0031]]],\n\n\n [[[-0.0267]],\n\n [[ 0.0108]],\n\n [[-0.0048]],\n\n ...,\n\n [[ 0.0188]],\n\n [[ 0.0111]],\n\n [[ 0.0011]]],\n\n\n ...,\n\n\n [[[-0.0076]],\n\n [[-0.0017]],\n\n [[ 0.0244]],\n\n ...,\n\n [[ 0.0160]],\n\n [[ 0.0117]],\n\n [[ 0.0079]]],\n\n\n [[[-0.0013]],\n\n [[-0.0059]],\n\n [[-0.0182]],\n\n ...,\n\n [[ 0.0297]],\n\n [[-0.0143]],\n\n [[ 0.0083]]],\n\n\n [[[-0.0106]],\n\n [[-0.0020]],\n\n [[-0.0062]],\n\n ...,\n\n [[-0.0193]],\n\n [[-0.0123]],\n\n [[-0.0006]]]]), 'model.layer3.4.bn1.weight': tensor([0.1276, 0.1822, 0.1411, 0.1512, 0.1589, 0.2100, 0.1788, 0.1921, 0.1501,\n 0.1454, 0.1523, 0.1956, 0.1208, 0.1984, 0.1608, 0.1776, 0.2204, 0.1589,\n 0.1482, 0.2058, 0.1649, 0.1582, 0.1742, 0.1549, 0.1723, 0.1312, 0.1895,\n 0.1785, 0.1426, 0.2004, 0.2083, 0.1391, 0.2028, 0.1626, 0.1461, 0.1706,\n 0.1131, 0.1260, 0.1728, 0.1456, 0.1834, 0.1485, 0.2031, 0.2295, 0.1634,\n 0.1583, 0.0932, 0.1573, 0.1546, 0.1691, 0.1369, 0.1186, 0.1384, 0.1839,\n 0.1667, 0.1781, 0.1750, 0.1574, 0.1287, 0.1325, 0.1758, 0.1267, 0.1397,\n 0.1940, 0.1478, 0.1745, 0.1144, 0.1492, 0.1875, 0.1364, 0.1672, 0.1618,\n 0.1218, 0.1414, 0.2069, 0.1464, 0.1856, 0.1528, 0.1337, 0.1449, 0.1333,\n 0.1915, 0.1874, 0.1980, 0.1541, 0.1750, 0.2300, 0.2036, 0.1161, 0.1766,\n 0.1608, 0.2177, 0.1907, 0.1178, 0.1356, 0.2539, 0.1058, 0.1187, 0.1001,\n 0.1380, 0.2392, 0.1359, 0.1673, 0.1626, 0.1524, 0.1614, 0.1564, 0.1567,\n 0.1525, 0.1514, 0.1805, 0.1686, 0.1633, 0.1083, 0.2729, 0.2032, 0.1571,\n 0.2047, 0.1643, 0.1361, 0.1724, 0.1856, 0.1681, 0.1703, 0.1870, 0.1194,\n 0.1739, 0.1741, 0.2456, 0.1793, 0.1304, 0.1539, 0.1577, 0.1285, 0.1749,\n 0.2690, 0.2077, 0.1365, 0.1630, 0.1859, 0.2044, 0.1286, 0.1490, 0.1644,\n 0.1545, 0.1116, 0.2445, 0.1721, 0.1876, 0.1446, 0.1295, 0.1432, 0.1502,\n 0.1838, 0.1825, 0.1693, 0.1749, 0.2003, 0.1811, 0.1386, 0.1539, 0.1958,\n 0.1195, 0.1692, 0.1449, 0.1809, 0.1242, 0.1317, 0.1961, 0.1729, 0.1574,\n 0.1704, 0.1763, 0.2014, 0.1347, 0.1716, 0.1584, 0.1807, 0.2046, 0.1975,\n 0.1400, 0.1130, 0.1993, 0.1764, 0.2083, 0.1400, 0.2103, 0.1611, 0.1380,\n 0.2047, 0.2119, 0.1839, 0.1554, 0.1524, 0.1453, 0.1252, 0.1899, 0.1403,\n 0.1237, 0.1795, 0.1615, 0.2183, 0.1682, 0.1983, 0.1579, 0.1571, 0.1706,\n 0.1772, 0.1724, 0.1702, 0.1616, 0.1595, 0.2538, 0.1533, 0.1229, 0.1510,\n 0.1801, 0.1490, 0.1453, 0.1566, 0.1624, 0.2018, 0.1319, 0.1123, 0.1303,\n 0.1454, 0.1415, 0.1821, 0.1342, 0.1272, 0.1291, 0.1588, 0.2283, 0.2189,\n 0.1905, 0.2348, 0.1609, 0.1502, 0.1695, 0.1713, 0.1469, 0.1619, 0.1799,\n 0.1447, 0.1719, 0.1857, 0.1985, 0.1590, 0.1622, 0.1916, 0.1361, 0.1834,\n 0.1955, 0.1673, 0.1537, 0.2409]), 'model.layer3.4.bn1.bias': tensor([-0.0004, -0.0710, -0.0169, -0.0671, -0.0658, -0.2575, -0.1832, -0.1463,\n -0.0718, -0.0936, -0.1319, -0.1481, 0.0585, -0.0824, -0.1298, -0.1603,\n -0.1767, -0.0393, -0.0025, -0.1601, -0.1329, -0.1306, -0.0548, -0.0673,\n -0.0991, -0.0169, -0.1550, -0.1373, -0.0427, -0.1444, -0.1042, -0.0478,\n -0.1796, -0.1339, -0.0213, -0.0959, -0.0084, 0.0188, -0.0599, -0.0978,\n -0.2090, -0.0336, -0.1404, -0.1454, -0.1140, -0.1321, 0.0420, -0.0867,\n -0.0997, -0.1080, 0.0003, -0.0326, -0.0315, -0.1662, -0.0942, -0.1773,\n -0.0237, -0.0601, -0.0275, -0.0212, -0.1409, 0.0041, -0.0416, -0.1427,\n -0.0695, -0.0869, 0.0103, 0.0063, -0.1778, -0.0258, -0.1004, -0.0949,\n -0.0444, -0.0592, -0.1192, -0.0254, -0.1695, -0.0528, 0.0567, -0.0399,\n -0.0280, -0.0939, -0.1889, -0.1577, -0.0940, -0.1018, -0.1617, -0.1754,\n 0.0363, -0.1696, -0.0923, -0.1567, -0.1550, 0.0969, -0.0399, -0.2684,\n 0.0790, -0.0326, 0.1312, -0.1483, -0.3306, -0.0502, -0.1628, -0.1104,\n -0.1014, -0.0794, -0.0648, -0.1392, -0.0908, -0.0480, -0.1742, -0.1623,\n 0.0010, -0.0089, -0.3161, -0.0909, -0.0820, -0.1395, -0.0424, 0.0709,\n -0.1246, -0.1366, -0.1299, -0.1146, -0.0851, -0.0260, -0.1104, -0.0647,\n -0.1757, -0.1187, -0.0449, -0.0947, -0.0150, 0.0113, -0.1232, -0.2351,\n -0.0876, -0.0123, -0.0498, -0.0922, -0.1567, -0.0280, -0.0201, -0.1439,\n -0.0405, 0.0977, -0.3158, -0.1473, -0.1020, -0.0343, -0.0067, -0.0664,\n -0.0772, -0.1814, -0.0814, -0.1202, -0.1210, -0.2386, -0.1086, 0.0294,\n -0.0918, -0.1198, -0.0018, -0.0593, -0.0674, -0.1514, 0.0004, -0.0386,\n -0.1904, -0.0953, -0.1123, -0.0991, -0.0787, -0.1057, -0.0013, -0.0369,\n -0.0879, -0.0863, -0.1878, -0.1729, -0.0087, 0.0682, -0.1591, -0.1373,\n -0.1975, -0.0454, -0.1837, -0.1072, -0.0421, -0.0690, -0.1947, -0.1432,\n -0.1238, -0.0521, -0.0849, -0.0451, -0.1415, -0.0239, -0.0423, -0.1310,\n -0.1724, -0.2094, -0.0980, -0.2065, -0.1178, -0.0332, -0.1084, -0.1131,\n -0.1286, -0.0432, -0.0695, -0.0758, -0.2483, -0.0860, 0.0145, -0.0446,\n -0.1610, -0.0115, -0.0634, -0.0586, -0.1095, -0.1289, -0.0651, 0.0114,\n 0.0023, 0.0419, -0.0189, -0.1290, -0.0457, 0.0819, -0.0015, -0.1226,\n -0.1849, -0.1969, -0.1035, -0.1153, -0.0272, -0.0616, -0.1112, -0.1248,\n -0.1334, -0.0664, -0.1258, -0.0138, -0.0825, -0.1185, -0.1591, -0.0976,\n -0.0637, -0.0918, 0.0615, -0.1491, -0.1055, -0.1264, -0.0851, -0.1861]), 'model.layer3.4.bn1.running_mean': tensor([-0.0086, -0.0677, -0.1333, -0.0364, -0.0509, 0.0422, -0.0686, -0.1081,\n -0.1113, -0.0418, 0.0491, 0.0300, -0.1457, -0.1067, -0.0461, -0.0916,\n -0.0629, -0.1590, -0.1050, -0.1480, -0.0495, -0.0446, -0.1391, -0.1724,\n 0.0584, -0.0242, 0.0311, 0.0525, -0.0657, -0.0789, -0.0727, -0.0272,\n -0.0732, 0.0214, -0.0005, -0.0251, -0.0809, -0.0863, -0.0871, 0.0042,\n -0.0478, -0.1424, -0.2321, -0.1000, 0.0047, 0.1051, -0.0628, -0.0288,\n -0.1515, -0.1976, -0.0611, 0.0050, -0.0693, -0.0072, -0.0327, -0.1614,\n -0.1010, -0.0691, -0.0435, -0.0944, 0.0477, -0.1177, -0.1500, -0.1027,\n -0.1156, -0.1072, -0.0906, -0.0330, -0.0592, -0.0208, -0.0914, -0.0921,\n -0.0297, -0.0281, 0.0274, -0.0266, -0.0155, -0.1378, -0.1080, 0.0192,\n -0.1109, -0.0461, -0.1654, -0.0082, -0.0685, -0.0558, -0.0808, -0.1170,\n -0.0504, -0.0551, 0.0434, -0.0280, 0.0102, -0.0168, -0.0790, -0.1578,\n -0.1439, -0.0863, -0.2370, -0.1233, -0.1067, -0.1446, -0.0060, -0.0623,\n -0.0662, -0.0690, -0.0427, -0.1178, 0.0228, -0.0777, -0.0918, -0.1292,\n -0.0022, -0.0996, -0.1251, -0.1320, -0.0395, 0.0049, 0.0362, -0.0162,\n 0.0189, -0.0675, 0.0143, -0.1186, 0.0286, -0.0897, -0.0042, 0.0334,\n 0.1679, 0.0908, -0.0673, -0.0535, -0.0611, -0.2047, -0.0057, -0.1413,\n -0.1038, -0.0725, -0.0553, -0.1249, -0.1136, -0.0244, -0.1267, -0.0386,\n -0.0836, -0.1214, -0.1424, -0.1171, -0.0692, -0.0611, -0.0647, -0.1042,\n -0.0020, -0.0371, -0.0858, 0.0494, -0.0733, -0.0445, -0.0699, 0.0107,\n -0.0216, 0.0111, -0.0183, -0.0978, -0.0523, -0.1943, -0.0886, -0.1065,\n -0.0528, -0.1180, -0.0666, -0.0387, 0.0043, -0.0818, 0.0056, -0.1090,\n -0.1405, -0.0258, -0.0689, -0.1864, -0.1936, -0.0066, -0.1543, -0.0209,\n -0.0197, -0.0741, 0.1284, 0.0529, -0.0899, 0.0573, -0.1790, -0.0611,\n -0.0141, -0.0841, -0.0862, -0.0687, -0.0546, -0.0501, -0.0039, -0.0909,\n -0.0379, -0.1552, -0.0527, 0.0106, -0.0553, -0.1084, -0.0813, -0.1706,\n 0.0605, -0.0976, -0.0117, -0.0076, -0.2019, -0.0097, -0.1287, 0.0142,\n -0.1662, -0.1143, -0.0100, -0.1070, 0.0340, -0.0707, -0.2060, -0.0285,\n -0.0885, -0.0435, -0.1343, -0.0601, -0.0903, -0.0592, -0.1321, -0.1146,\n -0.0595, -0.0527, -0.1319, -0.0857, -0.0703, -0.0089, -0.1304, -0.0231,\n -0.0548, -0.0862, -0.0700, -0.0490, -0.1359, -0.0918, -0.1065, -0.0208,\n -0.0241, -0.1401, -0.0657, -0.0343, -0.1255, -0.0559, 0.0046, -0.1824]), 'model.layer3.4.bn1.running_var': tensor([0.0139, 0.0154, 0.0293, 0.0217, 0.0126, 0.0076, 0.0148, 0.0168, 0.0265,\n 0.0152, 0.0120, 0.0178, 0.0251, 0.0197, 0.0194, 0.0150, 0.0150, 0.0242,\n 0.0238, 0.0143, 0.0128, 0.0103, 0.0289, 0.0270, 0.0218, 0.0269, 0.0158,\n 0.0269, 0.0147, 0.0166, 0.0299, 0.0116, 0.0139, 0.0274, 0.0180, 0.0168,\n 0.0165, 0.0233, 0.0199, 0.0148, 0.0115, 0.0229, 0.0366, 0.0204, 0.0150,\n 0.0172, 0.0241, 0.0178, 0.0140, 0.0265, 0.0164, 0.0166, 0.0176, 0.0208,\n 0.0131, 0.0173, 0.0267, 0.0221, 0.0173, 0.0162, 0.0109, 0.0181, 0.0133,\n 0.0228, 0.0183, 0.0183, 0.0152, 0.0261, 0.0131, 0.0143, 0.0143, 0.0175,\n 0.0173, 0.0238, 0.0293, 0.0127, 0.0230, 0.0185, 0.0261, 0.0130, 0.0123,\n 0.0142, 0.0199, 0.0135, 0.0128, 0.0205, 0.0188, 0.0234, 0.0197, 0.0182,\n 0.0146, 0.0208, 0.0107, 0.0246, 0.0163, 0.0134, 0.0246, 0.0159, 0.0359,\n 0.0286, 0.0144, 0.0257, 0.0180, 0.0140, 0.0234, 0.0134, 0.0181, 0.0242,\n 0.0137, 0.0166, 0.0126, 0.0143, 0.0326, 0.0172, 0.0164, 0.0259, 0.0151,\n 0.0227, 0.0218, 0.0380, 0.0242, 0.0128, 0.0165, 0.0159, 0.0197, 0.0137,\n 0.0215, 0.0208, 0.0871, 0.0365, 0.0244, 0.0181, 0.0195, 0.0223, 0.0166,\n 0.0166, 0.0233, 0.0246, 0.0230, 0.0180, 0.0198, 0.0099, 0.0219, 0.0191,\n 0.0179, 0.0546, 0.0150, 0.0150, 0.0140, 0.0151, 0.0199, 0.0139, 0.0110,\n 0.0118, 0.0139, 0.0208, 0.0160, 0.0108, 0.0182, 0.0255, 0.0123, 0.0320,\n 0.0135, 0.0125, 0.0129, 0.0249, 0.0195, 0.0141, 0.0144, 0.0184, 0.0119,\n 0.0109, 0.0256, 0.0183, 0.0317, 0.0168, 0.0249, 0.0224, 0.0088, 0.0209,\n 0.0217, 0.0305, 0.0217, 0.0143, 0.0141, 0.0195, 0.0325, 0.0148, 0.0173,\n 0.0238, 0.0402, 0.0121, 0.0133, 0.0201, 0.0141, 0.0211, 0.0169, 0.0119,\n 0.0117, 0.0172, 0.0086, 0.0260, 0.0151, 0.0089, 0.0189, 0.0218, 0.0236,\n 0.0240, 0.0115, 0.0286, 0.0154, 0.0170, 0.0221, 0.0164, 0.0214, 0.0176,\n 0.0190, 0.0205, 0.0117, 0.0223, 0.0204, 0.0136, 0.0177, 0.0185, 0.0253,\n 0.0285, 0.0243, 0.0128, 0.0115, 0.0261, 0.0234, 0.0189, 0.0204, 0.0215,\n 0.0213, 0.0215, 0.0171, 0.0119, 0.0168, 0.0168, 0.0117, 0.0152, 0.0158,\n 0.0109, 0.0276, 0.0195, 0.0140, 0.0116, 0.0200, 0.0151, 0.0253, 0.0129,\n 0.0232, 0.0122, 0.0117, 0.0155]), 'model.layer3.4.bn1.num_batches_tracked': tensor(7160), 'model.layer3.4.conv2.weight': tensor([[[[-1.1510e-02, 1.2564e-02, 1.6614e-02],\n [-3.5989e-02, -5.2395e-04, -8.6963e-04],\n [-5.0856e-03, -1.7566e-02, -1.7058e-02]],\n\n [[-4.1722e-04, 3.1197e-03, 4.5233e-03],\n [-7.4912e-03, -1.3689e-02, -7.4828e-03],\n [-4.6765e-05, 1.4609e-04, 3.5640e-03]],\n\n [[-2.1490e-02, -1.1280e-02, 9.2743e-03],\n [ 4.3337e-03, -1.5928e-02, -7.8189e-03],\n [-3.9512e-03, -6.0522e-03, -2.3605e-03]],\n\n ...,\n\n [[ 2.1336e-03, -8.3272e-03, -1.3176e-03],\n [-8.6805e-03, 1.3826e-02, 9.7805e-03],\n [-1.1616e-02, 4.1847e-03, 6.8519e-03]],\n\n [[-4.8726e-03, -2.6920e-02, -6.2504e-03],\n [-1.7924e-03, -1.3737e-02, -1.0216e-02],\n [ 1.1758e-02, 2.2968e-02, 1.4050e-02]],\n\n [[ 2.4137e-03, -5.1778e-03, -4.6643e-03],\n [-1.3431e-02, -8.1514e-03, -1.3127e-02],\n [-1.1920e-02, -1.5806e-02, -7.5167e-03]]],\n\n\n [[[-2.8559e-02, -1.6775e-02, -1.9417e-02],\n [-1.3584e-04, 2.4659e-02, 6.7771e-03],\n [-6.7995e-03, 1.8344e-02, 2.9657e-02]],\n\n [[-1.9287e-02, -2.0415e-03, -8.0341e-03],\n [ 1.9911e-03, 1.5553e-02, 1.3364e-02],\n [-6.9196e-03, 3.4938e-02, 3.0010e-02]],\n\n [[ 4.9357e-03, 1.3637e-02, 3.8899e-02],\n [-1.2835e-02, -5.3712e-03, 7.9617e-03],\n [ 1.4035e-02, -9.6369e-03, -2.0912e-02]],\n\n ...,\n\n [[ 5.0974e-03, 2.1830e-02, 3.4954e-02],\n [-1.0329e-02, -2.7162e-03, -6.7404e-03],\n [-1.4926e-02, -1.5393e-02, -5.7681e-04]],\n\n [[ 8.7237e-03, 1.9597e-02, 1.4785e-02],\n [-5.8044e-03, -1.1783e-02, -1.8679e-02],\n [-1.3223e-02, -1.2651e-02, -2.2660e-02]],\n\n [[-2.9237e-02, -2.6647e-02, -2.3056e-02],\n [-1.3753e-02, -2.1579e-02, -1.2088e-03],\n [-1.5514e-02, -3.0249e-02, -2.2865e-02]]],\n\n\n [[[ 1.6352e-02, 2.3803e-03, -3.2140e-03],\n [ 2.0404e-02, 1.3532e-02, 4.4473e-03],\n [-2.6690e-03, -1.6956e-02, -1.3238e-02]],\n\n [[-1.5508e-02, -1.1631e-02, -8.6746e-03],\n [ 1.4385e-02, 6.0808e-03, 1.6134e-02],\n [ 3.2638e-02, -8.6396e-03, -1.6459e-02]],\n\n [[ 7.9651e-03, 4.4529e-03, -2.9218e-02],\n [-2.5897e-02, 2.2859e-02, -5.8432e-03],\n [-2.0768e-02, 6.5851e-04, -8.0693e-03]],\n\n ...,\n\n [[-2.4180e-02, -1.4513e-02, -1.2354e-02],\n [ 5.8607e-04, -2.2479e-03, -1.2573e-02],\n [ 1.4502e-02, 3.3246e-04, 4.0001e-03]],\n\n [[-7.9515e-03, -1.0712e-02, -2.1670e-03],\n [-1.8093e-02, 1.5992e-03, -1.1388e-02],\n [-1.6890e-02, -1.9098e-02, -2.0472e-02]],\n\n [[ 3.6023e-02, 1.9645e-02, 1.4488e-02],\n [ 3.7393e-02, 2.6452e-02, 2.7784e-02],\n [ 2.2476e-02, 2.1808e-02, 1.6733e-02]]],\n\n\n ...,\n\n\n [[[-9.2124e-03, 2.2400e-02, 9.6463e-03],\n [-2.0225e-02, 7.4896e-03, 3.8303e-03],\n [-1.6334e-02, 2.8761e-02, 1.7360e-02]],\n\n [[ 1.7519e-02, 9.4688e-03, -9.0531e-03],\n [ 6.0826e-04, 5.8216e-03, -4.8342e-03],\n [-4.7937e-03, 5.2170e-03, -1.7243e-02]],\n\n [[-3.9593e-03, -2.0761e-02, -2.5141e-02],\n [ 3.5059e-02, 2.8438e-03, -1.4025e-02],\n [ 1.9024e-02, 1.5596e-03, -3.1181e-03]],\n\n ...,\n\n [[-1.5492e-03, 1.0265e-02, 4.8134e-03],\n [ 1.4579e-03, 5.4301e-03, 1.2189e-02],\n [-8.1344e-03, -2.6063e-02, -1.9810e-02]],\n\n [[-2.7138e-02, -1.2332e-02, -2.9929e-03],\n [-8.9929e-03, 1.9536e-02, 2.0426e-02],\n [ 8.5301e-03, 7.3796e-03, 6.0068e-03]],\n\n [[ 1.2420e-02, 1.3960e-02, -1.9567e-04],\n [-1.1221e-02, 2.5020e-02, 1.1809e-02],\n [ 1.0895e-02, 5.5659e-03, 1.1947e-02]]],\n\n\n [[[ 4.7549e-03, 1.4689e-02, -1.3448e-03],\n [-1.2156e-02, 8.0127e-03, -7.6878e-03],\n [ 2.3163e-03, 3.9528e-03, 6.8860e-03]],\n\n [[-9.9744e-03, -2.5119e-02, -2.1102e-02],\n [ 2.5103e-04, -8.6995e-03, -1.4612e-02],\n [-2.5691e-03, 1.5706e-02, 4.7549e-03]],\n\n [[ 2.9455e-03, 1.6295e-02, -2.4626e-02],\n [-1.8516e-03, 1.9540e-02, 1.9479e-03],\n [-3.2210e-03, 1.3864e-02, -4.4876e-03]],\n\n ...,\n\n [[ 8.4040e-04, 1.4694e-02, -5.3907e-03],\n [ 1.5624e-02, 2.8023e-02, 9.1238e-03],\n [ 1.7539e-02, 2.1718e-02, 1.9201e-02]],\n\n [[-9.3973e-03, -1.5055e-02, -4.6420e-03],\n [ 5.4294e-03, -8.4885e-03, 1.0936e-03],\n [ 9.1796e-03, -3.3718e-03, 3.0473e-03]],\n\n [[ 9.9491e-04, 6.0681e-04, -1.3127e-02],\n [ 2.9635e-03, 1.4540e-03, -4.1496e-03],\n [ 6.1575e-03, 8.5052e-03, -8.1010e-03]]],\n\n\n [[[-3.4933e-02, -1.6842e-02, 2.2642e-02],\n [ 1.9620e-02, -1.5386e-03, -1.7154e-03],\n [ 3.4748e-02, -9.7685e-04, -1.7038e-02]],\n\n [[-1.0158e-02, 5.0249e-04, 3.0729e-03],\n [ 4.1730e-03, 1.8437e-02, 3.4347e-03],\n [ 9.2914e-03, 1.7950e-02, 3.6429e-03]],\n\n [[-2.8604e-02, -1.1280e-02, -5.6950e-03],\n [-3.3552e-02, -1.4295e-02, -5.8265e-03],\n [-6.7371e-03, 5.5710e-03, 1.0540e-02]],\n\n ...,\n\n [[ 1.0088e-02, 7.4629e-03, 1.0378e-02],\n [-1.2724e-02, -1.7687e-02, 3.6523e-03],\n [ 1.9099e-03, -1.9644e-03, 2.0400e-02]],\n\n [[ 1.6821e-03, 6.3911e-03, 5.9533e-03],\n [-9.7294e-03, 1.4119e-02, 8.6688e-03],\n [-7.0464e-03, 1.1065e-02, -3.9862e-03]],\n\n [[ 1.1911e-02, -4.9160e-03, -2.9571e-04],\n [ 2.0336e-02, -1.8319e-02, 4.1985e-03],\n [ 2.0742e-02, 5.8763e-03, 3.4827e-03]]]]), 'model.layer3.4.bn2.weight': tensor([0.1933, 0.1616, 0.1308, 0.1771, 0.1957, 0.2571, 0.1616, 0.2034, 0.1935,\n 0.1530, 0.2065, 0.2077, 0.1973, 0.1720, 0.1825, 0.2150, 0.1519, 0.1473,\n 0.1706, 0.1709, 0.1989, 0.1639, 0.1200, 0.1879, 0.1659, 0.1824, 0.1294,\n 0.1873, 0.2408, 0.1683, 0.1480, 0.1811, 0.2281, 0.1724, 0.1863, 0.2054,\n 0.2019, 0.1581, 0.1394, 0.1755, 0.2010, 0.1728, 0.1667, 0.1870, 0.1689,\n 0.1472, 0.1996, 0.1933, 0.1874, 0.1698, 0.1941, 0.1582, 0.1417, 0.2639,\n 0.2137, 0.1653, 0.1778, 0.1879, 0.1179, 0.1611, 0.1771, 0.1090, 0.1362,\n 0.1982, 0.1711, 0.1578, 0.1879, 0.2061, 0.1741, 0.1644, 0.1509, 0.2024,\n 0.1851, 0.1948, 0.1340, 0.1236, 0.1970, 0.1438, 0.1869, 0.1887, 0.1745,\n 0.2241, 0.1987, 0.1455, 0.1654, 0.1681, 0.1798, 0.1618, 0.1581, 0.1962,\n 0.1404, 0.2761, 0.1822, 0.1615, 0.1943, 0.2454, 0.1658, 0.1697, 0.1601,\n 0.1229, 0.1794, 0.1972, 0.1518, 0.1323, 0.1730, 0.1401, 0.1053, 0.2343,\n 0.2238, 0.1710, 0.2096, 0.2063, 0.1854, 0.1842, 0.1757, 0.1825, 0.1929,\n 0.1618, 0.1216, 0.2375, 0.1931, 0.1902, 0.1571, 0.1570, 0.1625, 0.2031,\n 0.1847, 0.2002, 0.2323, 0.1610, 0.1939, 0.1777, 0.1593, 0.2195, 0.1971,\n 0.1656, 0.1045, 0.1805, 0.1851, 0.1283, 0.1372, 0.1243, 0.1823, 0.1874,\n 0.2228, 0.2174, 0.1570, 0.1551, 0.1189, 0.2101, 0.1530, 0.1958, 0.1732,\n 0.1790, 0.2070, 0.1649, 0.1840, 0.1948, 0.1402, 0.2064, 0.1821, 0.2286,\n 0.1751, 0.1262, 0.1339, 0.1983, 0.1713, 0.2433, 0.1924, 0.1835, 0.1443,\n 0.1941, 0.1899, 0.1877, 0.1724, 0.2050, 0.1522, 0.2033, 0.1446, 0.1829,\n 0.1908, 0.1628, 0.2044, 0.1594, 0.1654, 0.1469, 0.1960, 0.1735, 0.2043,\n 0.1445, 0.2058, 0.2151, 0.1741, 0.1950, 0.1791, 0.1715, 0.1967, 0.1904,\n 0.1546, 0.1900, 0.1925, 0.1402, 0.2076, 0.1809, 0.1235, 0.1760, 0.1681,\n 0.1690, 0.1790, 0.1721, 0.1499, 0.2174, 0.2214, 0.1956, 0.1458, 0.1990,\n 0.1741, 0.1696, 0.1822, 0.1642, 0.1501, 0.1648, 0.2025, 0.1459, 0.1275,\n 0.1679, 0.1627, 0.1721, 0.1297, 0.1477, 0.1566, 0.1978, 0.1197, 0.1473,\n 0.1410, 0.1807, 0.1722, 0.1870, 0.1898, 0.1824, 0.1190, 0.1516, 0.2013,\n 0.1747, 0.1826, 0.1769, 0.1907, 0.1999, 0.1859, 0.2005, 0.1944, 0.1825,\n 0.2005, 0.1163, 0.1634, 0.2023]), 'model.layer3.4.bn2.bias': tensor([-1.5906e-01, 2.5793e-02, 9.6816e-03, -1.1554e-01, -1.8497e-01,\n -1.3009e-01, -3.8913e-02, -1.7419e-01, -1.2192e-01, 1.5295e-02,\n -1.7871e-01, -1.5655e-01, -1.6600e-01, -2.1006e-02, -1.7664e-01,\n -1.3511e-01, -7.0368e-02, -3.9490e-02, -6.8340e-02, -1.8376e-01,\n -1.4671e-01, -8.7663e-02, -5.2990e-05, -7.4858e-02, -4.8708e-02,\n -1.3238e-01, 2.7215e-02, -9.4545e-02, -1.6122e-01, -7.2358e-02,\n -4.2049e-02, -8.3603e-02, -1.1083e-01, -1.0600e-01, -9.5053e-02,\n -1.3065e-01, -8.5309e-02, -5.4200e-02, -4.9244e-02, -8.6105e-02,\n -9.5439e-02, -7.7854e-02, -9.7605e-02, -1.4716e-01, -7.0858e-02,\n -1.0508e-01, -1.6715e-01, -1.1811e-01, -1.0121e-01, -1.0918e-01,\n -1.4181e-01, -8.1018e-02, -5.2426e-02, -3.2646e-01, -1.6352e-01,\n -5.2328e-02, -8.9668e-02, -1.6995e-01, 4.0639e-02, -2.4170e-02,\n -6.4925e-02, 1.4241e-01, -1.6931e-02, -1.4700e-01, -1.2113e-01,\n -2.7953e-02, -8.1062e-02, -1.4490e-01, -1.6433e-01, -8.4953e-02,\n -7.3743e-02, -1.0341e-01, -1.2654e-01, -1.6767e-01, -6.2639e-03,\n 2.0702e-01, -1.2788e-01, 1.3836e-03, -9.5726e-02, -1.0259e-01,\n -6.6150e-02, -1.5358e-01, -1.7945e-01, 5.5490e-02, -6.1540e-02,\n -1.4086e-01, -1.0648e-01, -6.5770e-02, -5.1452e-02, -1.5437e-01,\n -2.8650e-02, -9.1931e-02, -1.3124e-01, -8.8898e-03, -1.4182e-01,\n -1.2082e-01, -8.7154e-02, -1.0082e-01, -9.1121e-03, 2.6602e-02,\n -8.5675e-02, -1.4397e-01, -4.6560e-02, -3.4814e-02, -1.3846e-01,\n -9.1923e-02, 5.4747e-02, -6.2858e-02, -2.0472e-01, -2.3597e-02,\n -1.0622e-01, -1.3531e-01, -1.4267e-01, -6.7432e-02, -1.3053e-01,\n -1.1773e-01, -1.2323e-01, -1.2843e-01, 2.3084e-02, -1.0365e-01,\n -1.0597e-01, -7.9601e-02, -6.5997e-02, -5.8216e-02, -4.8978e-02,\n -1.6181e-01, -1.0919e-01, -1.7403e-01, -1.5956e-01, -5.2791e-02,\n -1.3523e-01, -1.3018e-01, -9.9342e-02, -4.7043e-02, -1.8084e-01,\n -5.5762e-02, 6.0722e-02, -7.7117e-02, -8.5823e-02, -1.2049e-02,\n -4.2649e-02, 8.3473e-02, -8.3788e-02, -1.6318e-01, -1.4552e-01,\n -1.4001e-01, -4.7691e-02, -5.2662e-02, 4.0821e-02, -1.0023e-01,\n -1.0779e-01, -1.4133e-01, -5.7397e-02, -1.0347e-01, -1.3389e-01,\n -8.1753e-02, -1.5692e-01, -1.8478e-01, -1.6630e-02, -1.0069e-01,\n -8.5015e-02, -1.7705e-01, -7.8374e-02, 4.0113e-02, -1.6171e-02,\n -2.3671e-01, -1.1314e-01, -1.0203e-01, -1.7279e-01, -1.2102e-01,\n -3.4372e-02, -1.3820e-01, -1.2509e-01, -1.2108e-01, -1.2322e-01,\n -1.5636e-01, -3.6948e-02, -1.5919e-01, -5.6154e-02, -1.3256e-01,\n -1.5618e-01, -7.6634e-02, -1.3655e-01, -4.6176e-02, -1.0408e-01,\n -3.6280e-02, -1.0130e-01, -7.8567e-02, -1.7071e-01, 6.1559e-02,\n -4.6288e-02, -8.6466e-02, -8.4491e-02, -1.5473e-01, -1.0917e-01,\n -5.4385e-02, -1.4250e-01, -1.4706e-01, -6.7961e-02, -1.5254e-01,\n -9.7860e-02, 2.0517e-02, -1.7014e-01, -6.2670e-02, 5.0207e-02,\n -1.4830e-01, -6.3856e-02, -1.2744e-01, -1.6318e-01, -9.8809e-02,\n -8.3079e-02, -1.7237e-01, -9.6537e-02, -1.7629e-01, -1.9407e-02,\n -1.4080e-01, -1.5775e-01, -6.2959e-02, -1.0550e-01, -7.1319e-02,\n -4.8031e-02, -1.2243e-01, -1.4295e-01, -4.6189e-02, 2.9928e-02,\n -7.6840e-02, 1.4165e-03, -9.1229e-02, 4.7516e-02, -1.3147e-01,\n -4.4394e-02, -1.3170e-01, 2.9149e-02, -3.7119e-03, -4.3656e-02,\n -1.2780e-01, -8.5124e-02, -8.7798e-02, -1.2483e-01, -1.2472e-01,\n 7.3082e-03, -6.3334e-02, -1.4226e-01, -1.0561e-01, -1.8121e-01,\n -1.1215e-01, -1.5946e-01, -1.2477e-01, -7.8723e-02, -1.2026e-01,\n -9.8730e-02, -1.2243e-01, -1.0442e-01, 4.5575e-02, -9.5863e-02,\n -1.4113e-01]), 'model.layer3.4.bn2.running_mean': tensor([-1.0686e-01, 5.0694e-02, -7.9495e-02, -1.1812e-01, -1.1752e-01,\n -1.0441e-01, -3.5068e-02, -7.9454e-02, -4.5331e-02, 5.8574e-02,\n -9.8469e-02, -9.2158e-02, -6.4894e-02, -1.3574e-01, -8.4917e-02,\n -1.2773e-01, -6.7048e-02, -1.9364e-02, -5.1732e-02, -4.0355e-02,\n -2.9910e-02, -1.0122e-01, -1.3138e-01, -1.9273e-01, -4.1586e-02,\n -6.8363e-02, 4.9313e-02, -3.3249e-02, 5.5220e-02, 2.4138e-02,\n -3.5910e-02, 2.7408e-03, -1.0929e-01, -7.3039e-02, -1.0564e-01,\n -1.0227e-01, -5.6189e-02, 1.3288e-02, -1.3180e-01, -3.5107e-02,\n -1.2527e-01, -7.7343e-02, 7.1032e-03, -3.5377e-02, -4.2591e-02,\n -1.4962e-01, -7.1921e-02, -1.0011e-01, -7.5311e-02, -1.1331e-01,\n -2.5837e-02, -1.2437e-01, 7.2692e-02, 1.8958e-05, -8.9258e-03,\n -1.0108e-01, -4.8500e-02, -6.0686e-02, -5.7597e-02, -4.0176e-02,\n -5.5189e-03, -6.2317e-02, -1.3122e-01, -2.6858e-02, -1.2998e-01,\n -1.0944e-01, -1.5032e-01, 3.4070e-03, 2.1125e-02, -8.1937e-02,\n -3.0898e-02, -7.3371e-02, -2.7331e-02, -1.1155e-01, -9.9165e-02,\n 9.2988e-02, -8.8181e-02, 2.9342e-02, -1.0568e-01, -7.7235e-02,\n -1.1928e-01, -1.4348e-01, -3.6628e-02, 4.2479e-02, 1.3303e-01,\n -1.3506e-01, -7.4615e-02, -5.7210e-02, -2.1237e-02, -8.1208e-02,\n -2.3891e-02, -8.3118e-02, -3.6846e-02, -1.1392e-01, -1.1881e-01,\n 1.2173e-02, 6.3298e-02, -8.9274e-02, 4.3484e-03, 7.2013e-02,\n -1.3678e-01, -1.2440e-01, -3.7797e-02, -8.5018e-02, -5.7553e-02,\n -5.7474e-02, 6.7270e-02, -1.6053e-01, -7.6698e-02, 4.7237e-02,\n -1.1162e-01, -4.0008e-02, -1.2022e-01, -8.7957e-02, -8.3102e-02,\n -3.8131e-02, -3.0355e-02, -7.9795e-02, -6.0880e-02, -2.1052e-01,\n -1.6746e-01, -3.0999e-02, -6.5944e-02, 1.6908e-02, -8.1794e-02,\n -9.6608e-02, 2.8053e-01, -1.0709e-01, -9.6457e-02, -9.0381e-02,\n -7.7241e-02, -4.7766e-02, -9.4560e-02, -1.6858e-01, -6.8355e-03,\n -2.7911e-02, 6.9681e-02, -4.3795e-02, 6.7536e-02, 2.0797e-02,\n -6.8850e-03, 2.7424e-02, -1.0121e-01, -4.9952e-02, 1.7622e-01,\n -7.4499e-02, -2.8302e-02, -7.5019e-03, 2.0946e-02, 7.7466e-02,\n 1.0013e-01, -1.2241e-01, -1.0462e-01, -8.3050e-02, -9.7825e-02,\n -1.5554e-01, -6.6660e-02, -1.0542e-01, -1.0740e-01, -7.9019e-04,\n -1.1374e-01, -9.8448e-02, -1.3948e-01, 2.4440e-02, 1.6765e-02,\n -4.0644e-02, -1.1018e-01, -4.4511e-02, -9.0010e-02, 1.0790e-01,\n 1.0283e-02, -3.4145e-02, -3.4730e-01, -1.2804e-01, -9.5316e-02,\n -4.9674e-02, -4.7396e-02, -7.1074e-03, -4.1776e-02, 6.0463e-03,\n -1.1443e-01, -1.1188e-01, -7.3520e-02, -1.0904e-01, -9.3209e-02,\n -1.2516e-01, 2.0886e-02, 4.8211e-03, -8.3732e-02, -1.5317e-02,\n -2.3144e-02, -1.0625e-01, 6.0901e-03, -8.3231e-02, -7.4611e-02,\n -4.4764e-02, -1.0508e-01, -1.5484e-01, -1.1266e-01, -8.3332e-02,\n 7.2418e-02, -9.7223e-02, -1.3489e-01, -6.2810e-02, -9.4188e-02,\n -8.8305e-02, 1.2847e-02, -2.4000e-02, -6.2743e-02, -7.8931e-02,\n 4.3052e-02, -9.8504e-02, 6.3984e-02, -1.1861e-01, -6.8736e-02,\n -9.8093e-02, -1.5658e-01, -9.1361e-02, -4.5889e-02, -1.4101e-01,\n -4.9316e-02, -7.6229e-02, -6.6394e-02, -5.3226e-02, -3.2666e-02,\n -1.3699e-01, -1.5996e-02, -8.2615e-02, -6.7368e-02, -1.1345e-01,\n -1.0619e-01, -7.8934e-02, 7.6310e-02, -6.0780e-02, -3.9245e-02,\n -2.1513e-02, -6.2541e-02, -5.3914e-02, -1.3064e-01, -5.7270e-02,\n -7.3410e-02, -4.1828e-02, 6.8222e-02, -1.2960e-01, 1.4801e-01,\n -1.1341e-01, -1.3563e-01, -4.5334e-02, -2.3606e-02, -9.7868e-02,\n -1.3163e-01, 7.1251e-03, 6.3210e-02, -1.1204e-02, -1.7382e-02,\n -4.7578e-02]), 'model.layer3.4.bn2.running_var': tensor([0.0075, 0.0152, 0.0105, 0.0153, 0.0068, 0.0172, 0.0122, 0.0089, 0.0106,\n 0.0235, 0.0080, 0.0200, 0.0116, 0.0123, 0.0088, 0.0237, 0.0127, 0.0099,\n 0.0121, 0.0154, 0.0099, 0.0088, 0.0122, 0.0116, 0.0129, 0.0207, 0.0101,\n 0.0237, 0.0084, 0.0107, 0.0172, 0.0198, 0.0205, 0.0082, 0.0108, 0.0140,\n 0.0111, 0.0147, 0.0169, 0.0147, 0.0108, 0.0068, 0.0094, 0.0151, 0.0117,\n 0.0175, 0.0093, 0.0133, 0.0187, 0.0198, 0.0090, 0.0128, 0.0110, 0.0104,\n 0.0071, 0.0152, 0.0097, 0.0070, 0.0098, 0.0115, 0.0096, 0.0160, 0.0084,\n 0.0098, 0.0094, 0.0125, 0.0140, 0.0122, 0.0216, 0.0124, 0.0069, 0.0138,\n 0.0156, 0.0141, 0.0133, 0.0215, 0.0080, 0.0173, 0.0119, 0.0084, 0.0102,\n 0.0081, 0.0073, 0.0161, 0.0122, 0.0098, 0.0152, 0.0096, 0.0105, 0.0110,\n 0.0125, 0.0258, 0.0086, 0.0148, 0.0167, 0.0092, 0.0177, 0.0130, 0.0204,\n 0.0106, 0.0084, 0.0135, 0.0092, 0.0106, 0.0121, 0.0119, 0.0193, 0.0155,\n 0.0087, 0.0208, 0.0083, 0.0078, 0.0111, 0.0185, 0.0095, 0.0082, 0.0077,\n 0.0123, 0.0158, 0.0102, 0.0166, 0.0210, 0.0149, 0.0074, 0.0115, 0.0077,\n 0.0246, 0.0124, 0.0170, 0.0117, 0.0128, 0.0140, 0.0055, 0.0182, 0.0063,\n 0.0105, 0.0120, 0.0135, 0.0165, 0.0104, 0.0140, 0.0143, 0.0205, 0.0139,\n 0.0134, 0.0117, 0.0205, 0.0093, 0.0176, 0.0128, 0.0099, 0.0094, 0.0140,\n 0.0085, 0.0185, 0.0093, 0.0057, 0.0147, 0.0257, 0.0088, 0.0119, 0.0077,\n 0.0125, 0.0196, 0.0067, 0.0104, 0.0122, 0.0162, 0.0075, 0.0161, 0.0101,\n 0.0123, 0.0153, 0.0091, 0.0158, 0.0130, 0.0111, 0.0073, 0.0090, 0.0146,\n 0.0154, 0.0095, 0.0158, 0.0102, 0.0082, 0.0105, 0.0130, 0.0091, 0.0092,\n 0.0124, 0.0178, 0.0142, 0.0137, 0.0122, 0.0102, 0.0098, 0.0093, 0.0163,\n 0.0066, 0.0145, 0.0064, 0.0092, 0.0125, 0.0122, 0.0119, 0.0090, 0.0110,\n 0.0075, 0.0070, 0.0080, 0.0077, 0.0194, 0.0131, 0.0114, 0.0101, 0.0119,\n 0.0093, 0.0103, 0.0190, 0.0084, 0.0134, 0.0120, 0.0101, 0.0068, 0.0128,\n 0.0126, 0.0104, 0.0128, 0.0113, 0.0081, 0.0115, 0.0105, 0.0094, 0.0134,\n 0.0104, 0.0085, 0.0180, 0.0130, 0.0155, 0.0086, 0.0126, 0.0093, 0.0142,\n 0.0170, 0.0127, 0.0168, 0.0085, 0.0169, 0.0142, 0.0130, 0.0124, 0.0078,\n 0.0080, 0.0122, 0.0094, 0.0086]), 'model.layer3.4.bn2.num_batches_tracked': tensor(7160), 'model.layer3.4.conv3.weight': tensor([[[[-9.8387e-04]],\n\n [[-1.4917e-03]],\n\n [[ 6.2357e-03]],\n\n ...,\n\n [[-1.2485e-03]],\n\n [[-4.1624e-03]],\n\n [[ 3.2926e-05]]],\n\n\n [[[-2.4180e-02]],\n\n [[-1.6574e-03]],\n\n [[-2.9574e-02]],\n\n ...,\n\n [[-1.5051e-02]],\n\n [[-2.6704e-02]],\n\n [[ 1.1421e-02]]],\n\n\n [[[-1.1777e-02]],\n\n [[ 2.7330e-02]],\n\n [[-5.6389e-03]],\n\n ...,\n\n [[ 8.3543e-03]],\n\n [[-9.4576e-03]],\n\n [[-1.8135e-02]]],\n\n\n ...,\n\n\n [[[-1.3570e-03]],\n\n [[ 1.9774e-02]],\n\n [[ 3.1463e-02]],\n\n ...,\n\n [[ 2.3672e-02]],\n\n [[-2.1378e-03]],\n\n [[ 3.4261e-02]]],\n\n\n [[[ 1.4740e-02]],\n\n [[-1.6622e-02]],\n\n [[ 1.2744e-02]],\n\n ...,\n\n [[ 5.8958e-03]],\n\n [[ 9.8421e-03]],\n\n [[ 1.3772e-02]]],\n\n\n [[[-2.0848e-02]],\n\n [[ 5.1490e-03]],\n\n [[ 1.6314e-02]],\n\n ...,\n\n [[-4.6069e-03]],\n\n [[-1.1073e-02]],\n\n [[ 3.2473e-03]]]]), 'model.layer3.4.bn3.weight': tensor([1.7610e-04, 1.8537e-01, 1.4843e-01, ..., 1.0778e-01, 5.2124e-02,\n 3.1762e-02]), 'model.layer3.4.bn3.bias': tensor([-0.0162, -0.2113, -0.1461, ..., -0.0989, -0.0246, -0.0225]), 'model.layer3.4.bn3.running_mean': tensor([ 0.0124, 0.0012, -0.0038, ..., -0.0293, -0.0219, -0.0091]), 'model.layer3.4.bn3.running_var': tensor([0.0004, 0.0011, 0.0013, ..., 0.0017, 0.0010, 0.0010]), 'model.layer3.4.bn3.num_batches_tracked': tensor(7160), 'model.layer3.5.conv1.weight': tensor([[[[-0.0061]],\n\n [[ 0.0107]],\n\n [[ 0.0491]],\n\n ...,\n\n [[ 0.0039]],\n\n [[-0.0325]],\n\n [[-0.0368]]],\n\n\n [[[ 0.0266]],\n\n [[-0.0293]],\n\n [[-0.0010]],\n\n ...,\n\n [[ 0.0039]],\n\n [[ 0.0094]],\n\n [[-0.0037]]],\n\n\n [[[ 0.0160]],\n\n [[-0.0097]],\n\n [[ 0.0072]],\n\n ...,\n\n [[-0.0248]],\n\n [[ 0.0203]],\n\n [[ 0.0045]]],\n\n\n ...,\n\n\n [[[-0.0007]],\n\n [[-0.0032]],\n\n [[ 0.0210]],\n\n ...,\n\n [[-0.0003]],\n\n [[-0.0013]],\n\n [[ 0.0208]]],\n\n\n [[[ 0.0172]],\n\n [[ 0.0106]],\n\n [[-0.0043]],\n\n ...,\n\n [[-0.0121]],\n\n [[ 0.0096]],\n\n [[-0.0352]]],\n\n\n [[[-0.0324]],\n\n [[ 0.0555]],\n\n [[-0.0161]],\n\n ...,\n\n [[ 0.0125]],\n\n [[-0.0169]],\n\n [[-0.0110]]]]), 'model.layer3.5.bn1.weight': tensor([0.1965, 0.2067, 0.1262, 0.2197, 0.2032, 0.2229, 0.2908, 0.1931, 0.1824,\n 0.1607, 0.1695, 0.2047, 0.1837, 0.1694, 0.1919, 0.1663, 0.1882, 0.1813,\n 0.2310, 0.2870, 0.1950, 0.1538, 0.1963, 0.1614, 0.1459, 0.1631, 0.1726,\n 0.1505, 0.1830, 0.1869, 0.1820, 0.1405, 0.1789, 0.1434, 0.1825, 0.1513,\n 0.1416, 0.1601, 0.1886, 0.1412, 0.2552, 0.1482, 0.1697, 0.2579, 0.2191,\n 0.1918, 0.1738, 0.2354, 0.1654, 0.1208, 0.1457, 0.2067, 0.2071, 0.1555,\n 0.1629, 0.1800, 0.1312, 0.1878, 0.1470, 0.1621, 0.2088, 0.1394, 0.1836,\n 0.1524, 0.1979, 0.1695, 0.1971, 0.1303, 0.1815, 0.1549, 0.2101, 0.2639,\n 0.1437, 0.1777, 0.2003, 0.2093, 0.1925, 0.2185, 0.1624, 0.1523, 0.1701,\n 0.2122, 0.2239, 0.1876, 0.1838, 0.0956, 0.1914, 0.1612, 0.2041, 0.2134,\n 0.1808, 0.1821, 0.1951, 0.1852, 0.1327, 0.1723, 0.2009, 0.1581, 0.1720,\n 0.1968, 0.1801, 0.2007, 0.1749, 0.1580, 0.2079, 0.1656, 0.1888, 0.2159,\n 0.2098, 0.2097, 0.1845, 0.2320, 0.1748, 0.1875, 0.1990, 0.2474, 0.1754,\n 0.2214, 0.1956, 0.1853, 0.1817, 0.1534, 0.2120, 0.2136, 0.1648, 0.2117,\n 0.1546, 0.2045, 0.1721, 0.0941, 0.1770, 0.1525, 0.2002, 0.1838, 0.1711,\n 0.1692, 0.1768, 0.2493, 0.1379, 0.2008, 0.1926, 0.2109, 0.1892, 0.1802,\n 0.1596, 0.2419, 0.2219, 0.2225, 0.1446, 0.1666, 0.1708, 0.1667, 0.1328,\n 0.2086, 0.1926, 0.1760, 0.2338, 0.2256, 0.2163, 0.2003, 0.1974, 0.2241,\n 0.1745, 0.1914, 0.1851, 0.1598, 0.1877, 0.1796, 0.2500, 0.1350, 0.2227,\n 0.1591, 0.0967, 0.2215, 0.1511, 0.1950, 0.1741, 0.1407, 0.1237, 0.2002,\n 0.1914, 0.1705, 0.1879, 0.1842, 0.2058, 0.1450, 0.1237, 0.1290, 0.1783,\n 0.1523, 0.1603, 0.1771, 0.1898, 0.1753, 0.1735, 0.1747, 0.1569, 0.1346,\n 0.1775, 0.1776, 0.1996, 0.1285, 0.2013, 0.1892, 0.1859, 0.2036, 0.1707,\n 0.2099, 0.2166, 0.1983, 0.2469, 0.2114, 0.1968, 0.1500, 0.1490, 0.1973,\n 0.1764, 0.1741, 0.1465, 0.1700, 0.1586, 0.1420, 0.1793, 0.1600, 0.2873,\n 0.2104, 0.2198, 0.1695, 0.1805, 0.2175, 0.1526, 0.1813, 0.1450, 0.1559,\n 0.1956, 0.1833, 0.1833, 0.1543, 0.2111, 0.1832, 0.1790, 0.1569, 0.1631,\n 0.1732, 0.1625, 0.1695, 0.1849, 0.2016, 0.2403, 0.1961, 0.1907, 0.1887,\n 0.2010, 0.1665, 0.1510, 0.2146]), 'model.layer3.5.bn1.bias': tensor([-0.1776, -0.2112, 0.0877, -0.1603, -0.1930, -0.2743, -0.3199, -0.0912,\n -0.1455, -0.0648, -0.1215, -0.2174, -0.0793, -0.1253, -0.1611, -0.1360,\n -0.1564, -0.1914, -0.2656, -0.2610, -0.1876, 0.0416, -0.1777, -0.0844,\n -0.0692, -0.0645, -0.0601, -0.1310, -0.1714, -0.1261, -0.1381, -0.0396,\n -0.0654, -0.0722, -0.0842, 0.0044, 0.0100, -0.1173, -0.0944, -0.1141,\n -0.2600, 0.0030, -0.0970, -0.2407, -0.1443, -0.1102, -0.1369, -0.1301,\n -0.1296, 0.0216, -0.0053, -0.1583, -0.1453, 0.0256, -0.1002, -0.1263,\n 0.0883, -0.1534, -0.0788, -0.0557, -0.1207, -0.0570, -0.1321, -0.0311,\n -0.1616, -0.1024, -0.1418, -0.0259, -0.1256, -0.0901, -0.1985, -0.1799,\n -0.0228, -0.0961, -0.1527, -0.2068, -0.1110, -0.1622, -0.0216, -0.0183,\n -0.1251, -0.2138, -0.2241, -0.1236, -0.1088, 0.1503, -0.1316, -0.0924,\n -0.1472, -0.2287, -0.1444, -0.1303, -0.1642, -0.0918, -0.0253, -0.1038,\n -0.2143, -0.0255, -0.0619, -0.1548, -0.1497, -0.1273, -0.1305, -0.0491,\n -0.1603, -0.0772, -0.0770, -0.1649, -0.1548, -0.1126, -0.0313, -0.1926,\n -0.1186, -0.1569, -0.1553, -0.2150, -0.0860, -0.1055, -0.0893, -0.1265,\n -0.0936, -0.0362, -0.1425, -0.1078, -0.0799, -0.1267, -0.1133, -0.1331,\n -0.1180, 0.1412, -0.0766, -0.0359, -0.1973, -0.1100, -0.0096, -0.0875,\n -0.0982, -0.1712, 0.1433, -0.1128, -0.0409, -0.1265, -0.1191, -0.0731,\n -0.0632, -0.2052, -0.1247, -0.1989, -0.0254, -0.1145, -0.1221, -0.1320,\n 0.0214, -0.2178, -0.1359, -0.1151, -0.1649, -0.2201, -0.1630, -0.1554,\n -0.1829, -0.1764, -0.1369, -0.1529, -0.1720, -0.0127, -0.1765, -0.0967,\n -0.2785, 0.0078, -0.1986, -0.0720, 0.0934, -0.1828, -0.0722, -0.1326,\n -0.1023, -0.0024, 0.0294, -0.1209, -0.0850, -0.0434, -0.1751, -0.1709,\n -0.1228, -0.0782, 0.0602, 0.0306, -0.1243, -0.0788, -0.1071, -0.0648,\n -0.1177, -0.1182, -0.1376, -0.0989, -0.0405, -0.0538, -0.0510, -0.1020,\n -0.1170, 0.0045, -0.1328, -0.1583, -0.1431, -0.1627, -0.1012, -0.2151,\n -0.0839, -0.1724, -0.1282, -0.1530, -0.1683, -0.0292, -0.0364, -0.1147,\n -0.1317, -0.0868, 0.0022, -0.0102, -0.1433, 0.0202, -0.1444, -0.0994,\n -0.0721, -0.1666, -0.1852, -0.1519, -0.1219, -0.1835, -0.0945, -0.1333,\n -0.0200, -0.0061, -0.1615, -0.1536, -0.1496, -0.0689, -0.0964, -0.1573,\n -0.1084, -0.0538, -0.0311, -0.0693, -0.0838, -0.1119, -0.1139, -0.1939,\n -0.2126, -0.1395, -0.1411, -0.1434, -0.1272, 0.0672, -0.0662, -0.1472]), 'model.layer3.5.bn1.running_mean': tensor([-0.0138, -0.0909, -0.0318, -0.1822, 0.0150, -0.2044, -0.1440, -0.0494,\n 0.0259, -0.0232, 0.0235, 0.0029, -0.0578, -0.0383, -0.0328, -0.1495,\n -0.0637, -0.0584, -0.1689, -0.1672, -0.1292, -0.1128, -0.0380, 0.0144,\n -0.0066, -0.0685, 0.0522, -0.1136, -0.0625, -0.0095, -0.0562, 0.0217,\n -0.0708, -0.1550, -0.0536, 0.0171, -0.0619, -0.0187, -0.0495, 0.0504,\n -0.0510, 0.1611, -0.0543, -0.1047, -0.0578, -0.0519, 0.0329, -0.1793,\n -0.0698, -0.0789, 0.0086, -0.0044, -0.1087, -0.0542, -0.0192, -0.0260,\n -0.1248, 0.0998, 0.0319, -0.1183, -0.2056, -0.0530, -0.0811, -0.0683,\n -0.0292, 0.0032, -0.0990, -0.0861, -0.0881, -0.0162, 0.0311, -0.0354,\n -0.0552, -0.0837, -0.1196, -0.1128, -0.0069, -0.1047, -0.0670, -0.0814,\n -0.0763, 0.0186, -0.0040, 0.0349, -0.0678, -0.0718, -0.0531, 0.0115,\n 0.0263, -0.0839, -0.0366, -0.0483, -0.0758, -0.0527, 0.0378, -0.0215,\n -0.0447, -0.0133, -0.0212, -0.0922, -0.0726, -0.0582, -0.0773, -0.0689,\n -0.0223, 0.0019, -0.0966, -0.0716, -0.1092, -0.0730, 0.0226, -0.0817,\n -0.1935, -0.1066, 0.0283, -0.0739, -0.0398, -0.1109, -0.1158, -0.0122,\n 0.0676, -0.0609, -0.0272, -0.0460, -0.0744, -0.0657, -0.0112, -0.0224,\n -0.0716, -0.0355, -0.0452, -0.0453, -0.1025, -0.0238, -0.0452, -0.0737,\n -0.0658, -0.0413, 0.1050, -0.0496, -0.1142, 0.0154, -0.0658, -0.0202,\n -0.0527, -0.0722, -0.0136, -0.0995, -0.0702, -0.0257, 0.0058, -0.0739,\n -0.0698, -0.0578, -0.0624, -0.0312, -0.0530, -0.0913, 0.0163, -0.0545,\n -0.0445, -0.0052, 0.0369, -0.0175, -0.0422, -0.0610, 0.0197, 0.0337,\n -0.0417, -0.0861, -0.0570, 0.0567, -0.0401, -0.0426, -0.1560, -0.1185,\n -0.0519, -0.0461, 0.0121, -0.0380, -0.0459, -0.1400, 0.0168, -0.0715,\n 0.0400, 0.0275, -0.0071, -0.0283, -0.0340, -0.0839, -0.0299, -0.0905,\n 0.0089, -0.0324, -0.0523, -0.0380, -0.0831, -0.0237, -0.1705, -0.0610,\n -0.1186, -0.1435, -0.1023, -0.0132, -0.1084, -0.0666, -0.0545, -0.0689,\n -0.0293, -0.0956, -0.1357, 0.0293, -0.0556, -0.1151, 0.0327, -0.1117,\n -0.1362, -0.0365, -0.1069, -0.0505, -0.0706, -0.0705, -0.0214, -0.1338,\n -0.1561, -0.0191, -0.0534, -0.0560, 0.0537, -0.1239, 0.0090, 0.0037,\n -0.1113, -0.0469, -0.0142, -0.0623, -0.0635, -0.0870, -0.0138, -0.0367,\n -0.0613, 0.0604, -0.0921, -0.0526, -0.0380, -0.0314, 0.0335, -0.0182,\n 0.0647, -0.1339, -0.0034, -0.0361, 0.0033, -0.0373, 0.0843, -0.0134]), 'model.layer3.5.bn1.running_var': tensor([0.0150, 0.0129, 0.0175, 0.0142, 0.0142, 0.0216, 0.0197, 0.0134, 0.0108,\n 0.0097, 0.0086, 0.0326, 0.0109, 0.0171, 0.0104, 0.0098, 0.0080, 0.0090,\n 0.0424, 0.0244, 0.0237, 0.0317, 0.0087, 0.0134, 0.0098, 0.0109, 0.0102,\n 0.0105, 0.0196, 0.0147, 0.0119, 0.0107, 0.0161, 0.0185, 0.0143, 0.0161,\n 0.0141, 0.0119, 0.0193, 0.0092, 0.0098, 0.0507, 0.0139, 0.0164, 0.0105,\n 0.0177, 0.0119, 0.0207, 0.0084, 0.0125, 0.0104, 0.0161, 0.0177, 0.0186,\n 0.0104, 0.0251, 0.0410, 0.0196, 0.0115, 0.0113, 0.0152, 0.0143, 0.0222,\n 0.0116, 0.0221, 0.0176, 0.0080, 0.0124, 0.0108, 0.0190, 0.0112, 0.0415,\n 0.0243, 0.0286, 0.0243, 0.0115, 0.0229, 0.0134, 0.0373, 0.0099, 0.0097,\n 0.0232, 0.0118, 0.0139, 0.0138, 0.0138, 0.0153, 0.0090, 0.0116, 0.0205,\n 0.0068, 0.0135, 0.0134, 0.0125, 0.0078, 0.0080, 0.0089, 0.0207, 0.0093,\n 0.0190, 0.0087, 0.0139, 0.0117, 0.0112, 0.0148, 0.0142, 0.0149, 0.0142,\n 0.0187, 0.0096, 0.0306, 0.0123, 0.0253, 0.0120, 0.0129, 0.0133, 0.0104,\n 0.0296, 0.0116, 0.0138, 0.0184, 0.0144, 0.0163, 0.0134, 0.0083, 0.0362,\n 0.0265, 0.0188, 0.0118, 0.0207, 0.0152, 0.0151, 0.0091, 0.0117, 0.0186,\n 0.0139, 0.0113, 0.0121, 0.0348, 0.0130, 0.0221, 0.0392, 0.0290, 0.0139,\n 0.0255, 0.0098, 0.0257, 0.0150, 0.0156, 0.0123, 0.0145, 0.0120, 0.0265,\n 0.0093, 0.0110, 0.0316, 0.0216, 0.0146, 0.0125, 0.0083, 0.0112, 0.0126,\n 0.0103, 0.0138, 0.0101, 0.0268, 0.0069, 0.0134, 0.0133, 0.0210, 0.0109,\n 0.0064, 0.0234, 0.0105, 0.0208, 0.0242, 0.0150, 0.0169, 0.0223, 0.0112,\n 0.0116, 0.0219, 0.0084, 0.0092, 0.0178, 0.0154, 0.0158, 0.0150, 0.0133,\n 0.0172, 0.0089, 0.0146, 0.0172, 0.0129, 0.0088, 0.0136, 0.0175, 0.0166,\n 0.0265, 0.0110, 0.0131, 0.0164, 0.0128, 0.0096, 0.0112, 0.0108, 0.0077,\n 0.0114, 0.0164, 0.0068, 0.0165, 0.0116, 0.0147, 0.0186, 0.0175, 0.0131,\n 0.0180, 0.0134, 0.0207, 0.0192, 0.0110, 0.0253, 0.0078, 0.0140, 0.0281,\n 0.0139, 0.0128, 0.0126, 0.0282, 0.0119, 0.0173, 0.0170, 0.0109, 0.0116,\n 0.0091, 0.0109, 0.0110, 0.0108, 0.0517, 0.0094, 0.0144, 0.0110, 0.0157,\n 0.0202, 0.0152, 0.0085, 0.0171, 0.0100, 0.0301, 0.0138, 0.0108, 0.0109,\n 0.0119, 0.0546, 0.0145, 0.0262]), 'model.layer3.5.bn1.num_batches_tracked': tensor(7160), 'model.layer3.5.conv2.weight': tensor([[[[-2.7460e-02, -3.9794e-02, -2.2574e-02],\n [-1.3448e-03, 2.7722e-02, -5.9162e-04],\n [-3.3398e-03, 4.1797e-03, -1.2841e-03]],\n\n [[ 2.0106e-02, 3.6526e-02, 2.2821e-02],\n [ 3.0380e-02, 5.2686e-02, 2.5805e-02],\n [-1.0094e-02, 6.0842e-03, -7.9888e-03]],\n\n [[-1.2213e-02, -1.3966e-03, 4.8221e-05],\n [-1.2262e-04, -1.3787e-02, 3.9879e-03],\n [ 1.1446e-02, 1.1849e-02, 1.5131e-02]],\n\n ...,\n\n [[-1.8573e-03, 1.6265e-02, 1.1444e-02],\n [-2.1843e-02, -2.1708e-03, -7.7648e-03],\n [-2.6695e-02, -6.1812e-03, 1.7369e-03]],\n\n [[-2.1341e-03, 8.1652e-03, 1.1399e-02],\n [-3.9427e-03, 4.9109e-03, 2.3551e-02],\n [-1.4089e-02, 8.4084e-03, 6.7664e-03]],\n\n [[ 1.5172e-03, 4.6264e-03, 2.4429e-02],\n [-6.7473e-03, -9.1602e-03, 1.7055e-02],\n [ 2.2783e-03, 2.2437e-03, 8.4227e-03]]],\n\n\n [[[ 1.4364e-02, 4.3031e-03, 6.1346e-03],\n [ 9.0990e-03, -1.0747e-02, 1.6818e-02],\n [ 2.5725e-03, 7.7056e-03, 1.6901e-02]],\n\n [[-2.6667e-02, -2.5619e-02, -1.2917e-02],\n [-1.5393e-02, -1.2916e-02, 1.2781e-02],\n [ 1.3763e-02, 6.9504e-03, 9.1953e-03]],\n\n [[ 1.1818e-02, 1.4551e-02, 6.4262e-03],\n [ 1.4531e-02, 1.2842e-02, 5.2062e-04],\n [-1.8653e-03, -2.5188e-03, -2.1949e-02]],\n\n ...,\n\n [[-1.4954e-03, -9.1277e-03, -1.7098e-02],\n [ 3.9499e-03, -6.4334e-03, -2.3366e-02],\n [ 3.2867e-03, -1.8518e-02, -2.8229e-02]],\n\n [[-3.5377e-02, -2.8321e-02, -3.7378e-02],\n [-9.9530e-03, 5.0925e-03, -2.4795e-03],\n [-2.2247e-02, -2.0299e-02, -1.9185e-02]],\n\n [[-9.0469e-03, -1.7823e-02, -2.5791e-03],\n [-4.7848e-03, 2.9720e-03, -1.1041e-02],\n [-1.9422e-02, -2.2075e-02, -2.4291e-02]]],\n\n\n [[[-1.9416e-02, -2.8224e-02, -2.7469e-02],\n [-2.6898e-02, -3.2923e-02, -3.2298e-02],\n [-2.0891e-02, -2.3690e-02, -2.7823e-02]],\n\n [[ 4.0945e-03, 4.4344e-03, 1.1138e-02],\n [-3.7946e-03, -4.0766e-02, -6.5668e-03],\n [ 2.1504e-02, 4.6015e-02, 1.8463e-02]],\n\n [[ 3.7846e-03, 7.2990e-03, 1.4971e-02],\n [-1.0823e-03, 3.1529e-02, 9.8942e-03],\n [-3.5165e-02, -1.8758e-02, -3.2324e-02]],\n\n ...,\n\n [[-1.7981e-03, 1.2296e-02, 3.2040e-02],\n [-1.9434e-02, 4.8430e-03, 1.2977e-02],\n [-1.3276e-02, 5.7568e-03, 4.8944e-04]],\n\n [[ 2.2172e-02, 3.7690e-02, 2.6792e-02],\n [-5.5743e-05, 9.8817e-03, -3.8667e-03],\n [ 6.6838e-03, 4.1203e-04, 3.6376e-03]],\n\n [[-2.4285e-02, -2.3158e-02, -2.7491e-02],\n [-2.5833e-02, -3.7468e-02, -1.9772e-02],\n [-8.2879e-04, -9.3711e-03, -4.5632e-03]]],\n\n\n ...,\n\n\n [[[-2.2773e-02, -7.9663e-03, 1.3650e-02],\n [-1.6836e-02, -3.5315e-02, 3.0271e-03],\n [-7.9221e-03, -3.4851e-02, -1.4659e-02]],\n\n [[-8.1104e-03, -8.6989e-03, -5.8615e-03],\n [ 3.6122e-03, 8.8096e-03, 4.1805e-03],\n [ 1.6882e-02, 4.5378e-02, 1.1896e-02]],\n\n [[ 1.2342e-02, -8.8450e-03, -1.1099e-02],\n [ 2.1645e-02, -1.3660e-02, 1.5600e-02],\n [ 3.7208e-02, -2.0460e-03, 2.6873e-02]],\n\n ...,\n\n [[-1.2473e-02, 7.4931e-03, 3.3763e-02],\n [-1.1667e-02, -2.5294e-02, 1.6085e-02],\n [ 1.1795e-04, -1.3193e-02, 2.6644e-02]],\n\n [[-6.4799e-03, 5.2122e-03, 7.1232e-03],\n [ 1.0016e-02, -7.4409e-03, 4.1851e-03],\n [ 1.1962e-02, 3.3279e-02, 1.4415e-02]],\n\n [[-2.2898e-02, -2.5776e-02, -2.5866e-02],\n [-1.7888e-02, -1.0995e-02, -3.6496e-02],\n [-1.2419e-02, -7.4454e-03, -7.6183e-03]]],\n\n\n [[[ 2.1076e-02, 5.8897e-03, 1.8262e-02],\n [ 1.6777e-02, -4.5140e-03, -1.6843e-03],\n [ 1.2015e-02, 2.0856e-02, 2.1313e-02]],\n\n [[ 5.0178e-04, -2.2424e-02, -1.3022e-02],\n [-1.9282e-02, -1.7869e-02, -3.1720e-02],\n [-1.2770e-02, -7.1618e-03, -2.0935e-02]],\n\n [[-7.2795e-03, 1.8958e-03, -7.8742e-03],\n [-9.5339e-03, 1.1826e-02, 6.5421e-03],\n [-2.1489e-02, -2.2284e-02, -1.8736e-02]],\n\n ...,\n\n [[-1.6924e-02, -5.3901e-03, -1.1037e-02],\n [-1.7034e-02, 5.9339e-03, 3.4978e-03],\n [-4.2843e-02, -6.5180e-03, 1.7559e-02]],\n\n [[-1.8640e-02, -5.1491e-03, -1.2567e-02],\n [-1.3252e-02, 1.9999e-03, -5.9602e-03],\n [-2.6601e-03, 1.2135e-03, 6.1452e-03]],\n\n [[-6.7909e-03, -1.1320e-03, 3.1303e-04],\n [-7.5666e-03, 4.5274e-03, -1.0467e-02],\n [-4.8564e-03, 2.1680e-03, 1.0068e-02]]],\n\n\n [[[-1.2450e-02, -8.9318e-03, -6.0592e-03],\n [-8.8395e-03, -1.4457e-02, 2.2903e-03],\n [-1.7844e-02, -2.7272e-02, 2.2017e-03]],\n\n [[ 9.9853e-04, -1.2388e-02, 2.1353e-04],\n [-2.4078e-03, -1.7928e-02, -7.4237e-03],\n [ 4.0734e-03, -1.6215e-02, -1.0232e-02]],\n\n [[-1.9751e-03, -9.2477e-03, 7.6392e-03],\n [-5.5263e-03, -2.2326e-02, 3.6051e-03],\n [ 8.2693e-03, -6.2639e-03, 1.6572e-02]],\n\n ...,\n\n [[-2.1451e-02, -1.2811e-02, 1.3807e-02],\n [-1.2682e-02, -9.5688e-03, -8.1314e-03],\n [-2.3794e-02, -3.9985e-03, 4.0381e-02]],\n\n [[ 6.3211e-04, 1.5736e-03, 8.6739e-03],\n [ 6.6791e-03, -4.4048e-04, 2.0593e-02],\n [ 8.0962e-03, 7.0344e-03, 3.6155e-03]],\n\n [[-9.5361e-03, -9.1248e-03, -1.9758e-03],\n [ 3.6287e-03, 6.6854e-03, 8.0088e-03],\n [-1.9481e-02, -2.1702e-02, -1.5170e-02]]]]), 'model.layer3.5.bn2.weight': tensor([0.1750, 0.1587, 0.1687, 0.2068, 0.1659, 0.1848, 0.1909, 0.1791, 0.1924,\n 0.1585, 0.2059, 0.1703, 0.1881, 0.1802, 0.1853, 0.1850, 0.1963, 0.2007,\n 0.1521, 0.1775, 0.1982, 0.1857, 0.2573, 0.2056, 0.2648, 0.2001, 0.1871,\n 0.1668, 0.1489, 0.1450, 0.2128, 0.1841, 0.2345, 0.1476, 0.2069, 0.2218,\n 0.1976, 0.2001, 0.1872, 0.2593, 0.2612, 0.1698, 0.1416, 0.2132, 0.1663,\n 0.1502, 0.1777, 0.1599, 0.2165, 0.2079, 0.1486, 0.2080, 0.1942, 0.2076,\n 0.1846, 0.2018, 0.2661, 0.2116, 0.2294, 0.1603, 0.1358, 0.1929, 0.1544,\n 0.1905, 0.1996, 0.2052, 0.1843, 0.1905, 0.1699, 0.1640, 0.2321, 0.1444,\n 0.1707, 0.1939, 0.1521, 0.2053, 0.1743, 0.1923, 0.1680, 0.2263, 0.1761,\n 0.1767, 0.1672, 0.1881, 0.1667, 0.1528, 0.1592, 0.2003, 0.2368, 0.1937,\n 0.2155, 0.1924, 0.1894, 0.1846, 0.1979, 0.1634, 0.1681, 0.1765, 0.2059,\n 0.1874, 0.2547, 0.1851, 0.1819, 0.1968, 0.2112, 0.2343, 0.1815, 0.2007,\n 0.2033, 0.1935, 0.1965, 0.1971, 0.1787, 0.1567, 0.2230, 0.1748, 0.2362,\n 0.2460, 0.1578, 0.1559, 0.1541, 0.1795, 0.2661, 0.2052, 0.1540, 0.1597,\n 0.1799, 0.1694, 0.1789, 0.1868, 0.2181, 0.1896, 0.1800, 0.1582, 0.1855,\n 0.2052, 0.1856, 0.1839, 0.2021, 0.1994, 0.1753, 0.2237, 0.1868, 0.1800,\n 0.1466, 0.2577, 0.1520, 0.1473, 0.1883, 0.1823, 0.1837, 0.1985, 0.1802,\n 0.2096, 0.1852, 0.1610, 0.2043, 0.1330, 0.1777, 0.1655, 0.1551, 0.2113,\n 0.1880, 0.1743, 0.1890, 0.1599, 0.1681, 0.1819, 0.1902, 0.1322, 0.1656,\n 0.1268, 0.1937, 0.2612, 0.1753, 0.1452, 0.1984, 0.2158, 0.1964, 0.1547,\n 0.1505, 0.2846, 0.2457, 0.1824, 0.2196, 0.2074, 0.2704, 0.1886, 0.1766,\n 0.2037, 0.1850, 0.1958, 0.1520, 0.1496, 0.1801, 0.1787, 0.2011, 0.1932,\n 0.2107, 0.4421, 0.1326, 0.2065, 0.2101, 0.2300, 0.1898, 0.1845, 0.2167,\n 0.2390, 0.2009, 0.1675, 0.1934, 0.2303, 0.1866, 0.2308, 0.1636, 0.2216,\n 0.1975, 0.1374, 0.1702, 0.2025, 0.1996, 0.1968, 0.1913, 0.2096, 0.1871,\n 0.1810, 0.1897, 0.1808, 0.2468, 0.1656, 0.1594, 0.2586, 0.2046, 0.1309,\n 0.2346, 0.5309, 0.1871, 0.1549, 0.1668, 0.1849, 0.1898, 0.1841, 0.1824,\n 0.1808, 0.2365, 0.1650, 0.2019, 0.1609, 0.1951, 0.2089, 0.1972, 0.1951,\n 0.1752, 0.2043, 0.1741, 0.2727]), 'model.layer3.5.bn2.bias': tensor([-0.1009, -0.0403, -0.0711, -0.1111, -0.1360, -0.0971, -0.1292, -0.0304,\n -0.1892, -0.0535, -0.1929, -0.0562, -0.1675, -0.1251, -0.1130, -0.0160,\n -0.0925, -0.0604, -0.0330, -0.1028, -0.1558, -0.0816, -0.1240, -0.0597,\n -0.1860, -0.0698, -0.0778, -0.0723, -0.0709, -0.0188, -0.1088, -0.0686,\n -0.0798, -0.0126, -0.1197, -0.0126, -0.1004, -0.0737, -0.0628, -0.1359,\n -0.1773, -0.0835, 0.1771, -0.1284, -0.0886, -0.0244, -0.1256, -0.0564,\n -0.2002, -0.0631, 0.1097, -0.1553, -0.0750, -0.1707, -0.1101, -0.1163,\n -0.1636, -0.1097, -0.1405, -0.0508, 0.0802, -0.0752, -0.0659, -0.0898,\n -0.2027, -0.1226, -0.0533, -0.0774, -0.0053, -0.0698, -0.1506, -0.0398,\n -0.1054, -0.1117, -0.0252, -0.0651, -0.0855, -0.0781, -0.0682, -0.0899,\n -0.0554, -0.1542, -0.0805, -0.0886, -0.0761, -0.0780, -0.0849, -0.0966,\n -0.2543, -0.0953, -0.0959, -0.1458, -0.0488, -0.1474, -0.1171, -0.0614,\n -0.0921, -0.1214, -0.1367, -0.0913, -0.0644, -0.1673, -0.1069, -0.1303,\n -0.0769, -0.2406, -0.0717, -0.0619, -0.1001, -0.1260, -0.0939, -0.0644,\n -0.1248, -0.0654, -0.0723, -0.1396, -0.0899, -0.0478, 0.0225, -0.0502,\n -0.0221, -0.1055, -0.1237, -0.1157, -0.0129, -0.0091, -0.1005, -0.1607,\n -0.1238, -0.0935, -0.1170, -0.0620, -0.0885, -0.0635, -0.1484, -0.1794,\n -0.1800, -0.1574, -0.1596, -0.0752, -0.0426, -0.2185, -0.0950, -0.0891,\n 0.0180, -0.0934, -0.0200, 0.0068, -0.1177, -0.0334, -0.0571, -0.0917,\n -0.1081, -0.0929, -0.0059, -0.0925, -0.1148, 0.0839, -0.0779, -0.0787,\n -0.0486, -0.0958, -0.1377, -0.1049, -0.0801, -0.0630, -0.1072, -0.1322,\n -0.1328, -0.0447, -0.0488, 0.0527, -0.0944, -0.0656, -0.0495, 0.0114,\n -0.1428, -0.0975, -0.1274, -0.0467, 0.0074, -0.2550, -0.0830, -0.0999,\n -0.0278, -0.0931, -0.1197, -0.1267, -0.1003, -0.1476, -0.0952, -0.1335,\n 0.0087, -0.0196, -0.0780, -0.0882, -0.0846, -0.1558, -0.1704, -0.1701,\n 0.0829, -0.1550, -0.0878, -0.1308, -0.1370, -0.0792, -0.1255, -0.1160,\n -0.1124, -0.0708, -0.0716, -0.1385, -0.0772, -0.1709, -0.0418, -0.1468,\n -0.0959, 0.0767, -0.0753, -0.1245, -0.0842, -0.1409, -0.1050, -0.1705,\n -0.0991, -0.0916, -0.1527, -0.0485, -0.0725, -0.0169, 0.0165, -0.2591,\n -0.0908, 0.1169, -0.1097, -0.3899, -0.0586, 0.0136, -0.0560, -0.1186,\n -0.0654, -0.0691, -0.0546, -0.0703, -0.2361, -0.0625, -0.1823, -0.0626,\n -0.1787, -0.1711, -0.1230, -0.0642, -0.0937, -0.0713, -0.0916, -0.0748]), 'model.layer3.5.bn2.running_mean': tensor([-8.4181e-02, -8.2326e-02, -6.7000e-02, 2.8380e-02, -8.9266e-02,\n -2.7789e-02, -7.9282e-02, -9.4030e-02, -1.0547e-01, 1.2810e-02,\n -1.0002e-01, -1.0160e-01, -1.8789e-01, -4.9570e-02, -6.5080e-02,\n -7.1006e-02, 2.2533e-01, -1.8595e-01, -9.4142e-02, 1.0086e-01,\n -1.0337e-01, -1.8474e-01, 7.8119e-02, -1.0911e-02, 2.9613e-02,\n -9.4249e-02, -1.1028e-01, -1.8137e-01, -9.8426e-02, -1.1198e-02,\n -5.3423e-02, -4.5980e-02, -2.1391e-02, -6.6220e-02, -7.2397e-02,\n -6.3837e-02, -2.1337e-01, -7.0305e-02, -9.1014e-02, -6.3084e-02,\n -9.0760e-02, 8.1402e-02, 2.2011e-04, -1.4538e-01, -6.6716e-02,\n 2.8895e-02, 4.0733e-02, -8.1939e-02, -1.2133e-01, -1.8008e-02,\n 3.0957e-02, -1.4883e-02, -7.5148e-02, -1.4288e-02, 3.9807e-02,\n -2.6728e-02, -6.2214e-02, -1.1109e-01, 8.3818e-03, -5.7483e-02,\n 6.0772e-03, -4.1076e-02, -3.7120e-02, -8.8404e-02, -1.4835e-01,\n -2.3938e-02, -1.2328e-01, -1.4945e-01, 1.2005e-02, 3.3990e-02,\n 6.6530e-02, -1.2301e-01, -1.1683e-01, -8.1122e-03, -1.2276e-01,\n -1.0402e-01, 1.4306e-02, -2.3934e-03, 6.1110e-02, 2.1150e-02,\n 3.3447e-02, -6.3191e-02, -7.3488e-02, -7.7903e-02, -7.3816e-02,\n -4.6019e-02, -8.1536e-02, -7.3652e-02, -1.3919e-01, -5.5852e-02,\n -1.3068e-01, 5.9639e-02, -9.5295e-02, -1.0258e-01, 1.2126e-01,\n -6.1944e-02, 2.4068e-02, -8.6513e-02, -3.4539e-02, -7.9883e-02,\n -4.6716e-02, -1.6339e-01, -1.1471e-01, -5.2539e-02, -3.6446e-02,\n 2.0635e-01, 6.4211e-02, -5.4585e-02, 4.2873e-02, -3.2897e-02,\n -2.0750e-02, 3.1847e-02, -1.3547e-01, 1.2281e-02, -4.9348e-02,\n -7.3229e-02, -2.0142e-02, 5.9411e-02, 3.6017e-02, -6.5846e-02,\n -1.3510e-01, -1.2991e-01, -9.9091e-02, -5.9973e-02, -8.7046e-02,\n -1.1048e-01, -8.5441e-02, -1.2895e-01, -6.2395e-02, -7.0458e-02,\n 2.6096e-02, -6.6930e-02, -9.0618e-02, -7.1837e-02, -1.2942e-01,\n -5.2548e-02, -1.4470e-01, 7.4290e-03, -1.1715e-01, -2.6683e-02,\n -5.4303e-02, -6.0601e-03, 6.0263e-02, 9.8338e-02, -5.3147e-02,\n -1.0542e-02, 9.2749e-02, -6.4288e-02, -8.6226e-02, 3.0741e-03,\n -3.2823e-02, 3.3325e-02, -6.7326e-02, -1.2881e-01, -7.9075e-02,\n -7.1262e-02, -2.3154e-02, -1.8101e-01, -1.3029e-01, -3.5888e-02,\n -1.9665e-01, -1.0845e-01, -7.7754e-02, 1.8175e-02, -2.2423e-02,\n -4.1685e-02, -4.6929e-02, -1.0649e-01, 5.1526e-03, -2.1710e-02,\n -9.2819e-02, 4.4477e-02, -6.8316e-02, -2.7507e-02, -9.5737e-02,\n -6.3383e-02, 5.8870e-02, -1.0825e-01, -4.4511e-02, -1.5717e-02,\n -1.5852e-01, -8.3429e-02, -9.0957e-03, 8.3562e-02, -6.4215e-02,\n -1.2740e-01, 4.9480e-02, -7.6528e-02, -1.2662e-01, 5.8105e-02,\n -9.2202e-02, -8.3319e-03, -2.1970e-02, -1.0069e-02, 3.6206e-02,\n -3.4947e-02, -1.6918e-02, -1.1844e-01, 2.1442e-02, -1.6731e-01,\n 2.7476e-02, -9.9975e-02, -6.7386e-02, 1.2262e-01, -8.2855e-02,\n -4.0228e-02, -7.2002e-03, -3.5221e-02, 4.9355e-02, 2.1895e-02,\n -1.0512e-01, 3.3680e-02, -1.6209e-01, 9.5936e-02, -6.6630e-03,\n 2.3074e-02, -3.8734e-02, -1.1970e-01, -1.6922e-01, 4.6492e-02,\n -9.3482e-02, 1.3027e-01, 5.8050e-02, -9.2339e-02, -1.0873e-01,\n -7.2134e-02, -1.3823e-01, 4.1838e-02, -7.0116e-02, -1.4505e-01,\n 4.6407e-03, -3.1226e-01, -5.7904e-02, 6.9387e-02, -1.2852e-02,\n -3.3404e-01, -8.6485e-02, -1.1261e-02, -6.3489e-02, 1.8326e-02,\n -6.5384e-03, -1.9885e-02, 2.9779e-02, -7.2005e-02, -7.1547e-02,\n -1.3066e-02, -9.4956e-02, -1.3677e-01, 1.5199e-01, -7.2918e-02,\n -2.2015e-02, -2.2407e-01, 2.6079e-03, -6.8740e-02, -5.2387e-02,\n -2.2323e-02]), 'model.layer3.5.bn2.running_var': tensor([0.0106, 0.0289, 0.0259, 0.0101, 0.0078, 0.0106, 0.0137, 0.0125, 0.0212,\n 0.0054, 0.0154, 0.0161, 0.0149, 0.0188, 0.0121, 0.0215, 0.0434, 0.0202,\n 0.0247, 0.0686, 0.0136, 0.0181, 0.0437, 0.0117, 0.0200, 0.0208, 0.0175,\n 0.0159, 0.0131, 0.0116, 0.0154, 0.0089, 0.0127, 0.0253, 0.0210, 0.0629,\n 0.0193, 0.0273, 0.0164, 0.0368, 0.0148, 0.0467, 0.0165, 0.0111, 0.0128,\n 0.0119, 0.0075, 0.0248, 0.0130, 0.0203, 0.0145, 0.0190, 0.0121, 0.0121,\n 0.0434, 0.0076, 0.0170, 0.0486, 0.0070, 0.0161, 0.0168, 0.0117, 0.0191,\n 0.0172, 0.0243, 0.0075, 0.0167, 0.0344, 0.0152, 0.0194, 0.0212, 0.0081,\n 0.0259, 0.0378, 0.0252, 0.0278, 0.0253, 0.0128, 0.0166, 0.0145, 0.0164,\n 0.0089, 0.0228, 0.0104, 0.0207, 0.0105, 0.0115, 0.0109, 0.0124, 0.0345,\n 0.0205, 0.0193, 0.0218, 0.0407, 0.0108, 0.0144, 0.0244, 0.0093, 0.0186,\n 0.0194, 0.0163, 0.0157, 0.0336, 0.0104, 0.0140, 0.0415, 0.0341, 0.0273,\n 0.0251, 0.0138, 0.0097, 0.0784, 0.0111, 0.0226, 0.0255, 0.0125, 0.0146,\n 0.1604, 0.0121, 0.0256, 0.0222, 0.0282, 0.0542, 0.0259, 0.0380, 0.0191,\n 0.0179, 0.0106, 0.0116, 0.0202, 0.0127, 0.0091, 0.0211, 0.0090, 0.0126,\n 0.0140, 0.0173, 0.0231, 0.0271, 0.0092, 0.0150, 0.0115, 0.0078, 0.0081,\n 0.0339, 0.0255, 0.0147, 0.0131, 0.0117, 0.0451, 0.0272, 0.0124, 0.0100,\n 0.0211, 0.0243, 0.0235, 0.0137, 0.0167, 0.0148, 0.0174, 0.0355, 0.0269,\n 0.0220, 0.0115, 0.0269, 0.0194, 0.0199, 0.0112, 0.0112, 0.0207, 0.0236,\n 0.0219, 0.0226, 0.0327, 0.0168, 0.0135, 0.0247, 0.0140, 0.0171, 0.0202,\n 0.0166, 0.0124, 0.0218, 0.0331, 0.0111, 0.0287, 0.0142, 0.0099, 0.0314,\n 0.0232, 0.0250, 0.0209, 0.0085, 0.0169, 0.0397, 0.0179, 0.0291, 0.0347,\n 0.0403, 0.0337, 0.0362, 0.0078, 0.0315, 0.0166, 0.0160, 0.0198, 0.0110,\n 0.0144, 0.0098, 0.0586, 0.0149, 0.0107, 0.0097, 0.0361, 0.0146, 0.0110,\n 0.0146, 0.0212, 0.0227, 0.0073, 0.0126, 0.0336, 0.0377, 0.0109, 0.0176,\n 0.0072, 0.0102, 0.0486, 0.0232, 0.0180, 0.0112, 0.0415, 0.0097, 0.0280,\n 0.0125, 0.0336, 0.0147, 0.0171, 0.0130, 0.0124, 0.0099, 0.0220, 0.0116,\n 0.0140, 0.0191, 0.0265, 0.0082, 0.0143, 0.0075, 0.0511, 0.0119, 0.0203,\n 0.0359, 0.0095, 0.0173, 0.0429]), 'model.layer3.5.bn2.num_batches_tracked': tensor(7160), 'model.layer3.5.conv3.weight': tensor([[[[-0.0042]],\n\n [[ 0.0078]],\n\n [[-0.0019]],\n\n ...,\n\n [[ 0.0002]],\n\n [[ 0.0034]],\n\n [[-0.0012]]],\n\n\n [[[ 0.0089]],\n\n [[ 0.0104]],\n\n [[ 0.0597]],\n\n ...,\n\n [[-0.0264]],\n\n [[-0.0043]],\n\n [[ 0.0049]]],\n\n\n [[[-0.0370]],\n\n [[-0.0096]],\n\n [[-0.0322]],\n\n ...,\n\n [[-0.0104]],\n\n [[ 0.0151]],\n\n [[-0.0425]]],\n\n\n ...,\n\n\n [[[-0.0290]],\n\n [[ 0.0054]],\n\n [[-0.0142]],\n\n ...,\n\n [[ 0.0339]],\n\n [[ 0.0137]],\n\n [[-0.0005]]],\n\n\n [[[-0.0041]],\n\n [[-0.0068]],\n\n [[ 0.0055]],\n\n ...,\n\n [[ 0.0139]],\n\n [[-0.0081]],\n\n [[-0.0238]]],\n\n\n [[[ 0.0081]],\n\n [[-0.0056]],\n\n [[ 0.0044]],\n\n ...,\n\n [[-0.0046]],\n\n [[-0.0171]],\n\n [[-0.0139]]]]), 'model.layer3.5.bn3.weight': tensor([-1.7373e-04, 2.3868e-01, 1.2591e-01, ..., 1.1618e-01,\n 1.0262e-01, 5.9561e-02]), 'model.layer3.5.bn3.bias': tensor([-0.0060, -0.2807, -0.1698, ..., -0.1645, -0.0935, -0.0582]), 'model.layer3.5.bn3.running_mean': tensor([-0.0162, -0.0560, -0.0332, ..., -0.0035, -0.0339, -0.0303]), 'model.layer3.5.bn3.running_var': tensor([0.0014, 0.0151, 0.0035, ..., 0.0035, 0.0031, 0.0033]), 'model.layer3.5.bn3.num_batches_tracked': tensor(7160), 'model.layer4.0.conv1.weight': tensor([[[[-0.0058]],\n\n [[ 0.0044]],\n\n [[ 0.0058]],\n\n ...,\n\n [[-0.0117]],\n\n [[-0.0074]],\n\n [[ 0.0164]]],\n\n\n [[[ 0.0443]],\n\n [[ 0.0338]],\n\n [[ 0.0117]],\n\n ...,\n\n [[-0.0069]],\n\n [[ 0.0016]],\n\n [[ 0.0330]]],\n\n\n [[[-0.0004]],\n\n [[ 0.0145]],\n\n [[-0.0125]],\n\n ...,\n\n [[-0.0226]],\n\n [[ 0.0306]],\n\n [[-0.0047]]],\n\n\n ...,\n\n\n [[[-0.0115]],\n\n [[-0.0082]],\n\n [[ 0.0512]],\n\n ...,\n\n [[ 0.0014]],\n\n [[ 0.0230]],\n\n [[ 0.0030]]],\n\n\n [[[-0.0127]],\n\n [[ 0.0011]],\n\n [[ 0.0359]],\n\n ...,\n\n [[-0.0145]],\n\n [[ 0.0279]],\n\n [[-0.0077]]],\n\n\n [[[ 0.0234]],\n\n [[ 0.0393]],\n\n [[-0.0082]],\n\n ...,\n\n [[-0.0335]],\n\n [[-0.0199]],\n\n [[-0.0336]]]]), 'model.layer4.0.bn1.weight': tensor([0.2497, 0.2023, 0.2156, 0.2002, 0.2483, 0.1165, 0.2013, 0.2096, 0.2542,\n 0.2115, 0.2138, 0.2299, 0.1979, 0.2243, 0.2212, 0.2203, 0.2428, 0.2802,\n 0.2225, 0.1772, 0.2101, 0.2248, 0.1707, 0.1743, 0.2050, 0.1927, 0.2319,\n 0.2495, 0.1960, 0.2403, 0.1949, 0.1868, 0.2191, 0.1948, 0.2039, 0.2017,\n 0.2611, 0.2219, 0.2435, 0.2337, 0.2158, 0.2216, 0.2053, 0.2315, 0.2614,\n 0.2162, 0.2010, 0.2256, 0.2300, 0.1141, 0.2335, 0.2331, 0.1782, 0.2272,\n 0.2326, 0.2811, 0.2152, 0.1842, 0.1846, 0.2587, 0.1864, 0.2132, 0.2319,\n 0.2038, 0.2537, 0.1780, 0.2038, 0.1882, 0.2497, 0.2163, 0.2496, 0.1884,\n 0.2318, 0.2063, 0.2124, 0.1993, 0.1987, 0.1975, 0.2395, 0.2330, 0.2356,\n 0.2435, 0.2160, 0.1981, 0.2033, 0.2314, 0.1785, 0.2298, 0.1528, 0.2415,\n 0.2224, 0.1895, 0.2175, 0.2287, 0.1912, 0.2109, 0.1967, 0.2515, 0.2547,\n 0.1897, 0.2335, 0.2315, 0.2646, 0.1991, 0.2130, 0.2431, 0.2042, 0.2085,\n 0.2289, 0.2441, 0.2020, 0.2537, 0.1868, 0.2100, 0.2042, 0.2340, 0.2130,\n 0.2257, 0.2213, 0.2165, 0.2391, 0.2050, 0.1988, 0.2128, 0.2290, 0.2215,\n 0.2485, 0.2409, 0.2193, 0.2180, 0.2249, 0.2196, 0.1937, 0.2172, 0.2362,\n 0.2012, 0.2332, 0.2248, 0.2308, 0.2234, 0.2272, 0.2057, 0.2959, 0.2160,\n 0.2310, 0.2136, 0.2018, 0.2203, 0.2529, 0.2205, 0.2275, 0.1407, 0.2140,\n 0.2158, 0.1749, 0.2351, 0.1982, 0.1922, 0.2298, 0.2440, 0.2393, 0.2623,\n 0.2239, 0.2544, 0.1963, 0.2486, 0.2305, 0.2112, 0.2220, 0.2084, 0.2312,\n 0.2476, 0.2152, 0.2427, 0.2058, 0.2291, 0.2182, 0.2167, 0.2490, 0.2579,\n 0.2556, 0.2225, 0.1901, 0.2105, 0.2379, 0.2221, 0.2329, 0.2161, 0.2203,\n 0.1986, 0.2466, 0.2227, 0.2226, 0.2095, 0.2159, 0.1796, 0.2190, 0.2051,\n 0.2520, 0.2296, 0.1978, 0.2144, 0.2025, 0.2324, 0.1906, 0.2632, 0.2083,\n 0.1436, 0.2087, 0.2145, 0.2172, 0.1987, 0.1927, 0.2149, 0.1926, 0.2029,\n 0.1906, 0.2198, 0.2436, 0.1994, 0.2271, 0.2198, 0.2119, 0.2116, 0.2321,\n 0.1845, 0.2213, 0.2285, 0.2746, 0.2471, 0.2265, 0.2247, 0.2665, 0.2408,\n 0.2054, 0.2281, 0.1804, 0.2599, 0.2365, 0.2069, 0.1238, 0.2388, 0.2224,\n 0.2139, 0.2257, 0.2257, 0.2014, 0.2255, 0.2514, 0.1746, 0.2420, 0.2576,\n 0.2175, 0.2646, 0.2161, 0.2546, 0.2081, 0.2137, 0.2172, 0.1863, 0.1886,\n 0.2461, 0.2008, 0.1768, 0.2149, 0.2050, 0.2196, 0.2098, 0.2116, 0.1900,\n 0.2080, 0.2094, 0.2258, 0.2487, 0.2515, 0.2076, 0.2195, 0.2145, 0.1758,\n 0.2259, 0.1977, 0.2198, 0.2346, 0.1870, 0.2630, 0.2316, 0.2277, 0.2375,\n 0.2464, 0.2250, 0.1703, 0.2416, 0.2557, 0.2412, 0.2063, 0.1770, 0.2161,\n 0.2155, 0.1869, 0.2019, 0.1886, 0.2127, 0.2270, 0.2130, 0.2197, 0.2395,\n 0.2395, 0.1904, 0.2379, 0.2166, 0.2536, 0.2252, 0.1799, 0.2420, 0.2207,\n 0.2195, 0.2559, 0.2383, 0.2709, 0.2277, 0.2317, 0.2103, 0.1840, 0.2175,\n 0.2187, 0.2318, 0.2107, 0.1758, 0.2338, 0.2134, 0.2166, 0.2154, 0.2255,\n 0.1972, 0.1974, 0.2084, 0.2214, 0.1536, 0.2074, 0.1973, 0.2588, 0.2068,\n 0.2340, 0.2213, 0.2398, 0.2011, 0.2120, 0.2167, 0.2311, 0.2498, 0.1801,\n 0.2200, 0.2419, 0.2066, 0.2119, 0.2170, 0.2305, 0.1898, 0.2091, 0.2160,\n 0.2503, 0.2168, 0.1968, 0.1796, 0.1791, 0.1911, 0.2480, 0.2443, 0.2162,\n 0.1825, 0.2920, 0.2142, 0.2378, 0.1809, 0.2175, 0.2231, 0.2238, 0.2240,\n 0.1821, 0.2277, 0.2370, 0.1938, 0.2428, 0.2317, 0.2184, 0.2256, 0.1985,\n 0.1965, 0.1985, 0.2153, 0.1915, 0.2322, 0.2081, 0.2168, 0.2597, 0.1893,\n 0.2013, 0.2412, 0.2390, 0.2572, 0.2161, 0.2598, 0.2398, 0.2358, 0.2256,\n 0.2447, 0.2477, 0.2016, 0.2452, 0.2312, 0.2438, 0.2066, 0.2029, 0.2341,\n 0.2345, 0.2004, 0.2228, 0.2400, 0.2165, 0.2260, 0.2418, 0.2350, 0.2007,\n 0.1366, 0.2370, 0.2453, 0.2297, 0.2198, 0.2126, 0.2488, 0.2606, 0.2478,\n 0.2244, 0.2518, 0.2082, 0.2437, 0.2165, 0.2315, 0.1176, 0.2124, 0.2402,\n 0.2254, 0.2228, 0.2293, 0.2464, 0.2305, 0.2610, 0.2186, 0.2279, 0.2442,\n 0.2070, 0.2056, 0.1956, 0.2194, 0.2524, 0.2227, 0.1989, 0.2039, 0.1837,\n 0.1915, 0.2703, 0.2386, 0.2567, 0.2041, 0.2356, 0.1983, 0.2264, 0.2101,\n 0.2355, 0.2314, 0.2078, 0.2157, 0.2084, 0.2100, 0.2032, 0.2282, 0.2118,\n 0.2196, 0.2386, 0.2268, 0.2513, 0.2289, 0.2386, 0.2308, 0.2218, 0.2250,\n 0.2801, 0.2261, 0.2287, 0.2322, 0.1980, 0.2017, 0.1852, 0.2166, 0.2324,\n 0.1919, 0.2437, 0.2057, 0.2344, 0.2118, 0.1834, 0.2782, 0.2043, 0.2516,\n 0.2261, 0.1993, 0.2086, 0.1980, 0.2027, 0.2201, 0.2462, 0.2291]), 'model.layer4.0.bn1.bias': tensor([-0.2289, -0.1777, -0.0923, -0.1532, -0.2755, 0.0628, -0.1239, -0.1880,\n -0.2339, -0.1059, -0.2000, -0.2068, -0.1892, -0.2130, -0.2327, -0.1570,\n -0.2531, -0.2128, -0.1890, -0.0612, -0.1518, -0.1606, -0.1140, -0.0892,\n -0.1449, -0.1160, -0.2392, -0.2636, -0.1571, -0.2394, -0.0857, -0.0729,\n -0.2326, -0.1226, -0.1806, -0.1307, -0.2016, -0.1859, -0.1781, -0.2481,\n -0.1640, -0.2204, -0.1527, -0.1277, -0.2629, -0.1004, -0.1102, -0.2585,\n -0.2515, 0.0883, -0.2158, -0.1258, -0.1321, -0.2422, -0.2421, -0.2851,\n -0.1700, -0.0597, -0.1045, -0.2839, -0.1010, -0.1555, -0.2104, -0.1424,\n -0.1807, -0.1211, -0.1452, -0.0618, -0.2525, -0.1297, -0.2560, -0.1202,\n -0.2536, -0.1806, -0.1851, -0.0907, -0.1745, -0.1610, -0.2652, -0.2122,\n -0.2352, -0.1988, -0.1308, -0.0948, -0.1344, -0.2122, -0.0992, -0.1618,\n -0.0350, -0.2531, -0.2360, -0.1606, -0.1760, -0.1974, -0.1563, -0.2052,\n -0.1478, -0.2454, -0.1878, -0.1114, -0.2844, -0.1610, -0.2664, -0.1234,\n -0.1348, -0.2250, -0.1291, -0.1197, -0.2538, -0.2477, -0.1496, -0.2158,\n -0.1312, -0.1418, -0.1853, -0.1964, -0.1476, -0.1845, -0.2447, -0.1835,\n -0.2533, -0.1157, -0.1605, -0.1051, -0.2109, -0.1998, -0.3167, -0.1856,\n -0.2201, -0.1686, -0.1963, -0.1606, -0.1730, -0.2023, -0.1840, -0.1393,\n -0.1519, -0.1153, -0.2064, -0.1929, -0.1723, -0.1462, -0.2804, -0.2375,\n -0.1308, -0.1770, -0.1606, -0.2127, -0.2448, -0.2083, -0.1960, -0.0532,\n -0.2124, -0.1012, -0.0665, -0.1721, -0.1384, -0.1689, -0.1809, -0.2330,\n -0.2197, -0.3149, -0.1791, -0.2592, -0.1192, -0.1312, -0.1565, -0.1943,\n -0.2144, -0.1264, -0.2133, -0.2634, -0.1799, -0.1992, -0.2023, -0.2134,\n -0.1445, -0.1910, -0.2157, -0.1602, -0.2195, -0.2076, -0.1572, -0.1847,\n -0.2152, -0.2305, -0.2426, -0.1300, -0.1739, -0.1882, -0.2177, -0.2071,\n -0.1495, -0.2046, -0.2150, -0.1388, -0.2277, -0.1723, -0.2444, -0.1841,\n -0.1501, -0.1836, -0.1405, -0.1835, -0.1536, -0.2723, -0.1490, 0.0625,\n -0.1365, -0.1359, -0.2210, -0.1839, -0.0919, -0.1773, -0.1242, -0.1462,\n -0.1162, -0.2473, -0.2379, -0.1652, -0.1983, -0.2146, -0.1035, -0.2039,\n -0.2329, -0.1476, -0.1722, -0.1975, -0.2391, -0.2679, -0.1680, -0.2179,\n -0.2599, -0.0299, -0.1969, -0.1662, -0.0717, -0.2424, -0.1931, -0.1133,\n 0.0235, -0.2114, -0.2102, -0.1794, -0.1856, -0.1310, -0.1430, -0.1589,\n -0.2314, -0.0953, -0.1721, -0.2975, -0.2197, -0.2556, -0.1198, -0.1655,\n -0.1373, -0.1854, -0.1608, -0.1480, -0.1595, -0.2265, -0.1186, -0.0925,\n -0.1888, -0.1327, -0.1641, -0.1383, -0.2147, -0.1402, -0.1933, -0.1431,\n -0.1266, -0.2100, -0.2668, -0.1132, -0.1951, -0.0904, -0.1142, -0.1768,\n -0.1569, -0.1627, -0.2261, -0.0990, -0.2717, -0.1417, -0.2549, -0.2121,\n -0.1585, -0.1683, -0.0614, -0.2357, -0.2714, -0.2899, -0.1959, -0.1015,\n -0.1739, -0.1862, -0.0914, -0.1425, -0.0978, -0.1944, -0.2098, -0.1967,\n -0.2313, -0.1930, -0.2350, -0.0792, -0.1591, -0.1574, -0.2329, -0.1973,\n -0.1365, -0.2229, -0.1959, -0.1947, -0.2474, -0.2426, -0.2869, -0.2105,\n -0.2249, -0.1878, -0.0872, -0.1269, -0.1641, -0.1687, -0.2147, -0.1299,\n -0.1574, -0.1649, -0.2109, -0.1599, -0.1076, -0.1547, -0.1676, -0.1753,\n -0.2252, -0.0896, -0.1205, -0.1067, -0.3294, -0.2100, -0.2073, -0.1452,\n -0.2373, -0.1215, -0.1374, -0.1395, -0.2068, -0.2163, -0.0934, -0.1882,\n -0.2674, -0.1906, -0.2118, -0.2799, -0.1517, -0.1385, -0.1949, -0.1769,\n -0.2529, -0.1794, -0.1705, -0.1034, -0.0907, -0.1429, -0.2241, -0.2819,\n -0.2547, -0.1668, -0.3544, -0.1494, -0.1640, -0.1366, -0.1470, -0.1673,\n -0.1873, -0.2071, -0.0903, -0.1641, -0.2678, -0.0945, -0.2126, -0.1463,\n -0.2173, -0.2397, -0.1014, -0.1766, -0.1359, -0.1863, -0.1330, -0.2751,\n -0.1951, -0.2176, -0.2197, -0.0909, -0.1222, -0.2614, -0.1519, -0.2180,\n -0.1520, -0.2994, -0.2601, -0.2759, -0.1971, -0.2954, -0.2539, -0.1638,\n -0.2743, -0.1790, -0.2671, -0.1777, -0.1287, -0.1724, -0.1955, -0.1111,\n -0.1728, -0.2656, -0.1612, -0.1717, -0.2277, -0.2410, -0.1205, 0.1029,\n -0.2177, -0.2167, -0.2102, -0.1480, -0.1207, -0.3207, -0.2871, -0.2670,\n -0.1558, -0.2107, -0.1436, -0.2923, -0.1635, -0.2108, 0.1344, -0.1677,\n -0.2302, -0.1616, -0.1804, -0.2091, -0.1978, -0.2229, -0.2133, -0.1498,\n -0.2394, -0.2335, -0.1520, -0.1611, -0.1403, -0.1809, -0.2605, -0.1536,\n -0.1099, -0.1255, -0.1218, -0.1016, -0.1917, -0.1991, -0.2475, -0.1648,\n -0.2563, -0.1152, -0.1896, -0.1990, -0.2153, -0.2177, -0.1591, -0.1597,\n -0.1471, -0.1623, -0.2016, -0.2294, -0.2035, -0.1890, -0.2503, -0.1769,\n -0.2463, -0.2038, -0.1903, -0.2162, -0.1746, -0.1794, -0.2582, -0.1984,\n -0.2333, -0.2101, -0.1595, -0.1335, -0.1234, -0.1488, -0.2151, -0.1036,\n -0.1966, -0.1368, -0.1749, -0.0930, -0.1202, -0.3007, -0.1746, -0.1553,\n -0.2291, -0.1096, -0.1936, -0.0892, -0.1524, -0.1500, -0.2820, -0.1964]), 'model.layer4.0.bn1.running_mean': tensor([-0.0544, 0.0054, -0.0070, 0.0090, -0.0726, 0.1031, -0.0695, -0.0136,\n -0.0719, -0.0732, -0.0377, -0.0917, 0.0240, 0.0043, -0.0413, -0.0609,\n -0.0371, -0.1523, -0.0311, -0.0020, -0.0369, -0.1510, -0.0943, -0.0180,\n -0.0728, -0.0461, -0.0793, -0.0497, -0.0372, -0.0643, -0.0312, 0.0371,\n -0.0202, -0.0140, 0.0192, -0.0211, -0.0543, -0.0116, -0.0722, -0.0650,\n -0.0740, -0.0397, -0.0307, -0.0156, -0.0493, -0.0262, -0.0519, -0.0793,\n -0.0580, -0.0005, -0.0680, -0.0783, 0.0029, 0.0087, -0.1005, -0.1177,\n -0.1061, -0.0182, 0.0103, -0.0860, -0.0321, -0.1169, -0.0524, -0.0703,\n -0.1628, 0.0195, -0.0960, -0.0392, -0.0458, -0.0304, -0.0271, -0.0413,\n -0.0392, -0.0549, -0.0560, 0.0086, -0.0240, -0.0586, -0.0111, -0.0902,\n -0.1387, -0.0852, 0.0210, -0.0317, -0.0461, -0.0857, -0.0224, -0.0547,\n -0.0876, -0.1320, -0.0905, -0.0400, 0.0419, -0.0900, -0.0159, -0.0318,\n -0.0626, -0.0663, -0.1027, -0.0410, -0.0698, -0.0168, -0.1121, -0.0951,\n -0.0794, -0.0264, -0.0431, -0.0951, -0.1026, -0.0453, -0.0876, -0.0879,\n -0.0408, -0.0462, -0.0598, -0.1047, -0.0222, -0.1334, -0.0591, -0.0505,\n -0.0609, -0.0375, -0.0784, -0.0722, -0.0568, -0.0444, -0.0752, -0.1268,\n -0.0833, -0.1228, -0.0739, -0.0494, -0.0871, -0.0387, -0.0374, -0.0908,\n -0.0428, -0.0078, -0.0028, -0.1253, -0.0650, -0.0836, -0.1148, -0.0023,\n -0.0606, -0.0966, -0.1500, -0.0344, -0.0738, 0.0047, -0.0484, 0.0511,\n -0.0289, -0.1493, -0.0591, -0.1019, -0.1200, 0.0172, -0.0664, 0.0149,\n -0.0185, -0.1348, -0.0578, -0.1164, -0.0704, -0.0489, -0.0577, -0.0787,\n -0.0158, -0.0809, -0.1257, -0.1005, -0.0297, -0.0430, -0.0279, -0.0257,\n -0.0795, -0.0346, -0.0378, -0.0344, -0.0549, -0.0396, -0.0104, -0.1086,\n -0.0568, -0.0391, -0.0912, 0.0242, -0.0643, -0.0305, -0.1082, -0.0262,\n 0.0338, -0.0184, 0.0057, 0.0126, -0.0721, 0.0017, -0.0603, -0.0892,\n -0.0940, -0.0401, -0.0680, -0.0340, -0.0668, -0.0400, -0.0232, -0.0596,\n -0.1669, -0.0680, -0.0037, -0.1041, -0.0729, -0.0527, -0.0248, -0.0247,\n -0.0283, -0.0391, -0.0753, -0.0408, -0.0134, -0.0335, -0.1117, -0.0699,\n -0.0522, 0.0324, -0.0488, -0.0505, -0.1150, -0.0672, -0.0439, -0.0413,\n -0.0797, 0.1700, -0.0437, -0.0895, 0.0345, -0.0265, -0.0539, -0.0876,\n -0.0457, -0.0078, -0.1144, -0.0626, -0.0354, -0.1164, -0.0717, -0.0957,\n -0.1836, -0.0286, -0.0865, -0.0577, -0.0279, -0.0691, -0.0747, -0.0794,\n -0.0233, -0.0692, -0.0515, -0.0483, -0.1014, -0.0960, -0.0657, -0.0817,\n -0.0563, -0.0686, -0.0534, -0.0352, -0.0934, 0.0337, -0.0899, -0.0783,\n -0.0597, -0.0233, -0.0918, -0.0319, -0.0472, 0.0110, -0.0066, -0.0297,\n -0.0642, 0.0019, -0.0127, 0.0382, -0.0200, -0.0596, -0.0486, -0.0710,\n -0.1069, -0.0301, -0.0889, -0.0860, -0.1711, -0.0391, -0.0657, -0.0270,\n -0.1319, 0.0047, -0.0165, 0.0187, 0.0063, -0.0287, -0.0477, -0.0459,\n -0.0577, -0.0665, -0.0612, -0.0857, -0.0528, -0.0576, -0.0057, -0.0358,\n -0.0251, -0.1039, -0.0532, -0.0671, -0.0387, -0.0689, -0.0931, -0.0402,\n -0.0321, -0.0298, 0.0594, 0.0036, -0.0165, 0.0129, -0.0177, -0.0338,\n -0.0891, -0.0203, 0.0157, 0.0091, -0.0622, -0.0243, -0.0513, -0.0805,\n -0.0333, -0.0265, -0.0919, -0.0695, -0.0941, -0.0198, -0.0243, -0.0739,\n -0.0792, -0.1014, -0.0489, -0.0614, -0.0781, -0.1154, -0.0008, -0.0746,\n -0.0501, -0.0234, -0.0591, -0.0069, -0.0253, -0.0353, 0.0125, -0.0396,\n -0.1106, -0.0556, -0.0235, -0.0795, -0.0572, -0.0764, -0.1733, -0.1227,\n -0.0294, -0.0353, -0.0479, 0.0086, -0.0390, -0.0674, -0.0491, -0.0739,\n -0.0199, -0.0303, -0.0593, -0.0800, -0.1007, 0.0007, -0.1234, -0.0617,\n -0.0405, -0.0595, -0.0352, -0.0530, -0.0396, -0.0525, -0.0364, -0.0961,\n -0.0771, -0.1100, -0.0054, -0.0193, -0.0377, -0.0529, -0.0970, -0.0287,\n -0.0736, -0.0135, -0.0458, -0.0723, -0.0490, -0.0592, -0.0774, -0.1019,\n -0.1045, -0.1022, -0.1015, -0.0088, 0.0348, -0.0541, -0.0880, -0.0315,\n -0.0146, -0.0640, -0.0077, -0.0081, -0.0552, -0.0271, -0.0035, -0.0533,\n -0.0582, -0.0869, -0.0872, -0.0335, -0.0093, -0.1191, -0.0845, -0.0733,\n -0.0185, -0.0683, -0.0117, -0.0707, -0.0541, -0.0513, -0.0702, -0.0921,\n 0.0222, 0.0027, -0.0531, -0.1011, -0.0913, -0.0402, -0.0306, -0.0851,\n -0.0754, -0.0673, -0.0021, -0.0377, -0.0170, 0.0157, -0.0427, -0.0448,\n -0.0721, -0.0208, -0.0956, -0.0617, -0.0994, -0.0692, -0.0093, -0.0899,\n -0.0650, -0.0644, -0.0512, -0.0694, -0.0731, 0.0037, -0.0448, -0.0172,\n -0.0345, -0.0724, -0.0890, -0.0702, -0.0600, -0.0372, -0.0118, -0.0493,\n -0.0713, -0.0320, -0.0907, -0.0966, -0.0738, -0.0441, -0.1190, -0.0626,\n -0.1004, -0.0741, -0.0110, -0.0864, -0.0303, -0.0688, -0.0332, -0.0464,\n -0.0431, -0.0625, -0.0147, -0.0271, -0.0245, -0.0603, -0.0720, -0.0661,\n -0.0038, -0.0297, -0.0421, -0.0404, -0.0034, -0.0547, -0.0476, -0.0504]), 'model.layer4.0.bn1.running_var': tensor([0.0120, 0.0063, 0.0111, 0.0095, 0.0158, 0.0200, 0.0138, 0.0081, 0.0107,\n 0.0103, 0.0101, 0.0099, 0.0144, 0.0117, 0.0085, 0.0107, 0.0090, 0.0132,\n 0.0151, 0.0095, 0.0123, 0.0153, 0.0206, 0.0086, 0.0098, 0.0097, 0.0157,\n 0.0125, 0.0117, 0.0099, 0.0151, 0.0087, 0.0072, 0.0103, 0.0114, 0.0070,\n 0.0192, 0.0121, 0.0153, 0.0162, 0.0107, 0.0130, 0.0118, 0.0104, 0.0130,\n 0.0162, 0.0162, 0.0248, 0.0087, 0.0161, 0.0084, 0.0139, 0.0106, 0.0063,\n 0.0135, 0.0127, 0.0149, 0.0118, 0.0081, 0.0113, 0.0102, 0.0196, 0.0091,\n 0.0135, 0.0177, 0.0082, 0.0147, 0.0135, 0.0183, 0.0115, 0.0101, 0.0078,\n 0.0152, 0.0100, 0.0123, 0.0123, 0.0069, 0.0157, 0.0074, 0.0086, 0.0165,\n 0.0108, 0.0124, 0.0133, 0.0177, 0.0099, 0.0072, 0.0098, 0.0103, 0.0130,\n 0.0111, 0.0132, 0.0065, 0.0078, 0.0137, 0.0144, 0.0081, 0.0094, 0.0299,\n 0.0114, 0.0099, 0.0156, 0.0201, 0.0077, 0.0147, 0.0111, 0.0169, 0.0094,\n 0.0126, 0.0092, 0.0142, 0.0097, 0.0087, 0.0091, 0.0083, 0.0098, 0.0123,\n 0.0201, 0.0119, 0.0138, 0.0086, 0.0148, 0.0112, 0.0111, 0.0108, 0.0088,\n 0.0085, 0.0130, 0.0080, 0.0109, 0.0099, 0.0178, 0.0164, 0.0084, 0.0108,\n 0.0131, 0.0076, 0.0113, 0.0078, 0.0075, 0.0152, 0.0112, 0.0174, 0.0081,\n 0.0135, 0.0116, 0.0227, 0.0066, 0.0083, 0.0064, 0.0077, 0.0122, 0.0151,\n 0.0231, 0.0128, 0.0212, 0.0143, 0.0059, 0.0094, 0.0168, 0.0099, 0.0160,\n 0.0098, 0.0168, 0.0094, 0.0161, 0.0091, 0.0088, 0.0071, 0.0144, 0.0169,\n 0.0157, 0.0084, 0.0163, 0.0094, 0.0098, 0.0115, 0.0094, 0.0101, 0.0166,\n 0.0170, 0.0108, 0.0056, 0.0133, 0.0142, 0.0112, 0.0141, 0.0083, 0.0104,\n 0.0094, 0.0190, 0.0092, 0.0218, 0.0103, 0.0117, 0.0107, 0.0093, 0.0179,\n 0.0119, 0.0109, 0.0126, 0.0081, 0.0126, 0.0137, 0.0076, 0.0097, 0.0102,\n 0.0182, 0.0265, 0.0108, 0.0085, 0.0161, 0.0227, 0.0088, 0.0084, 0.0117,\n 0.0097, 0.0108, 0.0122, 0.0135, 0.0168, 0.0099, 0.0156, 0.0106, 0.0126,\n 0.0069, 0.0117, 0.0122, 0.0205, 0.0107, 0.0163, 0.0113, 0.0092, 0.0422,\n 0.0159, 0.0094, 0.0096, 0.0128, 0.0124, 0.0106, 0.0065, 0.0129, 0.0123,\n 0.0131, 0.0121, 0.0254, 0.0162, 0.0094, 0.0170, 0.0082, 0.0198, 0.0091,\n 0.0098, 0.0096, 0.0108, 0.0103, 0.0138, 0.0117, 0.0158, 0.0088, 0.0085,\n 0.0128, 0.0139, 0.0087, 0.0121, 0.0187, 0.0093, 0.0067, 0.0121, 0.0088,\n 0.0124, 0.0090, 0.0178, 0.0078, 0.0121, 0.0118, 0.0066, 0.0096, 0.0110,\n 0.0082, 0.0143, 0.0081, 0.0117, 0.0126, 0.0110, 0.0207, 0.0107, 0.0090,\n 0.0166, 0.0103, 0.0139, 0.0113, 0.0125, 0.0071, 0.0135, 0.0081, 0.0142,\n 0.0088, 0.0154, 0.0085, 0.0122, 0.0080, 0.0117, 0.0070, 0.0104, 0.0141,\n 0.0129, 0.0130, 0.0143, 0.0143, 0.0116, 0.0116, 0.0070, 0.0130, 0.0185,\n 0.0169, 0.0151, 0.0110, 0.0189, 0.0135, 0.0124, 0.0083, 0.0117, 0.0087,\n 0.0099, 0.0075, 0.0117, 0.0163, 0.0117, 0.0089, 0.0081, 0.0203, 0.0128,\n 0.0094, 0.0090, 0.0093, 0.0064, 0.0053, 0.0142, 0.0143, 0.0066, 0.0103,\n 0.0093, 0.0104, 0.0140, 0.0097, 0.0130, 0.0158, 0.0161, 0.0106, 0.0110,\n 0.0194, 0.0103, 0.0079, 0.0088, 0.0089, 0.0089, 0.0120, 0.0189, 0.0090,\n 0.0126, 0.0090, 0.0134, 0.0134, 0.0093, 0.0197, 0.0189, 0.0096, 0.0088,\n 0.0117, 0.0153, 0.0112, 0.0148, 0.0169, 0.0147, 0.0121, 0.0153, 0.0127,\n 0.0147, 0.0138, 0.0122, 0.0117, 0.0158, 0.0212, 0.0092, 0.0167, 0.0149,\n 0.0097, 0.0198, 0.0076, 0.0098, 0.0103, 0.0087, 0.0104, 0.0186, 0.0142,\n 0.0085, 0.0153, 0.0123, 0.0119, 0.0097, 0.0106, 0.0170, 0.0090, 0.0079,\n 0.0077, 0.0100, 0.0174, 0.0099, 0.0146, 0.0104, 0.0071, 0.0120, 0.0137,\n 0.0176, 0.0100, 0.0100, 0.0121, 0.0077, 0.0198, 0.0121, 0.0152, 0.0087,\n 0.0197, 0.0064, 0.0149, 0.0097, 0.0145, 0.0171, 0.0085, 0.0170, 0.0101,\n 0.0134, 0.0062, 0.0147, 0.0189, 0.0123, 0.0181, 0.0260, 0.0158, 0.0118,\n 0.0099, 0.0082, 0.0116, 0.0165, 0.0055, 0.0114, 0.0139, 0.0079, 0.0115,\n 0.0103, 0.0128, 0.0082, 0.0146, 0.0103, 0.0088, 0.0165, 0.0113, 0.0121,\n 0.0153, 0.0239, 0.0189, 0.0115, 0.0175, 0.0090, 0.0091, 0.0092, 0.0093,\n 0.0115, 0.0173, 0.0122, 0.0158, 0.0140, 0.0203, 0.0154, 0.0113, 0.0131,\n 0.0103, 0.0063, 0.0088, 0.0162, 0.0222, 0.0138, 0.0151, 0.0145, 0.0085,\n 0.0201, 0.0168, 0.0117, 0.0109, 0.0061, 0.0159, 0.0087, 0.0103, 0.0142,\n 0.0123, 0.0157, 0.0144, 0.0226, 0.0171, 0.0179, 0.0182, 0.0167, 0.0154,\n 0.0120, 0.0101, 0.0069, 0.0096, 0.0099, 0.0085, 0.0110, 0.0140]), 'model.layer4.0.bn1.num_batches_tracked': tensor(7160), 'model.layer4.0.conv2.weight': tensor([[[[-3.4630e-03, -1.2428e-02, 1.2889e-02],\n [-3.6911e-03, -2.9329e-04, 5.6316e-03],\n [-7.8307e-03, -6.3704e-03, -1.5336e-02]],\n\n [[ 1.3649e-02, 1.1699e-02, 8.2261e-03],\n [ 2.3181e-02, 1.1960e-02, 1.7241e-02],\n [ 1.4340e-02, 1.6543e-02, 2.6014e-02]],\n\n [[ 1.8662e-02, 7.2164e-03, 2.0837e-02],\n [ 6.5987e-03, 1.0052e-02, 1.5684e-02],\n [ 7.0934e-03, 5.2095e-03, 2.8627e-03]],\n\n ...,\n\n [[-1.4502e-02, -7.7476e-03, -7.8422e-03],\n [-2.2571e-03, -3.8017e-03, -1.8680e-02],\n [-4.5107e-03, -1.9798e-02, -2.0846e-02]],\n\n [[-4.7030e-03, 3.6972e-03, 4.0114e-03],\n [-1.5526e-03, 2.1505e-02, 1.0873e-02],\n [ 1.5925e-02, 2.0714e-02, 1.9222e-02]],\n\n [[-4.8174e-03, -2.5818e-02, -1.7194e-02],\n [ 4.8200e-05, -3.7414e-03, -8.5297e-03],\n [ 4.0268e-03, 2.5653e-03, 8.2470e-03]]],\n\n\n [[[-4.5665e-03, -1.2880e-02, -1.3163e-02],\n [ 4.0917e-03, 5.6205e-04, 4.9353e-03],\n [ 3.2306e-03, -4.8418e-03, -2.9345e-03]],\n\n [[ 3.0958e-03, -1.7478e-02, -9.5489e-03],\n [ 2.6973e-03, -2.2771e-03, -1.5821e-02],\n [-5.0275e-03, -2.0649e-03, -5.5289e-03]],\n\n [[-1.0433e-02, -1.4048e-02, -8.1559e-03],\n [-1.2544e-02, -1.1379e-02, -2.5954e-03],\n [-5.5532e-03, 1.1127e-03, -1.1921e-02]],\n\n ...,\n\n [[-1.9947e-03, -3.5599e-03, 1.3914e-03],\n [-2.7772e-03, -1.2577e-03, -4.0089e-04],\n [ 4.0023e-03, 2.7747e-03, 1.7606e-02]],\n\n [[ 9.1757e-03, 1.3054e-02, 1.4169e-02],\n [ 5.8638e-03, 2.2934e-02, 1.0217e-02],\n [ 1.7381e-02, 2.7582e-02, 2.8655e-02]],\n\n [[ 1.0525e-02, 1.7293e-02, 2.1387e-02],\n [ 2.2401e-02, 1.0725e-02, 2.9929e-02],\n [ 1.5056e-02, 2.7866e-02, 4.4584e-04]]],\n\n\n [[[-8.9107e-03, -3.0170e-03, -1.7949e-02],\n [-4.2297e-03, -4.8236e-03, -1.1382e-02],\n [ 1.9679e-03, -2.7422e-03, -9.9884e-03]],\n\n [[-1.1756e-02, 6.5843e-03, 8.8698e-03],\n [ 8.9542e-03, 6.3191e-03, 1.2963e-02],\n [ 7.9263e-03, 1.6106e-02, 9.6161e-03]],\n\n [[ 1.4422e-02, 7.3808e-03, 1.3934e-02],\n [-8.4343e-03, 1.1174e-03, 1.4682e-04],\n [ 1.7398e-02, 4.8612e-03, 1.1352e-02]],\n\n ...,\n\n [[-2.4020e-02, -9.9869e-03, -9.1495e-03],\n [-1.6216e-02, 3.1288e-04, -1.1233e-02],\n [-4.8756e-03, -9.1365e-03, -9.3935e-03]],\n\n [[ 1.0263e-02, 5.5022e-03, 6.9018e-03],\n [ 1.2084e-02, -3.5223e-05, 6.8116e-03],\n [ 1.1122e-02, 1.4323e-02, 4.3233e-03]],\n\n [[ 9.6139e-03, -7.4315e-03, 5.1885e-03],\n [-1.6461e-03, -9.8449e-03, -7.4510e-03],\n [-1.9504e-03, -2.2423e-02, 2.1521e-03]]],\n\n\n ...,\n\n\n [[[ 9.0706e-03, 8.9116e-03, 5.3848e-03],\n [-4.5567e-03, -2.5360e-03, -1.1832e-02],\n [-5.1421e-03, 3.6405e-03, -1.4187e-02]],\n\n [[-9.0824e-03, -1.5345e-02, -1.2616e-02],\n [-1.8325e-02, -2.4997e-02, -2.3868e-02],\n [-9.3962e-03, -1.1331e-02, -5.7737e-03]],\n\n [[ 1.3459e-02, 7.5258e-03, 1.0640e-02],\n [ 5.3248e-03, 7.1960e-03, 1.9994e-02],\n [ 7.8380e-03, 1.4587e-02, 1.4341e-02]],\n\n ...,\n\n [[-5.8440e-03, 7.0863e-03, -1.1695e-02],\n [ 7.7927e-03, 1.7115e-02, 9.6631e-03],\n [ 1.3054e-02, 3.3289e-03, -1.5644e-03]],\n\n [[ 9.5569e-03, 4.9896e-03, -6.7540e-04],\n [-1.3702e-03, -4.9192e-03, 7.4727e-05],\n [ 1.2632e-03, 6.8232e-03, -7.4896e-04]],\n\n [[ 5.2314e-03, 1.4499e-02, 1.7850e-02],\n [ 1.5661e-03, -7.0366e-03, 3.3262e-03],\n [ 6.5894e-03, -9.0527e-03, -5.6415e-04]]],\n\n\n [[[-1.4401e-02, 7.5562e-04, -1.4519e-02],\n [-2.1916e-02, -5.6409e-03, 2.0301e-03],\n [-1.1346e-02, -2.3929e-03, -8.3506e-03]],\n\n [[-5.4914e-03, -3.0260e-03, -5.3406e-03],\n [-8.3956e-03, -3.2481e-03, -4.1416e-03],\n [-1.7680e-02, -8.6813e-04, -3.9965e-04]],\n\n [[-9.1588e-03, -7.9120e-03, -6.4680e-03],\n [-3.7685e-03, -6.1528e-04, 1.1661e-02],\n [-1.3700e-02, 4.0599e-04, 6.3709e-04]],\n\n ...,\n\n [[-1.1958e-02, -8.0960e-03, -6.7403e-05],\n [-6.6819e-03, 1.2399e-02, -4.3929e-04],\n [ 8.1369e-03, 2.3266e-03, 1.2799e-02]],\n\n [[ 1.5493e-02, 2.1186e-02, 1.9512e-02],\n [ 1.7342e-02, 5.7402e-03, 2.6945e-02],\n [ 1.9243e-02, 2.9370e-02, 3.7164e-02]],\n\n [[-4.3860e-03, 9.2209e-03, 8.7638e-03],\n [ 1.1110e-02, 1.5143e-02, 1.0715e-02],\n [ 1.5527e-02, -6.2796e-03, 1.5857e-02]]],\n\n\n [[[-8.9856e-03, -7.8182e-03, -8.2072e-03],\n [-4.6750e-03, -2.5308e-02, -8.1413e-03],\n [-9.8006e-03, -2.0263e-02, -1.6392e-02]],\n\n [[ 4.5261e-03, 2.5392e-02, 9.9774e-03],\n [-3.7039e-03, 2.1934e-02, 4.1014e-03],\n [-1.4464e-02, -2.3010e-04, 5.6713e-03]],\n\n [[-5.8849e-03, -1.9673e-02, -1.1095e-02],\n [-1.1203e-02, -2.2941e-02, -1.5013e-02],\n [-1.2531e-02, -3.0482e-02, -2.5673e-02]],\n\n ...,\n\n [[ 3.3822e-03, -7.5059e-03, -7.3766e-03],\n [-3.3269e-02, -2.6378e-02, -1.7773e-02],\n [-1.2832e-02, -7.9920e-03, -4.8157e-03]],\n\n [[ 1.2379e-02, 2.1643e-03, 1.0127e-02],\n [-6.5861e-03, -2.8548e-04, -5.8829e-03],\n [ 1.4114e-03, -1.2769e-02, 4.5239e-04]],\n\n [[ 1.3329e-03, 1.2004e-02, 3.1036e-03],\n [ 1.1607e-02, 4.5620e-03, 5.1076e-03],\n [ 6.2933e-03, -1.4041e-02, -7.6872e-03]]]]), 'model.layer4.0.bn2.weight': tensor([0.2273, 0.2141, 0.2201, 0.2572, 0.1998, 0.2322, 0.2307, 0.2022, 0.2145,\n 0.2140, 0.1906, 0.1756, 0.2093, 0.2108, 0.2046, 0.2222, 0.1843, 0.1893,\n 0.1530, 0.1917, 0.1671, 0.2338, 0.1798, 0.1937, 0.1722, 0.2129, 0.1947,\n 0.2201, 0.1772, 0.1732, 0.1846, 0.1716, 0.1773, 0.1579, 0.2115, 0.2054,\n 0.1735, 0.2130, 0.2063, 0.1719, 0.1662, 0.1638, 0.1668, 0.1935, 0.1885,\n 0.1736, 0.1894, 0.1866, 0.2426, 0.2089, 0.1946, 0.1813, 0.1543, 0.2188,\n 0.2081, 0.2193, 0.2183, 0.2043, 0.1907, 0.2237, 0.2147, 0.1794, 0.1945,\n 0.1999, 0.1960, 0.1656, 0.1828, 0.1568, 0.2204, 0.1896, 0.1505, 0.2267,\n 0.2024, 0.1915, 0.1849, 0.1739, 0.1733, 0.1920, 0.1686, 0.1888, 0.2106,\n 0.2050, 0.2245, 0.1931, 0.1946, 0.1860, 0.2448, 0.1861, 0.1674, 0.2026,\n 0.2331, 0.2023, 0.2219, 0.2284, 0.2973, 0.2060, 0.1804, 0.2197, 0.1884,\n 0.1657, 0.2241, 0.1881, 0.1880, 0.2363, 0.2288, 0.1958, 0.1960, 0.2051,\n 0.1831, 0.1936, 0.1898, 0.1551, 0.1960, 0.1837, 0.1572, 0.1687, 0.1828,\n 0.1982, 0.1573, 0.2030, 0.1771, 0.1880, 0.2408, 0.1856, 0.2236, 0.1505,\n 0.2023, 0.1806, 0.2350, 0.1771, 0.2013, 0.2231, 0.1806, 0.1911, 0.1686,\n 0.2117, 0.1694, 0.2080, 0.2410, 0.2296, 0.1906, 0.1785, 0.1672, 0.1769,\n 0.1818, 0.1673, 0.1545, 0.2076, 0.2103, 0.2207, 0.1691, 0.1956, 0.1981,\n 0.2264, 0.1750, 0.1894, 0.1890, 0.1672, 0.1920, 0.2127, 0.1862, 0.1948,\n 0.1824, 0.1728, 0.1893, 0.2318, 0.1789, 0.1650, 0.1859, 0.1806, 0.1879,\n 0.1934, 0.2425, 0.1839, 0.2417, 0.2055, 0.1723, 0.1732, 0.2040, 0.1745,\n 0.1739, 0.2087, 0.1844, 0.1568, 0.1835, 0.2044, 0.1865, 0.2055, 0.1647,\n 0.1561, 0.1888, 0.2117, 0.1776, 0.1677, 0.1860, 0.1938, 0.1612, 0.1802,\n 0.1973, 0.1808, 0.2085, 0.1730, 0.1609, 0.1835, 0.1945, 0.2003, 0.2014,\n 0.2185, 0.1998, 0.1957, 0.2161, 0.1906, 0.1571, 0.1684, 0.1864, 0.2009,\n 0.2346, 0.1961, 0.2139, 0.1711, 0.2111, 0.2067, 0.1980, 0.1512, 0.2143,\n 0.1843, 0.1755, 0.1790, 0.2155, 0.1964, 0.2025, 0.1867, 0.2019, 0.2315,\n 0.2228, 0.1891, 0.1820, 0.2180, 0.2090, 0.2317, 0.1973, 0.2081, 0.2323,\n 0.1881, 0.1755, 0.2103, 0.1883, 0.2041, 0.1647, 0.1794, 0.1795, 0.2024,\n 0.1722, 0.2079, 0.1881, 0.2114, 0.2299, 0.1679, 0.2086, 0.2152, 0.1992,\n 0.1848, 0.2148, 0.1873, 0.2176, 0.1717, 0.1561, 0.1841, 0.1964, 0.1849,\n 0.1669, 0.1743, 0.1675, 0.2139, 0.1838, 0.2068, 0.1826, 0.2068, 0.1969,\n 0.1906, 0.1823, 0.2218, 0.1758, 0.2008, 0.2102, 0.1717, 0.1584, 0.1757,\n 0.1941, 0.1566, 0.1846, 0.2292, 0.1887, 0.1992, 0.1952, 0.2114, 0.1927,\n 0.1774, 0.1843, 0.1870, 0.2022, 0.1887, 0.1867, 0.1631, 0.1910, 0.1785,\n 0.1900, 0.1977, 0.1934, 0.2267, 0.1979, 0.1975, 0.1938, 0.2010, 0.1623,\n 0.1887, 0.1893, 0.1599, 0.2550, 0.1826, 0.1878, 0.1619, 0.1966, 0.2012,\n 0.1807, 0.1806, 0.2176, 0.2395, 0.2215, 0.2152, 0.1827, 0.2363, 0.1969,\n 0.2071, 0.1763, 0.2031, 0.1855, 0.2419, 0.1969, 0.1876, 0.2451, 0.2211,\n 0.1879, 0.2079, 0.1829, 0.1955, 0.1703, 0.2214, 0.1693, 0.1909, 0.2167,\n 0.1836, 0.2171, 0.2120, 0.1552, 0.1999, 0.2286, 0.2004, 0.1880, 0.1579,\n 0.1953, 0.2176, 0.1634, 0.1771, 0.1680, 0.1963, 0.1931, 0.1853, 0.1903,\n 0.2061, 0.1934, 0.1886, 0.1640, 0.1704, 0.2160, 0.2073, 0.1910, 0.1862,\n 0.2013, 0.1514, 0.2163, 0.1830, 0.2065, 0.2302, 0.2156, 0.1560, 0.1964,\n 0.2011, 0.2018, 0.1898, 0.2555, 0.1873, 0.2112, 0.1992, 0.1740, 0.1757,\n 0.1732, 0.2203, 0.1856, 0.1609, 0.2229, 0.1907, 0.2189, 0.1784, 0.1698,\n 0.2029, 0.1707, 0.1735, 0.1938, 0.2246, 0.2190, 0.1930, 0.1977, 0.2228,\n 0.2153, 0.2246, 0.2055, 0.2034, 0.1713, 0.1996, 0.1609, 0.2306, 0.1913,\n 0.2018, 0.2108, 0.1713, 0.2152, 0.2257, 0.2274, 0.2024, 0.1988, 0.2040,\n 0.1831, 0.2356, 0.1803, 0.1872, 0.1901, 0.2201, 0.1788, 0.2005, 0.2156,\n 0.1936, 0.1993, 0.2588, 0.1861, 0.1967, 0.1879, 0.1861, 0.2456, 0.1864,\n 0.2083, 0.1989, 0.1772, 0.1687, 0.1605, 0.2218, 0.2105, 0.1769, 0.1670,\n 0.1842, 0.1860, 0.2034, 0.1742, 0.1877, 0.1876, 0.1714, 0.1837, 0.1971,\n 0.2223, 0.2639, 0.2389, 0.1962, 0.2057, 0.1786, 0.2297, 0.1781, 0.2181,\n 0.1898, 0.1681, 0.1855, 0.1792, 0.2250, 0.1801, 0.1874, 0.1760, 0.2235,\n 0.2090, 0.1949, 0.1956, 0.2145, 0.1952, 0.1764, 0.1660, 0.1863, 0.1668,\n 0.1652, 0.2003, 0.1955, 0.1998, 0.1663, 0.2240, 0.2210, 0.1933, 0.1821,\n 0.1930, 0.1795, 0.1807, 0.1622, 0.1934, 0.1784, 0.1866, 0.2073]), 'model.layer4.0.bn2.bias': tensor([-0.0962, -0.1407, -0.0426, -0.0972, -0.0655, -0.0501, -0.1162, -0.1348,\n -0.1010, -0.0657, -0.1268, -0.0878, -0.0654, -0.1612, -0.0237, -0.0817,\n 0.0861, -0.0710, -0.0243, -0.0798, -0.0332, -0.0801, -0.0149, -0.0423,\n -0.0636, -0.1320, -0.0558, -0.1256, -0.0581, -0.0316, -0.0435, -0.0103,\n -0.0904, -0.0089, -0.0457, -0.1251, -0.0194, -0.0538, -0.1553, -0.0509,\n -0.0738, 0.0142, -0.0054, -0.0690, -0.0962, -0.0293, -0.1332, -0.1036,\n -0.1319, -0.0963, -0.1079, -0.0503, 0.0188, -0.0603, -0.0939, -0.0609,\n -0.0629, -0.0887, -0.1235, -0.1098, -0.1377, -0.1043, -0.0337, -0.0864,\n -0.1360, -0.0472, -0.0914, -0.0584, -0.1211, -0.1270, 0.0192, -0.0892,\n -0.1413, -0.0917, -0.0843, -0.0057, -0.0189, -0.1139, -0.0554, -0.0685,\n -0.0681, -0.0308, -0.0963, -0.0821, -0.1031, -0.0310, -0.1267, -0.0704,\n 0.0004, -0.0742, -0.0719, -0.0868, -0.0970, -0.1487, 0.1682, -0.0844,\n -0.0537, -0.1181, -0.0646, -0.0558, -0.1249, -0.0622, -0.0380, -0.1460,\n -0.0750, -0.0749, -0.0776, -0.0815, -0.0839, -0.0828, -0.0444, -0.0431,\n -0.1126, -0.0627, -0.0644, -0.0331, -0.0499, -0.1498, 0.0237, -0.0658,\n -0.0358, -0.1037, -0.1208, -0.0807, -0.0816, 0.0241, -0.1163, -0.0637,\n -0.0980, -0.0302, -0.1285, -0.1016, -0.0407, -0.0122, -0.0119, -0.0981,\n -0.0724, -0.1028, -0.1237, -0.1167, -0.0278, -0.0735, -0.0659, -0.0867,\n 0.0004, 0.0165, -0.0102, -0.0339, -0.0882, -0.0763, -0.0426, -0.0506,\n -0.0927, -0.1047, -0.0783, -0.1351, -0.1087, -0.0148, -0.0493, -0.1567,\n -0.0885, -0.0353, -0.0680, -0.1002, -0.0644, -0.1321, -0.0770, -0.0127,\n -0.0676, -0.0567, -0.1054, -0.0944, -0.1367, -0.0136, -0.1259, -0.1452,\n -0.0169, -0.0271, -0.0843, -0.0776, -0.0813, -0.0977, -0.0349, -0.0056,\n -0.0340, -0.0715, -0.0450, -0.0684, -0.0288, -0.0306, -0.0227, -0.0776,\n -0.0104, -0.0362, -0.0246, -0.1010, 0.0080, -0.0931, -0.0717, -0.0626,\n -0.0897, 0.0024, -0.0244, -0.0888, -0.0697, -0.0784, -0.1039, -0.1557,\n -0.0705, -0.0684, -0.0679, -0.0986, 0.0540, -0.0381, -0.0498, -0.1065,\n -0.1760, -0.0922, -0.0874, -0.0404, -0.1186, -0.0697, -0.0465, -0.0172,\n -0.1181, -0.0716, -0.0253, -0.0533, -0.0896, -0.0373, -0.1592, -0.0715,\n -0.0471, -0.1025, -0.1035, -0.0255, -0.0857, -0.1298, -0.0928, -0.0889,\n -0.1221, -0.1297, -0.0940, -0.0846, -0.0498, -0.0934, -0.0470, -0.0580,\n -0.0338, -0.0198, -0.0265, -0.0379, 0.0456, -0.0813, -0.0684, -0.0982,\n -0.1096, -0.0441, -0.0864, -0.0872, -0.0859, -0.0476, -0.0786, -0.0895,\n -0.0778, -0.0554, -0.0151, -0.1033, -0.0399, -0.1058, -0.0210, -0.0347,\n -0.0665, -0.1544, -0.0697, -0.1021, -0.0403, -0.0898, -0.1283, -0.0635,\n -0.0742, -0.1096, -0.0403, -0.0803, -0.1271, -0.0747, -0.0231, -0.0825,\n -0.0721, -0.0426, -0.0655, -0.1190, -0.0414, -0.0910, -0.0821, -0.0887,\n -0.0789, -0.0294, -0.0210, -0.0295, -0.0835, -0.0748, -0.0817, -0.0015,\n -0.1061, -0.1059, -0.1329, -0.0930, -0.0524, -0.0337, -0.0914, -0.0745,\n -0.0969, -0.0430, -0.0288, -0.0644, -0.1000, -0.0347, -0.0637, -0.0731,\n -0.0654, -0.0215, -0.0477, -0.1026, -0.1110, -0.0803, -0.1022, -0.1006,\n -0.1082, -0.0788, -0.0657, -0.1012, 0.0121, -0.0926, -0.0304, -0.0993,\n -0.0333, -0.0852, -0.0521, -0.0880, -0.1601, -0.0788, -0.1046, -0.0682,\n -0.0955, -0.0591, -0.0256, -0.1384, 0.1279, -0.0398, -0.1095, -0.0878,\n -0.1722, -0.0688, -0.0190, -0.0981, -0.1573, -0.0836, -0.0864, 0.0070,\n -0.0260, -0.0970, -0.0614, -0.0242, 0.0037, -0.1443, -0.0483, -0.0508,\n -0.0785, -0.1016, -0.0959, -0.0915, -0.0565, -0.0155, -0.0751, -0.1146,\n -0.0013, -0.0762, -0.1413, -0.0140, -0.0739, -0.0804, -0.0362, -0.1050,\n -0.0895, 0.0450, -0.1132, -0.1187, -0.1090, -0.0192, -0.1090, -0.1110,\n -0.0764, -0.0977, -0.0126, -0.0616, -0.0834, -0.0928, -0.0116, 0.0048,\n -0.1344, -0.0715, -0.1077, -0.0065, -0.0283, -0.1250, -0.0512, -0.0224,\n -0.0695, -0.1708, -0.0963, -0.0257, -0.0744, -0.0447, -0.1157, -0.1390,\n -0.0732, -0.0538, -0.0314, -0.0633, -0.0529, -0.1873, -0.1327, -0.1057,\n -0.1135, -0.0068, -0.0927, -0.0680, -0.0968, -0.1113, -0.0930, -0.0675,\n -0.0650, -0.0865, -0.0478, -0.0297, -0.0842, -0.1190, -0.0566, -0.1155,\n -0.0450, -0.0990, -0.0796, -0.1357, -0.0813, -0.0690, -0.0473, -0.0489,\n -0.1031, -0.0223, -0.0614, -0.0803, -0.1164, -0.0334, -0.0826, -0.1307,\n -0.0557, -0.0262, -0.0208, -0.0175, -0.0658, -0.1071, -0.0465, -0.0484,\n -0.0479, -0.0604, -0.0469, -0.0734, -0.1059, -0.0899, -0.1171, -0.1054,\n -0.0945, -0.1161, -0.0555, -0.0365, -0.1528, -0.0531, -0.0482, -0.1164,\n -0.0414, -0.1885, -0.0653, -0.0876, -0.0443, -0.1193, -0.0756, -0.1168,\n -0.1265, -0.1290, -0.0871, -0.0238, 0.0007, -0.0566, -0.0323, 0.0053,\n -0.0561, -0.1071, -0.0976, -0.0628, -0.1066, -0.0719, -0.0751, -0.0283,\n -0.0987, -0.0387, -0.0495, 0.0375, -0.0476, -0.0341, -0.0151, -0.1763]), 'model.layer4.0.bn2.running_mean': tensor([-4.5494e-02, -3.5098e-03, -1.1036e-01, -1.6798e-02, -1.5204e-02,\n 9.0502e-02, 1.1177e-03, -7.8377e-02, 7.6748e-02, 7.4780e-03,\n 9.4527e-03, -1.2024e-01, -7.1467e-02, -1.5599e-01, -8.6145e-02,\n 2.6836e-02, -1.1700e-01, -2.2848e-02, -9.9761e-02, -1.5817e-02,\n -3.0885e-03, -7.0988e-02, -1.1368e-01, -6.5322e-02, -1.2709e-02,\n -3.6263e-02, -7.8852e-02, -6.5669e-02, -1.3199e-01, -1.0134e-01,\n -7.9627e-03, -1.3105e-02, -5.3780e-02, -1.8903e-02, -1.1476e-01,\n -7.2812e-02, -1.0977e-01, -8.0083e-02, -1.4799e-01, 2.7324e-02,\n -1.5773e-02, -1.3674e-01, -2.6285e-02, -6.6921e-02, -2.7103e-02,\n -7.3408e-02, -1.2792e-01, -1.1957e-01, -1.3100e-01, -1.6058e-01,\n -7.3417e-02, -4.5868e-03, 4.3246e-02, 4.0297e-02, -9.1374e-03,\n -7.5396e-02, -2.2155e-02, 6.1112e-02, -3.2139e-02, -4.7027e-02,\n -1.8922e-02, -6.3424e-02, -2.5177e-02, -7.2603e-02, -2.5647e-01,\n -1.3686e-01, 7.1049e-03, -4.1113e-02, -1.4474e-01, -1.0564e-01,\n 1.1661e-01, -8.5014e-02, 2.7311e-02, -6.9896e-02, 2.0193e-02,\n 6.7947e-02, 1.8340e-02, -1.3510e-01, -1.7472e-01, -5.8934e-03,\n -9.7540e-02, 3.5181e-03, -3.2651e-02, 6.0563e-03, 2.3383e-02,\n -8.8734e-02, -9.5417e-02, -9.4708e-02, -1.5356e-01, -3.0285e-02,\n -1.4790e-01, 7.8611e-02, -1.5704e-02, 3.1692e-02, 3.4555e-01,\n -1.8795e-01, 6.6640e-02, -1.9915e-01, -2.2680e-02, 5.1562e-02,\n -7.0092e-03, 6.1446e-02, -1.2587e-01, 3.7492e-02, -5.5892e-02,\n -5.9020e-02, -5.2540e-02, -3.1117e-02, -2.0359e-02, -1.8594e-01,\n 7.7659e-02, 6.5621e-02, 3.4891e-02, -1.8345e-03, 2.6282e-02,\n 8.3015e-02, -1.0997e-01, -1.1133e-01, -1.1628e-02, -9.0371e-03,\n -1.2192e-01, -7.7335e-02, -3.0318e-02, -7.9966e-02, 8.5793e-02,\n -7.1146e-02, -7.7951e-02, 5.9043e-02, -1.2954e-01, -1.3397e-01,\n -1.6064e-01, -1.5902e-01, -5.3990e-02, -8.4426e-02, 3.6722e-02,\n -1.1093e-01, 3.2955e-02, -3.6668e-02, -3.9071e-02, -6.5671e-02,\n -4.0911e-02, 1.1036e-02, -7.9404e-02, 3.4395e-02, -1.9812e-01,\n 6.2076e-02, -9.6137e-02, 7.4676e-03, -5.6568e-02, -1.7601e-02,\n 2.0127e-02, -9.4899e-02, -4.0219e-02, -2.4162e-01, -1.8959e-01,\n 5.7778e-02, -7.9702e-02, -8.2380e-02, -9.0777e-02, -1.8270e-01,\n -5.0477e-02, -5.8709e-03, -1.1191e-01, -1.1799e-01, -3.3777e-02,\n -1.5999e-02, 2.0048e-02, -7.9358e-02, -3.2929e-02, -3.2719e-02,\n -7.5389e-02, -1.2740e-01, -1.3499e-01, -1.6182e-01, -1.8117e-01,\n -1.6609e-01, -1.4391e-02, -1.5957e-01, -1.3388e-01, 2.8009e-02,\n -6.7336e-02, -1.3922e-01, 2.3113e-02, -1.6379e-01, -9.9128e-02,\n 4.4491e-02, -1.3628e-01, -1.7479e-01, -1.0653e-01, -8.5461e-02,\n 5.0559e-02, -1.0404e-01, 4.3944e-03, -2.0934e-01, 1.4577e-02,\n -8.4168e-02, -1.4653e-01, 2.4611e-02, -3.6691e-03, -1.5769e-01,\n -2.6588e-02, -1.0760e-01, -3.1867e-02, -3.5470e-02, -1.4396e-01,\n 2.2467e-02, -5.1402e-02, -1.3666e-01, -4.2838e-02, -4.9513e-02,\n -2.3639e-01, 1.6162e-02, 4.2922e-02, -3.2979e-03, 2.3790e-02,\n 1.1035e-02, 7.0316e-02, -4.9720e-02, -1.2282e-01, 1.8841e-03,\n -1.1014e-01, -2.3221e-02, -6.2586e-02, 5.1974e-02, -6.2369e-02,\n -1.4359e-01, -4.5191e-02, 2.9220e-02, 1.1066e-02, -1.6814e-01,\n -1.7498e-01, -8.9000e-02, -2.4602e-03, -2.3314e-02, -3.5775e-02,\n -1.0506e-01, -2.4441e-02, -1.5060e-01, -1.2550e-01, -1.4201e-02,\n -9.8971e-02, -2.0225e-02, -7.3145e-02, -9.7431e-02, 1.9247e-02,\n -6.5225e-03, -1.7457e-02, -1.1774e-01, 2.7342e-03, 9.6404e-02,\n -2.7426e-02, 2.0323e-02, -1.1192e-01, -1.6824e-02, 4.5990e-03,\n -9.9773e-02, -1.3303e-01, -1.7879e-02, 3.3567e-02, -1.5004e-01,\n -8.2079e-02, -1.2164e-02, 5.3833e-02, -9.8840e-02, -3.6402e-02,\n -1.2384e-01, -5.4256e-02, -1.8695e-01, -9.0998e-02, -8.9587e-02,\n 3.0687e-02, -9.5693e-02, -1.8596e-01, -5.2131e-03, -8.1925e-02,\n -3.0880e-02, -1.5355e-01, 2.0794e-02, -1.2040e-01, -8.3230e-02,\n -8.6700e-02, -1.1272e-01, -7.5530e-02, -2.0983e-01, -1.6991e-01,\n -5.9942e-02, -9.8729e-02, 1.7573e-02, -9.8042e-02, 3.5734e-02,\n -8.4514e-02, -1.0502e-01, 5.7974e-02, -1.2059e-01, -1.4805e-02,\n -1.9666e-01, -3.2430e-02, -1.7037e-02, 1.6607e-02, -5.0552e-02,\n -8.9392e-02, 3.0550e-02, -2.2338e-02, 7.9550e-03, -9.0846e-02,\n -1.3037e-02, -1.0196e-01, 4.1550e-02, 1.2307e-02, 8.0440e-03,\n -4.7754e-02, -1.3112e-01, -1.1982e-01, 1.5383e-02, -1.2203e-01,\n -1.6952e-01, -1.0578e-01, -2.5212e-02, -3.6029e-02, -7.0426e-02,\n 1.5983e-02, 2.2341e-02, -1.0797e-01, -2.3995e-02, -1.3987e-02,\n -9.7238e-02, -2.0149e-01, -5.0398e-02, -4.8947e-02, -3.5300e-02,\n -1.2368e-01, -7.3093e-02, -4.9208e-02, -3.2698e-02, -6.9597e-02,\n -7.7436e-03, -2.1863e-01, -5.8971e-02, -1.1487e-01, -5.3576e-02,\n -4.0173e-02, 3.0968e-02, -1.6135e-01, -1.5794e-01, -7.6603e-02,\n 2.5428e-02, -2.6889e-02, -1.3354e-01, 6.0952e-02, -7.0923e-02,\n -3.1199e-02, 1.6146e-03, -1.0270e-01, -2.4695e-01, 7.8923e-02,\n -1.4063e-01, -5.6391e-02, -3.8961e-02, -1.4726e-01, -1.2047e-01,\n -1.5173e-01, 1.4870e-02, -1.8259e-01, -1.4554e-01, -7.9175e-02,\n -1.0127e-01, -8.6108e-02, 4.8579e-02, -1.5769e-01, -1.9360e-02,\n -2.7622e-03, 2.8199e-02, -4.0283e-02, 8.6717e-03, -1.6243e-01,\n -5.9324e-02, 5.8695e-02, 1.0445e-02, -1.8505e-02, 9.2615e-02,\n -1.1441e-01, -4.7687e-02, -8.2156e-02, -9.3155e-02, -7.8361e-02,\n 6.3521e-03, -1.3477e-02, -1.2158e-01, -6.2297e-02, -1.4764e-01,\n -3.5734e-02, -1.1805e-01, -9.8226e-02, 4.3478e-02, -2.0635e-01,\n 5.4810e-02, -7.9425e-02, -7.0963e-02, 4.2186e-02, -1.0210e-01,\n -1.0066e-02, -1.1362e-01, -4.9337e-02, 5.3663e-02, -7.6428e-02,\n -1.0292e-01, -6.4188e-02, 1.2694e-02, -1.1669e-01, -1.3355e-01,\n -4.3626e-02, -9.0212e-02, 7.0458e-03, -1.2132e-01, -1.4289e-01,\n -5.9126e-03, -1.2005e-01, -7.9066e-02, 5.7554e-03, 2.9083e-02,\n -1.0314e-01, -1.0763e-01, -6.0204e-02, -1.6909e-01, -4.3530e-02,\n -4.2503e-02, -7.6748e-02, -2.1200e-01, -4.8963e-02, -1.0916e-01,\n 1.3411e-03, 2.0074e-02, 2.5333e-03, -8.4047e-02, -7.6331e-02,\n -1.1155e-01, -2.9604e-02, -1.0247e-01, 9.4411e-02, -9.9348e-02,\n -5.4027e-02, -5.9083e-03, -7.5440e-02, -9.1132e-02, -9.5339e-02,\n 6.3350e-02, -8.5424e-02, -4.5267e-02, -1.1532e-01, -9.8877e-02,\n 1.0833e-01, -9.4414e-02, -1.3545e-01, 6.6469e-02, 1.3243e-02,\n -1.3676e-01, 1.0825e-02, -1.1805e-01, 8.2583e-02, 6.5827e-02,\n -5.0193e-02, -4.2446e-02, -5.6495e-02, -1.0155e-01, -2.0772e-01,\n -4.6887e-02, 2.2645e-02, -9.8240e-02, -2.4419e-01, -1.1817e-01,\n 9.5380e-05, 6.4661e-02, -8.7557e-02, -2.4809e-02, -5.7467e-02,\n -1.1991e-01, -6.8614e-02, -1.3578e-01, 1.3500e-02, -1.0658e-01,\n -1.4678e-01, -7.6929e-02, -2.6270e-02, 7.7736e-02, -1.3086e-01,\n -1.1573e-01, -1.0476e-02, -7.5943e-02, -1.2126e-01, -1.2294e-01,\n -9.4711e-02, -1.1797e-01, -6.4388e-02, -7.6715e-02, -5.2046e-02,\n -9.4665e-02, -2.2912e-02, -1.0739e-01, -5.7332e-02, -1.5815e-03,\n -1.0010e-01, -7.9583e-02, -6.6151e-02, -1.3423e-01, -5.9937e-02,\n 4.7578e-02, 5.3457e-02, 9.4350e-02, -1.3122e-02, -9.1103e-02,\n -2.3319e-02, -2.9432e-03]), 'model.layer4.0.bn2.running_var': tensor([0.0153, 0.0148, 0.0137, 0.0147, 0.0245, 0.0283, 0.0132, 0.0115, 0.0268,\n 0.0162, 0.0129, 0.0215, 0.0253, 0.0275, 0.0188, 0.0153, 0.0419, 0.0197,\n 0.0107, 0.0128, 0.0155, 0.0209, 0.0233, 0.0157, 0.0201, 0.0201, 0.0151,\n 0.0258, 0.0204, 0.0226, 0.0505, 0.0144, 0.0183, 0.0135, 0.0199, 0.0151,\n 0.0120, 0.0165, 0.0283, 0.0181, 0.0124, 0.0244, 0.0140, 0.0205, 0.0197,\n 0.0124, 0.0192, 0.0159, 0.0204, 0.0372, 0.0145, 0.0197, 0.0146, 0.0373,\n 0.0210, 0.0210, 0.0194, 0.0341, 0.0087, 0.0256, 0.0150, 0.0194, 0.0088,\n 0.0205, 0.0500, 0.0209, 0.0118, 0.0231, 0.0192, 0.0155, 0.0169, 0.0146,\n 0.0216, 0.0199, 0.0171, 0.0230, 0.0169, 0.0193, 0.0201, 0.0124, 0.0134,\n 0.0209, 0.0144, 0.0114, 0.0166, 0.0148, 0.0250, 0.0177, 0.0234, 0.0129,\n 0.0229, 0.0203, 0.0140, 0.0154, 0.2099, 0.0210, 0.0241, 0.0318, 0.0143,\n 0.0206, 0.0127, 0.0175, 0.0278, 0.0138, 0.0147, 0.0192, 0.0168, 0.0227,\n 0.0178, 0.0202, 0.0314, 0.0182, 0.0305, 0.0172, 0.0133, 0.0426, 0.0219,\n 0.0377, 0.0152, 0.0135, 0.0164, 0.0147, 0.0207, 0.0120, 0.0226, 0.0119,\n 0.0224, 0.0491, 0.0156, 0.0283, 0.0278, 0.0189, 0.0130, 0.0175, 0.0229,\n 0.0250, 0.0181, 0.0240, 0.0126, 0.0180, 0.0168, 0.0203, 0.0196, 0.0159,\n 0.0471, 0.0304, 0.0216, 0.0205, 0.0143, 0.0164, 0.0128, 0.0139, 0.0136,\n 0.0438, 0.0381, 0.0341, 0.0174, 0.0181, 0.0253, 0.0268, 0.0104, 0.0158,\n 0.0131, 0.0195, 0.0119, 0.0178, 0.0306, 0.0194, 0.0232, 0.0123, 0.0203,\n 0.0185, 0.0171, 0.0316, 0.0271, 0.0255, 0.0217, 0.0240, 0.0252, 0.0135,\n 0.0280, 0.0202, 0.0157, 0.0203, 0.0187, 0.0145, 0.0208, 0.0348, 0.0148,\n 0.0207, 0.0214, 0.0156, 0.0222, 0.0257, 0.0179, 0.0177, 0.0178, 0.0132,\n 0.0277, 0.0225, 0.0147, 0.0232, 0.0103, 0.0169, 0.0218, 0.0303, 0.0112,\n 0.0163, 0.0158, 0.0179, 0.0364, 0.0111, 0.0258, 0.0105, 0.0184, 0.0200,\n 0.0210, 0.0224, 0.0321, 0.0160, 0.0121, 0.0104, 0.0341, 0.0248, 0.0158,\n 0.0163, 0.0139, 0.0131, 0.0147, 0.0344, 0.0208, 0.0112, 0.0169, 0.0124,\n 0.0194, 0.0324, 0.0237, 0.0172, 0.0312, 0.0128, 0.0229, 0.0135, 0.0158,\n 0.0173, 0.0234, 0.0119, 0.0179, 0.0263, 0.0182, 0.0239, 0.0132, 0.0260,\n 0.0265, 0.0341, 0.0194, 0.0222, 0.0236, 0.0129, 0.0190, 0.0175, 0.0107,\n 0.0158, 0.0283, 0.0144, 0.0145, 0.0238, 0.0241, 0.0385, 0.0119, 0.0244,\n 0.0140, 0.0193, 0.0432, 0.0199, 0.0228, 0.0147, 0.0319, 0.0142, 0.0328,\n 0.0118, 0.0128, 0.0308, 0.0138, 0.0379, 0.0256, 0.0165, 0.0174, 0.0152,\n 0.0202, 0.0120, 0.0206, 0.0153, 0.0283, 0.0137, 0.0128, 0.0261, 0.0150,\n 0.0188, 0.0256, 0.0134, 0.0174, 0.0171, 0.0196, 0.0226, 0.0132, 0.0269,\n 0.0150, 0.0186, 0.0164, 0.0188, 0.0180, 0.0170, 0.0223, 0.0170, 0.0120,\n 0.0338, 0.0146, 0.0186, 0.0220, 0.0134, 0.0130, 0.0132, 0.0126, 0.0142,\n 0.0151, 0.0140, 0.0237, 0.0162, 0.0218, 0.0260, 0.0198, 0.0205, 0.0217,\n 0.0122, 0.0162, 0.0135, 0.0335, 0.0122, 0.0147, 0.0165, 0.0121, 0.0153,\n 0.0163, 0.0142, 0.0159, 0.0221, 0.0129, 0.0208, 0.0299, 0.0173, 0.0198,\n 0.0240, 0.0109, 0.0301, 0.0234, 0.0158, 0.0156, 0.0156, 0.0176, 0.0221,\n 0.0403, 0.0312, 0.0167, 0.0334, 0.0213, 0.0120, 0.0211, 0.0240, 0.0165,\n 0.0223, 0.0292, 0.0134, 0.0184, 0.0144, 0.0292, 0.0178, 0.0206, 0.0221,\n 0.0117, 0.0151, 0.0357, 0.0317, 0.0230, 0.0258, 0.0357, 0.0228, 0.0177,\n 0.0208, 0.0223, 0.0321, 0.0209, 0.0214, 0.0180, 0.0315, 0.0518, 0.0203,\n 0.0182, 0.0184, 0.0125, 0.0230, 0.0168, 0.0132, 0.0189, 0.0151, 0.0205,\n 0.0170, 0.0217, 0.0158, 0.0140, 0.0182, 0.0123, 0.0180, 0.0222, 0.0235,\n 0.0239, 0.0165, 0.0147, 0.0127, 0.0152, 0.0154, 0.0401, 0.0169, 0.0235,\n 0.0169, 0.0124, 0.0219, 0.0184, 0.0243, 0.0214, 0.0185, 0.0279, 0.0187,\n 0.0154, 0.0155, 0.0223, 0.0182, 0.0132, 0.0149, 0.0403, 0.0127, 0.0229,\n 0.0205, 0.0134, 0.0201, 0.0199, 0.0313, 0.0132, 0.0251, 0.0290, 0.0137,\n 0.0359, 0.0146, 0.0117, 0.0254, 0.0155, 0.0277, 0.0244, 0.0116, 0.0207,\n 0.0286, 0.0117, 0.0165, 0.0200, 0.0184, 0.0374, 0.0315, 0.0195, 0.0202,\n 0.0353, 0.0262, 0.0334, 0.0264, 0.0213, 0.0181, 0.0189, 0.0206, 0.0112,\n 0.0227, 0.0257, 0.0147, 0.0267, 0.0181, 0.0155, 0.0171, 0.0251, 0.0125,\n 0.0163, 0.0245, 0.0103, 0.0169, 0.0119, 0.0239, 0.0226, 0.0161, 0.0156,\n 0.0132, 0.0139, 0.0152, 0.0138, 0.0291, 0.0161, 0.0205, 0.0228, 0.0279,\n 0.0160, 0.0179, 0.0183, 0.0284, 0.0143, 0.0181, 0.0185, 0.0252]), 'model.layer4.0.bn2.num_batches_tracked': tensor(7160), 'model.layer4.0.conv3.weight': tensor([[[[-0.0049]],\n\n [[ 0.0044]],\n\n [[-0.0107]],\n\n ...,\n\n [[-0.0065]],\n\n [[ 0.0031]],\n\n [[-0.0092]]],\n\n\n [[[-0.0010]],\n\n [[ 0.0431]],\n\n [[-0.0178]],\n\n ...,\n\n [[-0.0098]],\n\n [[-0.0313]],\n\n [[-0.0038]]],\n\n\n [[[ 0.0092]],\n\n [[-0.0253]],\n\n [[-0.0052]],\n\n ...,\n\n [[ 0.0105]],\n\n [[-0.0027]],\n\n [[-0.0180]]],\n\n\n ...,\n\n\n [[[ 0.0092]],\n\n [[-0.0156]],\n\n [[-0.0232]],\n\n ...,\n\n [[-0.0126]],\n\n [[ 0.0029]],\n\n [[ 0.0163]]],\n\n\n [[[-0.0008]],\n\n [[-0.0036]],\n\n [[-0.0158]],\n\n ...,\n\n [[ 0.0185]],\n\n [[-0.0107]],\n\n [[ 0.0032]]],\n\n\n [[[ 0.0094]],\n\n [[-0.0078]],\n\n [[ 0.0161]],\n\n ...,\n\n [[ 0.0063]],\n\n [[ 0.0095]],\n\n [[-0.0164]]]]), 'model.layer4.0.bn3.weight': tensor([0.3129, 0.4181, 0.3950, ..., 0.3272, 0.3617, 0.3135]), 'model.layer4.0.bn3.bias': tensor([-0.0601, -0.0957, -0.0747, ..., -0.0560, -0.0672, -0.0624]), 'model.layer4.0.bn3.running_mean': tensor([ 0.0189, -0.0632, -0.0224, ..., -0.0168, -0.0477, -0.0524]), 'model.layer4.0.bn3.running_var': tensor([0.0038, 0.0097, 0.0026, ..., 0.0028, 0.0038, 0.0064]), 'model.layer4.0.bn3.num_batches_tracked': tensor(7160), 'model.layer4.0.downsample.0.weight': tensor([[[[ 0.0075]],\n\n [[-0.0052]],\n\n [[ 0.0045]],\n\n ...,\n\n [[-0.0018]],\n\n [[-0.0017]],\n\n [[ 0.0011]]],\n\n\n [[[ 0.0032]],\n\n [[ 0.0075]],\n\n [[ 0.0016]],\n\n ...,\n\n [[-0.0037]],\n\n [[-0.0073]],\n\n [[-0.0053]]],\n\n\n [[[-0.0009]],\n\n [[-0.0070]],\n\n [[ 0.0018]],\n\n ...,\n\n [[-0.0146]],\n\n [[-0.0057]],\n\n [[ 0.0034]]],\n\n\n ...,\n\n\n [[[-0.0022]],\n\n [[ 0.0174]],\n\n [[ 0.0045]],\n\n ...,\n\n [[-0.0030]],\n\n [[ 0.0041]],\n\n [[-0.0189]]],\n\n\n [[[ 0.0014]],\n\n [[ 0.0032]],\n\n [[-0.0063]],\n\n ...,\n\n [[-0.0070]],\n\n [[-0.0080]],\n\n [[ 0.0012]]],\n\n\n [[[ 0.0062]],\n\n [[ 0.0030]],\n\n [[-0.0075]],\n\n ...,\n\n [[ 0.0172]],\n\n [[-0.0183]],\n\n [[ 0.0179]]]]), 'model.layer4.0.downsample.1.weight': tensor([0.2393, 0.2702, 0.2546, ..., 0.1860, 0.2623, 0.2532]), 'model.layer4.0.downsample.1.bias': tensor([-0.0601, -0.0957, -0.0747, ..., -0.0560, -0.0672, -0.0624]), 'model.layer4.0.downsample.1.running_mean': tensor([ 0.0043, 0.0121, -0.0252, ..., -0.0079, -0.0282, -0.0095]), 'model.layer4.0.downsample.1.running_var': tensor([0.0023, 0.0023, 0.0014, ..., 0.0024, 0.0020, 0.0014]), 'model.layer4.0.downsample.1.num_batches_tracked': tensor(7160), 'model.layer4.1.conv1.weight': tensor([[[[-1.2740e-02]],\n\n [[ 7.4937e-03]],\n\n [[-1.6283e-02]],\n\n ...,\n\n [[-1.4814e-02]],\n\n [[-1.6156e-02]],\n\n [[ 2.4434e-03]]],\n\n\n [[[-9.3730e-04]],\n\n [[ 3.0944e-02]],\n\n [[-1.9824e-03]],\n\n ...,\n\n [[ 1.1278e-02]],\n\n [[ 2.4050e-02]],\n\n [[-2.0723e-02]]],\n\n\n [[[-1.9629e-02]],\n\n [[-1.5041e-02]],\n\n [[-1.4131e-02]],\n\n ...,\n\n [[ 4.4919e-03]],\n\n [[ 8.1614e-03]],\n\n [[ 2.6370e-03]]],\n\n\n ...,\n\n\n [[[ 1.6123e-02]],\n\n [[-7.4214e-03]],\n\n [[-1.5916e-02]],\n\n ...,\n\n [[ 8.0543e-03]],\n\n [[ 1.4850e-03]],\n\n [[ 6.7865e-03]]],\n\n\n [[[-5.6553e-03]],\n\n [[-1.6181e-02]],\n\n [[-1.0349e-02]],\n\n ...,\n\n [[ 2.2569e-03]],\n\n [[ 5.2862e-03]],\n\n [[ 4.5152e-03]]],\n\n\n [[[-2.6533e-02]],\n\n [[-1.5368e-02]],\n\n [[ 1.8121e-02]],\n\n ...,\n\n [[ 2.8389e-03]],\n\n [[ 7.0274e-05]],\n\n [[ 1.5700e-02]]]]), 'model.layer4.1.bn1.weight': tensor([0.1814, 0.1950, 0.1744, 0.1973, 0.2030, 0.1567, 0.2241, 0.1958, 0.2167,\n 0.1685, 0.2166, 0.2051, 0.1853, 0.2025, 0.1881, 0.2022, 0.1722, 0.2161,\n 0.1728, 0.2147, 0.1987, 0.2148, 0.1730, 0.1922, 0.1981, 0.1926, 0.1943,\n 0.1820, 0.1339, 0.1758, 0.2013, 0.1798, 0.2315, 0.1886, 0.2005, 0.1610,\n 0.2002, 0.1785, 0.1849, 0.2030, 0.1299, 0.1973, 0.1951, 0.1801, 0.1864,\n 0.2027, 0.1932, 0.1982, 0.1806, 0.1655, 0.1777, 0.2399, 0.1885, 0.1533,\n 0.2388, 0.1833, 0.1915, 0.1883, 0.1749, 0.1830, 0.1823, 0.1991, 0.1875,\n 0.1807, 0.1965, 0.1976, 0.2078, 0.1611, 0.2092, 0.1862, 0.1748, 0.2114,\n 0.2426, 0.1759, 0.1880, 0.1809, 0.2081, 0.1779, 0.1927, 0.1307, 0.2217,\n 0.2341, 0.1954, 0.1679, 0.2098, 0.2013, 0.2133, 0.1843, 0.1808, 0.1908,\n 0.2253, 0.2073, 0.2038, 0.2078, 0.2376, 0.1889, 0.2069, 0.1970, 0.1669,\n 0.1684, 0.1680, 0.2068, 0.2012, 0.1437, 0.2162, 0.1908, 0.2097, 0.1882,\n 0.2616, 0.1919, 0.1859, 0.2162, 0.1870, 0.1715, 0.1891, 0.1834, 0.2219,\n 0.1946, 0.2120, 0.1843, 0.1825, 0.2055, 0.1665, 0.2062, 0.1965, 0.2120,\n 0.1858, 0.2241, 0.1854, 0.2142, 0.1833, 0.1823, 0.1699, 0.2310, 0.1665,\n 0.1658, 0.1982, 0.1751, 0.2257, 0.1674, 0.2167, 0.1923, 0.1820, 0.1788,\n 0.1579, 0.1983, 0.1707, 0.2025, 0.2017, 0.2029, 0.1840, 0.1527, 0.1639,\n 0.1797, 0.2087, 0.2084, 0.2123, 0.1945, 0.1964, 0.2055, 0.1904, 0.1680,\n 0.1647, 0.1946, 0.1848, 0.2125, 0.1635, 0.1910, 0.1971, 0.1684, 0.1950,\n 0.1670, 0.1715, 0.1737, 0.1973, 0.1748, 0.1958, 0.1733, 0.2140, 0.1662,\n 0.1926, 0.1682, 0.2111, 0.1867, 0.2161, 0.1734, 0.2016, 0.2246, 0.1961,\n 0.1801, 0.1872, 0.1988, 0.2054, 0.1885, 0.1775, 0.2200, 0.1958, 0.1846,\n 0.2049, 0.1794, 0.1877, 0.1644, 0.2099, 0.1878, 0.2320, 0.2019, 0.2172,\n 0.1973, 0.1886, 0.1689, 0.1923, 0.1903, 0.2010, 0.1963, 0.1805, 0.2139,\n 0.1516, 0.2059, 0.1824, 0.1862, 0.2003, 0.1951, 0.2295, 0.2148, 0.2000,\n 0.1769, 0.1849, 0.2062, 0.2231, 0.2085, 0.2116, 0.1690, 0.1858, 0.2193,\n 0.1657, 0.1937, 0.2127, 0.1839, 0.2912, 0.2078, 0.2133, 0.1650, 0.1563,\n 0.1937, 0.1963, 0.1874, 0.2058, 0.1829, 0.1978, 0.1783, 0.1923, 0.2342,\n 0.1629, 0.2102, 0.1946, 0.1976, 0.2172, 0.2002, 0.1944, 0.2022, 0.1923,\n 0.1663, 0.1939, 0.1827, 0.2006, 0.1647, 0.1710, 0.1909, 0.2043, 0.2024,\n 0.1849, 0.1941, 0.2321, 0.1736, 0.1888, 0.2013, 0.1718, 0.1872, 0.1818,\n 0.1613, 0.2164, 0.2096, 0.1966, 0.1491, 0.2015, 0.1923, 0.2135, 0.1758,\n 0.1729, 0.1926, 0.2082, 0.1950, 0.1933, 0.1987, 0.2025, 0.1881, 0.1842,\n 0.1763, 0.1602, 0.2376, 0.2131, 0.1932, 0.2046, 0.2127, 0.1773, 0.1990,\n 0.2149, 0.1586, 0.1938, 0.2080, 0.1572, 0.1850, 0.1965, 0.1945, 0.1919,\n 0.2066, 0.1921, 0.2051, 0.1932, 0.1948, 0.2153, 0.2151, 0.2064, 0.1935,\n 0.1977, 0.1880, 0.1876, 0.1617, 0.1868, 0.2358, 0.1879, 0.1959, 0.2016,\n 0.2182, 0.2027, 0.1953, 0.2238, 0.1685, 0.1871, 0.2225, 0.2143, 0.2197,\n 0.2046, 0.2132, 0.1830, 0.2223, 0.2099, 0.1693, 0.1762, 0.1888, 0.1948,\n 0.1899, 0.2294, 0.2178, 0.2067, 0.1787, 0.1794, 0.2122, 0.1677, 0.2224,\n 0.2113, 0.1661, 0.1879, 0.1959, 0.1978, 0.2166, 0.1683, 0.1960, 0.1794,\n 0.2007, 0.2099, 0.2171, 0.2017, 0.1896, 0.2050, 0.1889, 0.2091, 0.2030,\n 0.1951, 0.2185, 0.1738, 0.2034, 0.1966, 0.1995, 0.2025, 0.2071, 0.1489,\n 0.2204, 0.2150, 0.2152, 0.2006, 0.2085, 0.1785, 0.2170, 0.1810, 0.1700,\n 0.2122, 0.2080, 0.1824, 0.1782, 0.2007, 0.1223, 0.2043, 0.1962, 0.1815,\n 0.1927, 0.2276, 0.1884, 0.2011, 0.1894, 0.1650, 0.1815, 0.1941, 0.2052,\n 0.2049, 0.1997, 0.2448, 0.1670, 0.1935, 0.1764, 0.1985, 0.1686, 0.1680,\n 0.1793, 0.2044, 0.1685, 0.2009, 0.2054, 0.1906, 0.2175, 0.1464, 0.1533,\n 0.1908, 0.1600, 0.2323, 0.1756, 0.2186, 0.1829, 0.1770, 0.2249, 0.1686,\n 0.1968, 0.1632, 0.2010, 0.2114, 0.2315, 0.2232, 0.1759, 0.1859, 0.1943,\n 0.2012, 0.1932, 0.1772, 0.1572, 0.1883, 0.1957, 0.1932, 0.1343, 0.2105,\n 0.1963, 0.2112, 0.2042, 0.2047, 0.1824, 0.2015, 0.1745, 0.2075, 0.1569,\n 0.1873, 0.1128, 0.1851, 0.2221, 0.1646, 0.2053, 0.2211, 0.1806, 0.1765,\n 0.2034, 0.1878, 0.1797, 0.2205, 0.2098, 0.1984, 0.1983, 0.2174, 0.2174,\n 0.1929, 0.1651, 0.1442, 0.1958, 0.1919, 0.2236, 0.1431, 0.1942, 0.2232,\n 0.2030, 0.1916, 0.1981, 0.1779, 0.1829, 0.1468, 0.2164, 0.1892, 0.1994,\n 0.1961, 0.1980, 0.1667, 0.1704, 0.2516, 0.2086, 0.2426, 0.2098]), 'model.layer4.1.bn1.bias': tensor([-0.1333, -0.1092, -0.0686, -0.1484, -0.1617, -0.0161, -0.1065, -0.1231,\n -0.1701, -0.0622, -0.1967, -0.1350, -0.1419, -0.1431, -0.1271, -0.1392,\n -0.0451, -0.1373, -0.0796, -0.1806, -0.1159, -0.1472, -0.0820, -0.1098,\n -0.1440, -0.1308, -0.1370, -0.1154, 0.0938, -0.1166, -0.1539, -0.1261,\n -0.2036, -0.0528, -0.1579, -0.0243, -0.1265, -0.0898, -0.1201, -0.1005,\n 0.0522, -0.1431, -0.1389, -0.0799, -0.0879, -0.1631, -0.1637, -0.1675,\n -0.1003, -0.0768, -0.0649, -0.2257, -0.1418, -0.0476, -0.2199, -0.1589,\n -0.1154, -0.1357, -0.1108, -0.1097, -0.1064, -0.0789, -0.1224, -0.1516,\n -0.1968, -0.1544, -0.1342, 0.0007, -0.1973, -0.1742, -0.0671, -0.1837,\n -0.1932, -0.1034, -0.1111, -0.0890, -0.1369, -0.0731, -0.1629, 0.1015,\n -0.1320, -0.2040, -0.1163, -0.0674, -0.1687, -0.1453, -0.1356, -0.1464,\n -0.1291, -0.1158, -0.1682, -0.1683, -0.1661, -0.1935, -0.2052, -0.1518,\n -0.1346, -0.1497, -0.0802, -0.0906, -0.0890, -0.1773, -0.1518, -0.0143,\n -0.1640, -0.1179, -0.1356, -0.1246, -0.1638, -0.0660, -0.0599, -0.1366,\n -0.1191, -0.1013, -0.0375, -0.0710, -0.1625, -0.1282, -0.1519, -0.1540,\n -0.1165, -0.1727, -0.0690, -0.1407, -0.1245, -0.1915, -0.1428, -0.2333,\n -0.1113, -0.1765, -0.1130, -0.0411, -0.0797, -0.1751, -0.0857, -0.0469,\n -0.1035, -0.0552, -0.1385, 0.0032, -0.1633, -0.1558, -0.1004, -0.0732,\n -0.0585, -0.1823, 0.0537, -0.1940, -0.1343, -0.1767, -0.0971, -0.0078,\n -0.0591, -0.0778, -0.1419, -0.1716, -0.1652, -0.1121, -0.0928, -0.1699,\n -0.1179, -0.0956, -0.0248, -0.1119, -0.1439, -0.2059, -0.0281, -0.1542,\n -0.1782, -0.0836, -0.1013, -0.0361, -0.0783, -0.1054, -0.1228, -0.0590,\n -0.1547, -0.0127, -0.1529, -0.1190, -0.1120, -0.0774, -0.0651, -0.0665,\n -0.1400, -0.0936, -0.1542, -0.1701, -0.1417, -0.1653, -0.0852, -0.1574,\n -0.1592, -0.1252, -0.1141, -0.2164, -0.0854, -0.0796, -0.1778, -0.0615,\n -0.1403, -0.0623, -0.2118, -0.1301, -0.1679, -0.1281, -0.1810, -0.1135,\n -0.0789, -0.1077, -0.1128, -0.1153, -0.1700, -0.1533, -0.1340, -0.1592,\n -0.0532, -0.1945, -0.1432, -0.0591, -0.1699, -0.0980, -0.2026, -0.1726,\n -0.1506, -0.0776, -0.0929, -0.1544, -0.2477, -0.1652, -0.1564, -0.1048,\n -0.0496, -0.1526, -0.0848, -0.1044, -0.1466, -0.0411, -0.3193, -0.1571,\n -0.1712, -0.0578, -0.0391, -0.1406, -0.1257, -0.1540, -0.1432, -0.0844,\n -0.1518, -0.0891, -0.1111, -0.1439, 0.1348, -0.1471, -0.1576, -0.1613,\n -0.1656, -0.1427, -0.1262, -0.1344, -0.1265, -0.0287, -0.1085, -0.1388,\n -0.1026, -0.0582, -0.1224, -0.1491, -0.1876, -0.1529, -0.0849, -0.1352,\n -0.1076, -0.1203, -0.1590, -0.1655, -0.0642, -0.1213, -0.0783, -0.0370,\n -0.1467, -0.1638, -0.1924, -0.0054, -0.1399, -0.1262, -0.1280, -0.0399,\n -0.0537, -0.0927, -0.1270, -0.1457, -0.1289, -0.0931, -0.1225, -0.1378,\n -0.1582, -0.1247, 0.0264, -0.1809, -0.1643, -0.1475, -0.1295, -0.1632,\n -0.1058, -0.1857, -0.1741, -0.1073, -0.1075, -0.1555, -0.0721, -0.1364,\n -0.0655, -0.1607, -0.1121, -0.2034, -0.1659, -0.1561, -0.1172, -0.1845,\n -0.1618, -0.1799, -0.1332, -0.1678, -0.1336, -0.1212, -0.1261, -0.0551,\n -0.0549, -0.1672, -0.1669, -0.1012, -0.1773, -0.1773, -0.1565, -0.1329,\n -0.1645, -0.0619, -0.0788, -0.2362, -0.2119, -0.1652, -0.1534, -0.1165,\n -0.0878, -0.1803, -0.1695, -0.0999, -0.1061, -0.1021, -0.1214, -0.1204,\n -0.1735, -0.1183, -0.1742, -0.0577, -0.1174, -0.2010, -0.1040, -0.1981,\n -0.1419, -0.0866, -0.1538, -0.1474, -0.1310, -0.1694, -0.0697, -0.1382,\n -0.0935, -0.1596, -0.1616, -0.1132, -0.1209, -0.1630, -0.1548, -0.1240,\n -0.1436, -0.1246, -0.1055, -0.1467, -0.0759, -0.1837, -0.1362, -0.1041,\n -0.1158, -0.1533, -0.0377, -0.0240, -0.1531, -0.2134, -0.1134, -0.1330,\n -0.0857, -0.2001, -0.0722, -0.0803, -0.1567, -0.1499, -0.0898, -0.0652,\n -0.1456, 0.0439, -0.1227, -0.1003, -0.1329, -0.1296, -0.2301, -0.1229,\n -0.1107, -0.1216, -0.0615, -0.0677, -0.1334, -0.1109, -0.1728, -0.1571,\n -0.2268, -0.0770, -0.1683, -0.1211, -0.1569, -0.0659, -0.0888, -0.0933,\n -0.1293, -0.0770, -0.1601, -0.1823, -0.1761, -0.0903, 0.0234, -0.0573,\n -0.1254, -0.0488, -0.2219, -0.0891, -0.1876, -0.1403, -0.0989, -0.2068,\n -0.0168, -0.1404, -0.0909, -0.1790, -0.1728, -0.2051, -0.1556, -0.1271,\n -0.0908, -0.1417, -0.1669, -0.1459, -0.0899, -0.0460, -0.0738, -0.1477,\n -0.1416, 0.0067, -0.1620, -0.1517, -0.1651, -0.1236, -0.1562, -0.1279,\n -0.1490, -0.1118, -0.0918, -0.0399, -0.1092, 0.1163, -0.1233, -0.1922,\n -0.1106, -0.1773, -0.2082, -0.1330, -0.0657, -0.1851, -0.1333, -0.0631,\n -0.1670, -0.1601, -0.1287, -0.1401, -0.1770, -0.1878, -0.0782, -0.0759,\n -0.0364, -0.1590, -0.1036, -0.1850, -0.0500, -0.0898, -0.1653, -0.1319,\n -0.1012, -0.1437, -0.0633, -0.1920, -0.0210, -0.0808, -0.1076, -0.1121,\n -0.1349, -0.1521, -0.1076, -0.1207, -0.2767, -0.1386, -0.1997, -0.1715]), 'model.layer4.1.bn1.running_mean': tensor([-0.0896, 0.2545, -0.9735, -0.5404, -0.1219, 0.1721, -0.9636, -0.4505,\n -0.4037, -0.1237, -0.2960, -0.1706, -0.2069, -0.6973, -0.4099, -0.3956,\n -0.6068, -0.2352, -0.4827, -0.3920, -0.7351, -0.4990, -0.1718, -0.0293,\n -0.2215, -0.4154, 0.1890, -0.6560, 0.0733, -0.5423, -0.2353, -0.3181,\n -0.7305, -0.9289, -0.2945, -0.0297, -0.8165, -0.5351, -0.6161, 0.0561,\n -0.2644, -0.1043, -0.2911, -0.5115, -0.0835, -0.1860, -0.6630, -0.0606,\n -0.1568, -0.0255, -0.1514, -0.5652, -0.7566, 0.0694, -0.1037, -0.8474,\n 0.1617, 0.0411, -0.0018, -0.2143, -0.2794, -0.7277, 0.0554, -0.7295,\n 0.2426, -0.8190, -0.2475, -0.7036, -0.3579, -0.6405, -0.6009, 0.0147,\n -0.1958, -0.6832, -0.4245, -0.2869, -0.1955, -0.0316, -0.8395, -0.8246,\n -0.3885, -0.5597, -0.3013, -0.2441, -0.3928, -0.2215, -0.5407, -0.5044,\n -0.4639, -0.4545, -0.6440, -0.7353, -0.6872, -0.0369, -0.1108, -0.5415,\n -0.9916, -0.0757, -0.1232, -0.3023, -0.2336, -0.6333, -0.8444, -0.0128,\n -0.0980, -0.2198, -0.0878, -0.7190, -1.2036, -0.6253, -0.6760, -0.3701,\n -0.3457, -0.2081, -0.1395, -0.1441, 0.1248, 0.0998, -0.8767, -0.5155,\n -0.0131, -0.8331, 0.0861, -0.5842, -0.5491, -0.5186, -0.2896, -0.4552,\n -0.0442, -0.4013, -0.3099, -0.5567, -0.3287, -0.3095, -0.2770, -0.1490,\n -0.3557, -0.5782, -0.5787, -0.2021, -0.4966, -0.4216, -0.6295, -0.5413,\n -0.7503, -0.5654, -0.2003, -0.6854, -0.1436, 0.0049, -0.3703, -0.8433,\n 0.0311, 0.0738, -0.3665, -0.6305, -0.1424, 0.0176, -0.7682, -0.8041,\n -0.2930, -0.6458, -0.1522, -0.3953, -0.2838, -0.3038, -0.5709, -0.6373,\n 0.2142, -0.8383, -0.7974, -0.0142, -0.1678, -0.4629, -0.1915, -0.4969,\n -0.7993, -0.5643, -0.3401, -0.2123, -0.1815, -0.0885, -0.5136, -0.4321,\n -0.7601, -0.1985, -0.2437, -0.3605, -0.3782, -0.6054, -0.5837, -0.6076,\n -0.1999, 0.1072, -0.4015, -0.4864, -0.3618, -0.3887, -0.2649, -0.9616,\n -0.9768, 0.0804, -0.5993, -0.3334, -1.0576, 0.2524, -0.2188, -0.7681,\n -0.1840, -0.7648, -0.7477, -0.3838, -0.5212, -0.5291, -0.1745, -0.6113,\n -0.6433, -0.6119, -0.6070, -0.3725, -0.1569, -0.7514, -0.6100, -0.9501,\n -0.0061, -0.6984, -0.8749, -0.7342, 0.2513, -0.5014, -0.5554, 0.1235,\n -0.3250, 0.2451, 0.0518, -0.0106, -0.7689, -0.4332, -0.3696, -0.5916,\n -0.0578, -0.6198, -0.2398, -0.2494, -0.2786, -0.6307, -0.7135, -0.1256,\n -0.4795, -0.1306, -0.5177, -0.0778, -1.1195, 0.2095, -0.5781, -0.7277,\n -0.5453, -0.2205, -0.1789, -0.4170, -0.1303, 0.1746, -0.7996, -0.3277,\n -0.0932, -0.4702, -0.3762, -0.4122, -0.3216, 0.2005, -0.2160, -0.7434,\n -0.1459, 0.1888, -0.3505, 0.0026, -0.5198, -0.0856, -0.0674, -0.3284,\n -0.7661, -0.6474, -0.4704, -0.4361, -0.3559, -0.1696, -0.0479, -0.8507,\n -0.3428, -0.1192, 0.0408, -0.3533, -0.1942, -0.0605, -0.7968, -0.4466,\n -0.4997, -0.5380, -0.2086, -0.6305, 0.0557, -0.4463, -0.4607, -0.9877,\n -0.3824, -0.1028, -0.1834, -0.6718, 0.0336, 0.1844, -0.3772, -0.1225,\n -0.4345, -0.4910, -0.8319, -0.4215, -0.4633, -0.0899, 0.0183, -0.5764,\n -0.5377, -0.5594, -0.1488, -0.5930, -0.3439, 0.0449, -0.4957, 0.3275,\n -0.5532, -0.1964, -0.5267, -0.1603, 0.5578, -0.0097, -0.5869, -0.4688,\n -0.6538, -0.3628, -0.5571, -0.5184, -0.5356, -0.6178, -0.7991, -0.6007,\n -0.2330, -0.4521, -0.3617, -0.6489, -0.4005, -0.2811, -0.6492, -0.1793,\n 0.0223, -0.5268, 0.2889, -0.1318, -0.2684, -0.4466, -0.2879, -0.0779,\n -0.5665, 0.0806, -0.0675, -0.5157, -0.6688, -0.4261, -0.1626, -0.7846,\n -0.4978, -0.6282, -0.3285, -0.7556, -0.8807, -0.6462, -0.2783, -0.8773,\n -0.2960, -0.8699, -0.7831, -0.4412, -0.1959, -0.7434, -0.5341, -0.4139,\n -0.1730, -0.3967, -0.5550, 1.1504, -0.4717, -0.8879, -0.0626, -0.2747,\n -0.7508, -0.0841, 0.1545, -0.3256, -0.3994, -0.6468, -0.3838, -0.4697,\n -0.6780, -0.4675, -0.8545, -0.0480, -0.5068, -0.5288, -0.3296, -0.1603,\n -0.6373, -0.6551, -0.2854, -0.5961, 0.0665, -0.3004, -0.4691, -0.4546,\n -0.8998, -0.3259, -0.1546, -0.0570, -0.2786, -0.3778, -0.1462, -0.0260,\n -0.3767, -0.2078, -0.5123, -0.0673, 0.3438, -0.6391, -0.1386, -0.4357,\n -0.5944, -0.4487, -0.8333, -0.4315, -0.0803, -0.2207, -0.3136, -0.5710,\n -0.2365, -0.5991, -0.1451, -0.4300, -0.5550, -0.3170, 0.0767, -0.6625,\n -0.3487, -0.6801, -0.4415, -0.1021, -0.8506, -0.3090, -0.2575, -0.2251,\n -0.6930, -0.3346, -0.0418, -0.4783, -0.0705, -0.8748, -0.6803, -0.6060,\n -0.5396, -0.8795, -0.7355, -0.0714, -0.1989, -0.2000, -0.2000, -0.3075,\n -0.2350, -0.6166, -0.5534, -0.0205, -0.6975, -0.3303, -0.1274, 0.0941,\n 0.2169, 0.1126, -0.4742, -0.3515, -0.8789, -0.2748, -0.7664, -0.4936,\n -0.6926, -0.7548, -0.1987, -0.1401, -0.7311, -0.1737, -0.7827, -0.3519,\n -0.6124, -0.6504, -0.1290, -0.1733, -0.8438, -0.9081, -0.4607, -0.4501,\n -0.7335, -0.4903, -0.5778, -0.6506, -0.7297, -0.3516, 0.0772, -0.0511]), 'model.layer4.1.bn1.running_var': tensor([0.3025, 0.4853, 0.8385, 0.4152, 0.2847, 0.6007, 0.9709, 0.4660, 0.4302,\n 0.3954, 0.9153, 0.4276, 0.2427, 0.3295, 0.3363, 0.7021, 0.4094, 0.5710,\n 0.9263, 0.5142, 0.4751, 0.3273, 0.4079, 0.6310, 0.4090, 0.4148, 0.3986,\n 0.5412, 0.7790, 0.6826, 0.4913, 0.5497, 0.8866, 1.3269, 0.4561, 0.3279,\n 0.8308, 0.5834, 0.8758, 0.4934, 0.5891, 0.5849, 0.4555, 0.4248, 0.6434,\n 0.3809, 0.4465, 0.2950, 0.5211, 0.3372, 0.5170, 0.3763, 0.6458, 0.8230,\n 0.5145, 0.4231, 0.6132, 0.8206, 0.4349, 0.4671, 0.5570, 1.0915, 0.3668,\n 0.8596, 0.8368, 0.8333, 0.3236, 2.1768, 0.2158, 0.3996, 1.0411, 0.3690,\n 0.4450, 0.5803, 0.3792, 0.4361, 0.3494, 0.8070, 0.4533, 2.4564, 0.4998,\n 0.5918, 0.2195, 0.7255, 0.9040, 0.3184, 0.4827, 0.3325, 0.4105, 0.4057,\n 1.0442, 0.3330, 0.5167, 0.2849, 0.1860, 0.4309, 0.5239, 0.3709, 0.6594,\n 0.4579, 0.4145, 0.7217, 0.8134, 0.3441, 0.4977, 0.2813, 0.3367, 0.5380,\n 0.6526, 1.3596, 1.1448, 0.5263, 0.8725, 0.3288, 0.7060, 0.4856, 0.8719,\n 0.7046, 0.8155, 0.3287, 0.6225, 0.5532, 0.4092, 0.7872, 0.2352, 0.8896,\n 0.3306, 0.4075, 0.5915, 0.5961, 0.4421, 1.5167, 0.5500, 0.4701, 0.4293,\n 0.2054, 0.5001, 0.2889, 0.3470, 0.7790, 0.6779, 0.7115, 0.5280, 0.5716,\n 0.5579, 0.4633, 0.8981, 0.5725, 0.6368, 0.2752, 0.3036, 1.5371, 0.5466,\n 0.5370, 0.3967, 0.7240, 0.6003, 0.4762, 1.3217, 0.5393, 0.5342, 0.7394,\n 0.9140, 0.5295, 0.5794, 0.4787, 1.6292, 0.6075, 0.5521, 1.0158, 1.2211,\n 0.3486, 0.5712, 0.2153, 0.4098, 0.4061, 0.8372, 1.4452, 0.3027, 0.4375,\n 0.4958, 0.2502, 1.3176, 0.5493, 0.5788, 0.3031, 0.4076, 0.4200, 0.3504,\n 0.6316, 0.5406, 0.5118, 0.6023, 0.5403, 0.4301, 0.2772, 0.2987, 0.4647,\n 0.5408, 0.9122, 1.6487, 0.5623, 0.3651, 0.3577, 1.4161, 0.4240, 0.2701,\n 1.3561, 0.7779, 0.4541, 1.0952, 0.8948, 0.3939, 0.4364, 0.2370, 0.7781,\n 0.3715, 0.3236, 0.7493, 0.5280, 0.2635, 0.8846, 0.5357, 1.1078, 0.3432,\n 0.6673, 0.9245, 0.4026, 0.5611, 0.3192, 0.9848, 0.5285, 0.3599, 0.7847,\n 0.5723, 0.4831, 0.4547, 0.8259, 0.5480, 1.1402, 0.3531, 0.7270, 0.2680,\n 0.4977, 0.3080, 0.4674, 0.3039, 0.1706, 0.7746, 0.4117, 0.3999, 0.5864,\n 3.4031, 0.4346, 0.6486, 0.4551, 0.3491, 0.3939, 0.3748, 0.4484, 0.5522,\n 0.8044, 0.4395, 0.2813, 0.5689, 0.3145, 0.3713, 0.2930, 0.2780, 0.7847,\n 0.5191, 0.6421, 0.3356, 0.3219, 0.2820, 0.3955, 0.5335, 0.4278, 0.4574,\n 0.3234, 0.3951, 0.7138, 0.5835, 0.4254, 0.4344, 0.7584, 0.2055, 0.9165,\n 0.4528, 0.6166, 0.4102, 0.2185, 0.4633, 0.2553, 1.1491, 0.3370, 0.7689,\n 0.6984, 0.3566, 0.2367, 0.6695, 0.6214, 0.5680, 0.6533, 0.7644, 0.6836,\n 0.3686, 0.8400, 0.6181, 0.5793, 0.5098, 0.7195, 0.5559, 0.4018, 0.5264,\n 0.2466, 0.4945, 0.3010, 0.3506, 0.6918, 0.4726, 0.6318, 0.6641, 0.6478,\n 0.5489, 0.6803, 0.5686, 0.6525, 0.7955, 0.4947, 0.5401, 0.4483, 0.8707,\n 0.5278, 0.4262, 0.8857, 0.3605, 0.3342, 0.3504, 0.4996, 0.5239, 0.7460,\n 0.3805, 0.4662, 0.3796, 0.2408, 0.3290, 1.0945, 0.7165, 0.4893, 0.7539,\n 0.5033, 0.3011, 0.3626, 1.0688, 0.4260, 0.3157, 0.5070, 0.2259, 0.8154,\n 0.3988, 0.5116, 0.6775, 0.4099, 0.3131, 0.3396, 0.4313, 0.3629, 0.5268,\n 0.6058, 0.3011, 0.3750, 0.9430, 0.6937, 0.5351, 0.8549, 0.3290, 1.1574,\n 1.2078, 0.5551, 0.3669, 0.4899, 1.1228, 0.4845, 0.2523, 0.2936, 0.7208,\n 1.2261, 0.4503, 0.4719, 0.6247, 0.5463, 0.6141, 0.2143, 0.5889, 0.5152,\n 0.2632, 0.7770, 0.2905, 0.7570, 1.1505, 1.4258, 0.6827, 0.3869, 0.8848,\n 0.6890, 0.3328, 0.5699, 0.6119, 0.3822, 0.3969, 0.3688, 0.5600, 0.8442,\n 0.4727, 0.3937, 0.3951, 0.2693, 0.5630, 0.4663, 0.3332, 0.2238, 0.5462,\n 0.4321, 0.2682, 0.4616, 0.3815, 0.2740, 1.1032, 0.5894, 0.9186, 0.3746,\n 0.4437, 0.4219, 0.3213, 0.8743, 0.2315, 0.4302, 0.4605, 0.6260, 0.4469,\n 0.8324, 0.1845, 0.4615, 0.3801, 0.5231, 0.4667, 0.4130, 0.4609, 0.8443,\n 0.9848, 0.2801, 0.7741, 0.2200, 0.7331, 0.4979, 0.5462, 0.4254, 0.6730,\n 0.3809, 0.8123, 0.3904, 0.6393, 0.3341, 0.7845, 0.6585, 1.4386, 0.7008,\n 0.6794, 0.4771, 0.2298, 0.3789, 0.4849, 0.4167, 0.7061, 0.4156, 0.4456,\n 0.3704, 0.8955, 0.7009, 0.5269, 0.2121, 0.2816, 0.5099, 0.2590, 0.3271,\n 1.1722, 0.3549, 0.8006, 0.5245, 0.5011, 0.7200, 0.6163, 0.6358, 0.6269,\n 0.3381, 0.3662, 0.3503, 0.3837, 0.7000, 1.4092, 0.7386, 0.4183, 0.4203,\n 1.3545, 0.2109, 0.3473, 0.3195, 0.5565, 0.6169, 0.4939, 0.5090]), 'model.layer4.1.bn1.num_batches_tracked': tensor(7160), 'model.layer4.1.conv2.weight': tensor([[[[ 1.9628e-03, -8.4222e-04, 1.5083e-03],\n [-1.2539e-02, -1.3855e-02, -5.3860e-03],\n [ 4.6341e-03, 1.5689e-03, -1.9104e-02]],\n\n [[ 4.6381e-03, -6.1042e-03, 2.3362e-03],\n [-1.9381e-02, -2.9795e-03, 2.7487e-02],\n [-4.6173e-03, 2.1600e-03, 5.8630e-03]],\n\n [[ 3.4193e-02, -2.6210e-04, 1.1629e-02],\n [ 2.3546e-02, -1.6292e-02, -1.3967e-02],\n [ 2.0225e-02, -7.9843e-03, -2.4696e-03]],\n\n ...,\n\n [[-5.4516e-04, -3.5009e-03, -9.0307e-03],\n [-1.4830e-02, 8.7379e-03, 2.6435e-03],\n [ 3.5039e-03, 1.8318e-02, -5.7737e-04]],\n\n [[-2.4436e-02, -1.5531e-03, 4.7318e-03],\n [-2.2804e-02, -6.7348e-03, 8.6773e-03],\n [-1.3834e-02, -1.5934e-03, -2.6715e-03]],\n\n [[-4.0921e-04, 4.7723e-03, 1.0467e-02],\n [ 1.4751e-02, 1.2079e-02, 1.1237e-02],\n [-1.4567e-03, 2.8511e-02, 1.7868e-02]]],\n\n\n [[[ 5.3616e-03, -2.4268e-03, -3.2431e-03],\n [ 1.1451e-02, 1.2101e-03, 3.8723e-03],\n [ 7.1887e-03, 8.6954e-03, 3.2351e-03]],\n\n [[-5.7159e-03, -4.8946e-03, -8.6715e-03],\n [-2.0544e-02, -7.8370e-03, -1.5247e-02],\n [-7.8713e-03, -2.0163e-03, -1.8852e-02]],\n\n [[ 1.1697e-02, 8.8283e-03, 1.6509e-02],\n [ 1.3980e-02, 7.1405e-03, 1.5109e-02],\n [ 1.5173e-02, 4.7808e-03, 1.2081e-02]],\n\n ...,\n\n [[-6.2681e-03, -3.0476e-03, 2.0858e-03],\n [ 2.5701e-03, 3.8797e-03, 1.1202e-02],\n [-1.9302e-03, 3.5195e-03, -2.4248e-04]],\n\n [[-9.7869e-03, -1.3748e-02, 1.2516e-03],\n [ 3.5519e-03, -1.8973e-02, 9.6382e-04],\n [-1.1337e-02, -1.4824e-02, -4.8686e-03]],\n\n [[-7.2560e-03, -3.6065e-03, -3.3028e-03],\n [ 1.8409e-02, 1.6671e-02, 1.1694e-02],\n [ 1.3778e-02, 1.3338e-02, 4.4669e-03]]],\n\n\n [[[-3.9285e-03, -1.5666e-02, -9.0209e-03],\n [-5.4489e-03, -1.6615e-02, -2.6943e-02],\n [-1.7620e-02, -1.9218e-02, -1.8514e-02]],\n\n [[-4.5106e-03, 6.5579e-03, 5.0591e-03],\n [-5.7095e-03, -1.1077e-03, 9.8761e-03],\n [-1.1854e-03, 8.7858e-04, 4.0445e-03]],\n\n [[-1.2229e-02, -1.4904e-02, -1.0886e-02],\n [-1.1351e-02, -3.6091e-02, -2.3979e-02],\n [-7.0895e-03, -2.7977e-02, -7.7430e-03]],\n\n ...,\n\n [[ 3.2240e-03, 2.9989e-04, -1.1620e-03],\n [ 1.1339e-02, 6.4976e-03, 7.5899e-04],\n [ 4.1461e-03, 1.7898e-02, 6.7564e-03]],\n\n [[-1.6180e-02, -2.3253e-02, -9.2805e-03],\n [-3.6333e-03, -2.0210e-03, 1.5562e-02],\n [-3.7729e-03, 7.1437e-03, 7.7068e-03]],\n\n [[ 1.4915e-03, 3.2583e-03, -1.1709e-03],\n [ 6.8125e-03, 1.5125e-02, 1.0786e-03],\n [-5.8975e-03, -7.3113e-03, -1.4589e-02]]],\n\n\n ...,\n\n\n [[[ 1.0680e-02, 1.4973e-02, 1.4521e-02],\n [ 5.6501e-03, 1.9482e-02, 1.1537e-02],\n [-4.0120e-03, 1.7745e-03, 6.6537e-03]],\n\n [[-3.0122e-03, -8.8626e-04, -1.4865e-03],\n [ 1.4245e-03, 2.4362e-03, 1.3142e-02],\n [-9.3529e-03, -2.8946e-03, 3.9135e-03]],\n\n [[ 3.7848e-03, 3.2157e-03, 2.8941e-03],\n [-9.9436e-03, 9.8158e-04, -7.9702e-03],\n [-5.0497e-03, -2.4284e-03, -7.3349e-03]],\n\n ...,\n\n [[-2.0322e-02, -2.9388e-02, -3.6300e-02],\n [-2.3264e-02, -2.2721e-02, -3.1545e-02],\n [-2.3037e-02, -2.4347e-02, -2.4568e-02]],\n\n [[-2.1225e-02, -1.2392e-02, -2.3306e-02],\n [ 2.2700e-03, 1.2100e-02, -5.6215e-03],\n [-1.4436e-02, -1.5730e-02, -1.5980e-02]],\n\n [[-1.5773e-03, -7.4264e-03, 2.8296e-03],\n [-5.2907e-03, -4.0542e-03, 1.4398e-03],\n [-8.0293e-05, -1.0263e-02, -5.0020e-03]]],\n\n\n [[[ 6.6638e-03, 4.1643e-03, -1.4486e-04],\n [ 9.9131e-03, 6.5204e-03, 2.6971e-03],\n [-5.4672e-03, -4.1378e-04, 3.3591e-04]],\n\n [[ 4.2678e-03, 7.6403e-03, 1.0234e-02],\n [-6.1716e-03, -1.4156e-03, -6.9032e-03],\n [-4.7833e-03, -8.3633e-03, -6.3128e-03]],\n\n [[ 6.7385e-03, -1.2662e-03, 9.0645e-03],\n [ 2.7960e-02, 5.5544e-03, 3.1091e-02],\n [ 2.8625e-02, 1.4001e-02, 2.5238e-02]],\n\n ...,\n\n [[ 4.6986e-03, 1.6832e-02, 4.1796e-03],\n [ 3.7032e-03, -2.4746e-03, -8.5439e-03],\n [-1.5308e-04, 6.2816e-03, 6.0415e-04]],\n\n [[ 6.5840e-03, -2.2446e-04, 3.6011e-03],\n [ 7.5549e-03, 1.2389e-02, 6.9652e-03],\n [ 1.5234e-02, 2.3532e-02, 2.6323e-02]],\n\n [[-8.6893e-03, -1.4541e-03, -7.1697e-03],\n [-4.2198e-04, -5.5165e-03, -1.5439e-03],\n [-1.3471e-02, -6.0914e-04, 1.8243e-03]]],\n\n\n [[[-9.3906e-03, -2.7355e-02, -2.2498e-02],\n [-2.4807e-02, -1.7257e-02, -2.6546e-02],\n [-3.0291e-02, -2.7507e-02, -3.3331e-02]],\n\n [[-4.5957e-03, -9.2216e-03, -9.2543e-03],\n [-1.8739e-04, -1.5537e-03, -9.0663e-03],\n [ 5.2438e-03, 5.3227e-03, 4.0768e-03]],\n\n [[-2.8806e-02, -1.1788e-02, -2.4405e-02],\n [-2.2791e-02, 5.3881e-03, -2.2677e-02],\n [-2.9314e-02, -2.0864e-02, -2.9246e-02]],\n\n ...,\n\n [[ 1.3416e-02, 1.9806e-02, 1.9446e-02],\n [ 2.1906e-02, 1.3482e-02, 2.2927e-02],\n [ 7.2961e-03, 2.1321e-02, 2.4639e-02]],\n\n [[-2.2232e-03, 4.5769e-04, 6.4585e-03],\n [ 7.7751e-03, -1.0960e-02, 2.1752e-03],\n [ 9.0937e-03, 4.0271e-03, 1.5087e-02]],\n\n [[-7.2763e-03, -5.6345e-03, -7.8618e-03],\n [-1.9359e-03, 3.9393e-03, 1.0420e-03],\n [ 2.2364e-03, 9.7197e-03, -7.4971e-03]]]]), 'model.layer4.1.bn2.weight': tensor([0.1922, 0.2297, 0.1869, 0.2211, 0.2355, 0.2289, 0.1803, 0.2064, 0.1996,\n 0.1971, 0.2177, 0.2160, 0.1959, 0.2106, 0.2043, 0.1993, 0.2210, 0.2307,\n 0.1937, 0.1967, 0.1833, 0.2030, 0.2059, 0.2011, 0.2143, 0.1965, 0.2088,\n 0.1986, 0.2232, 0.2114, 0.2042, 0.2185, 0.2133, 0.1745, 0.1965, 0.1574,\n 0.1981, 0.1983, 0.2008, 0.2185, 0.2265, 0.1965, 0.2136, 0.1947, 0.2134,\n 0.1803, 0.2179, 0.2154, 0.2245, 0.2268, 0.2240, 0.1923, 0.1806, 0.1963,\n 0.2034, 0.1983, 0.2027, 0.2387, 0.1906, 0.2618, 0.2104, 0.2171, 0.2022,\n 0.1996, 0.1639, 0.2269, 0.2243, 0.1977, 0.2055, 0.2039, 0.2104, 0.1973,\n 0.1998, 0.2157, 0.1838, 0.2190, 0.1922, 0.1929, 0.1946, 0.1952, 0.2485,\n 0.2165, 0.2034, 0.2115, 0.2067, 0.1951, 0.2147, 0.1935, 0.2045, 0.2045,\n 0.2105, 0.2364, 0.2258, 0.2023, 0.2184, 0.1932, 0.2084, 0.1937, 0.2187,\n 0.2056, 0.2101, 0.2128, 0.2051, 0.2150, 0.1850, 0.1812, 0.2162, 0.2028,\n 0.2277, 0.1890, 0.2390, 0.2044, 0.2555, 0.2132, 0.2344, 0.2033, 0.2353,\n 0.2134, 0.2146, 0.1902, 0.2198, 0.2103, 0.2111, 0.1920, 0.2277, 0.1739,\n 0.2011, 0.1856, 0.2010, 0.2195, 0.1927, 0.2251, 0.2367, 0.2073, 0.1801,\n 0.2932, 0.1946, 0.1994, 0.1805, 0.2391, 0.1914, 0.2417, 0.2084, 0.2263,\n 0.2225, 0.1894, 0.2201, 0.2197, 0.2027, 0.2018, 0.2189, 0.1759, 0.2240,\n 0.2038, 0.2076, 0.2315, 0.2316, 0.2091, 0.2046, 0.2086, 0.1934, 0.2663,\n 0.1936, 0.2452, 0.2347, 0.2124, 0.2102, 0.2580, 0.2064, 0.2186, 0.2105,\n 0.1944, 0.2168, 0.2046, 0.2173, 0.2433, 0.2135, 0.2150, 0.2289, 0.1897,\n 0.1982, 0.2082, 0.2066, 0.2275, 0.1954, 0.1985, 0.2059, 0.2064, 0.2264,\n 0.2237, 0.2334, 0.1859, 0.2156, 0.1956, 0.2030, 0.1964, 0.2211, 0.2125,\n 0.2219, 0.2080, 0.2202, 0.1898, 0.1838, 0.1970, 0.2253, 0.2158, 0.1891,\n 0.2068, 0.2220, 0.2268, 0.2106, 0.2104, 0.1782, 0.1944, 0.2206, 0.1911,\n 0.2026, 0.2260, 0.2177, 0.2308, 0.2078, 0.1791, 0.2042, 0.2054, 0.2264,\n 0.1911, 0.2071, 0.2205, 0.2117, 0.2116, 0.2494, 0.2121, 0.1807, 0.2008,\n 0.2328, 0.2039, 0.2067, 0.1973, 0.2159, 0.2368, 0.2058, 0.1983, 0.1784,\n 0.2456, 0.1970, 0.1865, 0.2151, 0.2012, 0.2224, 0.2180, 0.2024, 0.2097,\n 0.1936, 0.1987, 0.1816, 0.2388, 0.1940, 0.2071, 0.2053, 0.2259, 0.1939,\n 0.2082, 0.1843, 0.2089, 0.1894, 0.1999, 0.1781, 0.2137, 0.2214, 0.2178,\n 0.2473, 0.1944, 0.2024, 0.2304, 0.2340, 0.1933, 0.2129, 0.1673, 0.2061,\n 0.1723, 0.2293, 0.2311, 0.1834, 0.2056, 0.2109, 0.1990, 0.2253, 0.2173,\n 0.2002, 0.2204, 0.2223, 0.2615, 0.2151, 0.1912, 0.2138, 0.2781, 0.2173,\n 0.1816, 0.2037, 0.2103, 0.1911, 0.2021, 0.1717, 0.2178, 0.1841, 0.2201,\n 0.2130, 0.1812, 0.2172, 0.2076, 0.1944, 0.2143, 0.1938, 0.2011, 0.1977,\n 0.1621, 0.2020, 0.2075, 0.2027, 0.2111, 0.2243, 0.2351, 0.2242, 0.2183,\n 0.2179, 0.2017, 0.2478, 0.2372, 0.2054, 0.1653, 0.2320, 0.2153, 0.2247,\n 0.2229, 0.1916, 0.1922, 0.2094, 0.2035, 0.2082, 0.1873, 0.2324, 0.2462,\n 0.2235, 0.2107, 0.1995, 0.1968, 0.2226, 0.1994, 0.2205, 0.2262, 0.2056,\n 0.1984, 0.2409, 0.2351, 0.1895, 0.2029, 0.2101, 0.2484, 0.2206, 0.2207,\n 0.2656, 0.2292, 0.2014, 0.1952, 0.2259, 0.2071, 0.1979, 0.2339, 0.2341,\n 0.2189, 0.2064, 0.2383, 0.2173, 0.2316, 0.1684, 0.2052, 0.2021, 0.2559,\n 0.2183, 0.2122, 0.2168, 0.2072, 0.2049, 0.1812, 0.2071, 0.2363, 0.2160,\n 0.2060, 0.1974, 0.2360, 0.1780, 0.2234, 0.2280, 0.2183, 0.1882, 0.2172,\n 0.2076, 0.2133, 0.3097, 0.2050, 0.1904, 0.2287, 0.2397, 0.2360, 0.2207,\n 0.1889, 0.1824, 0.1965, 0.2133, 0.2154, 0.2283, 0.2159, 0.2199, 0.2068,\n 0.1935, 0.2070, 0.1989, 0.2447, 0.2322, 0.2031, 0.2139, 0.1869, 0.2150,\n 0.2087, 0.1867, 0.2324, 0.2164, 0.2323, 0.2166, 0.2128, 0.1919, 0.2228,\n 0.2069, 0.2131, 0.2153, 0.2061, 0.1699, 0.1734, 0.2095, 0.2028, 0.2292,\n 0.2197, 0.2209, 0.1829, 0.2409, 0.2312, 0.1689, 0.1981, 0.1797, 0.2078,\n 0.2029, 0.2113, 0.2041, 0.2134, 0.2014, 0.2025, 0.2423, 0.2019, 0.2146,\n 0.2073, 0.2370, 0.1695, 0.2281, 0.2424, 0.1972, 0.2329, 0.2051, 0.1891,\n 0.1980, 0.2153, 0.1915, 0.2011, 0.2170, 0.1832, 0.2072, 0.1965, 0.2352,\n 0.2189, 0.1844, 0.1953, 0.1983, 0.2016, 0.2097, 0.1980, 0.1805, 0.2051,\n 0.1968, 0.2109, 0.2287, 0.2106, 0.1962, 0.1773, 0.2370, 0.2233, 0.2122,\n 0.2200, 0.2266, 0.2164, 0.2267, 0.2195, 0.2212, 0.2087, 0.1972, 0.2139,\n 0.1714, 0.2351, 0.2521, 0.1735, 0.2110, 0.1650, 0.1832, 0.1915]), 'model.layer4.1.bn2.bias': tensor([-0.1425, -0.1370, -0.0823, -0.1454, -0.1844, -0.1655, -0.0582, -0.0846,\n -0.1042, -0.1002, -0.1354, -0.1753, -0.1562, -0.1260, -0.1192, -0.1231,\n -0.1586, -0.1355, -0.1355, -0.1082, -0.1142, -0.1332, -0.0792, -0.1285,\n -0.1605, -0.1173, -0.0380, -0.0987, -0.1383, -0.1406, -0.0996, -0.1022,\n -0.1777, -0.0466, -0.1772, -0.0845, -0.1213, -0.1009, -0.1000, -0.1640,\n -0.1599, -0.0651, -0.0974, -0.0839, -0.1068, -0.0774, -0.0850, -0.1346,\n -0.0930, -0.1523, -0.1183, -0.0578, -0.0345, -0.1522, -0.1443, -0.1223,\n -0.1080, -0.1651, -0.1215, -0.2713, -0.1226, -0.1462, -0.1711, -0.0974,\n 0.0055, -0.1517, -0.1375, -0.1709, -0.1068, -0.0646, -0.1374, -0.0986,\n -0.1408, -0.1494, -0.0587, -0.2210, -0.0921, -0.0377, -0.1264, -0.1070,\n -0.1809, -0.0938, -0.1553, -0.0992, -0.0368, -0.1024, -0.1350, -0.1154,\n -0.1289, -0.1397, -0.1224, -0.1750, -0.1451, -0.0894, -0.1506, -0.1068,\n -0.1355, -0.0959, -0.1827, -0.1637, -0.0772, -0.0693, -0.0710, -0.0779,\n -0.0671, -0.0024, -0.1077, -0.1501, -0.1915, -0.0815, -0.1175, -0.1089,\n -0.1137, -0.0838, -0.1622, -0.0553, -0.1549, -0.1096, -0.1191, -0.0959,\n -0.2158, -0.0995, -0.1288, -0.0576, -0.1486, -0.0714, -0.1590, -0.0376,\n -0.1425, -0.1648, -0.0919, -0.1419, -0.1688, -0.0540, -0.1114, -0.3229,\n -0.0938, -0.0997, -0.0700, -0.1499, -0.1166, -0.1980, -0.0988, -0.1955,\n -0.1942, -0.0897, -0.1105, -0.0804, -0.1475, -0.0542, -0.1907, -0.1110,\n -0.1611, -0.1196, -0.0891, -0.2061, -0.1808, -0.0837, -0.1021, -0.1658,\n -0.0574, -0.2693, -0.0741, -0.2179, -0.1704, -0.0778, -0.1052, -0.1940,\n -0.0802, -0.1286, -0.1377, -0.0600, -0.1487, -0.0702, -0.0752, -0.1416,\n -0.1472, -0.1017, -0.1765, -0.0674, -0.0763, -0.0727, -0.1362, -0.1490,\n -0.1231, -0.0884, -0.1001, -0.1176, -0.1256, -0.1071, -0.2138, -0.0521,\n -0.1015, -0.1319, -0.1472, -0.0951, -0.0897, -0.1622, -0.1506, -0.1685,\n -0.0948, -0.1220, -0.0863, -0.1011, -0.1779, -0.1710, -0.0802, -0.1153,\n -0.1154, -0.1862, -0.1834, -0.1392, -0.1002, -0.1212, -0.1252, -0.1165,\n -0.0851, -0.0847, -0.0966, -0.1409, -0.1031, -0.0579, -0.1058, -0.1611,\n -0.1567, -0.0991, -0.0494, -0.1364, -0.1796, -0.1615, -0.1361, -0.1631,\n -0.0850, -0.0346, -0.1281, -0.1309, -0.0750, -0.0792, -0.1052, -0.1896,\n -0.1200, -0.0856, -0.1297, -0.1838, -0.0718, -0.1033, -0.1383, -0.0756,\n -0.1516, -0.1518, -0.0674, -0.1477, -0.1141, -0.0859, 0.0032, -0.1633,\n -0.0955, -0.1497, -0.0935, -0.1167, -0.1106, -0.0872, -0.0778, -0.0884,\n -0.0761, -0.1038, -0.0318, -0.1144, -0.1547, -0.1147, -0.1747, 0.0142,\n -0.1208, -0.1297, -0.1836, -0.1696, -0.1597, -0.0602, -0.1045, -0.0305,\n -0.1747, -0.1611, -0.1186, -0.1342, -0.1571, -0.1450, -0.1564, -0.1313,\n -0.0550, -0.1262, -0.1576, -0.2716, -0.1712, -0.1101, -0.1457, -0.2188,\n -0.1257, -0.0812, -0.1164, -0.1449, -0.1285, -0.1426, -0.0451, -0.0718,\n -0.0833, -0.1162, -0.0715, -0.0519, -0.1303, -0.1440, -0.1071, -0.1454,\n -0.0940, -0.0954, -0.1024, 0.0776, -0.1626, -0.1562, -0.1615, -0.1201,\n -0.1043, -0.2027, -0.1417, -0.0701, -0.0964, -0.0958, -0.2027, -0.1610,\n -0.1443, -0.0494, -0.1124, -0.1549, -0.1150, -0.1320, -0.0802, -0.0663,\n -0.0917, -0.1174, -0.1458, -0.0337, -0.1157, -0.0575, -0.0947, -0.1152,\n -0.0588, -0.0947, -0.1570, -0.1042, -0.1238, -0.1381, -0.1389, -0.1402,\n -0.1659, -0.1250, -0.0702, -0.1172, -0.1491, -0.1396, -0.1202, -0.0895,\n -0.1774, -0.1473, -0.0945, -0.1448, -0.1196, -0.1706, -0.0640, -0.1660,\n -0.1923, -0.1242, -0.1006, -0.1185, -0.2054, -0.1470, -0.0884, -0.1517,\n -0.0505, -0.1454, -0.1676, -0.1063, -0.1738, -0.1872, -0.1201, -0.0881,\n -0.1181, -0.1354, -0.1339, -0.0895, -0.0764, -0.1638, -0.0349, -0.1558,\n -0.1543, -0.1337, -0.0979, -0.1696, -0.1499, -0.1336, -0.3462, -0.1140,\n -0.0647, -0.1622, -0.0956, -0.1689, -0.1230, -0.1345, -0.0539, -0.0281,\n -0.1350, -0.1733, -0.1187, -0.0835, -0.1290, -0.1468, -0.1121, -0.1173,\n -0.1246, -0.1255, -0.1427, -0.1138, -0.1714, -0.0572, -0.1546, -0.1105,\n -0.0712, -0.1316, -0.1360, -0.1549, -0.1059, -0.1040, -0.0631, -0.1091,\n -0.1013, -0.1233, -0.1303, -0.1391, -0.0428, -0.0510, -0.0602, -0.1142,\n -0.1963, -0.1480, -0.1069, -0.1286, -0.1763, -0.1823, -0.0473, -0.0337,\n -0.1035, -0.1052, -0.0721, -0.0786, -0.1211, -0.1523, -0.1178, -0.1354,\n -0.1564, -0.1895, -0.1363, -0.1505, -0.1744, -0.0388, -0.1091, -0.1524,\n -0.0636, -0.1250, -0.1153, -0.0647, -0.1118, -0.1781, -0.1238, -0.1262,\n -0.1207, -0.0729, -0.0999, -0.1005, -0.1142, -0.2089, -0.1133, -0.0922,\n -0.1289, -0.1568, -0.1143, -0.1458, -0.1362, -0.0764, -0.0894, -0.1633,\n -0.1184, -0.1379, -0.1172, -0.0083, -0.1732, -0.1129, -0.1104, -0.0883,\n -0.1422, -0.1811, -0.1326, -0.1342, -0.1436, -0.1012, -0.1318, -0.1350,\n -0.0902, -0.1579, -0.1749, -0.0125, -0.1010, -0.0144, -0.0827, -0.0672]), 'model.layer4.1.bn2.running_mean': tensor([-2.0501e-01, -8.5038e-02, -2.0138e-01, -2.3983e-01, -5.3060e-02,\n -1.6815e-01, -1.3090e-01, -1.5372e-01, -1.7416e-01, -1.3019e-01,\n -1.1000e-01, -1.2829e-01, -1.8358e-01, -2.0779e-01, -4.4757e-02,\n -1.4470e-01, 1.8142e-02, -2.1030e-01, -1.1914e-01, -4.2256e-02,\n -1.5198e-01, -1.1527e-01, -1.8122e-01, -5.4737e-02, -1.1098e-01,\n -1.8334e-01, -1.9758e-01, -7.9292e-02, -1.6415e-01, -1.8361e-01,\n -2.8570e-01, -1.9542e-01, -9.2860e-02, -1.7500e-01, -6.7286e-02,\n -8.5589e-02, -1.2541e-01, -7.9773e-02, -1.0404e-01, -1.7403e-01,\n -4.5196e-02, -1.4430e-01, -2.4138e-01, -2.1558e-01, -1.2800e-01,\n -1.2811e-01, -9.3412e-02, -1.2881e-01, -1.5870e-01, -1.6788e-01,\n -2.1787e-01, -1.6465e-01, 2.9339e-01, 8.6726e-02, -1.0576e-01,\n -9.3948e-02, -1.7155e-02, -9.0268e-02, -3.5280e-02, -1.4707e-01,\n -9.8546e-03, -1.0533e-01, -9.4832e-02, 1.2267e-01, -1.4519e-01,\n -4.3128e-02, -4.9314e-02, -9.9452e-02, -1.3751e-01, -1.4716e-01,\n -1.1826e-01, -1.8959e-01, -9.0925e-02, -6.9320e-02, -7.8717e-02,\n -4.4545e-02, -1.2549e-01, -2.0426e-01, -1.9394e-01, -7.2556e-02,\n -1.5731e-01, -9.9558e-02, -5.4279e-02, -1.0350e-01, -2.0384e-02,\n -5.9372e-02, -3.5032e-02, -6.4488e-02, -1.2529e-01, -1.8166e-01,\n -2.3088e-01, -1.3829e-01, -2.2885e-01, -8.7677e-02, -1.4746e-02,\n -1.3586e-01, -1.5552e-02, -1.6880e-01, -8.7259e-02, -9.7220e-02,\n -2.3380e-02, -2.2303e-01, -1.1225e-01, -1.6071e-01, -1.5330e-01,\n -2.1072e-01, -9.1050e-02, -8.6360e-02, -8.5150e-02, -1.5508e-01,\n -1.7101e-01, -1.5770e-01, -2.4232e-01, -5.8490e-02, -1.0499e-01,\n -1.0214e-01, -2.0678e-01, -1.5678e-01, -1.3556e-01, -2.5936e-02,\n -7.2932e-02, -1.3979e-01, -8.5321e-02, -4.9722e-02, -1.3010e-01,\n -9.1691e-02, -1.0323e-01, -1.8495e-01, -7.7956e-02, -9.6004e-02,\n -1.1812e-01, -1.5330e-01, -1.0781e-01, -2.0973e-01, 6.7527e-02,\n -2.5295e-01, -1.2629e-01, -1.0618e-01, -1.5419e-01, -2.0852e-01,\n 4.1391e-02, -9.2466e-02, -7.4221e-02, -6.3705e-02, -1.0326e-01,\n -1.5798e-01, -2.8862e-01, -1.4556e-01, -1.0391e-01, -1.9354e-01,\n -1.1416e-01, -3.2372e-01, -2.0041e-01, -1.9721e-01, -2.1053e-01,\n -7.0908e-02, -7.5029e-02, -1.3740e-01, -1.6199e-01, -4.6163e-02,\n -1.2663e-01, -1.5621e-01, -5.0405e-02, 5.5394e-02, -2.0417e-01,\n -1.2047e-01, -1.1794e-01, -1.5226e-01, -1.3365e-01, -1.5628e-01,\n -2.2416e-01, -1.7406e-01, -1.4083e-01, -9.6047e-02, -1.5783e-01,\n -1.2721e-01, -1.9940e-01, -1.3425e-01, -1.0026e-01, -1.1193e-01,\n -1.9898e-02, -1.9362e-01, 3.2149e-04, -2.0403e-01, -8.1846e-02,\n -1.1840e-01, -1.1213e-01, -1.4213e-01, -1.6899e-01, -2.0267e-01,\n -2.4743e-01, -1.2279e-01, -1.3964e-01, -1.1213e-01, 1.2068e-01,\n -1.1284e-01, -4.4110e-02, -1.1475e-01, -1.8636e-01, -1.8583e-01,\n -1.6894e-01, -9.8062e-02, -6.8598e-02, -1.9623e-01, -2.2470e-01,\n -5.9905e-02, -7.9618e-03, -1.2635e-01, -6.8829e-02, -2.2054e-01,\n -1.5514e-01, -1.0166e-01, -3.4310e-01, -7.7241e-02, -1.9339e-01,\n -1.2547e-01, -1.1312e-01, -1.1343e-01, -1.3998e-01, -1.5205e-01,\n -1.7637e-01, -7.7073e-02, -2.3935e-02, -2.5705e-02, -1.3071e-01,\n 1.4212e-02, -7.9492e-02, -1.7444e-01, -2.6316e-03, -5.6287e-02,\n -1.2002e-01, -9.0150e-02, -1.6247e-01, -1.5821e-01, -1.2380e-01,\n -1.4938e-01, -1.8217e-01, -1.6684e-01, -1.2877e-01, -1.3431e-01,\n -1.0050e-01, -1.8052e-01, -2.1286e-01, -1.4807e-01, -1.5636e-01,\n -1.1070e-01, -6.3079e-02, -7.8545e-02, -1.2213e-01, -1.2845e-01,\n -1.4097e-01, -1.2236e-01, -1.7091e-01, -2.8393e-01, -1.6663e-01,\n -7.5195e-02, -9.5691e-02, -1.0217e-01, -1.7512e-01, -1.5781e-01,\n -3.2546e-02, -1.6199e-01, -1.6609e-01, -3.3082e-02, -1.6732e-01,\n -1.4391e-01, -9.2429e-02, -9.6069e-02, -3.7649e-02, -1.0388e-01,\n -1.0742e-01, -4.2966e-02, -1.5270e-01, -9.7966e-02, -1.8818e-01,\n -1.5547e-01, -1.3201e-01, -1.4401e-01, -1.4147e-01, -7.3524e-02,\n -2.2262e-01, -7.3705e-02, -1.7971e-01, -1.5254e-01, -1.2391e-01,\n -1.4668e-01, -1.1149e-01, -1.7791e-02, -8.6162e-02, -1.4446e-01,\n -4.2905e-02, -8.6898e-02, -1.5463e-01, -4.3801e-02, 8.8580e-02,\n -3.1424e-01, -1.0296e-01, 2.3097e-02, -8.1574e-02, -1.1265e-01,\n -1.7539e-01, -3.1424e-02, -1.2133e-01, -2.0850e-01, -1.8055e-01,\n -5.9024e-02, -1.5658e-01, -1.3780e-01, -1.3654e-01, -6.8124e-02,\n -8.3184e-02, -2.0797e-01, -5.4602e-02, -1.2459e-01, -1.3360e-01,\n -9.8761e-03, -1.9338e-01, -6.7111e-02, -1.3794e-01, -1.7461e-01,\n -2.1449e-01, -1.4036e-01, -1.9764e-01, -2.3005e-01, -2.5510e-01,\n -1.0462e-01, -9.0828e-02, -9.3120e-02, -1.8950e-01, -1.5440e-01,\n -1.4962e-01, -6.6446e-02, -1.4911e-01, -1.3648e-01, -2.1199e-01,\n -1.1646e-01, -7.8000e-02, -5.6291e-02, -1.3122e-01, -1.4393e-01,\n -1.8622e-01, -2.7173e-01, -2.3402e-01, -1.0568e-01, -1.7543e-01,\n -1.0845e-01, -1.7358e-01, -6.1552e-02, -9.6486e-02, -1.9093e-01,\n -1.6391e-01, -7.7516e-02, -5.0050e-02, -1.9254e-01, -1.4493e-01,\n -1.5272e-01, -1.1010e-01, -1.7875e-01, -1.1378e-01, -2.1713e-01,\n -1.8114e-01, -1.4639e-01, -8.3611e-02, -1.9269e-01, -2.0339e-01,\n -5.5946e-02, -1.6133e-01, -1.1092e-01, -2.6033e-02, -1.4460e-02,\n -1.6979e-01, -2.7165e-01, -4.5725e-02, -1.1478e-01, -1.3745e-01,\n 2.9454e-02, -6.2997e-02, -1.3150e-01, -1.0725e-01, -1.0724e-01,\n -1.5252e-01, -9.4428e-02, -2.2697e-01, 4.6927e-02, -8.6486e-02,\n -2.3073e-01, -1.5727e-01, -1.0583e-01, -1.2428e-01, -2.3649e-01,\n -1.4627e-01, -1.4879e-01, -2.0244e-01, -1.7040e-01, -1.3331e-01,\n -2.5396e-01, -9.2458e-02, -1.4234e-01, -3.8723e-01, -1.9582e-01,\n -1.2257e-01, -1.9146e-01, -2.4135e-01, -1.1217e-01, -2.4723e-01,\n -9.4742e-02, -1.8524e-01, -1.6330e-01, -3.0748e-02, -2.4247e-01,\n -1.4453e-01, -1.5308e-01, -1.5167e-01, -4.4290e-02, -5.9810e-02,\n -1.0479e-01, -6.2734e-02, -1.9629e-01, -1.3733e-01, -6.0156e-03,\n -1.4126e-01, -1.3371e-01, -6.6595e-02, -1.0006e-01, -6.3786e-02,\n -1.7125e-01, -2.0110e-01, -2.3312e-01, -1.8036e-01, -1.1349e-01,\n -2.7262e-02, -2.0933e-01, -1.4335e-01, -1.4306e-01, -3.5907e-02,\n -9.2723e-03, -8.5694e-02, -1.0224e-01, -1.8486e-01, -1.3155e-01,\n -1.1747e-01, -2.0069e-01, -1.8036e-01, -8.5680e-02, -1.6026e-01,\n -9.3243e-02, 1.2677e-02, -2.2742e-01, -1.1545e-01, -1.2178e-01,\n -1.3369e-01, -1.5580e-01, -1.5784e-01, -1.7327e-01, -1.1787e-01,\n -1.0018e-01, -2.2839e-01, -2.2062e-01, -2.1390e-01, -7.4086e-02,\n -1.6686e-01, -1.2676e-01, -1.3170e-01, -2.2716e-01, -1.2798e-01,\n -7.1499e-02, -2.5718e-01, -2.5524e-02, -1.0353e-01, 4.1220e-01,\n -1.8028e-01, -5.6395e-02, -6.1464e-02, -1.7931e-01, -1.3512e-01,\n -2.1342e-02, -8.4536e-02, -1.5158e-01, -8.7365e-02, 2.5122e-02,\n -1.2539e-01, -8.5629e-02, -9.6696e-02, -1.9786e-02, -2.0584e-01,\n -9.5139e-02, 3.1641e-02, -1.7088e-01, -8.5102e-02, -5.5087e-02,\n -6.3201e-02, -1.3891e-01, -1.4078e-01, -1.7381e-01, 2.4440e-03,\n -1.8636e-01, -7.5071e-02, -5.0673e-02, -1.8529e-01, -1.1910e-01,\n -5.5007e-02, -2.1552e-01, -1.6377e-01, -1.4877e-01, -4.8918e-02,\n 8.6385e-02, -1.3303e-01, -1.3100e-01, -3.7216e-02, -8.7302e-02,\n -1.0444e-01, -7.5085e-02]), 'model.layer4.1.bn2.running_var': tensor([0.0465, 0.0725, 0.0788, 0.0672, 0.0542, 0.0646, 0.0376, 0.0422, 0.0403,\n 0.0317, 0.0344, 0.0544, 0.0334, 0.0567, 0.0299, 0.0298, 0.0464, 0.0371,\n 0.0442, 0.0352, 0.0355, 0.0286, 0.0376, 0.0415, 0.0380, 0.0381, 0.0886,\n 0.0455, 0.0642, 0.0284, 0.0459, 0.1134, 0.0245, 0.0374, 0.0237, 0.0328,\n 0.0410, 0.0450, 0.0624, 0.0369, 0.0472, 0.0595, 0.0441, 0.0674, 0.1034,\n 0.0324, 0.1496, 0.0314, 0.1003, 0.0402, 0.1085, 0.0503, 0.0497, 0.0407,\n 0.0237, 0.0416, 0.0423, 0.0710, 0.0349, 0.0338, 0.0230, 0.0281, 0.0225,\n 0.0462, 0.0980, 0.0492, 0.0241, 0.0391, 0.0304, 0.0412, 0.0315, 0.0285,\n 0.0258, 0.0261, 0.0312, 0.0362, 0.0500, 0.0354, 0.0391, 0.0347, 0.0616,\n 0.0383, 0.0314, 0.0665, 0.0326, 0.0379, 0.0413, 0.0277, 0.0296, 0.0427,\n 0.0494, 0.0273, 0.0437, 0.0292, 0.0493, 0.0446, 0.0237, 0.0573, 0.0405,\n 0.0431, 0.0388, 0.0383, 0.0945, 0.0979, 0.0826, 0.0424, 0.0626, 0.0368,\n 0.0395, 0.0735, 0.0589, 0.0551, 0.0300, 0.0407, 0.0264, 0.0394, 0.0473,\n 0.0524, 0.0266, 0.0628, 0.0539, 0.0226, 0.0399, 0.0565, 0.0585, 0.0256,\n 0.0177, 0.0541, 0.0230, 0.0195, 0.0344, 0.0375, 0.0344, 0.0756, 0.0547,\n 0.0786, 0.0490, 0.0678, 0.0441, 0.0492, 0.0261, 0.0221, 0.0360, 0.0557,\n 0.0312, 0.0548, 0.0362, 0.0285, 0.0221, 0.0433, 0.0239, 0.0736, 0.0514,\n 0.0430, 0.0600, 0.0400, 0.0306, 0.0450, 0.0318, 0.0287, 0.0949, 0.0267,\n 0.0255, 0.0472, 0.0791, 0.0196, 0.0272, 0.0708, 0.0286, 0.0852, 0.0803,\n 0.0416, 0.0578, 0.0760, 0.0355, 0.0242, 0.0397, 0.0381, 0.0302, 0.0277,\n 0.0430, 0.0513, 0.0242, 0.0626, 0.0255, 0.0328, 0.0230, 0.0317, 0.0346,\n 0.0473, 0.0409, 0.0702, 0.0512, 0.0368, 0.0422, 0.0287, 0.0308, 0.0272,\n 0.0744, 0.0501, 0.0488, 0.0365, 0.0333, 0.0883, 0.0747, 0.0371, 0.0528,\n 0.0723, 0.0320, 0.0674, 0.0540, 0.0342, 0.0306, 0.0271, 0.0694, 0.0277,\n 0.0584, 0.0671, 0.0832, 0.0364, 0.0331, 0.0614, 0.0427, 0.0460, 0.0761,\n 0.0375, 0.0376, 0.0488, 0.0401, 0.0294, 0.0603, 0.0273, 0.0366, 0.0647,\n 0.0500, 0.0285, 0.0737, 0.0951, 0.0602, 0.0276, 0.0489, 0.0374, 0.0436,\n 0.0544, 0.0555, 0.0218, 0.0303, 0.0434, 0.0187, 0.0450, 0.0382, 0.0362,\n 0.0344, 0.0384, 0.1091, 0.0243, 0.0545, 0.0263, 0.0277, 0.0314, 0.0456,\n 0.0997, 0.1053, 0.0371, 0.0467, 0.0503, 0.0334, 0.0876, 0.0536, 0.0659,\n 0.0405, 0.0403, 0.0337, 0.0441, 0.0667, 0.0471, 0.0348, 0.0394, 0.0641,\n 0.0513, 0.0402, 0.0211, 0.0317, 0.0628, 0.0605, 0.0371, 0.0394, 0.0269,\n 0.0408, 0.0175, 0.0431, 0.0664, 0.0431, 0.0327, 0.0324, 0.0497, 0.0879,\n 0.0325, 0.0367, 0.0526, 0.0292, 0.0387, 0.0374, 0.0991, 0.0753, 0.0577,\n 0.0702, 0.0796, 0.0341, 0.0486, 0.0214, 0.0343, 0.0698, 0.0449, 0.0328,\n 0.0646, 0.0396, 0.0438, 0.0498, 0.0351, 0.0418, 0.0389, 0.0554, 0.1183,\n 0.0460, 0.0293, 0.0506, 0.0420, 0.0323, 0.0576, 0.0221, 0.0163, 0.0264,\n 0.0979, 0.0435, 0.0271, 0.0326, 0.0304, 0.0501, 0.0378, 0.0765, 0.0319,\n 0.1171, 0.0916, 0.0333, 0.0271, 0.0326, 0.0482, 0.0382, 0.0647, 0.0560,\n 0.0231, 0.0388, 0.0264, 0.1091, 0.0485, 0.0228, 0.0211, 0.0395, 0.0459,\n 0.1016, 0.0550, 0.0365, 0.0515, 0.0568, 0.0313, 0.0294, 0.0335, 0.0171,\n 0.0565, 0.0402, 0.0445, 0.0390, 0.0240, 0.0625, 0.0205, 0.0573, 0.0349,\n 0.0387, 0.0239, 0.0340, 0.0263, 0.0520, 0.0317, 0.0261, 0.0565, 0.0884,\n 0.0399, 0.1297, 0.0617, 0.0330, 0.0422, 0.0565, 0.0438, 0.0243, 0.0348,\n 0.0272, 0.0382, 0.0559, 0.0756, 0.0593, 0.0249, 0.0444, 0.0279, 0.0359,\n 0.0232, 0.0821, 0.0620, 0.0260, 0.0321, 0.0765, 0.1029, 0.0613, 0.0464,\n 0.0334, 0.0353, 0.0539, 0.0653, 0.0258, 0.0303, 0.0424, 0.0466, 0.0224,\n 0.0275, 0.0223, 0.0386, 0.0649, 0.0625, 0.0631, 0.0471, 0.0207, 0.0552,\n 0.0227, 0.0371, 0.0245, 0.0249, 0.0364, 0.0520, 0.0294, 0.0493, 0.0265,\n 0.0479, 0.0546, 0.0330, 0.0290, 0.0238, 0.0305, 0.0287, 0.0445, 0.0776,\n 0.0675, 0.0822, 0.0500, 0.0309, 0.0385, 0.0225, 0.0401, 0.0395, 0.0722,\n 0.0215, 0.0297, 0.0962, 0.0612, 0.0467, 0.0504, 0.0206, 0.0535, 0.0461,\n 0.0453, 0.0672, 0.0289, 0.0283, 0.0351, 0.0533, 0.0391, 0.0383, 0.0291,\n 0.0354, 0.0517, 0.0232, 0.0244, 0.0476, 0.0294, 0.0343, 0.0534, 0.0427,\n 0.0567, 0.0306, 0.0557, 0.0350, 0.0343, 0.1081, 0.0331, 0.0403, 0.0411,\n 0.0671, 0.0249, 0.0335, 0.0500, 0.0371, 0.0427, 0.0527, 0.0297, 0.0587,\n 0.0652, 0.0535, 0.0287, 0.0260, 0.0205, 0.0394, 0.0333, 0.0420]), 'model.layer4.1.bn2.num_batches_tracked': tensor(7160), 'model.layer4.1.conv3.weight': tensor([[[[-0.0011]],\n\n [[-0.0028]],\n\n [[ 0.0071]],\n\n ...,\n\n [[-0.0144]],\n\n [[ 0.0049]],\n\n [[-0.0039]]],\n\n\n [[[ 0.0117]],\n\n [[-0.0496]],\n\n [[ 0.0260]],\n\n ...,\n\n [[-0.0192]],\n\n [[-0.0155]],\n\n [[ 0.0158]]],\n\n\n [[[ 0.0062]],\n\n [[-0.0128]],\n\n [[-0.0289]],\n\n ...,\n\n [[ 0.0052]],\n\n [[-0.0039]],\n\n [[-0.0014]]],\n\n\n ...,\n\n\n [[[ 0.0127]],\n\n [[-0.0206]],\n\n [[ 0.0108]],\n\n ...,\n\n [[-0.0120]],\n\n [[ 0.0329]],\n\n [[-0.0004]]],\n\n\n [[[-0.0127]],\n\n [[ 0.0236]],\n\n [[ 0.0093]],\n\n ...,\n\n [[ 0.0004]],\n\n [[ 0.0108]],\n\n [[ 0.0037]]],\n\n\n [[[ 0.0155]],\n\n [[-0.0034]],\n\n [[-0.0206]],\n\n ...,\n\n [[-0.0033]],\n\n [[-0.0016]],\n\n [[ 0.0031]]]]), 'model.layer4.1.bn3.weight': tensor([0.2957, 0.4990, 0.3179, ..., 0.2609, 0.3131, 0.2520]), 'model.layer4.1.bn3.bias': tensor([-0.0828, -0.0771, -0.0877, ..., -0.0637, -0.0950, -0.0778]), 'model.layer4.1.bn3.running_mean': tensor([ 0.0279, -0.0206, 0.0072, ..., -0.0082, 0.0048, -0.0343]), 'model.layer4.1.bn3.running_var': tensor([0.0030, 0.0047, 0.0045, ..., 0.0077, 0.0068, 0.0019]), 'model.layer4.1.bn3.num_batches_tracked': tensor(7160), 'model.layer4.2.conv1.weight': tensor([[[[ 0.0137]],\n\n [[ 0.0140]],\n\n [[ 0.0014]],\n\n ...,\n\n [[ 0.0265]],\n\n [[ 0.0190]],\n\n [[ 0.0097]]],\n\n\n [[[-0.0429]],\n\n [[ 0.0096]],\n\n [[-0.0186]],\n\n ...,\n\n [[-0.0314]],\n\n [[-0.0106]],\n\n [[ 0.0059]]],\n\n\n [[[-0.0041]],\n\n [[-0.0082]],\n\n [[-0.0183]],\n\n ...,\n\n [[ 0.0073]],\n\n [[-0.0055]],\n\n [[-0.0004]]],\n\n\n ...,\n\n\n [[[-0.0063]],\n\n [[ 0.0214]],\n\n [[-0.0170]],\n\n ...,\n\n [[ 0.0146]],\n\n [[ 0.0248]],\n\n [[ 0.0215]]],\n\n\n [[[-0.0191]],\n\n [[-0.0065]],\n\n [[-0.0068]],\n\n ...,\n\n [[ 0.0021]],\n\n [[ 0.0044]],\n\n [[ 0.0440]]],\n\n\n [[[ 0.0007]],\n\n [[ 0.0043]],\n\n [[-0.0330]],\n\n ...,\n\n [[-0.0296]],\n\n [[-0.0219]],\n\n [[ 0.0152]]]]), 'model.layer4.2.bn1.weight': tensor([0.2155, 0.1938, 0.2196, 0.2147, 0.2024, 0.2193, 0.2234, 0.2196, 0.1888,\n 0.1860, 0.1889, 0.1945, 0.2405, 0.2370, 0.2210, 0.2311, 0.2322, 0.2015,\n 0.2070, 0.2217, 0.1767, 0.2171, 0.1676, 0.2048, 0.2120, 0.2088, 0.2031,\n 0.2204, 0.2170, 0.2038, 0.2140, 0.2477, 0.2308, 0.2371, 0.2270, 0.1676,\n 0.2499, 0.2258, 0.1976, 0.1482, 0.2133, 0.2225, 0.2355, 0.1918, 0.1898,\n 0.2153, 0.2440, 0.2201, 0.2105, 0.2677, 0.2107, 0.1848, 0.1916, 0.2381,\n 0.2381, 0.2064, 0.2496, 0.2386, 0.2257, 0.2155, 0.2123, 0.2280, 0.2288,\n 0.1386, 0.2435, 0.2328, 0.2013, 0.1795, 0.1878, 0.2313, 0.2245, 0.2396,\n 0.1735, 0.2242, 0.1428, 0.2069, 0.2086, 0.2107, 0.2427, 0.2180, 0.1879,\n 0.2241, 0.1805, 0.1434, 0.2149, 0.2274, 0.1824, 0.2421, 0.2333, 0.2366,\n 0.1909, 0.2624, 0.2444, 0.2162, 0.2361, 0.2252, 0.2109, 0.2440, 0.2409,\n 0.2243, 0.2180, 0.2159, 0.2252, 0.2367, 0.2004, 0.2137, 0.1984, 0.2461,\n 0.1720, 0.2494, 0.2380, 0.2163, 0.2167, 0.2155, 0.1850, 0.2177, 0.2074,\n 0.2176, 0.2390, 0.2314, 0.2041, 0.2278, 0.2210, 0.1637, 0.1706, 0.2139,\n 0.2583, 0.1526, 0.2249, 0.2343, 0.1953, 0.2278, 0.2464, 0.2168, 0.1954,\n 0.2537, 0.2273, 0.2125, 0.2541, 0.1638, 0.2325, 0.2042, 0.2250, 0.2013,\n 0.2010, 0.2160, 0.2251, 0.2156, 0.2236, 0.2380, 0.1793, 0.2491, 0.2236,\n 0.2061, 0.2208, 0.2278, 0.2054, 0.2408, 0.1973, 0.2463, 0.1989, 0.1284,\n 0.2064, 0.2206, 0.2357, 0.2224, 0.1910, 0.2149, 0.2260, 0.2162, 0.2435,\n 0.2345, 0.2013, 0.2186, 0.2409, 0.2160, 0.1853, 0.2110, 0.2130, 0.2250,\n 0.1738, 0.2154, 0.2371, 0.2335, 0.1794, 0.1984, 0.2188, 0.2175, 0.2359,\n 0.1791, 0.2089, 0.2594, 0.1387, 0.2517, 0.2159, 0.2412, 0.2061, 0.2258,\n 0.2142, 0.2424, 0.2269, 0.1908, 0.2057, 0.2309, 0.1889, 0.2368, 0.1950,\n 0.2110, 0.1711, 0.2387, 0.2361, 0.1936, 0.2235, 0.2058, 0.2051, 0.2345,\n 0.2036, 0.2117, 0.2441, 0.2067, 0.2143, 0.2433, 0.1487, 0.1597, 0.2162,\n 0.2209, 0.1456, 0.2124, 0.2077, 0.1916, 0.2025, 0.2222, 0.2134, 0.2217,\n 0.2077, 0.2437, 0.2066, 0.2008, 0.2136, 0.2433, 0.2335, 0.1948, 0.2279,\n 0.1887, 0.1952, 0.2006, 0.2147, 0.2174, 0.2090, 0.2537, 0.2161, 0.2652,\n 0.2184, 0.2255, 0.2111, 0.2298, 0.2154, 0.2309, 0.2398, 0.2156, 0.2307,\n 0.1999, 0.2660, 0.1825, 0.2122, 0.2359, 0.2241, 0.2453, 0.2181, 0.2394,\n 0.1994, 0.2192, 0.2033, 0.2203, 0.2483, 0.1811, 0.2798, 0.1655, 0.2240,\n 0.2156, 0.2327, 0.2073, 0.1698, 0.1392, 0.2025, 0.2342, 0.1976, 0.2337,\n 0.1915, 0.2010, 0.2482, 0.2093, 0.2169, 0.2498, 0.2312, 0.1662, 0.2230,\n 0.2268, 0.2134, 0.1958, 0.2022, 0.2505, 0.1393, 0.2156, 0.2354, 0.2554,\n 0.2286, 0.2390, 0.1465, 0.2437, 0.1429, 0.2369, 0.1371, 0.2259, 0.2204,\n 0.1894, 0.2320, 0.2339, 0.1982, 0.2075, 0.2330, 0.2122, 0.2052, 0.2220,\n 0.2316, 0.2389, 0.2068, 0.2111, 0.2327, 0.2257, 0.2433, 0.2283, 0.2235,\n 0.1940, 0.2168, 0.2542, 0.2139, 0.1928, 0.2419, 0.1546, 0.1811, 0.2115,\n 0.2026, 0.2207, 0.2327, 0.2219, 0.1888, 0.2473, 0.2302, 0.2204, 0.1728,\n 0.1762, 0.2135, 0.2244, 0.2361, 0.1667, 0.2177, 0.2160, 0.1966, 0.2251,\n 0.2440, 0.2148, 0.2224, 0.2049, 0.2429, 0.2285, 0.2142, 0.2094, 0.1973,\n 0.2270, 0.5018, 0.2073, 0.2434, 0.1946, 0.2233, 0.2058, 0.2272, 0.2033,\n 0.2157, 0.1805, 0.2094, 0.1671, 0.2378, 0.2321, 0.2101, 0.1976, 0.2135,\n 0.2229, 0.2217, 0.2194, 0.2226, 0.2249, 0.2142, 0.1569, 0.1943, 0.1887,\n 0.2235, 0.1693, 0.2280, 0.2345, 0.2197, 0.2350, 0.2313, 0.2531, 0.2588,\n 0.2226, 0.2243, 0.2214, 0.2188, 0.2016, 0.2060, 0.2003, 0.1786, 0.1851,\n 0.2232, 0.2358, 0.1324, 0.2264, 0.1870, 0.2106, 0.1842, 0.2209, 0.2235,\n 0.1996, 0.2175, 0.1722, 0.2213, 0.2256, 0.2360, 0.1937, 0.2294, 0.2015,\n 0.2145, 0.2035, 0.2200, 0.2575, 0.2337, 0.2351, 0.2267, 0.1848, 0.2218,\n 0.2210, 0.2325, 0.2324, 0.1882, 0.2106, 0.2174, 0.2595, 0.2029, 0.2106,\n 0.1901, 0.2320, 0.1871, 0.2314, 0.2166, 0.2343, 0.2131, 0.2143, 0.1854,\n 0.2237, 0.2462, 0.2286, 0.2198, 0.2144, 0.2487, 0.1728, 0.2608, 0.2052,\n 0.2057, 0.1650, 0.1963, 0.1992, 0.2066, 0.2255, 0.2109, 0.2287, 0.2099,\n 0.1980, 0.2269, 0.2547, 0.2193, 0.2134, 0.2276, 0.2373, 0.2388, 0.2191,\n 0.1681, 0.3013, 0.1776, 0.1999, 0.1922, 0.2195, 0.1899, 0.2256, 0.2529,\n 0.1214, 0.2318, 0.2215, 0.2242, 0.1851, 0.1977, 0.2210, 0.1802, 0.2181,\n 0.2830, 0.2443, 0.2054, 0.2077, 0.2285, 0.2107, 0.2225, 0.2220]), 'model.layer4.2.bn1.bias': tensor([-0.1545, -0.1661, -0.1778, -0.2135, -0.1730, -0.2021, -0.2156, -0.2060,\n -0.1252, -0.1287, -0.1164, -0.1525, -0.2169, -0.2192, -0.1966, -0.1992,\n -0.0320, -0.1816, -0.1593, -0.2148, -0.0628, -0.1966, -0.1054, -0.1828,\n -0.1911, -0.1494, -0.1915, -0.1767, -0.1617, -0.1573, -0.1470, -0.2777,\n -0.1920, -0.1925, -0.1800, -0.0799, -0.1871, -0.1794, -0.1517, -0.0369,\n -0.1699, -0.1716, -0.1762, -0.1204, -0.1607, -0.1725, -0.1987, -0.1494,\n -0.2092, -0.2784, -0.1670, -0.1150, -0.1390, -0.2460, -0.2084, -0.1486,\n -0.2294, -0.2354, -0.1821, -0.1249, -0.1441, -0.2252, -0.1690, -0.0254,\n -0.1929, -0.2079, -0.0507, -0.0881, -0.1051, -0.2134, -0.2303, -0.2303,\n -0.0259, -0.2136, -0.0012, -0.1653, -0.1608, -0.1886, -0.2388, -0.1881,\n -0.0887, -0.1722, -0.0946, -0.0470, -0.1523, -0.2143, -0.1066, -0.2185,\n -0.1815, -0.2138, -0.1427, -0.2782, -0.2558, -0.2006, -0.2317, -0.2246,\n -0.2022, -0.2622, -0.2557, -0.2035, -0.1958, -0.1445, -0.2021, -0.2426,\n -0.1412, -0.1724, -0.1677, -0.2299, -0.0810, -0.2594, -0.2238, -0.1753,\n -0.1858, -0.1644, -0.1270, -0.1634, -0.1787, -0.1967, -0.2447, -0.1900,\n -0.1758, -0.1775, -0.1802, -0.0529, -0.0943, -0.1405, -0.2581, -0.0688,\n -0.2070, -0.2096, -0.1478, -0.2118, -0.2719, -0.1570, -0.1325, -0.2380,\n -0.2092, -0.1833, -0.2618, -0.0591, -0.1930, -0.1404, -0.1920, -0.1342,\n -0.1938, -0.1971, -0.1994, -0.1619, -0.2066, -0.2828, -0.1244, -0.2355,\n -0.1954, -0.1668, -0.1826, -0.1779, -0.1782, -0.2374, -0.1461, -0.2302,\n -0.1752, 0.0682, -0.1599, -0.1923, -0.2273, -0.1802, -0.0966, -0.2136,\n -0.1818, -0.1934, -0.2164, -0.2387, -0.1384, -0.1565, -0.2338, -0.1743,\n -0.0485, -0.1688, -0.1764, -0.1840, -0.1012, -0.1869, -0.2138, -0.2175,\n -0.1225, -0.1338, -0.2076, -0.1678, -0.2293, -0.1259, -0.1691, -0.2740,\n 0.0611, -0.2342, -0.2237, -0.1996, -0.1628, -0.1876, -0.2076, -0.1763,\n -0.2262, -0.1538, -0.1513, -0.2410, -0.0700, -0.2680, -0.1486, -0.1776,\n -0.0789, -0.2776, -0.2006, -0.1575, -0.1932, -0.1821, -0.1653, -0.2325,\n -0.1571, -0.1925, -0.2406, -0.1482, -0.1911, -0.2272, -0.0366, -0.0043,\n -0.1630, -0.2153, -0.0627, -0.1648, -0.1411, -0.1578, -0.1028, -0.2142,\n -0.1940, -0.1754, -0.1459, -0.2605, -0.1760, -0.1753, -0.1634, -0.2119,\n -0.2279, -0.1418, -0.1619, -0.1478, -0.1693, -0.1713, -0.1981, -0.2244,\n -0.1403, -0.2487, -0.1149, -0.3211, -0.1361, -0.2310, -0.1843, -0.2219,\n -0.1647, -0.2357, -0.2268, -0.1976, -0.2230, -0.1492, -0.2873, -0.0955,\n -0.1581, -0.2405, -0.2000, -0.2559, -0.1186, -0.2174, -0.1782, -0.1521,\n -0.1387, -0.1819, -0.2371, -0.1152, -0.1845, -0.0278, -0.1894, -0.1687,\n -0.2027, -0.1359, -0.0814, -0.0063, -0.1252, -0.2186, -0.1345, -0.2206,\n -0.1865, -0.1469, -0.2600, -0.1739, -0.1866, -0.2594, -0.2447, -0.0693,\n -0.2208, -0.1905, -0.1694, -0.1532, -0.1060, -0.2023, 0.0757, -0.1435,\n -0.2249, -0.2025, -0.1671, -0.2271, -0.0050, -0.2373, 0.0592, -0.2154,\n 0.0687, -0.1760, -0.1713, -0.1396, -0.1980, -0.2206, -0.1044, -0.1423,\n -0.2539, -0.1797, -0.1417, -0.1431, -0.2083, -0.2254, -0.1217, -0.2068,\n -0.2289, -0.2113, -0.2453, -0.1935, -0.2018, -0.1850, -0.2037, -0.2411,\n -0.1472, -0.1372, -0.2522, 0.0856, -0.1255, -0.1897, -0.1281, -0.1796,\n -0.2505, -0.1765, -0.0179, -0.2616, -0.2018, -0.1320, -0.0857, -0.0880,\n -0.1657, -0.1952, -0.1916, -0.0926, -0.1915, -0.1756, -0.2123, -0.1781,\n -0.2685, -0.1633, -0.1779, -0.1001, -0.2563, -0.1851, -0.1970, -0.1858,\n -0.1444, -0.2302, -0.3201, -0.1747, -0.1576, -0.1229, -0.1999, -0.1655,\n -0.2246, -0.1499, -0.1430, -0.0837, -0.2094, -0.1162, -0.2170, -0.2152,\n -0.1712, 0.0583, -0.1826, -0.1945, -0.1680, -0.1649, -0.2315, -0.2335,\n -0.1638, -0.0268, -0.1420, -0.0839, -0.1954, -0.1268, -0.2234, -0.2587,\n -0.1640, -0.2453, -0.1999, -0.2591, -0.2673, -0.1863, -0.1965, -0.2008,\n -0.1839, -0.1885, -0.1437, -0.1705, -0.1100, -0.0850, -0.1666, -0.1975,\n 0.0980, -0.2001, -0.1411, -0.1936, -0.0612, -0.1757, -0.2063, -0.1551,\n -0.1852, -0.1020, -0.1952, -0.1721, -0.2515, -0.0627, -0.1749, -0.1245,\n -0.1665, -0.1915, -0.2167, -0.2677, -0.2084, -0.1538, -0.2039, -0.1080,\n -0.2338, -0.1609, -0.2277, -0.2552, -0.1285, -0.1827, -0.1960, -0.2793,\n -0.1457, -0.1532, -0.1205, -0.2011, 0.0781, -0.2215, -0.1715, -0.1698,\n -0.1880, -0.1690, -0.1424, -0.2141, -0.2473, -0.1803, -0.1511, -0.1893,\n -0.2738, -0.1224, -0.2776, -0.0773, -0.2112, -0.1043, -0.1223, -0.1429,\n -0.1470, -0.2179, -0.1734, -0.1522, -0.1438, -0.1464, -0.2401, -0.2957,\n -0.1914, -0.1993, -0.1890, -0.2300, -0.2507, -0.2249, -0.0681, -0.0821,\n -0.1061, -0.1253, -0.1305, -0.1968, -0.1551, -0.2187, -0.2616, 0.0537,\n -0.2274, -0.2200, -0.1967, -0.1042, -0.1408, -0.2190, -0.1007, -0.1952,\n -0.3317, -0.2710, -0.1187, -0.1513, -0.1623, -0.1395, -0.1831, -0.2220]), 'model.layer4.2.bn1.running_mean': tensor([ 0.2787, -1.2147, -0.6695, -1.0231, 0.1235, -1.0126, -1.1896, -0.6289,\n -0.0595, -0.2489, -0.6745, -1.3470, 0.2367, -0.3167, -0.9602, -0.7514,\n 0.3343, -0.3471, -0.8354, -0.5989, -0.1361, -0.6929, -0.7556, 0.3533,\n -1.1223, -0.9664, 0.0586, -0.6015, -0.6397, -1.2052, 0.0901, -1.1049,\n -1.3454, -0.5251, -0.5422, 0.6638, -0.0246, -0.7415, -0.6213, 0.3221,\n -1.3430, 0.3337, -0.2615, -0.4010, -1.1547, 0.0725, -0.0899, -0.7424,\n -1.2643, -0.3181, -0.6107, -1.0647, -1.1829, -1.1686, -0.2406, -0.6729,\n -1.1948, -1.1255, -0.7804, -0.4294, -0.3019, -1.1218, -0.3706, -0.9696,\n -0.4293, -0.0840, -0.3997, -0.3959, -0.0581, -0.2493, -0.7627, -0.8307,\n -0.1772, -0.8449, -0.2329, -0.8265, -0.3207, -1.2905, -0.4291, -0.4197,\n 0.3886, -0.0739, -0.8115, -0.4621, -0.1453, -0.6726, 0.0475, -0.1543,\n -0.5351, -0.6590, -0.5064, -0.5366, -0.8648, -0.7677, -1.4716, -0.1719,\n -0.1018, -0.1242, -1.3045, -1.0105, -0.9556, -0.0254, -1.0961, -0.3347,\n 0.1826, -0.8773, -0.2746, -0.3654, -0.2862, -0.3449, -0.5195, -0.4286,\n -1.5594, -0.0062, -0.7738, -0.3945, -0.4048, -0.5807, -0.6896, 0.2052,\n -0.8638, -0.9309, -0.3707, -0.1863, -0.7976, -0.4791, -0.8673, -1.3552,\n -0.3381, -0.8048, -1.3911, -0.5697, -0.4016, -0.1806, -0.4871, -0.7966,\n -0.3362, -1.4552, -0.9165, 0.5128, -0.3910, -0.2952, -0.5033, -0.1149,\n -0.4301, -0.7729, -1.1638, -0.9103, -0.9085, -1.1795, -1.0962, -0.0344,\n -0.0242, 0.1319, -0.9706, -0.3085, -0.3102, -0.0809, -0.9338, -0.3632,\n -0.8179, -0.1155, -0.1099, -0.7425, -0.6196, -1.5833, -0.1151, -0.8201,\n -0.3932, -1.1715, 0.0953, -1.4468, -1.2240, -0.7294, -1.3615, -0.6013,\n -0.3000, -0.8101, 1.0694, -0.5120, -0.0220, -1.4379, -0.5565, 0.4477,\n -0.1514, -0.3253, -0.6162, 0.1277, -0.7452, -1.1974, 0.3654, -1.0784,\n 0.3186, 0.1991, -1.0485, 0.0476, -1.3239, 0.0379, -1.1949, -0.2383,\n -1.0050, -1.0970, 0.4429, -0.9958, -0.2154, -1.2942, -0.4679, -0.7473,\n -0.4075, -0.8069, -0.2498, -1.4133, -0.7381, 0.0738, -1.1117, -0.3882,\n -1.3344, -0.9885, -0.5298, -1.0965, 0.2437, -0.8361, -0.3473, -0.5771,\n 0.4569, -0.2289, -0.8162, -0.3150, -0.4236, -1.4273, -0.3161, -1.2617,\n -0.8695, -1.3002, -0.3275, -1.0152, -0.3458, -1.1311, -0.8292, 0.2131,\n -1.1838, -1.4553, 0.0767, -1.2600, 0.0059, -1.2937, -1.2509, 0.1557,\n -0.2520, -0.1420, -0.0184, -1.0103, -0.2540, -0.5563, -0.9655, -0.0497,\n 0.4775, -1.2031, 0.1245, -0.5669, -0.6205, -0.8012, -0.7461, -0.7422,\n -0.6036, -1.3523, 0.4689, -1.2364, -0.3892, -0.5749, -0.9400, -0.7682,\n -0.6807, -0.5774, -0.2634, -1.3803, 0.5380, -0.4888, -0.6250, -1.1211,\n -0.4180, -0.4476, -0.4908, 0.3491, -0.3845, -0.8909, -0.0864, -1.0198,\n -0.7722, -0.8958, -0.3491, -0.9257, -0.5284, -0.6439, -1.1526, 0.0078,\n -0.4055, -0.9404, -0.1443, -0.3699, -0.5062, -1.3412, -0.1049, 0.0545,\n -1.0644, -0.6477, 0.1430, -0.6683, -0.1130, -1.4914, 0.1540, -1.1583,\n 0.1278, -0.0720, 0.1889, -0.5754, 0.0149, -1.4741, -0.4135, -0.7204,\n -1.0563, -1.0196, 0.3971, -0.0068, -0.6412, -1.1449, -0.4685, -1.0688,\n -1.2378, -0.9516, -1.2351, -0.0223, -0.9480, -0.4503, -1.1944, 0.5431,\n -0.3499, -0.6831, -0.8512, 0.3979, -0.5833, -0.3742, -0.6102, -0.8966,\n -0.4306, -0.8444, -0.6469, -0.3368, -0.6313, -0.1104, -0.2524, 0.7239,\n -0.0388, 0.8480, -0.7530, -0.3233, -0.5070, 0.0642, -1.2835, -0.8325,\n -0.6746, 0.0332, -0.7292, -0.0710, -1.1210, -0.6827, -1.1582, -0.6550,\n 0.5476, -0.9237, 1.9325, -0.5189, -0.4357, -1.0167, -0.8354, -0.0116,\n -1.0483, -0.2536, -0.7469, 0.3478, -1.0755, -0.2962, -0.3862, -1.3852,\n -0.3132, -0.7641, -0.7141, -1.0315, -0.4981, -0.3623, 0.2902, -1.2507,\n 0.0325, -0.0728, -0.6092, -0.2458, -0.5385, -0.9761, -0.1167, -0.2374,\n -0.1572, -0.1031, -0.6444, -0.4777, -1.3970, -0.5546, -0.2222, -0.7961,\n -0.9376, -1.0124, -0.2556, -0.9518, -0.3250, -0.1855, -0.2078, -0.8804,\n 0.0855, -1.3501, -0.6854, -0.6168, -0.7024, -0.5473, -0.7856, -0.2101,\n -0.7754, -0.2112, -0.9610, -0.3616, -1.3202, -0.3098, -0.1827, -0.8083,\n -0.3050, -0.2726, -0.2405, 0.9257, -0.5033, 0.1761, -0.9605, -0.9760,\n -0.8865, -0.3079, -1.4668, 0.1691, 0.4223, -0.5194, -0.7585, -0.7942,\n -0.9942, 0.2201, -0.3009, -1.0612, -0.2476, -1.1416, -0.2880, -0.1658,\n -1.1660, -1.0769, -1.2655, -0.6919, -0.5023, -0.5030, -0.4691, -0.5198,\n -0.3573, -1.1263, -0.4082, -0.5497, -0.8806, -0.3346, -0.6337, -0.2799,\n -1.2525, -1.0290, -1.0412, -0.1413, -0.4457, -1.3163, -0.2331, -1.0087,\n -0.2857, 0.0210, -1.3754, -1.1071, -0.8300, -0.9878, -0.3063, -1.1166,\n -1.1619, 0.4082, -0.8273, 0.0138, 0.1413, -0.8160, -0.1917, 0.0695,\n -0.9464, -1.0774, -0.6748, -0.3535, -0.3182, -1.2174, -0.4922, -1.1444,\n -0.2628, -0.5137, -0.3632, -0.9149, -0.3013, -0.0956, -0.1798, 0.0825]), 'model.layer4.2.bn1.running_var': tensor([ 1.7176, 2.4043, 0.6088, 1.7994, 2.9449, 1.7590, 0.9804, 1.4170,\n 1.7845, 1.3720, 0.6626, 1.5346, 2.0606, 1.0191, 0.7585, 2.2696,\n 5.5601, 0.6275, 0.7496, 0.9803, 3.3418, 1.2734, 1.5723, 1.7805,\n 2.2371, 1.2424, 1.0763, 1.7934, 1.8716, 0.6496, 0.7056, 1.7295,\n 1.6167, 2.3120, 1.5240, 1.3410, 2.1321, 1.8106, 1.4550, 0.5136,\n 1.7943, 3.2101, 2.0453, 0.7620, 1.8125, 0.7452, 2.4447, 2.6155,\n 2.5595, 2.2671, 1.5459, 1.9019, 1.7352, 1.0413, 3.8209, 1.8838,\n 2.0857, 2.9146, 0.6362, 2.9795, 1.3391, 1.4573, 1.6128, 2.5203,\n 2.2563, 0.5873, 4.3312, 0.8601, 1.8095, 0.7858, 1.1781, 0.6503,\n 3.8302, 0.5792, 2.5352, 1.4553, 2.2888, 2.0179, 0.5226, 2.1422,\n 2.2572, 2.8522, 2.1926, 1.4025, 3.4829, 1.4035, 0.8195, 1.4919,\n 2.2091, 1.7116, 1.6545, 2.1620, 0.4508, 1.2502, 2.0571, 0.9361,\n 0.7444, 1.0292, 1.7513, 2.6191, 1.2694, 0.6945, 1.4017, 1.8092,\n 0.9354, 2.5079, 1.7545, 1.4336, 1.6375, 2.4701, 1.4539, 0.9502,\n 3.0083, 3.4076, 2.6775, 2.2308, 0.7860, 1.0813, 0.7617, 1.5407,\n 2.1911, 1.7970, 0.7787, 0.6066, 0.8010, 2.4889, 1.8127, 2.1338,\n 1.8120, 0.6320, 1.3774, 2.0034, 1.0091, 2.4029, 1.9411, 1.1333,\n 2.0169, 2.4324, 1.3817, 2.7103, 2.7821, 2.2658, 2.5628, 3.6925,\n 1.0636, 1.4942, 1.5911, 1.0883, 0.5607, 1.0385, 1.3641, 0.7005,\n 1.8731, 0.6620, 1.3027, 0.5829, 1.6203, 0.8570, 1.6799, 1.1327,\n 1.4142, 3.3888, 1.0648, 0.5261, 1.5913, 3.6666, 3.4993, 0.6292,\n 0.8556, 2.0526, 1.1991, 1.7536, 1.8725, 2.4372, 2.9093, 1.9171,\n 0.6714, 0.7011, 3.5888, 2.3403, 0.9791, 2.4367, 1.1383, 1.4790,\n 0.8843, 0.6576, 0.3999, 1.5928, 0.5691, 2.0279, 0.9816, 1.8024,\n 2.9792, 2.1157, 0.8552, 2.3150, 1.3079, 1.7880, 0.8760, 3.0750,\n 0.4622, 1.7037, 0.6545, 0.7357, 3.7188, 0.9956, 1.2332, 1.4215,\n 0.6240, 3.0856, 2.3541, 1.7708, 1.1240, 0.8447, 1.6576, 1.1805,\n 2.3569, 2.2035, 0.7625, 1.3794, 1.4187, 1.8343, 0.6158, 3.4432,\n 1.8190, 0.8526, 0.7539, 1.3093, 1.9784, 2.4753, 1.7809, 1.4734,\n 0.6468, 1.2676, 2.8402, 2.7161, 2.6978, 2.1547, 0.5402, 0.8769,\n 1.7004, 1.8505, 2.8289, 2.5247, 1.1279, 1.6749, 1.2026, 1.5041,\n 3.1996, 1.4583, 3.3426, 1.1353, 3.2273, 1.7285, 1.3860, 1.2543,\n 1.1106, 1.5160, 0.9445, 1.5662, 1.8705, 1.4315, 0.8712, 1.6649,\n 2.4140, 1.1910, 1.4472, 2.1322, 4.1498, 1.8244, 0.7558, 0.9347,\n 0.5639, 1.9123, 2.3086, 2.4912, 4.9193, 3.9189, 2.5148, 0.6111,\n 1.1746, 2.1574, 0.9818, 1.5818, 0.4991, 1.0808, 0.6182, 1.1103,\n 0.4860, 1.3279, 1.1637, 0.6827, 1.0458, 1.4439, 2.3362, 0.8938,\n 1.5770, 1.5119, 0.8358, 0.7277, 1.9011, 1.0184, 4.5990, 2.7950,\n 1.4035, 0.9884, 2.6736, 1.1159, 0.7184, 2.6923, 4.8029, 1.4798,\n 2.7733, 2.3578, 1.0892, 2.1764, 1.2563, 1.9555, 1.0778, 1.6043,\n 0.9391, 1.3822, 0.9337, 3.7654, 0.8472, 0.5964, 3.0490, 1.1346,\n 1.2672, 1.4139, 1.8327, 2.7282, 1.2831, 0.7020, 1.5740, 1.0080,\n 1.5819, 1.7634, 1.3866, 7.5584, 2.8361, 1.3637, 1.4120, 2.1029,\n 0.9555, 0.6644, 5.1756, 1.0443, 2.2415, 1.7797, 0.6120, 2.2659,\n 0.5658, 1.8181, 2.0669, 1.6030, 2.5924, 2.8200, 1.7685, 0.7483,\n 0.6688, 3.1857, 1.1745, 2.1434, 1.5830, 1.3503, 2.7878, 0.7290,\n 0.9167, 0.7918, 15.2728, 1.0671, 2.5571, 3.1089, 0.7624, 1.2570,\n 1.0056, 1.3314, 0.7570, 2.4496, 1.3173, 0.6368, 2.7302, 1.7571,\n 2.3712, 4.0544, 0.9176, 0.7610, 2.5873, 0.5200, 2.1340, 2.4016,\n 2.7161, 1.5670, 1.4735, 2.0914, 0.7260, 1.6589, 1.0990, 0.9243,\n 2.2149, 2.1434, 2.3153, 0.6631, 1.5036, 2.5398, 2.0089, 1.0682,\n 1.4106, 2.3192, 1.2725, 1.3908, 0.8828, 1.9880, 1.9207, 2.5122,\n 0.6187, 1.1817, 1.7398, 1.7291, 3.8382, 2.4959, 0.9197, 0.4221,\n 1.2759, 0.7664, 1.0471, 2.8095, 1.7549, 4.8955, 2.8248, 2.1225,\n 1.4301, 1.0569, 2.2273, 2.1023, 0.4913, 3.7530, 1.0346, 0.6622,\n 0.9708, 2.1661, 1.8241, 1.7126, 2.7907, 0.9628, 0.6159, 0.7832,\n 1.6554, 1.2938, 1.3608, 0.8185, 4.5052, 1.3289, 1.9500, 0.6968,\n 0.7923, 1.6531, 2.2569, 1.0049, 1.6509, 0.5017, 1.7096, 0.6497,\n 1.2363, 1.2852, 0.9569, 1.2223, 1.1760, 1.6871, 1.4319, 1.7817,\n 1.9380, 2.6628, 1.2768, 4.1222, 2.2056, 1.6591, 1.1897, 0.6646,\n 0.7578, 1.6335, 1.4246, 0.9180, 0.8152, 2.5929, 0.6000, 7.0945,\n 2.6933, 2.0917, 1.2963, 1.0854, 0.6811, 1.9064, 2.1158, 2.4371,\n 1.3687, 1.2980, 0.6682, 1.4279, 1.4020, 1.5457, 1.1724, 2.0915,\n 2.3912, 1.1792, 2.6319, 1.0961, 1.2340, 2.1602, 2.7125, 1.9662]), 'model.layer4.2.bn1.num_batches_tracked': tensor(7160), 'model.layer4.2.conv2.weight': tensor([[[[-1.3168e-03, 3.3930e-03, 3.2394e-03],\n [ 8.3782e-04, 3.8125e-03, 5.0055e-03],\n [ 7.3740e-03, 4.3614e-03, 4.1662e-03]],\n\n [[ 9.8378e-03, 8.9725e-03, 1.5274e-02],\n [ 7.3459e-03, 8.3131e-03, 5.3135e-03],\n [ 9.0840e-03, 7.8536e-03, 2.6870e-03]],\n\n [[ 8.6639e-03, 8.6420e-03, 1.2931e-02],\n [ 2.7017e-03, 1.1030e-03, 7.0209e-03],\n [ 2.7042e-03, 4.6435e-03, 7.7412e-03]],\n\n ...,\n\n [[-9.9025e-03, 3.2146e-03, -1.7042e-04],\n [-7.9152e-04, 4.5308e-03, 4.5934e-03],\n [-4.4142e-04, 1.3988e-02, 8.7403e-03]],\n\n [[-8.3775e-03, -3.6660e-03, -4.1232e-03],\n [-4.7666e-03, -2.1986e-04, -6.4811e-03],\n [-9.6399e-03, -7.3605e-03, -1.4775e-02]],\n\n [[-5.0097e-03, -8.1527e-03, -5.9550e-03],\n [-3.1148e-03, -1.7063e-03, 3.0027e-03],\n [-7.7158e-03, -7.3996e-03, -5.8103e-03]]],\n\n\n [[[-1.4251e-02, -5.6742e-03, -1.2103e-02],\n [-1.1623e-02, -2.9398e-03, -8.4562e-03],\n [-1.2970e-02, -5.2646e-03, -9.6015e-03]],\n\n [[ 8.0156e-03, 8.3555e-03, 1.1225e-02],\n [ 8.0157e-04, 3.9258e-03, 7.3236e-03],\n [ 3.7232e-03, 4.5246e-03, 6.4030e-03]],\n\n [[ 1.8563e-02, 2.8577e-02, 2.8172e-02],\n [ 1.5815e-02, 2.2666e-02, 2.3206e-02],\n [ 1.6964e-02, 2.4181e-02, 2.6963e-02]],\n\n ...,\n\n [[-8.9092e-03, -8.9711e-03, -1.3233e-02],\n [-4.1864e-03, -4.7642e-03, -6.8998e-03],\n [-2.4545e-06, 1.8775e-04, 5.6371e-03]],\n\n [[-5.0527e-03, -4.8427e-03, -4.2303e-03],\n [-5.3217e-03, -2.9973e-03, -3.8954e-03],\n [-8.8944e-03, -5.6507e-03, -4.8887e-03]],\n\n [[-2.7762e-03, -1.8349e-03, -3.5113e-03],\n [ 1.8681e-03, 9.3854e-03, 2.7426e-03],\n [-3.9564e-03, -6.9075e-06, -5.0764e-03]]],\n\n\n [[[-6.5264e-04, -3.1810e-03, -1.1190e-02],\n [-9.6947e-03, -1.0765e-02, -1.6479e-02],\n [-8.1375e-03, -1.2344e-02, -1.0495e-02]],\n\n [[ 2.6363e-02, 2.0265e-02, 3.0699e-02],\n [ 1.8640e-02, 1.1278e-02, 2.3180e-02],\n [ 1.8580e-02, 1.3749e-02, 2.0589e-02]],\n\n [[ 1.5536e-02, 1.0019e-02, 2.2830e-02],\n [ 1.5666e-02, 5.8354e-03, 2.0790e-02],\n [ 1.5133e-02, 1.0153e-02, 2.0274e-02]],\n\n ...,\n\n [[-1.3343e-02, -1.5504e-02, -1.5619e-02],\n [-9.0868e-03, -1.1172e-02, -1.5760e-02],\n [-1.4473e-02, -1.7999e-02, -1.4048e-02]],\n\n [[-1.7130e-02, -1.4543e-02, -9.9193e-03],\n [-1.0177e-02, -1.0861e-02, -8.4659e-03],\n [-2.8144e-03, -1.4374e-02, -9.1455e-03]],\n\n [[-1.6545e-02, -2.0945e-02, -1.6093e-02],\n [-1.1710e-02, -1.3532e-02, -1.4594e-02],\n [-1.3110e-02, -2.0846e-02, -1.5711e-02]]],\n\n\n ...,\n\n\n [[[ 3.2706e-03, 6.3379e-03, -4.8277e-03],\n [-1.1392e-03, -4.7019e-03, -5.2764e-03],\n [-1.2168e-02, -1.4237e-02, -1.2048e-02]],\n\n [[-1.1272e-02, -1.2488e-02, -1.2983e-02],\n [-8.4507e-03, -5.6784e-03, -8.2368e-03],\n [ 2.3516e-03, 3.3041e-03, -4.7587e-03]],\n\n [[-2.3059e-03, -1.9994e-03, -3.5227e-04],\n [-1.8870e-03, -2.3869e-03, 1.4438e-03],\n [ 2.6389e-03, 1.1421e-03, 3.1684e-03]],\n\n ...,\n\n [[ 1.3315e-03, 2.9363e-03, 4.6714e-03],\n [ 7.2412e-03, 1.9923e-02, 1.5744e-02],\n [-2.0676e-03, 8.6223e-03, 8.9566e-03]],\n\n [[-2.2812e-03, 4.2265e-04, 4.9611e-03],\n [-7.1824e-03, -9.6813e-04, -1.2473e-03],\n [-1.2115e-02, -2.6844e-03, -7.4285e-03]],\n\n [[ 2.9484e-02, 2.5445e-02, 3.7313e-02],\n [ 2.0824e-02, 2.0252e-02, 3.3055e-02],\n [ 2.4435e-02, 1.6965e-02, 2.6901e-02]]],\n\n\n [[[-4.9001e-03, -1.1060e-02, -1.8702e-02],\n [-7.9015e-03, -6.5581e-03, -1.7760e-02],\n [-1.6747e-02, -2.1343e-02, -2.4839e-02]],\n\n [[ 2.2936e-02, 1.8057e-02, 1.3975e-02],\n [ 2.1526e-02, 1.0272e-02, 1.8664e-02],\n [ 2.3081e-02, 1.5889e-02, 1.8745e-02]],\n\n [[-9.6219e-05, 7.4289e-04, 4.3295e-03],\n [-5.8493e-04, 7.4604e-04, -8.2564e-04],\n [-2.9599e-03, -7.0954e-04, -9.6368e-04]],\n\n ...,\n\n [[ 6.4570e-03, 8.4657e-03, 3.7822e-03],\n [ 1.0234e-02, 1.1943e-02, 5.5413e-03],\n [-2.3618e-03, -5.0656e-04, -8.2522e-03]],\n\n [[-2.1838e-02, -1.1923e-02, -1.0403e-02],\n [-4.1736e-03, -5.2275e-03, -3.4047e-03],\n [-2.3199e-03, -5.4538e-03, -6.6744e-03]],\n\n [[-6.2604e-03, -6.0248e-03, -6.0211e-03],\n [-3.7099e-03, -2.8774e-03, -2.6738e-03],\n [-1.3232e-03, -3.0676e-03, -4.6920e-03]]],\n\n\n [[[ 3.4912e-03, -1.0226e-03, -3.8056e-03],\n [-4.3113e-03, -6.1425e-03, -5.8768e-03],\n [-4.8927e-03, -8.2345e-03, -6.6314e-03]],\n\n [[ 1.4054e-02, 1.2516e-02, 1.0289e-02],\n [ 1.5866e-02, 1.0736e-02, 1.5715e-02],\n [ 2.3180e-02, 2.2504e-02, 2.1664e-02]],\n\n [[-4.1740e-03, -1.4976e-02, -1.1874e-02],\n [-4.1885e-03, -7.9695e-03, -6.9984e-03],\n [-3.1763e-03, -8.1781e-03, -1.2031e-02]],\n\n ...,\n\n [[-4.3372e-03, -3.2511e-03, -9.7832e-03],\n [-3.8466e-03, -4.6802e-03, -1.3155e-02],\n [-1.0507e-02, -1.2052e-02, -1.0519e-02]],\n\n [[-5.4531e-03, -3.9759e-03, -4.2130e-03],\n [-1.1244e-02, -4.3210e-03, -6.3320e-03],\n [-4.5883e-03, -3.9160e-03, -7.2285e-03]],\n\n [[-3.0179e-03, -6.5762e-03, -7.8913e-03],\n [-5.6479e-03, -1.0623e-02, -1.1847e-02],\n [-1.3783e-02, -1.8651e-02, -1.9262e-02]]]]), 'model.layer4.2.bn2.weight': tensor([0.2187, 0.1849, 0.1852, 0.2421, 0.2388, 0.1807, 0.2468, 0.2324, 0.2180,\n 0.2330, 0.2221, 0.2540, 0.2152, 0.2019, 0.1961, 0.2901, 0.2177, 0.1961,\n 0.2247, 0.1842, 0.1853, 0.2006, 0.1800, 0.2304, 0.2561, 0.2387, 0.1886,\n 0.1799, 0.2158, 0.2280, 0.2001, 0.1579, 0.3047, 0.2377, 0.2366, 0.1994,\n 0.1908, 0.1962, 0.2500, 0.1947, 0.1899, 0.2106, 0.2140, 0.2175, 0.2172,\n 0.2321, 0.1902, 0.2140, 0.2270, 0.1993, 0.1957, 0.1898, 0.2300, 0.2192,\n 0.2036, 0.2010, 0.2273, 0.2157, 0.1997, 0.2238, 0.2320, 0.2137, 0.1897,\n 0.1980, 0.2073, 0.1901, 0.1971, 0.1421, 0.2286, 0.2433, 0.2276, 0.1744,\n 0.2279, 0.2006, 0.2177, 0.2307, 0.2592, 0.2077, 0.2207, 0.2355, 0.1995,\n 0.1930, 0.2009, 0.2153, 0.2448, 0.1938, 0.1750, 0.2048, 0.2004, 0.2288,\n 0.2066, 0.2400, 0.2161, 0.1995, 0.2382, 0.2192, 0.2218, 0.2292, 0.2519,\n 0.2517, 0.1754, 0.2370, 0.2211, 0.1932, 0.2156, 0.2182, 0.2085, 0.2164,\n 0.2139, 0.2113, 0.2301, 0.1985, 0.2347, 0.2000, 0.2047, 0.2071, 0.2058,\n 0.2640, 0.1725, 0.2217, 0.1700, 0.2181, 0.2246, 0.2038, 0.2222, 0.2455,\n 0.2449, 0.2214, 0.2118, 0.2011, 0.1759, 0.1973, 0.2242, 0.1932, 0.1940,\n 0.2041, 0.2259, 0.2044, 0.1928, 0.2325, 0.1696, 0.2602, 0.1687, 0.1741,\n 0.2162, 0.2220, 0.2455, 0.2047, 0.2178, 0.2016, 0.2211, 0.2307, 0.2194,\n 0.2333, 0.1635, 0.1949, 0.1872, 0.2116, 0.2133, 0.2805, 0.1947, 0.2372,\n 0.2258, 0.2029, 0.2411, 0.1931, 0.2264, 0.1874, 0.1941, 0.2071, 0.2215,\n 0.2237, 0.2316, 0.2847, 0.2832, 0.1987, 0.2288, 0.2493, 0.2249, 0.2274,\n 0.1858, 0.2138, 0.2373, 0.2320, 0.2142, 0.2498, 0.2106, 0.2493, 0.2443,\n 0.2465, 0.2017, 0.2108, 0.2201, 0.2372, 0.1887, 0.2021, 0.2161, 0.2251,\n 0.1933, 0.1913, 0.1862, 0.1952, 0.1949, 0.1989, 0.1921, 0.1777, 0.2041,\n 0.1832, 0.1707, 0.1908, 0.2100, 0.2198, 0.1974, 0.2270, 0.2183, 0.2707,\n 0.2814, 0.1919, 0.2554, 0.2324, 0.2104, 0.1863, 0.1877, 0.2152, 0.1805,\n 0.2004, 0.1961, 0.2664, 0.2329, 0.1855, 0.2009, 0.1922, 0.1760, 0.1814,\n 0.2071, 0.2152, 0.2231, 0.1766, 0.1849, 0.1968, 0.1741, 0.2040, 0.2174,\n 0.2111, 0.1732, 0.2619, 0.2028, 0.2421, 0.2209, 0.2066, 0.2432, 0.2317,\n 0.2252, 0.1984, 0.2156, 0.1935, 0.2781, 0.2489, 0.2074, 0.2155, 0.2006,\n 0.1783, 0.2010, 0.2420, 0.1763, 0.2032, 0.2034, 0.2188, 0.2316, 0.2352,\n 0.2674, 0.1943, 0.1849, 0.2132, 0.2069, 0.2197, 0.1699, 0.1991, 0.2088,\n 0.2425, 0.2278, 0.2277, 0.1743, 0.1873, 0.2105, 0.1860, 0.2008, 0.2033,\n 0.2298, 0.2144, 0.2192, 0.1618, 0.1795, 0.2460, 0.2039, 0.2064, 0.2143,\n 0.2130, 0.1773, 0.1890, 0.2088, 0.1969, 0.1967, 0.2107, 0.2088, 0.1993,\n 0.2026, 0.2310, 0.1833, 0.2351, 0.2017, 0.1853, 0.2222, 0.1926, 0.1994,\n 0.2143, 0.2186, 0.2170, 0.1963, 0.2086, 0.2185, 0.2057, 0.1592, 0.2015,\n 0.2113, 0.2147, 0.2156, 0.1972, 0.2553, 0.2638, 0.2217, 0.2032, 0.2504,\n 0.2534, 0.1783, 0.2031, 0.2070, 0.2129, 0.2127, 0.2396, 0.2143, 0.2090,\n 0.1849, 0.2409, 0.2090, 0.1925, 0.2210, 0.2005, 0.2164, 0.1658, 0.2384,\n 0.2254, 0.2088, 0.2165, 0.1797, 0.2212, 0.1833, 0.2108, 0.1820, 0.2635,\n 0.2025, 0.2124, 0.1911, 0.2188, 0.2245, 0.1733, 0.2253, 0.2129, 0.2503,\n 0.1814, 0.1929, 0.2211, 0.1877, 0.2109, 0.1903, 0.1967, 0.2192, 0.2141,\n 0.1883, 0.2160, 0.2652, 0.2317, 0.2508, 0.2009, 0.2417, 0.2400, 0.2167,\n 0.1850, 0.2174, 0.1695, 0.1823, 0.2125, 0.2293, 0.2615, 0.2475, 0.1975,\n 0.1939, 0.1691, 0.2436, 0.2026, 0.2387, 0.2045, 0.2069, 0.2300, 0.2190,\n 0.1985, 0.2111, 0.2350, 0.1770, 0.1922, 0.2098, 0.2338, 0.1984, 0.2054,\n 0.2215, 0.1951, 0.2258, 0.2270, 0.2082, 0.2454, 0.2095, 0.1943, 0.1982,\n 0.2197, 0.2074, 0.2068, 0.2536, 0.2254, 0.1895, 0.2253, 0.2140, 0.2675,\n 0.2208, 0.2191, 0.2374, 0.2570, 0.1970, 0.1913, 0.1857, 0.2087, 0.1966,\n 0.2195, 0.2019, 0.2067, 0.1918, 0.2049, 0.2127, 0.2077, 0.2370, 0.2247,\n 0.2173, 0.1823, 0.2345, 0.2468, 0.1839, 0.2396, 0.2098, 0.2297, 0.1760,\n 0.2107, 0.1879, 0.1829, 0.1748, 0.1970, 0.2526, 0.1913, 0.2282, 0.2203,\n 0.1966, 0.2058, 0.2020, 0.1996, 0.2097, 0.2349, 0.2868, 0.2236, 0.1814,\n 0.1733, 0.2063, 0.2339, 0.1904, 0.1996, 0.1862, 0.1881, 0.2167, 0.1818,\n 0.2007, 0.2338, 0.2121, 0.2298, 0.2327, 0.2143, 0.1811, 0.1723, 0.2242,\n 0.2059, 0.3288, 0.2197, 0.2159, 0.2093, 0.2337, 0.2208, 0.1748, 0.2257,\n 0.2242, 0.2565, 0.2091, 0.1973, 0.1962, 0.2057, 0.1967, 0.2061]), 'model.layer4.2.bn2.bias': tensor([-0.1029, -0.0067, -0.0573, -0.1379, -0.1714, -0.0251, -0.1542, -0.1501,\n -0.1334, -0.1138, -0.0082, -0.1585, -0.1347, -0.0663, -0.0768, -0.1985,\n -0.1120, -0.0731, -0.0883, -0.0446, -0.0353, -0.0475, -0.0348, -0.1411,\n -0.1275, -0.1496, -0.0918, -0.0578, -0.0720, -0.1135, -0.0636, 0.0261,\n -0.2198, -0.1393, -0.1806, -0.0554, -0.0687, -0.0796, -0.1499, -0.0560,\n -0.0470, -0.0715, -0.1092, -0.1203, -0.1215, -0.0889, -0.0629, -0.1046,\n -0.1035, -0.0781, -0.0595, -0.0415, -0.1117, -0.1014, -0.0662, -0.0693,\n -0.1182, -0.0865, -0.0588, -0.1148, -0.0848, -0.0971, -0.0680, -0.0907,\n -0.0851, -0.0011, -0.0338, 0.1976, -0.0882, -0.1449, -0.1060, -0.0420,\n -0.1262, -0.0846, -0.0580, -0.1007, -0.1535, -0.0668, -0.0851, -0.0633,\n -0.0875, -0.0673, -0.0365, -0.1211, -0.1368, -0.0876, 0.0277, -0.0860,\n -0.0540, -0.1382, -0.0689, -0.1339, -0.1192, -0.0825, -0.1067, -0.0989,\n -0.0969, -0.1275, -0.1535, -0.1460, -0.0338, -0.1264, -0.1079, -0.0541,\n -0.0963, -0.1159, -0.0387, -0.0609, -0.1318, -0.0765, -0.1245, -0.0090,\n -0.1204, -0.0420, -0.0987, -0.0908, -0.0082, -0.1516, -0.0319, -0.1252,\n -0.0364, -0.0799, -0.1007, -0.0565, -0.1016, -0.1559, -0.1304, -0.1033,\n -0.0743, -0.0811, -0.0139, -0.0764, -0.0953, -0.0533, -0.0479, -0.0758,\n -0.0903, -0.0498, -0.0642, -0.1017, -0.0192, -0.1729, -0.0547, -0.0367,\n -0.0999, -0.1022, -0.1423, -0.0526, -0.1052, -0.0705, -0.0975, -0.1023,\n -0.0804, -0.1285, -0.0295, -0.0574, -0.0627, -0.1048, -0.0996, -0.2270,\n -0.0462, -0.1279, -0.0975, -0.0812, -0.1275, -0.0684, -0.1175, -0.0490,\n -0.0717, -0.0720, -0.1168, -0.1316, -0.1208, -0.2710, -0.2008, -0.0881,\n -0.1223, -0.1453, -0.1331, -0.0871, -0.0439, -0.1022, -0.1494, -0.1136,\n -0.0971, -0.1554, -0.0812, -0.1522, -0.1449, -0.1359, -0.0505, -0.0506,\n -0.0936, -0.1560, -0.0425, -0.0530, -0.0940, -0.0674, -0.0827, -0.0865,\n -0.0067, -0.0981, -0.0533, -0.0276, -0.0631, -0.0601, -0.0491, -0.0157,\n 0.0105, -0.0419, -0.0912, 0.0438, -0.0949, -0.1368, -0.1022, -0.1787,\n -0.1829, -0.0356, -0.1397, -0.1230, -0.0361, -0.0138, -0.0229, -0.1132,\n -0.0644, -0.0808, -0.0471, -0.1557, -0.1376, -0.0069, -0.0773, -0.0509,\n -0.0277, -0.0170, -0.0835, -0.1033, -0.0956, -0.0351, -0.0138, -0.0599,\n -0.0133, -0.0438, -0.1146, -0.0739, 0.0855, -0.1436, -0.0789, -0.1406,\n -0.1003, -0.0569, -0.1188, -0.0888, -0.0900, -0.0617, -0.1062, -0.0776,\n -0.1966, -0.1588, -0.1055, -0.0861, -0.0583, -0.0128, -0.0784, -0.1234,\n -0.0270, -0.0383, -0.0645, -0.0910, -0.0975, -0.1297, -0.1837, -0.0024,\n -0.0364, -0.0505, -0.0755, -0.1096, 0.0160, -0.0815, -0.0891, -0.1807,\n -0.1057, -0.1148, -0.0498, -0.0708, -0.0845, -0.0889, -0.0778, -0.0909,\n -0.1326, -0.0699, -0.0605, 0.0064, -0.0210, -0.1274, -0.0994, -0.0779,\n -0.0818, -0.0831, -0.0325, -0.0464, -0.0348, -0.0564, -0.0515, -0.1099,\n -0.0682, -0.0766, -0.0860, -0.0957, -0.0600, -0.1340, -0.0720, -0.0262,\n -0.1120, -0.0753, -0.0823, -0.0709, -0.1068, -0.1173, -0.0546, -0.0858,\n -0.0931, -0.0817, -0.0258, -0.0720, -0.1102, -0.0914, -0.0986, -0.0825,\n -0.1670, -0.1528, -0.0936, -0.0711, -0.1169, -0.1531, -0.0226, -0.0680,\n -0.0733, -0.1146, -0.1029, -0.1157, -0.0542, -0.1003, -0.0672, -0.0926,\n -0.1122, -0.0568, -0.0852, -0.0657, -0.1212, -0.0245, -0.1069, -0.1208,\n -0.0608, -0.1131, -0.0773, -0.1426, -0.0346, -0.1008, -0.0112, -0.2067,\n -0.0703, -0.0686, -0.0282, -0.1018, -0.1622, -0.0053, -0.0974, -0.1093,\n -0.1559, -0.0554, -0.0767, -0.1111, -0.0573, -0.1448, -0.0306, -0.0920,\n -0.1019, -0.0970, -0.0900, -0.0964, -0.1312, -0.1276, -0.1646, -0.0720,\n -0.1632, -0.1663, -0.0828, -0.0486, -0.0911, -0.0196, 0.0143, -0.0792,\n -0.0812, -0.1507, -0.1313, -0.0533, -0.1008, -0.0184, -0.1594, -0.0480,\n -0.1331, -0.0800, -0.1187, -0.1449, -0.0314, -0.0750, -0.1171, -0.1183,\n -0.0412, -0.0528, -0.0892, -0.0992, -0.0611, -0.0529, -0.0880, -0.0128,\n -0.1045, -0.1425, -0.0482, -0.1293, -0.0776, -0.0549, -0.0667, -0.1001,\n -0.0907, -0.0481, -0.1549, -0.0891, -0.0578, -0.1133, -0.0277, -0.2464,\n -0.0956, -0.1005, -0.1532, -0.1456, -0.0870, -0.0527, -0.0346, -0.0381,\n -0.0829, -0.1001, -0.0699, -0.0910, -0.0659, -0.0714, -0.0966, -0.0899,\n -0.1272, -0.1055, -0.0813, -0.0292, -0.1249, -0.1488, -0.0525, -0.1408,\n -0.0159, -0.1188, -0.0642, -0.0914, -0.0583, -0.0320, -0.0420, -0.0756,\n -0.1461, -0.0720, -0.1171, -0.1277, -0.0326, -0.1097, -0.0856, -0.0723,\n -0.0683, -0.1058, -0.1876, -0.1006, -0.0102, -0.0211, -0.0928, -0.1251,\n -0.0357, -0.0458, -0.0403, -0.0543, -0.1059, -0.0514, -0.1164, -0.1031,\n -0.0896, -0.0991, -0.1191, -0.1077, 0.0140, -0.0449, -0.1280, -0.0715,\n -0.2939, -0.1059, -0.0731, -0.0949, -0.1140, -0.1294, -0.0660, -0.0996,\n -0.0994, -0.1313, -0.0775, -0.0802, -0.0484, -0.0887, -0.0374, -0.1205]), 'model.layer4.2.bn2.running_mean': tensor([-0.4319, -0.5097, -0.3606, -0.3076, -0.3048, -0.4290, -0.2875, -0.2866,\n -0.4593, -0.3432, -0.5256, -0.4434, -0.3476, -0.4149, -0.4163, -0.3989,\n -0.4775, -0.2832, -0.3862, -0.4130, -0.3734, -0.4525, -0.5370, -0.3601,\n -0.4487, -0.4014, -0.2614, -0.3540, -0.4006, -0.3761, -0.5478, -0.4780,\n -0.4020, -0.3507, -0.3461, -0.4721, -0.3224, -0.4399, -0.5292, -0.3218,\n -0.4386, -0.5097, -0.3962, -0.4523, -0.3776, -0.4979, -0.4884, -0.3581,\n -0.3434, -0.2774, -0.4581, -0.1827, -0.2870, -0.3652, -0.2637, -0.3890,\n -0.4803, -0.4100, -0.4358, -0.4095, -0.4784, -0.3558, -0.3392, -0.3423,\n -0.3657, -0.4901, -0.4233, -0.3147, -0.3971, -0.4006, -0.4551, -0.4664,\n -0.3639, -0.2498, -0.4902, -0.3704, -0.4544, -0.4302, -0.3245, -0.4913,\n -0.4446, -0.4056, -0.5386, -0.1748, -0.3954, -0.2375, -0.4944, -0.3541,\n -0.4523, -0.3861, -0.2648, -0.4468, -0.3958, -0.3191, -0.4472, -0.3822,\n -0.4718, -0.3543, -0.3964, -0.3571, -0.4686, -0.4799, -0.5034, -0.4369,\n -0.4144, -0.4486, -0.5217, -0.4263, -0.2635, -0.4226, -0.3658, -0.5628,\n -0.3170, -0.4982, -0.4042, -0.4849, -0.4664, -0.3101, -0.5035, -0.4029,\n -0.1033, -0.4068, -0.4625, -0.4291, -0.3916, -0.4337, -0.5245, -0.3903,\n -0.4877, -0.2902, -0.5407, -0.3018, -0.4269, -0.4327, -0.5502, -0.5200,\n -0.3828, -0.4807, -0.0852, -0.4576, -0.5065, -0.4470, -0.3011, -0.4358,\n -0.4231, -0.4484, -0.3884, -0.3497, -0.3621, -0.4346, -0.5274, -0.4042,\n -0.3528, -0.3819, -0.4341, -0.4343, -0.3062, -0.4444, -0.4499, -0.3944,\n -0.4548, -0.3605, -0.3693, -0.2751, -0.4386, -0.3679, -0.5015, -0.4730,\n -0.4272, -0.4503, -0.4667, -0.4391, -0.4459, -0.4031, -0.4264, -0.4445,\n -0.3361, -0.3961, -0.3421, -0.4745, -0.3158, -0.2855, -0.3351, -0.4594,\n -0.4301, -0.2970, -0.4273, -0.4037, -0.3659, -0.4586, -0.5539, -0.5170,\n -0.3608, -0.2274, -0.4518, -0.4927, -0.3705, -0.4813, -0.3793, -0.4428,\n -0.4241, -0.4014, -0.3478, -0.5458, -0.2624, -0.4407, -0.4780, -0.4652,\n -0.4716, -0.4838, -0.4394, -0.4070, -0.2997, -0.1995, -0.4383, -0.4277,\n -0.4389, -0.5375, -0.4371, -0.3239, -0.5294, -0.4592, -0.5200, -0.3432,\n -0.0967, -0.4551, -0.4408, -0.4167, -0.3879, -0.4826, -0.3617, -0.4543,\n -0.2998, -0.5718, -0.3931, -0.4484, -0.3943, -0.4463, -0.4588, -0.2147,\n -0.1657, -0.4860, -0.4900, -0.4520, -0.3769, -0.4294, -0.3925, -0.3827,\n -0.2670, -0.5016, -0.3480, -0.5300, -0.4510, -0.1890, -0.3825, -0.4634,\n -0.4643, -0.4123, -0.3584, -0.4021, -0.4477, -0.5507, -0.4020, -0.3707,\n -0.2862, -0.5221, -0.4682, -0.3667, -0.3741, -0.3564, -0.3599, -0.5150,\n -0.4680, -0.4851, -0.4129, -0.4112, -0.4880, -0.4519, -0.3965, -0.3017,\n -0.3851, -0.4324, -0.2289, -0.3753, -0.4066, -0.3679, -0.3978, -0.3658,\n -0.4045, -0.4014, -0.4511, -0.3499, -0.4190, -0.3806, -0.4012, -0.4228,\n -0.3767, -0.4604, -0.2284, -0.4682, -0.4707, -0.4337, -0.3974, -0.3915,\n -0.3665, -0.3510, -0.3975, -0.3714, -0.4349, -0.3284, -0.3740, -0.4825,\n -0.3791, -0.4279, -0.4375, -0.3806, -0.4724, -0.3290, -0.5141, -0.4982,\n -0.5646, -0.3405, -0.3507, -0.3216, -0.2455, -0.3534, -0.4814, -0.1834,\n -0.4614, -0.4426, -0.4203, -0.4086, -0.4231, -0.4581, -0.5415, -0.4575,\n -0.4155, -0.3519, -0.2575, -0.3486, -0.4863, -0.4709, -0.3561, -0.4735,\n -0.3487, -0.4478, -0.3476, -0.3781, -0.4110, -0.4273, -0.4044, -0.3736,\n -0.5645, -0.3996, -0.4604, -0.2907, -0.4619, -0.3475, -0.5365, -0.4380,\n -0.2857, -0.4473, -0.4297, -0.3680, -0.2827, -0.5462, -0.4312, -0.3969,\n -0.4531, -0.2308, -0.2938, -0.5315, -0.1349, -0.3062, -0.5167, -0.3829,\n -0.3445, -0.4377, -0.1363, -0.4491, -0.4124, -0.3032, -0.2416, -0.1812,\n -0.3081, -0.4600, -0.4277, -0.4071, -0.4353, -0.3763, -0.5336, -0.5010,\n -0.4719, -0.4477, -0.4165, -0.5061, -0.3771, -0.5518, -0.3275, -0.4312,\n -0.2878, -0.2014, -0.4625, -0.4271, -0.5044, -0.2982, -0.2976, -0.3462,\n -0.1596, -0.4427, -0.2983, -0.4289, -0.3352, -0.3985, -0.3068, -0.5584,\n -0.4236, -0.2713, -0.5478, -0.2994, -0.4391, -0.4275, -0.3277, -0.3431,\n -0.3651, -0.5061, -0.4377, -0.3508, -0.3903, -0.4446, -0.3995, -0.4737,\n -0.3625, -0.3572, -0.3841, -0.4744, -0.4328, -0.4013, -0.5502, -0.5680,\n -0.2233, -0.5335, -0.4243, -0.3955, -0.3796, -0.4603, -0.4263, -0.3852,\n -0.4261, -0.4138, -0.5066, -0.4815, -0.3475, -0.4421, -0.3780, -0.2875,\n -0.4819, -0.4551, -0.3932, -0.2565, -0.3535, -0.5120, -0.3272, -0.2918,\n -0.4047, -0.3919, -0.3178, -0.4347, -0.4827, -0.3011, -0.3743, -0.4480,\n -0.2545, -0.4066, -0.4944, -0.2494, -0.4858, -0.3038, -0.2678, -0.3809,\n -0.5581, -0.4450, -0.4475, -0.2653, -0.3859, -0.3912, -0.3236, -0.3964,\n -0.4535, -0.4302, -0.4220, -0.2709, -0.4953, -0.0816, -0.4073, -0.4863,\n -0.2345, -0.4275, -0.4476, -0.4132, -0.3939, -0.2826, -0.4523, -0.4480,\n -0.4385, -0.3828, -0.3628, -0.5008, -0.5118, -0.4473, -0.5002, -0.2928]), 'model.layer4.2.bn2.running_var': tensor([0.4867, 0.5397, 0.3679, 0.1447, 0.2480, 0.4224, 0.2240, 0.1046, 0.3511,\n 0.3064, 0.6112, 0.3744, 0.3630, 0.5615, 0.2975, 0.2441, 0.3871, 0.1240,\n 0.3691, 0.2262, 0.4067, 0.4080, 0.3959, 0.1906, 0.5857, 0.2213, 0.0661,\n 0.3495, 0.3901, 0.2335, 0.4248, 0.4588, 0.2472, 0.1838, 0.3032, 0.3472,\n 0.2526, 0.4422, 0.4239, 0.2752, 0.4611, 0.4947, 0.3066, 0.2586, 0.2820,\n 0.5882, 0.5760, 0.3486, 0.3070, 0.1774, 0.5001, 0.0771, 0.1380, 0.1969,\n 0.1029, 0.4165, 0.3134, 0.3850, 0.4263, 0.2715, 0.3013, 0.1502, 0.2813,\n 0.1589, 0.3582, 0.5102, 0.4572, 0.2790, 0.4006, 0.2742, 0.2224, 0.5873,\n 0.1742, 0.2135, 0.4807, 0.3695, 0.2486, 0.3948, 0.3648, 0.3355, 0.3548,\n 0.1651, 0.5470, 0.0549, 0.3462, 0.1318, 0.6107, 0.3327, 0.4868, 0.3808,\n 0.1222, 0.3516, 0.3477, 0.2254, 0.4464, 0.3279, 0.2592, 0.2860, 0.3797,\n 0.2138, 0.4833, 0.4199, 0.3389, 0.2996, 0.4676, 0.3130, 0.5125, 0.3670,\n 0.2074, 0.5056, 0.2710, 0.7012, 0.1171, 0.5769, 0.3978, 0.4513, 0.3437,\n 0.0788, 0.5345, 0.2593, 0.1083, 0.4994, 0.5255, 0.4862, 0.4320, 0.2547,\n 0.4037, 0.3388, 0.2684, 0.2381, 0.6546, 0.1007, 0.4369, 0.4792, 0.5910,\n 0.6114, 0.4089, 0.5093, 0.0897, 0.5484, 0.5009, 0.2798, 0.1820, 0.6172,\n 0.2301, 0.4472, 0.3530, 0.3679, 0.1827, 0.4089, 0.4589, 0.3689, 0.3223,\n 0.2191, 0.4635, 0.2068, 0.2464, 0.3023, 0.4304, 0.4145, 0.2412, 0.3093,\n 0.2663, 0.1255, 0.4962, 0.1594, 0.3895, 0.5291, 0.4160, 0.2392, 0.4551,\n 0.2999, 0.4565, 0.3348, 0.2349, 0.4368, 0.3328, 0.4446, 0.1137, 0.3225,\n 0.3312, 0.2403, 0.2443, 0.3178, 0.3660, 0.2129, 0.3924, 0.2379, 0.3443,\n 0.3032, 0.5048, 0.5238, 0.1527, 0.0932, 0.4164, 0.4215, 0.3575, 0.3816,\n 0.3540, 0.2926, 0.3612, 0.4578, 0.3732, 0.6286, 0.0833, 0.2909, 0.5744,\n 0.4356, 0.4807, 0.2900, 0.2741, 0.4324, 0.2495, 0.0722, 0.3402, 0.1951,\n 0.2218, 0.6217, 0.2228, 0.2711, 0.5152, 0.3686, 0.6512, 0.1562, 0.0455,\n 0.3913, 0.3149, 0.4451, 0.2126, 0.5306, 0.2932, 0.2503, 0.2964, 0.6452,\n 0.4449, 0.4749, 0.4076, 0.4335, 0.4114, 0.0944, 0.0656, 0.5211, 0.3231,\n 0.4953, 0.4889, 0.4427, 0.3866, 0.1743, 0.0859, 0.4767, 0.2969, 0.5970,\n 0.4893, 0.0743, 0.4474, 0.2411, 0.2666, 0.2782, 0.3095, 0.4879, 0.4527,\n 0.8437, 0.2544, 0.3734, 0.1242, 0.4824, 0.3138, 0.4061, 0.3407, 0.3162,\n 0.2941, 0.5440, 0.5399, 0.3230, 0.3295, 0.4161, 0.4872, 0.3755, 0.3941,\n 0.0990, 0.3292, 0.2345, 0.0913, 0.2134, 0.3041, 0.2481, 0.4025, 0.3363,\n 0.3189, 0.4388, 0.2695, 0.2948, 0.3971, 0.1910, 0.3902, 0.5244, 0.2853,\n 0.5806, 0.1534, 0.4023, 0.3705, 0.2747, 0.3894, 0.4113, 0.4329, 0.4089,\n 0.3974, 0.3055, 0.2491, 0.2461, 0.3591, 0.5301, 0.3577, 0.3125, 0.2053,\n 0.4633, 0.4638, 0.2880, 0.5527, 0.4856, 0.4926, 0.1959, 0.1686, 0.1315,\n 0.0844, 0.3694, 0.5168, 0.1624, 0.3054, 0.2450, 0.4721, 0.4304, 0.3180,\n 0.3561, 0.6412, 0.4974, 0.4699, 0.1811, 0.1171, 0.3683, 0.4157, 0.4050,\n 0.3654, 0.4899, 0.1891, 0.2322, 0.3269, 0.3824, 0.2556, 0.4020, 0.4435,\n 0.3612, 0.5982, 0.2720, 0.3670, 0.1962, 0.3716, 0.1929, 0.6818, 0.5054,\n 0.2615, 0.5237, 0.4503, 0.1759, 0.2504, 0.6464, 0.4591, 0.3268, 0.3356,\n 0.1092, 0.1175, 0.3957, 0.0929, 0.3321, 0.4715, 0.3127, 0.3663, 0.3988,\n 0.0980, 0.4349, 0.3784, 0.2082, 0.1732, 0.1018, 0.2459, 0.3853, 0.4304,\n 0.4243, 0.4877, 0.4170, 0.6330, 0.4436, 0.6154, 0.3154, 0.3019, 0.4436,\n 0.2979, 0.6472, 0.2494, 0.3830, 0.2215, 0.0841, 0.4458, 0.3232, 0.5870,\n 0.2457, 0.2322, 0.2685, 0.0797, 0.3210, 0.1261, 0.3044, 0.2874, 0.4796,\n 0.2652, 0.7802, 0.2370, 0.2091, 0.6496, 0.1353, 0.2835, 0.4429, 0.3469,\n 0.1818, 0.3478, 0.5716, 0.3702, 0.1491, 0.3791, 0.3553, 0.2987, 0.5512,\n 0.3028, 0.3884, 0.2349, 0.3203, 0.2804, 0.3542, 0.6984, 0.6048, 0.1509,\n 0.3861, 0.4613, 0.3949, 0.3419, 0.2870, 0.3962, 0.3401, 0.3447, 0.4414,\n 0.3676, 0.5345, 0.3012, 0.3374, 0.3310, 0.1285, 0.5664, 0.2436, 0.2636,\n 0.0980, 0.1405, 0.5763, 0.3414, 0.2899, 0.1793, 0.2270, 0.2883, 0.3938,\n 0.4203, 0.2169, 0.3814, 0.3692, 0.1190, 0.4371, 0.4719, 0.0795, 0.5138,\n 0.2651, 0.2041, 0.3701, 0.6383, 0.5210, 0.3282, 0.2297, 0.1865, 0.4567,\n 0.2199, 0.4038, 0.3067, 0.3896, 0.4098, 0.2467, 0.7000, 0.0839, 0.2360,\n 0.2860, 0.0915, 0.3693, 0.5365, 0.3611, 0.4139, 0.1874, 0.4688, 0.3038,\n 0.5067, 0.3322, 0.3000, 0.4215, 0.4892, 0.4412, 0.5584, 0.2022]), 'model.layer4.2.bn2.num_batches_tracked': tensor(7160), 'model.layer4.2.conv3.weight': tensor([[[[ 0.0003]],\n\n [[ 0.0016]],\n\n [[-0.0277]],\n\n ...,\n\n [[ 0.0047]],\n\n [[-0.0206]],\n\n [[ 0.0039]]],\n\n\n [[[ 0.0054]],\n\n [[-0.0029]],\n\n [[ 0.0119]],\n\n ...,\n\n [[-0.0042]],\n\n [[ 0.0253]],\n\n [[ 0.0075]]],\n\n\n [[[ 0.0087]],\n\n [[-0.0059]],\n\n [[ 0.0235]],\n\n ...,\n\n [[-0.0017]],\n\n [[-0.0192]],\n\n [[-0.0058]]],\n\n\n ...,\n\n\n [[[ 0.0009]],\n\n [[-0.0136]],\n\n [[ 0.0070]],\n\n ...,\n\n [[-0.0070]],\n\n [[-0.0194]],\n\n [[-0.0146]]],\n\n\n [[[ 0.0496]],\n\n [[-0.0198]],\n\n [[ 0.0069]],\n\n ...,\n\n [[ 0.0103]],\n\n [[ 0.0105]],\n\n [[-0.0038]]],\n\n\n [[[ 0.0005]],\n\n [[-0.0003]],\n\n [[-0.0014]],\n\n ...,\n\n [[-0.0060]],\n\n [[ 0.0206]],\n\n [[-0.0090]]]]), 'model.layer4.2.bn3.weight': tensor([0.6691, 0.8366, 0.7845, ..., 0.5988, 0.7845, 0.5696]), 'model.layer4.2.bn3.bias': tensor([0.0258, 0.0493, 0.0297, ..., 0.0496, 0.0161, 0.0025]), 'model.layer4.2.bn3.running_mean': tensor([-0.0555, -0.0033, 0.0055, ..., -0.0660, 0.0163, 0.0133]), 'model.layer4.2.bn3.running_var': tensor([0.0026, 0.0039, 0.0025, ..., 0.0032, 0.0029, 0.0021]), 'model.layer4.2.bn3.num_batches_tracked': tensor(7160), 'model.fc.weight': tensor([[ 0.0356, -0.0160, 0.0080, ..., 0.0274, -0.0094, -0.0085],\n [-0.0132, 0.0075, 0.0140, ..., -0.0086, 0.0016, 0.0246]]), 'model.fc.bias': tensor([-0.0097, 0.0011])})", + "callbacks": {}, + "optimizer_states": "[{'state': {0: {'step': 7160, 'exp_avg': tensor([[[[-1.7605e-04, -1.2847e-04, -1.0603e-04, ..., -1.1091e-04,\n -1.2258e-04, -1.5182e-04],\n [-1.0093e-04, -5.8610e-05, -3.6033e-05, ..., -4.7586e-05,\n -6.1282e-05, -9.2022e-05],\n [-4.9631e-05, -2.3213e-05, -1.6384e-05, ..., -4.7294e-05,\n -6.9224e-05, -1.0693e-04],\n ...,\n [ 4.2510e-05, 3.9442e-05, 1.7314e-05, ..., -6.0491e-05,\n -1.0613e-04, -1.4941e-04],\n [ 5.1635e-05, 4.4005e-05, 2.1838e-05, ..., -6.6506e-05,\n -1.1733e-04, -1.6008e-04],\n [ 5.7694e-05, 4.5937e-05, 2.5900e-05, ..., -7.8603e-05,\n -1.2755e-04, -1.6151e-04]],\n\n [[-2.1525e-04, -1.7258e-04, -1.6367e-04, ..., -2.0062e-04,\n -2.1490e-04, -2.5162e-04],\n [-1.3529e-04, -9.5907e-05, -8.9804e-05, ..., -1.2767e-04,\n -1.3762e-04, -1.7489e-04],\n [-9.7281e-05, -6.9517e-05, -7.3732e-05, ..., -1.1568e-04,\n -1.2961e-04, -1.7472e-04],\n ...,\n [-3.4369e-05, -2.8250e-05, -4.7189e-05, ..., -1.1463e-04,\n -1.5032e-04, -2.0897e-04],\n [-2.1781e-05, -2.3542e-05, -4.6520e-05, ..., -1.2941e-04,\n -1.7087e-04, -2.2567e-04],\n [-1.3904e-05, -2.0076e-05, -4.4400e-05, ..., -1.5271e-04,\n -1.9665e-04, -2.3944e-04]],\n\n [[ 7.6326e-05, 1.1592e-04, 1.3385e-04, ..., 1.3018e-04,\n 1.2067e-04, 8.1819e-05],\n [ 1.3864e-04, 1.7146e-04, 1.8476e-04, ..., 1.7641e-04,\n 1.7092e-04, 1.3779e-04],\n [ 1.7249e-04, 1.9095e-04, 1.9168e-04, ..., 1.7290e-04,\n 1.6390e-04, 1.3143e-04],\n ...,\n [ 2.4629e-04, 2.3684e-04, 2.0823e-04, ..., 1.4207e-04,\n 1.2016e-04, 9.3188e-05],\n [ 2.7168e-04, 2.5197e-04, 2.2015e-04, ..., 1.2872e-04,\n 9.6914e-05, 6.8443e-05],\n [ 2.8702e-04, 2.6261e-04, 2.3313e-04, ..., 1.1750e-04,\n 7.8533e-05, 5.5044e-05]]],\n\n\n [[[ 3.3828e-04, 3.5300e-04, 3.8609e-04, ..., 5.0895e-04,\n 5.1820e-04, 4.9372e-04],\n [ 2.7267e-04, 2.7974e-04, 3.1696e-04, ..., 4.3563e-04,\n 4.4306e-04, 4.4196e-04],\n [ 2.2248e-04, 2.1171e-04, 2.5277e-04, ..., 3.4718e-04,\n 3.5342e-04, 3.6334e-04],\n ...,\n [ 2.0560e-04, 1.5224e-04, 1.4569e-04, ..., 1.6463e-04,\n 1.8064e-04, 2.0629e-04],\n [ 2.0144e-04, 1.3796e-04, 1.0411e-04, ..., 1.1450e-04,\n 1.2967e-04, 1.3780e-04],\n [ 2.3319e-04, 1.6567e-04, 1.1981e-04, ..., 8.9121e-05,\n 7.9953e-05, 6.0951e-05]],\n\n [[ 2.9359e-04, 2.9949e-04, 3.3296e-04, ..., 4.3429e-04,\n 4.2353e-04, 3.7365e-04],\n [ 2.2047e-04, 2.1640e-04, 2.5166e-04, ..., 3.5475e-04,\n 3.3902e-04, 3.1565e-04],\n [ 1.7340e-04, 1.5069e-04, 1.8953e-04, ..., 2.7742e-04,\n 2.5704e-04, 2.5190e-04],\n ...,\n [ 1.6243e-04, 1.0017e-04, 8.5662e-05, ..., 1.0636e-04,\n 1.0558e-04, 1.1893e-04],\n [ 1.4544e-04, 7.7858e-05, 3.0463e-05, ..., 5.2119e-05,\n 6.6903e-05, 6.7087e-05],\n [ 1.6161e-04, 9.0596e-05, 3.0459e-05, ..., 1.6352e-05,\n 1.7517e-05, -7.3438e-07]],\n\n [[ 1.7588e-04, 1.9859e-04, 2.3669e-04, ..., 3.3700e-04,\n 3.2568e-04, 2.7780e-04],\n [ 1.0980e-04, 1.2851e-04, 1.6701e-04, ..., 2.6263e-04,\n 2.4249e-04, 2.1289e-04],\n [ 7.7560e-05, 7.5896e-05, 1.1194e-04, ..., 1.7915e-04,\n 1.5625e-04, 1.4306e-04],\n ...,\n [ 4.9308e-05, 9.4880e-06, 9.8113e-06, ..., -9.2777e-06,\n -2.2506e-05, 7.7460e-07],\n [ 1.5383e-05, -2.8847e-05, -4.2478e-05, ..., -5.2306e-05,\n -6.0153e-05, -4.8448e-05],\n [ 1.9883e-05, -3.0021e-05, -4.8561e-05, ..., -6.8911e-05,\n -9.1728e-05, -1.0655e-04]]],\n\n\n [[[ 2.3818e-04, 2.0687e-04, 1.7264e-04, ..., 1.6344e-04,\n 1.5905e-04, 1.5911e-04],\n [ 2.2117e-04, 1.8994e-04, 1.6077e-04, ..., 1.5900e-04,\n 1.5777e-04, 1.5917e-04],\n [ 1.9989e-04, 1.7121e-04, 1.4335e-04, ..., 1.3622e-04,\n 1.3325e-04, 1.3377e-04],\n ...,\n [ 1.4907e-04, 1.1798e-04, 8.6847e-05, ..., 6.5285e-05,\n 6.1502e-05, 6.6681e-05],\n [ 1.2445e-04, 9.3653e-05, 6.2080e-05, ..., 3.5765e-05,\n 3.1889e-05, 3.5471e-05],\n [ 1.1147e-04, 8.3208e-05, 5.2606e-05, ..., 2.3803e-05,\n 1.8033e-05, 1.8732e-05]],\n\n [[ 2.3073e-04, 1.9908e-04, 1.6540e-04, ..., 1.4754e-04,\n 1.4102e-04, 1.4223e-04],\n [ 2.1181e-04, 1.7865e-04, 1.4791e-04, ..., 1.3742e-04,\n 1.3542e-04, 1.3837e-04],\n [ 1.8606e-04, 1.5384e-04, 1.2491e-04, ..., 1.1170e-04,\n 1.0823e-04, 1.0986e-04],\n ...,\n [ 1.3553e-04, 1.0265e-04, 7.0791e-05, ..., 4.7504e-05,\n 4.3794e-05, 4.8391e-05],\n [ 1.1161e-04, 8.0695e-05, 5.0660e-05, ..., 2.3725e-05,\n 1.9280e-05, 2.1898e-05],\n [ 1.0171e-04, 7.5127e-05, 4.9068e-05, ..., 2.2617e-05,\n 1.7235e-05, 1.8131e-05]],\n\n [[ 1.7276e-04, 1.4879e-04, 1.1811e-04, ..., 1.1136e-04,\n 1.1452e-04, 1.1734e-04],\n [ 1.4840e-04, 1.2480e-04, 1.0030e-04, ..., 1.0344e-04,\n 1.1119e-04, 1.1575e-04],\n [ 1.2902e-04, 1.0726e-04, 8.4430e-05, ..., 8.5087e-05,\n 9.1927e-05, 9.4770e-05],\n ...,\n [ 8.3716e-05, 6.5377e-05, 4.3347e-05, ..., 3.4094e-05,\n 3.8447e-05, 4.1431e-05],\n [ 6.7991e-05, 5.2442e-05, 3.1803e-05, ..., 1.6555e-05,\n 1.8484e-05, 1.6993e-05],\n [ 6.1549e-05, 4.9101e-05, 2.9410e-05, ..., 1.2099e-05,\n 1.0781e-05, 4.8609e-06]]],\n\n\n ...,\n\n\n [[[ 5.4995e-06, 3.3071e-05, 3.2968e-05, ..., 4.8202e-06,\n -3.5759e-05, -9.5220e-05],\n [-1.2958e-04, -9.8792e-05, -8.9687e-05, ..., -7.8363e-05,\n -9.8249e-05, -1.4083e-04],\n [-1.6546e-04, -1.2697e-04, -1.0584e-04, ..., -6.3778e-05,\n -6.7140e-05, -9.3810e-05],\n ...,\n [-1.4734e-04, -1.0278e-04, -7.2694e-05, ..., -3.3695e-05,\n -2.8161e-05, -4.4081e-05],\n [-9.4443e-05, -5.2138e-05, -2.2088e-05, ..., 9.4103e-06,\n 1.4142e-05, -6.6966e-07],\n [-4.2069e-05, -6.9966e-06, 1.4492e-05, ..., 3.3005e-05,\n 3.0059e-05, 8.4428e-06]],\n\n [[ 2.3800e-05, 3.0721e-05, 1.8677e-05, ..., -2.9138e-05,\n -6.6231e-05, -1.2389e-04],\n [-1.1592e-04, -1.0830e-04, -1.1856e-04, ..., -1.2658e-04,\n -1.3651e-04, -1.6798e-04],\n [-1.5743e-04, -1.4188e-04, -1.4110e-04, ..., -1.0972e-04,\n -1.0044e-04, -1.1346e-04],\n ...,\n [-1.7774e-04, -1.4824e-04, -1.2608e-04, ..., -7.2696e-05,\n -6.0057e-05, -6.7181e-05],\n [-1.3476e-04, -1.0421e-04, -7.6744e-05, ..., -2.0725e-05,\n -8.0647e-06, -1.8868e-05],\n [-8.6407e-05, -6.0813e-05, -4.0650e-05, ..., 6.4567e-06,\n 1.5086e-05, -5.0844e-06]],\n\n [[ 1.2062e-04, 1.3375e-04, 1.2334e-04, ..., 9.1819e-05,\n 6.7512e-05, 1.6867e-05],\n [ 2.2566e-05, 3.7099e-05, 2.8479e-05, ..., 1.7550e-05,\n 1.1041e-05, -1.4588e-05],\n [-6.3064e-06, 1.6227e-05, 1.4840e-05, ..., 2.6623e-05,\n 3.1799e-05, 2.2524e-05],\n ...,\n [-3.3936e-05, 4.0208e-06, 1.9394e-05, ..., 4.6922e-05,\n 5.5237e-05, 4.9210e-05],\n [ 3.3133e-06, 4.1984e-05, 5.8618e-05, ..., 7.6716e-05,\n 8.4850e-05, 7.9998e-05],\n [ 4.7658e-05, 8.3244e-05, 9.5493e-05, ..., 9.8812e-05,\n 9.7474e-05, 8.4326e-05]]],\n\n\n [[[-6.9964e-05, -1.6185e-05, 1.0171e-05, ..., 1.7046e-05,\n 1.6880e-05, 2.3632e-05],\n [-1.0079e-04, -4.9486e-05, -2.1546e-05, ..., -7.1937e-06,\n -7.8101e-06, -4.8684e-06],\n [-8.8714e-05, -4.6193e-05, -2.0535e-05, ..., -1.8079e-07,\n 1.5286e-06, 2.4590e-06],\n ...,\n [-6.8340e-05, -3.7699e-05, -2.2697e-05, ..., -3.7381e-06,\n 4.1618e-06, 1.0076e-05],\n [-3.6147e-05, -1.0740e-05, 3.6200e-06, ..., 1.8880e-05,\n 2.7803e-05, 3.2016e-05],\n [-2.1799e-05, -5.1679e-06, 1.2197e-05, ..., 2.7881e-05,\n 3.7350e-05, 3.9435e-05]],\n\n [[-3.3976e-05, 1.9914e-05, 4.8818e-05, ..., 5.1734e-05,\n 4.9704e-05, 5.4505e-05],\n [-5.8840e-05, -5.9733e-06, 2.3784e-05, ..., 3.4217e-05,\n 3.2866e-05, 3.4491e-05],\n [-3.6323e-05, 9.4067e-06, 3.6629e-05, ..., 5.2749e-05,\n 5.2480e-05, 4.8832e-05],\n ...,\n [-1.3611e-05, 1.9165e-05, 3.6217e-05, ..., 5.2353e-05,\n 5.7954e-05, 5.8244e-05],\n [ 2.3684e-05, 5.0964e-05, 6.5941e-05, ..., 7.8682e-05,\n 8.5784e-05, 8.6315e-05],\n [ 3.5472e-05, 5.4656e-05, 7.1711e-05, ..., 8.4354e-05,\n 9.3291e-05, 9.2713e-05]],\n\n [[ 3.1032e-05, 7.2347e-05, 9.6314e-05, ..., 9.9873e-05,\n 9.8904e-05, 1.0288e-04],\n [ 8.2762e-06, 4.3645e-05, 6.6457e-05, ..., 7.8329e-05,\n 8.0740e-05, 8.3381e-05],\n [ 1.4388e-05, 4.1600e-05, 6.3160e-05, ..., 8.5797e-05,\n 9.3064e-05, 9.7778e-05],\n ...,\n [ 1.3252e-05, 3.7264e-05, 5.7309e-05, ..., 8.5924e-05,\n 9.9503e-05, 1.1283e-04],\n [ 3.7234e-05, 6.0481e-05, 8.2409e-05, ..., 1.1360e-04,\n 1.3030e-04, 1.4041e-04],\n [ 4.7531e-05, 6.6930e-05, 9.1976e-05, ..., 1.2752e-04,\n 1.4633e-04, 1.5353e-04]]],\n\n\n [[[-2.0923e-04, -1.5055e-04, -6.3728e-05, ..., -5.9529e-05,\n -1.2035e-04, -2.0037e-04],\n [-1.3285e-04, -6.8845e-05, 1.4349e-05, ..., 7.0212e-05,\n 4.8482e-05, -2.3535e-05],\n [-2.1040e-04, -1.2968e-04, -4.6201e-05, ..., 3.0763e-05,\n 5.0238e-05, 9.9655e-06],\n ...,\n [-2.6239e-04, -1.6019e-04, -6.6399e-05, ..., 3.3394e-05,\n 7.8611e-05, 8.7764e-05],\n [-2.1026e-04, -1.3581e-04, -5.4217e-05, ..., 3.7164e-05,\n 6.7550e-05, 9.1007e-05],\n [-2.5139e-04, -2.1924e-04, -1.5302e-04, ..., -7.6854e-05,\n -5.1633e-05, 2.1351e-06]],\n\n [[-1.1977e-04, -6.8771e-05, 2.2806e-05, ..., 1.5358e-05,\n -7.7927e-05, -1.7640e-04],\n [-5.7607e-05, -1.9444e-06, 8.4673e-05, ..., 1.2051e-04,\n 7.8178e-05, -8.0151e-06],\n [-1.3015e-04, -6.2876e-05, 1.6439e-05, ..., 8.3616e-05,\n 9.6394e-05, 4.4606e-05],\n ...,\n [-1.9629e-04, -1.2414e-04, -5.6160e-05, ..., 4.3874e-05,\n 9.0915e-05, 1.0321e-04],\n [-1.9442e-04, -1.4776e-04, -8.4713e-05, ..., 3.0685e-05,\n 7.0187e-05, 1.0710e-04],\n [-2.6009e-04, -2.5482e-04, -2.0693e-04, ..., -9.9104e-05,\n -6.4692e-05, -1.3938e-06]],\n\n [[-2.4436e-04, -2.1492e-04, -1.5815e-04, ..., -1.6562e-04,\n -2.3398e-04, -2.9689e-04],\n [-2.0376e-04, -1.5974e-04, -1.0028e-04, ..., -8.3998e-05,\n -1.2617e-04, -1.8687e-04],\n [-2.4049e-04, -1.7694e-04, -1.1333e-04, ..., -6.8919e-05,\n -8.1653e-05, -1.2449e-04],\n ...,\n [-2.9420e-04, -2.0622e-04, -1.4142e-04, ..., -6.0307e-05,\n -4.0933e-05, -2.5031e-05],\n [-2.6991e-04, -1.9285e-04, -1.3171e-04, ..., -5.7294e-05,\n -4.2073e-05, 5.1786e-06],\n [-3.0633e-04, -2.5858e-04, -2.0069e-04, ..., -1.2360e-04,\n -1.0689e-04, -2.8471e-05]]]]), 'exp_avg_sq': tensor([[[[6.8514e-06, 7.4309e-06, 7.1820e-06, ..., 7.0949e-06,\n 6.2407e-06, 6.1171e-06],\n [6.6557e-06, 7.2741e-06, 6.8425e-06, ..., 6.4144e-06,\n 5.8510e-06, 5.8694e-06],\n [5.7823e-06, 6.0409e-06, 5.5446e-06, ..., 5.4229e-06,\n 5.2988e-06, 5.5483e-06],\n ...,\n [4.7701e-06, 4.8127e-06, 4.4041e-06, ..., 4.5711e-06,\n 4.6513e-06, 5.3452e-06],\n [4.7788e-06, 4.9318e-06, 4.6646e-06, ..., 4.9889e-06,\n 4.9383e-06, 5.5572e-06],\n [5.0203e-06, 5.2221e-06, 5.0893e-06, ..., 5.3834e-06,\n 5.1713e-06, 5.6545e-06]],\n\n [[3.3532e-06, 3.8017e-06, 3.9334e-06, ..., 4.0687e-06,\n 3.7787e-06, 3.7764e-06],\n [3.1546e-06, 3.4748e-06, 3.4531e-06, ..., 3.4838e-06,\n 3.4738e-06, 3.4917e-06],\n [2.9982e-06, 2.8920e-06, 2.7076e-06, ..., 2.9287e-06,\n 3.1861e-06, 3.1976e-06],\n ...,\n [3.0016e-06, 2.5449e-06, 2.5010e-06, ..., 2.4434e-06,\n 2.6557e-06, 2.7915e-06],\n [3.1857e-06, 2.7698e-06, 2.9342e-06, ..., 2.8771e-06,\n 2.9603e-06, 2.9372e-06],\n [3.6474e-06, 3.1764e-06, 3.4868e-06, ..., 3.4898e-06,\n 3.4827e-06, 3.2483e-06]],\n\n [[5.5234e-06, 6.1439e-06, 6.1688e-06, ..., 6.2107e-06,\n 5.6354e-06, 5.1916e-06],\n [5.0231e-06, 5.4995e-06, 5.3566e-06, ..., 5.0055e-06,\n 4.6520e-06, 4.4816e-06],\n [4.1787e-06, 4.3245e-06, 4.2065e-06, ..., 3.9330e-06,\n 3.7923e-06, 3.8422e-06],\n ...,\n [3.6592e-06, 3.4705e-06, 3.2971e-06, ..., 2.9999e-06,\n 3.0537e-06, 3.3718e-06],\n [3.8793e-06, 3.6605e-06, 3.4728e-06, ..., 3.1910e-06,\n 3.1994e-06, 3.4567e-06],\n [4.1825e-06, 3.9422e-06, 3.7598e-06, ..., 3.4587e-06,\n 3.4024e-06, 3.5512e-06]]],\n\n\n [[[2.1060e-05, 2.1515e-05, 2.1958e-05, ..., 2.0833e-05,\n 2.0180e-05, 1.9621e-05],\n [2.0211e-05, 2.0894e-05, 2.1564e-05, ..., 1.9934e-05,\n 1.9005e-05, 1.8558e-05],\n [1.9623e-05, 2.0153e-05, 2.0930e-05, ..., 1.9632e-05,\n 1.8728e-05, 1.8583e-05],\n ...,\n [2.0658e-05, 2.0323e-05, 2.0097e-05, ..., 1.9950e-05,\n 1.9531e-05, 1.9523e-05],\n [2.0904e-05, 2.0209e-05, 1.9476e-05, ..., 1.9836e-05,\n 1.9989e-05, 2.0197e-05],\n [2.0927e-05, 2.0016e-05, 1.9134e-05, ..., 1.9765e-05,\n 2.0469e-05, 2.0787e-05]],\n\n [[1.9806e-05, 2.0420e-05, 2.0850e-05, ..., 1.9125e-05,\n 1.8247e-05, 1.7600e-05],\n [1.8605e-05, 1.9242e-05, 1.9909e-05, ..., 1.7889e-05,\n 1.6789e-05, 1.6222e-05],\n [1.7474e-05, 1.7894e-05, 1.8712e-05, ..., 1.7553e-05,\n 1.6522e-05, 1.6192e-05],\n ...,\n [1.8381e-05, 1.8146e-05, 1.7922e-05, ..., 1.7333e-05,\n 1.6971e-05, 1.6930e-05],\n [1.8772e-05, 1.8038e-05, 1.7226e-05, ..., 1.7093e-05,\n 1.7362e-05, 1.7746e-05],\n [1.8944e-05, 1.7891e-05, 1.6772e-05, ..., 1.6932e-05,\n 1.7735e-05, 1.8369e-05]],\n\n [[2.0778e-05, 2.1088e-05, 2.2065e-05, ..., 2.1953e-05,\n 2.1694e-05, 2.1033e-05],\n [1.9657e-05, 2.0273e-05, 2.1608e-05, ..., 2.1415e-05,\n 2.0816e-05, 2.0143e-05],\n [1.8934e-05, 1.9505e-05, 2.0799e-05, ..., 2.1274e-05,\n 2.0749e-05, 2.0287e-05],\n ...,\n [2.0712e-05, 2.0578e-05, 2.0730e-05, ..., 2.1416e-05,\n 2.1345e-05, 2.1078e-05],\n [2.1116e-05, 2.0612e-05, 2.0241e-05, ..., 2.1300e-05,\n 2.1982e-05, 2.2328e-05],\n [2.0961e-05, 2.0300e-05, 1.9664e-05, ..., 2.0954e-05,\n 2.2458e-05, 2.3142e-05]]],\n\n\n [[[2.4576e-06, 2.4354e-06, 2.4626e-06, ..., 2.3325e-06,\n 2.3767e-06, 2.4215e-06],\n [2.3291e-06, 2.2407e-06, 2.2130e-06, ..., 2.1208e-06,\n 2.1724e-06, 2.1843e-06],\n [2.2199e-06, 2.0961e-06, 2.0287e-06, ..., 1.9711e-06,\n 2.0718e-06, 2.1279e-06],\n ...,\n [1.9317e-06, 1.8473e-06, 1.7907e-06, ..., 1.7597e-06,\n 1.9034e-06, 2.0611e-06],\n [1.9036e-06, 1.7985e-06, 1.7731e-06, ..., 1.7314e-06,\n 1.8233e-06, 1.9527e-06],\n [1.9677e-06, 1.8173e-06, 1.7848e-06, ..., 1.7056e-06,\n 1.8109e-06, 1.9494e-06]],\n\n [[1.7725e-06, 1.7976e-06, 1.8198e-06, ..., 1.7440e-06,\n 1.7658e-06, 1.7985e-06],\n [1.7406e-06, 1.6906e-06, 1.6336e-06, ..., 1.6113e-06,\n 1.6332e-06, 1.6378e-06],\n [1.6292e-06, 1.5222e-06, 1.4550e-06, ..., 1.4938e-06,\n 1.5594e-06, 1.5798e-06],\n ...,\n [1.3759e-06, 1.2785e-06, 1.2369e-06, ..., 1.2885e-06,\n 1.3978e-06, 1.4915e-06],\n [1.3837e-06, 1.2557e-06, 1.2029e-06, ..., 1.2667e-06,\n 1.3233e-06, 1.3934e-06],\n [1.4490e-06, 1.2901e-06, 1.1973e-06, ..., 1.2044e-06,\n 1.2880e-06, 1.3991e-06]],\n\n [[7.5253e-07, 7.2422e-07, 7.1332e-07, ..., 7.4897e-07,\n 7.8964e-07, 7.9361e-07],\n [6.9149e-07, 6.1204e-07, 5.6660e-07, ..., 6.5234e-07,\n 7.0375e-07, 6.9650e-07],\n [5.8697e-07, 4.7360e-07, 4.0705e-07, ..., 4.8132e-07,\n 5.4064e-07, 5.7886e-07],\n ...,\n [4.1939e-07, 2.6824e-07, 1.8691e-07, ..., 1.5896e-07,\n 2.2641e-07, 3.4360e-07],\n [4.4011e-07, 2.6741e-07, 1.6800e-07, ..., 1.1846e-07,\n 1.6529e-07, 2.7091e-07],\n [5.1605e-07, 3.3349e-07, 2.1768e-07, ..., 1.2302e-07,\n 1.7635e-07, 2.9167e-07]]],\n\n\n ...,\n\n\n [[[4.8970e-06, 4.6383e-06, 4.3649e-06, ..., 4.5108e-06,\n 4.6402e-06, 4.5851e-06],\n [4.6564e-06, 4.5080e-06, 4.1191e-06, ..., 4.0129e-06,\n 4.2030e-06, 4.2801e-06],\n [4.7184e-06, 4.6240e-06, 3.9948e-06, ..., 3.6514e-06,\n 3.9304e-06, 4.1854e-06],\n ...,\n [4.6507e-06, 4.4264e-06, 3.8279e-06, ..., 3.7737e-06,\n 4.2294e-06, 4.5386e-06],\n [4.6755e-06, 4.4538e-06, 4.0063e-06, ..., 4.0611e-06,\n 4.4436e-06, 4.5552e-06],\n [4.6036e-06, 4.4396e-06, 4.1160e-06, ..., 4.2389e-06,\n 4.5243e-06, 4.4518e-06]],\n\n [[4.5792e-06, 4.5059e-06, 4.2044e-06, ..., 4.4206e-06,\n 4.6515e-06, 4.6364e-06],\n [4.8674e-06, 4.9159e-06, 4.3651e-06, ..., 4.1876e-06,\n 4.4283e-06, 4.5240e-06],\n [5.1903e-06, 5.2999e-06, 4.4202e-06, ..., 3.7491e-06,\n 3.8981e-06, 4.0698e-06],\n ...,\n [4.4959e-06, 4.3292e-06, 3.5629e-06, ..., 3.3320e-06,\n 3.6633e-06, 3.9581e-06],\n [4.3850e-06, 4.1922e-06, 3.5985e-06, ..., 3.5573e-06,\n 3.8830e-06, 4.1718e-06],\n [4.2626e-06, 4.1884e-06, 3.7207e-06, ..., 3.7029e-06,\n 3.9274e-06, 4.2268e-06]],\n\n [[4.3500e-06, 4.6015e-06, 4.6289e-06, ..., 4.6747e-06,\n 4.6371e-06, 4.3458e-06],\n [4.8069e-06, 5.0785e-06, 4.8787e-06, ..., 4.6161e-06,\n 4.5898e-06, 4.3844e-06],\n [5.4277e-06, 5.5958e-06, 5.0322e-06, ..., 4.2357e-06,\n 4.1063e-06, 4.0198e-06],\n ...,\n [4.8381e-06, 4.5358e-06, 3.8621e-06, ..., 3.5233e-06,\n 3.6626e-06, 3.7428e-06],\n [4.9621e-06, 4.6522e-06, 4.0966e-06, ..., 3.8744e-06,\n 4.0136e-06, 4.0802e-06],\n [5.0514e-06, 4.9792e-06, 4.5425e-06, ..., 4.2942e-06,\n 4.3670e-06, 4.4646e-06]]],\n\n\n [[[1.5929e-06, 1.0799e-06, 9.3398e-07, ..., 6.4317e-07,\n 6.2298e-07, 7.0361e-07],\n [1.4099e-06, 8.9696e-07, 6.7342e-07, ..., 3.9578e-07,\n 4.2075e-07, 5.3248e-07],\n [1.3065e-06, 7.8558e-07, 4.8668e-07, ..., 2.1865e-07,\n 2.6646e-07, 3.9965e-07],\n ...,\n [1.1219e-06, 6.0751e-07, 2.8701e-07, ..., 8.1084e-08,\n 1.7525e-07, 3.7104e-07],\n [1.1511e-06, 6.3462e-07, 3.2562e-07, ..., 1.4537e-07,\n 2.8399e-07, 5.0563e-07],\n [1.1507e-06, 6.9186e-07, 4.5889e-07, ..., 3.2324e-07,\n 4.5075e-07, 6.2555e-07]],\n\n [[1.8992e-06, 1.5666e-06, 1.5020e-06, ..., 1.1865e-06,\n 1.0811e-06, 1.1052e-06],\n [1.6419e-06, 1.2589e-06, 1.1257e-06, ..., 9.1807e-07,\n 8.8596e-07, 9.5423e-07],\n [1.5616e-06, 1.1301e-06, 9.1966e-07, ..., 7.6586e-07,\n 7.6159e-07, 8.4260e-07],\n ...,\n [1.5294e-06, 1.0665e-06, 8.1514e-07, ..., 6.7859e-07,\n 6.9976e-07, 8.2628e-07],\n [1.4141e-06, 1.0020e-06, 7.7263e-07, ..., 6.4194e-07,\n 7.0002e-07, 8.5676e-07],\n [1.3298e-06, 1.0066e-06, 8.5141e-07, ..., 8.0321e-07,\n 8.6427e-07, 9.7534e-07]],\n\n [[2.5012e-06, 2.1980e-06, 2.0617e-06, ..., 1.8397e-06,\n 1.8116e-06, 1.8508e-06],\n [2.3940e-06, 2.0943e-06, 1.9004e-06, ..., 1.6971e-06,\n 1.7000e-06, 1.7551e-06],\n [2.3656e-06, 2.0776e-06, 1.8282e-06, ..., 1.5619e-06,\n 1.5581e-06, 1.6224e-06],\n ...,\n [2.2882e-06, 1.9779e-06, 1.7677e-06, ..., 1.5783e-06,\n 1.5870e-06, 1.6956e-06],\n [2.3355e-06, 2.0642e-06, 1.9085e-06, ..., 1.7924e-06,\n 1.8473e-06, 1.9694e-06],\n [2.4290e-06, 2.2184e-06, 2.1628e-06, ..., 2.0806e-06,\n 2.1156e-06, 2.1888e-06]]],\n\n\n [[[2.7175e-05, 2.6388e-05, 2.5582e-05, ..., 2.4319e-05,\n 2.4106e-05, 2.5298e-05],\n [2.6271e-05, 2.4835e-05, 2.3347e-05, ..., 2.0959e-05,\n 2.1619e-05, 2.3150e-05],\n [2.6992e-05, 2.4794e-05, 2.2346e-05, ..., 1.9107e-05,\n 2.0847e-05, 2.3104e-05],\n ...,\n [2.9118e-05, 2.6216e-05, 2.3409e-05, ..., 2.4199e-05,\n 2.5351e-05, 2.5484e-05],\n [3.1004e-05, 2.7953e-05, 2.6223e-05, ..., 2.8066e-05,\n 2.7535e-05, 2.6836e-05],\n [3.5755e-05, 3.2781e-05, 3.1689e-05, ..., 3.1630e-05,\n 2.9784e-05, 2.9452e-05]],\n\n [[3.1572e-05, 2.8043e-05, 2.4943e-05, ..., 2.3759e-05,\n 2.5882e-05, 2.9070e-05],\n [3.2764e-05, 2.8594e-05, 2.4419e-05, ..., 2.0710e-05,\n 2.2912e-05, 2.5710e-05],\n [3.4312e-05, 2.9898e-05, 2.5135e-05, ..., 2.0684e-05,\n 2.4025e-05, 2.7336e-05],\n ...,\n [4.0258e-05, 3.5756e-05, 3.2691e-05, ..., 2.9015e-05,\n 3.0137e-05, 3.0254e-05],\n [4.7026e-05, 4.2670e-05, 4.1679e-05, ..., 3.5314e-05,\n 3.1964e-05, 2.8768e-05],\n [5.7189e-05, 5.2967e-05, 5.2858e-05, ..., 4.2000e-05,\n 3.4730e-05, 2.8770e-05]],\n\n [[3.5304e-05, 3.2798e-05, 2.9903e-05, ..., 3.1082e-05,\n 3.4815e-05, 3.9856e-05],\n [3.8799e-05, 3.5743e-05, 3.1851e-05, ..., 2.8995e-05,\n 3.1226e-05, 3.4243e-05],\n [4.3522e-05, 4.0464e-05, 3.6120e-05, ..., 3.1101e-05,\n 3.3238e-05, 3.6173e-05],\n ...,\n [5.4020e-05, 5.1400e-05, 4.9979e-05, ..., 4.3231e-05,\n 4.3645e-05, 4.3811e-05],\n [6.1947e-05, 5.9254e-05, 5.9691e-05, ..., 5.0922e-05,\n 4.7405e-05, 4.3543e-05],\n [7.1741e-05, 6.9527e-05, 7.0640e-05, ..., 5.7818e-05,\n 5.0205e-05, 4.2463e-05]]]])}, 1: {'step': 7160, 'exp_avg': tensor([-1.2636e-05, -4.6544e-04, -2.0839e-04, 3.0394e-04, 1.3540e-04,\n -4.6368e-04, -1.2547e-05, 2.6321e-04, 3.5152e-04, 6.3207e-05,\n 2.5633e-05, 3.4064e-04, 7.2038e-04, 0.0000e+00, 1.4004e-04,\n 1.4986e-04, 5.5561e-05, -6.6516e-04, -6.2187e-04, -5.1399e-04,\n 2.1506e-04, 7.5732e-04, -6.3875e-05, 8.7653e-04, 2.4461e-04,\n -1.7128e-04, 7.3959e-05, -4.0972e-04, 1.0493e-04, 4.6057e-04,\n 8.9130e-04, -3.2004e-05, 2.0748e-04, -5.9624e-04, 5.9728e-05,\n 6.0239e-04, 2.2285e-05, -8.9625e-04, -8.6406e-05, 5.6436e-04,\n 3.4789e-04, -6.0082e-04, 1.3047e-04, -7.0377e-04, -1.8397e-05,\n -4.3045e-04, -2.7691e-04, 2.8897e-04, -8.3856e-05, 3.4687e-04,\n -3.5828e-05, -2.5516e-04, -1.0149e-04, -4.9289e-04, -6.5219e-04,\n 2.5097e-04, 2.5930e-04, 7.9581e-05, -1.7439e-06, -9.6294e-05,\n -1.8696e-04, -3.0377e-04, -8.0853e-05, -2.9640e-04]), 'exp_avg_sq': tensor([5.5518e-05, 7.8460e-04, 7.5084e-06, 6.3105e-05, 8.5783e-05, 7.8133e-05,\n 5.0995e-05, 4.5580e-05, 6.9586e-05, 6.5881e-05, 5.6743e-05, 1.1490e-05,\n 6.8817e-05, 0.0000e+00, 5.8163e-05, 8.9226e-05, 5.3945e-05, 1.1204e-04,\n 3.4813e-05, 1.8864e-04, 2.5456e-05, 1.0559e-04, 4.1072e-05, 1.0272e-04,\n 4.0978e-05, 4.5757e-05, 4.9245e-05, 6.9312e-05, 7.5440e-06, 8.2170e-05,\n 5.5611e-05, 1.5392e-06, 9.2479e-05, 2.6320e-05, 2.3689e-04, 2.2436e-04,\n 8.7976e-05, 1.0225e-04, 6.8962e-05, 1.0156e-04, 5.0407e-05, 5.2171e-05,\n 9.2091e-06, 1.1153e-04, 7.3720e-06, 7.3165e-05, 4.3348e-05, 8.2960e-05,\n 1.3213e-05, 1.2212e-04, 5.2216e-05, 5.0892e-05, 8.6716e-06, 5.9128e-05,\n 9.3892e-05, 7.6506e-05, 2.0922e-04, 2.4885e-06, 7.0373e-06, 7.0309e-06,\n 4.3232e-05, 4.0963e-05, 1.1380e-04, 7.1122e-05])}, 2: {'step': 7160, 'exp_avg': tensor([ 8.5738e-06, -6.1719e-06, -3.3141e-04, -1.8526e-04, 4.0215e-05,\n 8.9641e-05, -7.4095e-06, 9.2849e-07, -8.0273e-05, -2.5556e-04,\n 1.0098e-04, 2.2770e-04, -9.7662e-05, 0.0000e+00, 2.8524e-06,\n -1.2548e-05, -1.6770e-06, 8.0467e-07, 5.7868e-04, 1.5087e-04,\n -1.9879e-05, -4.7649e-06, 3.2591e-07, 3.7746e-10, -5.5259e-06,\n -9.6771e-06, 3.9980e-06, 4.6061e-05, -1.0057e-04, -3.6358e-04,\n 1.2336e-04, -1.2410e-05, -9.4651e-05, 3.4781e-04, 2.4554e-05,\n 5.2712e-05, -3.7894e-04, -9.8722e-05, 3.4296e-05, -1.5977e-04,\n -1.9315e-05, -4.8024e-04, -7.8721e-06, 1.1934e-04, -2.3296e-04,\n 1.1449e-05, -7.2126e-07, 1.2110e-04, -6.0452e-05, -8.6838e-06,\n -2.3581e-04, -1.8851e-04, -1.5328e-04, 1.6661e-06, 8.7271e-05,\n -2.1789e-05, -1.6660e-05, 1.0637e-04, -8.8407e-05, -1.5426e-04,\n 3.2686e-04, 6.8359e-06, 1.3523e-05, -7.4790e-06]), 'exp_avg_sq': tensor([1.7988e-06, 1.9869e-06, 7.9731e-06, 1.5223e-05, 3.1121e-07, 4.6182e-06,\n 5.3755e-07, 6.9455e-09, 4.5520e-06, 3.2383e-06, 1.9141e-06, 1.0019e-05,\n 1.3486e-06, 0.0000e+00, 1.4750e-09, 4.6221e-07, 4.5672e-09, 1.1158e-07,\n 4.0304e-06, 3.5524e-05, 3.0461e-08, 6.2834e-07, 5.8397e-08, 8.9987e-16,\n 1.6272e-07, 4.1979e-07, 1.3412e-06, 1.3597e-06, 9.2440e-07, 2.2439e-05,\n 2.3023e-05, 1.4184e-06, 6.9057e-07, 3.2640e-06, 1.0476e-05, 2.5704e-06,\n 4.1008e-06, 1.5119e-06, 2.1729e-07, 3.4800e-06, 9.7638e-08, 3.0686e-06,\n 3.7570e-06, 1.3495e-06, 3.8793e-06, 3.0602e-07, 2.4254e-08, 1.8205e-06,\n 7.6794e-06, 2.6631e-07, 1.5562e-06, 4.1464e-06, 5.6252e-06, 8.1550e-07,\n 2.1024e-06, 1.5050e-07, 1.4477e-06, 1.7698e-06, 4.6962e-06, 3.2281e-06,\n 1.4196e-06, 1.6975e-06, 8.2445e-08, 1.6900e-06])}, 3: {'step': 7160, 'exp_avg': tensor([[[[ 4.5531e-05]],\n\n [[-1.2283e-04]],\n\n [[ 5.6167e-05]],\n\n ...,\n\n [[ 8.2284e-06]],\n\n [[-3.4986e-05]],\n\n [[-1.8834e-05]]],\n\n\n [[[ 1.7539e-04]],\n\n [[-3.4002e-04]],\n\n [[ 1.8800e-04]],\n\n ...,\n\n [[ 3.3386e-05]],\n\n [[ 1.0105e-04]],\n\n [[ 3.7509e-05]]],\n\n\n [[[ 7.9702e-06]],\n\n [[-7.5717e-06]],\n\n [[-1.2330e-05]],\n\n ...,\n\n [[-4.6394e-05]],\n\n [[-6.2377e-05]],\n\n [[-1.2913e-05]]],\n\n\n ...,\n\n\n [[[ 8.7540e-05]],\n\n [[-2.3392e-05]],\n\n [[ 1.3818e-05]],\n\n ...,\n\n [[ 5.8085e-05]],\n\n [[ 7.8073e-05]],\n\n [[ 4.8906e-05]]],\n\n\n [[[ 5.7197e-05]],\n\n [[-2.7106e-05]],\n\n [[ 6.3861e-05]],\n\n ...,\n\n [[ 6.9501e-05]],\n\n [[ 4.3015e-05]],\n\n [[ 1.8786e-05]]],\n\n\n [[[-2.6558e-05]],\n\n [[ 8.0255e-05]],\n\n [[ 1.9261e-05]],\n\n ...,\n\n [[-4.9252e-05]],\n\n [[-3.5068e-05]],\n\n [[-6.7556e-07]]]]), 'exp_avg_sq': tensor([[[[2.3557e-06]],\n\n [[5.1954e-06]],\n\n [[1.0284e-06]],\n\n ...,\n\n [[2.1067e-06]],\n\n [[1.5620e-06]],\n\n [[9.5231e-07]]],\n\n\n [[[1.4578e-06]],\n\n [[6.9968e-06]],\n\n [[2.3032e-06]],\n\n ...,\n\n [[1.3838e-06]],\n\n [[7.5846e-06]],\n\n [[1.1373e-06]]],\n\n\n [[[5.1976e-07]],\n\n [[5.3362e-07]],\n\n [[2.8389e-07]],\n\n ...,\n\n [[4.4139e-07]],\n\n [[5.3951e-07]],\n\n [[3.0276e-07]]],\n\n\n ...,\n\n\n [[[5.5700e-07]],\n\n [[3.7279e-07]],\n\n [[7.4550e-08]],\n\n ...,\n\n [[9.6248e-07]],\n\n [[5.1522e-07]],\n\n [[2.9246e-07]]],\n\n\n [[[7.6293e-07]],\n\n [[4.6538e-06]],\n\n [[1.2184e-06]],\n\n ...,\n\n [[7.1304e-07]],\n\n [[2.7296e-06]],\n\n [[4.4031e-07]]],\n\n\n [[[7.5446e-07]],\n\n [[1.4452e-06]],\n\n [[3.5229e-07]],\n\n ...,\n\n [[1.0359e-06]],\n\n [[6.5637e-07]],\n\n [[4.0996e-07]]]])}, 4: {'step': 7160, 'exp_avg': tensor([-5.3531e-04, 1.4568e-05, 3.0897e-04, -2.5479e-04, 4.8271e-04,\n 2.0656e-04, -1.6641e-04, 0.0000e+00, 3.2135e-04, 2.0818e-04,\n 1.5452e-04, -2.7499e-04, -2.2402e-04, -1.1631e-06, -2.0104e-04,\n 8.3095e-05, -3.8252e-06, -1.8624e-04, -4.8503e-05, 1.1128e-04,\n -6.8096e-05, -3.6143e-05, -1.3839e-04, 0.0000e+00, -2.3115e-04,\n -1.8224e-04, 1.4728e-04, 0.0000e+00, 8.1481e-05, 4.2416e-04,\n 7.0878e-05, 3.0057e-04, 9.3647e-05, 9.0846e-05, -6.0170e-05,\n -7.4511e-06, 3.3158e-04, -1.0165e-04, -7.1230e-06, 4.5537e-05,\n 1.4785e-04, -9.7205e-05, 2.5287e-04, 2.0752e-04, -4.3450e-05,\n -1.2689e-04, 1.0880e-05, 2.2856e-04, -1.1085e-04, 1.1812e-05,\n 3.5865e-04, -1.8487e-04, -5.6449e-05, 4.6126e-06, 2.0748e-04,\n 1.1955e-04, 0.0000e+00, -1.9154e-04, 0.0000e+00, -1.3185e-04,\n 2.5241e-05, -2.7195e-05, -9.6055e-06, -1.9997e-04]), 'exp_avg_sq': tensor([4.9386e-05, 5.4872e-06, 7.4912e-06, 3.7141e-06, 2.3310e-05, 5.5298e-06,\n 1.0169e-05, 0.0000e+00, 1.0553e-05, 3.1491e-06, 4.6361e-06, 3.1425e-05,\n 3.9526e-06, 7.5210e-06, 7.5587e-06, 6.8735e-06, 6.7255e-06, 1.0774e-05,\n 2.6237e-06, 8.5733e-06, 2.4976e-06, 1.0944e-05, 6.3878e-06, 0.0000e+00,\n 6.1063e-06, 6.4809e-06, 7.8441e-06, 0.0000e+00, 1.6915e-06, 1.1064e-05,\n 2.3276e-05, 5.4805e-06, 4.1266e-06, 2.6565e-06, 1.3398e-05, 4.6188e-06,\n 3.3342e-05, 2.2038e-06, 2.5531e-06, 1.0711e-05, 7.2639e-06, 2.6447e-06,\n 1.0954e-05, 9.6558e-06, 3.7465e-06, 3.2060e-06, 1.4805e-06, 1.5122e-05,\n 2.3793e-06, 4.5833e-06, 4.0185e-06, 8.0606e-06, 5.9133e-06, 1.0795e-05,\n 8.1683e-06, 5.0806e-06, 0.0000e+00, 4.4321e-06, 0.0000e+00, 2.8730e-05,\n 3.8722e-06, 1.4335e-05, 4.2278e-06, 2.4643e-05])}, 5: {'step': 7160, 'exp_avg': tensor([ 1.8554e-04, -7.7588e-05, 2.0666e-04, -3.9108e-05, -6.5570e-06,\n 1.9043e-04, 2.7706e-05, 0.0000e+00, 1.3663e-04, 1.8396e-04,\n -1.5239e-04, 7.6596e-05, -1.1421e-04, -1.0934e-05, -2.1489e-04,\n 7.7375e-05, -7.9962e-06, 5.7417e-05, -3.9671e-05, 3.2323e-05,\n -1.5670e-04, -1.4729e-04, -1.7561e-04, 0.0000e+00, 1.8394e-06,\n 1.2558e-04, 1.6870e-06, 0.0000e+00, 1.0142e-04, 1.7143e-04,\n -1.1674e-04, 8.7627e-05, 4.9997e-05, -3.8184e-05, -1.9698e-04,\n -4.6567e-05, -4.6055e-05, -4.3649e-04, -4.0310e-06, -6.1852e-05,\n 2.2658e-04, -1.3092e-04, -1.2389e-04, 2.7729e-05, 1.5225e-04,\n -1.3515e-04, -2.5497e-05, -1.1783e-04, -1.6597e-04, 8.4567e-05,\n 2.5855e-04, -1.6213e-04, -3.2493e-05, 6.8970e-05, 1.2299e-05,\n 9.8881e-05, 0.0000e+00, 4.9474e-05, 0.0000e+00, 3.5802e-05,\n -2.2060e-04, -2.6292e-05, -2.1889e-04, 1.5286e-05]), 'exp_avg_sq': tensor([2.1750e-06, 8.1212e-06, 3.0542e-06, 6.4598e-06, 2.3526e-06, 5.6060e-06,\n 2.8403e-06, 0.0000e+00, 2.4884e-06, 3.1905e-06, 8.6326e-06, 3.0711e-06,\n 6.3658e-06, 2.4427e-06, 3.6318e-06, 1.0708e-06, 1.6474e-05, 8.6288e-07,\n 5.7065e-06, 1.2125e-05, 5.3717e-06, 1.9784e-05, 9.4621e-06, 0.0000e+00,\n 9.6870e-06, 5.6504e-06, 1.5047e-05, 0.0000e+00, 4.9051e-06, 4.6887e-06,\n 5.7553e-06, 3.4153e-06, 2.6901e-06, 9.7796e-07, 9.5846e-06, 8.3743e-06,\n 4.0951e-06, 1.2405e-05, 5.8069e-06, 3.2953e-06, 1.8176e-05, 2.9623e-06,\n 3.9740e-06, 2.6655e-06, 1.0275e-05, 7.0157e-06, 2.3851e-06, 6.8445e-07,\n 5.4474e-06, 7.8079e-06, 6.4818e-06, 1.3537e-05, 3.0893e-06, 4.4168e-06,\n 2.2186e-06, 4.6779e-06, 0.0000e+00, 6.0448e-06, 0.0000e+00, 1.1332e-06,\n 1.1670e-05, 4.3353e-06, 1.6743e-05, 2.4020e-06])}, 6: {'step': 7160, 'exp_avg': tensor([[[[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n ...,\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]]],\n\n\n [[[-1.0676e-05, -9.3483e-06, -4.6568e-06],\n [-1.3265e-05, -1.1870e-05, -1.2497e-05],\n [ 1.0947e-05, 7.8370e-06, 4.4289e-07]],\n\n [[-6.5276e-06, 1.3195e-06, -3.8606e-06],\n [-1.7772e-05, -1.3752e-05, -3.9039e-06],\n [-2.2533e-05, -2.7193e-06, -1.4478e-05]],\n\n [[-6.0614e-06, 6.6788e-07, 7.0747e-06],\n [ 2.9413e-06, 7.3192e-06, 2.1440e-05],\n [ 1.8497e-05, 1.0365e-05, 2.0566e-05]],\n\n ...,\n\n [[ 3.0393e-06, 3.5639e-07, 6.5956e-06],\n [ 7.6724e-06, 6.1448e-06, 9.9467e-06],\n [ 7.4712e-06, 7.2854e-06, 1.1749e-05]],\n\n [[-2.5547e-05, -1.5195e-05, -3.1812e-05],\n [-1.7483e-05, -2.6399e-05, -3.0530e-05],\n [-2.5104e-05, -5.9192e-06, -2.5870e-05]],\n\n [[ 4.7966e-05, 1.8326e-05, 5.9652e-06],\n [ 5.1468e-05, 1.3724e-05, 1.2317e-05],\n [ 2.0172e-05, -1.6777e-05, -1.7720e-05]]],\n\n\n [[[ 5.3711e-05, 6.1609e-05, 9.5580e-06],\n [ 6.8444e-05, 3.4639e-05, -3.1508e-05],\n [ 5.5160e-05, 5.0341e-06, -4.4681e-05]],\n\n [[ 2.1535e-06, 1.8711e-05, -3.6922e-06],\n [ 2.2913e-06, 2.5163e-05, -1.1297e-07],\n [-2.2888e-05, 1.5487e-07, -3.2181e-05]],\n\n [[-2.8518e-05, -2.5261e-05, -3.5455e-05],\n [-4.3200e-05, -2.5706e-05, -2.1157e-05],\n [-2.9132e-05, -2.5390e-05, -1.3371e-05]],\n\n ...,\n\n [[ 1.5883e-05, 2.7870e-06, -2.0654e-05],\n [ 7.8104e-06, -2.0941e-05, -1.3279e-05],\n [ 2.1002e-05, -5.4516e-06, 4.0327e-06]],\n\n [[ 2.1169e-05, 3.4636e-05, 2.3798e-05],\n [ 2.0018e-05, 2.2351e-05, 5.0191e-06],\n [ 1.0275e-05, 2.1112e-05, 1.8125e-05]],\n\n [[-9.9551e-05, -8.3689e-05, -1.9993e-05],\n [-7.4286e-05, -2.5585e-05, 4.2560e-05],\n [-3.8444e-05, 3.2745e-05, 8.0617e-05]]],\n\n\n ...,\n\n\n [[[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n ...,\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00],\n [ 0.0000e+00, 0.0000e+00, 0.0000e+00]]],\n\n\n [[[ 4.8082e-05, 4.8347e-05, 4.3672e-05],\n [ 4.3841e-05, 3.2224e-05, 3.6060e-05],\n [ 5.8128e-05, 3.3972e-05, 3.0467e-05]],\n\n [[-9.5324e-06, -2.6272e-06, 3.7244e-06],\n [ 1.8902e-06, 3.4235e-06, 1.8271e-05],\n [-1.8351e-05, -1.5856e-05, 6.4881e-07]],\n\n [[ 8.2688e-06, 1.3539e-06, -6.9253e-06],\n [-3.1738e-07, -5.9370e-06, -1.3621e-05],\n [-2.0747e-06, -5.5691e-06, -1.0646e-05]],\n\n ...,\n\n [[-6.0687e-07, 1.0314e-05, 7.0481e-06],\n [ 3.0444e-06, 5.6490e-07, 6.2609e-07],\n [-7.0638e-06, -2.1361e-06, 1.4603e-06]],\n\n [[-2.1455e-05, -1.7523e-05, -4.2912e-06],\n [-1.2566e-05, -1.0980e-05, -4.1285e-06],\n [-2.6861e-05, -3.0111e-05, -1.8032e-05]],\n\n [[-3.8833e-05, -4.3774e-05, -3.0665e-05],\n [-4.7931e-05, -4.4552e-05, -3.2233e-05],\n [-5.0309e-05, -4.0627e-05, -2.8677e-05]]],\n\n\n [[[ 6.6824e-05, 4.2390e-05, -2.8496e-06],\n [ 7.2592e-05, 6.4876e-05, 3.8617e-05],\n [ 4.5947e-05, 3.6782e-05, 1.8702e-05]],\n\n [[-2.9569e-05, -3.1215e-05, -4.7957e-05],\n [-1.3231e-05, -2.4940e-05, -4.3396e-05],\n [-1.7817e-05, -2.0943e-05, -2.3152e-05]],\n\n [[-1.8930e-05, -1.5246e-05, -2.3250e-05],\n [-1.5970e-05, 4.1379e-06, -2.7294e-05],\n [-3.4218e-05, -7.8447e-06, -2.6572e-05]],\n\n ...,\n\n [[ 7.1428e-06, -3.9668e-06, -5.0625e-06],\n [-2.6365e-06, 4.0818e-06, 5.0375e-06],\n [ 2.7398e-06, 1.3159e-05, 1.0800e-05]],\n\n [[ 1.1265e-05, 4.1003e-06, -4.4481e-06],\n [ 1.6419e-05, 6.2987e-06, 1.8585e-06],\n [ 2.5943e-05, 2.4275e-05, 7.1874e-06]],\n\n [[-1.3673e-04, -1.0294e-04, -1.0633e-04],\n [-6.2914e-05, -4.3259e-05, -5.7844e-05],\n [-5.4895e-05, -3.2131e-05, -6.6003e-05]]]]), 'exp_avg_sq': tensor([[[[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n ...,\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]]],\n\n\n [[[2.2067e-07, 2.0767e-07, 1.9484e-07],\n [1.8268e-07, 1.5066e-07, 1.6006e-07],\n [1.7313e-07, 1.5472e-07, 1.9668e-07]],\n\n [[3.9476e-08, 4.0662e-08, 3.8639e-08],\n [3.8693e-08, 2.9253e-08, 3.4593e-08],\n [4.6923e-08, 3.5896e-08, 3.1842e-08]],\n\n [[1.6512e-08, 1.4996e-08, 2.3103e-08],\n [1.5797e-08, 1.8115e-08, 2.5572e-08],\n [1.6651e-08, 2.7246e-08, 2.8506e-08]],\n\n ...,\n\n [[2.5981e-08, 2.1124e-08, 2.0496e-08],\n [2.4855e-08, 1.8467e-08, 1.6972e-08],\n [2.3615e-08, 1.9745e-08, 1.9420e-08]],\n\n [[7.7519e-08, 4.6944e-08, 4.2618e-08],\n [5.5260e-08, 4.9541e-08, 3.8345e-08],\n [4.9471e-08, 4.4030e-08, 4.0658e-08]],\n\n [[4.6890e-07, 3.1292e-07, 3.5794e-07],\n [3.4718e-07, 1.9217e-07, 2.3291e-07],\n [3.2137e-07, 1.9639e-07, 2.9888e-07]]],\n\n\n [[[2.1053e-07, 1.3494e-07, 1.7114e-07],\n [1.2629e-07, 6.5931e-08, 1.2072e-07],\n [2.0153e-07, 1.0946e-07, 1.5677e-07]],\n\n [[7.9878e-08, 6.2604e-08, 5.7851e-08],\n [6.4747e-08, 5.7718e-08, 5.4444e-08],\n [7.0977e-08, 5.5911e-08, 5.9455e-08]],\n\n [[7.1866e-08, 6.1437e-08, 7.2846e-08],\n [6.1162e-08, 6.8028e-08, 9.2795e-08],\n [5.9892e-08, 6.9104e-08, 1.1061e-07]],\n\n ...,\n\n [[8.4697e-08, 1.0215e-07, 1.0049e-07],\n [1.2472e-07, 1.1801e-07, 9.7585e-08],\n [1.6238e-07, 1.1642e-07, 9.9205e-08]],\n\n [[6.9547e-08, 6.2435e-08, 7.5950e-08],\n [6.6737e-08, 8.1112e-08, 9.2152e-08],\n [6.0272e-08, 8.9767e-08, 7.5191e-08]],\n\n [[1.9601e-07, 1.4757e-07, 2.0487e-07],\n [1.2280e-07, 6.6253e-08, 1.3197e-07],\n [2.4374e-07, 1.2816e-07, 1.6329e-07]]],\n\n\n ...,\n\n\n [[[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n ...,\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]],\n\n [[0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00],\n [0.0000e+00, 0.0000e+00, 0.0000e+00]]],\n\n\n [[[3.8811e-07, 4.2999e-07, 2.9707e-07],\n [3.6487e-07, 3.8526e-07, 3.2923e-07],\n [2.8244e-07, 2.8500e-07, 3.1970e-07]],\n\n [[3.6006e-08, 2.8203e-08, 2.4498e-08],\n [2.3227e-08, 2.3060e-08, 2.0782e-08],\n [2.3215e-08, 2.1924e-08, 2.1020e-08]],\n\n [[1.6301e-08, 1.5613e-08, 5.1702e-08],\n [8.9292e-09, 1.9526e-08, 1.0265e-07],\n [6.4625e-09, 1.4416e-08, 6.8789e-08]],\n\n ...,\n\n [[4.9086e-08, 4.8407e-08, 3.0189e-08],\n [3.4385e-08, 3.0946e-08, 1.4672e-08],\n [2.7758e-08, 2.0580e-08, 1.1273e-08]],\n\n [[3.7224e-08, 6.4280e-08, 7.9858e-08],\n [2.9874e-08, 3.0239e-08, 4.3949e-08],\n [2.5240e-08, 2.6558e-08, 3.0880e-08]],\n\n [[4.5826e-07, 5.5747e-07, 4.3503e-07],\n [3.8329e-07, 4.5173e-07, 3.5701e-07],\n [3.1628e-07, 3.2442e-07, 3.2376e-07]]],\n\n\n [[[9.1275e-07, 8.2082e-07, 8.6020e-07],\n [7.7298e-07, 6.9725e-07, 6.5090e-07],\n [9.3497e-07, 8.2601e-07, 7.4856e-07]],\n\n [[3.5979e-07, 3.0571e-07, 3.1245e-07],\n [2.9349e-07, 2.6617e-07, 2.4217e-07],\n [2.5993e-07, 2.3148e-07, 2.1485e-07]],\n\n [[1.2884e-07, 1.4515e-07, 1.1338e-07],\n [1.2631e-07, 1.0574e-07, 1.0093e-07],\n [1.2866e-07, 1.3711e-07, 1.3838e-07]],\n\n ...,\n\n [[3.8975e-07, 4.4314e-07, 4.7705e-07],\n [3.9152e-07, 4.0622e-07, 4.4764e-07],\n [4.5479e-07, 4.4435e-07, 4.4309e-07]],\n\n [[2.7886e-07, 2.9229e-07, 3.1253e-07],\n [2.6395e-07, 2.7493e-07, 3.1427e-07],\n [2.6059e-07, 2.7968e-07, 3.3017e-07]],\n\n [[1.0461e-06, 1.0419e-06, 1.2296e-06],\n [6.9209e-07, 6.6742e-07, 6.4786e-07],\n [7.1027e-07, 7.0353e-07, 6.3473e-07]]]])}, 7: {'step': 7160, 'exp_avg': tensor([ 0.0000e+00, 7.3529e-05, -1.2866e-04, 2.3839e-04, 2.7887e-04,\n -2.2097e-04, -4.6529e-04, -2.4499e-04, 2.0653e-04, -1.2892e-04,\n -1.7699e-05, 1.5559e-05, -3.2155e-04, 4.4454e-06, -8.1936e-05,\n 5.4524e-04, -1.0974e-04, -2.8265e-05, 2.4667e-04, 0.0000e+00,\n 1.5066e-04, 2.5412e-04, -1.8637e-04, 4.4786e-04, 4.6869e-05,\n 3.1607e-05, -2.5867e-04, -1.8919e-04, -8.2384e-05, -3.0135e-05,\n -4.6138e-06, 2.6588e-04, -1.0366e-04, -4.0358e-05, -7.8682e-05,\n -6.6448e-05, -7.1672e-05, 3.2227e-05, 2.0733e-04, -3.2351e-05,\n 3.8341e-04, -2.9784e-04, 2.9182e-05, -2.5938e-04, 1.4776e-05,\n 1.9417e-04, 2.4708e-04, 1.2360e-04, -3.4160e-04, -7.7870e-05,\n 2.0133e-05, 2.8417e-04, 1.7230e-04, -1.2389e-04, 7.9603e-05,\n 8.2448e-05, 1.2873e-04, 1.8033e-04, -3.4133e-05, 5.6052e-45,\n -9.8699e-05, 0.0000e+00, -1.0806e-05, -3.9901e-04]), 'exp_avg_sq': tensor([0.0000e+00, 2.5884e-06, 7.4478e-06, 1.7846e-05, 2.0651e-05, 1.3292e-05,\n 1.9728e-05, 1.8263e-05, 5.7680e-06, 1.3726e-06, 7.9742e-07, 6.9166e-05,\n 1.5218e-05, 1.7063e-06, 9.4162e-07, 2.3882e-05, 5.5616e-05, 1.4613e-06,\n 1.4804e-05, 0.0000e+00, 1.2460e-05, 1.5418e-05, 4.1743e-06, 2.2399e-05,\n 6.7142e-06, 2.1900e-05, 1.4989e-05, 2.2010e-06, 3.1371e-06, 5.3004e-06,\n 1.0700e-05, 1.7460e-05, 2.1243e-05, 3.7446e-05, 2.7907e-06, 2.0378e-06,\n 6.4184e-06, 1.3570e-05, 9.7448e-06, 1.3878e-05, 2.0709e-05, 1.6467e-05,\n 2.2365e-05, 1.1697e-05, 4.8688e-06, 6.2518e-06, 3.6230e-05, 1.2281e-05,\n 5.3129e-05, 2.9442e-06, 8.3775e-06, 9.0905e-06, 1.3125e-05, 8.2334e-06,\n 1.2227e-05, 1.7923e-06, 1.0550e-05, 3.7612e-06, 1.8458e-06, 3.0490e-16,\n 1.2075e-06, 0.0000e+00, 2.9174e-06, 1.0071e-05])}, 8: {'step': 7160, 'exp_avg': tensor([ 0.0000e+00, -1.0869e-04, 8.5503e-05, -1.2631e-04, 2.3837e-05,\n 1.5808e-04, 1.0014e-05, -5.4838e-05, 1.5957e-04, -6.2068e-05,\n 8.2900e-06, 1.8020e-05, 1.0836e-04, 8.4368e-05, -7.3073e-05,\n -7.0216e-06, 2.6208e-07, 2.4387e-05, -1.1523e-04, 0.0000e+00,\n -9.5206e-05, 1.2039e-04, -1.0574e-04, -8.4507e-05, -7.5145e-05,\n 1.4838e-04, 6.9476e-06, -1.6479e-04, -8.1497e-05, -1.8194e-04,\n -5.1838e-05, -1.2237e-05, 1.3590e-05, -6.3695e-06, -9.1218e-06,\n -2.1963e-05, -4.0665e-06, 7.2860e-05, -1.7124e-04, -2.8344e-04,\n -3.4458e-04, 4.1107e-04, 1.4529e-05, 2.7633e-05, 9.4471e-05,\n 4.6344e-05, -7.2124e-06, 2.2076e-04, 5.8950e-05, -9.9017e-05,\n -2.5333e-05, -1.8993e-04, 3.8329e-06, 6.6000e-05, 1.0935e-04,\n -4.1643e-05, -2.6432e-05, 1.1195e-04, -1.2430e-05, 5.6052e-45,\n -8.9549e-05, 0.0000e+00, 1.7855e-05, 2.9504e-05]), 'exp_avg_sq': tensor([0.0000e+00, 3.3942e-06, 1.2648e-06, 5.5823e-06, 1.0036e-07, 7.7593e-07,\n 9.4285e-08, 2.3794e-06, 2.8692e-06, 1.0447e-06, 6.2811e-07, 1.3554e-06,\n 7.0506e-07, 2.0100e-06, 4.3167e-07, 2.4033e-07, 2.8756e-07, 1.1575e-06,\n 5.1008e-06, 0.0000e+00, 1.4648e-05, 6.2717e-06, 3.6374e-06, 3.7718e-07,\n 1.5162e-06, 4.4878e-06, 2.7152e-06, 3.4687e-06, 2.0720e-06, 5.0963e-06,\n 3.5845e-06, 6.0488e-08, 8.2318e-07, 2.0499e-06, 2.6215e-06, 1.0712e-06,\n 9.8789e-09, 2.3952e-06, 5.5849e-06, 8.3597e-06, 2.2387e-06, 1.1660e-05,\n 6.8136e-06, 4.7162e-07, 3.4483e-06, 4.1956e-06, 2.6210e-08, 9.0317e-07,\n 3.9595e-07, 3.2785e-06, 4.9335e-08, 7.3307e-06, 5.6462e-06, 1.1586e-06,\n 7.5604e-06, 1.0137e-06, 1.1735e-06, 2.1323e-06, 9.7937e-07, 1.8498e-17,\n 1.4514e-06, 0.0000e+00, 2.4362e-06, 1.0287e-05])}, 9: {'step': 7160, 'exp_avg': tensor([[[[ 0.0000e+00]],\n\n [[-1.8965e-05]],\n\n [[-7.7865e-05]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-9.4553e-06]],\n\n [[-8.7087e-05]]],\n\n\n [[[ 0.0000e+00]],\n\n [[-2.4557e-06]],\n\n [[ 1.3654e-05]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-1.4125e-06]],\n\n [[ 2.8474e-06]]],\n\n\n [[[ 0.0000e+00]],\n\n [[-4.8385e-06]],\n\n [[ 6.9770e-05]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-6.1298e-07]],\n\n [[-7.3574e-06]]],\n\n\n ...,\n\n\n [[[ 0.0000e+00]],\n\n [[ 1.0021e-06]],\n\n [[-6.6898e-07]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[ 6.7967e-07]],\n\n [[ 9.4300e-07]]],\n\n\n [[[ 0.0000e+00]],\n\n [[ 4.2955e-05]],\n\n [[-5.3301e-05]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[ 6.4565e-05]],\n\n [[-8.1140e-05]]],\n\n\n [[[ 0.0000e+00]],\n\n [[-3.3100e-06]],\n\n [[-1.1954e-05]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-8.5787e-06]],\n\n [[-2.9472e-07]]]]), 'exp_avg_sq': tensor([[[[0.0000e+00]],\n\n [[2.6408e-07]],\n\n [[3.0452e-07]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[1.6266e-07]],\n\n [[1.0637e-06]]],\n\n\n [[[0.0000e+00]],\n\n [[6.7374e-10]],\n\n [[2.1715e-08]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[4.4283e-10]],\n\n [[1.5698e-09]]],\n\n\n [[[0.0000e+00]],\n\n [[4.6956e-08]],\n\n [[5.1736e-07]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[3.2036e-08]],\n\n [[4.4048e-07]]],\n\n\n ...,\n\n\n [[[0.0000e+00]],\n\n [[2.3550e-09]],\n\n [[2.6586e-08]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[1.5115e-09]],\n\n [[5.5636e-09]]],\n\n\n [[[0.0000e+00]],\n\n [[1.9042e-07]],\n\n [[3.6794e-07]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[4.1928e-07]],\n\n [[2.9340e-06]]],\n\n\n [[[0.0000e+00]],\n\n [[1.4445e-07]],\n\n [[3.1070e-07]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[2.5072e-07]],\n\n [[3.9894e-07]]]])}, 10: {'step': 7160, 'exp_avg': tensor([-1.8579e-03, 3.0375e-04, 9.1391e-05, 4.2872e-04, 4.3621e-05,\n 1.2597e-03, 1.7756e-04, 1.9575e-04, -1.1887e-03, -1.2007e-04,\n -1.8295e-04, 4.1716e-04, 9.3213e-05, -6.6287e-04, 3.3570e-04,\n 1.1872e-04, -2.9439e-04, -2.0766e-05, -1.3085e-05, -7.0517e-04,\n 8.7155e-05, -1.5983e-04, 0.0000e+00, 0.0000e+00, 4.5846e-04,\n 0.0000e+00, -1.1919e-04, 5.3080e-05, -1.2956e-06, -1.5225e-04,\n 1.9855e-04, 2.3864e-04, 4.7863e-05, 3.1603e-05, -8.0212e-05,\n -1.2895e-04, 1.0549e-04, -1.1627e-04, 2.9469e-04, -1.7204e-03,\n 2.7506e-05, -3.4452e-04, -4.5900e-04, -5.6974e-04, -9.9287e-05,\n 0.0000e+00, 2.1639e-04, -2.1014e-04, 1.5976e-04, 8.9201e-05,\n 8.5903e-04, -2.1873e-04, 0.0000e+00, 7.6564e-05, 3.4010e-04,\n -3.1633e-04, -1.4993e-05, -1.3610e-04, 6.9951e-05, 2.1810e-04,\n 2.6663e-04, -5.6283e-05, 1.8251e-04, 6.6923e-05, 0.0000e+00,\n 7.2432e-05, -2.6509e-05, -1.8434e-04, 2.1100e-07, 2.5399e-04,\n 1.7981e-04, 0.0000e+00, -3.5195e-04, -1.5200e-03, -2.1099e-04,\n -2.7890e-05, -5.6052e-45, -1.6650e-04, -1.0309e-04, 2.8830e-04,\n -4.8617e-04, -1.3358e-04, -4.1440e-04, 0.0000e+00, 2.4804e-05,\n 5.9478e-05, 1.2134e-04, 0.0000e+00, -4.4644e-04, 0.0000e+00,\n 4.6885e-04, 3.7981e-05, 2.0211e-04, -5.6052e-45, 5.0640e-07,\n 7.5212e-05, -7.0216e-04, -6.0101e-05, 5.8485e-05, -1.6557e-05,\n 3.3534e-04, 0.0000e+00, 3.5747e-05, 1.8224e-04, -1.1800e-04,\n -7.1009e-05, 8.9463e-05, 0.0000e+00, 3.9701e-05, 2.3070e-04,\n 1.5592e-03, 6.6459e-05, 5.1550e-05, -1.4507e-04, 1.6270e-04,\n 7.9125e-05, 2.9616e-04, 0.0000e+00, 2.7143e-04, 4.0427e-04,\n -1.1793e-04, 2.0519e-04, -1.0129e-04, 0.0000e+00, 1.9067e-04,\n 8.6276e-05, 5.3733e-06, 0.0000e+00, 3.8389e-04, 6.0726e-04,\n 6.4336e-05, -1.4602e-04, 3.6163e-04, 0.0000e+00, 0.0000e+00,\n 5.5547e-05, -1.3407e-04, -7.6632e-05, 1.4736e-04, -1.3474e-05,\n -4.5546e-06, 5.4107e-05, 4.4659e-05, 6.4260e-05, 6.5403e-05,\n 3.0490e-04, 2.5589e-04, 2.9291e-04, 4.5407e-04, -3.4159e-04,\n 1.2997e-04, -2.0758e-04, 3.4801e-05, -1.1326e-05, 6.7800e-05,\n -1.1825e-04, 1.4662e-04, 3.0621e-04, 3.4256e-04, -2.0398e-04,\n 6.1801e-04, -2.7915e-04, -1.6353e-04, -5.9844e-04, -1.9918e-05,\n 2.4543e-04, 3.1233e-04, 1.2711e-05, -1.4934e-04, -6.9267e-05,\n 6.4092e-05, 4.0934e-07, -9.2233e-05, -3.2699e-05, 0.0000e+00,\n 1.5718e-04, -1.1088e-04, 1.0832e-03, -4.1012e-05, -1.6601e-04,\n 1.3614e-04, -2.8823e-05, 2.8256e-04, 1.6673e-05, -2.8702e-04,\n 0.0000e+00, 1.8882e-04, 3.2543e-04, 7.0199e-04, -5.0942e-04,\n 2.8774e-04, -2.6479e-05, 2.9596e-03, -2.4608e-04, -1.8747e-05,\n 1.6480e-04, 4.2145e-04, 3.8141e-04, 2.4684e-04, 0.0000e+00,\n -3.8234e-04, 5.5238e-05, 0.0000e+00, 2.6344e-04, 0.0000e+00,\n -2.6928e-04, 1.0630e-04, -5.6125e-05, 1.4302e-04, 2.0001e-04,\n -1.6025e-04, -3.3259e-05, -2.2892e-04, -1.8343e-04, 0.0000e+00,\n -1.5669e-04, -6.1706e-05, 2.7963e-04, -1.7642e-05, 1.0109e-05,\n 1.1062e-03, 7.1746e-06, 4.3074e-05, 1.1481e-03, -1.2305e-04,\n 1.4660e-04, -5.1885e-04, 1.1222e-04, 8.2162e-05, 1.0963e-04,\n 3.0290e-05, -3.0165e-04, 1.0693e-04, -2.0936e-04, 3.2530e-04,\n -9.5258e-05, -1.8054e-04, 1.8621e-04, -2.9513e-05, 3.1229e-05,\n 6.5708e-05, 4.4177e-04, -1.0697e-04, -6.9475e-04, 4.5369e-04,\n 1.7242e-05, 0.0000e+00, -2.3820e-04, -3.5605e-05, 2.4075e-04,\n -2.3746e-05, -6.8917e-04, 5.3073e-04, 2.5586e-04, -1.9631e-04,\n -4.0625e-04]), 'exp_avg_sq': tensor([5.3324e-04, 7.3164e-06, 4.2992e-06, 4.0802e-05, 3.3465e-07, 5.3819e-05,\n 1.6152e-05, 4.2425e-05, 1.7470e-04, 1.0729e-05, 3.1571e-05, 5.8867e-06,\n 2.8954e-05, 2.3545e-05, 1.4569e-05, 7.6144e-06, 1.4707e-05, 2.2977e-05,\n 7.0929e-07, 1.5256e-04, 1.1993e-05, 5.2464e-06, 0.0000e+00, 0.0000e+00,\n 2.0986e-05, 0.0000e+00, 4.3004e-06, 5.3055e-06, 1.9848e-05, 5.6865e-06,\n 1.0327e-05, 1.6648e-05, 2.4243e-05, 1.5498e-06, 9.3444e-06, 1.2743e-05,\n 7.7698e-06, 7.6786e-06, 3.9106e-06, 2.1903e-04, 8.2782e-07, 1.6423e-05,\n 8.7897e-06, 1.8977e-05, 7.9182e-06, 0.0000e+00, 9.4230e-06, 7.9134e-06,\n 9.1711e-07, 3.4665e-06, 1.5814e-05, 9.0066e-06, 0.0000e+00, 2.8487e-06,\n 1.3746e-05, 1.4886e-05, 2.9482e-06, 9.1930e-06, 4.5986e-06, 4.0168e-06,\n 7.1978e-06, 1.2120e-05, 1.1965e-05, 5.0781e-06, 0.0000e+00, 7.1942e-06,\n 4.2177e-06, 7.3477e-06, 2.1551e-06, 3.7214e-06, 1.9048e-06, 0.0000e+00,\n 2.6144e-05, 2.7676e-04, 1.3876e-05, 3.9537e-06, 6.6356e-22, 9.6049e-06,\n 1.7866e-05, 4.6066e-06, 2.1777e-05, 1.2905e-05, 3.7989e-05, 0.0000e+00,\n 1.1137e-05, 1.9127e-05, 6.1403e-06, 0.0000e+00, 6.4067e-05, 0.0000e+00,\n 2.3762e-05, 1.1502e-06, 1.2906e-05, 1.8449e-16, 3.2220e-08, 5.9735e-06,\n 4.2710e-05, 4.4591e-06, 1.1311e-05, 4.1613e-06, 8.1754e-06, 0.0000e+00,\n 7.8395e-06, 1.4244e-05, 1.6597e-05, 1.1227e-05, 5.0545e-06, 0.0000e+00,\n 3.7368e-06, 2.4087e-05, 4.4982e-04, 1.0143e-05, 2.7532e-05, 1.1389e-05,\n 1.2027e-05, 7.9212e-06, 2.0992e-05, 0.0000e+00, 4.1947e-05, 1.4365e-05,\n 4.7710e-06, 6.7890e-06, 1.7669e-05, 0.0000e+00, 1.1861e-05, 1.6167e-05,\n 5.2181e-06, 0.0000e+00, 1.1169e-05, 2.4160e-05, 2.2760e-05, 2.2457e-06,\n 1.2919e-05, 0.0000e+00, 0.0000e+00, 3.1284e-06, 4.5718e-06, 5.1188e-06,\n 1.8776e-05, 2.4121e-06, 2.5610e-06, 2.8435e-05, 7.1448e-06, 8.2838e-06,\n 2.7246e-06, 1.5206e-05, 1.4907e-05, 1.0207e-05, 2.6859e-06, 4.3083e-06,\n 5.2413e-06, 1.1806e-05, 3.2411e-06, 4.6544e-06, 4.2006e-06, 1.2424e-05,\n 6.7250e-06, 4.7221e-06, 2.5816e-05, 3.8713e-06, 3.0127e-05, 3.5791e-05,\n 4.5390e-06, 1.3832e-05, 1.5811e-06, 1.7917e-06, 5.1278e-06, 1.1063e-05,\n 8.7356e-06, 5.1187e-06, 1.0551e-05, 4.0253e-06, 2.8916e-06, 1.7264e-06,\n 0.0000e+00, 4.0556e-06, 7.9185e-06, 7.7373e-05, 4.1630e-06, 2.3067e-05,\n 4.0522e-06, 2.8057e-06, 5.1887e-06, 5.1704e-06, 3.4560e-05, 0.0000e+00,\n 9.9060e-06, 1.4819e-05, 1.5374e-05, 2.5881e-05, 1.4546e-05, 1.4808e-05,\n 7.8893e-04, 9.0027e-06, 1.8418e-06, 1.6646e-05, 7.5548e-06, 1.7513e-05,\n 4.8316e-06, 0.0000e+00, 2.3768e-05, 1.6322e-05, 0.0000e+00, 2.5896e-05,\n 0.0000e+00, 1.4360e-05, 2.5390e-06, 5.6365e-06, 6.6502e-06, 1.1665e-05,\n 3.7473e-06, 6.2943e-06, 3.5686e-06, 1.3216e-05, 0.0000e+00, 1.3167e-05,\n 3.5063e-06, 5.8191e-06, 4.3901e-06, 1.7732e-05, 6.2945e-05, 4.5362e-06,\n 7.3993e-07, 2.6010e-04, 2.1181e-06, 5.6321e-06, 1.3985e-05, 1.0051e-05,\n 1.2689e-05, 1.4241e-05, 1.8078e-06, 1.2500e-05, 5.0286e-06, 1.0398e-05,\n 1.0596e-05, 2.2150e-05, 1.2087e-05, 1.2615e-05, 2.1606e-06, 5.3709e-07,\n 3.7837e-06, 4.4251e-06, 1.0796e-05, 2.8573e-05, 3.0981e-05, 7.5678e-06,\n 0.0000e+00, 8.5484e-06, 1.8432e-06, 3.4958e-06, 9.2429e-06, 8.8668e-05,\n 5.1407e-05, 2.1160e-05, 3.0240e-05, 4.9304e-06])}, 11: {'step': 7160, 'exp_avg': tensor([-5.3852e-04, -7.6589e-04, -1.2752e-04, 1.2238e-04, 2.8605e-05,\n -2.6611e-05, 7.9632e-05, -8.0774e-05, 2.0900e-04, -1.2416e-04,\n -1.5559e-04, 5.1897e-05, -2.3026e-04, -3.2187e-04, -1.0091e-04,\n 9.9587e-05, -7.9291e-06, 3.9303e-05, 2.8513e-05, -1.9129e-04,\n 1.8064e-04, 2.6736e-04, 0.0000e+00, 0.0000e+00, 2.4610e-05,\n 0.0000e+00, 9.6100e-05, 4.9804e-06, -1.4888e-04, 1.0076e-05,\n 2.5023e-06, 2.2428e-04, 5.7515e-06, 1.5137e-05, -7.6934e-05,\n -3.4460e-05, -1.2055e-04, 5.1809e-05, -1.6487e-04, -1.7205e-04,\n -4.1977e-06, -8.5301e-06, -1.2913e-04, -1.8105e-04, -5.3070e-05,\n 0.0000e+00, -1.0219e-05, 2.6046e-05, 1.1932e-04, -7.0902e-07,\n 5.7557e-05, -9.9773e-05, 0.0000e+00, 1.7003e-04, -6.0926e-05,\n -7.7165e-05, -4.1106e-06, -1.5290e-04, -2.5914e-05, -7.8494e-05,\n -1.3884e-05, -1.1094e-04, -9.6523e-05, 1.8387e-05, 0.0000e+00,\n 5.3471e-05, -6.3959e-06, -1.0840e-04, 6.7761e-05, 1.0702e-04,\n 1.8672e-05, 0.0000e+00, -1.5596e-05, 3.4683e-04, 1.8508e-04,\n -1.8558e-04, 5.6052e-45, -1.0550e-04, 1.3675e-05, -1.0574e-05,\n 1.3286e-05, 8.0451e-05, 7.2873e-05, 0.0000e+00, 1.0708e-04,\n 1.0171e-04, -1.8202e-04, 0.0000e+00, -3.7707e-04, 0.0000e+00,\n -3.9506e-04, 1.3939e-05, -2.8642e-04, 5.6052e-45, -6.6762e-07,\n 8.8169e-05, -6.6275e-05, -7.1026e-05, 2.7556e-05, 1.3388e-04,\n -1.6700e-04, 0.0000e+00, -1.6426e-04, 1.4894e-04, -1.3569e-04,\n 3.4735e-06, 4.6119e-05, 0.0000e+00, -4.6071e-05, -1.2164e-05,\n -1.7507e-04, 3.4677e-05, 9.6173e-05, 5.8866e-05, -6.9294e-05,\n 1.0905e-04, -1.4553e-04, 0.0000e+00, -1.5057e-05, 1.6754e-05,\n 7.5192e-05, 6.7397e-05, -7.6130e-05, 0.0000e+00, -4.4992e-05,\n -4.2591e-05, 1.4343e-04, 0.0000e+00, 1.5138e-04, -8.2941e-06,\n -5.7039e-05, -1.2057e-04, 1.4196e-04, 0.0000e+00, 0.0000e+00,\n -1.0349e-04, -1.6135e-04, -2.1787e-05, 3.8479e-05, -2.4011e-05,\n -1.9524e-05, 4.9054e-06, 5.2707e-05, -9.3493e-05, 4.3036e-05,\n -1.2569e-04, 5.9840e-05, 9.5915e-05, 2.1690e-04, -9.7707e-05,\n 1.0550e-05, -7.1002e-06, -9.0613e-05, -7.8175e-05, 3.3086e-05,\n -1.5847e-04, 4.8291e-05, 5.3410e-05, -8.5672e-06, 8.0684e-06,\n -1.1560e-04, -4.4501e-06, 1.4299e-04, 6.9599e-06, -5.8835e-05,\n -1.2068e-04, 2.4569e-05, -1.4745e-04, 9.2171e-05, -3.1829e-05,\n -2.9050e-05, -2.4117e-05, 3.5344e-05, -5.1934e-06, 0.0000e+00,\n 1.4367e-04, -7.8826e-05, -6.4235e-05, 9.8305e-05, -8.8477e-05,\n -3.6163e-05, 2.2624e-05, -1.4237e-04, -3.5687e-05, 9.0886e-05,\n 0.0000e+00, 1.4260e-04, 5.5705e-06, -8.0084e-07, 2.4835e-05,\n 6.1438e-05, -1.0880e-04, -6.4456e-04, 2.7526e-05, -2.5398e-05,\n -1.6124e-05, -1.0174e-04, 2.5300e-04, 1.1386e-04, 0.0000e+00,\n -7.7838e-05, 1.3619e-04, 0.0000e+00, -1.0304e-05, 0.0000e+00,\n 8.9870e-05, 1.6830e-04, 7.1222e-05, 9.3573e-05, -2.8563e-05,\n -1.4254e-04, 5.7442e-05, -8.6306e-05, 1.2254e-04, 0.0000e+00,\n -2.3597e-05, -6.3676e-05, 1.2265e-05, 4.1332e-05, -1.6975e-05,\n 4.7285e-04, -5.5872e-05, 5.5041e-05, 3.9504e-04, -1.3199e-05,\n -2.2674e-04, -3.2921e-04, 6.1405e-05, -3.1703e-04, 5.6551e-05,\n -6.8127e-06, 1.7217e-04, 2.3836e-04, 1.6971e-04, 1.7729e-05,\n -6.9820e-05, -1.5470e-04, 3.0731e-04, -1.5153e-04, 7.2049e-05,\n 1.7458e-04, -7.3870e-05, -8.4865e-04, 1.9973e-04, 4.0711e-05,\n 2.5935e-04, 0.0000e+00, -1.7366e-04, 1.4405e-04, 1.2397e-04,\n 6.8429e-05, -1.7686e-05, -1.1908e-04, 1.1179e-04, -9.8637e-06,\n -8.2084e-05]), 'exp_avg_sq': tensor([3.8778e-05, 4.1508e-05, 1.6254e-06, 5.4758e-06, 8.0671e-08, 5.2697e-06,\n 2.4090e-06, 2.3938e-06, 7.6537e-06, 1.4269e-06, 1.7519e-05, 2.0127e-06,\n 5.2135e-06, 2.5832e-05, 4.1255e-06, 2.5164e-06, 2.3386e-06, 1.4021e-06,\n 4.8449e-07, 9.7291e-06, 2.1001e-06, 3.9173e-06, 0.0000e+00, 0.0000e+00,\n 4.5090e-06, 0.0000e+00, 3.8680e-06, 3.0400e-06, 2.4608e-06, 2.5476e-06,\n 2.6696e-06, 5.6947e-06, 7.3151e-06, 1.2392e-06, 2.7367e-06, 4.1511e-06,\n 2.2061e-06, 1.9964e-06, 1.2594e-05, 2.0105e-06, 8.1114e-07, 3.6393e-06,\n 3.1407e-06, 2.8790e-06, 2.8970e-06, 0.0000e+00, 3.6010e-06, 1.6765e-06,\n 3.4666e-07, 2.2122e-06, 2.1218e-06, 1.7385e-06, 0.0000e+00, 1.8663e-06,\n 3.6037e-06, 3.7505e-06, 4.1844e-07, 2.3227e-06, 2.3562e-06, 3.9022e-06,\n 7.2258e-06, 2.7851e-06, 1.8192e-06, 1.3684e-06, 0.0000e+00, 1.0605e-05,\n 1.2834e-06, 2.6340e-06, 1.3799e-06, 8.3964e-06, 1.8810e-06, 0.0000e+00,\n 2.5291e-07, 1.0674e-05, 3.1035e-06, 1.7147e-06, 9.5187e-21, 1.9927e-06,\n 4.6837e-06, 1.7228e-06, 3.1576e-06, 5.3891e-06, 3.4807e-06, 0.0000e+00,\n 6.2956e-07, 9.6600e-07, 2.1036e-06, 0.0000e+00, 2.3489e-05, 0.0000e+00,\n 1.3431e-05, 5.1270e-07, 1.1131e-05, 4.4698e-16, 7.3125e-09, 6.2385e-07,\n 3.0445e-07, 2.0859e-06, 2.2636e-06, 1.8742e-06, 1.5470e-06, 0.0000e+00,\n 3.7729e-06, 2.3262e-06, 3.0856e-06, 4.1679e-06, 4.7079e-07, 0.0000e+00,\n 2.9123e-06, 9.4290e-07, 1.3123e-05, 2.1773e-06, 1.2347e-05, 2.2769e-06,\n 7.6678e-06, 2.6982e-06, 2.1970e-06, 0.0000e+00, 2.3556e-06, 2.2455e-06,\n 1.2799e-06, 7.1320e-07, 2.6737e-06, 0.0000e+00, 1.3694e-06, 4.2988e-06,\n 1.5825e-06, 0.0000e+00, 3.1380e-06, 2.5246e-06, 3.4553e-06, 1.5750e-06,\n 2.8019e-06, 0.0000e+00, 0.0000e+00, 1.7617e-06, 1.5092e-06, 1.6733e-06,\n 3.4434e-06, 7.8204e-07, 9.6323e-07, 2.0439e-06, 1.9452e-06, 1.0698e-06,\n 1.3053e-06, 5.2162e-06, 1.1724e-06, 2.9955e-06, 9.5643e-07, 1.7600e-06,\n 2.7776e-06, 2.3341e-06, 1.7715e-06, 3.5824e-06, 2.6016e-06, 2.9819e-06,\n 4.0174e-06, 2.5383e-06, 8.8079e-06, 2.6669e-06, 8.0022e-06, 5.7117e-06,\n 3.3418e-06, 9.9440e-09, 7.2450e-07, 2.3373e-06, 2.0245e-06, 5.0545e-06,\n 2.9572e-06, 1.4325e-06, 7.7833e-07, 2.0341e-06, 1.6397e-06, 1.4004e-06,\n 0.0000e+00, 3.1767e-06, 4.0644e-06, 1.5583e-06, 1.8688e-06, 3.3055e-06,\n 2.2029e-06, 2.6883e-06, 1.7905e-06, 2.7062e-06, 6.7732e-06, 0.0000e+00,\n 3.8590e-06, 1.3886e-06, 2.4665e-06, 2.2197e-06, 5.1529e-06, 9.4462e-06,\n 5.5686e-05, 2.2226e-06, 1.2091e-06, 6.3336e-06, 3.5001e-06, 2.1280e-06,\n 3.2402e-06, 0.0000e+00, 2.7995e-06, 1.3063e-06, 0.0000e+00, 3.8832e-07,\n 0.0000e+00, 1.2458e-06, 1.3637e-06, 1.5473e-06, 1.4380e-06, 1.6813e-06,\n 1.8029e-06, 5.2861e-06, 1.5441e-06, 2.1279e-06, 0.0000e+00, 4.4501e-06,\n 2.0197e-06, 2.8426e-06, 2.8437e-06, 2.0172e-06, 6.7185e-05, 1.1811e-06,\n 2.9168e-07, 2.7926e-05, 1.6981e-06, 1.7191e-06, 6.4528e-05, 1.5981e-06,\n 1.2516e-05, 9.5247e-07, 8.6073e-07, 4.7361e-06, 3.8463e-06, 3.6978e-06,\n 1.8189e-07, 8.9163e-06, 3.5575e-06, 3.6363e-05, 1.3345e-06, 4.7542e-07,\n 9.0701e-07, 1.3863e-06, 7.7790e-05, 4.0114e-06, 2.5681e-06, 3.2226e-06,\n 0.0000e+00, 3.6083e-06, 1.4741e-06, 2.2239e-06, 2.5991e-06, 1.7857e-05,\n 4.8854e-06, 1.4427e-05, 9.2954e-07, 1.9094e-06])}, 12: {'step': 7160, 'exp_avg': tensor([[[[ 3.3229e-04]],\n\n [[ 7.2756e-05]],\n\n [[ 1.7736e-04]],\n\n ...,\n\n [[-6.8700e-06]],\n\n [[ 6.5827e-04]],\n\n [[ 3.1048e-04]]],\n\n\n [[[ 4.0733e-04]],\n\n [[-1.0257e-04]],\n\n [[ 3.2941e-04]],\n\n ...,\n\n [[ 2.9051e-05]],\n\n [[ 1.0916e-03]],\n\n [[ 4.5372e-04]]],\n\n\n [[[-4.4107e-05]],\n\n [[ 6.9560e-06]],\n\n [[-1.3594e-05]],\n\n ...,\n\n [[-2.7654e-05]],\n\n [[-7.8154e-05]],\n\n [[-3.3963e-05]]],\n\n\n ...,\n\n\n [[[ 9.7892e-05]],\n\n [[ 4.3251e-05]],\n\n [[-1.1681e-05]],\n\n ...,\n\n [[-7.3078e-07]],\n\n [[ 4.4978e-05]],\n\n [[ 1.4447e-05]]],\n\n\n [[[ 1.0035e-04]],\n\n [[ 7.4158e-05]],\n\n [[ 3.4965e-05]],\n\n ...,\n\n [[-1.4941e-05]],\n\n [[ 3.0255e-06]],\n\n [[ 3.2891e-05]]],\n\n\n [[[ 3.9149e-06]],\n\n [[ 3.6100e-05]],\n\n [[-1.7815e-05]],\n\n ...,\n\n [[ 1.7893e-05]],\n\n [[-7.5394e-05]],\n\n [[-3.2240e-05]]]]), 'exp_avg_sq': tensor([[[[1.7300e-05]],\n\n [[6.9550e-06]],\n\n [[9.4376e-06]],\n\n ...,\n\n [[1.8551e-05]],\n\n [[4.3153e-05]],\n\n [[1.4199e-05]]],\n\n\n [[[1.9284e-05]],\n\n [[1.0389e-05]],\n\n [[9.0550e-06]],\n\n ...,\n\n [[1.7266e-05]],\n\n [[6.8265e-05]],\n\n [[1.6980e-05]]],\n\n\n [[[1.0127e-06]],\n\n [[1.4044e-06]],\n\n [[3.6941e-07]],\n\n ...,\n\n [[1.3010e-06]],\n\n [[1.3182e-06]],\n\n [[6.0418e-07]]],\n\n\n ...,\n\n\n [[[1.1793e-06]],\n\n [[8.8785e-07]],\n\n [[1.4750e-06]],\n\n ...,\n\n [[2.2879e-06]],\n\n [[3.7512e-06]],\n\n [[1.1200e-06]]],\n\n\n [[[1.6535e-06]],\n\n [[3.7647e-06]],\n\n [[1.0854e-06]],\n\n ...,\n\n [[2.4002e-06]],\n\n [[2.0704e-06]],\n\n [[1.1561e-06]]],\n\n\n [[[3.1343e-07]],\n\n [[5.2285e-07]],\n\n [[2.4180e-07]],\n\n ...,\n\n [[3.1837e-07]],\n\n [[6.4302e-07]],\n\n [[1.9051e-07]]]])}, 13: {'step': 7160, 'exp_avg': tensor([ 7.0646e-04, 4.2393e-04, -1.1149e-04, -3.8586e-04, 1.8632e-05,\n -7.2862e-04, -1.1289e-04, -8.0368e-05, -1.7451e-04, 1.7169e-04,\n 1.5703e-04, -3.3948e-04, -2.0432e-04, -6.7871e-04, -2.5786e-04,\n 6.4030e-05, 4.7517e-04, -1.8716e-04, 7.1973e-05, 3.9984e-04,\n -1.8745e-04, 2.8896e-04, 0.0000e+00, 0.0000e+00, -3.6088e-04,\n 0.0000e+00, 3.4882e-04, 1.2103e-04, 8.1736e-06, 1.4931e-04,\n -2.7179e-04, -2.8100e-05, -1.8640e-05, 2.4586e-05, 8.6954e-05,\n 9.1182e-05, -1.1729e-04, 2.7803e-05, 1.9317e-04, 4.6889e-04,\n -3.9539e-05, 1.8219e-04, 2.8092e-04, 5.0945e-04, 1.8415e-05,\n 0.0000e+00, -9.7825e-05, 1.9776e-04, 6.2557e-04, -9.5535e-05,\n -6.9601e-04, 1.0586e-04, 0.0000e+00, 4.0862e-05, -1.5426e-04,\n 5.0717e-05, 7.0859e-05, 1.5625e-04, 5.8924e-05, -2.3224e-04,\n 6.8712e-05, 1.9494e-04, -8.9042e-05, 1.1137e-05, 0.0000e+00,\n 2.7145e-04, 5.4468e-05, 1.2817e-04, 5.0097e-05, 4.2467e-05,\n 8.9476e-05, 0.0000e+00, 3.7072e-04, -8.3815e-05, 6.5566e-05,\n 7.1054e-05, 5.6052e-45, -1.4108e-04, 1.6800e-04, -3.1960e-04,\n 3.2137e-04, 7.0160e-05, -9.6800e-05, 0.0000e+00, -2.2360e-04,\n -2.1662e-04, -2.0120e-04, 0.0000e+00, -4.4169e-04, 0.0000e+00,\n 2.0344e-05, 2.4747e-05, -2.0331e-04, 5.6052e-45, -2.5924e-06,\n -1.6634e-04, 7.1857e-04, -1.4131e-04, -2.2685e-04, 7.4950e-05,\n -5.0593e-04, 0.0000e+00, -1.2976e-04, -4.5717e-05, 5.0729e-05,\n 1.0985e-04, 1.6898e-04, 0.0000e+00, -9.5058e-05, -2.2883e-04,\n -8.7186e-04, 4.8294e-05, 1.8570e-04, 6.6053e-05, 2.1114e-04,\n -2.9699e-05, -4.5944e-04, 0.0000e+00, -2.4590e-04, -6.2606e-04,\n 1.3371e-04, 1.3685e-04, 1.0920e-04, 0.0000e+00, 1.1942e-05,\n -1.4016e-04, -1.8887e-05, 0.0000e+00, -1.8600e-05, -4.7628e-04,\n -1.0824e-04, -1.3196e-04, -1.3518e-04, 0.0000e+00, 0.0000e+00,\n 4.1272e-05, 6.6046e-05, 1.2051e-04, -1.3247e-04, 6.8541e-05,\n -3.1319e-05, -1.4016e-04, 6.6231e-05, -4.0576e-05, 1.3153e-04,\n -2.0039e-04, -3.4499e-04, -6.2877e-05, 6.0255e-04, 2.5208e-04,\n 7.7518e-05, -3.0420e-05, -1.8427e-04, -1.0545e-04, 2.5326e-05,\n 3.5187e-05, 1.7574e-04, -1.4129e-04, -5.9244e-05, -3.6882e-05,\n -5.4936e-04, 3.5018e-04, 2.9445e-04, -1.9962e-05, -5.2034e-05,\n -2.0138e-04, 3.4774e-04, -1.1806e-04, 1.4964e-04, -1.1048e-04,\n -1.1118e-04, -4.9679e-05, -2.7321e-05, -1.2559e-04, 0.0000e+00,\n -2.7453e-06, 1.9865e-04, -1.2173e-03, -6.6432e-05, 1.9180e-05,\n -1.2057e-04, 1.5937e-04, -2.7314e-04, 1.2593e-05, -2.9300e-04,\n 0.0000e+00, -7.7094e-06, -3.3780e-04, -6.6132e-04, -1.9346e-03,\n -9.1071e-05, -1.1206e-04, -6.5094e-04, -1.4198e-05, -5.3763e-05,\n -7.5845e-05, -2.1668e-04, 2.5105e-04, -9.2798e-05, 0.0000e+00,\n 1.0040e-04, -5.0738e-05, 0.0000e+00, -4.1182e-04, 0.0000e+00,\n -6.7028e-06, 2.0084e-05, 6.9604e-05, 2.8321e-05, -2.8507e-04,\n -1.9894e-05, -1.4169e-05, -1.6318e-04, 5.8319e-06, 0.0000e+00,\n 1.7208e-04, 3.1932e-06, -2.3062e-04, 1.0603e-04, -4.9849e-06,\n -7.8897e-04, -4.6848e-05, 2.9473e-05, -1.4823e-03, -4.0734e-05,\n -2.3849e-04, -4.2398e-04, -4.1192e-05, 5.5551e-04, -2.3723e-04,\n 6.2479e-05, 2.1794e-04, 1.2136e-04, 1.6969e-04, -2.2545e-04,\n 1.1465e-04, 5.0087e-05, -1.5423e-05, -1.1036e-04, 1.3642e-04,\n -6.2151e-05, 7.9839e-05, 4.6637e-04, 6.7314e-04, -5.3859e-04,\n 1.2741e-04, 0.0000e+00, -3.4528e-04, 1.0794e-04, -7.0310e-05,\n 1.3664e-04, 5.4686e-05, -3.6925e-04, 3.0489e-05, 4.5979e-04,\n 2.2756e-04]), 'exp_avg_sq': tensor([3.1963e-05, 4.1440e-05, 1.4568e-05, 2.8977e-05, 3.9391e-08, 4.9025e-05,\n 6.0059e-06, 3.3983e-05, 4.6216e-05, 8.0744e-06, 1.5029e-05, 4.7942e-06,\n 2.4968e-05, 2.0803e-05, 9.4304e-06, 6.3609e-06, 2.3665e-05, 2.2795e-05,\n 3.0168e-06, 3.4105e-05, 4.7750e-06, 4.4843e-06, 0.0000e+00, 0.0000e+00,\n 1.7218e-05, 0.0000e+00, 1.0720e-05, 4.8661e-06, 2.0952e-05, 7.6531e-06,\n 1.2052e-05, 1.3464e-05, 1.5807e-05, 1.1699e-06, 2.3815e-06, 5.1045e-06,\n 1.3305e-06, 7.3152e-06, 1.1451e-05, 1.9830e-05, 2.9262e-06, 5.7655e-06,\n 2.7858e-06, 1.3490e-05, 2.9396e-06, 0.0000e+00, 2.4758e-06, 4.9843e-06,\n 2.0877e-06, 1.0441e-06, 8.6701e-06, 7.2979e-06, 0.0000e+00, 4.3330e-06,\n 9.2130e-06, 8.3404e-06, 1.1847e-05, 4.7778e-06, 4.2693e-06, 2.2435e-06,\n 8.1662e-06, 8.0941e-06, 6.5869e-06, 1.4936e-06, 0.0000e+00, 8.4908e-06,\n 2.3948e-06, 5.2338e-06, 1.5159e-06, 4.3971e-06, 4.3217e-06, 0.0000e+00,\n 3.2356e-05, 5.3798e-05, 1.8576e-05, 5.5428e-06, 4.9326e-20, 1.4142e-05,\n 1.4711e-05, 7.0195e-06, 9.8923e-06, 9.8035e-06, 1.3589e-05, 0.0000e+00,\n 1.3842e-05, 1.8404e-05, 3.7693e-06, 0.0000e+00, 5.8949e-05, 0.0000e+00,\n 2.7443e-05, 8.8570e-07, 1.5608e-05, 3.5139e-14, 4.4548e-08, 4.6992e-06,\n 4.5137e-05, 8.7926e-06, 1.5688e-05, 1.0021e-06, 8.2140e-06, 0.0000e+00,\n 5.3772e-06, 5.2792e-06, 1.1505e-05, 6.9295e-06, 1.8882e-06, 0.0000e+00,\n 6.2821e-06, 1.2988e-05, 1.3542e-04, 1.0784e-05, 1.0139e-05, 4.4400e-06,\n 5.9568e-06, 6.1395e-06, 1.8538e-05, 0.0000e+00, 2.7814e-05, 9.9900e-06,\n 2.5535e-06, 6.7023e-06, 1.5395e-05, 0.0000e+00, 1.1205e-05, 1.4373e-05,\n 4.7889e-06, 0.0000e+00, 4.1795e-06, 1.8454e-05, 2.3661e-05, 9.1537e-07,\n 8.6461e-06, 0.0000e+00, 0.0000e+00, 4.9480e-06, 2.7779e-06, 5.8079e-06,\n 1.6946e-05, 2.5617e-06, 1.0707e-06, 2.8907e-05, 2.7870e-06, 6.4094e-06,\n 7.9343e-06, 9.2596e-06, 1.5464e-05, 2.1901e-06, 7.3767e-06, 2.7031e-06,\n 9.5273e-06, 5.7227e-06, 2.1264e-06, 4.1079e-06, 4.1196e-06, 7.1535e-06,\n 3.0852e-06, 3.8474e-06, 8.8382e-06, 2.6064e-06, 2.2362e-05, 2.2328e-05,\n 3.0102e-06, 1.0040e-04, 1.2132e-06, 1.4386e-06, 5.2173e-06, 1.2643e-05,\n 3.6221e-06, 3.6920e-06, 7.7024e-06, 2.4645e-06, 3.4208e-06, 1.9631e-06,\n 0.0000e+00, 7.1347e-06, 7.4154e-06, 6.1510e-05, 6.2690e-06, 5.9529e-06,\n 3.4374e-06, 5.7572e-06, 2.2081e-06, 3.7971e-06, 1.0386e-05, 0.0000e+00,\n 4.5351e-06, 1.1860e-05, 1.7239e-05, 2.8409e-04, 5.4068e-06, 1.4328e-05,\n 9.1623e-05, 4.6085e-06, 1.8674e-06, 3.8126e-06, 4.1489e-06, 1.5554e-05,\n 5.3711e-06, 0.0000e+00, 1.9472e-05, 1.6498e-05, 0.0000e+00, 2.5047e-05,\n 0.0000e+00, 9.0601e-06, 2.6137e-06, 2.5701e-06, 3.1023e-06, 1.4556e-05,\n 2.6247e-06, 7.1812e-06, 9.3521e-07, 6.2008e-06, 0.0000e+00, 9.1515e-06,\n 6.4162e-06, 5.9786e-06, 2.3512e-06, 1.5912e-05, 1.1769e-04, 7.8056e-06,\n 2.8065e-07, 1.0026e-04, 5.6388e-06, 1.5696e-06, 6.9587e-05, 1.1141e-05,\n 4.2746e-05, 1.7230e-05, 1.1525e-06, 1.7436e-05, 1.9271e-06, 8.6885e-06,\n 1.0341e-05, 4.7168e-06, 6.6929e-06, 9.9060e-05, 7.8761e-07, 7.4674e-07,\n 2.6242e-06, 1.1387e-06, 3.4163e-05, 2.0545e-05, 3.5358e-05, 9.4741e-07,\n 0.0000e+00, 5.8058e-06, 8.8588e-07, 4.3572e-06, 4.8583e-06, 1.4640e-05,\n 3.2427e-05, 1.8513e-05, 2.2101e-05, 5.6073e-06])}, 14: {'step': 7160, 'exp_avg': tensor([-5.3852e-04, -7.6589e-04, -1.2752e-04, 1.2238e-04, 2.8605e-05,\n -2.6611e-05, 7.9632e-05, -8.0774e-05, 2.0900e-04, -1.2416e-04,\n -1.5559e-04, 5.1897e-05, -2.3026e-04, -3.2187e-04, -1.0091e-04,\n 9.9587e-05, -7.9291e-06, 3.9303e-05, 2.8513e-05, -1.9129e-04,\n 1.8064e-04, 2.6736e-04, 0.0000e+00, 0.0000e+00, 2.4610e-05,\n 0.0000e+00, 9.6100e-05, 4.9804e-06, -1.4888e-04, 1.0076e-05,\n 2.5023e-06, 2.2428e-04, 5.7515e-06, 1.5137e-05, -7.6934e-05,\n -3.4460e-05, -1.2055e-04, 5.1809e-05, -1.6487e-04, -1.7205e-04,\n -4.1977e-06, -8.5301e-06, -1.2913e-04, -1.8105e-04, -5.3070e-05,\n 0.0000e+00, -1.0219e-05, 2.6046e-05, 1.1932e-04, -7.0902e-07,\n 5.7557e-05, -9.9773e-05, 0.0000e+00, 1.7003e-04, -6.0926e-05,\n -7.7165e-05, -4.1106e-06, -1.5290e-04, -2.5914e-05, -7.8494e-05,\n -1.3884e-05, -1.1094e-04, -9.6523e-05, 1.8387e-05, 0.0000e+00,\n 5.3471e-05, -6.3959e-06, -1.0840e-04, 6.7761e-05, 1.0702e-04,\n 1.8672e-05, 0.0000e+00, -1.5596e-05, 3.4683e-04, 1.8508e-04,\n -1.8558e-04, 5.6052e-45, -1.0550e-04, 1.3675e-05, -1.0574e-05,\n 1.3286e-05, 8.0451e-05, 7.2873e-05, 0.0000e+00, 1.0708e-04,\n 1.0171e-04, -1.8202e-04, 0.0000e+00, -3.7707e-04, 0.0000e+00,\n -3.9506e-04, 1.3939e-05, -2.8642e-04, 5.6052e-45, -6.6762e-07,\n 8.8169e-05, -6.6275e-05, -7.1026e-05, 2.7556e-05, 1.3388e-04,\n -1.6700e-04, 0.0000e+00, -1.6426e-04, 1.4894e-04, -1.3569e-04,\n 3.4735e-06, 4.6119e-05, 0.0000e+00, -4.6071e-05, -1.2164e-05,\n -1.7507e-04, 3.4677e-05, 9.6173e-05, 5.8866e-05, -6.9294e-05,\n 1.0905e-04, -1.4553e-04, 0.0000e+00, -1.5057e-05, 1.6754e-05,\n 7.5192e-05, 6.7397e-05, -7.6130e-05, 0.0000e+00, -4.4992e-05,\n -4.2591e-05, 1.4343e-04, 0.0000e+00, 1.5138e-04, -8.2941e-06,\n -5.7039e-05, -1.2057e-04, 1.4196e-04, 0.0000e+00, 0.0000e+00,\n -1.0349e-04, -1.6135e-04, -2.1787e-05, 3.8479e-05, -2.4011e-05,\n -1.9524e-05, 4.9054e-06, 5.2707e-05, -9.3493e-05, 4.3036e-05,\n -1.2569e-04, 5.9840e-05, 9.5915e-05, 2.1690e-04, -9.7707e-05,\n 1.0550e-05, -7.1002e-06, -9.0613e-05, -7.8175e-05, 3.3086e-05,\n -1.5847e-04, 4.8291e-05, 5.3410e-05, -8.5672e-06, 8.0684e-06,\n -1.1560e-04, -4.4501e-06, 1.4299e-04, 6.9599e-06, -5.8835e-05,\n -1.2068e-04, 2.4569e-05, -1.4745e-04, 9.2171e-05, -3.1829e-05,\n -2.9050e-05, -2.4117e-05, 3.5344e-05, -5.1934e-06, 0.0000e+00,\n 1.4367e-04, -7.8826e-05, -6.4235e-05, 9.8305e-05, -8.8477e-05,\n -3.6163e-05, 2.2624e-05, -1.4237e-04, -3.5687e-05, 9.0886e-05,\n 0.0000e+00, 1.4260e-04, 5.5705e-06, -8.0084e-07, 2.4835e-05,\n 6.1438e-05, -1.0880e-04, -6.4456e-04, 2.7526e-05, -2.5398e-05,\n -1.6124e-05, -1.0174e-04, 2.5300e-04, 1.1386e-04, 0.0000e+00,\n -7.7838e-05, 1.3619e-04, 0.0000e+00, -1.0304e-05, 0.0000e+00,\n 8.9870e-05, 1.6830e-04, 7.1222e-05, 9.3573e-05, -2.8563e-05,\n -1.4254e-04, 5.7442e-05, -8.6306e-05, 1.2254e-04, 0.0000e+00,\n -2.3597e-05, -6.3676e-05, 1.2265e-05, 4.1332e-05, -1.6975e-05,\n 4.7285e-04, -5.5872e-05, 5.5041e-05, 3.9504e-04, -1.3199e-05,\n -2.2674e-04, -3.2921e-04, 6.1405e-05, -3.1703e-04, 5.6551e-05,\n -6.8127e-06, 1.7217e-04, 2.3836e-04, 1.6971e-04, 1.7729e-05,\n -6.9820e-05, -1.5470e-04, 3.0731e-04, -1.5153e-04, 7.2049e-05,\n 1.7458e-04, -7.3870e-05, -8.4865e-04, 1.9973e-04, 4.0711e-05,\n 2.5935e-04, 0.0000e+00, -1.7366e-04, 1.4405e-04, 1.2397e-04,\n 6.8429e-05, -1.7686e-05, -1.1908e-04, 1.1179e-04, -9.8637e-06,\n -8.2084e-05]), 'exp_avg_sq': tensor([3.8778e-05, 4.1508e-05, 1.6254e-06, 5.4758e-06, 8.0671e-08, 5.2697e-06,\n 2.4090e-06, 2.3938e-06, 7.6537e-06, 1.4269e-06, 1.7519e-05, 2.0127e-06,\n 5.2135e-06, 2.5832e-05, 4.1255e-06, 2.5164e-06, 2.3386e-06, 1.4021e-06,\n 4.8449e-07, 9.7291e-06, 2.1001e-06, 3.9173e-06, 0.0000e+00, 0.0000e+00,\n 4.5090e-06, 0.0000e+00, 3.8680e-06, 3.0400e-06, 2.4608e-06, 2.5476e-06,\n 2.6696e-06, 5.6947e-06, 7.3151e-06, 1.2392e-06, 2.7367e-06, 4.1511e-06,\n 2.2061e-06, 1.9964e-06, 1.2594e-05, 2.0105e-06, 8.1114e-07, 3.6393e-06,\n 3.1407e-06, 2.8790e-06, 2.8970e-06, 0.0000e+00, 3.6010e-06, 1.6765e-06,\n 3.4666e-07, 2.2122e-06, 2.1218e-06, 1.7385e-06, 0.0000e+00, 1.8663e-06,\n 3.6037e-06, 3.7505e-06, 4.1844e-07, 2.3227e-06, 2.3562e-06, 3.9022e-06,\n 7.2258e-06, 2.7851e-06, 1.8192e-06, 1.3684e-06, 0.0000e+00, 1.0605e-05,\n 1.2834e-06, 2.6340e-06, 1.3799e-06, 8.3964e-06, 1.8810e-06, 0.0000e+00,\n 2.5291e-07, 1.0674e-05, 3.1035e-06, 1.7147e-06, 9.5187e-21, 1.9927e-06,\n 4.6837e-06, 1.7228e-06, 3.1576e-06, 5.3891e-06, 3.4807e-06, 0.0000e+00,\n 6.2956e-07, 9.6600e-07, 2.1036e-06, 0.0000e+00, 2.3489e-05, 0.0000e+00,\n 1.3431e-05, 5.1270e-07, 1.1131e-05, 4.4698e-16, 7.3125e-09, 6.2385e-07,\n 3.0445e-07, 2.0859e-06, 2.2636e-06, 1.8742e-06, 1.5470e-06, 0.0000e+00,\n 3.7729e-06, 2.3262e-06, 3.0856e-06, 4.1679e-06, 4.7079e-07, 0.0000e+00,\n 2.9123e-06, 9.4290e-07, 1.3123e-05, 2.1773e-06, 1.2347e-05, 2.2769e-06,\n 7.6678e-06, 2.6982e-06, 2.1970e-06, 0.0000e+00, 2.3556e-06, 2.2455e-06,\n 1.2799e-06, 7.1320e-07, 2.6737e-06, 0.0000e+00, 1.3694e-06, 4.2988e-06,\n 1.5825e-06, 0.0000e+00, 3.1380e-06, 2.5246e-06, 3.4553e-06, 1.5750e-06,\n 2.8019e-06, 0.0000e+00, 0.0000e+00, 1.7617e-06, 1.5092e-06, 1.6733e-06,\n 3.4434e-06, 7.8204e-07, 9.6323e-07, 2.0439e-06, 1.9452e-06, 1.0698e-06,\n 1.3053e-06, 5.2162e-06, 1.1724e-06, 2.9955e-06, 9.5643e-07, 1.7600e-06,\n 2.7776e-06, 2.3341e-06, 1.7715e-06, 3.5824e-06, 2.6016e-06, 2.9819e-06,\n 4.0174e-06, 2.5383e-06, 8.8079e-06, 2.6669e-06, 8.0022e-06, 5.7117e-06,\n 3.3418e-06, 9.9440e-09, 7.2450e-07, 2.3373e-06, 2.0245e-06, 5.0545e-06,\n 2.9572e-06, 1.4325e-06, 7.7833e-07, 2.0341e-06, 1.6397e-06, 1.4004e-06,\n 0.0000e+00, 3.1767e-06, 4.0644e-06, 1.5583e-06, 1.8688e-06, 3.3055e-06,\n 2.2029e-06, 2.6883e-06, 1.7905e-06, 2.7062e-06, 6.7732e-06, 0.0000e+00,\n 3.8590e-06, 1.3886e-06, 2.4665e-06, 2.2197e-06, 5.1529e-06, 9.4462e-06,\n 5.5686e-05, 2.2226e-06, 1.2091e-06, 6.3336e-06, 3.5001e-06, 2.1280e-06,\n 3.2402e-06, 0.0000e+00, 2.7995e-06, 1.3063e-06, 0.0000e+00, 3.8832e-07,\n 0.0000e+00, 1.2458e-06, 1.3637e-06, 1.5473e-06, 1.4380e-06, 1.6813e-06,\n 1.8029e-06, 5.2861e-06, 1.5441e-06, 2.1279e-06, 0.0000e+00, 4.4501e-06,\n 2.0197e-06, 2.8426e-06, 2.8437e-06, 2.0172e-06, 6.7185e-05, 1.1811e-06,\n 2.9168e-07, 2.7926e-05, 1.6981e-06, 1.7191e-06, 6.4528e-05, 1.5981e-06,\n 1.2516e-05, 9.5247e-07, 8.6073e-07, 4.7361e-06, 3.8463e-06, 3.6978e-06,\n 1.8189e-07, 8.9163e-06, 3.5575e-06, 3.6363e-05, 1.3345e-06, 4.7542e-07,\n 9.0701e-07, 1.3863e-06, 7.7790e-05, 4.0114e-06, 2.5681e-06, 3.2226e-06,\n 0.0000e+00, 3.6083e-06, 1.4741e-06, 2.2239e-06, 2.5991e-06, 1.7857e-05,\n 4.8854e-06, 1.4427e-05, 9.2954e-07, 1.9094e-06])}, 15: {'step': 7160, 'exp_avg': tensor([[[[ 4.1740e-05]],\n\n [[ 8.9538e-05]],\n\n [[ 2.6259e-05]],\n\n ...,\n\n [[ 2.4566e-05]],\n\n [[ 8.0669e-06]],\n\n [[-1.0516e-05]]],\n\n\n [[[ 4.8438e-05]],\n\n [[ 7.1557e-05]],\n\n [[-2.1626e-05]],\n\n ...,\n\n [[ 1.2985e-05]],\n\n [[ 6.6274e-05]],\n\n [[ 2.0315e-05]]],\n\n\n [[[ 1.7635e-05]],\n\n [[ 9.7099e-06]],\n\n [[ 5.9701e-06]],\n\n ...,\n\n [[ 1.0500e-05]],\n\n [[-4.3008e-05]],\n\n [[-2.8577e-05]]],\n\n\n ...,\n\n\n [[[ 3.0310e-06]],\n\n [[-1.8804e-05]],\n\n [[-3.0916e-05]],\n\n ...,\n\n [[-1.7859e-05]],\n\n [[-3.0743e-05]],\n\n [[-2.0943e-05]]],\n\n\n [[[-4.5225e-05]],\n\n [[-5.2497e-05]],\n\n [[-2.6376e-06]],\n\n ...,\n\n [[-1.9082e-05]],\n\n [[ 4.2985e-06]],\n\n [[ 5.9950e-06]]],\n\n\n [[[-5.3960e-05]],\n\n [[-6.3872e-05]],\n\n [[ 1.9454e-05]],\n\n ...,\n\n [[-3.7857e-05]],\n\n [[-3.1783e-05]],\n\n [[ 2.2575e-05]]]]), 'exp_avg_sq': tensor([[[[5.7163e-07]],\n\n [[1.2568e-06]],\n\n [[3.8030e-07]],\n\n ...,\n\n [[3.8410e-07]],\n\n [[9.3664e-07]],\n\n [[2.3996e-07]]],\n\n\n [[[1.7818e-07]],\n\n [[3.9372e-07]],\n\n [[5.0207e-08]],\n\n ...,\n\n [[1.1153e-07]],\n\n [[1.5367e-07]],\n\n [[2.7920e-08]]],\n\n\n [[[1.1879e-07]],\n\n [[3.3679e-07]],\n\n [[3.9678e-08]],\n\n ...,\n\n [[6.4428e-08]],\n\n [[1.0749e-07]],\n\n [[1.3000e-07]]],\n\n\n ...,\n\n\n [[[2.2157e-07]],\n\n [[4.3330e-07]],\n\n [[2.9769e-07]],\n\n ...,\n\n [[1.1999e-07]],\n\n [[5.9595e-07]],\n\n [[2.6381e-07]]],\n\n\n [[[1.0603e-07]],\n\n [[1.6900e-07]],\n\n [[7.8534e-08]],\n\n ...,\n\n [[8.7881e-08]],\n\n [[1.5936e-07]],\n\n [[4.0489e-08]]],\n\n\n [[[4.3336e-07]],\n\n [[8.5948e-07]],\n\n [[1.5566e-07]],\n\n ...,\n\n [[2.6772e-07]],\n\n [[3.1234e-07]],\n\n [[1.0446e-07]]]])}, 16: {'step': 7160, 'exp_avg': tensor([ 5.7655e-05, 7.3670e-05, -1.0060e-04, -4.3549e-05, -1.8235e-04,\n -4.5077e-05, -1.1138e-04, 9.7073e-05, -3.2718e-04, -1.3258e-04,\n -1.7877e-04, 1.0112e-04, 4.6755e-05, 0.0000e+00, 1.0811e-04,\n -1.4271e-04, 2.8081e-05, -1.5211e-04, 1.1806e-04, 2.0199e-05,\n -1.0733e-05, -2.2556e-05, -3.8222e-05, -2.0229e-04, -1.4177e-04,\n -2.9357e-04, -7.7165e-05, 1.5493e-04, 5.5523e-04, 4.4309e-05,\n -2.0060e-04, 5.7107e-05, 5.2669e-05, -1.3607e-04, 2.9507e-04,\n -2.0959e-04, 2.1861e-05, 2.6935e-04, -1.4378e-04, 4.0242e-05,\n -1.7664e-04, -1.4152e-04, -3.0404e-04, 1.6753e-04, 8.6159e-05,\n 0.0000e+00, -2.2019e-04, 0.0000e+00, -6.0600e-05, -7.2362e-05,\n -9.5140e-05, 1.5458e-04, -3.2891e-04, 2.6525e-05, 3.3256e-05,\n 5.2280e-05, 0.0000e+00, 2.6441e-04, 1.8344e-05, -2.8884e-04,\n 4.0638e-04, -5.6007e-04, -1.2066e-04, -1.1473e-04]), 'exp_avg_sq': tensor([7.7646e-06, 5.4011e-06, 4.1912e-06, 6.0012e-06, 4.5878e-06, 9.1598e-06,\n 2.9894e-06, 4.0114e-06, 1.0689e-05, 3.0413e-06, 4.4930e-06, 3.0921e-06,\n 7.6313e-06, 0.0000e+00, 5.9117e-06, 3.0030e-06, 8.4554e-06, 4.1922e-06,\n 4.7768e-06, 6.2625e-06, 5.4889e-06, 6.5835e-06, 5.3147e-06, 4.2655e-06,\n 9.3279e-06, 5.1094e-06, 4.3568e-06, 2.5235e-05, 9.3175e-06, 2.5420e-06,\n 6.3424e-06, 4.5839e-06, 2.3405e-05, 3.3917e-06, 2.9992e-06, 3.3007e-06,\n 4.2147e-05, 1.2768e-05, 5.2106e-06, 3.7579e-06, 6.5735e-06, 6.1598e-06,\n 5.0362e-06, 3.1719e-06, 1.2295e-05, 0.0000e+00, 4.5771e-06, 0.0000e+00,\n 6.9969e-06, 1.1023e-05, 9.6419e-06, 6.2838e-06, 2.8137e-05, 9.7847e-06,\n 1.5192e-05, 5.0731e-06, 0.0000e+00, 2.0591e-05, 7.6528e-06, 8.5995e-06,\n 5.0815e-06, 1.8380e-05, 8.7565e-06, 4.6769e-06])}, 17: {'step': 7160, 'exp_avg': tensor([-5.8003e-05, 9.7905e-05, -1.1999e-04, 1.1230e-04, -3.3146e-05,\n -3.8892e-05, -1.5202e-04, 4.3274e-05, 4.5682e-05, -8.8205e-05,\n -2.3228e-04, 4.6178e-05, -1.5526e-05, 0.0000e+00, 9.6568e-05,\n 2.3251e-05, -1.0535e-04, -6.1307e-05, 2.9375e-05, -3.3703e-05,\n -2.1876e-04, 2.0779e-04, -1.6835e-04, -1.3360e-04, 2.9386e-04,\n 1.5718e-04, -5.2760e-05, 4.2086e-05, 1.7725e-04, 8.6256e-06,\n -1.5591e-04, -3.6151e-05, 1.2343e-04, -6.9544e-05, 2.0748e-04,\n -1.7760e-04, -9.9257e-05, 1.7914e-04, -2.3658e-04, -2.2389e-04,\n -1.7998e-04, -1.1549e-04, -1.4114e-04, 1.0084e-04, 2.3049e-05,\n 0.0000e+00, -1.5791e-04, 0.0000e+00, -9.9643e-05, -2.7048e-05,\n -1.7277e-05, 3.3128e-06, 1.3272e-04, 2.0305e-05, 9.7227e-05,\n -9.2190e-06, 0.0000e+00, 7.4020e-05, 5.7157e-05, 2.3972e-04,\n 5.7191e-05, 4.1800e-05, -4.4291e-05, -3.8708e-04]), 'exp_avg_sq': tensor([3.7949e-06, 3.4412e-06, 2.9680e-06, 5.0080e-06, 6.0491e-06, 5.9642e-06,\n 2.5932e-06, 2.1174e-06, 4.6016e-06, 8.8178e-07, 3.5382e-06, 2.2201e-06,\n 5.6897e-06, 0.0000e+00, 5.9778e-06, 2.7363e-06, 5.2544e-06, 4.3705e-06,\n 2.8829e-06, 1.0255e-06, 3.0738e-06, 5.7295e-06, 4.0067e-06, 4.7309e-06,\n 3.0864e-06, 2.5168e-06, 4.2832e-06, 1.5387e-06, 3.8136e-06, 2.5537e-06,\n 4.0932e-06, 1.2785e-05, 1.2713e-05, 2.2813e-06, 5.2799e-06, 1.4934e-06,\n 1.7121e-06, 5.1469e-06, 3.2080e-06, 3.7172e-06, 4.0508e-06, 3.6305e-06,\n 1.4591e-06, 2.8906e-06, 8.7465e-07, 0.0000e+00, 1.8959e-06, 0.0000e+00,\n 2.9235e-06, 1.6885e-06, 3.5231e-06, 6.7431e-06, 2.1493e-06, 1.1076e-05,\n 1.0933e-06, 3.2109e-06, 0.0000e+00, 1.2338e-06, 3.5080e-06, 3.0874e-06,\n 5.3858e-06, 1.6464e-06, 2.8410e-06, 4.4371e-06])}, 18: {'step': 7160, 'exp_avg': tensor([[[[-1.7393e-05, -2.2645e-06, -6.8765e-06],\n [-3.0878e-06, 1.4052e-06, 2.0894e-06],\n [ 5.5447e-05, 5.7573e-05, 6.0463e-05]],\n\n [[-3.9204e-05, -4.3623e-05, -3.9462e-05],\n [ 5.4167e-05, 5.9706e-05, 7.7745e-05],\n [-1.0625e-05, -8.9691e-06, -5.3523e-06]],\n\n [[-3.8937e-06, -5.6967e-05, -3.4906e-05],\n [-3.4407e-05, -7.1934e-05, -4.4800e-05],\n [-1.6836e-05, -3.6937e-05, -2.8020e-05]],\n\n ...,\n\n [[-5.7457e-05, -8.2560e-05, -7.1945e-05],\n [-1.0333e-04, -1.2363e-04, -9.2856e-05],\n [ 6.7831e-06, 7.3332e-06, 2.2824e-05]],\n\n [[ 9.2862e-06, 8.3367e-06, 8.1530e-06],\n [ 7.4188e-05, 8.8483e-05, 6.8991e-05],\n [ 3.7706e-05, 4.4133e-05, 3.5113e-05]],\n\n [[ 1.8526e-05, 1.6473e-05, 9.8968e-06],\n [-6.6292e-05, -7.2736e-05, -8.1083e-05],\n [-1.1206e-05, -1.8403e-05, -6.2262e-06]]],\n\n\n [[[ 5.2057e-05, 6.0917e-05, 5.8577e-05],\n [ 6.5800e-05, 6.6217e-05, 5.5903e-05],\n [ 8.1615e-05, 7.6913e-05, 7.3555e-05]],\n\n [[-9.0201e-06, 6.3851e-06, -8.4344e-06],\n [ 1.4402e-05, 3.3900e-05, 1.4077e-05],\n [-1.6214e-05, 2.0282e-05, 2.3977e-05]],\n\n [[ 2.6494e-06, 8.4597e-06, 1.1024e-05],\n [-6.7934e-07, 1.6408e-06, 6.2579e-06],\n [-3.5163e-06, -2.2014e-06, 3.9839e-06]],\n\n ...,\n\n [[-1.4194e-05, -1.4425e-05, 4.8753e-06],\n [-5.0608e-06, -1.2643e-05, 1.1734e-05],\n [-1.4927e-05, -2.7795e-05, -3.2426e-06]],\n\n [[-6.6652e-05, -5.0414e-05, -4.7593e-05],\n [-7.0078e-05, -5.0586e-05, -4.0379e-05],\n [-3.1789e-05, -8.2784e-06, -2.2301e-05]],\n\n [[ 3.4024e-05, 3.3637e-05, 2.8467e-05],\n [ 3.7672e-05, 2.0209e-05, 1.9219e-05],\n [ 3.4512e-05, 2.2164e-05, 1.3785e-05]]],\n\n\n [[[ 2.1784e-06, -4.9976e-06, 2.7467e-05],\n [ 1.5030e-06, 9.2500e-06, 2.9454e-05],\n [ 1.9460e-05, 2.0633e-05, 6.3724e-06]],\n\n [[ 3.3061e-05, 7.1172e-06, -1.8050e-05],\n [ 7.5939e-06, 1.2885e-05, 1.5368e-06],\n [ 7.3984e-06, 1.0675e-05, -4.8915e-06]],\n\n [[ 7.2442e-06, 9.6848e-06, -2.7614e-06],\n [ 1.3442e-05, -4.0086e-06, -1.8030e-05],\n [ 1.8996e-05, -4.0356e-06, -1.1434e-06]],\n\n ...,\n\n [[ 7.8942e-05, 5.2462e-05, 4.3541e-05],\n [ 5.8062e-05, 3.8837e-06, 3.3230e-05],\n [ 4.0618e-05, 1.3499e-05, 4.9431e-05]],\n\n [[ 5.7717e-06, 7.0220e-06, 1.0180e-05],\n [ 7.1518e-06, 4.0223e-06, 3.2417e-05],\n [-1.3252e-05, -2.8205e-06, 2.3324e-05]],\n\n [[-2.4463e-05, 3.4722e-05, 3.3021e-05],\n [-8.4211e-06, 2.1391e-07, -1.3759e-05],\n [ 3.2839e-05, -1.1881e-06, -8.3005e-06]]],\n\n\n ...,\n\n\n [[[ 1.8179e-05, -2.3435e-05, -1.1103e-05],\n [-8.3427e-06, -2.0850e-05, 6.0172e-06],\n [-1.5422e-05, -2.4181e-05, -1.8913e-05]],\n\n [[ 8.8186e-05, -3.0168e-06, 6.4929e-07],\n [ 7.1808e-05, 1.3687e-06, 1.5408e-05],\n [ 4.7356e-05, 2.0526e-05, 3.2459e-05]],\n\n [[-1.8185e-06, 3.1164e-05, 2.0304e-05],\n [-2.4003e-05, 1.4331e-05, -3.5328e-06],\n [-1.4837e-05, 9.5741e-07, -1.4126e-05]],\n\n ...,\n\n [[ 6.4393e-05, 5.7128e-05, -6.1712e-05],\n [-3.8080e-05, 1.0507e-05, -6.1526e-05],\n [-3.3886e-05, 2.7545e-05, -2.0396e-05]],\n\n [[ 1.4091e-05, 1.6038e-05, -2.5455e-06],\n [ 4.5241e-05, 4.2148e-05, 2.7416e-05],\n [ 2.7561e-05, 9.6477e-06, 2.5537e-06]],\n\n [[ 7.0774e-06, 6.6327e-05, 4.3067e-05],\n [-4.8652e-05, -8.0166e-06, -1.9781e-05],\n [-5.9919e-05, -2.8636e-05, -1.8514e-05]]],\n\n\n [[[ 5.2950e-05, 3.4465e-05, 5.4650e-06],\n [ 1.4391e-05, 3.2806e-05, 1.8782e-06],\n [ 2.5213e-05, 3.6101e-05, -2.0408e-05]],\n\n [[-2.5565e-05, 4.1218e-05, 1.7261e-05],\n [-3.7210e-05, 4.0328e-06, 4.1401e-05],\n [-1.9927e-05, 3.0051e-05, 2.6327e-05]],\n\n [[-3.4823e-05, -7.4955e-05, -3.7699e-05],\n [-1.5904e-05, -5.2850e-05, -7.1508e-06],\n [-2.0292e-05, -2.2081e-05, 3.4337e-06]],\n\n ...,\n\n [[-1.6113e-06, -5.1676e-05, -2.4997e-05],\n [-3.6137e-05, -4.2322e-07, 1.9935e-05],\n [-4.5381e-05, -1.0017e-05, 5.0599e-05]],\n\n [[ 4.7718e-06, 6.8961e-06, 1.5643e-05],\n [ 2.5740e-05, 4.0106e-05, 6.3666e-05],\n [ 2.7016e-05, 1.4283e-05, 2.3585e-05]],\n\n [[ 8.4661e-06, -1.9620e-05, -1.1135e-05],\n [ 3.6103e-05, -2.6312e-05, -7.5224e-05],\n [ 1.0638e-05, -3.7156e-05, -5.2436e-05]]],\n\n\n [[[ 1.2831e-05, 9.3061e-07, -1.7801e-05],\n [-1.5605e-05, -2.2259e-05, -4.7066e-05],\n [-2.6298e-05, -4.0172e-05, -4.0546e-05]],\n\n [[ 1.8586e-05, -1.1435e-05, 6.4150e-05],\n [ 6.3790e-06, -1.6535e-05, 4.4805e-05],\n [ 6.6111e-05, -1.1679e-06, 4.0943e-05]],\n\n [[ 2.4201e-05, 1.8017e-05, -1.1130e-05],\n [ 1.9301e-05, 3.0998e-05, -3.6335e-05],\n [-6.9747e-06, 1.6191e-05, -3.9852e-05]],\n\n ...,\n\n [[ 1.3894e-05, 3.4288e-05, -2.9430e-05],\n [-1.4222e-06, 3.3474e-05, -2.6482e-05],\n [-1.4429e-05, 8.0850e-05, 2.9996e-05]],\n\n [[-1.0847e-05, -1.9649e-06, -2.8856e-05],\n [-7.0572e-07, 1.0908e-05, -2.7167e-05],\n [-5.2527e-06, -7.9269e-06, -1.6495e-05]],\n\n [[ 2.8018e-06, -1.7948e-05, -8.8217e-06],\n [-5.5062e-06, -2.5758e-05, -3.3192e-05],\n [-5.4618e-05, -2.6710e-05, -4.6742e-05]]]]), 'exp_avg_sq': tensor([[[[8.5667e-08, 8.6409e-08, 9.9535e-08],\n [5.7905e-08, 5.2265e-08, 7.0927e-08],\n [4.2885e-08, 4.0132e-08, 4.9840e-08]],\n\n [[3.5146e-08, 4.8720e-08, 3.4595e-08],\n [4.6455e-08, 6.6258e-08, 6.3988e-08],\n [9.4886e-09, 3.1189e-08, 2.9809e-08]],\n\n [[4.2358e-08, 1.0416e-07, 6.8330e-08],\n [5.5251e-08, 8.4796e-08, 6.6409e-08],\n [5.1191e-08, 7.1176e-08, 4.2513e-08]],\n\n ...,\n\n [[1.2523e-07, 8.9444e-08, 7.4608e-08],\n [1.1027e-07, 9.1696e-08, 8.1101e-08],\n [7.3470e-08, 7.3868e-08, 7.8656e-08]],\n\n [[2.6920e-08, 2.5733e-08, 1.3249e-08],\n [4.0031e-08, 4.4875e-08, 2.6389e-08],\n [1.1185e-08, 1.4168e-08, 1.2825e-08]],\n\n [[3.9864e-08, 4.0007e-08, 3.3929e-08],\n [1.3894e-07, 1.6650e-07, 1.7347e-07],\n [4.3993e-08, 2.6537e-08, 2.4628e-08]]],\n\n\n [[[8.3628e-08, 1.1500e-07, 1.1362e-07],\n [8.7926e-08, 1.0744e-07, 1.1172e-07],\n [1.0344e-07, 1.0887e-07, 1.3541e-07]],\n\n [[4.5244e-08, 4.8492e-08, 3.1569e-08],\n [9.9542e-08, 3.4780e-08, 7.1890e-08],\n [3.6788e-08, 3.0566e-08, 8.8631e-08]],\n\n [[1.6601e-08, 2.8238e-08, 2.1848e-08],\n [1.7770e-08, 1.8129e-08, 3.2454e-08],\n [1.5483e-08, 1.7038e-08, 2.3098e-08]],\n\n ...,\n\n [[3.3687e-08, 3.3362e-08, 4.1812e-08],\n [3.6773e-08, 5.4562e-08, 5.5259e-08],\n [3.9781e-08, 3.1165e-08, 4.9052e-08]],\n\n [[8.3093e-08, 8.3939e-08, 7.4087e-08],\n [9.2704e-08, 1.1299e-07, 6.7623e-08],\n [1.0758e-07, 7.7515e-08, 6.3552e-08]],\n\n [[5.8780e-08, 6.1687e-08, 2.8083e-08],\n [3.9955e-08, 4.4282e-08, 3.3541e-08],\n [2.1227e-08, 2.0367e-08, 2.7893e-08]]],\n\n\n [[[2.3648e-07, 2.9140e-07, 3.3043e-07],\n [2.5111e-07, 3.5421e-07, 4.1187e-07],\n [2.8747e-07, 3.5668e-07, 3.3676e-07]],\n\n [[9.7326e-08, 3.9555e-08, 2.9214e-08],\n [6.4356e-08, 2.7902e-08, 3.5675e-08],\n [6.7019e-08, 4.3818e-08, 5.2798e-08]],\n\n [[1.3608e-07, 1.3094e-07, 5.2086e-08],\n [1.4158e-07, 1.0228e-07, 5.8418e-08],\n [1.4442e-07, 7.6943e-08, 5.0768e-08]],\n\n ...,\n\n [[2.1166e-07, 1.3828e-07, 1.1935e-07],\n [3.0364e-07, 1.9980e-07, 1.1188e-07],\n [2.1881e-07, 1.3627e-07, 2.2151e-07]],\n\n [[6.0203e-09, 9.3761e-09, 3.0680e-08],\n [6.7727e-09, 1.2342e-08, 5.7015e-08],\n [1.7433e-08, 1.8049e-08, 2.3788e-08]],\n\n [[1.7084e-07, 1.6020e-07, 1.6059e-07],\n [1.4309e-07, 1.0085e-07, 1.0882e-07],\n [1.9443e-07, 1.2923e-07, 9.4785e-08]]],\n\n\n ...,\n\n\n [[[2.9112e-07, 3.8307e-07, 4.3286e-07],\n [5.6166e-07, 4.0388e-07, 3.6884e-07],\n [3.7461e-07, 3.7964e-07, 4.0988e-07]],\n\n [[2.2488e-07, 1.3282e-07, 1.1991e-07],\n [1.9470e-07, 2.1678e-07, 1.3598e-07],\n [2.0700e-07, 2.3255e-07, 1.1821e-07]],\n\n [[1.5946e-07, 1.9630e-07, 9.2906e-08],\n [8.2412e-08, 2.4436e-07, 1.2310e-07],\n [9.9725e-08, 1.4397e-07, 1.0224e-07]],\n\n ...,\n\n [[2.4730e-07, 2.7672e-07, 3.7746e-07],\n [2.6305e-07, 1.8569e-07, 3.1430e-07],\n [1.9802e-07, 2.1733e-07, 2.8342e-07]],\n\n [[7.7841e-08, 1.2843e-07, 9.6511e-08],\n [8.2793e-08, 1.2726e-07, 5.7267e-08],\n [8.4047e-08, 9.6551e-08, 9.3462e-08]],\n\n [[2.0572e-07, 2.8935e-07, 2.0840e-07],\n [2.5351e-07, 2.2608e-07, 2.5301e-07],\n [3.9770e-07, 3.4681e-07, 3.4259e-07]]],\n\n\n [[[5.1911e-07, 5.9460e-07, 4.2805e-07],\n [1.0645e-06, 7.9550e-07, 5.0702e-07],\n [9.4115e-07, 6.0664e-07, 3.9966e-07]],\n\n [[1.3585e-07, 5.2709e-08, 6.1095e-08],\n [1.0875e-07, 5.6160e-08, 5.1881e-08],\n [8.2952e-08, 5.5010e-08, 9.5904e-08]],\n\n [[1.4687e-07, 4.7410e-07, 1.6649e-07],\n [1.4703e-07, 3.3445e-07, 1.5418e-07],\n [1.3412e-07, 4.2314e-07, 1.5537e-07]],\n\n ...,\n\n [[2.0351e-07, 3.6831e-07, 2.9108e-07],\n [2.2614e-07, 3.6056e-07, 2.2596e-07],\n [2.2298e-07, 2.5243e-07, 2.5131e-07]],\n\n [[6.6023e-08, 8.4998e-08, 1.2614e-07],\n [8.8698e-08, 1.0988e-07, 1.8081e-07],\n [1.2930e-07, 1.3112e-07, 1.7698e-07]],\n\n [[4.7281e-07, 2.5388e-07, 3.8587e-07],\n [8.3085e-07, 2.9629e-07, 3.5026e-07],\n [6.7979e-07, 2.3573e-07, 3.1742e-07]]],\n\n\n [[[2.3033e-07, 1.8948e-07, 2.1373e-07],\n [2.5144e-07, 2.1917e-07, 3.1162e-07],\n [2.4922e-07, 3.8865e-07, 3.5958e-07]],\n\n [[1.4263e-07, 1.4888e-07, 1.0195e-07],\n [1.4647e-07, 3.2749e-07, 9.7986e-08],\n [1.8028e-07, 3.4183e-07, 9.4850e-08]],\n\n [[1.3951e-07, 1.4268e-07, 1.4681e-07],\n [1.4078e-07, 1.2143e-07, 1.9051e-07],\n [9.8576e-08, 1.4684e-07, 2.2373e-07]],\n\n ...,\n\n [[2.9870e-07, 2.2379e-07, 3.8228e-07],\n [3.2807e-07, 3.9929e-07, 4.0342e-07],\n [3.7870e-07, 6.6772e-07, 4.6817e-07]],\n\n [[6.4038e-08, 7.2322e-08, 8.2402e-08],\n [4.4950e-08, 2.1607e-08, 1.3773e-07],\n [7.3203e-08, 7.9808e-08, 8.4444e-08]],\n\n [[4.5341e-07, 2.5277e-07, 1.9824e-07],\n [2.8271e-07, 2.3899e-07, 1.8794e-07],\n [2.4496e-07, 2.1059e-07, 4.6211e-07]]]])}, 19: {'step': 7160, 'exp_avg': tensor([ 3.9868e-04, -3.7090e-04, 3.7594e-05, 7.0836e-05, 2.2028e-04,\n -1.9122e-04, -1.7213e-04, 7.7270e-05, 8.0766e-05, 6.1868e-05,\n -1.3394e-04, 1.8297e-04, -1.1347e-04, -5.0542e-05, -6.7899e-04,\n 5.2959e-05, -1.1399e-04, 3.1400e-05, 1.2011e-04, 2.9759e-05,\n 4.0647e-05, 1.5785e-04, -9.1133e-06, 3.4221e-06, -7.6382e-06,\n 2.4039e-04, -3.7871e-05, 1.3806e-04, -6.3628e-05, -1.9102e-04,\n -1.7027e-04, -1.3784e-04, 1.0847e-04, -2.9847e-05, -2.1917e-05,\n 3.9154e-06, 1.7481e-04, 1.6401e-04, -2.6715e-04, -1.0593e-04,\n 7.9096e-05, 4.6503e-05, -1.8851e-04, 9.1062e-06, -1.6086e-04,\n 1.4048e-04, -2.6283e-06, 8.7297e-05, -3.9426e-05, 1.5416e-04,\n 2.0272e-04, 1.1316e-04, -3.5943e-04, -5.8798e-05, 2.9757e-04,\n -3.1985e-04, 2.6144e-04, 2.5334e-04, -1.3314e-04, -8.0448e-05,\n 1.9658e-04, -1.1839e-04, -2.0674e-04, -1.3311e-04]), 'exp_avg_sq': tensor([1.0533e-05, 8.5022e-06, 3.8467e-06, 2.5247e-06, 6.6455e-06, 3.1171e-05,\n 6.9895e-06, 3.5651e-06, 1.2946e-05, 1.1342e-05, 2.5686e-06, 5.1323e-06,\n 2.7473e-06, 3.2880e-06, 1.9516e-05, 4.4650e-06, 4.9453e-06, 5.6327e-06,\n 5.3014e-06, 3.3746e-06, 8.0173e-06, 2.1366e-06, 1.6880e-05, 7.8029e-06,\n 8.9523e-06, 1.4180e-06, 2.0971e-05, 1.3902e-06, 2.6742e-05, 2.4829e-05,\n 3.8964e-06, 1.3274e-05, 3.6679e-06, 3.4134e-06, 4.1000e-06, 2.5774e-06,\n 1.8325e-05, 1.1955e-05, 2.4600e-06, 2.9284e-06, 4.4608e-06, 2.0556e-06,\n 7.8816e-06, 3.8154e-06, 3.5896e-06, 1.1717e-05, 2.2427e-06, 3.7753e-06,\n 2.9992e-06, 3.1464e-06, 5.5697e-06, 8.4401e-06, 6.5181e-06, 5.4943e-06,\n 2.5987e-05, 5.1896e-06, 1.1452e-05, 3.2437e-06, 3.7413e-06, 5.7223e-06,\n 1.0856e-05, 9.2843e-06, 6.0410e-06, 4.0476e-06])}, 20: {'step': 7160, 'exp_avg': tensor([ 1.3791e-04, -1.4688e-04, -1.0769e-04, 1.7798e-04, 1.6874e-04,\n 1.8167e-05, -1.3998e-04, 1.4467e-04, -1.0264e-05, 2.4371e-04,\n -6.5258e-05, 8.6417e-05, -8.5450e-05, 1.0196e-04, 1.1255e-04,\n -1.9499e-05, 1.4456e-04, 6.3134e-05, 9.5814e-05, 5.4427e-05,\n -5.4085e-05, 5.7444e-05, 1.4677e-04, 1.4766e-05, -1.0210e-04,\n 1.4656e-04, 5.3629e-05, 9.1058e-05, -6.6476e-06, -2.0356e-05,\n -8.2111e-05, -1.8313e-04, 3.8120e-05, -4.4806e-05, 1.0234e-04,\n 9.1343e-05, 8.9034e-06, 1.3627e-04, -2.1461e-04, -2.3857e-05,\n -1.4468e-06, 3.0244e-05, -9.6231e-05, 3.7268e-05, -1.9642e-04,\n 1.0989e-04, 1.2171e-05, 9.9908e-05, -9.7627e-05, 6.6140e-05,\n 2.7139e-04, 1.2576e-04, -2.1822e-04, -3.9380e-06, 7.5617e-06,\n -8.3359e-05, -1.7200e-05, 8.5452e-05, -5.3970e-05, -1.9198e-04,\n 9.0857e-05, 4.4750e-05, -1.6615e-04, -1.2664e-04]), 'exp_avg_sq': tensor([4.7771e-07, 4.3135e-06, 2.0539e-06, 4.4967e-06, 3.3171e-06, 1.9295e-07,\n 4.1193e-06, 3.0040e-06, 4.3916e-07, 9.2732e-06, 1.4739e-06, 4.8230e-06,\n 1.2776e-06, 3.2670e-06, 5.9972e-06, 2.1831e-06, 4.2220e-06, 2.9032e-06,\n 3.8214e-06, 2.2763e-06, 4.1042e-06, 9.7757e-07, 6.7380e-06, 3.1991e-06,\n 3.5825e-06, 5.4935e-07, 8.7738e-07, 6.0918e-07, 6.8622e-07, 7.2646e-07,\n 2.0605e-06, 7.5559e-06, 3.2734e-06, 2.5964e-06, 3.6384e-06, 3.7820e-06,\n 1.7045e-06, 6.6718e-06, 1.8889e-06, 1.8352e-06, 5.6958e-07, 1.5140e-06,\n 5.0370e-06, 3.2627e-06, 3.7894e-06, 9.3525e-06, 1.2300e-06, 5.5908e-06,\n 1.2219e-06, 1.2896e-06, 4.3037e-06, 8.2603e-06, 5.4207e-06, 3.6325e-06,\n 3.5661e-07, 3.6167e-06, 1.4648e-06, 1.5666e-06, 1.8766e-06, 3.8878e-06,\n 4.3416e-06, 1.3167e-06, 5.3298e-06, 2.5821e-06])}, 21: {'step': 7160, 'exp_avg': tensor([[[[-2.4883e-06]],\n\n [[-3.2379e-06]],\n\n [[ 5.0615e-06]],\n\n ...,\n\n [[ 1.0467e-05]],\n\n [[ 5.5392e-06]],\n\n [[ 2.8812e-06]]],\n\n\n [[[ 3.0343e-07]],\n\n [[ 9.7631e-07]],\n\n [[-4.4601e-07]],\n\n ...,\n\n [[-4.1072e-06]],\n\n [[-1.4126e-06]],\n\n [[ 5.0020e-07]]],\n\n\n [[[-1.0441e-04]],\n\n [[-6.9788e-06]],\n\n [[-1.5638e-05]],\n\n ...,\n\n [[-1.0745e-05]],\n\n [[-2.6555e-05]],\n\n [[-4.3895e-05]]],\n\n\n ...,\n\n\n [[[-1.3165e-07]],\n\n [[-1.8946e-08]],\n\n [[-2.8515e-08]],\n\n ...,\n\n [[ 9.6713e-07]],\n\n [[ 2.5615e-07]],\n\n [[ 2.0273e-07]]],\n\n\n [[[ 7.9249e-05]],\n\n [[ 4.1869e-05]],\n\n [[-1.5653e-05]],\n\n ...,\n\n [[-7.9832e-05]],\n\n [[ 2.5305e-06]],\n\n [[ 3.4716e-07]]],\n\n\n [[[-1.6828e-06]],\n\n [[-3.7585e-05]],\n\n [[ 7.8194e-05]],\n\n ...,\n\n [[ 8.7409e-05]],\n\n [[ 2.2975e-06]],\n\n [[ 7.0344e-05]]]]), 'exp_avg_sq': tensor([[[[1.0713e-09]],\n\n [[3.6292e-09]],\n\n [[7.1978e-09]],\n\n ...,\n\n [[1.3136e-08]],\n\n [[2.3484e-09]],\n\n [[9.2524e-09]]],\n\n\n [[[4.5685e-10]],\n\n [[8.1208e-10]],\n\n [[5.5328e-09]],\n\n ...,\n\n [[4.5547e-09]],\n\n [[1.3677e-09]],\n\n [[9.6203e-09]]],\n\n\n [[[7.2789e-07]],\n\n [[8.2644e-08]],\n\n [[2.6896e-07]],\n\n ...,\n\n [[7.8168e-07]],\n\n [[3.4999e-07]],\n\n [[2.3076e-07]]],\n\n\n ...,\n\n\n [[[1.9036e-10]],\n\n [[1.4045e-09]],\n\n [[1.1656e-09]],\n\n ...,\n\n [[2.1932e-09]],\n\n [[4.3881e-10]],\n\n [[1.3054e-09]]],\n\n\n [[[2.8807e-07]],\n\n [[6.7545e-08]],\n\n [[1.3360e-07]],\n\n ...,\n\n [[3.2139e-07]],\n\n [[1.4080e-07]],\n\n [[1.6996e-07]]],\n\n\n [[[3.2090e-07]],\n\n [[1.4339e-07]],\n\n [[3.6455e-07]],\n\n ...,\n\n [[6.5581e-07]],\n\n [[3.4442e-07]],\n\n [[5.8512e-07]]]])}, 22: {'step': 7160, 'exp_avg': tensor([-5.8663e-05, -6.7411e-05, 2.1159e-04, 1.0023e-04, 6.8216e-06,\n 1.2033e-04, 1.0141e-04, 4.3844e-05, -2.1998e-04, 3.2274e-04,\n -8.5128e-05, 2.9828e-04, 9.0582e-06, -2.7699e-04, 3.2897e-04,\n 7.1001e-05, 2.2295e-04, -4.0480e-05, 1.2060e-05, -3.2347e-04,\n 2.3850e-05, 5.9440e-05, 1.0399e-04, 2.1672e-04, 2.6501e-05,\n 1.1510e-05, 4.2089e-05, 2.0862e-04, -3.8334e-05, -3.6939e-05,\n 1.2185e-04, -5.4980e-05, 1.1051e-04, 1.9031e-05, -2.5291e-05,\n -4.7487e-06, -5.7874e-05, 1.3742e-04, -1.6313e-05, -2.1530e-05,\n 1.1009e-04, 1.7309e-04, 6.9700e-05, 1.7858e-06, 1.1980e-04,\n -8.1887e-05, 1.6525e-04, 6.0955e-05, 3.6903e-05, -7.0450e-06,\n -7.4808e-06, 1.1620e-04, -3.9492e-05, 1.6799e-04, 4.9176e-05,\n -2.1709e-04, -4.0920e-04, -3.8727e-04, -4.9147e-05, 4.1502e-05,\n -1.1859e-06, -1.8867e-04, 5.9901e-05, -2.3177e-04, 0.0000e+00,\n 4.9270e-05, 5.4983e-05, 1.2429e-04, 4.7467e-05, 3.9075e-05,\n 3.3758e-05, 0.0000e+00, 3.9258e-05, -2.3966e-05, 1.6411e-04,\n 1.9620e-04, -3.2331e-05, 3.6577e-05, -1.9740e-04, 1.2263e-04,\n 1.6872e-04, -9.0045e-05, 8.9138e-05, -3.1386e-05, 9.3710e-05,\n 2.4224e-04, -7.6219e-06, 8.6505e-05, 8.0952e-05, 0.0000e+00,\n 1.3774e-04, -4.6170e-05, 2.7318e-05, 9.1730e-05, -1.0111e-05,\n 1.6762e-04, -4.7447e-05, -2.3812e-04, 1.8572e-04, -1.0030e-04,\n -2.1317e-04, 0.0000e+00, -6.5204e-05, -6.5349e-05, 1.9798e-04,\n -1.7550e-04, 1.3797e-04, -1.1514e-04, -1.3435e-05, -2.6165e-04,\n 7.8400e-05, -1.7872e-05, 7.6587e-05, -1.3159e-04, 1.9798e-04,\n 2.3466e-05, 3.2900e-04, 1.4822e-05, 1.8622e-04, 2.8950e-04,\n -2.3914e-05, 1.9019e-04, 3.9664e-04, 0.0000e+00, 9.2588e-05,\n -4.0135e-05, 7.3453e-05, 0.0000e+00, -1.3897e-04, 1.9931e-04,\n 3.0869e-04, 6.0821e-05, 1.9236e-04, 2.4671e-05, 2.1049e-04,\n -7.2096e-05, -2.0490e-04, 1.2035e-04, 3.1800e-04, -4.3409e-05,\n -1.0265e-04, 4.2891e-04, 1.3953e-05, 3.3617e-04, 6.0293e-05,\n -1.8016e-04, -8.5843e-05, -1.2172e-04, 3.3748e-04, -7.7884e-05,\n -2.4342e-05, 1.6949e-05, 8.4410e-05, -2.9768e-05, 1.0163e-04,\n 1.3864e-05, -2.7500e-04, 2.1718e-04, -9.3963e-05, -2.2576e-04,\n -7.4579e-05, -9.6391e-05, -3.0714e-05, 1.0667e-04, -2.1667e-05,\n 1.7465e-04, 1.1647e-04, 4.4577e-05, -1.2998e-05, -5.6849e-05,\n 8.6929e-05, -1.7030e-05, -2.7644e-04, -8.8070e-05, 1.2164e-04,\n 1.1835e-04, -1.4273e-04, -7.8881e-06, -5.1014e-06, -3.2325e-05,\n 1.1805e-05, 9.1796e-05, 1.0922e-04, 1.6441e-04, 1.6331e-04,\n 0.0000e+00, 2.3775e-04, 2.2654e-04, -4.5522e-04, 4.4150e-04,\n -1.6495e-04, -1.1423e-04, 1.3860e-04, 9.5185e-05, -1.7071e-04,\n 1.1142e-04, 4.0112e-04, -4.8610e-05, 1.0510e-05, -2.1901e-05,\n -4.9814e-06, 1.1262e-05, 0.0000e+00, -1.5561e-04, -9.3755e-05,\n -1.3772e-05, 3.2919e-05, -1.7783e-04, -8.9205e-06, 8.3088e-05,\n 3.6471e-05, -2.2087e-05, 2.9861e-04, -2.0031e-04, -1.6110e-05,\n -1.1162e-04, -8.8141e-05, 1.7412e-04, -2.5122e-04, 9.5004e-05,\n 2.3173e-04, -3.9405e-05, 8.6019e-05, 2.5291e-05, 2.7562e-06,\n -1.4153e-04, -2.4303e-05, 4.7482e-05, -5.8735e-06, -5.7773e-05,\n 3.6777e-05, -5.4426e-05, -1.7881e-04, 6.2304e-05, -2.7839e-04,\n -2.7782e-05, 1.3939e-05, 2.5295e-04, 7.2392e-05, -4.7288e-05,\n 1.3746e-04, 1.4712e-04, 1.8018e-05, 4.1135e-04, 4.5421e-04,\n -1.3944e-04, 1.5294e-04, -6.2998e-05, 2.1342e-05, 7.6706e-05,\n -1.1499e-04, 1.9743e-05, 2.1605e-04, 4.2293e-05, 1.4431e-04,\n 7.3072e-05]), 'exp_avg_sq': tensor([4.7961e-06, 1.0719e-05, 2.4394e-06, 5.3510e-06, 1.5618e-06, 3.4570e-06,\n 8.1266e-06, 5.9700e-06, 3.5825e-06, 5.7679e-06, 2.7771e-06, 3.3023e-06,\n 2.8466e-06, 6.7260e-06, 6.8510e-06, 2.7978e-06, 6.0199e-06, 8.3526e-06,\n 2.0468e-06, 4.5798e-06, 4.1360e-06, 1.1873e-06, 3.9945e-06, 3.4329e-06,\n 7.5849e-06, 1.0618e-06, 4.5054e-07, 3.5344e-06, 4.0141e-06, 3.0928e-06,\n 1.9291e-06, 2.8583e-06, 6.1002e-06, 1.8416e-06, 6.5716e-06, 6.4990e-06,\n 5.1658e-06, 2.9251e-06, 4.0773e-06, 4.3814e-06, 1.7263e-06, 6.9320e-06,\n 3.5956e-06, 3.3052e-06, 7.0099e-06, 1.8879e-06, 6.4008e-06, 2.0067e-06,\n 7.7096e-07, 1.7141e-06, 4.4978e-06, 1.1479e-05, 1.8124e-06, 2.5052e-06,\n 3.3019e-06, 4.1953e-06, 1.2172e-05, 4.2939e-06, 4.6977e-06, 4.9971e-06,\n 2.1924e-06, 6.8018e-06, 1.6125e-06, 3.1356e-06, 0.0000e+00, 4.0178e-06,\n 1.8261e-06, 5.2896e-06, 1.7595e-06, 9.4938e-06, 1.7748e-06, 0.0000e+00,\n 1.4577e-05, 5.0340e-06, 2.6963e-06, 2.4738e-06, 3.2129e-06, 7.4783e-06,\n 3.4655e-06, 2.8570e-06, 1.2119e-05, 1.0227e-05, 4.2414e-06, 5.1386e-06,\n 9.6546e-06, 7.6771e-06, 3.3943e-06, 1.3541e-06, 3.9152e-06, 0.0000e+00,\n 5.5512e-06, 2.1814e-06, 1.7028e-06, 2.8494e-06, 2.8491e-06, 4.1993e-06,\n 2.3424e-06, 2.7297e-06, 7.3234e-06, 7.8333e-06, 4.2625e-06, 0.0000e+00,\n 5.3249e-06, 1.7044e-06, 4.9610e-06, 8.9124e-06, 1.2687e-06, 2.7845e-06,\n 2.2918e-06, 1.9053e-06, 3.8702e-06, 5.9982e-06, 3.1575e-06, 1.1611e-05,\n 8.1056e-06, 2.3761e-06, 3.2548e-06, 1.9969e-06, 1.0813e-05, 4.4015e-06,\n 8.1683e-06, 5.1964e-06, 9.2980e-06, 0.0000e+00, 7.3398e-06, 9.8649e-06,\n 3.4110e-06, 0.0000e+00, 3.9718e-06, 1.2879e-05, 2.2658e-05, 4.7630e-06,\n 5.9945e-06, 1.9737e-06, 1.0900e-06, 9.2563e-06, 2.0170e-06, 2.7633e-06,\n 1.1741e-05, 2.6270e-06, 1.0206e-06, 6.8287e-06, 4.5463e-06, 5.2176e-06,\n 1.3454e-05, 5.6809e-06, 6.5522e-06, 3.5044e-06, 3.1965e-06, 1.6803e-06,\n 9.3084e-07, 1.9968e-06, 2.5395e-06, 3.9315e-06, 5.4750e-06, 4.5276e-06,\n 6.5161e-06, 2.9896e-06, 3.9720e-06, 1.5943e-06, 2.3981e-06, 8.1685e-06,\n 2.2946e-06, 1.0944e-05, 1.1436e-06, 3.5875e-06, 2.0240e-06, 1.9784e-06,\n 6.8831e-06, 2.1291e-06, 5.1752e-06, 1.1694e-06, 2.9215e-06, 2.9568e-06,\n 1.1065e-06, 3.6551e-06, 6.0279e-06, 1.7906e-06, 4.7019e-06, 3.5883e-06,\n 1.9190e-06, 1.1576e-06, 2.7729e-06, 3.6231e-06, 3.3407e-06, 0.0000e+00,\n 2.9574e-06, 3.1534e-06, 9.8838e-06, 1.4860e-05, 8.4957e-06, 2.0707e-06,\n 6.8267e-06, 1.7929e-06, 2.5727e-06, 2.1034e-06, 4.3319e-06, 5.9683e-06,\n 3.5029e-06, 8.5632e-07, 2.1962e-06, 5.3931e-06, 0.0000e+00, 5.7545e-06,\n 4.6650e-06, 3.9340e-06, 1.2294e-06, 2.8491e-06, 4.7207e-06, 6.8839e-06,\n 1.5715e-06, 2.4547e-06, 2.0453e-06, 5.4806e-06, 4.6731e-06, 5.1711e-06,\n 6.8384e-06, 2.5221e-06, 2.0695e-06, 6.3981e-06, 1.1109e-05, 2.1246e-06,\n 1.7548e-06, 4.5168e-06, 1.9402e-06, 6.1503e-06, 5.9079e-06, 8.1520e-06,\n 4.7721e-06, 1.3706e-05, 1.4638e-06, 5.5747e-06, 7.4132e-06, 3.0192e-06,\n 7.2428e-06, 2.8295e-06, 2.8146e-06, 7.7635e-06, 3.0717e-06, 7.0776e-07,\n 2.5640e-06, 7.4060e-06, 1.1442e-05, 5.9837e-06, 1.5609e-05, 5.7369e-06,\n 2.1188e-06, 4.5810e-06, 2.8879e-06, 2.4623e-06, 4.2793e-06, 3.6689e-06,\n 2.8580e-06, 2.4485e-06, 7.0787e-06, 2.5136e-06])}, 23: {'step': 7160, 'exp_avg': tensor([-5.5843e-04, -2.6872e-06, 1.2839e-05, 1.1146e-04, 7.5199e-05,\n -1.9397e-09, 1.5395e-04, -2.2141e-05, 1.7632e-04, -9.0262e-05,\n -1.5843e-04, 6.4545e-06, -9.7775e-05, 1.2264e-04, 3.7789e-06,\n 1.6800e-04, 6.3170e-05, 2.1168e-05, 5.3682e-06, 8.8559e-08,\n 7.2277e-05, 2.4866e-04, 1.9580e-04, 2.1577e-04, -2.9116e-05,\n 2.2384e-05, 1.0473e-04, -9.7207e-06, -1.6066e-09, 2.9209e-05,\n -6.8002e-06, -3.3930e-07, 1.0281e-05, -5.5194e-06, -4.9072e-05,\n 5.8002e-05, -1.0755e-04, -4.3756e-05, -1.2362e-04, -1.7716e-04,\n 5.7615e-05, -5.2069e-05, -1.3405e-04, -1.6290e-04, -5.9703e-05,\n -6.2319e-05, -8.3352e-05, -1.4192e-06, 4.2993e-05, 2.9545e-05,\n 7.3416e-06, -5.9618e-05, -4.1928e-05, 1.3070e-04, -2.2050e-05,\n -2.2377e-05, -4.1104e-06, -1.2020e-04, -5.4184e-05, -1.0732e-05,\n -9.4455e-05, -7.5165e-05, 1.5702e-06, -7.1658e-05, 0.0000e+00,\n -1.2735e-06, 7.2658e-06, -3.8546e-05, 3.6773e-05, 6.1200e-05,\n 5.3960e-05, 0.0000e+00, -4.2577e-05, -3.3379e-10, 1.4557e-04,\n -2.0951e-05, -6.9338e-05, -7.2830e-05, -4.0038e-07, -2.4258e-06,\n 4.7723e-05, 1.0096e-05, -3.1034e-05, 1.6635e-04, 6.2671e-05,\n 7.0147e-06, -1.1228e-04, 5.5562e-05, 1.9441e-07, 0.0000e+00,\n -2.2897e-11, -8.8464e-05, 1.2676e-06, 6.2187e-05, -4.7004e-05,\n 2.7898e-05, -1.6824e-09, -8.2584e-05, -2.5480e-05, -7.5661e-05,\n -2.9524e-05, 0.0000e+00, -2.5791e-04, 1.3630e-04, -1.2598e-05,\n -3.0005e-05, 5.0907e-05, -1.5437e-04, -1.1531e-10, -3.1475e-05,\n -1.4779e-04, -2.7673e-06, -1.6581e-06, 7.7592e-05, -6.3115e-05,\n 3.5636e-05, -2.4380e-05, 5.9080e-05, -5.5520e-05, -1.1429e-05,\n 2.4301e-06, -6.2792e-06, 5.3662e-05, 0.0000e+00, -6.4424e-05,\n -1.1675e-05, 8.2262e-05, 0.0000e+00, 1.2631e-04, 2.9873e-05,\n -6.9926e-05, -4.7828e-05, 4.7593e-05, 3.8531e-05, 1.5362e-04,\n -2.3726e-05, -9.7185e-05, 5.1213e-05, 2.6168e-05, -6.2714e-06,\n -8.6313e-05, 1.0696e-06, 2.1071e-05, -4.5399e-05, -1.2492e-05,\n -8.8930e-05, 4.8832e-05, -8.3448e-06, 3.2383e-05, -5.7255e-06,\n 2.1814e-05, 8.2400e-06, -2.2969e-05, 1.2704e-05, 2.4370e-06,\n -1.2323e-04, -5.9949e-07, 8.0298e-06, 8.2911e-06, 1.6720e-10,\n -7.6301e-05, 1.1479e-05, 1.4088e-06, 2.3209e-07, -7.0442e-05,\n -5.2702e-05, 2.9009e-05, 1.7583e-06, 5.1852e-05, -6.4853e-05,\n 1.1827e-05, -4.8143e-05, 2.5464e-05, -3.0321e-05, 4.6035e-05,\n 1.0386e-04, -4.7662e-05, 1.6070e-09, 9.1344e-05, -4.2332e-05,\n 6.4311e-05, 5.3548e-06, 2.5490e-05, 7.6939e-05, 3.0278e-07,\n 0.0000e+00, -8.2336e-05, -6.1964e-07, 1.3261e-04, -3.8985e-08,\n -8.8859e-05, -8.4010e-05, -2.8593e-09, 8.1997e-05, -3.0272e-05,\n 2.2314e-08, -1.4127e-04, 3.0892e-04, 1.5298e-04, -3.3382e-05,\n -3.8769e-05, 7.2591e-05, 0.0000e+00, -2.1827e-07, -1.1807e-05,\n 1.4366e-06, 1.3820e-04, -1.5515e-05, 4.0341e-05, 7.8782e-06,\n -7.8051e-05, 7.3150e-05, -1.3232e-05, 2.7456e-05, -9.7007e-06,\n 3.4722e-05, -8.4878e-05, 8.5293e-05, -1.2223e-04, -4.8586e-05,\n -4.5589e-07, 2.3649e-05, 2.9672e-05, 6.9084e-08, -1.0860e-07,\n -1.7590e-04, -2.7785e-08, 2.6616e-05, 1.1050e-07, 5.1956e-05,\n 3.9779e-06, -2.8904e-11, 1.0306e-05, 1.2025e-05, 3.3880e-06,\n 2.3407e-05, -1.2279e-04, 7.5636e-10, 5.5592e-05, 2.2724e-07,\n 1.2246e-04, 2.2835e-05, -4.2193e-08, 2.4890e-04, 8.0998e-05,\n -4.4007e-06, 1.0002e-04, -1.1667e-04, 2.7393e-05, 7.6095e-05,\n 5.0508e-05, -6.3566e-06, -1.0947e-04, 2.3171e-07, 8.1081e-06,\n -7.9109e-05]), 'exp_avg_sq': tensor([3.7757e-05, 9.3232e-09, 1.2542e-06, 1.9475e-06, 8.2872e-07, 2.0687e-11,\n 1.4123e-06, 1.8942e-06, 6.9812e-06, 8.3036e-07, 1.1164e-05, 1.6401e-06,\n 1.0206e-06, 7.5321e-06, 3.8365e-06, 1.2649e-06, 1.7641e-06, 1.4208e-06,\n 3.4154e-07, 2.4836e-10, 1.3208e-06, 2.1727e-06, 1.7803e-06, 1.5247e-06,\n 2.9069e-06, 5.7984e-07, 3.4156e-06, 3.0391e-06, 3.0188e-10, 3.1579e-06,\n 2.9495e-06, 6.5961e-10, 5.7195e-08, 2.4713e-07, 6.7319e-07, 1.0114e-07,\n 2.7950e-06, 1.1713e-06, 1.1772e-05, 2.0432e-06, 1.1116e-06, 2.5513e-06,\n 2.7325e-06, 2.2128e-06, 3.9919e-07, 9.4896e-07, 1.1303e-06, 1.1089e-06,\n 1.3617e-07, 4.6933e-07, 7.5767e-08, 5.7023e-07, 7.6994e-07, 1.3395e-06,\n 5.9975e-08, 1.3909e-06, 4.1844e-07, 2.3169e-06, 2.1000e-06, 1.5060e-06,\n 9.1019e-07, 1.9095e-06, 1.1665e-09, 8.0620e-07, 0.0000e+00, 3.2338e-09,\n 9.0417e-07, 3.3305e-07, 7.7966e-07, 8.3532e-06, 9.6940e-07, 0.0000e+00,\n 5.8176e-08, 3.8976e-11, 2.2167e-06, 1.1173e-06, 2.5123e-06, 1.8563e-06,\n 9.8996e-09, 1.5344e-06, 1.2519e-06, 6.5665e-07, 3.2894e-07, 1.5828e-06,\n 1.0473e-07, 2.8970e-08, 1.6250e-06, 9.6392e-07, 3.2579e-10, 0.0000e+00,\n 4.1209e-10, 8.8277e-07, 5.9895e-09, 3.0572e-06, 1.3860e-06, 3.8848e-07,\n 8.4467e-12, 1.2966e-06, 6.4567e-07, 4.2261e-07, 1.5215e-06, 0.0000e+00,\n 2.9882e-06, 3.6737e-07, 1.9177e-06, 5.2968e-06, 3.8649e-07, 1.8226e-06,\n 5.8451e-10, 7.9714e-08, 1.3284e-05, 6.1409e-08, 4.9352e-09, 1.5182e-06,\n 4.3472e-06, 2.5873e-06, 2.7736e-08, 9.9072e-07, 1.9192e-06, 2.0500e-07,\n 1.2827e-06, 7.9621e-07, 2.3085e-06, 0.0000e+00, 8.2203e-07, 7.8934e-07,\n 1.5173e-06, 0.0000e+00, 2.4223e-06, 1.6735e-06, 3.0733e-06, 2.0006e-06,\n 1.9180e-06, 1.0724e-06, 5.3159e-07, 5.8266e-07, 5.8220e-07, 1.0316e-06,\n 1.2675e-06, 1.0699e-06, 7.2481e-07, 4.0408e-08, 1.1833e-06, 6.4231e-07,\n 9.9950e-07, 4.9992e-06, 3.5101e-07, 1.5855e-06, 1.2994e-06, 9.6550e-07,\n 2.4296e-06, 1.9950e-06, 1.4009e-06, 2.1249e-06, 3.8446e-07, 1.8942e-06,\n 3.1900e-06, 1.8131e-06, 3.0423e-08, 4.5008e-11, 7.2797e-06, 3.1808e-06,\n 1.7758e-09, 1.0670e-10, 9.8153e-07, 3.1378e-07, 1.6581e-06, 2.3912e-09,\n 2.1885e-06, 1.0532e-06, 5.9951e-07, 9.6460e-07, 1.0348e-06, 1.2848e-06,\n 7.7304e-07, 3.0069e-06, 2.4925e-06, 2.2098e-11, 8.3643e-07, 9.7623e-07,\n 1.8320e-06, 2.6267e-06, 8.9814e-07, 2.3750e-06, 8.9082e-08, 0.0000e+00,\n 2.4700e-06, 6.6892e-08, 1.4720e-06, 7.2430e-11, 4.7351e-06, 9.3691e-06,\n 1.1074e-08, 6.1350e-07, 1.1408e-06, 1.1700e-09, 2.9421e-06, 1.5118e-06,\n 3.2074e-06, 5.9964e-07, 1.7108e-06, 7.8734e-07, 0.0000e+00, 5.9777e-09,\n 1.4775e-06, 2.1413e-09, 1.1063e-06, 1.6566e-07, 8.8766e-07, 7.7700e-08,\n 4.9605e-07, 4.1605e-06, 7.9118e-07, 1.2240e-06, 5.6397e-07, 1.2396e-07,\n 1.4837e-06, 1.7283e-06, 2.4272e-06, 1.2862e-06, 4.8388e-08, 1.0539e-06,\n 8.3256e-07, 2.0177e-07, 1.0430e-07, 1.5509e-06, 2.2936e-10, 1.2864e-06,\n 9.4402e-10, 8.1838e-07, 7.9360e-07, 3.6542e-11, 3.8974e-07, 1.3111e-06,\n 4.1893e-08, 5.4931e-06, 2.3900e-06, 2.4876e-13, 1.1279e-06, 3.5087e-07,\n 6.0739e-07, 3.3241e-07, 2.8287e-10, 2.5258e-06, 1.3307e-06, 1.7779e-06,\n 8.9828e-07, 1.9323e-06, 1.3920e-06, 1.2295e-06, 1.0370e-06, 1.8133e-05,\n 4.2498e-06, 5.0456e-10, 1.1725e-07, 1.2512e-06])}, 24: {'step': 7160, 'exp_avg': tensor([[[[ 1.8946e-05]],\n\n [[ 3.4159e-05]],\n\n [[-1.6788e-06]],\n\n ...,\n\n [[ 3.0388e-05]],\n\n [[ 2.5848e-05]],\n\n [[ 3.5966e-05]]],\n\n\n [[[ 5.5355e-06]],\n\n [[ 2.8912e-06]],\n\n [[ 2.9040e-05]],\n\n ...,\n\n [[ 2.9904e-05]],\n\n [[-1.6908e-05]],\n\n [[ 1.2611e-05]]],\n\n\n [[[ 9.9253e-06]],\n\n [[ 2.5997e-05]],\n\n [[ 1.8418e-05]],\n\n ...,\n\n [[-1.9276e-05]],\n\n [[-8.2889e-06]],\n\n [[-2.6485e-06]]],\n\n\n ...,\n\n\n [[[-7.8912e-06]],\n\n [[-3.1503e-05]],\n\n [[ 8.1221e-06]],\n\n ...,\n\n [[ 1.8450e-05]],\n\n [[-1.2194e-05]],\n\n [[-1.1459e-05]]],\n\n\n [[[-2.4805e-05]],\n\n [[-3.4711e-05]],\n\n [[ 2.4086e-05]],\n\n ...,\n\n [[-1.2258e-06]],\n\n [[ 2.6252e-05]],\n\n [[-4.8319e-05]]],\n\n\n [[[ 3.4438e-05]],\n\n [[ 3.1802e-05]],\n\n [[ 1.7067e-05]],\n\n ...,\n\n [[ 1.4664e-05]],\n\n [[ 4.1054e-05]],\n\n [[ 1.6057e-05]]]]), 'exp_avg_sq': tensor([[[[1.5850e-07]],\n\n [[3.0065e-07]],\n\n [[1.2775e-07]],\n\n ...,\n\n [[1.2725e-07]],\n\n [[2.8323e-07]],\n\n [[1.9501e-07]]],\n\n\n [[[2.1592e-07]],\n\n [[4.4161e-07]],\n\n [[3.6535e-07]],\n\n ...,\n\n [[1.5887e-07]],\n\n [[4.2668e-07]],\n\n [[8.2820e-07]]],\n\n\n [[[5.5265e-07]],\n\n [[1.3197e-06]],\n\n [[3.7169e-08]],\n\n ...,\n\n [[2.8363e-07]],\n\n [[3.0396e-07]],\n\n [[1.2292e-07]]],\n\n\n ...,\n\n\n [[[1.6895e-07]],\n\n [[2.6471e-07]],\n\n [[1.4051e-07]],\n\n ...,\n\n [[1.6032e-07]],\n\n [[2.6138e-07]],\n\n [[3.1882e-07]]],\n\n\n [[[2.9215e-07]],\n\n [[8.0233e-07]],\n\n [[1.1169e-07]],\n\n ...,\n\n [[3.6951e-07]],\n\n [[3.1947e-07]],\n\n [[3.8022e-07]]],\n\n\n [[[2.4213e-07]],\n\n [[5.9328e-07]],\n\n [[7.5211e-08]],\n\n ...,\n\n [[2.0030e-07]],\n\n [[3.3297e-07]],\n\n [[4.4354e-07]]]])}, 25: {'step': 7160, 'exp_avg': tensor([ 9.8499e-05, 7.4919e-05, 4.7670e-04, 1.5243e-04, -1.0167e-04,\n 1.0130e-04, 5.0629e-05, 2.6908e-04, -3.1690e-04, 2.0524e-04,\n 2.8077e-05, 8.1195e-05, 5.7393e-06, -2.0994e-04, -5.4920e-07,\n -5.5773e-05, 3.7886e-04, -6.4930e-05, 7.4119e-05, 3.5296e-04,\n 1.3475e-05, -2.4594e-04, 7.8172e-05, -6.4123e-05, -1.4679e-04,\n 1.2309e-04, -3.5438e-04, -2.1057e-04, -4.0482e-04, 1.0205e-04,\n -8.1248e-05, -4.0040e-05, -1.9004e-05, -5.4495e-06, -1.7818e-04,\n -9.4336e-06, -1.1359e-04, -2.3176e-04, 1.0772e-04, 3.4714e-04,\n 3.0640e-04, -2.9734e-04, 4.4870e-05, -3.5925e-04, 8.5188e-05,\n -1.3475e-04, 1.0184e-04, 1.4266e-04, -3.0579e-05, 1.3874e-04,\n 1.6548e-04, -2.1088e-04, 4.1071e-05, 1.7494e-04, 1.9488e-04,\n -4.2057e-04, -1.9589e-04, -1.2561e-04, -1.7138e-04, -1.4975e-04,\n -4.9029e-05, -9.1040e-05, -2.0735e-04, -1.9706e-05]), 'exp_avg_sq': tensor([4.8802e-06, 5.4417e-06, 1.1377e-05, 1.8172e-06, 8.0951e-06, 1.1675e-05,\n 2.4076e-06, 7.8729e-06, 1.0439e-05, 8.5291e-06, 5.4856e-06, 8.5999e-06,\n 1.1954e-05, 8.8241e-06, 8.3522e-06, 1.3214e-05, 1.1151e-05, 1.0418e-05,\n 5.5686e-06, 1.5958e-05, 5.7374e-06, 9.6408e-06, 4.5868e-06, 7.1382e-06,\n 1.4181e-05, 1.0685e-05, 9.9739e-06, 4.9479e-06, 6.0649e-06, 5.3819e-06,\n 4.2806e-06, 7.6391e-06, 1.0286e-05, 7.2992e-06, 1.2296e-05, 1.0765e-05,\n 8.8705e-06, 4.7351e-06, 4.5250e-06, 6.2335e-06, 7.5752e-06, 6.9424e-06,\n 5.0762e-06, 6.4511e-06, 5.0525e-06, 1.9695e-06, 6.1878e-06, 4.2267e-06,\n 6.3258e-06, 6.2059e-06, 4.5510e-06, 1.4541e-05, 6.6350e-06, 7.1507e-06,\n 7.1426e-06, 1.2293e-05, 6.3896e-06, 6.1797e-06, 7.3996e-06, 5.0020e-06,\n 3.1344e-06, 5.7550e-06, 5.9040e-06, 4.0627e-06])}, 26: {'step': 7160, 'exp_avg': tensor([ 1.1205e-04, -1.2051e-05, 3.5262e-04, 9.1957e-05, -1.6576e-04,\n 1.2121e-04, 4.1435e-05, -2.5331e-05, 4.4805e-04, 2.0763e-04,\n -1.7080e-05, 3.4373e-05, -9.6738e-05, -2.4993e-04, 4.0603e-06,\n -6.2616e-05, 1.0909e-04, 3.4221e-06, 6.3307e-05, 3.0347e-04,\n 1.5371e-05, 1.7327e-04, -8.6281e-05, -4.3380e-05, -3.9400e-04,\n 2.5553e-04, -1.3515e-04, 2.8790e-05, -2.5011e-04, 5.9530e-05,\n 9.9690e-05, -4.0281e-05, 4.6203e-06, 7.4929e-05, 2.6274e-04,\n -2.2110e-04, -1.7713e-05, -2.4083e-04, 1.9732e-04, 1.9061e-04,\n 2.0420e-04, 1.7376e-04, 3.6115e-05, -9.9285e-05, 1.8760e-04,\n -8.6026e-05, 7.7751e-05, 1.0474e-04, -1.8390e-04, 1.3306e-04,\n 2.1075e-04, 2.6963e-04, 6.4171e-06, 2.0709e-05, 8.9701e-05,\n -1.6031e-04, -1.0902e-04, -2.0654e-04, -1.3948e-04, -1.8207e-04,\n -5.3316e-05, -2.3215e-04, -9.0749e-05, 4.9583e-05]), 'exp_avg_sq': tensor([3.0001e-06, 4.6272e-06, 8.5525e-06, 6.0975e-07, 5.8664e-06, 8.7015e-06,\n 1.3901e-06, 4.7363e-06, 5.9133e-06, 3.2263e-06, 2.5674e-06, 7.8720e-07,\n 5.2491e-06, 5.4447e-06, 3.9600e-06, 3.8586e-06, 4.2637e-06, 4.7422e-06,\n 3.1687e-06, 5.8464e-06, 3.6563e-06, 3.1987e-06, 4.5079e-06, 3.5250e-06,\n 8.4508e-06, 3.3190e-06, 6.1820e-06, 4.7749e-06, 3.8813e-06, 2.9471e-06,\n 2.6688e-06, 4.3207e-06, 2.3200e-06, 4.4057e-06, 3.0866e-06, 7.3979e-06,\n 3.4181e-06, 2.7170e-06, 3.8610e-06, 4.1001e-06, 4.2880e-06, 4.9540e-06,\n 3.6189e-06, 4.0934e-06, 4.5483e-06, 8.1558e-07, 3.4140e-06, 2.6987e-06,\n 1.1607e-05, 2.2264e-06, 3.1333e-06, 4.7359e-06, 3.7505e-06, 4.9061e-06,\n 2.7653e-06, 4.8606e-06, 4.6387e-06, 4.3438e-06, 3.8015e-06, 3.0587e-06,\n 3.3519e-06, 4.2105e-06, 4.3383e-06, 2.6935e-06])}, 27: {'step': 7160, 'exp_avg': tensor([[[[ 1.1174e-05, -8.6258e-06, -3.7721e-05],\n [ 3.9574e-06, -8.0471e-06, 3.9499e-06],\n [ 7.9925e-06, 2.1849e-05, 5.5625e-06]],\n\n [[ 2.2334e-05, -7.3446e-06, -2.0818e-05],\n [ 3.4859e-05, 2.1777e-05, -5.5172e-06],\n [ 2.2876e-05, 3.2126e-05, -2.3171e-05]],\n\n [[-3.4414e-07, 1.0672e-05, 5.3242e-06],\n [ 4.7537e-06, 1.0708e-05, 1.6806e-05],\n [-1.6467e-06, 9.6992e-06, 3.1347e-05]],\n\n ...,\n\n [[-1.5614e-05, -1.1711e-05, -2.8623e-05],\n [ 2.5068e-06, 1.6591e-05, -5.1431e-06],\n [ 2.3201e-05, 4.6681e-05, -3.5221e-06]],\n\n [[-4.9847e-06, -1.1961e-05, -6.2668e-07],\n [-1.4983e-05, 1.2439e-06, -1.4823e-05],\n [-2.2495e-05, -2.8850e-05, -4.9801e-05]],\n\n [[-6.1669e-06, -5.0403e-06, -2.2059e-05],\n [-2.3889e-05, 1.7899e-05, -1.2596e-05],\n [-7.0733e-06, -4.1869e-06, -3.1853e-05]]],\n\n\n [[[-1.0918e-05, -4.2797e-05, 3.0806e-05],\n [ 3.3851e-05, -3.7121e-06, 1.8522e-05],\n [ 5.2818e-05, 4.2164e-05, 1.0331e-05]],\n\n [[-2.8603e-05, -1.1227e-05, 1.8023e-05],\n [ 1.6267e-06, 1.5995e-05, 2.1218e-05],\n [ 3.7655e-05, 8.9447e-06, -8.4419e-06]],\n\n [[-4.6471e-06, -6.1521e-06, -1.3466e-05],\n [ 2.2680e-06, 9.1349e-06, 1.1987e-05],\n [-6.9308e-06, 6.9178e-06, 8.2890e-06]],\n\n ...,\n\n [[ 1.3681e-05, 1.0908e-05, 2.2791e-05],\n [ 1.0998e-05, -5.1999e-06, -6.5322e-06],\n [ 2.2560e-05, 9.2414e-06, -5.0632e-05]],\n\n [[ 5.4137e-06, 2.1929e-06, 2.5979e-05],\n [ 2.6183e-05, -4.7037e-06, 1.1730e-06],\n [ 5.3454e-06, -1.9366e-05, 8.9604e-06]],\n\n [[ 2.2222e-05, 2.5761e-05, 7.2477e-06],\n [ 4.3310e-05, 1.8755e-05, 4.4388e-06],\n [ 3.6692e-05, 8.2891e-06, 1.1187e-05]]],\n\n\n [[[ 2.6825e-06, -2.3710e-05, -3.1833e-05],\n [-5.0283e-06, 1.9419e-05, 5.9266e-07],\n [-2.5290e-05, -3.3838e-05, -4.3038e-05]],\n\n [[-2.0043e-05, 5.3932e-07, 6.2840e-05],\n [ 1.0054e-05, -1.1462e-05, 4.5358e-05],\n [ 1.6923e-05, 2.7540e-05, 3.0614e-05]],\n\n [[ 1.6031e-05, 1.4880e-05, 2.1594e-05],\n [ 9.9500e-06, 4.1370e-06, 8.6071e-06],\n [ 1.1367e-05, 1.2668e-05, 5.0205e-06]],\n\n ...,\n\n [[-3.3499e-05, -3.2557e-05, -6.2064e-05],\n [-1.3517e-05, -3.0325e-05, -7.3136e-05],\n [-3.5592e-05, -1.8335e-05, -5.1403e-05]],\n\n [[ 1.5919e-05, 2.1872e-05, 8.6898e-06],\n [ 1.2785e-05, 2.3130e-05, 6.7723e-06],\n [ 3.8698e-05, 2.0725e-06, -3.2998e-05]],\n\n [[-4.0477e-05, 1.3060e-05, 8.5800e-06],\n [-8.7686e-06, 2.0475e-05, -2.9636e-05],\n [-5.1384e-05, -4.6214e-05, -1.0810e-04]]],\n\n\n ...,\n\n\n [[[ 1.1084e-05, 1.3529e-05, 2.7429e-05],\n [-4.2001e-06, 3.7091e-05, 4.2111e-05],\n [-1.1196e-05, 1.6931e-05, 4.5383e-05]],\n\n [[-2.1700e-05, 7.4988e-06, 1.6659e-05],\n [ 1.3827e-05, 3.4848e-05, 4.1153e-05],\n [ 2.7717e-05, 4.8360e-05, 8.1153e-05]],\n\n [[-1.7325e-05, 6.5346e-06, 3.7089e-06],\n [-2.2861e-05, 2.0792e-06, 9.7866e-06],\n [-6.8219e-06, -3.8478e-06, -5.2009e-06]],\n\n ...,\n\n [[-1.0355e-07, -1.1541e-05, 9.4042e-06],\n [-7.0500e-06, -5.7089e-06, 9.4452e-06],\n [-5.3603e-05, 2.3019e-05, 6.0057e-05]],\n\n [[ 2.7221e-05, 1.0819e-05, 2.1742e-05],\n [-3.8961e-06, -8.3838e-07, 1.1615e-05],\n [-1.5804e-05, -1.8851e-05, -7.5307e-06]],\n\n [[ 2.9311e-05, -2.2119e-05, 4.0551e-05],\n [-1.3379e-05, -2.1888e-05, 1.6714e-06],\n [-2.3413e-05, -2.9015e-06, 1.1826e-05]]],\n\n\n [[[-5.6605e-05, -7.1954e-06, -4.1909e-05],\n [-1.3068e-05, 1.2384e-05, -1.7057e-05],\n [-2.8541e-05, -2.5149e-05, -2.1711e-05]],\n\n [[-3.7599e-05, -3.9575e-05, 1.0479e-06],\n [ 3.4871e-06, -9.5856e-06, -4.7990e-06],\n [ 3.1997e-06, -4.3328e-05, 1.8827e-06]],\n\n [[-5.3141e-06, 6.7235e-06, 5.2977e-06],\n [ 3.7783e-06, 1.2137e-05, 1.4346e-05],\n [ 1.5778e-05, 1.5905e-05, 2.1006e-05]],\n\n ...,\n\n [[-2.3805e-06, 1.4757e-05, 1.4406e-05],\n [ 2.2318e-05, 5.2814e-05, 3.1875e-05],\n [ 8.9187e-06, 2.4633e-05, 3.0567e-05]],\n\n [[ 4.8125e-06, 1.8071e-05, -2.8687e-06],\n [ 2.2350e-05, 3.7008e-05, -2.2395e-06],\n [-6.8200e-06, -1.5441e-05, -2.6606e-08]],\n\n [[ 8.2893e-06, -7.4172e-06, -2.1074e-05],\n [ 1.3943e-05, 8.9266e-06, 1.1112e-05],\n [-1.9631e-05, -3.3827e-05, -7.0374e-06]]],\n\n\n [[[ 1.3991e-05, -2.2490e-05, 1.6542e-06],\n [-2.8700e-05, -3.4529e-05, -2.4375e-05],\n [-2.9061e-05, 5.7020e-06, -4.3230e-06]],\n\n [[ 8.2119e-05, -1.7985e-06, -2.0873e-05],\n [ 3.8249e-05, -4.1523e-06, -1.8538e-05],\n [ 3.3182e-05, -4.7937e-05, -4.7254e-05]],\n\n [[-3.1614e-05, -3.6033e-05, -3.2563e-05],\n [-2.0219e-05, -4.5383e-05, -3.1197e-05],\n [-4.3221e-05, -4.9989e-05, -2.4764e-05]],\n\n ...,\n\n [[-5.4427e-05, -5.3071e-05, -3.3441e-05],\n [-3.4964e-05, -4.4610e-05, -4.4453e-05],\n [ 4.4115e-06, 3.6546e-05, 1.1676e-05]],\n\n [[-2.5584e-05, 8.5229e-06, 9.5275e-06],\n [ 2.8455e-06, 2.5299e-05, 1.9938e-05],\n [ 3.8289e-05, 5.2905e-05, 1.6139e-05]],\n\n [[-1.6379e-05, 1.8263e-05, 1.2060e-05],\n [ 1.7125e-06, 2.2861e-05, -3.3829e-05],\n [ 5.4494e-05, 3.1581e-05, -1.6347e-05]]]]), 'exp_avg_sq': tensor([[[[1.3927e-07, 7.1435e-08, 1.5135e-07],\n [8.9634e-08, 1.0804e-07, 1.6117e-07],\n [1.1545e-07, 1.3571e-07, 1.5619e-07]],\n\n [[1.4806e-07, 8.3378e-08, 1.3838e-07],\n [1.2067e-07, 1.0018e-07, 2.1876e-07],\n [8.9584e-08, 1.2370e-07, 1.7024e-07]],\n\n [[5.8124e-08, 5.7249e-08, 5.1803e-08],\n [4.9836e-08, 5.6770e-08, 5.5182e-08],\n [6.7605e-08, 6.5442e-08, 6.0826e-08]],\n\n ...,\n\n [[1.7740e-07, 1.6803e-07, 1.9769e-07],\n [1.4974e-07, 2.5535e-07, 1.4967e-07],\n [2.1306e-07, 1.7591e-07, 1.4743e-07]],\n\n [[4.5742e-08, 8.0053e-08, 1.0569e-07],\n [6.3916e-08, 1.2867e-07, 1.4642e-07],\n [9.9101e-08, 1.6745e-07, 1.2332e-07]],\n\n [[7.2111e-08, 9.3068e-08, 9.8695e-08],\n [1.0500e-07, 1.3135e-07, 8.0057e-08],\n [1.0497e-07, 1.3215e-07, 8.2779e-08]]],\n\n\n [[[1.1520e-07, 2.2832e-07, 2.2185e-07],\n [1.6203e-07, 3.5733e-07, 1.5514e-07],\n [1.8191e-07, 2.7732e-07, 1.3602e-07]],\n\n [[1.0262e-07, 2.8145e-07, 1.9018e-07],\n [1.1531e-07, 2.7357e-07, 1.3203e-07],\n [1.8268e-07, 3.3534e-07, 1.0966e-07]],\n\n [[4.4916e-08, 5.7323e-08, 5.0587e-08],\n [4.8585e-08, 6.1455e-08, 4.0453e-08],\n [1.0316e-07, 5.7094e-08, 4.2505e-08]],\n\n ...,\n\n [[1.8695e-07, 1.4990e-07, 1.9328e-07],\n [2.5064e-07, 1.8261e-07, 1.9491e-07],\n [2.2159e-07, 1.7210e-07, 1.8866e-07]],\n\n [[7.9414e-08, 1.7292e-07, 1.7229e-07],\n [1.7927e-07, 1.3060e-07, 8.7080e-08],\n [1.9939e-07, 1.1592e-07, 1.5750e-07]],\n\n [[1.8881e-07, 1.3472e-07, 1.2453e-07],\n [1.9508e-07, 1.5379e-07, 8.5861e-08],\n [2.2527e-07, 7.6304e-08, 1.3179e-07]]],\n\n\n [[[4.8725e-07, 4.1380e-07, 3.1307e-07],\n [4.6888e-07, 4.0755e-07, 3.4795e-07],\n [4.7527e-07, 4.3678e-07, 4.9235e-07]],\n\n [[2.2471e-07, 1.9173e-07, 4.3686e-07],\n [3.0351e-07, 2.0944e-07, 3.2813e-07],\n [3.5146e-07, 3.7654e-07, 3.3577e-07]],\n\n [[8.2620e-08, 5.7736e-08, 9.5629e-08],\n [9.6783e-08, 5.9487e-08, 7.8799e-08],\n [9.3445e-08, 7.7041e-08, 7.6223e-08]],\n\n ...,\n\n [[2.9774e-07, 4.0143e-07, 3.2833e-07],\n [2.4826e-07, 4.7230e-07, 4.5788e-07],\n [3.9402e-07, 2.2458e-07, 2.9591e-07]],\n\n [[2.6769e-07, 2.7671e-07, 1.4193e-07],\n [3.1260e-07, 3.7753e-07, 1.9795e-07],\n [1.4850e-07, 3.3778e-07, 3.3897e-07]],\n\n [[3.3749e-07, 2.9048e-07, 1.5960e-07],\n [2.1359e-07, 2.6135e-07, 2.6579e-07],\n [2.2564e-07, 3.1388e-07, 3.6766e-07]]],\n\n\n ...,\n\n\n [[[1.5686e-07, 2.6883e-07, 3.0682e-07],\n [1.3623e-07, 2.8493e-07, 3.6353e-07],\n [9.7873e-08, 1.8298e-07, 2.7454e-07]],\n\n [[1.4444e-07, 1.1991e-07, 4.4368e-07],\n [1.4146e-07, 8.9464e-08, 3.2805e-07],\n [1.0026e-07, 1.3885e-07, 2.0388e-07]],\n\n [[7.3955e-08, 6.1637e-08, 6.3613e-08],\n [1.1384e-07, 9.6517e-08, 6.4368e-08],\n [9.2407e-08, 1.1063e-07, 9.5226e-08]],\n\n ...,\n\n [[1.5051e-07, 2.0228e-07, 2.7387e-07],\n [1.3340e-07, 1.6599e-07, 2.5583e-07],\n [3.0942e-07, 2.4226e-07, 2.6656e-07]],\n\n [[9.6426e-08, 1.2493e-07, 2.2108e-07],\n [1.1962e-07, 1.0125e-07, 1.8012e-07],\n [1.0913e-07, 1.1952e-07, 1.6019e-07]],\n\n [[7.8661e-08, 1.4775e-07, 2.5235e-07],\n [7.4203e-08, 1.0481e-07, 1.8950e-07],\n [9.6827e-08, 1.7805e-07, 2.1010e-07]]],\n\n\n [[[3.1286e-07, 1.5245e-07, 2.2441e-07],\n [1.6927e-07, 1.6055e-07, 3.4575e-07],\n [1.6465e-07, 2.0256e-07, 3.0474e-07]],\n\n [[2.1669e-07, 2.1978e-07, 1.5963e-07],\n [2.4472e-07, 2.1199e-07, 1.2096e-07],\n [1.8462e-07, 1.7798e-07, 1.3637e-07]],\n\n [[6.1412e-08, 7.1060e-08, 5.2997e-08],\n [6.0095e-08, 6.9431e-08, 5.5117e-08],\n [7.4971e-08, 6.9755e-08, 5.9976e-08]],\n\n ...,\n\n [[1.7168e-07, 1.6684e-07, 2.0494e-07],\n [1.8777e-07, 1.8157e-07, 2.5605e-07],\n [2.0441e-07, 1.6667e-07, 2.3589e-07]],\n\n [[1.1138e-07, 6.7682e-08, 1.0924e-07],\n [1.0295e-07, 1.2509e-07, 1.6580e-07],\n [1.1699e-07, 2.0302e-07, 1.5969e-07]],\n\n [[1.1406e-07, 1.1644e-07, 1.4015e-07],\n [1.2419e-07, 1.6792e-07, 1.6804e-07],\n [1.7748e-07, 2.4234e-07, 1.6970e-07]]],\n\n\n [[[3.0847e-07, 3.8996e-07, 3.5003e-07],\n [3.0756e-07, 1.7651e-07, 2.8066e-07],\n [2.8450e-07, 3.4497e-07, 2.9509e-07]],\n\n [[3.1886e-07, 3.2614e-07, 3.4596e-07],\n [4.2011e-07, 4.5068e-07, 3.9839e-07],\n [2.2093e-07, 2.4928e-07, 4.5607e-07]],\n\n [[6.7759e-08, 7.4798e-08, 5.8828e-08],\n [6.0343e-08, 1.0008e-07, 9.8471e-08],\n [5.5787e-08, 6.3369e-08, 7.4491e-08]],\n\n ...,\n\n [[4.6169e-07, 3.9576e-07, 3.2646e-07],\n [4.1311e-07, 2.6722e-07, 2.4035e-07],\n [3.8988e-07, 3.7888e-07, 3.1210e-07]],\n\n [[1.5429e-07, 2.2906e-07, 3.3080e-07],\n [1.4605e-07, 1.2853e-07, 2.1588e-07],\n [1.7535e-07, 1.6268e-07, 1.6142e-07]],\n\n [[3.0558e-07, 2.3858e-07, 2.3561e-07],\n [3.9513e-07, 1.7402e-07, 2.3289e-07],\n [2.2351e-07, 1.6388e-07, 2.2466e-07]]]])}, 28: {'step': 7160, 'exp_avg': tensor([-4.9333e-05, 2.4261e-04, -2.2767e-04, 1.6150e-04, 3.7002e-05,\n -3.4704e-05, 1.0013e-04, -7.0998e-05, -6.4538e-06, -8.5676e-05,\n 9.8990e-05, 1.6058e-05, 3.6995e-04, 1.9975e-04, 3.8805e-04,\n -8.0791e-05, -1.7737e-04, 1.2826e-04, 1.7128e-05, -3.4915e-04,\n 1.6139e-04, -1.1595e-04, 2.4586e-04, -2.7169e-04, -3.3783e-05,\n 5.9755e-05, 2.2421e-04, 5.2311e-05, -9.5172e-05, -2.4054e-04,\n -1.4738e-04, -4.4104e-04, -1.1678e-04, -4.8081e-06, 1.5969e-04,\n -1.6569e-04, 9.6239e-05, 2.8426e-04, -6.4933e-05, 3.9746e-04,\n 6.7964e-05, -5.3321e-04, -1.6992e-04, -1.9853e-04, -5.1605e-05,\n -3.5215e-04, 2.2871e-04, 1.2937e-05, -1.7209e-04, 1.4170e-04,\n 4.5180e-04, -2.2411e-04, -8.0496e-07, -2.2099e-04, -4.4448e-05,\n -2.3475e-05, -6.1443e-05, -1.4145e-04, 3.3160e-04, 3.5168e-05,\n -1.6257e-04, -3.0976e-05, -1.2483e-04, 2.9035e-06]), 'exp_avg_sq': tensor([5.9589e-06, 8.4347e-06, 1.0294e-05, 9.3528e-06, 6.3883e-06, 1.3230e-05,\n 7.0463e-06, 7.0090e-06, 1.0580e-05, 1.2199e-05, 6.2732e-06, 3.3094e-06,\n 9.8547e-06, 7.7299e-06, 8.1724e-06, 7.4728e-06, 1.0229e-05, 8.0818e-06,\n 7.5607e-06, 1.4619e-05, 6.9542e-06, 4.9929e-06, 1.0784e-05, 8.4212e-06,\n 6.1767e-06, 5.3877e-06, 9.3886e-06, 7.7919e-06, 1.1066e-05, 8.8010e-06,\n 1.1696e-05, 8.2556e-06, 6.1414e-06, 9.3343e-06, 4.8192e-06, 6.8414e-06,\n 9.2307e-06, 1.0704e-05, 2.0781e-05, 1.2024e-05, 7.8065e-06, 9.2912e-06,\n 7.6073e-06, 5.7530e-06, 1.1732e-05, 7.7179e-06, 9.6587e-06, 5.8358e-06,\n 9.8932e-06, 4.3856e-06, 1.1160e-05, 6.9930e-06, 7.4311e-06, 6.2794e-06,\n 5.1868e-06, 8.0873e-06, 7.5188e-06, 7.5337e-06, 6.1913e-06, 6.6844e-06,\n 9.1350e-06, 8.0673e-06, 8.2568e-06, 6.1239e-06])}, 29: {'step': 7160, 'exp_avg': tensor([-1.9648e-04, 2.6664e-04, -5.7363e-05, -8.2540e-05, 5.0865e-05,\n 6.0394e-05, 1.7958e-04, -7.0151e-05, 4.7831e-05, -2.7610e-05,\n 1.1285e-04, 1.6215e-06, 2.2058e-04, -1.1016e-04, -3.3049e-06,\n -9.5949e-05, -1.1457e-04, 1.1974e-05, 4.4091e-06, -1.2276e-04,\n 2.0893e-04, -1.4999e-04, -4.3755e-05, -2.6242e-04, -3.3286e-05,\n 2.6830e-04, -1.1577e-04, -1.8729e-05, 1.2206e-04, -9.1087e-05,\n -1.0399e-04, -3.4903e-04, -2.0010e-05, -1.2730e-04, 1.6957e-04,\n 3.9022e-05, 8.9219e-05, -8.9357e-05, -2.3289e-06, 3.2726e-04,\n 1.2303e-04, 1.3275e-04, -1.3373e-04, 3.1246e-04, 2.7499e-04,\n -2.6722e-04, 2.0114e-04, -1.0906e-05, -1.4670e-05, 1.2462e-04,\n -4.6781e-05, -2.2413e-04, -1.4331e-04, -2.9928e-04, 6.1541e-05,\n -9.6433e-05, -1.2665e-04, -1.9877e-04, 3.3911e-04, 1.2591e-04,\n 1.4673e-04, -1.3208e-05, -8.8517e-05, -1.1900e-04]), 'exp_avg_sq': tensor([6.5045e-06, 5.2305e-06, 6.2798e-06, 7.9299e-06, 4.3066e-06, 7.1240e-06,\n 4.8442e-06, 4.4835e-06, 4.3692e-06, 5.1334e-06, 6.5496e-06, 9.9647e-07,\n 5.8770e-06, 7.1441e-06, 5.2707e-06, 4.4747e-06, 6.6799e-06, 4.5587e-06,\n 5.3180e-06, 5.4223e-06, 4.9817e-06, 2.2231e-06, 6.7023e-06, 8.2133e-06,\n 3.1500e-06, 5.2157e-06, 6.3077e-06, 4.0394e-06, 8.8510e-06, 5.5272e-06,\n 3.8792e-06, 4.4701e-06, 4.3692e-06, 5.8012e-06, 5.0619e-06, 3.4731e-06,\n 3.8349e-06, 4.4208e-06, 2.2071e-07, 3.3084e-06, 4.5840e-06, 6.6572e-06,\n 4.3172e-06, 4.9871e-06, 7.3656e-06, 4.5665e-06, 3.9345e-06, 3.6357e-06,\n 6.0669e-06, 2.6734e-06, 5.8340e-06, 4.2000e-06, 5.6080e-06, 4.1046e-06,\n 3.3303e-06, 4.2655e-06, 4.6488e-06, 4.6009e-06, 6.6383e-06, 5.0104e-06,\n 4.6003e-06, 5.2180e-06, 4.3904e-06, 3.5701e-06])}, 30: {'step': 7160, 'exp_avg': tensor([[[[ 2.4028e-05]],\n\n [[ 2.9602e-05]],\n\n [[ 5.4290e-05]],\n\n ...,\n\n [[ 3.3224e-07]],\n\n [[ 7.9172e-05]],\n\n [[ 2.2592e-05]]],\n\n\n [[[ 1.2476e-05]],\n\n [[-3.4652e-05]],\n\n [[-4.6174e-05]],\n\n ...,\n\n [[ 1.9135e-05]],\n\n [[-3.3148e-05]],\n\n [[-1.9760e-05]]],\n\n\n [[[-6.7322e-05]],\n\n [[ 2.1041e-05]],\n\n [[ 8.5889e-05]],\n\n ...,\n\n [[-1.0084e-05]],\n\n [[ 4.1670e-05]],\n\n [[ 8.9534e-05]]],\n\n\n ...,\n\n\n [[[-2.8083e-06]],\n\n [[-2.2289e-06]],\n\n [[-3.1258e-06]],\n\n ...,\n\n [[ 4.3003e-07]],\n\n [[-2.8623e-06]],\n\n [[-2.5185e-06]]],\n\n\n [[[-3.0741e-06]],\n\n [[-7.3420e-06]],\n\n [[-3.0104e-06]],\n\n ...,\n\n [[-1.3197e-05]],\n\n [[ 1.9350e-05]],\n\n [[-1.6455e-07]]],\n\n\n [[[ 1.0316e-05]],\n\n [[-7.9525e-05]],\n\n [[ 1.5555e-05]],\n\n ...,\n\n [[ 3.6493e-05]],\n\n [[ 5.7309e-05]],\n\n [[ 2.0417e-06]]]]), 'exp_avg_sq': tensor([[[[1.2648e-07]],\n\n [[1.1710e-07]],\n\n [[1.3579e-07]],\n\n ...,\n\n [[1.8550e-07]],\n\n [[1.7022e-07]],\n\n [[1.4472e-07]]],\n\n\n [[[2.0386e-07]],\n\n [[1.3872e-07]],\n\n [[1.7091e-07]],\n\n ...,\n\n [[2.4229e-07]],\n\n [[1.9880e-07]],\n\n [[2.0131e-07]]],\n\n\n [[[4.1636e-07]],\n\n [[3.9483e-07]],\n\n [[4.1757e-07]],\n\n ...,\n\n [[6.5166e-07]],\n\n [[4.5981e-07]],\n\n [[2.7062e-07]]],\n\n\n ...,\n\n\n [[[4.8088e-09]],\n\n [[7.0688e-09]],\n\n [[5.6152e-09]],\n\n ...,\n\n [[8.2014e-09]],\n\n [[7.4867e-09]],\n\n [[5.8139e-09]]],\n\n\n [[[2.3632e-08]],\n\n [[3.9257e-08]],\n\n [[4.3955e-08]],\n\n ...,\n\n [[3.4958e-08]],\n\n [[4.2696e-08]],\n\n [[6.1394e-08]]],\n\n\n [[[5.6912e-07]],\n\n [[3.6511e-07]],\n\n [[2.8040e-07]],\n\n ...,\n\n [[6.9841e-07]],\n\n [[5.7509e-07]],\n\n [[3.1279e-07]]]])}, 31: {'step': 7160, 'exp_avg': tensor([ 3.4629e-04, -1.0620e-05, -6.6535e-05, -1.4208e-04, 5.4333e-05,\n 7.6926e-05, -9.3627e-06, 8.6335e-05, -1.8943e-04, 7.9038e-05,\n -2.7595e-04, -7.7210e-05, -1.5536e-04, -2.1651e-04, -6.8697e-05,\n -6.4832e-05, 1.8870e-05, 9.4562e-05, 2.5032e-05, 3.3286e-04,\n 9.2449e-06, 3.9701e-05, -5.1920e-05, 7.0043e-05, 1.8332e-04,\n -2.6905e-05, 4.8097e-06, -1.1930e-04, 6.4754e-05, -1.6263e-05,\n 4.0426e-05, -1.1862e-08, -7.1970e-05, 1.4358e-04, 3.0692e-05,\n 3.1472e-04, -8.6705e-05, 1.5395e-05, 1.7573e-05, 6.0576e-05,\n -8.4289e-05, 9.8192e-06, -6.3685e-05, -1.2289e-04, 1.0550e-05,\n 2.8817e-05, -4.2553e-05, 3.6528e-05, -1.0958e-04, 2.7056e-04,\n -9.0457e-05, 1.7986e-04, 9.4235e-05, -2.8647e-05, -8.2358e-05,\n -7.0280e-06, 6.3449e-05, -1.1702e-05, -1.1834e-04, -1.5022e-04,\n -1.4394e-05, -6.9394e-05, 6.3531e-05, -8.5517e-05, -3.9068e-05,\n -8.2650e-05, 9.1244e-05, -9.6421e-05, -2.2310e-05, 1.0976e-04,\n -5.3278e-05, 3.1839e-05, 1.7349e-04, 1.1546e-04, -1.6584e-05,\n -1.2830e-04, -7.0129e-05, 1.0187e-04, -2.0091e-05, 3.7344e-06,\n -1.3328e-05, -2.5927e-05, -2.0235e-04, 2.2460e-04, -1.3949e-04,\n -1.0543e-05, -1.9312e-05, 9.7786e-05, 1.5356e-04, -7.6655e-06,\n 2.3352e-04, -4.1723e-05, 8.1877e-05, 6.4791e-05, -1.5422e-05,\n 1.7780e-04, 4.5227e-05, -1.0744e-04, 2.0454e-04, 5.5062e-05,\n 3.7904e-05, 5.6572e-05, -4.7505e-05, -9.8327e-05, 6.3984e-05,\n -1.5479e-04, -5.6004e-06, 7.1432e-05, -1.0752e-04, 1.5517e-04,\n 5.5857e-05, -8.3540e-05, 2.0222e-04, -5.4951e-05, -6.4457e-05,\n 1.6717e-04, -4.3719e-05, 5.5756e-05, -5.4383e-05, -9.3526e-05,\n 4.2976e-05, 8.9213e-05, -5.7037e-05, -6.5296e-05, 2.0319e-05,\n -2.0750e-05, -4.4585e-05, 2.7211e-04, -1.4024e-04, 1.8891e-04,\n -5.6026e-05, 3.3283e-06, -7.8912e-05, -2.7548e-05, 1.3721e-04,\n -2.0066e-05, 5.3808e-05, 1.3368e-05, -1.2442e-04, 6.8977e-05,\n -1.4243e-04, 1.5777e-04, 4.3744e-05, -2.0433e-05, 6.1474e-06,\n 4.3142e-05, -2.1867e-05, 4.1599e-05, -3.5067e-04, -4.0370e-05,\n -4.7078e-05, -4.0074e-05, -1.2406e-04, -4.9628e-05, 1.9058e-04,\n 6.0948e-05, 9.9184e-05, 5.9215e-05, -2.2611e-04, -5.8617e-05,\n -2.0091e-04, -8.7710e-05, -1.1669e-04, -9.3341e-05, 3.6061e-06,\n -5.3685e-05, -3.5716e-05, -8.9833e-05, 2.4939e-05, 8.6593e-05,\n -4.4108e-05, -2.3021e-05, -2.1087e-04, -6.0209e-05, -9.5881e-05,\n -1.3943e-05, 1.3496e-05, 1.3919e-04, 9.4572e-05, 5.9994e-05,\n 1.6114e-04, -1.6067e-05, 2.4547e-05, 5.1394e-05, 1.7223e-04,\n 2.9794e-04, 2.0291e-04, -3.3108e-04, -3.4283e-05, 5.4277e-04,\n -1.4227e-04, -6.6883e-05, 6.9016e-04, -1.1541e-04, 1.4951e-04,\n 3.0491e-04, 7.8313e-05, -1.0218e-04, -5.8005e-05, 1.1209e-04,\n -1.5889e-04, -5.5953e-05, -3.9703e-05, 8.4439e-05, 7.0259e-05,\n 1.0737e-04, 4.2341e-05, -1.1965e-04, -1.4944e-04, -8.9486e-05,\n -3.8836e-05, -1.2519e-04, -3.5500e-05, -2.3274e-04, -7.9335e-05,\n 1.1202e-04, -2.8484e-05, -1.3421e-04, -5.5747e-06, -1.2320e-04,\n -2.5709e-04, 3.1073e-05, 1.5576e-04, 1.7372e-04, -7.7218e-05,\n 1.3492e-05, -3.5899e-04, 3.8497e-05, -1.4900e-04, -1.1029e-05,\n -8.8534e-05, -1.5064e-04, 6.5300e-06, -8.3635e-05, 3.3736e-06,\n -8.1967e-05, -7.2793e-05, 3.9119e-04, -1.7738e-04, 5.1420e-07,\n -8.5260e-05, -1.0047e-04, -6.6934e-04, 1.0577e-04, -1.7923e-05,\n 6.0238e-05, -1.2362e-04, -3.0782e-05, 5.1315e-05, -6.7046e-05,\n -6.5648e-05, -1.0702e-04, 1.0424e-04, 1.8109e-04, 9.7263e-05,\n 5.1887e-05]), 'exp_avg_sq': tensor([3.3158e-05, 4.3967e-05, 2.2009e-06, 4.3189e-06, 2.8100e-06, 8.4266e-06,\n 5.7275e-06, 1.0646e-05, 1.2938e-05, 2.2222e-06, 4.8169e-06, 1.3453e-06,\n 3.6413e-06, 9.0724e-06, 3.1124e-06, 2.9568e-06, 2.3301e-06, 4.3745e-06,\n 3.0087e-07, 9.7188e-06, 2.7044e-06, 1.6441e-06, 1.8256e-06, 3.3529e-06,\n 6.1417e-06, 7.0208e-07, 1.5295e-06, 2.4982e-06, 3.0928e-06, 2.7785e-06,\n 2.7354e-06, 1.7864e-06, 2.5533e-06, 1.8709e-06, 2.4048e-06, 4.0537e-06,\n 3.2480e-06, 2.4283e-06, 7.4425e-06, 1.2153e-05, 1.2324e-06, 4.6241e-06,\n 2.5621e-06, 4.3062e-06, 3.8973e-06, 1.3125e-06, 1.5154e-06, 1.6405e-06,\n 1.6620e-06, 3.3799e-06, 3.1196e-06, 3.5164e-06, 1.7257e-06, 1.1581e-06,\n 2.6263e-06, 5.5042e-06, 5.4727e-06, 3.2436e-06, 1.2487e-06, 1.5461e-06,\n 3.2472e-06, 2.9284e-06, 3.1635e-06, 1.8599e-06, 2.4269e-06, 2.1459e-05,\n 1.1452e-06, 1.0662e-06, 7.2892e-07, 6.5706e-06, 5.0031e-07, 1.8153e-06,\n 7.8927e-06, 1.2618e-05, 2.7188e-06, 1.8317e-06, 4.3885e-06, 1.0765e-06,\n 7.5298e-07, 2.5125e-06, 3.8191e-06, 2.7563e-06, 4.4742e-06, 2.7570e-06,\n 3.9474e-06, 7.3710e-06, 1.9603e-06, 1.1353e-06, 1.1092e-05, 5.5197e-06,\n 1.0700e-05, 7.5804e-07, 1.0292e-05, 1.5664e-06, 1.6073e-06, 2.9333e-06,\n 3.5910e-06, 8.9930e-07, 3.0911e-06, 3.0748e-06, 2.5365e-06, 2.0009e-06,\n 3.5261e-06, 3.2909e-06, 3.1084e-06, 3.2713e-06, 1.8877e-06, 3.5037e-06,\n 4.3769e-06, 1.3978e-06, 1.4973e-05, 2.2829e-06, 1.2865e-05, 2.9089e-06,\n 4.1586e-06, 3.4941e-06, 2.0043e-06, 1.2429e-06, 1.0802e-05, 3.0506e-06,\n 1.2706e-06, 2.6986e-06, 2.6691e-06, 3.4673e-06, 2.5172e-06, 3.0996e-06,\n 1.1658e-06, 3.9475e-06, 4.3427e-06, 6.3142e-06, 7.6904e-06, 2.1233e-06,\n 2.4033e-06, 1.6452e-06, 1.8589e-06, 2.5114e-06, 1.1115e-06, 3.7811e-06,\n 3.1464e-06, 1.4211e-06, 1.3548e-06, 1.7387e-06, 2.3387e-06, 2.9154e-06,\n 5.0021e-07, 5.0794e-06, 2.8580e-06, 2.1964e-06, 2.3946e-06, 2.3811e-06,\n 2.8503e-06, 2.9737e-06, 2.4403e-06, 3.0190e-06, 3.1145e-06, 1.8352e-06,\n 2.1673e-06, 2.2230e-06, 5.0463e-06, 2.9694e-06, 6.6029e-06, 1.9818e-05,\n 2.6577e-06, 2.3039e-05, 1.2960e-06, 2.6914e-06, 1.1692e-06, 2.8890e-06,\n 2.1230e-06, 1.0125e-06, 2.6232e-06, 1.8208e-06, 1.3778e-06, 1.5934e-06,\n 2.6548e-06, 3.0323e-06, 2.1294e-06, 7.0537e-06, 1.0904e-06, 2.3804e-06,\n 1.0973e-06, 6.6485e-07, 1.1176e-06, 2.6595e-06, 1.3159e-05, 6.0644e-06,\n 4.1303e-06, 5.3622e-06, 3.5439e-06, 6.2322e-05, 4.6370e-06, 3.3329e-06,\n 2.9306e-05, 1.5080e-06, 1.4076e-06, 3.8911e-06, 1.8477e-06, 2.3630e-06,\n 1.6662e-06, 1.5799e-06, 3.6104e-06, 3.8791e-06, 2.7866e-06, 2.9951e-06,\n 3.3360e-06, 2.6952e-06, 8.6251e-07, 3.4323e-06, 1.9186e-06, 2.7382e-06,\n 6.7391e-07, 2.1844e-06, 1.6473e-06, 3.9128e-06, 4.5528e-07, 3.0093e-06,\n 1.2880e-06, 1.3455e-06, 2.1350e-06, 4.1606e-06, 6.5957e-05, 2.7884e-06,\n 1.3511e-06, 2.2436e-05, 7.2542e-07, 1.1030e-06, 1.5335e-05, 2.0546e-06,\n 1.4843e-05, 6.3152e-06, 2.1876e-06, 3.5817e-06, 3.0892e-06, 1.2596e-06,\n 3.4481e-06, 3.3029e-06, 3.5658e-06, 4.7711e-05, 2.4298e-06, 2.1066e-07,\n 1.7024e-06, 2.4193e-06, 4.3015e-05, 5.9466e-06, 6.6862e-06, 2.2632e-06,\n 2.5626e-06, 3.1877e-06, 3.1148e-06, 1.2325e-06, 2.2113e-06, 1.2087e-05,\n 5.9160e-06, 1.3215e-05, 6.8766e-06, 1.5608e-06])}, 32: {'step': 7160, 'exp_avg': tensor([-3.5179e-04, -2.6871e-06, -5.1462e-05, -4.9843e-05, 6.4064e-05,\n -6.7916e-11, 7.2110e-05, -3.0943e-05, 1.7637e-04, -7.4003e-05,\n -3.8239e-06, 1.3535e-05, -9.7775e-05, 1.2979e-04, -1.7243e-05,\n 1.5550e-05, -1.5011e-05, 5.0137e-05, 1.1875e-06, 4.8685e-11,\n 2.8740e-05, 1.8667e-04, 1.0222e-04, 1.2649e-04, -6.4803e-05,\n -2.7072e-05, 8.8336e-05, 2.5364e-06, -3.2300e-10, -7.7383e-11,\n -5.3009e-05, -3.3932e-07, 7.5705e-09, -1.6138e-05, -1.9509e-05,\n -2.9797e-06, -3.5152e-05, -3.0851e-08, -3.6005e-07, -1.7761e-04,\n 3.4244e-05, -5.1764e-08, -2.7209e-04, -8.4243e-06, -6.0174e-05,\n -3.7151e-05, -1.4790e-10, 3.0666e-06, -6.2422e-05, 2.5881e-05,\n 8.0972e-06, 3.1372e-06, 9.5872e-05, 1.0729e-04, -3.4356e-11,\n -4.8088e-07, -1.3399e-08, -7.3215e-05, -6.5345e-05, -2.5451e-11,\n -9.0314e-05, -6.5706e-05, -4.4569e-08, -2.8599e-06, 2.6350e-05,\n -1.7465e-07, 2.8111e-05, -2.5334e-05, 1.7432e-05, -2.0285e-05,\n -2.5655e-05, -2.1729e-05, -2.3621e-05, 1.2594e-10, 1.0698e-04,\n -7.3439e-05, 4.4078e-05, -7.1142e-05, 3.1815e-08, -2.4780e-05,\n 1.8175e-05, -7.6155e-08, -7.1338e-07, 1.3257e-04, 2.0007e-05,\n 4.7729e-06, -5.8197e-05, 8.6309e-05, 1.9442e-07, 6.8704e-06,\n 4.5240e-11, -3.4037e-05, 1.2676e-06, 3.9838e-05, -5.7608e-06,\n 4.8414e-05, 4.7932e-11, -4.7967e-05, 3.2560e-06, -1.0821e-05,\n 3.8299e-05, -1.5653e-04, -2.1150e-04, 1.3630e-04, -9.2718e-05,\n -1.6356e-06, -4.1157e-05, -5.5410e-05, -1.7524e-11, -4.3783e-11,\n 5.9565e-07, 3.6940e-11, 1.5260e-10, 3.0908e-06, -2.5439e-05,\n 3.7241e-05, -6.0669e-06, 5.1275e-05, -3.7619e-05, -1.1429e-05,\n 1.8446e-05, 5.1787e-05, -7.5112e-05, 1.0358e-04, -6.5815e-05,\n -1.3635e-10, 6.3916e-05, 9.3990e-05, 2.1650e-05, 5.1043e-05,\n -7.3304e-05, 1.5310e-05, -4.1960e-06, 3.2256e-05, 1.0943e-04,\n -2.4870e-05, 1.2617e-05, 5.6631e-05, -1.4132e-05, -4.5797e-05,\n -6.3955e-05, 1.0673e-06, 2.3929e-05, -7.0519e-05, 5.5207e-06,\n 3.9053e-06, 3.3328e-05, -3.7529e-05, 1.6150e-05, -2.0786e-05,\n -3.9542e-05, 1.4345e-05, -3.4840e-05, 1.2203e-05, -3.0156e-08,\n -3.7285e-05, -5.4350e-06, 7.8138e-05, 8.2912e-06, 2.7110e-10,\n 6.0131e-05, -9.5448e-06, 1.4088e-06, 2.3180e-07, -4.9502e-05,\n -9.4822e-05, 3.0271e-05, 1.4686e-10, 7.2067e-05, 5.5769e-06,\n -7.3067e-06, -6.6756e-05, -8.1470e-05, 4.4523e-06, 7.7806e-05,\n -3.8007e-05, 1.1686e-05, 1.0872e-10, 8.9981e-05, -5.0993e-06,\n 8.7289e-05, 8.7396e-06, 2.8124e-05, 6.4780e-05, 3.0276e-07,\n 4.9501e-05, -2.8270e-11, -6.1972e-07, -2.3363e-11, -3.9013e-08,\n -1.2596e-05, 1.8037e-07, -1.8695e-09, 6.7777e-05, 3.7446e-05,\n -1.9060e-10, -1.0752e-04, 1.5195e-05, -9.7531e-06, 8.7410e-05,\n -4.2316e-05, 4.1819e-05, -7.7848e-05, 2.5239e-09, 4.5414e-05,\n 8.1370e-09, 6.2278e-05, 2.0890e-05, 2.8788e-05, 5.1083e-07,\n -3.4922e-05, -1.5472e-05, -1.5439e-05, 1.5426e-05, -2.6395e-05,\n 8.7977e-07, -5.4745e-05, 6.0023e-05, -1.2778e-04, -9.3964e-05,\n -4.5615e-07, -1.4199e-05, 1.1440e-05, -5.9930e-09, -1.4621e-08,\n -1.3128e-04, -2.7764e-08, 5.8857e-05, 1.1084e-07, 4.7471e-05,\n -2.0234e-05, 2.1297e-10, 2.2368e-05, 6.7746e-06, 2.4766e-06,\n -5.0250e-05, -4.5870e-05, 4.6466e-10, 4.8260e-05, 2.8265e-05,\n 5.2093e-05, 7.5835e-06, -4.3828e-10, 4.0181e-12, 7.5549e-05,\n 4.8909e-07, 4.7432e-06, -8.7967e-05, -5.8829e-05, -1.3541e-05,\n -1.0059e-10, -3.8872e-05, -1.2189e-04, 2.3051e-07, -3.8086e-06,\n 1.4420e-05]), 'exp_avg_sq': tensor([2.8167e-05, 9.0060e-09, 9.8988e-07, 2.4979e-07, 4.3484e-07, 7.2863e-12,\n 9.2218e-07, 1.2598e-06, 6.9488e-06, 4.8723e-07, 7.4481e-10, 6.6242e-07,\n 1.0206e-06, 7.3873e-06, 2.4492e-06, 3.0518e-07, 3.0511e-08, 7.7632e-07,\n 2.9550e-07, 3.0475e-11, 9.4952e-07, 1.0318e-06, 1.1262e-06, 1.1934e-06,\n 2.1401e-06, 5.4095e-07, 3.4779e-06, 8.0102e-08, 3.0645e-11, 6.9691e-09,\n 2.6651e-06, 5.8100e-10, 2.5323e-10, 1.1394e-07, 3.4740e-07, 3.2892e-08,\n 1.8399e-06, 6.7552e-08, 1.5797e-09, 1.9829e-06, 9.4701e-07, 2.7452e-08,\n 2.7500e-06, 5.4889e-09, 1.8358e-07, 8.4027e-07, 4.5166e-11, 9.5440e-07,\n 5.6992e-07, 4.4953e-07, 5.5481e-08, 1.0928e-08, 1.7832e-06, 6.0105e-07,\n 8.7753e-11, 1.1062e-08, 6.4726e-09, 1.3206e-06, 1.9300e-06, 2.4147e-10,\n 9.0242e-07, 1.0143e-06, 1.0639e-09, 4.7342e-09, 1.5550e-06, 2.4520e-09,\n 5.4160e-07, 1.8902e-07, 4.4061e-07, 2.5247e-06, 5.1643e-07, 6.6415e-07,\n 3.7346e-08, 3.8127e-14, 1.9116e-06, 5.9480e-07, 3.7210e-07, 1.7355e-06,\n 5.2276e-09, 9.2685e-07, 1.5875e-07, 9.0261e-10, 4.5323e-10, 1.5560e-06,\n 2.4950e-08, 2.6386e-08, 7.3696e-07, 8.7319e-07, 5.7347e-11, 1.2745e-06,\n 7.9897e-11, 5.2475e-07, 4.2001e-09, 1.2046e-06, 9.7732e-07, 1.9873e-07,\n 3.6080e-13, 5.0130e-07, 4.4169e-08, 4.3201e-07, 1.1060e-06, 2.0431e-06,\n 2.5714e-06, 3.5673e-07, 1.7092e-06, 3.9264e-06, 1.1254e-06, 1.1132e-06,\n 8.9270e-11, 1.1198e-11, 2.6364e-09, 5.9906e-10, 5.0707e-09, 9.3220e-08,\n 4.2088e-06, 1.5453e-06, 5.8807e-09, 5.3458e-07, 1.6484e-06, 2.0273e-07,\n 1.0805e-06, 7.9956e-07, 1.0744e-06, 2.4058e-06, 8.1576e-07, 1.1524e-11,\n 7.1786e-07, 1.8003e-06, 3.3060e-07, 1.2639e-06, 3.1803e-06, 1.9031e-06,\n 1.1353e-06, 7.7675e-07, 5.7316e-07, 5.6827e-07, 4.0158e-07, 6.0448e-07,\n 2.1825e-07, 6.4102e-07, 5.0044e-07, 9.7123e-09, 1.1249e-06, 4.8068e-07,\n 9.0487e-07, 1.0267e-07, 2.3008e-07, 6.3860e-07, 7.8319e-07, 1.4260e-07,\n 4.0885e-06, 1.0005e-06, 9.6403e-07, 3.3134e-07, 6.6739e-10, 7.6369e-07,\n 1.6878e-06, 1.0175e-06, 2.9950e-08, 7.8991e-12, 6.7713e-06, 2.8949e-06,\n 1.6648e-09, 1.0677e-10, 6.0625e-07, 3.1134e-07, 6.2517e-07, 9.1172e-13,\n 1.8361e-06, 5.9408e-07, 2.0627e-07, 2.4961e-07, 5.5655e-07, 5.9648e-07,\n 6.4630e-07, 7.9684e-07, 3.0622e-06, 1.9799e-11, 5.0370e-07, 5.5912e-07,\n 1.4309e-06, 2.5208e-06, 4.5170e-07, 2.1579e-06, 8.8635e-08, 6.9204e-07,\n 6.7593e-07, 6.6892e-08, 3.4204e-09, 7.2111e-11, 1.2398e-07, 7.1168e-11,\n 1.0573e-08, 5.0014e-07, 4.2257e-07, 3.1515e-10, 2.3942e-06, 1.8270e-07,\n 4.8336e-07, 5.1225e-07, 6.8656e-07, 4.0696e-07, 1.3277e-06, 4.3590e-13,\n 8.7971e-07, 1.9577e-10, 5.1378e-07, 6.4833e-08, 4.7606e-07, 2.7941e-08,\n 4.9883e-07, 2.0859e-06, 4.9297e-07, 8.4937e-07, 6.4531e-07, 1.6410e-08,\n 6.1949e-07, 9.6148e-07, 2.3486e-06, 1.1590e-06, 2.2582e-08, 8.9148e-07,\n 1.2466e-06, 2.0226e-07, 2.4111e-11, 1.2622e-06, 2.1070e-10, 9.2486e-07,\n 3.4988e-10, 3.3065e-07, 5.3476e-07, 4.2931e-12, 2.1760e-07, 1.2593e-06,\n 7.5774e-09, 1.0574e-06, 1.9876e-06, 6.8751e-17, 9.2757e-07, 2.5565e-07,\n 4.7207e-07, 5.7438e-08, 8.9349e-12, 3.5967e-11, 1.0969e-06, 4.5594e-09,\n 7.9814e-07, 1.2550e-06, 7.5365e-07, 4.2799e-07, 3.0477e-11, 1.8408e-05,\n 4.2799e-06, 4.6437e-10, 5.1056e-08, 7.2178e-07])}, 33: {'step': 7160, 'exp_avg': tensor([[[[ 8.7076e-06]],\n\n [[ 2.1466e-05]],\n\n [[ 6.0639e-05]],\n\n ...,\n\n [[ 2.8830e-05]],\n\n [[-2.6208e-05]],\n\n [[ 3.1459e-05]]],\n\n\n [[[-6.3886e-05]],\n\n [[-7.2161e-05]],\n\n [[-2.6604e-05]],\n\n ...,\n\n [[-7.6971e-05]],\n\n [[-5.1463e-05]],\n\n [[-1.7199e-06]]],\n\n\n [[[-5.1808e-05]],\n\n [[-7.7473e-05]],\n\n [[ 1.2400e-05]],\n\n ...,\n\n [[-2.7529e-05]],\n\n [[-1.9946e-05]],\n\n [[-8.7953e-06]]],\n\n\n ...,\n\n\n [[[-1.1412e-05]],\n\n [[-1.3654e-05]],\n\n [[-4.8210e-05]],\n\n ...,\n\n [[-2.7715e-05]],\n\n [[ 1.3657e-05]],\n\n [[-4.3604e-05]]],\n\n\n [[[-5.3016e-05]],\n\n [[-8.4816e-05]],\n\n [[ 4.9317e-05]],\n\n ...,\n\n [[-5.9636e-05]],\n\n [[-9.9217e-06]],\n\n [[ 5.6305e-06]]],\n\n\n [[[-2.8576e-05]],\n\n [[-5.0646e-05]],\n\n [[-7.9308e-05]],\n\n ...,\n\n [[-2.6321e-05]],\n\n [[ 5.1405e-05]],\n\n [[ 4.0899e-05]]]]), 'exp_avg_sq': tensor([[[[4.6612e-07]],\n\n [[1.0978e-06]],\n\n [[4.1109e-07]],\n\n ...,\n\n [[4.2113e-07]],\n\n [[3.7332e-07]],\n\n [[3.4213e-07]]],\n\n\n [[[2.4056e-07]],\n\n [[6.2979e-07]],\n\n [[1.6162e-07]],\n\n ...,\n\n [[2.2512e-07]],\n\n [[3.3309e-07]],\n\n [[1.3431e-07]]],\n\n\n [[[2.0410e-07]],\n\n [[3.7440e-07]],\n\n [[5.7791e-08]],\n\n ...,\n\n [[1.4057e-07]],\n\n [[3.9384e-07]],\n\n [[1.2459e-07]]],\n\n\n ...,\n\n\n [[[3.6953e-07]],\n\n [[6.2180e-07]],\n\n [[1.7312e-07]],\n\n ...,\n\n [[2.4085e-07]],\n\n [[3.7911e-07]],\n\n [[4.2381e-07]]],\n\n\n [[[5.4309e-07]],\n\n [[1.2801e-06]],\n\n [[6.0317e-07]],\n\n ...,\n\n [[3.4345e-07]],\n\n [[6.9306e-07]],\n\n [[7.7793e-07]]],\n\n\n [[[6.2890e-07]],\n\n [[1.9711e-06]],\n\n [[6.4774e-07]],\n\n ...,\n\n [[4.6292e-07]],\n\n [[1.0931e-06]],\n\n [[3.1673e-07]]]])}, 34: {'step': 7160, 'exp_avg': tensor([-1.8944e-05, 1.3049e-04, -1.1325e-04, 5.8129e-05, -2.4728e-04,\n 2.9974e-05, -2.2574e-06, -9.5120e-05, -2.3595e-04, -7.3165e-05,\n -1.2707e-04, 1.0036e-04, 1.3476e-04, -1.5198e-04, 4.5252e-05,\n -1.9223e-04, 2.9131e-05, 2.3785e-05, 1.1934e-04, 2.1131e-04,\n 2.7245e-04, 8.2660e-06, -1.3803e-04, 2.3570e-04, 1.9185e-04,\n -1.3649e-04, -2.5665e-05, -5.1204e-05, 1.1086e-04, -2.6853e-04,\n -1.4573e-04, -1.9654e-06, 4.9952e-05, -2.4679e-04, -1.8216e-04,\n 1.5539e-04, 5.1246e-05, -3.5867e-05, -3.2684e-04, -3.3396e-04,\n -4.4545e-05, 1.4652e-04, 1.1845e-04, 7.4099e-05, 2.6737e-05,\n 5.1060e-05, 3.3578e-05, 1.3902e-04, 2.0103e-04, -2.8717e-04,\n 3.4323e-05, 1.2261e-04, 3.4169e-04, 7.6352e-06, -1.1382e-04,\n 1.6712e-04, -8.4872e-05, 1.3821e-05, 7.2029e-05, 3.1714e-04,\n -1.0213e-06, 8.4038e-05, 1.1334e-04, -7.2667e-05, -2.5658e-04,\n 6.4055e-04, 4.7873e-04, 1.0076e-04, 7.3410e-06, -2.0697e-05,\n -3.3233e-05, 1.9044e-04, 2.9519e-05, -2.3761e-05, -2.8591e-04,\n 3.0553e-04, 1.8019e-04, -4.4773e-05, 4.7895e-05, -1.7265e-04,\n -3.4879e-06, 2.1011e-04, -2.5697e-04, -1.6789e-04, 3.1246e-04,\n 1.9193e-05, 4.6616e-05, -3.3155e-05, 3.4468e-04, 7.4620e-06,\n 4.1390e-05, 2.5844e-05, -4.7373e-05, 5.1037e-05, 1.9967e-04,\n -3.9654e-05, -2.1689e-04, -2.6153e-05, 9.2056e-05, -7.9973e-05,\n -1.5898e-04, -2.8860e-04, -2.4205e-04, -3.7727e-04, 1.9133e-04,\n -3.2129e-05, 8.7481e-06, -7.4641e-05, 2.7916e-05, -2.0977e-04,\n -2.6669e-06, 8.3807e-05, -3.7371e-06, -1.3044e-04, -1.2892e-04,\n 3.7190e-05, 1.2475e-04, 4.0073e-05, 2.0722e-04, 7.1247e-05,\n -8.2866e-05, -6.4933e-05, 1.0474e-04, 9.0880e-05, 1.6689e-04,\n -1.2742e-04, -2.0837e-04, -5.5163e-05]), 'exp_avg_sq': tensor([6.9191e-06, 4.1624e-06, 6.2278e-06, 4.8731e-06, 5.8602e-06, 1.5116e-05,\n 5.3100e-06, 5.7159e-06, 2.2361e-06, 4.8220e-06, 5.1531e-06, 3.1627e-06,\n 1.4397e-05, 1.1285e-05, 8.4814e-06, 9.0132e-06, 5.4070e-06, 1.0455e-05,\n 9.9827e-06, 3.1075e-06, 1.4180e-05, 4.2914e-06, 1.3291e-05, 3.1677e-06,\n 7.1403e-06, 5.8838e-06, 4.4978e-06, 1.3484e-05, 1.6110e-05, 7.0896e-06,\n 3.6107e-06, 8.5548e-06, 3.7571e-06, 4.7611e-06, 9.7032e-06, 9.3933e-06,\n 8.8185e-06, 6.9033e-06, 7.3637e-06, 7.2470e-06, 9.1571e-06, 3.8539e-06,\n 7.9022e-06, 5.1786e-06, 4.9515e-06, 7.1779e-06, 2.4710e-06, 4.0475e-06,\n 4.0261e-06, 3.3447e-06, 8.3095e-06, 5.1688e-06, 4.0479e-06, 7.5639e-06,\n 1.3451e-06, 5.4611e-06, 7.7695e-06, 5.6099e-06, 1.2986e-05, 1.1579e-05,\n 6.8957e-06, 3.8889e-06, 2.9533e-06, 1.1450e-05, 8.9169e-06, 7.1691e-06,\n 1.0120e-05, 3.1651e-06, 4.7150e-06, 4.1500e-06, 1.1949e-05, 4.5647e-06,\n 9.4769e-06, 6.4841e-06, 4.2442e-06, 8.6548e-06, 1.6437e-05, 6.0424e-06,\n 8.6209e-06, 4.6041e-06, 3.6498e-06, 1.0772e-05, 4.8726e-06, 5.7795e-06,\n 1.1761e-05, 4.2164e-06, 4.4191e-06, 2.7524e-06, 7.5287e-06, 4.9970e-06,\n 2.3675e-06, 4.0282e-06, 7.3872e-06, 4.6534e-06, 9.4670e-06, 9.0413e-06,\n 9.1956e-06, 4.9543e-06, 4.4928e-06, 7.0317e-06, 6.3662e-06, 5.3454e-06,\n 6.2225e-06, 1.1871e-05, 7.4907e-06, 5.8743e-06, 8.6328e-06, 6.5796e-06,\n 6.5931e-06, 7.8973e-06, 4.0687e-06, 4.2337e-06, 6.1785e-06, 5.4216e-06,\n 5.6194e-06, 1.0081e-05, 5.2390e-06, 4.2977e-06, 7.6196e-06, 3.4040e-06,\n 1.1244e-05, 4.8164e-06, 4.9921e-06, 2.7656e-06, 9.2049e-06, 6.1640e-06,\n 8.9116e-06, 1.3142e-05])}, 35: {'step': 7160, 'exp_avg': tensor([-3.2257e-06, -2.5714e-05, -1.0886e-04, 7.3692e-05, -9.7971e-05,\n -9.8553e-05, 9.9440e-05, -1.0095e-04, -1.2483e-04, -9.3328e-05,\n -3.7570e-05, 3.2967e-06, 3.0684e-05, -1.1063e-04, -6.5812e-05,\n -1.2557e-04, 3.0168e-05, -1.5700e-04, 2.4947e-04, 9.6852e-05,\n 2.0179e-04, -4.8435e-05, -4.9452e-05, -1.1586e-04, 1.3758e-04,\n -8.4161e-05, -9.3784e-06, 7.8175e-05, 6.3061e-06, -2.6885e-04,\n -5.8951e-05, -2.1913e-05, 1.1452e-04, -7.7898e-05, -1.0955e-04,\n 1.6722e-05, -1.1957e-04, 3.3659e-05, -5.0309e-05, -3.8189e-04,\n -1.1492e-04, 1.4432e-04, 1.0892e-04, 8.2002e-05, -1.5912e-04,\n 8.8098e-05, 2.2284e-04, 5.5875e-06, -1.2667e-05, -2.3509e-04,\n 3.4793e-05, 1.3928e-04, 2.2576e-04, 1.7827e-05, -8.2255e-05,\n 2.3602e-04, 1.0116e-04, 4.6079e-05, -2.5744e-05, 3.2672e-04,\n 9.4742e-05, 1.5104e-04, 6.7398e-05, -5.2967e-05, -1.4420e-04,\n 4.4153e-04, 2.7056e-04, 4.1547e-05, 2.7823e-05, 9.6008e-06,\n -5.2663e-05, 2.5875e-04, 8.4571e-05, 8.2678e-05, -1.6346e-04,\n 2.6837e-04, 1.7800e-04, 3.8821e-05, 9.5552e-05, -2.3641e-04,\n -1.5228e-04, 2.2733e-04, -1.6776e-04, -5.8640e-05, 1.6488e-04,\n 4.8758e-05, 5.1465e-05, 3.2016e-05, 2.1257e-04, 1.9747e-05,\n 4.5373e-05, 7.9506e-05, -8.4107e-05, 6.4578e-05, 2.0521e-05,\n -1.4772e-05, -1.5292e-04, -8.0630e-05, 9.9656e-05, -7.6143e-05,\n -5.4947e-05, -2.4256e-04, -4.9218e-05, -1.3804e-04, 1.0423e-04,\n 1.0564e-05, -1.2033e-05, -5.6790e-05, 4.5794e-05, -7.6884e-05,\n -2.0714e-06, -3.8511e-05, -2.9214e-05, -2.6559e-04, -1.8438e-04,\n -1.6187e-05, 1.0069e-04, -7.7012e-06, 8.9416e-05, -2.6864e-05,\n -3.9081e-05, -3.5239e-05, 4.3009e-05, 5.5447e-05, -5.2923e-05,\n -4.9526e-05, -3.6720e-04, -2.2557e-06]), 'exp_avg_sq': tensor([2.8989e-06, 2.5881e-06, 1.2679e-06, 2.7158e-06, 4.2346e-06, 4.4095e-06,\n 2.7024e-06, 1.8947e-06, 1.3318e-06, 2.8901e-06, 2.8115e-06, 1.5909e-06,\n 7.6361e-07, 4.1444e-06, 2.8057e-06, 3.9270e-06, 2.6577e-06, 3.3027e-06,\n 5.6140e-06, 1.2005e-06, 5.0176e-06, 2.8399e-06, 4.3132e-06, 1.8331e-06,\n 4.2912e-06, 2.0359e-06, 2.1720e-06, 2.5938e-06, 6.7377e-06, 3.2871e-06,\n 3.2770e-06, 2.7599e-06, 1.9969e-06, 2.6921e-06, 5.2348e-06, 5.6812e-06,\n 4.5806e-06, 4.1043e-06, 6.2127e-06, 5.5403e-06, 3.6798e-06, 2.6028e-06,\n 2.8426e-06, 2.3409e-06, 3.1658e-06, 2.8787e-06, 2.3991e-06, 2.7338e-06,\n 3.2434e-06, 1.8322e-06, 3.5306e-06, 2.8147e-06, 2.3041e-06, 9.2278e-07,\n 2.5191e-07, 3.3685e-06, 5.2927e-06, 4.0302e-06, 4.3940e-06, 7.8924e-06,\n 3.8770e-06, 1.7427e-06, 1.3147e-06, 3.4452e-06, 3.5346e-06, 2.9591e-06,\n 2.5053e-06, 1.3895e-06, 1.6157e-06, 2.5987e-06, 4.1860e-06, 6.9130e-06,\n 3.7507e-06, 2.5599e-06, 3.0333e-06, 4.8973e-06, 7.2440e-06, 2.7525e-06,\n 3.2940e-06, 2.9105e-06, 3.1732e-06, 4.1037e-06, 1.8844e-06, 3.6200e-06,\n 5.0313e-06, 2.0626e-06, 1.7956e-06, 1.9268e-06, 3.1981e-06, 2.3449e-06,\n 1.9758e-06, 3.4328e-06, 7.8298e-07, 3.9170e-06, 5.4844e-06, 3.7910e-06,\n 5.2553e-06, 3.2350e-06, 2.6500e-06, 2.2470e-06, 3.7409e-06, 2.0618e-06,\n 2.8764e-06, 4.4026e-06, 2.5783e-06, 4.8507e-06, 4.3332e-06, 7.9145e-06,\n 2.8284e-06, 3.6594e-06, 1.7497e-06, 2.9070e-06, 2.4787e-06, 2.9028e-06,\n 2.1516e-06, 5.1846e-06, 2.8443e-06, 1.6391e-06, 3.5215e-06, 1.7637e-06,\n 3.8872e-06, 9.9717e-07, 1.8295e-06, 2.1443e-06, 3.2463e-06, 3.2479e-06,\n 6.3700e-06, 2.7275e-06])}, 36: {'step': 7160, 'exp_avg': tensor([[[[-2.6756e-05, 2.9540e-05, -1.7592e-06],\n [ 9.4683e-06, -6.6805e-06, -6.9014e-06],\n [-2.6585e-06, 3.1976e-05, 2.8999e-07]],\n\n [[ 1.9952e-05, 1.3951e-05, 1.1000e-05],\n [ 2.2751e-05, -1.1370e-06, 4.7157e-06],\n [ 3.3455e-05, 1.7580e-05, 8.8558e-06]],\n\n [[-1.1001e-05, -2.8383e-06, -1.0411e-05],\n [ 7.7242e-06, 1.7713e-05, 1.9544e-05],\n [-4.9376e-06, 1.2070e-05, -2.6198e-06]],\n\n ...,\n\n [[ 4.4860e-06, -1.4232e-05, 1.6166e-06],\n [-2.8204e-06, -1.4666e-05, -2.8144e-06],\n [ 6.4554e-06, -1.0777e-05, 4.1996e-05]],\n\n [[ 2.0283e-05, 5.3520e-05, 5.1983e-05],\n [ 1.7713e-05, 1.8504e-05, 4.1550e-05],\n [ 3.7341e-05, 3.2352e-05, 4.9015e-05]],\n\n [[-3.8468e-06, 8.6322e-06, -4.8414e-06],\n [-4.1247e-06, -6.5243e-06, -4.8724e-06],\n [ 2.2274e-05, 2.9787e-05, -7.7463e-06]]],\n\n\n [[[ 5.0330e-05, 1.7187e-05, 2.3859e-05],\n [ 6.0786e-05, 7.7815e-06, 5.5435e-05],\n [ 1.6926e-05, 2.2801e-06, 2.1247e-05]],\n\n [[ 1.8932e-05, -2.1086e-05, 3.1177e-06],\n [ 2.1484e-05, -3.6840e-05, 2.6173e-05],\n [ 4.4645e-06, 1.2270e-05, 3.1955e-05]],\n\n [[ 2.2115e-05, -7.2756e-06, -1.7807e-06],\n [ 2.7570e-05, -5.9117e-05, 2.0927e-05],\n [ 2.9120e-05, 1.4977e-05, 1.9447e-06]],\n\n ...,\n\n [[-1.0292e-05, -9.8775e-06, 1.9581e-05],\n [-6.4082e-06, 7.2059e-06, 1.5361e-05],\n [ 1.0782e-05, 2.3242e-05, 5.2421e-06]],\n\n [[-3.9271e-05, -1.1212e-05, -4.3967e-07],\n [-2.3802e-05, 1.1802e-05, 3.7769e-05],\n [ 1.1411e-05, -2.7862e-06, 9.4562e-06]],\n\n [[ 2.4253e-05, -6.0662e-05, -5.5882e-06],\n [ 4.3832e-05, -1.5314e-04, 8.0272e-05],\n [ 3.5439e-05, 8.8142e-07, 4.2575e-05]]],\n\n\n [[[-3.2349e-06, 1.2491e-06, 2.4928e-05],\n [ 9.6671e-06, 1.7808e-06, 3.9050e-05],\n [-2.0202e-06, 3.0341e-05, -1.7799e-05]],\n\n [[ 4.0563e-06, -1.6012e-06, -3.2242e-05],\n [ 1.5833e-05, -1.8815e-06, -1.1219e-05],\n [ 1.0732e-06, 1.2839e-05, -8.1647e-06]],\n\n [[ 1.0346e-05, 2.5830e-05, 5.4998e-05],\n [ 4.4321e-06, -1.9061e-05, 1.4707e-05],\n [ 1.9289e-05, -6.1415e-07, 2.4330e-05]],\n\n ...,\n\n [[ 4.9258e-05, 1.2329e-05, 3.8869e-05],\n [ 2.5813e-05, 2.4118e-05, 1.1795e-05],\n [ 1.8170e-05, 5.1499e-06, 6.2550e-06]],\n\n [[-8.4968e-06, -1.1461e-05, -1.2146e-05],\n [-4.5211e-06, 1.6841e-05, -1.9030e-06],\n [-3.5231e-05, -3.5144e-05, -1.0179e-05]],\n\n [[-2.3679e-05, 1.9017e-05, -3.3321e-06],\n [ 6.4897e-06, -8.8649e-06, -4.6036e-06],\n [-1.7555e-05, 2.6501e-05, -3.8612e-06]]],\n\n\n ...,\n\n\n [[[ 8.5000e-06, -1.8075e-05, -3.2924e-05],\n [-3.5836e-05, 3.5729e-05, -1.6094e-05],\n [ 5.4439e-06, 1.3158e-05, -2.1412e-05]],\n\n [[ 1.7333e-06, 9.5517e-06, 2.4969e-06],\n [ 2.1081e-05, 3.6231e-05, -9.7907e-06],\n [ 1.1721e-05, 1.8201e-05, -2.5810e-06]],\n\n [[ 1.0580e-05, 1.7256e-05, 1.2363e-05],\n [-1.5472e-05, 3.1041e-05, 2.9830e-06],\n [-1.6805e-05, -4.0399e-06, 3.3453e-06]],\n\n ...,\n\n [[ 6.3716e-06, -3.2272e-06, -7.3861e-06],\n [ 3.4407e-05, 1.2177e-06, -6.4284e-06],\n [ 9.1867e-06, -5.5490e-06, -3.6419e-05]],\n\n [[-2.8546e-05, -4.0590e-05, -3.8867e-05],\n [ 7.1651e-06, -4.5644e-05, -3.8245e-05],\n [-1.0522e-05, -4.0060e-05, -3.4315e-05]],\n\n [[-2.0923e-05, 9.0039e-06, -7.7001e-06],\n [-7.2282e-06, 9.9976e-05, -4.9259e-05],\n [ 8.1739e-06, 1.3618e-05, -2.4243e-06]]],\n\n\n [[[ 2.9057e-05, 4.3110e-05, 2.2089e-05],\n [ 1.0061e-05, -1.4677e-05, -5.7402e-06],\n [ 3.8120e-05, 1.7287e-05, 1.8953e-05]],\n\n [[ 1.8265e-05, 3.2605e-05, 9.6608e-06],\n [-7.2043e-06, -6.0990e-06, -2.7347e-05],\n [ 1.5173e-05, 2.3890e-05, -5.8212e-07]],\n\n [[-1.8308e-05, 2.3857e-06, 9.9808e-06],\n [ 1.2868e-05, 2.7133e-05, 7.5687e-06],\n [ 2.2337e-05, 1.1820e-05, 7.1585e-06]],\n\n ...,\n\n [[ 1.6463e-05, 2.6886e-05, 1.0713e-05],\n [ 1.0236e-05, 2.6518e-05, 9.2952e-06],\n [ 9.0884e-06, -8.0409e-06, 1.4472e-05]],\n\n [[ 9.9759e-06, 1.0134e-05, 2.6426e-06],\n [-1.0611e-07, 1.1860e-05, -1.4081e-06],\n [ 3.7753e-06, 8.7235e-06, -1.8401e-05]],\n\n [[ 6.2661e-06, 3.2053e-05, 5.4472e-07],\n [ 2.0475e-05, -1.2369e-05, -1.0126e-05],\n [ 1.6936e-06, 1.5121e-05, -2.0899e-05]]],\n\n\n [[[-1.1500e-05, 9.5163e-07, 5.1451e-06],\n [-1.5303e-05, -9.3425e-06, -1.9265e-05],\n [-3.2781e-06, -3.5731e-05, -1.8809e-05]],\n\n [[ 6.2551e-06, 9.8821e-06, -7.9616e-06],\n [ 2.1059e-06, -1.1310e-05, -1.5258e-05],\n [-2.5256e-05, -3.7565e-05, -1.9316e-05]],\n\n [[-9.2039e-06, 8.1574e-06, 5.2028e-06],\n [ 6.6375e-06, 1.4143e-06, -2.1929e-05],\n [-1.1422e-05, -2.9330e-05, -4.2592e-05]],\n\n ...,\n\n [[-3.1425e-05, -1.3773e-05, -2.2839e-05],\n [-3.6383e-05, -9.9387e-06, -4.6767e-06],\n [-2.4466e-05, -3.1936e-06, 1.2965e-05]],\n\n [[-2.2499e-05, 5.1416e-06, -1.8117e-05],\n [-6.1740e-06, -7.2574e-06, -1.2423e-05],\n [-1.1593e-05, 6.6337e-06, 1.2737e-05]],\n\n [[-4.7784e-06, -5.2455e-06, -1.4746e-05],\n [-7.7159e-06, -1.9336e-05, -2.0838e-05],\n [ 1.0275e-06, -1.8590e-05, -2.4316e-05]]]]), 'exp_avg_sq': tensor([[[[5.9431e-08, 5.0085e-08, 3.8672e-08],\n [4.2315e-08, 5.5344e-08, 4.3620e-08],\n [8.9750e-08, 6.4478e-08, 6.1390e-08]],\n\n [[6.5572e-08, 2.8088e-08, 3.3451e-08],\n [3.5491e-08, 5.0905e-08, 4.2863e-08],\n [7.4345e-08, 5.8688e-08, 6.5870e-08]],\n\n [[3.3019e-08, 3.1756e-08, 5.7109e-08],\n [2.8095e-08, 5.1128e-08, 6.3116e-08],\n [7.5799e-08, 6.9861e-08, 6.4798e-08]],\n\n ...,\n\n [[5.0813e-08, 5.4443e-08, 4.7440e-08],\n [6.5839e-08, 7.3794e-08, 5.2995e-08],\n [6.4006e-08, 6.5115e-08, 5.9248e-08]],\n\n [[5.0842e-08, 6.9943e-08, 9.4949e-08],\n [5.1489e-08, 3.9889e-08, 6.3310e-08],\n [7.9037e-08, 7.6620e-08, 1.0098e-07]],\n\n [[5.9405e-08, 4.0944e-08, 4.4593e-08],\n [4.8099e-08, 6.6879e-08, 5.3366e-08],\n [7.0023e-08, 7.3502e-08, 7.2701e-08]]],\n\n\n [[[1.6571e-07, 1.1110e-07, 1.0811e-07],\n [1.4601e-07, 1.5580e-07, 1.1876e-07],\n [1.2998e-07, 1.3056e-07, 1.4475e-07]],\n\n [[7.7225e-08, 1.0719e-07, 6.5385e-08],\n [8.8665e-08, 9.4405e-08, 6.6067e-08],\n [8.0309e-08, 7.6132e-08, 1.0072e-07]],\n\n [[7.0849e-08, 8.5081e-08, 1.1985e-07],\n [7.4779e-08, 1.1405e-07, 7.8847e-08],\n [6.5996e-08, 1.3942e-07, 1.5093e-07]],\n\n ...,\n\n [[1.2512e-07, 1.2406e-07, 6.4379e-08],\n [7.5816e-08, 1.0907e-07, 9.3926e-08],\n [1.1327e-07, 1.2173e-07, 1.0126e-07]],\n\n [[2.3271e-07, 2.4137e-07, 2.0041e-07],\n [2.6736e-07, 2.5309e-07, 3.5018e-07],\n [3.3642e-07, 2.8930e-07, 3.2996e-07]],\n\n [[2.2440e-07, 1.5656e-07, 1.2258e-07],\n [1.7895e-07, 2.6914e-07, 1.6165e-07],\n [1.3733e-07, 2.1610e-07, 1.8580e-07]]],\n\n\n [[[1.2759e-07, 1.2425e-07, 1.6938e-07],\n [1.0340e-07, 1.3079e-07, 1.3617e-07],\n [1.3235e-07, 1.0547e-07, 1.5910e-07]],\n\n [[7.8022e-08, 1.4319e-07, 7.5885e-08],\n [5.9722e-08, 6.9848e-08, 1.1520e-07],\n [6.0913e-08, 2.2046e-07, 1.0159e-07]],\n\n [[8.2778e-08, 7.6214e-08, 1.0433e-07],\n [6.5929e-08, 6.1755e-08, 9.4635e-08],\n [6.3480e-08, 8.9417e-08, 9.0359e-08]],\n\n ...,\n\n [[1.1148e-07, 8.9906e-08, 9.2389e-08],\n [1.0182e-07, 9.2793e-08, 9.8180e-08],\n [1.1942e-07, 9.3588e-08, 6.9656e-08]],\n\n [[1.5837e-07, 1.5815e-07, 1.5206e-07],\n [1.8627e-07, 1.5844e-07, 1.9973e-07],\n [2.1825e-07, 1.3361e-07, 1.6267e-07]],\n\n [[1.1151e-07, 2.4690e-07, 1.6109e-07],\n [8.8987e-08, 1.2279e-07, 1.7812e-07],\n [1.1807e-07, 2.1015e-07, 1.5823e-07]]],\n\n\n ...,\n\n\n [[[1.2411e-07, 1.7843e-07, 1.2074e-07],\n [1.7092e-07, 1.2690e-07, 1.1064e-07],\n [1.4648e-07, 1.2664e-07, 9.6489e-08]],\n\n [[8.6165e-08, 1.2807e-07, 8.3947e-08],\n [9.7763e-08, 1.1886e-07, 1.0081e-07],\n [8.9382e-08, 1.0575e-07, 7.5897e-08]],\n\n [[9.7418e-08, 9.1732e-08, 7.9850e-08],\n [7.4711e-08, 8.2176e-08, 8.6108e-08],\n [7.8532e-08, 9.1178e-08, 1.3114e-07]],\n\n ...,\n\n [[9.1639e-08, 1.1308e-07, 8.2078e-08],\n [1.3202e-07, 9.7304e-08, 1.0671e-07],\n [1.2118e-07, 1.0459e-07, 1.4864e-07]],\n\n [[1.8254e-07, 1.8215e-07, 1.8545e-07],\n [1.8185e-07, 1.9489e-07, 1.6622e-07],\n [2.0341e-07, 1.7380e-07, 2.5714e-07]],\n\n [[1.2309e-07, 1.7069e-07, 1.6495e-07],\n [1.4097e-07, 2.1300e-07, 1.7484e-07],\n [1.6287e-07, 1.3981e-07, 1.6792e-07]]],\n\n\n [[[4.8059e-08, 6.7577e-08, 5.9999e-08],\n [4.7921e-08, 6.3298e-08, 5.0839e-08],\n [4.5069e-08, 5.5798e-08, 7.9412e-08]],\n\n [[3.4471e-08, 3.9797e-08, 7.4926e-08],\n [3.1883e-08, 5.0196e-08, 4.6738e-08],\n [6.1848e-08, 5.1312e-08, 7.1555e-08]],\n\n [[2.7005e-08, 9.1709e-08, 1.0866e-07],\n [3.8994e-08, 4.9702e-08, 8.1235e-08],\n [4.1578e-08, 4.6491e-08, 4.6926e-08]],\n\n ...,\n\n [[5.2067e-08, 5.6613e-08, 8.8513e-08],\n [4.0072e-08, 3.8015e-08, 4.6163e-08],\n [4.7394e-08, 4.0751e-08, 6.0439e-08]],\n\n [[1.2076e-07, 1.0611e-07, 7.1324e-08],\n [8.3647e-08, 6.0307e-08, 5.9038e-08],\n [9.8630e-08, 7.9852e-08, 7.8386e-08]],\n\n [[1.0335e-07, 1.0073e-07, 1.0481e-07],\n [7.5529e-08, 8.6719e-08, 4.7212e-08],\n [1.0294e-07, 6.0321e-08, 7.0222e-08]]],\n\n\n [[[5.1559e-08, 3.4831e-08, 5.6324e-08],\n [5.3280e-08, 1.0106e-07, 5.3067e-08],\n [9.0297e-08, 8.8371e-08, 1.1409e-07]],\n\n [[3.5948e-08, 5.3311e-08, 5.1287e-08],\n [3.3460e-08, 3.0521e-08, 3.8697e-08],\n [5.6271e-08, 4.9909e-08, 5.4911e-08]],\n\n [[3.6866e-08, 1.8015e-08, 2.4114e-08],\n [3.8941e-08, 5.2479e-08, 4.6977e-08],\n [3.9473e-08, 3.8785e-08, 5.2826e-08]],\n\n ...,\n\n [[4.6185e-08, 5.9866e-08, 5.5334e-08],\n [4.7778e-08, 6.2466e-08, 4.9289e-08],\n [8.3386e-08, 4.6042e-08, 4.8379e-08]],\n\n [[9.1763e-08, 1.2456e-07, 1.1579e-07],\n [9.8559e-08, 1.1360e-07, 1.1187e-07],\n [9.7537e-08, 8.0335e-08, 8.3862e-08]],\n\n [[6.8513e-08, 1.0639e-07, 1.1983e-07],\n [6.3504e-08, 9.6422e-08, 6.4935e-08],\n [1.8809e-07, 1.3427e-07, 1.1946e-07]]]])}, 37: {'step': 7160, 'exp_avg': tensor([-2.1027e-05, 5.2263e-04, -3.5553e-04, -1.0290e-04, 7.4549e-05,\n -7.3719e-05, -8.5834e-05, 1.4709e-04, 2.4463e-05, -2.2876e-05,\n -2.9505e-04, 1.0382e-04, -5.7282e-05, 1.5142e-04, -1.0083e-04,\n 1.2438e-04, 1.2848e-04, -1.7814e-04, 2.0264e-05, -9.0565e-05,\n -4.6947e-05, -1.4612e-04, -2.3542e-04, -1.2292e-05, -2.9028e-04,\n -1.2051e-04, -4.6664e-05, 1.7998e-04, -1.4249e-04, -1.9037e-04,\n 1.9830e-04, -3.3219e-04, 2.4530e-04, 5.6926e-05, 1.2575e-05,\n 9.6892e-05, 1.4751e-04, -7.2848e-05, -3.6533e-05, 3.8185e-04,\n -3.1862e-05, -1.9643e-04, 1.2129e-05, -1.7218e-04, -2.6239e-04,\n -2.0848e-04, -3.4630e-04, 2.9918e-06, -2.6200e-05, -2.0388e-04,\n 3.9312e-04, -4.6917e-05, -4.9661e-05, 1.3734e-04, 1.0637e-04,\n 2.2509e-05, 4.4171e-04, -1.3049e-04, -2.4389e-04, -6.1377e-05,\n 1.5983e-04, 1.2933e-04, -3.1688e-04, -1.5286e-04, -1.1265e-04,\n -2.2538e-04, -2.6573e-04, 2.7124e-04, -1.3312e-04, 6.5384e-05,\n 3.1400e-05, 2.1486e-04, -3.1396e-06, -9.3821e-05, -1.6640e-04,\n -1.3313e-04, 1.1105e-04, -1.0660e-04, 1.1190e-04, -7.1570e-05,\n 9.6740e-06, 4.6804e-06, -2.3177e-05, -1.8335e-05, 1.5415e-04,\n 2.4142e-04, -8.3388e-05, -2.7390e-04, 5.0583e-05, -2.3085e-04,\n -2.2436e-04, 3.3344e-04, 4.2156e-05, 2.8317e-04, -1.1119e-04,\n 3.4990e-04, -2.1595e-05, -9.4099e-05, 3.0786e-05, -1.1396e-04,\n 4.5565e-05, -1.8234e-04, 9.7546e-05, -1.6624e-04, 9.5170e-05,\n 3.3981e-04, -7.2909e-06, -6.0536e-06, -1.2858e-04, 6.0542e-05,\n -2.5135e-05, -1.1668e-04, -1.4574e-04, -2.5253e-05, -1.0272e-04,\n 2.6011e-04, -1.0130e-04, 1.9592e-04, 1.3695e-04, 4.8608e-05,\n 1.4761e-04, 2.3201e-05, 1.9744e-04, 7.1801e-04, 1.2249e-04,\n 2.2754e-05, 9.1853e-05, 2.7585e-04]), 'exp_avg_sq': tensor([4.0818e-06, 1.2343e-05, 8.6469e-06, 6.4849e-06, 4.1218e-06, 4.1402e-06,\n 4.9069e-06, 5.4128e-06, 6.1381e-06, 2.3290e-06, 7.6691e-06, 2.9857e-06,\n 3.7370e-06, 4.5175e-06, 2.7650e-06, 7.1607e-06, 4.6418e-06, 4.2370e-06,\n 3.6228e-06, 4.4887e-06, 5.0039e-06, 4.4568e-06, 5.2656e-06, 5.9992e-06,\n 7.5216e-06, 3.9891e-06, 3.6166e-06, 6.7088e-06, 4.4381e-06, 3.0155e-06,\n 6.2471e-06, 8.0599e-06, 6.5479e-06, 5.2522e-06, 3.7334e-06, 3.3175e-06,\n 3.1497e-06, 5.0886e-06, 5.8168e-06, 1.5080e-05, 5.5654e-06, 3.6894e-06,\n 4.9171e-06, 6.0130e-06, 6.6431e-06, 9.0347e-06, 6.8181e-06, 2.2219e-06,\n 7.0331e-06, 9.7350e-06, 9.5961e-06, 3.7244e-06, 9.1869e-06, 5.9407e-06,\n 4.3477e-06, 4.1866e-06, 9.2570e-06, 5.5023e-06, 2.9296e-06, 1.2293e-05,\n 7.1780e-06, 3.9718e-06, 9.4517e-06, 2.6633e-06, 5.0735e-06, 4.1195e-06,\n 2.9188e-06, 5.9782e-06, 8.6454e-06, 3.8563e-06, 2.0090e-05, 6.5162e-06,\n 4.5170e-06, 3.7307e-06, 4.8100e-06, 5.1137e-06, 7.6764e-06, 4.4068e-06,\n 6.5572e-06, 1.5072e-05, 4.3094e-06, 8.1724e-06, 6.0221e-06, 5.7877e-06,\n 5.0594e-06, 4.7682e-06, 6.5578e-06, 6.6931e-06, 2.6523e-06, 9.0692e-06,\n 9.7693e-06, 6.1435e-06, 2.6296e-06, 6.5181e-06, 4.4581e-06, 1.0054e-05,\n 5.8050e-06, 3.3585e-06, 4.3562e-06, 7.8974e-06, 2.4767e-06, 6.3806e-06,\n 1.0734e-05, 4.1404e-06, 2.9711e-06, 3.9888e-06, 3.3280e-06, 5.5177e-06,\n 8.6939e-06, 2.9707e-06, 3.8246e-06, 4.0358e-06, 8.0364e-06, 5.0902e-06,\n 2.8272e-06, 4.5797e-06, 5.8105e-06, 3.4738e-06, 9.2646e-06, 8.4837e-06,\n 6.9450e-06, 5.0288e-06, 5.1457e-06, 6.3796e-06, 1.0748e-05, 6.0082e-06,\n 6.3797e-06, 4.7426e-06])}, 38: {'step': 7160, 'exp_avg': tensor([ 1.9204e-04, -1.4510e-06, 3.7619e-05, -2.3618e-05, -2.7206e-05,\n -6.8897e-05, 3.6146e-05, -9.2820e-05, -1.2235e-04, -4.0274e-05,\n -1.1295e-04, 1.1674e-04, -3.6357e-05, 1.1711e-05, -6.2538e-05,\n -1.1698e-04, 5.6928e-05, -1.4663e-04, 2.5249e-05, 5.7675e-05,\n 8.9129e-05, -7.1694e-05, -1.8571e-04, -1.0896e-04, -1.5653e-04,\n -6.7702e-05, -7.6449e-05, 1.3209e-04, -1.3514e-04, -7.8883e-05,\n 5.8629e-05, -1.7319e-04, 1.4324e-05, 6.2642e-05, -5.5555e-05,\n 6.0720e-05, -3.1654e-06, -9.5788e-05, -1.0810e-04, -1.5686e-05,\n -7.9603e-05, -1.2864e-04, 5.4403e-06, -1.9811e-04, -2.4508e-04,\n -6.7343e-05, -2.1373e-04, 2.6577e-05, 1.0362e-04, -1.3348e-04,\n 1.6061e-04, 1.1247e-04, -1.2379e-04, 3.3169e-05, 6.7137e-05,\n -1.6597e-04, 5.3476e-05, -3.6102e-05, -1.0893e-04, -6.9774e-05,\n 1.5615e-05, 9.3992e-05, -6.4222e-06, -6.2783e-05, 4.8494e-05,\n -1.6413e-05, -1.4285e-04, 2.6116e-04, -5.2064e-06, 1.6973e-06,\n -2.7110e-05, 6.4518e-05, -1.0795e-04, -3.9524e-05, -5.3143e-05,\n -2.3991e-04, 3.0685e-04, -6.2972e-05, 1.6714e-05, 4.6129e-05,\n -1.2890e-04, 6.1114e-05, -1.8873e-04, -8.7257e-05, 8.1957e-06,\n 8.8727e-05, -1.6584e-04, -2.0274e-05, 7.0776e-06, -6.4642e-05,\n -1.2081e-04, -9.5503e-05, -4.7268e-05, 3.8678e-05, 2.6757e-04,\n 7.0752e-05, -6.7239e-05, 2.5567e-05, 4.6965e-05, 5.9281e-05,\n 8.0967e-05, -1.1310e-04, -2.7218e-05, -1.0597e-04, -1.0548e-04,\n 7.4673e-05, -5.3754e-05, 1.0125e-04, -1.6376e-04, -6.1274e-05,\n 5.0816e-05, 2.7122e-05, 2.3141e-05, 4.2954e-05, 1.1777e-05,\n 1.1410e-04, 1.5434e-04, 8.6346e-05, 9.6248e-05, 4.0123e-05,\n 9.0591e-05, -2.3206e-04, -1.5862e-05, 1.9704e-04, -6.7360e-05,\n 4.4231e-05, 8.7644e-05, 1.9757e-04]), 'exp_avg_sq': tensor([2.6624e-06, 3.9182e-06, 1.0231e-06, 3.4371e-06, 1.7797e-06, 1.5784e-06,\n 4.5972e-06, 2.2005e-06, 2.2872e-06, 1.5118e-06, 5.1003e-06, 1.2791e-06,\n 1.8611e-06, 2.1881e-06, 1.5158e-06, 3.3830e-06, 1.9157e-06, 2.8286e-06,\n 1.6760e-06, 2.5645e-06, 3.3005e-06, 2.0743e-06, 2.2436e-06, 3.0612e-06,\n 5.3551e-06, 1.4954e-06, 2.1091e-06, 1.4090e-06, 3.5378e-06, 2.2862e-06,\n 2.8932e-06, 2.9257e-06, 3.3536e-06, 3.9995e-06, 2.9988e-06, 1.7391e-06,\n 2.2747e-06, 2.1499e-06, 2.1088e-06, 2.1280e-06, 5.7164e-06, 1.4595e-06,\n 3.9697e-06, 3.3333e-06, 2.6069e-06, 5.0717e-06, 3.0901e-06, 1.4207e-06,\n 4.3174e-06, 3.4509e-06, 1.6789e-06, 2.4294e-06, 8.6081e-07, 2.5598e-06,\n 2.8715e-06, 2.1220e-06, 3.2287e-06, 3.0733e-06, 2.5117e-06, 3.5183e-06,\n 2.0545e-06, 3.0948e-06, 2.5873e-06, 1.5701e-06, 2.3060e-06, 2.3469e-06,\n 1.4301e-06, 3.3586e-06, 1.2580e-06, 2.6485e-06, 1.4914e-06, 1.6803e-06,\n 3.8862e-06, 2.1594e-06, 3.4060e-06, 2.6424e-06, 5.8352e-06, 1.8798e-06,\n 2.7866e-06, 1.6632e-06, 1.7336e-06, 2.9680e-06, 3.3106e-06, 2.9748e-06,\n 2.5152e-06, 2.0241e-06, 2.4358e-06, 2.5226e-06, 1.5492e-06, 3.0208e-06,\n 1.1929e-06, 4.0278e-06, 1.8769e-06, 1.5069e-06, 2.1142e-06, 4.9780e-06,\n 2.9719e-06, 1.5894e-06, 2.5340e-06, 2.5735e-06, 1.9693e-06, 2.9834e-06,\n 9.1579e-07, 2.5862e-06, 2.9020e-06, 2.3784e-06, 1.3588e-06, 3.7507e-06,\n 1.5286e-06, 1.7834e-06, 1.8187e-06, 2.5032e-06, 2.9687e-06, 5.1743e-06,\n 1.3910e-06, 2.1858e-06, 1.5827e-06, 2.2071e-06, 1.0065e-06, 5.8326e-06,\n 5.2335e-06, 2.9956e-06, 2.6512e-06, 2.2934e-06, 1.8431e-06, 1.1982e-06,\n 2.5529e-06, 2.4773e-06])}, 39: {'step': 7160, 'exp_avg': tensor([[[[ 5.3859e-06]],\n\n [[-1.6713e-06]],\n\n [[-3.4503e-06]],\n\n ...,\n\n [[-5.2870e-07]],\n\n [[-1.0265e-06]],\n\n [[-3.0191e-06]]],\n\n\n [[[-2.5862e-05]],\n\n [[-2.6525e-05]],\n\n [[ 1.7866e-05]],\n\n ...,\n\n [[-3.2988e-05]],\n\n [[-3.9737e-05]],\n\n [[-7.2813e-05]]],\n\n\n [[[ 5.6052e-45]],\n\n [[-5.6052e-45]],\n\n [[ 5.6052e-45]],\n\n ...,\n\n [[ 5.6052e-45]],\n\n [[ 5.6052e-45]],\n\n [[ 5.6052e-45]]],\n\n\n ...,\n\n\n [[[ 0.0000e+00]],\n\n [[ 0.0000e+00]],\n\n [[ 0.0000e+00]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[ 0.0000e+00]],\n\n [[ 0.0000e+00]]],\n\n\n [[[ 1.1066e-05]],\n\n [[-1.7137e-05]],\n\n [[ 2.2760e-05]],\n\n ...,\n\n [[-1.4171e-05]],\n\n [[ 4.7764e-05]],\n\n [[ 2.5378e-06]]],\n\n\n [[[-4.1276e-06]],\n\n [[-4.7741e-06]],\n\n [[-6.2670e-10]],\n\n ...,\n\n [[ 5.1353e-06]],\n\n [[ 7.4490e-06]],\n\n [[ 3.5797e-06]]]]), 'exp_avg_sq': tensor([[[[4.5389e-10]],\n\n [[5.7697e-10]],\n\n [[5.0343e-10]],\n\n ...,\n\n [[6.2808e-10]],\n\n [[2.5249e-10]],\n\n [[4.4575e-10]]],\n\n\n [[[1.5593e-07]],\n\n [[5.4750e-07]],\n\n [[4.3365e-07]],\n\n ...,\n\n [[3.8538e-07]],\n\n [[2.3994e-07]],\n\n [[4.4645e-07]]],\n\n\n [[[9.4188e-19]],\n\n [[8.2188e-18]],\n\n [[3.7756e-18]],\n\n ...,\n\n [[1.2521e-17]],\n\n [[1.8084e-18]],\n\n [[4.6212e-18]]],\n\n\n ...,\n\n\n [[[0.0000e+00]],\n\n [[0.0000e+00]],\n\n [[0.0000e+00]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[0.0000e+00]],\n\n [[0.0000e+00]]],\n\n\n [[[1.7579e-07]],\n\n [[2.6064e-07]],\n\n [[1.9257e-07]],\n\n ...,\n\n [[2.9969e-07]],\n\n [[3.8221e-07]],\n\n [[1.6319e-07]]],\n\n\n [[[1.2119e-09]],\n\n [[3.0691e-09]],\n\n [[3.4141e-09]],\n\n ...,\n\n [[2.6441e-09]],\n\n [[1.2790e-09]],\n\n [[2.3479e-09]]]])}, 40: {'step': 7160, 'exp_avg': tensor([ 2.2653e-05, -1.5774e-06, -5.6052e-45, -6.4482e-05, 5.8617e-05,\n 0.0000e+00, -1.5727e-05, 4.3354e-04, 1.1113e-04, -1.5265e-04,\n -7.9953e-05, 7.3821e-05, -3.5282e-05, -1.6685e-04, 0.0000e+00,\n 3.7356e-05, 2.2076e-05, 1.5780e-05, 2.4776e-04, 1.0747e-04,\n 1.2995e-05, 2.2994e-04, 1.2635e-04, 0.0000e+00, -1.5379e-04,\n -1.3344e-04, -2.6085e-05, -5.7957e-05, 0.0000e+00, -2.2647e-04,\n 7.6552e-05, 1.4396e-04, -4.1670e-05, -7.7334e-05, -8.5836e-05,\n -6.1125e-05, -1.6695e-04, 4.6574e-05, 5.6052e-45, 1.6118e-04,\n -7.5521e-05, -1.2019e-05, -6.0990e-05, 1.2952e-06, -5.6231e-05,\n 2.2216e-04, 1.7196e-04, -2.0583e-04, 1.5358e-05, 5.9860e-06,\n 1.1966e-04, 5.6052e-45, 1.4293e-04, 1.1544e-05, 5.0330e-06,\n 4.7797e-05, -3.6511e-05, -5.8923e-05, -2.1922e-04, 0.0000e+00,\n -4.1838e-05, -5.7857e-05, 3.6449e-05, 9.3230e-05, 3.7465e-05,\n -3.8961e-05, 1.6450e-04, -1.9956e-06, 0.0000e+00, -1.2564e-05,\n 2.3514e-04, 7.0891e-05, 5.4320e-05, 1.0957e-04, 1.6708e-04,\n 3.1991e-04, 1.8712e-05, 9.0076e-05, 1.0426e-04, 1.8230e-04,\n 5.4640e-05, -5.9384e-05, 5.1928e-05, 4.2591e-05, -1.0679e-04,\n 2.8386e-04, 8.5304e-05, 1.7832e-04, -4.6028e-05, 0.0000e+00,\n 0.0000e+00, -5.9812e-05, -7.6799e-05, 4.0536e-04, 0.0000e+00,\n -3.8040e-05, 1.6469e-05, -1.1801e-05, 3.6398e-05, 3.7739e-06,\n 2.1349e-04, 2.2822e-05, 4.1983e-04, 4.3348e-05, -3.5954e-04,\n 0.0000e+00, 1.5820e-04, -1.1974e-04, -1.1213e-04, 1.5451e-05,\n 1.7115e-04, 4.5457e-05, 0.0000e+00, -8.0389e-05, 1.3849e-04,\n 1.4087e-04, 6.2132e-05, 3.8429e-05, 1.0290e-04, -1.1151e-04,\n -5.8639e-05, -5.6777e-05, -1.5578e-04, -8.0237e-05, 3.0336e-05,\n 5.7030e-04, 9.6156e-05, 3.7388e-04, 1.4714e-05, -5.5277e-05,\n 1.2703e-04, 2.1646e-05, -1.8757e-04, 0.0000e+00, -3.4936e-05,\n 3.5597e-05, 2.0879e-04, 1.1457e-04, 0.0000e+00, 4.4112e-05,\n 2.0186e-04, 1.1597e-04, 2.5710e-04, 0.0000e+00, 4.6610e-05,\n 2.0512e-05, -1.6374e-04, -1.7926e-06, -2.1443e-06, -1.2268e-05,\n 4.3063e-05, 4.7721e-05, 1.4027e-04, 0.0000e+00, 2.8079e-04,\n 9.2305e-05, -1.2907e-04, 0.0000e+00, -9.5701e-05, -3.2703e-05,\n 2.0160e-04, 3.7867e-04, -1.1178e-06, 6.4174e-05, -1.9706e-04,\n 0.0000e+00, 8.6803e-05, 2.2972e-04, 1.6575e-05, 8.9275e-05,\n 0.0000e+00, 3.5180e-05, 2.0037e-04, -1.2012e-04, 0.0000e+00,\n -1.3678e-04, 1.1105e-05, -4.5650e-05, -7.4058e-05, -1.6186e-04,\n -1.0669e-04, -4.6236e-05, -1.1999e-04, 7.8061e-05, -5.0367e-05,\n 2.5739e-04, 0.0000e+00, -9.6008e-06, -7.0621e-05, -9.1288e-05,\n -9.1370e-05, -4.4500e-05, 1.5466e-04, -6.0306e-05, 2.7887e-05,\n 2.6385e-04, 0.0000e+00, 1.3032e-04, -2.0218e-05, 3.1128e-04,\n 0.0000e+00, -2.7918e-05, -2.9218e-04, -2.6227e-05, 0.0000e+00,\n 1.6238e-05, -9.7348e-05, -4.9307e-05, -1.6397e-04, -1.1494e-09,\n 1.6941e-05, -9.6731e-05, -2.1524e-04, 0.0000e+00, 4.0779e-05,\n 2.3224e-05, 8.5965e-05, 4.4216e-04, 7.8095e-05, -3.8558e-05,\n 3.8063e-05, 5.8901e-06, 0.0000e+00, 5.9662e-05, 1.3359e-04,\n 1.5552e-04, 1.6049e-04, -2.7445e-04, -2.2873e-06, 5.5089e-05,\n 7.7126e-05, -9.1826e-05, -4.7585e-05, 8.6225e-05, 0.0000e+00,\n -1.4211e-04, 0.0000e+00, -1.7497e-04, -1.4224e-04, 5.9468e-05,\n 0.0000e+00, -1.1648e-05, 2.8140e-05, -2.0402e-04, 5.5548e-05,\n 1.0843e-04, 2.8715e-04, 1.6443e-05, -4.1907e-06, -6.5462e-07,\n -1.3879e-04, 1.1064e-04, 1.4720e-05, 3.7948e-05, 5.9954e-05,\n -1.9316e-04, 1.0779e-04, -1.9803e-04, 5.8394e-05, 1.2018e-04,\n -1.0745e-04, 1.4287e-04, 2.0403e-04, 3.2945e-05, -1.1883e-04,\n 1.3998e-04, 4.6891e-05, -1.0073e-05, -2.2586e-04, -1.6297e-04,\n 0.0000e+00, -1.0118e-04, 0.0000e+00, -1.0119e-05, -5.6520e-05,\n -5.4899e-05, 1.8607e-05, -1.8903e-04, 1.1760e-05, -7.9192e-05,\n -8.6732e-05, 6.9896e-05, 8.7395e-05, -9.4885e-05, -2.1830e-04,\n 1.4594e-04, 2.1434e-05, 4.6252e-06, -2.9177e-05, -3.5469e-05,\n -1.0816e-04, 0.0000e+00, -5.2658e-05, 5.4396e-05, 5.8693e-05,\n 1.2252e-04, 9.4586e-05, 0.0000e+00, 1.7353e-05, 0.0000e+00,\n -1.2198e-04, -4.1706e-05, -2.4658e-05, -2.1435e-05, 6.5650e-05,\n 6.2171e-06, 1.8746e-04, -4.9294e-05, 5.3659e-05, 7.4867e-05,\n -2.4550e-04, 0.0000e+00, 0.0000e+00, 0.0000e+00, -1.1286e-04,\n -8.5253e-06, 2.7605e-05, -1.2654e-04, 0.0000e+00, 2.8786e-04,\n -8.7580e-05, -1.1531e-04, 1.8959e-04, 1.8012e-05, 1.6514e-04,\n 0.0000e+00, 9.9068e-05, -8.1992e-05, 8.1647e-05, -1.3030e-04,\n -1.9597e-05, -9.6546e-05, 0.0000e+00, 6.6002e-05, -1.8993e-05,\n 5.9288e-05, 1.5731e-04, 5.6256e-05, 1.0005e-04, -4.0862e-05,\n 1.4519e-04, 5.3864e-05, -2.5127e-05, 5.9619e-05, 9.3292e-05,\n -1.0592e-06, 0.0000e+00, 2.0450e-04, 2.0578e-05, 2.8352e-04,\n -1.5160e-04, 2.5003e-05, -4.0717e-06, -2.3753e-05, 1.8470e-04,\n -8.5826e-05, 1.0297e-04, -4.9394e-04, 6.3242e-05, 3.2783e-05,\n 1.1562e-04, -6.6004e-05, -8.4133e-05, -8.8123e-06, 0.0000e+00,\n 6.6599e-05, -8.5571e-05, 1.1063e-04, -2.4606e-04, 1.7730e-04,\n 0.0000e+00, -3.8463e-05, -2.0127e-05, -2.2796e-05, -6.8255e-05,\n -2.0470e-04, 3.5288e-07, 6.5686e-05, 7.1596e-05, -1.2544e-04,\n -6.2702e-05, 1.5826e-04, 2.3417e-04, 1.1030e-04, 1.7176e-04,\n 4.9623e-05, 0.0000e+00, 2.0725e-04, 1.6303e-05, 4.9854e-05,\n 1.0096e-05, -9.9909e-05, -9.4145e-05, 3.3202e-05, 6.4055e-05,\n -3.6196e-05, 1.3545e-04, -1.4406e-07, 3.6178e-06, -3.9920e-04,\n 0.0000e+00, 2.2183e-04, -3.7114e-05, -7.1470e-06, 1.2713e-04,\n -6.3136e-05, -5.8092e-05, 1.9922e-05, 3.1677e-05, 0.0000e+00,\n 2.6885e-04, -9.8850e-05, -2.2833e-04, 0.0000e+00, -1.3238e-04,\n 7.3623e-05, 2.7558e-05, -2.7029e-05, 3.1461e-05, -1.7096e-04,\n -6.7810e-05, 1.2179e-04, -1.0910e-04, -8.8369e-05, -4.7463e-05,\n -3.8430e-05, 0.0000e+00, 1.7279e-04, -1.4737e-05, -2.0078e-05,\n 0.0000e+00, -6.0545e-05, -8.1613e-05, 0.0000e+00, -6.6705e-05,\n -2.0205e-05, 2.9172e-07, -6.6823e-05, -1.2454e-05, 5.5974e-05,\n -3.2308e-05, 2.7310e-04, 4.2406e-05, 3.1547e-04, -8.4675e-05,\n -1.5721e-04, 0.0000e+00, 2.3738e-04, 2.1936e-04, 0.0000e+00,\n 5.7890e-04, 0.0000e+00, 0.0000e+00, 3.3281e-05, 0.0000e+00,\n -6.4040e-05, 1.4961e-04, 1.1151e-04, 3.5910e-05, -8.4585e-05,\n 8.5808e-05, -9.6877e-05, 1.2542e-05, -2.3483e-05, 2.6699e-04,\n 2.0052e-04, -1.7010e-05, 0.0000e+00, -1.2752e-04, 1.4027e-05,\n -1.1843e-04, 5.5985e-04, 0.0000e+00, 3.1012e-04, 5.8432e-05,\n 1.2885e-04, 2.2107e-04, 8.1295e-06, -3.8241e-05, 1.2022e-04,\n -1.3663e-04, -5.5953e-05, -8.3864e-05, 9.1285e-05, -6.6241e-05,\n 1.3462e-05, 0.0000e+00, -2.2989e-05, -1.9007e-04, -1.3301e-04,\n -1.1284e-04, -1.1906e-04, -1.3781e-04, -2.6424e-05, 1.0679e-04,\n -5.2660e-05, 6.2697e-05, 1.2255e-04, 0.0000e+00, -6.9145e-05,\n 1.9617e-05, 2.2402e-05, -2.4752e-06, 1.5557e-04, -1.3128e-04,\n 2.0687e-05, 2.4790e-05, 1.1057e-04, 1.1137e-04, 0.0000e+00,\n 1.4331e-04, 2.5253e-04]), 'exp_avg_sq': tensor([4.1933e-06, 1.9679e-06, 1.2669e-16, 2.0986e-06, 2.5020e-06, 0.0000e+00,\n 1.8896e-06, 6.4964e-06, 2.3441e-06, 2.1594e-06, 7.2091e-07, 1.5278e-06,\n 6.4453e-06, 3.6557e-06, 0.0000e+00, 2.3874e-06, 1.8660e-06, 4.5954e-06,\n 1.7494e-06, 1.8912e-06, 2.1240e-06, 6.0600e-06, 2.1839e-06, 0.0000e+00,\n 4.2477e-06, 2.8263e-06, 1.6201e-06, 2.2350e-06, 0.0000e+00, 4.4077e-06,\n 1.4613e-06, 5.0088e-06, 4.3499e-06, 2.0168e-06, 4.1135e-06, 2.2324e-06,\n 3.9516e-05, 2.0052e-06, 2.0836e-19, 4.8798e-06, 2.9174e-06, 2.7132e-06,\n 9.7921e-07, 2.7422e-06, 1.1792e-06, 3.1354e-06, 2.6918e-06, 2.5801e-06,\n 1.4770e-06, 2.1319e-06, 5.1699e-06, 5.3643e-21, 4.0817e-06, 1.5341e-06,\n 1.8701e-06, 1.2221e-06, 1.4211e-06, 1.2028e-06, 4.1269e-06, 0.0000e+00,\n 7.2239e-06, 1.2829e-06, 1.8997e-06, 1.3589e-06, 1.0222e-06, 2.3380e-06,\n 4.9012e-07, 1.5861e-06, 0.0000e+00, 3.0744e-06, 4.0527e-06, 3.4664e-06,\n 2.1998e-06, 2.5967e-06, 5.8640e-06, 3.7161e-06, 4.3067e-06, 6.9066e-06,\n 7.2494e-06, 1.6440e-06, 2.2878e-06, 1.1795e-06, 1.5075e-07, 2.4101e-06,\n 2.0619e-06, 2.7176e-06, 2.4453e-06, 1.7886e-06, 1.4238e-05, 0.0000e+00,\n 0.0000e+00, 2.5031e-06, 1.0661e-06, 9.6348e-06, 0.0000e+00, 2.0578e-06,\n 1.9406e-06, 4.7479e-06, 2.4571e-06, 1.1335e-05, 2.9988e-06, 9.1285e-07,\n 7.4878e-06, 1.8177e-06, 1.8664e-05, 0.0000e+00, 5.4604e-06, 1.5052e-06,\n 2.5652e-06, 1.5886e-06, 3.4840e-06, 3.0009e-06, 0.0000e+00, 1.6608e-06,\n 4.2619e-06, 5.1754e-06, 2.5497e-06, 2.3600e-06, 3.9438e-06, 2.5259e-06,\n 1.0607e-06, 1.8481e-06, 6.2022e-06, 3.0309e-06, 1.9527e-06, 2.8171e-05,\n 2.7959e-06, 4.8971e-06, 1.1067e-06, 3.7900e-06, 2.3867e-06, 1.6277e-06,\n 1.9736e-06, 0.0000e+00, 7.4349e-06, 2.1394e-06, 4.2070e-06, 1.9180e-06,\n 0.0000e+00, 3.0162e-06, 1.9553e-06, 3.1884e-06, 3.4834e-06, 0.0000e+00,\n 6.1580e-07, 2.5659e-06, 2.8958e-06, 2.6655e-06, 2.2829e-06, 1.3252e-06,\n 3.1931e-06, 2.6029e-06, 2.8351e-06, 0.0000e+00, 1.4567e-05, 4.7311e-06,\n 1.6435e-05, 0.0000e+00, 2.5093e-06, 2.2064e-06, 1.4114e-06, 1.2951e-05,\n 3.0573e-06, 1.2601e-06, 1.8351e-06, 0.0000e+00, 1.6326e-06, 2.8810e-06,\n 2.1296e-06, 2.6512e-06, 0.0000e+00, 6.1287e-06, 8.0421e-06, 1.6750e-05,\n 0.0000e+00, 3.4304e-06, 2.5434e-06, 3.5527e-06, 2.0295e-06, 6.9482e-07,\n 1.8359e-06, 1.9577e-06, 2.0610e-06, 6.6097e-06, 1.9038e-06, 2.9615e-06,\n 0.0000e+00, 1.6617e-06, 2.7272e-06, 2.0528e-06, 3.1523e-06, 1.3541e-06,\n 2.1324e-06, 5.4340e-06, 1.8888e-05, 1.9743e-06, 0.0000e+00, 2.3467e-06,\n 1.1148e-06, 2.0961e-05, 0.0000e+00, 5.2878e-06, 4.7006e-06, 3.1013e-06,\n 0.0000e+00, 1.3137e-06, 1.9190e-06, 3.2319e-06, 9.2162e-06, 7.9026e-12,\n 1.7425e-06, 3.2979e-06, 7.0630e-06, 0.0000e+00, 1.9116e-06, 2.7018e-06,\n 1.4984e-06, 2.6843e-05, 2.4058e-06, 2.5202e-06, 3.2114e-06, 1.5319e-06,\n 0.0000e+00, 3.0789e-06, 3.2056e-06, 3.1079e-06, 1.7282e-06, 2.1911e-05,\n 2.1078e-06, 2.5856e-06, 4.2878e-06, 4.9986e-06, 5.0728e-06, 3.4875e-07,\n 0.0000e+00, 2.5927e-06, 0.0000e+00, 1.5294e-05, 3.7499e-06, 2.8175e-06,\n 0.0000e+00, 1.8525e-05, 1.8471e-06, 5.7835e-06, 1.7474e-06, 2.3656e-06,\n 1.8778e-06, 2.5590e-06, 5.7760e-06, 3.4944e-06, 2.2111e-06, 2.4156e-05,\n 2.6252e-06, 2.0280e-06, 1.2205e-06, 4.4301e-06, 1.4070e-06, 1.7336e-06,\n 2.2658e-06, 2.3641e-06, 7.5827e-07, 1.6218e-06, 1.3003e-06, 6.9192e-06,\n 2.6187e-06, 4.2873e-05, 3.3311e-06, 1.0596e-06, 1.2465e-05, 3.3149e-06,\n 0.0000e+00, 2.2037e-06, 0.0000e+00, 5.1826e-06, 2.4045e-06, 1.0307e-05,\n 1.0663e-06, 1.6555e-06, 1.8990e-06, 2.1706e-06, 1.6147e-06, 2.9871e-06,\n 2.3188e-06, 4.4175e-06, 7.8328e-06, 4.5583e-06, 1.4813e-06, 2.3356e-06,\n 3.0613e-06, 1.5154e-06, 4.6969e-06, 0.0000e+00, 3.2154e-06, 2.1931e-06,\n 1.1400e-06, 2.5121e-06, 2.4272e-06, 0.0000e+00, 1.8039e-06, 0.0000e+00,\n 1.0946e-06, 1.4022e-06, 1.8449e-06, 3.1158e-06, 1.1300e-06, 1.3614e-06,\n 7.4915e-07, 1.4840e-06, 2.5364e-06, 4.7197e-06, 2.9447e-06, 0.0000e+00,\n 0.0000e+00, 0.0000e+00, 5.6464e-06, 3.0251e-06, 2.2934e-06, 8.9723e-06,\n 0.0000e+00, 4.7824e-06, 2.1035e-06, 5.6732e-06, 2.0521e-06, 1.3251e-06,\n 3.4208e-06, 0.0000e+00, 1.5001e-06, 2.2089e-06, 2.3063e-06, 6.4306e-06,\n 3.7932e-06, 3.7062e-06, 0.0000e+00, 3.5195e-06, 2.1159e-06, 2.8103e-06,\n 2.6085e-06, 6.8013e-06, 1.2569e-06, 1.4536e-06, 1.0081e-05, 3.8034e-06,\n 4.0101e-06, 2.3150e-06, 2.5734e-05, 3.2399e-06, 0.0000e+00, 4.8202e-06,\n 1.7350e-06, 1.4139e-05, 2.2962e-06, 5.1220e-07, 3.4906e-06, 1.9238e-06,\n 1.7844e-05, 1.4271e-06, 1.7635e-06, 2.6016e-05, 3.3180e-06, 4.9766e-06,\n 1.9930e-06, 2.9009e-06, 1.2183e-06, 9.9003e-06, 0.0000e+00, 2.3667e-06,\n 2.6336e-06, 3.6370e-06, 3.9942e-06, 4.0023e-06, 0.0000e+00, 4.4792e-06,\n 2.5646e-06, 2.2675e-06, 2.0442e-06, 3.1647e-06, 1.2484e-06, 2.3386e-06,\n 6.5387e-07, 3.4101e-06, 5.5855e-06, 3.8283e-06, 3.7508e-06, 2.2131e-06,\n 4.3020e-06, 1.5134e-06, 0.0000e+00, 2.4412e-06, 3.5212e-06, 2.4761e-06,\n 1.8951e-06, 2.1451e-06, 4.7759e-06, 1.1417e-07, 4.0030e-06, 1.7724e-05,\n 6.4220e-06, 2.2049e-06, 1.6770e-06, 5.4921e-06, 0.0000e+00, 6.3872e-06,\n 2.3068e-06, 4.0647e-06, 3.4917e-06, 1.6599e-06, 8.4751e-06, 1.7833e-06,\n 2.2523e-06, 0.0000e+00, 1.4522e-06, 2.9398e-06, 8.4740e-06, 0.0000e+00,\n 4.7152e-06, 1.8582e-06, 9.0574e-07, 2.5589e-06, 3.5824e-06, 5.6454e-06,\n 1.2290e-06, 2.4016e-06, 1.0048e-06, 2.4148e-06, 2.5668e-06, 8.7847e-07,\n 0.0000e+00, 4.8952e-06, 5.7077e-06, 1.1697e-06, 0.0000e+00, 1.2489e-06,\n 1.9171e-06, 0.0000e+00, 1.5956e-06, 2.2875e-06, 1.8412e-06, 2.1935e-06,\n 7.9297e-07, 3.5524e-06, 2.0023e-06, 1.1289e-05, 9.4331e-07, 3.8892e-05,\n 1.9946e-06, 1.7153e-06, 0.0000e+00, 4.7067e-06, 2.8320e-06, 0.0000e+00,\n 1.3402e-05, 0.0000e+00, 0.0000e+00, 2.6636e-06, 0.0000e+00, 3.7576e-06,\n 2.1353e-06, 2.1014e-06, 1.0255e-05, 5.5417e-06, 2.4047e-06, 4.8765e-06,\n 5.8983e-07, 2.5503e-06, 2.5806e-05, 2.2353e-06, 1.5556e-06, 0.0000e+00,\n 4.2331e-06, 2.5264e-06, 2.1042e-06, 3.6352e-05, 0.0000e+00, 8.3238e-06,\n 2.0049e-06, 2.5691e-06, 5.6279e-06, 7.2014e-07, 6.5056e-06, 3.6962e-06,\n 1.0495e-06, 4.9145e-06, 3.9368e-06, 3.5413e-06, 3.1851e-06, 1.3152e-06,\n 0.0000e+00, 2.5037e-06, 7.3919e-06, 4.0737e-06, 1.7591e-06, 1.5200e-06,\n 2.9531e-06, 1.9816e-06, 7.4579e-06, 1.5863e-06, 5.2971e-06, 2.0507e-06,\n 0.0000e+00, 3.0350e-06, 1.1813e-06, 6.7444e-07, 2.4999e-06, 1.3370e-06,\n 2.0118e-06, 1.5975e-06, 2.9253e-06, 1.8810e-06, 1.4848e-06, 0.0000e+00,\n 2.9743e-06, 5.2230e-06])}, 41: {'step': 7160, 'exp_avg': tensor([-4.9454e-05, 1.9144e-05, 5.6052e-45, -1.2987e-04, 1.4433e-05,\n 0.0000e+00, 7.4798e-05, -1.5681e-04, -8.0725e-05, 2.6235e-05,\n -5.9702e-05, 3.0701e-06, 7.1627e-05, -2.3729e-04, 0.0000e+00,\n 1.8481e-05, 8.1764e-05, -7.5850e-07, 1.4560e-04, 1.1068e-05,\n 3.0413e-05, -3.8442e-05, 4.6541e-05, 0.0000e+00, 8.3388e-05,\n -1.5270e-05, -7.2595e-05, 1.0685e-05, 0.0000e+00, 2.7214e-06,\n 9.2899e-05, -1.0211e-04, -1.3208e-04, -2.3303e-06, -1.2978e-04,\n -2.6574e-05, -1.6205e-05, -8.1402e-05, 5.6052e-45, 2.5290e-05,\n -1.6937e-05, -3.9123e-05, 8.3049e-05, -6.1848e-05, 1.5659e-04,\n 8.4616e-05, 1.7502e-04, -1.3272e-04, -3.5982e-05, -5.1393e-06,\n 5.3111e-06, 5.6052e-45, 3.2657e-05, 8.9079e-05, 1.8909e-06,\n 1.3947e-05, -4.0644e-05, -6.7275e-05, -1.6259e-04, 0.0000e+00,\n 1.0850e-04, -1.7852e-04, -1.6276e-06, 8.0599e-05, 1.9256e-05,\n -1.1927e-05, 1.4665e-04, 1.8814e-05, 0.0000e+00, 3.2882e-05,\n 9.0885e-05, 8.2894e-05, 4.9136e-05, 1.0280e-04, 4.1447e-05,\n -5.7985e-05, -5.8358e-06, -3.0850e-05, 3.7252e-05, 1.0898e-04,\n 3.8823e-05, -7.5905e-05, -1.2071e-05, -3.9477e-05, -1.0634e-04,\n 9.7661e-05, -6.6543e-06, 9.4731e-05, -1.9458e-05, 0.0000e+00,\n 0.0000e+00, -8.1609e-05, -3.1704e-05, -4.4914e-04, 0.0000e+00,\n -2.4927e-05, -1.0982e-05, -4.6911e-05, -7.6021e-05, 1.4819e-04,\n -9.5577e-05, -7.0775e-06, -1.0266e-04, 5.8104e-05, 5.0555e-05,\n 0.0000e+00, 9.4277e-05, 1.2273e-05, -7.2250e-05, -1.8979e-05,\n 7.6213e-05, 1.3195e-04, 0.0000e+00, -5.3978e-05, 1.6433e-04,\n 2.9165e-05, 8.6854e-05, 2.3434e-06, -8.5568e-05, 3.5121e-05,\n -1.2872e-04, -3.3180e-05, -5.4187e-05, -4.4866e-05, 1.0577e-05,\n 9.7637e-05, 1.2888e-04, -1.5576e-04, 6.4116e-05, -2.0913e-05,\n 7.0963e-05, -3.5865e-05, -6.8456e-05, 0.0000e+00, 3.7230e-06,\n 7.6083e-05, 4.2422e-05, 4.3134e-05, 0.0000e+00, -1.2985e-06,\n -1.5743e-05, 1.1148e-04, 1.6042e-04, 0.0000e+00, -4.8805e-05,\n -5.8823e-05, 2.9555e-05, 1.1138e-05, 2.0100e-05, 8.3891e-05,\n 6.0606e-05, 7.7356e-05, 1.0095e-04, 0.0000e+00, 1.2229e-04,\n -9.3974e-06, -1.5548e-04, 0.0000e+00, 1.5327e-04, -9.2868e-05,\n 1.4351e-04, 5.8069e-05, -5.6555e-06, 1.6486e-04, 7.3766e-06,\n 0.0000e+00, 1.0101e-04, 9.0580e-05, -6.2354e-06, 8.5288e-06,\n 0.0000e+00, -1.4034e-06, 1.1899e-04, 1.3210e-04, 0.0000e+00,\n -6.2430e-05, 7.3909e-06, 5.0901e-05, -5.4160e-06, -3.7853e-05,\n -6.5435e-05, -4.4524e-06, 3.8043e-06, -6.1252e-05, -4.7645e-05,\n -1.5952e-06, 0.0000e+00, -1.3456e-04, -2.1165e-04, -1.2671e-04,\n -2.8345e-05, -1.8167e-05, 1.5516e-04, 1.9221e-05, 1.4289e-04,\n 6.6838e-05, 0.0000e+00, 8.2566e-05, 5.9903e-05, -1.2254e-04,\n 0.0000e+00, -5.7807e-05, -7.4314e-05, -1.9485e-06, 0.0000e+00,\n 9.7555e-06, -1.0192e-04, -9.2218e-05, -9.1848e-05, -3.1185e-10,\n -3.5595e-06, -1.3480e-05, -1.7453e-05, 0.0000e+00, 1.1067e-04,\n 4.7691e-05, -1.1522e-05, -2.3730e-04, 1.8210e-05, -2.5250e-05,\n 2.7342e-05, -3.1786e-05, 0.0000e+00, 2.4084e-05, -1.1190e-04,\n 1.6719e-05, 5.0222e-05, 6.2330e-05, 2.8262e-05, 4.3103e-05,\n 1.5192e-05, 1.4276e-05, 1.0948e-05, 5.5502e-05, 0.0000e+00,\n 1.1717e-05, 0.0000e+00, -8.2872e-05, 5.7641e-05, 4.5756e-05,\n 0.0000e+00, -7.3951e-05, 2.6523e-05, 1.8148e-04, -1.7137e-05,\n 8.6776e-05, 1.2332e-04, -4.5485e-05, -7.9795e-06, -1.4859e-05,\n 1.5164e-05, 2.3328e-04, 8.9865e-05, 1.4702e-05, 1.3850e-05,\n -5.6759e-05, 9.7365e-05, 3.4938e-05, -1.6189e-05, 9.0384e-05,\n -8.5659e-05, 1.4351e-04, 1.9256e-04, 7.8086e-05, -4.4336e-05,\n -1.1377e-04, 1.4745e-04, -1.0039e-04, -1.7161e-04, 1.4252e-04,\n 0.0000e+00, -1.1425e-05, 0.0000e+00, -1.8714e-04, 1.2660e-05,\n -1.1349e-04, 1.0618e-05, -3.6141e-05, -1.0111e-04, -2.1594e-05,\n -2.3617e-05, -6.3555e-05, 1.1438e-04, -1.9795e-05, -3.2578e-05,\n -3.1110e-05, 1.7605e-05, 9.7793e-06, -1.1695e-05, 2.1745e-05,\n -9.0514e-05, 0.0000e+00, 6.4441e-06, 2.5619e-05, 8.7247e-05,\n 1.4520e-04, 3.8760e-05, 0.0000e+00, 1.7221e-05, 0.0000e+00,\n -5.8831e-05, -7.5295e-05, 3.5189e-05, -4.5112e-05, 7.3547e-05,\n 1.6156e-04, 1.2757e-04, -4.9937e-05, -5.3478e-07, 5.8482e-05,\n -9.9389e-05, 0.0000e+00, 0.0000e+00, 0.0000e+00, 1.2540e-04,\n -5.1147e-05, -6.1338e-05, -1.8496e-05, 0.0000e+00, 4.5042e-05,\n -3.2683e-05, -1.1451e-04, 7.9106e-05, 8.1907e-05, 5.3002e-05,\n 0.0000e+00, 8.7699e-05, -4.4098e-05, -3.2089e-05, -1.1989e-04,\n -2.0026e-05, -4.5696e-05, 0.0000e+00, -4.3260e-05, -8.5932e-05,\n 1.3079e-05, 5.3568e-05, 2.7710e-05, 9.9911e-05, -6.5453e-08,\n -1.1451e-04, 7.7526e-05, -3.9310e-05, -2.6170e-06, -1.1285e-05,\n 5.1036e-05, 0.0000e+00, 3.5048e-05, -2.7218e-05, -2.8764e-05,\n -1.2599e-04, -3.9535e-05, 4.0113e-05, -1.2777e-04, 4.4260e-05,\n -2.4913e-05, 3.2799e-05, 1.6299e-04, -8.8179e-05, -3.4980e-06,\n -8.0974e-06, -6.8985e-05, -9.1765e-05, 2.5475e-04, 0.0000e+00,\n 4.4935e-05, -4.5527e-05, 9.2149e-06, -1.0643e-04, 8.1968e-05,\n 0.0000e+00, 1.7699e-04, 8.7514e-06, -2.5493e-05, 6.5577e-05,\n -1.4851e-04, -4.0236e-05, 1.1874e-05, 1.8839e-05, -1.6846e-05,\n -1.3983e-04, 2.1514e-05, 5.2231e-05, -3.0308e-05, 1.2178e-04,\n 2.9087e-05, 0.0000e+00, 5.1559e-05, 1.4832e-04, 3.6962e-05,\n -8.0114e-05, -3.9206e-05, -7.4997e-05, 3.0776e-05, 2.0904e-05,\n -3.9540e-05, -2.8363e-04, 7.7506e-05, 5.5966e-05, -2.2887e-04,\n 0.0000e+00, -2.3940e-04, -9.0769e-05, -4.8502e-05, 1.0563e-05,\n 1.9133e-05, -2.2287e-05, 2.8805e-05, 7.9450e-05, 0.0000e+00,\n 1.4604e-04, -2.2283e-05, -2.1249e-05, 0.0000e+00, -5.6520e-05,\n 3.6743e-05, -1.0277e-05, 4.7650e-05, -1.0456e-04, 4.8176e-06,\n 1.8331e-05, 5.0230e-05, -1.0159e-04, -1.2810e-04, 8.8724e-05,\n -2.1761e-05, 0.0000e+00, 9.1760e-05, -2.2720e-05, -4.2902e-05,\n 0.0000e+00, 1.9870e-05, 7.6620e-06, 0.0000e+00, -9.6662e-05,\n -1.8148e-05, -1.8787e-06, -3.5511e-05, -1.7841e-05, -4.1862e-06,\n 6.1666e-06, -2.1965e-05, 2.8880e-05, 3.7099e-04, -1.6627e-05,\n -6.0690e-05, 0.0000e+00, 1.1602e-04, 7.4878e-05, 0.0000e+00,\n 1.5739e-04, 0.0000e+00, 0.0000e+00, 6.9551e-05, 0.0000e+00,\n -7.2953e-05, 1.1631e-04, 4.7907e-06, -4.7170e-05, 7.6205e-05,\n -2.2192e-05, -1.6069e-05, 1.3995e-05, 3.3372e-05, 4.8928e-05,\n 1.0889e-04, 4.0438e-05, 0.0000e+00, 5.9142e-05, -2.5676e-05,\n -1.2764e-04, 6.8173e-04, 0.0000e+00, 1.1841e-04, -2.9164e-05,\n 1.4978e-05, 1.5187e-04, 5.6375e-05, 7.0375e-05, -1.2485e-06,\n -1.0491e-04, 1.3695e-05, -1.7533e-04, -3.1958e-05, -4.0280e-05,\n 4.4818e-05, 0.0000e+00, 1.3691e-05, -4.2685e-05, -3.2466e-05,\n -3.3346e-05, -7.3000e-05, 2.4047e-06, -1.5742e-05, 1.5366e-05,\n 7.1827e-05, -2.6046e-05, -3.0174e-05, 0.0000e+00, 7.4379e-05,\n -4.9739e-05, 6.6799e-05, -8.7937e-06, 1.6888e-04, -4.7865e-05,\n 4.3769e-05, -7.9603e-06, 7.7277e-05, 7.7407e-05, 0.0000e+00,\n 5.7162e-05, 6.8096e-05]), 'exp_avg_sq': tensor([1.8749e-06, 1.2941e-06, 3.6692e-15, 1.0852e-06, 7.7323e-07, 0.0000e+00,\n 8.9515e-07, 2.0760e-06, 9.2001e-07, 1.4942e-06, 7.0259e-07, 8.0385e-07,\n 1.5857e-06, 1.6116e-06, 0.0000e+00, 9.2184e-07, 1.4554e-06, 1.6274e-06,\n 1.3122e-06, 1.3169e-06, 7.4358e-07, 2.4108e-06, 1.5006e-06, 0.0000e+00,\n 2.0572e-06, 1.4214e-06, 9.3591e-07, 1.5228e-06, 0.0000e+00, 1.5602e-06,\n 8.2904e-07, 6.3910e-06, 2.9247e-06, 9.7269e-07, 3.7430e-06, 1.7370e-06,\n 3.6087e-06, 1.2340e-06, 1.3204e-20, 2.9395e-06, 8.7296e-07, 8.7942e-07,\n 1.0555e-06, 1.4244e-06, 1.1443e-06, 7.0274e-07, 2.9323e-06, 1.0526e-06,\n 8.5174e-07, 1.0293e-06, 7.8889e-07, 7.5690e-19, 9.0782e-07, 9.9749e-07,\n 1.4242e-06, 6.2376e-07, 6.7129e-07, 8.4478e-07, 2.9202e-06, 0.0000e+00,\n 2.9024e-06, 8.8193e-07, 7.6903e-07, 1.2337e-06, 5.3271e-07, 1.1696e-06,\n 5.4511e-07, 8.9265e-07, 0.0000e+00, 9.7671e-07, 9.3254e-07, 1.6163e-06,\n 1.2493e-06, 1.2283e-06, 1.7432e-06, 2.0578e-06, 1.3494e-06, 1.6174e-06,\n 3.1990e-06, 6.6740e-07, 1.2995e-06, 6.9521e-07, 1.1217e-07, 9.2459e-07,\n 9.2873e-07, 1.5864e-06, 1.2286e-06, 2.6612e-06, 5.0662e-06, 0.0000e+00,\n 0.0000e+00, 1.0232e-06, 3.2280e-07, 7.7094e-06, 0.0000e+00, 7.2239e-07,\n 2.0544e-06, 2.4719e-06, 9.9935e-07, 9.2445e-06, 1.8429e-06, 3.9494e-07,\n 2.7704e-06, 9.5465e-07, 1.2548e-06, 0.0000e+00, 1.7931e-06, 6.3046e-07,\n 1.7190e-06, 1.4743e-06, 1.5591e-06, 2.0939e-06, 0.0000e+00, 1.4136e-06,\n 2.1329e-06, 2.4415e-06, 9.9118e-07, 1.2360e-06, 1.4899e-06, 1.5296e-06,\n 5.8488e-07, 1.0574e-06, 1.3279e-06, 1.3924e-06, 1.0822e-06, 9.8699e-06,\n 1.4183e-06, 5.4111e-06, 8.8336e-07, 1.7323e-06, 1.4000e-06, 7.7143e-07,\n 1.0676e-06, 0.0000e+00, 2.0138e-06, 8.8300e-07, 1.1953e-06, 1.3745e-06,\n 0.0000e+00, 1.2232e-06, 9.1414e-07, 1.7686e-06, 6.8910e-07, 0.0000e+00,\n 4.2107e-07, 2.2580e-06, 1.6173e-06, 9.5094e-07, 2.0016e-06, 9.5494e-07,\n 1.5222e-06, 2.7670e-06, 1.6280e-06, 0.0000e+00, 3.8305e-06, 1.7395e-06,\n 8.5114e-06, 0.0000e+00, 1.4017e-06, 8.9301e-07, 8.8612e-07, 3.3829e-06,\n 1.2915e-06, 9.3655e-07, 7.9382e-07, 0.0000e+00, 1.4220e-06, 1.1119e-06,\n 6.8746e-07, 1.3619e-06, 0.0000e+00, 2.6704e-06, 2.7602e-06, 3.0591e-06,\n 0.0000e+00, 1.2090e-06, 1.2096e-06, 1.5233e-06, 1.0754e-06, 5.9833e-07,\n 5.8720e-07, 9.0232e-07, 1.2542e-06, 2.4326e-06, 1.1087e-06, 2.8776e-06,\n 0.0000e+00, 1.2581e-06, 2.6023e-06, 1.5893e-06, 2.2937e-06, 7.5513e-07,\n 9.8891e-07, 2.7039e-06, 4.6559e-06, 1.1132e-06, 0.0000e+00, 7.6990e-07,\n 1.0125e-06, 1.1563e-05, 0.0000e+00, 9.3384e-07, 1.7171e-06, 1.0422e-06,\n 0.0000e+00, 6.0432e-07, 1.4749e-06, 1.0879e-06, 6.5624e-06, 8.6833e-13,\n 9.4092e-07, 1.6172e-06, 3.9008e-06, 0.0000e+00, 1.0475e-06, 1.2128e-06,\n 1.0141e-06, 6.5951e-06, 2.2068e-06, 2.4536e-06, 1.2755e-06, 5.8586e-07,\n 0.0000e+00, 1.3280e-06, 1.4568e-06, 1.3028e-06, 1.1734e-06, 1.1261e-06,\n 1.1454e-06, 1.2045e-06, 2.0124e-06, 1.4116e-06, 1.8013e-06, 2.2191e-07,\n 0.0000e+00, 1.4196e-06, 0.0000e+00, 3.6012e-06, 2.1275e-06, 3.6746e-06,\n 0.0000e+00, 9.8409e-07, 8.9950e-07, 1.8480e-06, 8.8633e-07, 9.1552e-07,\n 1.1235e-06, 1.3176e-06, 1.5932e-06, 2.0480e-06, 9.9525e-07, 1.6146e-05,\n 1.6135e-06, 8.4653e-07, 5.2452e-07, 1.8517e-06, 9.8078e-07, 8.9104e-07,\n 1.3862e-06, 1.3929e-06, 3.2321e-07, 1.1053e-06, 1.0701e-06, 2.3258e-06,\n 1.0121e-06, 1.2715e-05, 2.1055e-06, 1.1877e-06, 9.2597e-06, 3.0815e-06,\n 0.0000e+00, 7.5847e-07, 0.0000e+00, 3.0062e-06, 1.0652e-06, 4.4771e-06,\n 1.1021e-06, 6.8786e-07, 5.8480e-07, 9.5305e-07, 1.1111e-06, 1.7077e-06,\n 6.7385e-07, 1.3172e-06, 1.4327e-06, 2.7993e-06, 6.7181e-07, 8.5768e-07,\n 8.5595e-07, 6.2300e-07, 5.6239e-06, 0.0000e+00, 6.7069e-07, 6.5126e-07,\n 6.2678e-07, 1.1425e-06, 9.6610e-07, 0.0000e+00, 1.4256e-06, 0.0000e+00,\n 8.4359e-07, 8.6617e-07, 8.7438e-07, 1.7714e-06, 5.8104e-07, 9.8375e-07,\n 2.9998e-07, 1.2692e-06, 1.3578e-06, 3.2002e-06, 9.5169e-07, 0.0000e+00,\n 0.0000e+00, 0.0000e+00, 1.8538e-06, 1.9294e-06, 1.3564e-06, 3.7077e-06,\n 0.0000e+00, 9.8398e-07, 1.5780e-06, 2.1837e-06, 9.9139e-07, 7.6913e-07,\n 2.4374e-06, 0.0000e+00, 5.3144e-07, 1.0868e-06, 8.5792e-07, 3.8895e-06,\n 2.1510e-06, 1.3078e-06, 0.0000e+00, 4.8235e-06, 9.0311e-07, 1.0111e-06,\n 1.5102e-06, 2.6887e-06, 5.7027e-07, 8.4988e-07, 3.1089e-06, 1.1824e-06,\n 2.4017e-06, 7.5170e-07, 3.5820e-06, 1.6989e-06, 0.0000e+00, 2.0267e-06,\n 8.6254e-07, 5.6231e-06, 2.0105e-06, 7.1438e-07, 1.6942e-06, 1.2543e-06,\n 5.2477e-06, 9.7849e-07, 7.9002e-07, 1.4636e-05, 1.8968e-06, 1.9603e-06,\n 1.0157e-06, 1.5986e-06, 6.9874e-07, 2.4090e-06, 0.0000e+00, 1.4984e-06,\n 9.0926e-07, 1.5219e-06, 8.7663e-07, 1.1531e-06, 0.0000e+00, 2.7509e-06,\n 1.4209e-06, 1.3227e-06, 1.8017e-06, 1.3401e-06, 7.5713e-07, 9.7679e-07,\n 3.2986e-07, 1.1596e-06, 1.7696e-06, 1.9963e-06, 1.6517e-06, 1.1193e-06,\n 9.8749e-07, 8.8535e-07, 0.0000e+00, 2.6688e-06, 1.2575e-06, 1.3290e-06,\n 1.2157e-06, 8.3166e-07, 5.6310e-06, 8.3160e-08, 1.4857e-06, 1.9304e-06,\n 3.6449e-06, 9.8234e-07, 1.0002e-06, 3.9349e-06, 0.0000e+00, 4.6503e-06,\n 1.2846e-06, 4.9515e-06, 1.1806e-06, 9.9208e-07, 2.0010e-06, 7.4852e-07,\n 1.2046e-06, 0.0000e+00, 1.3101e-06, 8.9588e-07, 1.8220e-06, 0.0000e+00,\n 4.8793e-06, 6.7762e-07, 5.7353e-07, 1.1508e-06, 1.7554e-06, 3.6277e-06,\n 7.1172e-07, 1.0005e-06, 5.8750e-07, 1.1741e-06, 1.4694e-06, 5.7909e-07,\n 0.0000e+00, 3.9580e-06, 1.9459e-06, 4.9178e-07, 0.0000e+00, 4.2578e-07,\n 1.3545e-06, 0.0000e+00, 7.3827e-07, 1.2845e-06, 6.2994e-07, 1.4521e-06,\n 8.0962e-07, 1.0122e-06, 1.6763e-06, 3.6377e-06, 4.5655e-07, 1.4786e-05,\n 6.4796e-07, 8.8282e-07, 0.0000e+00, 1.0289e-06, 1.9564e-06, 0.0000e+00,\n 4.5820e-06, 0.0000e+00, 0.0000e+00, 1.0577e-06, 0.0000e+00, 1.3378e-06,\n 1.2257e-06, 9.1467e-07, 5.0694e-06, 3.5707e-06, 1.0010e-06, 1.2478e-06,\n 1.7334e-07, 1.4064e-06, 2.1335e-06, 1.0483e-06, 7.7759e-07, 0.0000e+00,\n 4.9092e-06, 8.0205e-07, 8.0685e-07, 1.6514e-05, 0.0000e+00, 3.9641e-06,\n 1.2516e-06, 9.7309e-07, 4.2271e-06, 5.1609e-07, 2.0212e-06, 1.3647e-06,\n 1.0302e-06, 1.1891e-06, 3.6931e-06, 1.5070e-06, 1.0137e-06, 7.4116e-07,\n 0.0000e+00, 1.0296e-06, 1.0503e-06, 2.8710e-06, 5.3511e-07, 1.3085e-06,\n 1.2472e-06, 1.3442e-06, 3.7520e-06, 9.1878e-07, 2.4385e-06, 2.7503e-06,\n 0.0000e+00, 1.6288e-06, 6.5256e-07, 5.7734e-07, 7.3027e-07, 9.0762e-07,\n 1.3521e-06, 1.8405e-06, 3.7539e-06, 1.1808e-06, 7.6427e-07, 0.0000e+00,\n 1.2854e-06, 2.0941e-06])}, 42: {'step': 7160, 'exp_avg': tensor([[[[ 1.3530e-05]],\n\n [[ 6.1582e-06]],\n\n [[-1.4688e-05]],\n\n ...,\n\n [[-2.1557e-06]],\n\n [[ 1.9547e-05]],\n\n [[ 2.2462e-05]]],\n\n\n [[[ 2.1106e-05]],\n\n [[ 2.0360e-05]],\n\n [[ 3.5097e-06]],\n\n ...,\n\n [[ 1.9485e-05]],\n\n [[-1.5620e-05]],\n\n [[-1.0103e-05]]],\n\n\n [[[ 5.6052e-45]],\n\n [[ 5.6052e-45]],\n\n [[-5.6052e-45]],\n\n ...,\n\n [[ 5.6052e-45]],\n\n [[-5.6052e-45]],\n\n [[-5.6052e-45]]],\n\n\n ...,\n\n\n [[[ 0.0000e+00]],\n\n [[ 0.0000e+00]],\n\n [[ 0.0000e+00]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[ 0.0000e+00]],\n\n [[ 0.0000e+00]]],\n\n\n [[[ 6.8426e-06]],\n\n [[ 1.7499e-05]],\n\n [[-1.4752e-05]],\n\n ...,\n\n [[ 8.4112e-06]],\n\n [[ 1.3927e-05]],\n\n [[-2.3549e-05]]],\n\n\n [[[-2.1291e-05]],\n\n [[-1.1263e-05]],\n\n [[-1.6747e-05]],\n\n ...,\n\n [[-7.8232e-05]],\n\n [[-1.4582e-05]],\n\n [[ 7.0949e-05]]]]), 'exp_avg_sq': tensor([[[[1.9692e-07]],\n\n [[3.8220e-07]],\n\n [[1.8462e-07]],\n\n ...,\n\n [[8.5071e-08]],\n\n [[4.2171e-07]],\n\n [[4.0737e-07]]],\n\n\n [[[6.7512e-08]],\n\n [[1.8159e-07]],\n\n [[7.5237e-08]],\n\n ...,\n\n [[3.8947e-08]],\n\n [[1.0844e-07]],\n\n [[1.0907e-07]]],\n\n\n [[[4.4560e-19]],\n\n [[2.1211e-19]],\n\n [[1.4422e-17]],\n\n ...,\n\n [[2.9856e-18]],\n\n [[2.9623e-17]],\n\n [[1.1376e-17]]],\n\n\n ...,\n\n\n [[[0.0000e+00]],\n\n [[0.0000e+00]],\n\n [[0.0000e+00]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[0.0000e+00]],\n\n [[0.0000e+00]]],\n\n\n [[[3.7791e-08]],\n\n [[7.9956e-08]],\n\n [[2.5000e-08]],\n\n ...,\n\n [[3.1845e-08]],\n\n [[4.0333e-08]],\n\n [[5.6901e-08]]],\n\n\n [[[2.7893e-07]],\n\n [[5.1813e-07]],\n\n [[2.6413e-07]],\n\n ...,\n\n [[3.5949e-07]],\n\n [[5.2277e-07]],\n\n [[5.7046e-07]]]])}, 43: {'step': 7160, 'exp_avg': tensor([ 1.5949e-05, 7.8980e-05, 5.6052e-45, -3.3331e-04, 4.9634e-05,\n 0.0000e+00, 9.5510e-05, -2.9780e-04, -7.5649e-05, -7.0295e-05,\n -2.5373e-05, -1.5285e-05, 5.8802e-05, -3.6523e-04, 0.0000e+00,\n -2.4797e-05, 5.5089e-05, 8.8671e-05, 1.7996e-04, -5.6133e-05,\n -5.9781e-05, 7.4110e-05, 1.3296e-04, 0.0000e+00, 1.9694e-04,\n -1.1172e-04, -1.2082e-04, 2.6203e-05, 0.0000e+00, 2.9243e-05,\n 1.8301e-04, -3.2245e-04, 6.2818e-05, -2.4278e-05, -4.1841e-04,\n 3.9232e-05, -4.0275e-06, -2.5687e-05, -5.6052e-45, -2.8784e-05,\n -5.2164e-05, -1.0342e-04, 1.9663e-05, -5.7564e-05, 1.3697e-04,\n 3.9061e-06, 1.1845e-04, -1.4636e-04, -1.8413e-04, -5.4207e-05,\n 1.6295e-04, 5.6052e-45, 2.3788e-04, 2.0643e-06, -4.6375e-06,\n 5.4407e-05, -6.0465e-05, -4.1186e-05, -2.1710e-04, 0.0000e+00,\n 4.4007e-04, -1.5587e-04, -3.6480e-05, 4.5346e-05, 7.9242e-05,\n 5.7056e-05, 4.0573e-04, 1.2765e-04, 0.0000e+00, -1.5466e-04,\n 1.7816e-05, 7.8430e-05, 7.2765e-06, 2.8925e-05, -7.8237e-05,\n -2.7298e-04, 2.8562e-05, -1.1289e-04, 2.5111e-05, 1.0010e-04,\n 1.0585e-04, -6.3791e-05, -1.6851e-05, -2.6292e-05, -2.4516e-04,\n 2.3016e-04, -4.5890e-05, 1.1678e-04, -3.9212e-05, 0.0000e+00,\n 0.0000e+00, -4.2468e-05, 2.0423e-05, -2.9495e-04, 0.0000e+00,\n -6.4070e-05, -7.4486e-06, -8.5290e-05, -9.3397e-05, 3.3171e-04,\n -3.3904e-04, -5.0256e-05, -1.8785e-04, 7.2013e-05, 1.0172e-04,\n 0.0000e+00, 1.2065e-05, -4.3362e-05, -4.2592e-05, 4.7433e-05,\n -6.3530e-05, 1.9899e-04, 0.0000e+00, -1.1368e-04, -7.0608e-05,\n 4.3604e-05, 1.6894e-05, -5.5243e-05, -7.4466e-05, -2.0902e-05,\n -2.0059e-04, -1.2248e-04, -1.2297e-04, -8.9005e-05, -5.4468e-05,\n -2.3579e-04, 1.1099e-04, -2.2058e-04, 4.6724e-05, -2.8306e-05,\n -1.2383e-05, -5.3498e-05, -1.6555e-04, 0.0000e+00, 1.2631e-04,\n 1.0936e-05, -4.1476e-05, 5.3871e-05, 0.0000e+00, -8.7001e-05,\n 5.1213e-05, 5.9534e-05, 1.4499e-04, 0.0000e+00, -8.5494e-05,\n 9.0525e-06, 4.1273e-05, 1.5799e-04, -1.6605e-05, 9.1379e-05,\n 9.4754e-05, 3.6165e-06, 7.6498e-05, 0.0000e+00, -1.3512e-04,\n -6.5192e-05, -2.0089e-04, 0.0000e+00, -2.1565e-05, -1.0595e-04,\n 1.6758e-04, -2.3645e-06, -5.7584e-05, 1.3076e-04, 1.3976e-04,\n 0.0000e+00, 1.4248e-04, 2.6222e-04, 4.9157e-05, 5.2743e-05,\n 0.0000e+00, -1.2270e-04, 2.2392e-04, -1.7126e-04, 0.0000e+00,\n 1.7900e-04, -1.1301e-04, 1.6601e-04, 1.1064e-04, 1.1343e-04,\n -4.5707e-05, -4.8127e-05, -6.8127e-06, -4.8642e-05, -1.8776e-05,\n -3.7274e-05, 0.0000e+00, -1.5722e-04, -8.1558e-05, -8.2725e-05,\n 8.7857e-05, 8.6444e-05, 1.1920e-04, 2.5868e-05, -1.1165e-04,\n 1.0261e-04, 0.0000e+00, 7.8159e-05, 5.8368e-05, 2.6095e-04,\n 0.0000e+00, -5.8192e-05, -7.0395e-05, 3.0395e-05, 0.0000e+00,\n 1.8115e-05, 1.4646e-04, -1.3100e-04, -1.6940e-04, -2.8729e-10,\n -6.0876e-05, -1.9388e-05, -1.4445e-04, 0.0000e+00, 7.1607e-05,\n -1.5613e-05, -1.2701e-04, -3.4348e-04, -8.5530e-05, -2.3493e-05,\n 3.4888e-05, -1.3258e-04, 0.0000e+00, -1.8902e-05, -8.8036e-05,\n -5.4486e-05, -4.4950e-05, -9.7124e-05, -1.1451e-04, 4.8131e-05,\n 1.7171e-04, 1.0306e-04, -1.2140e-04, 4.2011e-05, 0.0000e+00,\n 7.4322e-05, 0.0000e+00, -1.8295e-04, 4.1916e-05, 3.3356e-05,\n 0.0000e+00, -1.9394e-05, 1.7563e-04, 1.2521e-04, 6.9540e-05,\n 1.0800e-04, -1.7534e-05, 7.4989e-05, 4.8784e-05, -9.1452e-05,\n -1.3776e-04, -3.0896e-04, 3.7373e-05, 1.1488e-04, 8.5151e-05,\n 7.4968e-05, -1.6676e-06, -1.2314e-04, 5.1889e-05, 1.4312e-04,\n -5.8466e-05, 2.0856e-04, 2.2048e-04, 1.1205e-04, 5.8116e-05,\n -7.6863e-04, 1.2032e-04, -2.0881e-04, -5.1837e-05, 1.2917e-04,\n 0.0000e+00, 3.7009e-05, 0.0000e+00, -1.3636e-04, -3.1534e-05,\n -3.0808e-04, -1.0568e-05, 2.3524e-05, -1.0401e-04, 7.0739e-05,\n -2.7785e-06, -7.9224e-05, 6.2162e-05, -2.8894e-05, 4.0721e-05,\n 7.3026e-05, -6.5334e-05, 5.3196e-05, 3.2236e-05, -4.1291e-05,\n -6.1824e-05, 0.0000e+00, -1.1533e-04, 1.2439e-04, 8.1157e-05,\n 5.6660e-05, 7.7580e-05, 0.0000e+00, -1.2858e-05, 0.0000e+00,\n -1.9534e-05, -1.1992e-04, -3.6069e-05, 1.2222e-04, 1.4605e-05,\n 2.5569e-04, 1.9702e-04, -3.6036e-06, -6.9753e-05, 1.1176e-04,\n -1.8428e-04, 0.0000e+00, 0.0000e+00, 0.0000e+00, 3.0213e-06,\n -8.9747e-05, -6.9010e-05, -3.8000e-05, 0.0000e+00, 1.5409e-04,\n -4.0595e-05, -1.2045e-04, 1.0132e-04, 7.1269e-06, 2.0281e-05,\n 0.0000e+00, 7.7254e-05, -2.0243e-05, -2.0420e-07, -2.6780e-04,\n -2.0586e-04, 3.1729e-05, 0.0000e+00, -1.7703e-05, -2.1579e-04,\n -2.1759e-05, 3.3940e-05, 1.2856e-04, 1.5875e-04, -9.1405e-05,\n -1.6176e-04, -5.5746e-05, -1.1591e-04, -1.6163e-05, 4.0714e-05,\n 5.9573e-05, 0.0000e+00, 3.7055e-05, -6.6971e-05, 1.3323e-04,\n -1.6094e-04, -5.8163e-05, 9.7289e-06, -2.3858e-04, -2.0548e-04,\n 6.8110e-07, -4.4410e-05, -8.5683e-04, -9.4039e-05, 1.4029e-04,\n -4.7871e-05, -1.6793e-04, -1.1221e-04, 2.6415e-04, 0.0000e+00,\n 2.8816e-05, -8.5288e-05, 2.0093e-04, -3.8812e-05, 3.9739e-05,\n 0.0000e+00, -1.4266e-04, 1.0312e-04, -5.6185e-05, 3.7379e-05,\n -1.3867e-04, -5.5309e-05, 6.6363e-05, 4.4096e-05, -4.5251e-05,\n 5.1088e-05, 1.3605e-04, -5.7661e-05, -2.1658e-05, 1.2369e-04,\n 1.1009e-05, 0.0000e+00, 1.2716e-05, -9.5771e-05, -2.6259e-05,\n -1.4871e-05, -1.3255e-04, 7.7043e-05, 4.1927e-05, -1.5491e-04,\n 1.5379e-04, -3.2436e-04, 1.7318e-04, -4.6233e-05, -4.2147e-04,\n 0.0000e+00, -4.8159e-05, -3.3383e-04, -5.0836e-05, 7.8630e-05,\n 6.0933e-05, 4.4922e-06, 3.1259e-05, 2.0222e-05, 0.0000e+00,\n -4.5816e-05, -5.0383e-05, -2.5578e-05, 0.0000e+00, -8.8328e-05,\n 5.2385e-05, 2.4966e-05, 1.1783e-04, -1.4016e-04, -1.6301e-05,\n -3.7664e-05, 1.1141e-04, -1.3599e-04, -7.6848e-05, 7.1667e-05,\n -3.5793e-05, 0.0000e+00, 6.1588e-05, 8.4515e-05, -5.3025e-05,\n 0.0000e+00, 1.2665e-05, 2.1478e-04, 0.0000e+00, -1.0202e-04,\n -3.9473e-05, -8.8647e-06, -6.3266e-05, -2.8509e-05, -7.1207e-06,\n -5.7394e-05, 6.1476e-05, 6.6058e-05, -7.9474e-04, 5.0631e-05,\n -1.3468e-04, 0.0000e+00, -2.8449e-05, 5.1685e-05, 0.0000e+00,\n 3.4519e-04, 0.0000e+00, 0.0000e+00, -3.0760e-04, 0.0000e+00,\n -3.9765e-05, 1.6384e-04, 1.7970e-04, 1.7553e-04, 1.3359e-04,\n 7.3972e-05, 3.7053e-05, -8.0760e-06, -9.3463e-05, 7.0332e-05,\n -3.5424e-05, 1.7691e-04, 0.0000e+00, 1.2790e-04, -8.3870e-05,\n -8.7162e-05, -9.0783e-04, 0.0000e+00, -9.7956e-05, 4.3872e-05,\n 1.3854e-04, 1.5041e-05, 8.2180e-05, 2.9249e-05, 1.2240e-04,\n 1.3396e-05, -6.0910e-05, -2.0824e-04, -1.1282e-04, -4.4312e-05,\n 1.0290e-04, 0.0000e+00, -1.2288e-04, -1.0812e-04, -1.7228e-04,\n 2.6296e-05, -5.9955e-05, -1.4395e-04, -2.5788e-05, -2.9552e-04,\n 5.7416e-05, -3.8246e-05, -4.1407e-05, 0.0000e+00, 1.5196e-04,\n 2.6269e-06, 2.2198e-04, 1.0796e-04, 9.8904e-05, 4.2922e-05,\n 1.0536e-04, 7.3149e-06, 6.5305e-05, 7.3735e-05, 0.0000e+00,\n 1.3566e-04, -3.0122e-04]), 'exp_avg_sq': tensor([5.1158e-06, 3.1915e-06, 3.0218e-14, 2.9381e-06, 1.4726e-06, 0.0000e+00,\n 3.0544e-06, 5.0821e-06, 1.1378e-06, 3.2750e-06, 9.1066e-07, 2.7549e-06,\n 3.0344e-06, 3.8491e-06, 0.0000e+00, 1.9473e-06, 2.5794e-06, 4.0565e-06,\n 3.7398e-06, 2.6370e-06, 1.3197e-06, 4.8761e-06, 3.9954e-06, 0.0000e+00,\n 3.3179e-06, 2.6213e-06, 1.3951e-06, 3.6290e-06, 0.0000e+00, 5.6036e-06,\n 1.3365e-06, 2.6252e-05, 3.5412e-06, 1.4550e-06, 2.2206e-05, 2.1581e-06,\n 3.3440e-05, 1.2104e-06, 4.1790e-20, 3.0857e-06, 2.0424e-06, 1.7448e-06,\n 1.1652e-06, 2.2446e-06, 1.0359e-06, 2.0989e-06, 4.8301e-06, 3.9364e-06,\n 2.7066e-06, 1.5375e-06, 3.9593e-06, 2.4231e-18, 2.7702e-06, 1.9661e-06,\n 2.1215e-06, 1.3081e-06, 2.2338e-06, 1.2234e-06, 2.5188e-06, 0.0000e+00,\n 6.9076e-06, 1.1758e-06, 1.1659e-06, 3.6246e-06, 9.8947e-07, 2.2527e-06,\n 5.0336e-06, 1.2137e-06, 0.0000e+00, 2.1227e-06, 2.4175e-06, 3.8709e-06,\n 1.8099e-06, 2.3880e-06, 2.9044e-06, 4.6046e-06, 1.6868e-06, 7.8220e-06,\n 5.0588e-06, 1.1364e-06, 2.0833e-06, 1.3435e-06, 2.9847e-07, 1.4137e-06,\n 2.8426e-06, 2.7113e-06, 2.0713e-06, 3.7510e-06, 2.9347e-05, 0.0000e+00,\n 0.0000e+00, 1.5508e-06, 7.0261e-07, 1.2805e-05, 0.0000e+00, 8.7801e-07,\n 3.0698e-06, 7.6541e-06, 1.2016e-06, 1.4488e-05, 1.8395e-06, 5.6581e-07,\n 8.0347e-06, 2.1262e-06, 8.9834e-06, 0.0000e+00, 6.0150e-06, 9.5571e-07,\n 2.6958e-06, 1.5369e-06, 2.4495e-06, 5.1643e-06, 0.0000e+00, 3.3057e-06,\n 3.6526e-06, 5.6777e-06, 1.3381e-06, 3.3046e-06, 1.3732e-05, 2.3733e-06,\n 1.5712e-06, 1.3732e-06, 3.3700e-06, 2.6147e-06, 1.9748e-06, 2.8955e-05,\n 2.0953e-06, 4.0025e-06, 1.7471e-06, 6.1473e-06, 2.1468e-06, 1.2286e-06,\n 2.0831e-06, 0.0000e+00, 4.3517e-06, 1.5840e-06, 3.5090e-06, 2.5349e-06,\n 0.0000e+00, 1.3479e-06, 2.2620e-06, 3.4593e-06, 1.4814e-06, 0.0000e+00,\n 1.7463e-06, 4.9050e-06, 3.3629e-06, 2.1743e-06, 1.7512e-06, 1.2027e-06,\n 2.2845e-06, 2.5982e-06, 2.5256e-06, 0.0000e+00, 1.3465e-05, 5.3985e-06,\n 3.4299e-05, 0.0000e+00, 3.5981e-06, 3.3791e-06, 1.5279e-06, 2.0698e-05,\n 4.0876e-06, 1.2055e-06, 2.9820e-06, 0.0000e+00, 3.2619e-06, 3.0809e-06,\n 1.3410e-06, 1.8103e-06, 0.0000e+00, 8.0277e-06, 6.9337e-06, 3.1618e-05,\n 0.0000e+00, 1.7259e-06, 2.1059e-06, 2.3467e-06, 1.3200e-06, 1.0695e-06,\n 1.4331e-06, 2.8842e-06, 4.4862e-06, 3.3489e-06, 1.5012e-06, 8.3877e-06,\n 0.0000e+00, 2.0618e-06, 2.9781e-06, 1.3898e-06, 3.1286e-06, 1.3878e-06,\n 1.7279e-06, 1.3143e-05, 9.5605e-06, 1.8180e-06, 0.0000e+00, 1.5118e-06,\n 1.5439e-06, 6.3052e-06, 0.0000e+00, 2.7547e-06, 2.8224e-06, 5.3679e-06,\n 0.0000e+00, 8.0370e-07, 3.4116e-06, 2.3019e-06, 1.5881e-05, 1.3941e-12,\n 2.7643e-06, 7.1301e-06, 4.4642e-06, 0.0000e+00, 1.3208e-06, 3.1793e-06,\n 2.6518e-06, 1.3474e-05, 3.5834e-06, 4.1405e-06, 4.6601e-06, 1.0663e-06,\n 0.0000e+00, 1.2501e-06, 1.5909e-06, 2.0267e-06, 2.9968e-06, 1.2197e-05,\n 2.1487e-06, 5.0041e-06, 3.9067e-06, 6.7600e-06, 5.4275e-06, 4.1113e-07,\n 0.0000e+00, 4.0366e-06, 0.0000e+00, 4.6116e-06, 1.9589e-06, 3.8835e-06,\n 0.0000e+00, 1.1407e-05, 1.9545e-06, 2.0408e-06, 2.4353e-06, 2.5531e-06,\n 1.3604e-06, 3.7194e-06, 2.1728e-06, 3.0226e-06, 2.7871e-06, 5.0060e-05,\n 3.0906e-06, 1.6874e-06, 1.7030e-06, 7.4475e-06, 1.1075e-06, 1.4357e-06,\n 5.6376e-06, 2.4602e-06, 5.8795e-07, 2.3943e-06, 1.6898e-06, 3.9350e-06,\n 1.3320e-06, 9.3772e-05, 6.5326e-06, 1.7962e-06, 2.3743e-05, 1.1356e-05,\n 0.0000e+00, 3.0254e-06, 0.0000e+00, 2.8928e-06, 2.5021e-06, 1.6733e-05,\n 2.2958e-06, 1.7304e-06, 1.2384e-06, 1.7356e-06, 1.5251e-06, 5.2012e-06,\n 9.1937e-07, 2.7369e-06, 4.7149e-06, 6.0886e-06, 1.2986e-06, 1.9755e-06,\n 1.8728e-06, 2.1142e-06, 7.0882e-06, 0.0000e+00, 1.8491e-06, 1.0484e-06,\n 1.1938e-06, 2.0145e-06, 2.6960e-06, 0.0000e+00, 2.0365e-06, 0.0000e+00,\n 1.0452e-06, 1.2986e-06, 1.2141e-06, 2.5044e-06, 1.6132e-06, 2.7218e-06,\n 5.8046e-07, 3.0269e-06, 4.5547e-06, 4.6246e-06, 2.4104e-06, 0.0000e+00,\n 0.0000e+00, 0.0000e+00, 5.5596e-06, 2.9343e-06, 3.9611e-06, 9.2980e-06,\n 0.0000e+00, 4.0905e-06, 1.7162e-06, 5.2038e-06, 1.6973e-06, 2.1099e-06,\n 7.9938e-06, 0.0000e+00, 1.0848e-06, 1.5854e-06, 2.6373e-06, 4.9100e-06,\n 4.8838e-06, 2.4190e-06, 0.0000e+00, 9.5185e-06, 1.6161e-06, 2.3988e-06,\n 2.4155e-06, 1.4677e-05, 1.8461e-06, 1.5560e-06, 2.5012e-05, 4.2590e-06,\n 4.5360e-06, 1.1903e-06, 2.2332e-05, 2.9998e-06, 0.0000e+00, 9.5235e-06,\n 2.1964e-06, 2.1998e-05, 3.8117e-06, 1.5360e-06, 3.2535e-06, 1.6469e-06,\n 1.3594e-05, 1.6153e-06, 1.5890e-06, 4.7616e-05, 2.2460e-06, 2.2821e-06,\n 4.5966e-06, 2.2691e-06, 9.4767e-07, 6.8368e-06, 0.0000e+00, 2.0890e-06,\n 1.0878e-06, 3.0496e-06, 2.8151e-06, 3.8333e-06, 0.0000e+00, 2.6668e-06,\n 2.9680e-06, 4.1962e-06, 3.8219e-06, 4.1980e-06, 1.4790e-06, 2.2214e-06,\n 6.0529e-07, 4.0122e-06, 3.4206e-06, 3.1559e-06, 3.2306e-06, 1.3328e-06,\n 2.0455e-06, 1.0213e-06, 0.0000e+00, 1.0736e-05, 2.2878e-06, 2.3551e-06,\n 2.2990e-06, 1.8971e-06, 9.8662e-06, 4.8071e-07, 2.4160e-06, 1.6085e-05,\n 8.7071e-06, 1.6537e-06, 1.5149e-06, 5.6100e-06, 0.0000e+00, 1.1063e-05,\n 1.7236e-06, 3.1627e-05, 2.3257e-06, 2.0104e-06, 5.7185e-06, 1.2679e-06,\n 1.5067e-06, 0.0000e+00, 4.4965e-06, 1.6889e-06, 4.2022e-06, 0.0000e+00,\n 5.7188e-06, 1.6746e-06, 7.2888e-07, 2.4206e-06, 4.1125e-06, 2.8357e-06,\n 1.1687e-06, 2.9821e-06, 1.0964e-06, 2.0548e-06, 3.6415e-06, 8.6103e-07,\n 0.0000e+00, 3.8917e-06, 2.6805e-06, 1.0925e-06, 0.0000e+00, 1.4987e-06,\n 5.6865e-06, 0.0000e+00, 1.4150e-06, 1.8339e-06, 7.9081e-07, 2.8615e-06,\n 1.5419e-06, 1.4409e-06, 1.8910e-06, 9.6985e-06, 9.5844e-07, 5.8880e-05,\n 1.2465e-06, 2.1684e-06, 0.0000e+00, 2.9634e-06, 2.7286e-06, 0.0000e+00,\n 7.5527e-06, 0.0000e+00, 0.0000e+00, 3.5351e-06, 0.0000e+00, 1.8776e-06,\n 2.9111e-06, 1.7746e-06, 6.2347e-06, 8.1662e-06, 1.4908e-06, 2.1540e-06,\n 3.8813e-07, 1.9198e-06, 1.2437e-05, 2.5415e-06, 1.4313e-06, 0.0000e+00,\n 4.3256e-06, 2.0781e-06, 1.2135e-06, 3.9394e-05, 0.0000e+00, 6.4707e-06,\n 1.8908e-06, 1.9048e-06, 1.3873e-05, 1.1813e-06, 5.2474e-06, 2.0233e-06,\n 1.5680e-06, 4.3256e-06, 9.9280e-06, 4.7265e-06, 2.7124e-06, 1.0915e-06,\n 0.0000e+00, 2.7607e-06, 6.8971e-06, 5.0121e-06, 1.2361e-06, 2.2047e-06,\n 2.0504e-06, 2.6066e-06, 7.2190e-06, 4.9977e-06, 3.8008e-06, 6.9689e-06,\n 0.0000e+00, 2.9724e-06, 1.3026e-06, 4.9404e-06, 9.4771e-07, 1.2594e-06,\n 1.7969e-06, 1.5809e-06, 8.6015e-06, 2.1192e-06, 1.2241e-06, 0.0000e+00,\n 2.4496e-06, 1.0682e-05])}, 44: {'step': 7160, 'exp_avg': tensor([-4.9454e-05, 1.9144e-05, 5.6052e-45, -1.2987e-04, 1.4433e-05,\n 0.0000e+00, 7.4798e-05, -1.5681e-04, -8.0725e-05, 2.6235e-05,\n -5.9702e-05, 3.0701e-06, 7.1627e-05, -2.3729e-04, 0.0000e+00,\n 1.8481e-05, 8.1764e-05, -7.5850e-07, 1.4560e-04, 1.1068e-05,\n 3.0413e-05, -3.8442e-05, 4.6541e-05, 0.0000e+00, 8.3388e-05,\n -1.5270e-05, -7.2595e-05, 1.0685e-05, 0.0000e+00, 2.7214e-06,\n 9.2899e-05, -1.0211e-04, -1.3208e-04, -2.3303e-06, -1.2978e-04,\n -2.6574e-05, -1.6205e-05, -8.1402e-05, 5.6052e-45, 2.5290e-05,\n -1.6937e-05, -3.9123e-05, 8.3049e-05, -6.1848e-05, 1.5659e-04,\n 8.4616e-05, 1.7502e-04, -1.3272e-04, -3.5982e-05, -5.1393e-06,\n 5.3111e-06, 5.6052e-45, 3.2657e-05, 8.9079e-05, 1.8909e-06,\n 1.3947e-05, -4.0644e-05, -6.7275e-05, -1.6259e-04, 0.0000e+00,\n 1.0850e-04, -1.7852e-04, -1.6276e-06, 8.0599e-05, 1.9256e-05,\n -1.1927e-05, 1.4665e-04, 1.8814e-05, 0.0000e+00, 3.2882e-05,\n 9.0885e-05, 8.2894e-05, 4.9136e-05, 1.0280e-04, 4.1447e-05,\n -5.7985e-05, -5.8358e-06, -3.0850e-05, 3.7252e-05, 1.0898e-04,\n 3.8823e-05, -7.5905e-05, -1.2071e-05, -3.9477e-05, -1.0634e-04,\n 9.7661e-05, -6.6543e-06, 9.4731e-05, -1.9458e-05, 0.0000e+00,\n 0.0000e+00, -8.1609e-05, -3.1704e-05, -4.4914e-04, 0.0000e+00,\n -2.4927e-05, -1.0982e-05, -4.6911e-05, -7.6021e-05, 1.4819e-04,\n -9.5577e-05, -7.0775e-06, -1.0266e-04, 5.8104e-05, 5.0555e-05,\n 0.0000e+00, 9.4277e-05, 1.2273e-05, -7.2250e-05, -1.8979e-05,\n 7.6213e-05, 1.3195e-04, 0.0000e+00, -5.3978e-05, 1.6433e-04,\n 2.9165e-05, 8.6854e-05, 2.3434e-06, -8.5568e-05, 3.5121e-05,\n -1.2872e-04, -3.3180e-05, -5.4187e-05, -4.4866e-05, 1.0577e-05,\n 9.7637e-05, 1.2888e-04, -1.5576e-04, 6.4116e-05, -2.0913e-05,\n 7.0963e-05, -3.5865e-05, -6.8456e-05, 0.0000e+00, 3.7230e-06,\n 7.6083e-05, 4.2422e-05, 4.3134e-05, 0.0000e+00, -1.2985e-06,\n -1.5743e-05, 1.1148e-04, 1.6042e-04, 0.0000e+00, -4.8805e-05,\n -5.8823e-05, 2.9555e-05, 1.1138e-05, 2.0100e-05, 8.3891e-05,\n 6.0606e-05, 7.7356e-05, 1.0095e-04, 0.0000e+00, 1.2229e-04,\n -9.3974e-06, -1.5548e-04, 0.0000e+00, 1.5327e-04, -9.2868e-05,\n 1.4351e-04, 5.8069e-05, -5.6555e-06, 1.6486e-04, 7.3766e-06,\n 0.0000e+00, 1.0101e-04, 9.0580e-05, -6.2354e-06, 8.5288e-06,\n 0.0000e+00, -1.4034e-06, 1.1899e-04, 1.3210e-04, 0.0000e+00,\n -6.2430e-05, 7.3909e-06, 5.0901e-05, -5.4160e-06, -3.7853e-05,\n -6.5435e-05, -4.4524e-06, 3.8043e-06, -6.1252e-05, -4.7645e-05,\n -1.5952e-06, 0.0000e+00, -1.3456e-04, -2.1165e-04, -1.2671e-04,\n -2.8345e-05, -1.8167e-05, 1.5516e-04, 1.9221e-05, 1.4289e-04,\n 6.6838e-05, 0.0000e+00, 8.2566e-05, 5.9903e-05, -1.2254e-04,\n 0.0000e+00, -5.7807e-05, -7.4314e-05, -1.9485e-06, 0.0000e+00,\n 9.7555e-06, -1.0192e-04, -9.2218e-05, -9.1848e-05, -3.1185e-10,\n -3.5595e-06, -1.3480e-05, -1.7453e-05, 0.0000e+00, 1.1067e-04,\n 4.7691e-05, -1.1522e-05, -2.3730e-04, 1.8210e-05, -2.5250e-05,\n 2.7342e-05, -3.1786e-05, 0.0000e+00, 2.4084e-05, -1.1190e-04,\n 1.6719e-05, 5.0222e-05, 6.2330e-05, 2.8262e-05, 4.3103e-05,\n 1.5192e-05, 1.4276e-05, 1.0948e-05, 5.5502e-05, 0.0000e+00,\n 1.1717e-05, 0.0000e+00, -8.2872e-05, 5.7641e-05, 4.5756e-05,\n 0.0000e+00, -7.3951e-05, 2.6523e-05, 1.8148e-04, -1.7137e-05,\n 8.6776e-05, 1.2332e-04, -4.5485e-05, -7.9795e-06, -1.4859e-05,\n 1.5164e-05, 2.3328e-04, 8.9865e-05, 1.4702e-05, 1.3850e-05,\n -5.6759e-05, 9.7365e-05, 3.4938e-05, -1.6189e-05, 9.0384e-05,\n -8.5659e-05, 1.4351e-04, 1.9256e-04, 7.8086e-05, -4.4336e-05,\n -1.1377e-04, 1.4745e-04, -1.0039e-04, -1.7161e-04, 1.4252e-04,\n 0.0000e+00, -1.1425e-05, 0.0000e+00, -1.8714e-04, 1.2660e-05,\n -1.1349e-04, 1.0618e-05, -3.6141e-05, -1.0111e-04, -2.1594e-05,\n -2.3617e-05, -6.3555e-05, 1.1438e-04, -1.9795e-05, -3.2578e-05,\n -3.1110e-05, 1.7605e-05, 9.7793e-06, -1.1695e-05, 2.1745e-05,\n -9.0514e-05, 0.0000e+00, 6.4441e-06, 2.5619e-05, 8.7247e-05,\n 1.4520e-04, 3.8760e-05, 0.0000e+00, 1.7221e-05, 0.0000e+00,\n -5.8831e-05, -7.5295e-05, 3.5189e-05, -4.5112e-05, 7.3547e-05,\n 1.6156e-04, 1.2757e-04, -4.9937e-05, -5.3478e-07, 5.8482e-05,\n -9.9389e-05, 0.0000e+00, 0.0000e+00, 0.0000e+00, 1.2540e-04,\n -5.1147e-05, -6.1338e-05, -1.8496e-05, 0.0000e+00, 4.5042e-05,\n -3.2683e-05, -1.1451e-04, 7.9106e-05, 8.1907e-05, 5.3002e-05,\n 0.0000e+00, 8.7699e-05, -4.4098e-05, -3.2089e-05, -1.1989e-04,\n -2.0026e-05, -4.5696e-05, 0.0000e+00, -4.3260e-05, -8.5932e-05,\n 1.3079e-05, 5.3568e-05, 2.7710e-05, 9.9911e-05, -6.5453e-08,\n -1.1451e-04, 7.7526e-05, -3.9310e-05, -2.6170e-06, -1.1285e-05,\n 5.1036e-05, 0.0000e+00, 3.5048e-05, -2.7218e-05, -2.8764e-05,\n -1.2599e-04, -3.9535e-05, 4.0113e-05, -1.2777e-04, 4.4260e-05,\n -2.4913e-05, 3.2799e-05, 1.6299e-04, -8.8179e-05, -3.4980e-06,\n -8.0974e-06, -6.8985e-05, -9.1765e-05, 2.5475e-04, 0.0000e+00,\n 4.4935e-05, -4.5527e-05, 9.2149e-06, -1.0643e-04, 8.1968e-05,\n 0.0000e+00, 1.7699e-04, 8.7514e-06, -2.5493e-05, 6.5577e-05,\n -1.4851e-04, -4.0236e-05, 1.1874e-05, 1.8839e-05, -1.6846e-05,\n -1.3983e-04, 2.1514e-05, 5.2231e-05, -3.0308e-05, 1.2178e-04,\n 2.9087e-05, 0.0000e+00, 5.1559e-05, 1.4832e-04, 3.6962e-05,\n -8.0114e-05, -3.9206e-05, -7.4997e-05, 3.0776e-05, 2.0904e-05,\n -3.9540e-05, -2.8363e-04, 7.7506e-05, 5.5966e-05, -2.2887e-04,\n 0.0000e+00, -2.3940e-04, -9.0769e-05, -4.8502e-05, 1.0563e-05,\n 1.9133e-05, -2.2287e-05, 2.8805e-05, 7.9450e-05, 0.0000e+00,\n 1.4604e-04, -2.2283e-05, -2.1249e-05, 0.0000e+00, -5.6520e-05,\n 3.6743e-05, -1.0277e-05, 4.7650e-05, -1.0456e-04, 4.8176e-06,\n 1.8331e-05, 5.0230e-05, -1.0159e-04, -1.2810e-04, 8.8724e-05,\n -2.1761e-05, 0.0000e+00, 9.1760e-05, -2.2720e-05, -4.2902e-05,\n 0.0000e+00, 1.9870e-05, 7.6620e-06, 0.0000e+00, -9.6662e-05,\n -1.8148e-05, -1.8787e-06, -3.5511e-05, -1.7841e-05, -4.1862e-06,\n 6.1666e-06, -2.1965e-05, 2.8880e-05, 3.7099e-04, -1.6627e-05,\n -6.0690e-05, 0.0000e+00, 1.1602e-04, 7.4878e-05, 0.0000e+00,\n 1.5739e-04, 0.0000e+00, 0.0000e+00, 6.9551e-05, 0.0000e+00,\n -7.2953e-05, 1.1631e-04, 4.7907e-06, -4.7170e-05, 7.6205e-05,\n -2.2192e-05, -1.6069e-05, 1.3995e-05, 3.3372e-05, 4.8928e-05,\n 1.0889e-04, 4.0438e-05, 0.0000e+00, 5.9142e-05, -2.5676e-05,\n -1.2764e-04, 6.8173e-04, 0.0000e+00, 1.1841e-04, -2.9164e-05,\n 1.4978e-05, 1.5187e-04, 5.6375e-05, 7.0375e-05, -1.2485e-06,\n -1.0491e-04, 1.3695e-05, -1.7533e-04, -3.1958e-05, -4.0280e-05,\n 4.4818e-05, 0.0000e+00, 1.3691e-05, -4.2685e-05, -3.2466e-05,\n -3.3346e-05, -7.3000e-05, 2.4047e-06, -1.5742e-05, 1.5366e-05,\n 7.1827e-05, -2.6046e-05, -3.0174e-05, 0.0000e+00, 7.4379e-05,\n -4.9739e-05, 6.6799e-05, -8.7937e-06, 1.6888e-04, -4.7865e-05,\n 4.3769e-05, -7.9603e-06, 7.7277e-05, 7.7407e-05, 0.0000e+00,\n 5.7162e-05, 6.8096e-05]), 'exp_avg_sq': tensor([1.8749e-06, 1.2941e-06, 3.6692e-15, 1.0852e-06, 7.7323e-07, 0.0000e+00,\n 8.9515e-07, 2.0760e-06, 9.2001e-07, 1.4942e-06, 7.0259e-07, 8.0385e-07,\n 1.5857e-06, 1.6116e-06, 0.0000e+00, 9.2184e-07, 1.4554e-06, 1.6274e-06,\n 1.3122e-06, 1.3169e-06, 7.4358e-07, 2.4108e-06, 1.5006e-06, 0.0000e+00,\n 2.0572e-06, 1.4214e-06, 9.3591e-07, 1.5228e-06, 0.0000e+00, 1.5602e-06,\n 8.2904e-07, 6.3910e-06, 2.9247e-06, 9.7269e-07, 3.7430e-06, 1.7370e-06,\n 3.6087e-06, 1.2340e-06, 1.3204e-20, 2.9395e-06, 8.7296e-07, 8.7942e-07,\n 1.0555e-06, 1.4244e-06, 1.1443e-06, 7.0274e-07, 2.9323e-06, 1.0526e-06,\n 8.5174e-07, 1.0293e-06, 7.8889e-07, 7.5690e-19, 9.0782e-07, 9.9749e-07,\n 1.4242e-06, 6.2376e-07, 6.7129e-07, 8.4478e-07, 2.9202e-06, 0.0000e+00,\n 2.9024e-06, 8.8193e-07, 7.6903e-07, 1.2337e-06, 5.3271e-07, 1.1696e-06,\n 5.4511e-07, 8.9265e-07, 0.0000e+00, 9.7671e-07, 9.3254e-07, 1.6163e-06,\n 1.2493e-06, 1.2283e-06, 1.7432e-06, 2.0578e-06, 1.3494e-06, 1.6174e-06,\n 3.1990e-06, 6.6740e-07, 1.2995e-06, 6.9521e-07, 1.1217e-07, 9.2459e-07,\n 9.2873e-07, 1.5864e-06, 1.2286e-06, 2.6612e-06, 5.0662e-06, 0.0000e+00,\n 0.0000e+00, 1.0232e-06, 3.2280e-07, 7.7094e-06, 0.0000e+00, 7.2239e-07,\n 2.0544e-06, 2.4719e-06, 9.9935e-07, 9.2445e-06, 1.8429e-06, 3.9494e-07,\n 2.7704e-06, 9.5465e-07, 1.2548e-06, 0.0000e+00, 1.7931e-06, 6.3046e-07,\n 1.7190e-06, 1.4743e-06, 1.5591e-06, 2.0939e-06, 0.0000e+00, 1.4136e-06,\n 2.1329e-06, 2.4415e-06, 9.9118e-07, 1.2360e-06, 1.4899e-06, 1.5296e-06,\n 5.8488e-07, 1.0574e-06, 1.3279e-06, 1.3924e-06, 1.0822e-06, 9.8699e-06,\n 1.4183e-06, 5.4111e-06, 8.8336e-07, 1.7323e-06, 1.4000e-06, 7.7143e-07,\n 1.0676e-06, 0.0000e+00, 2.0138e-06, 8.8300e-07, 1.1953e-06, 1.3745e-06,\n 0.0000e+00, 1.2232e-06, 9.1414e-07, 1.7686e-06, 6.8910e-07, 0.0000e+00,\n 4.2107e-07, 2.2580e-06, 1.6173e-06, 9.5094e-07, 2.0016e-06, 9.5494e-07,\n 1.5222e-06, 2.7670e-06, 1.6280e-06, 0.0000e+00, 3.8305e-06, 1.7395e-06,\n 8.5114e-06, 0.0000e+00, 1.4017e-06, 8.9301e-07, 8.8612e-07, 3.3829e-06,\n 1.2915e-06, 9.3655e-07, 7.9382e-07, 0.0000e+00, 1.4220e-06, 1.1119e-06,\n 6.8746e-07, 1.3619e-06, 0.0000e+00, 2.6704e-06, 2.7602e-06, 3.0591e-06,\n 0.0000e+00, 1.2090e-06, 1.2096e-06, 1.5233e-06, 1.0754e-06, 5.9833e-07,\n 5.8720e-07, 9.0232e-07, 1.2542e-06, 2.4326e-06, 1.1087e-06, 2.8776e-06,\n 0.0000e+00, 1.2581e-06, 2.6023e-06, 1.5893e-06, 2.2937e-06, 7.5513e-07,\n 9.8891e-07, 2.7039e-06, 4.6559e-06, 1.1132e-06, 0.0000e+00, 7.6990e-07,\n 1.0125e-06, 1.1563e-05, 0.0000e+00, 9.3384e-07, 1.7171e-06, 1.0422e-06,\n 0.0000e+00, 6.0432e-07, 1.4749e-06, 1.0879e-06, 6.5624e-06, 8.6833e-13,\n 9.4092e-07, 1.6172e-06, 3.9008e-06, 0.0000e+00, 1.0475e-06, 1.2128e-06,\n 1.0141e-06, 6.5951e-06, 2.2068e-06, 2.4536e-06, 1.2755e-06, 5.8586e-07,\n 0.0000e+00, 1.3280e-06, 1.4568e-06, 1.3028e-06, 1.1734e-06, 1.1261e-06,\n 1.1454e-06, 1.2045e-06, 2.0124e-06, 1.4116e-06, 1.8013e-06, 2.2191e-07,\n 0.0000e+00, 1.4196e-06, 0.0000e+00, 3.6012e-06, 2.1275e-06, 3.6746e-06,\n 0.0000e+00, 9.8409e-07, 8.9950e-07, 1.8480e-06, 8.8633e-07, 9.1552e-07,\n 1.1235e-06, 1.3176e-06, 1.5932e-06, 2.0480e-06, 9.9525e-07, 1.6146e-05,\n 1.6135e-06, 8.4653e-07, 5.2452e-07, 1.8517e-06, 9.8078e-07, 8.9104e-07,\n 1.3862e-06, 1.3929e-06, 3.2321e-07, 1.1053e-06, 1.0701e-06, 2.3258e-06,\n 1.0121e-06, 1.2715e-05, 2.1055e-06, 1.1877e-06, 9.2597e-06, 3.0815e-06,\n 0.0000e+00, 7.5847e-07, 0.0000e+00, 3.0062e-06, 1.0652e-06, 4.4771e-06,\n 1.1021e-06, 6.8786e-07, 5.8480e-07, 9.5305e-07, 1.1111e-06, 1.7077e-06,\n 6.7385e-07, 1.3172e-06, 1.4327e-06, 2.7993e-06, 6.7181e-07, 8.5768e-07,\n 8.5595e-07, 6.2300e-07, 5.6239e-06, 0.0000e+00, 6.7069e-07, 6.5126e-07,\n 6.2678e-07, 1.1425e-06, 9.6610e-07, 0.0000e+00, 1.4256e-06, 0.0000e+00,\n 8.4359e-07, 8.6617e-07, 8.7438e-07, 1.7714e-06, 5.8104e-07, 9.8375e-07,\n 2.9998e-07, 1.2692e-06, 1.3578e-06, 3.2002e-06, 9.5169e-07, 0.0000e+00,\n 0.0000e+00, 0.0000e+00, 1.8538e-06, 1.9294e-06, 1.3564e-06, 3.7077e-06,\n 0.0000e+00, 9.8398e-07, 1.5780e-06, 2.1837e-06, 9.9139e-07, 7.6913e-07,\n 2.4374e-06, 0.0000e+00, 5.3144e-07, 1.0868e-06, 8.5792e-07, 3.8895e-06,\n 2.1510e-06, 1.3078e-06, 0.0000e+00, 4.8235e-06, 9.0311e-07, 1.0111e-06,\n 1.5102e-06, 2.6887e-06, 5.7027e-07, 8.4988e-07, 3.1089e-06, 1.1824e-06,\n 2.4017e-06, 7.5170e-07, 3.5820e-06, 1.6989e-06, 0.0000e+00, 2.0267e-06,\n 8.6254e-07, 5.6231e-06, 2.0105e-06, 7.1438e-07, 1.6942e-06, 1.2543e-06,\n 5.2477e-06, 9.7849e-07, 7.9002e-07, 1.4636e-05, 1.8968e-06, 1.9603e-06,\n 1.0157e-06, 1.5986e-06, 6.9874e-07, 2.4090e-06, 0.0000e+00, 1.4984e-06,\n 9.0926e-07, 1.5219e-06, 8.7663e-07, 1.1531e-06, 0.0000e+00, 2.7509e-06,\n 1.4209e-06, 1.3227e-06, 1.8017e-06, 1.3401e-06, 7.5713e-07, 9.7679e-07,\n 3.2986e-07, 1.1596e-06, 1.7696e-06, 1.9963e-06, 1.6517e-06, 1.1193e-06,\n 9.8749e-07, 8.8535e-07, 0.0000e+00, 2.6688e-06, 1.2575e-06, 1.3290e-06,\n 1.2157e-06, 8.3166e-07, 5.6310e-06, 8.3160e-08, 1.4857e-06, 1.9304e-06,\n 3.6449e-06, 9.8234e-07, 1.0002e-06, 3.9349e-06, 0.0000e+00, 4.6503e-06,\n 1.2846e-06, 4.9515e-06, 1.1806e-06, 9.9208e-07, 2.0010e-06, 7.4852e-07,\n 1.2046e-06, 0.0000e+00, 1.3101e-06, 8.9588e-07, 1.8220e-06, 0.0000e+00,\n 4.8793e-06, 6.7762e-07, 5.7353e-07, 1.1508e-06, 1.7554e-06, 3.6277e-06,\n 7.1172e-07, 1.0005e-06, 5.8750e-07, 1.1741e-06, 1.4694e-06, 5.7909e-07,\n 0.0000e+00, 3.9580e-06, 1.9459e-06, 4.9178e-07, 0.0000e+00, 4.2578e-07,\n 1.3545e-06, 0.0000e+00, 7.3827e-07, 1.2845e-06, 6.2994e-07, 1.4521e-06,\n 8.0962e-07, 1.0122e-06, 1.6763e-06, 3.6377e-06, 4.5655e-07, 1.4786e-05,\n 6.4796e-07, 8.8282e-07, 0.0000e+00, 1.0289e-06, 1.9564e-06, 0.0000e+00,\n 4.5820e-06, 0.0000e+00, 0.0000e+00, 1.0577e-06, 0.0000e+00, 1.3378e-06,\n 1.2257e-06, 9.1467e-07, 5.0694e-06, 3.5707e-06, 1.0010e-06, 1.2478e-06,\n 1.7334e-07, 1.4064e-06, 2.1335e-06, 1.0483e-06, 7.7759e-07, 0.0000e+00,\n 4.9092e-06, 8.0205e-07, 8.0685e-07, 1.6514e-05, 0.0000e+00, 3.9641e-06,\n 1.2516e-06, 9.7309e-07, 4.2271e-06, 5.1609e-07, 2.0212e-06, 1.3647e-06,\n 1.0302e-06, 1.1891e-06, 3.6931e-06, 1.5070e-06, 1.0137e-06, 7.4116e-07,\n 0.0000e+00, 1.0296e-06, 1.0503e-06, 2.8710e-06, 5.3511e-07, 1.3085e-06,\n 1.2472e-06, 1.3442e-06, 3.7520e-06, 9.1878e-07, 2.4385e-06, 2.7503e-06,\n 0.0000e+00, 1.6288e-06, 6.5256e-07, 5.7734e-07, 7.3027e-07, 9.0762e-07,\n 1.3521e-06, 1.8405e-06, 3.7539e-06, 1.1808e-06, 7.6427e-07, 0.0000e+00,\n 1.2854e-06, 2.0941e-06])}, 45: {'step': 7160, 'exp_avg': tensor([[[[-4.3435e-05]],\n\n [[-2.2843e-05]],\n\n [[-5.6052e-45]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[ 2.0403e-05]],\n\n [[-3.8436e-05]]],\n\n\n [[[ 1.3702e-05]],\n\n [[ 1.5575e-05]],\n\n [[-5.6052e-45]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-7.0319e-06]],\n\n [[ 2.1273e-05]]],\n\n\n [[[-9.2098e-06]],\n\n [[ 2.3152e-05]],\n\n [[ 5.6052e-45]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-2.1647e-06]],\n\n [[ 2.4031e-05]]],\n\n\n ...,\n\n\n [[[ 2.0459e-05]],\n\n [[ 1.0721e-05]],\n\n [[ 5.6052e-45]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-2.5463e-05]],\n\n [[ 1.5661e-05]]],\n\n\n [[[-1.0035e-05]],\n\n [[-2.9416e-06]],\n\n [[ 5.6052e-45]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[ 2.8796e-05]],\n\n [[ 2.4578e-05]]],\n\n\n [[[-8.4869e-06]],\n\n [[ 7.2353e-06]],\n\n [[ 5.6052e-45]],\n\n ...,\n\n [[ 0.0000e+00]],\n\n [[-1.0697e-05]],\n\n [[ 1.7141e-05]]]]), 'exp_avg_sq': tensor([[[[1.3467e-07]],\n\n [[5.9842e-08]],\n\n [[3.8514e-23]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[1.2886e-07]],\n\n [[8.4366e-08]]],\n\n\n [[[7.3527e-08]],\n\n [[3.2094e-08]],\n\n [[4.9197e-29]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[7.9068e-08]],\n\n [[9.2680e-08]]],\n\n\n [[[6.6355e-08]],\n\n [[3.8636e-08]],\n\n [[1.5349e-21]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[1.2337e-07]],\n\n [[8.2222e-08]]],\n\n\n ...,\n\n\n [[[6.5749e-08]],\n\n [[5.7897e-08]],\n\n [[6.5136e-23]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[1.2147e-07]],\n\n [[6.7379e-08]]],\n\n\n [[[2.0124e-07]],\n\n [[1.6727e-07]],\n\n [[1.4673e-22]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[3.4885e-07]],\n\n [[3.0881e-07]]],\n\n\n [[[1.5224e-07]],\n\n [[4.3566e-08]],\n\n [[1.2401e-21]],\n\n ...,\n\n [[0.0000e+00]],\n\n [[1.2370e-07]],\n\n [[1.9151e-07]]]])}, 46: {'step': 7160, 'exp_avg': tensor([-3.6264e-05, 1.2680e-04, -1.9242e-05, -4.1937e-04, 2.1184e-04,\n -1.9660e-04, 1.0858e-04, -8.2218e-05, -5.5378e-05, 2.4125e-04,\n 2.4271e-05, -1.7907e-04, -1.0292e-04, -7.1384e-06, -3.2660e-04,\n -1.2842e-04, 3.3849e-04, 1.3732e-04, -2.0049e-04, -1.2212e-05,\n 7.0601e-05, 2.1581e-05, -2.9170e-05, -3.7777e-05, 2.6520e-04,\n -3.1639e-04, 1.4093e-04, 2.8435e-04, 2.6898e-04, 1.2748e-04,\n -2.2948e-05, -2.1607e-04, -1.1781e-04, -5.5356e-05, -9.4823e-05,\n -5.8814e-05, -3.9435e-05, -9.8608e-05, 1.3610e-04, -1.7044e-04,\n 8.7450e-05, -3.6747e-04, 1.4732e-04, 2.3299e-04, 1.2187e-04,\n -2.0091e-04, -1.1099e-04, -1.4490e-04, -5.7929e-05, 1.0370e-04,\n -1.5729e-04, -1.7179e-05, -4.3592e-06, 3.6449e-05, 1.3281e-04,\n 3.4937e-04, -7.6323e-05, -1.4808e-04, 2.3037e-04, -1.8489e-04,\n 6.0345e-05, -4.9137e-05, -2.4840e-05, -1.6807e-05, -5.8353e-04,\n 2.1712e-06, -6.5054e-05, -5.6553e-05, -2.5680e-05, 1.2802e-05,\n 7.3949e-05, -1.0908e-04, -6.6890e-05, -4.0958e-05, -4.2121e-05,\n -1.4384e-04, -7.7580e-05, 4.6360e-05, 1.1801e-05, -3.5257e-04,\n -1.8393e-04, 2.4655e-04, 5.5097e-05, 2.7195e-05, 8.6863e-05,\n -6.5131e-05, -9.3228e-05, -4.9562e-05, -1.6467e-04, -4.6411e-04,\n -3.0997e-05, 3.5984e-07, 3.3240e-04, 1.3458e-04, 1.1542e-04,\n -1.8598e-04, 2.9257e-05, 1.9419e-04, -1.9610e-04, 1.2213e-04,\n -1.7915e-04, 8.8578e-05, 1.7041e-04, 3.8283e-04, 4.3444e-04,\n 9.2830e-05, 2.9705e-04, -2.2777e-04, -1.5546e-04, 2.6040e-04,\n 4.1377e-04, -1.8815e-04, 2.3705e-04, -3.8889e-05, -3.2130e-04,\n 3.2138e-06, 1.5380e-04, 2.1754e-05, -1.4609e-04, -8.0132e-05,\n 3.1889e-05, 8.9641e-05, -2.0749e-04, 5.3842e-05, 5.8634e-05,\n 2.8851e-04, -4.4676e-05, -1.3139e-05]), 'exp_avg_sq': tensor([7.7322e-06, 8.3855e-06, 1.3143e-05, 5.3242e-06, 4.0341e-06, 7.3816e-06,\n 7.8257e-06, 1.0868e-05, 1.8423e-06, 1.0284e-05, 3.7064e-05, 3.9204e-05,\n 1.8041e-05, 8.7992e-06, 1.6459e-05, 3.6336e-06, 8.4089e-06, 3.2741e-06,\n 3.5838e-06, 6.2408e-06, 3.4702e-06, 1.1097e-05, 5.1817e-06, 1.1955e-06,\n 9.9293e-06, 1.3693e-05, 2.4967e-06, 1.9964e-06, 7.9922e-06, 1.8789e-05,\n 2.7660e-06, 1.4845e-05, 1.0620e-05, 1.5571e-05, 5.9889e-06, 1.2675e-05,\n 4.2736e-06, 4.0614e-06, 7.6153e-06, 3.6363e-06, 3.6759e-06, 1.1738e-05,\n 1.5504e-06, 5.1477e-06, 2.3634e-06, 5.8299e-06, 3.4824e-05, 1.6684e-05,\n 2.6409e-06, 6.7138e-06, 6.5005e-06, 1.8690e-05, 2.4275e-06, 2.5466e-06,\n 4.8585e-06, 1.8805e-05, 5.6064e-06, 8.4842e-06, 3.0734e-06, 3.7976e-06,\n 1.0582e-05, 2.0702e-06, 4.9795e-06, 1.9432e-06, 1.9368e-05, 6.4749e-06,\n 8.4050e-06, 2.1546e-06, 1.1056e-05, 1.4154e-06, 1.6026e-05, 4.2964e-06,\n 6.1032e-06, 8.4109e-06, 2.9268e-06, 1.0390e-05, 1.3233e-05, 3.4856e-06,\n 8.4631e-06, 1.1255e-05, 4.5434e-06, 6.2002e-06, 4.0497e-06, 2.4975e-06,\n 9.9051e-06, 4.1963e-06, 6.7321e-06, 3.1260e-06, 9.1910e-06, 2.0155e-05,\n 2.2727e-06, 2.5585e-06, 3.2762e-05, 4.0413e-06, 1.5642e-05, 1.1118e-05,\n 2.8619e-06, 6.3574e-06, 7.8577e-06, 7.6502e-07, 5.1559e-06, 3.7774e-06,\n 6.5737e-06, 2.3273e-05, 2.5567e-05, 5.2351e-06, 8.6247e-06, 2.4147e-06,\n 3.8253e-06, 8.5998e-06, 6.8013e-06, 2.7106e-06, 3.1366e-05, 6.3954e-06,\n 1.9135e-05, 1.3581e-05, 7.9647e-06, 5.7685e-06, 4.8187e-06, 5.4589e-06,\n 3.2593e-06, 6.6288e-06, 2.4686e-06, 4.5251e-06, 3.5360e-06, 9.8980e-06,\n 4.5060e-05, 4.7060e-06])}, 47: {'step': 7160, 'exp_avg': tensor([-2.9854e-05, 2.8222e-05, -3.8704e-06, -1.3548e-04, 5.9279e-05,\n -7.5501e-05, -8.6758e-06, -6.2781e-05, -1.0732e-04, 9.1835e-06,\n 4.3527e-05, 1.1670e-04, 3.5194e-05, 1.1609e-05, 5.3947e-06,\n -1.5275e-04, 9.1753e-05, -9.7854e-05, -5.2304e-05, 1.0758e-04,\n 3.1478e-05, -9.4983e-05, -8.4983e-05, -3.5110e-05, 1.0117e-04,\n -3.0559e-05, 1.6884e-04, 1.6530e-04, 7.5216e-05, 6.7843e-05,\n -4.6126e-05, -2.5321e-04, -2.2896e-05, -4.9543e-05, -7.7153e-05,\n -5.9519e-05, -6.6340e-05, -8.6798e-05, 1.9120e-04, -5.5435e-05,\n 5.4396e-05, -2.5076e-04, 7.9068e-05, 1.3270e-04, 9.7505e-05,\n -1.1690e-04, 4.4544e-06, 4.6509e-06, -3.3189e-05, 8.8308e-05,\n -9.2571e-05, -2.3962e-05, -3.3565e-05, -3.7472e-05, 8.1459e-05,\n -2.0498e-04, -4.7276e-05, -3.2616e-05, 2.2927e-04, -1.3424e-04,\n 1.6320e-04, -8.6575e-05, 1.0117e-05, 1.5919e-05, -1.4469e-05,\n 6.1239e-06, 4.1368e-05, -8.7361e-05, 2.2526e-06, -4.4451e-05,\n -7.3637e-06, -2.2033e-04, -2.6547e-05, 4.4531e-05, -2.5649e-05,\n 5.3660e-05, -1.4608e-04, 1.4065e-04, -1.3933e-04, -3.6495e-04,\n -1.1702e-04, 1.8972e-05, -7.9754e-05, -1.5917e-04, 6.8009e-05,\n -6.4927e-05, -1.6381e-04, -5.9601e-05, -1.5520e-05, 1.0792e-04,\n -3.4401e-05, -6.0860e-06, -1.4352e-04, 2.4527e-04, -3.3329e-05,\n -1.7484e-05, 2.5181e-05, -1.2851e-04, 1.4074e-04, 7.6985e-05,\n -1.5467e-04, -1.0165e-04, 5.5193e-05, 1.0862e-04, 1.0236e-04,\n -4.7743e-05, 1.3866e-05, -2.2651e-04, -1.5649e-04, 6.1234e-05,\n 2.0502e-04, -8.9192e-07, 1.3878e-04, -2.5061e-04, -6.2018e-05,\n -1.6430e-04, -2.5438e-05, 9.8756e-05, -8.3409e-05, -2.1312e-04,\n 9.4169e-05, 6.6192e-05, -1.6738e-04, -1.6902e-04, -1.2094e-05,\n 7.6819e-05, -5.5957e-05, 3.6753e-05]), 'exp_avg_sq': tensor([5.1816e-06, 2.2648e-06, 4.3514e-06, 3.7153e-06, 1.8312e-06, 2.9060e-06,\n 1.4942e-06, 5.5450e-06, 1.2601e-06, 2.6044e-07, 1.0226e-06, 2.7110e-06,\n 7.6732e-06, 7.3471e-06, 5.2774e-07, 3.0125e-06, 1.2254e-06, 5.9064e-06,\n 1.9087e-06, 1.4459e-06, 1.8891e-06, 2.1521e-06, 4.3641e-06, 7.4610e-07,\n 6.1974e-06, 3.1812e-07, 1.4274e-06, 1.3166e-06, 3.9358e-06, 7.7912e-06,\n 2.6043e-06, 7.1376e-06, 2.6052e-07, 1.2416e-05, 2.9138e-06, 4.5455e-07,\n 3.5769e-06, 2.8021e-06, 4.3913e-06, 3.1288e-06, 3.1903e-06, 5.6053e-06,\n 9.9889e-07, 3.3884e-06, 1.6423e-06, 2.1914e-06, 1.9459e-06, 4.7786e-07,\n 1.1028e-06, 3.6813e-06, 3.6789e-06, 1.8667e-06, 1.8037e-06, 1.3677e-06,\n 3.7134e-06, 9.0559e-06, 3.4645e-06, 2.0648e-07, 2.0108e-06, 4.9229e-06,\n 2.8043e-06, 1.5396e-06, 2.0431e-06, 2.6681e-06, 6.3239e-07, 1.3175e-07,\n 1.4397e-06, 2.3500e-06, 3.0790e-07, 1.7936e-06, 5.1260e-06, 2.6955e-06,\n 3.5135e-06, 1.2927e-06, 2.6969e-06, 5.0892e-06, 1.7265e-06, 2.9982e-06,\n 4.3516e-06, 9.8528e-06, 4.7216e-06, 6.2079e-06, 1.9111e-06, 2.3644e-06,\n 4.2395e-07, 1.8385e-06, 4.8100e-06, 1.6997e-06, 7.5084e-07, 8.0941e-06,\n 1.6010e-06, 1.9258e-06, 1.1667e-06, 2.6512e-06, 3.5597e-06, 1.0094e-06,\n 5.8444e-06, 3.8640e-06, 8.9805e-06, 3.2659e-07, 2.7121e-06, 5.2230e-06,\n 4.4210e-06, 1.1671e-05, 1.0281e-06, 3.5141e-06, 5.9537e-06, 1.7098e-06,\n 2.8974e-06, 6.4629e-06, 3.9705e-06, 1.1725e-06, 4.6638e-06, 4.1572e-06,\n 3.2136e-06, 5.8274e-06, 3.8883e-06, 2.2256e-06, 1.9764e-06, 3.2680e-06,\n 2.3590e-06, 3.7353e-06, 2.8251e-06, 3.6501e-06, 2.3721e-06, 4.1312e-07,\n 1.1420e-05, 3.1668e-06])}, 48: {'step': 7160, 'exp_avg': tensor([[[[ 7.8509e-06, 5.6023e-06, 6.4036e-06],\n [ 8.3690e-06, 7.4544e-06, 2.8913e-06],\n [ 3.2300e-07, -3.5909e-06, -2.5724e-07]],\n\n [[ 3.3390e-06, -4.0041e-06, -1.5919e-05],\n [ 9.9026e-06, 5.9203e-06, 2.6494e-06],\n [ 6.2887e-06, 2.0097e-05, 1.3082e-05]],\n\n [[ 4.3286e-06, -6.2478e-06, -2.2146e-06],\n [-4.7731e-06, -5.9813e-06, 5.4150e-06],\n [-3.9199e-06, -5.0171e-06, -3.6282e-06]],\n\n ...,\n\n [[-1.1759e-05, -3.4881e-06, -3.1162e-06],\n [-2.8296e-06, 5.2037e-06, -3.6538e-06],\n [ 5.9142e-06, 6.5316e-06, -3.6557e-06]],\n\n [[-3.6003e-06, -1.3747e-05, -2.3501e-05],\n [-3.4058e-06, -1.2513e-05, -1.0213e-05],\n [-6.1313e-06, 1.9216e-06, 8.9594e-06]],\n\n [[ 5.0050e-06, -2.6780e-07, 3.7251e-08],\n [ 6.2860e-07, 7.0334e-06, 4.0899e-06],\n [-7.2340e-07, 5.6672e-06, -2.4839e-07]]],\n\n\n [[[-1.2693e-05, -1.3057e-05, 5.4404e-06],\n [ 3.7865e-06, -1.1327e-05, -9.3786e-06],\n [-2.6476e-05, -5.5546e-06, -1.7166e-05]],\n\n [[-3.2916e-05, -2.9277e-05, -1.9921e-05],\n [-5.2846e-05, -5.9997e-06, -1.7023e-05],\n [ 1.6890e-06, -2.5187e-05, -1.5643e-05]],\n\n [[ 3.7195e-05, 3.0983e-05, 2.5707e-05],\n [ 2.9451e-05, 1.4938e-05, 4.8900e-05],\n [ 3.0701e-05, 4.5753e-05, 5.6787e-05]],\n\n ...,\n\n [[-2.0106e-05, -1.8808e-05, -2.1019e-06],\n [-9.3250e-06, -5.6411e-06, 1.2347e-05],\n [-1.4720e-05, -1.2139e-05, 1.2028e-05]],\n\n [[ 3.1290e-05, 2.9815e-05, 3.8871e-05],\n [ 1.0440e-05, 2.1728e-05, 2.6553e-05],\n [ 4.5811e-05, 2.7098e-05, 4.5929e-05]],\n\n [[-1.7094e-05, -2.5642e-05, -3.1231e-06],\n [-2.0099e-05, -1.9603e-05, 9.4324e-06],\n [-4.0485e-05, -2.4325e-05, 1.3462e-06]]],\n\n\n [[[ 5.1012e-05, 4.3932e-05, 3.0018e-05],\n [ 1.5662e-05, 2.2584e-05, -5.5493e-06],\n [ 8.7712e-06, 7.3478e-06, -2.7620e-06]],\n\n [[-8.4894e-06, -4.8816e-06, -1.8523e-05],\n [ 1.9401e-05, -1.0955e-05, 1.4364e-05],\n [ 1.8832e-05, 1.2635e-05, 1.6987e-05]],\n\n [[ 2.4447e-05, 1.1431e-05, 2.4848e-05],\n [ 2.3183e-05, 4.0365e-05, 3.5152e-05],\n [ 1.9781e-05, 3.3151e-05, 1.6832e-05]],\n\n ...,\n\n [[-2.3425e-05, -2.3104e-05, -1.7444e-05],\n [-1.5456e-05, -9.9807e-06, -1.1868e-05],\n [-7.7983e-06, -4.7490e-07, -2.2690e-06]],\n\n [[-1.6710e-05, -4.1857e-06, 6.6095e-06],\n [ 2.0808e-05, 8.4274e-06, 4.4823e-05],\n [ 2.5201e-05, 2.3280e-05, 4.0340e-05]],\n\n [[-2.4153e-07, -1.0744e-05, -6.1899e-06],\n [-1.4674e-05, -9.7007e-06, -2.3495e-05],\n [-1.7872e-05, 1.5176e-06, -2.0560e-05]]],\n\n\n ...,\n\n\n [[[ 6.0677e-05, 2.1011e-05, 4.2453e-05],\n [ 4.6495e-05, 3.7402e-05, 3.2722e-05],\n [ 9.5875e-05, 4.7184e-05, 4.4117e-05]],\n\n [[ 9.9696e-06, -7.9929e-06, -2.6469e-05],\n [-1.7409e-05, 7.7504e-06, -1.9500e-05],\n [-4.2247e-05, -2.2221e-05, -2.3692e-05]],\n\n [[-1.6612e-05, -8.1773e-06, -9.4727e-06],\n [-1.2094e-05, -1.4565e-05, 1.2339e-05],\n [-1.8859e-05, -4.3923e-07, 1.3812e-05]],\n\n ...,\n\n [[-1.4014e-05, -8.9556e-06, 2.1772e-06],\n [ 2.2511e-05, 3.1181e-06, 1.6410e-05],\n [ 4.5760e-05, 4.1721e-05, 4.4628e-05]],\n\n [[-2.5076e-05, -1.5759e-05, -3.9623e-05],\n [-6.9397e-05, -4.8041e-05, -6.8833e-05],\n [-8.7354e-05, -5.6274e-05, -6.3352e-05]],\n\n [[-8.8064e-06, -3.1552e-06, -8.4119e-06],\n [ 2.0935e-05, 1.5338e-06, 7.8901e-06],\n [ 2.6684e-05, 9.8628e-06, 1.7903e-05]]],\n\n\n [[[ 1.1465e-05, 3.2195e-07, 3.2769e-06],\n [ 7.3144e-06, 1.8473e-06, 1.0274e-06],\n [ 1.0558e-05, 9.7801e-06, 1.0819e-06]],\n\n [[-7.4151e-06, -8.1738e-06, -1.1517e-05],\n [-1.5205e-05, -1.0108e-05, -6.1840e-07],\n [-9.4508e-06, -1.1354e-06, -6.6763e-07]],\n\n [[ 6.6805e-06, 7.4245e-06, 3.1911e-06],\n [ 1.3041e-05, 1.3384e-05, 4.2342e-06],\n [ 7.3649e-06, 1.8198e-06, 6.1128e-06]],\n\n ...,\n\n [[-1.5595e-05, -1.2550e-05, -1.2136e-05],\n [ 1.2305e-05, 1.4713e-05, 4.5984e-06],\n [ 2.2217e-05, 2.0666e-05, 1.9126e-05]],\n\n [[-8.9267e-06, -8.8893e-07, -1.2586e-05],\n [-2.8690e-05, -2.4416e-05, -1.8254e-05],\n [-1.9142e-05, -7.4233e-06, -1.1253e-05]],\n\n [[ 5.1857e-08, -3.2907e-06, 2.4910e-06],\n [ 9.7557e-06, 8.0431e-06, 9.1850e-06],\n [ 1.1249e-05, 2.6442e-06, 8.7952e-06]]],\n\n\n [[[-4.6947e-06, -1.3795e-05, -1.4367e-05],\n [-1.6159e-05, -8.1445e-06, -3.6791e-06],\n [-9.5207e-06, -2.0370e-05, -1.1776e-05]],\n\n [[-6.3402e-06, -7.2274e-06, -1.0874e-05],\n [-7.5061e-06, -1.8112e-05, -1.9630e-05],\n [-6.7245e-06, -1.9109e-05, -1.8105e-06]],\n\n [[-3.7193e-05, -2.6208e-05, -1.7345e-05],\n [-1.2274e-05, 7.0693e-06, 2.5369e-06],\n [-1.3981e-05, 2.1103e-06, -1.0612e-05]],\n\n ...,\n\n [[-2.3280e-05, -1.4944e-05, -7.0782e-06],\n [ 3.2604e-05, 4.0680e-05, 3.5688e-05],\n [ 3.0153e-05, 3.2022e-05, 2.1342e-05]],\n\n [[-6.5513e-05, -5.4092e-05, -6.5586e-05],\n [-4.8972e-05, -5.7711e-05, -5.8362e-05],\n [-7.5877e-05, -6.3059e-05, -5.6737e-05]],\n\n [[ 1.8937e-05, 1.9750e-05, 8.4304e-07],\n [ 3.9184e-05, 4.6713e-05, 2.7566e-05],\n [ 2.9756e-05, 4.1336e-05, 1.9845e-05]]]]), 'exp_avg_sq': tensor([[[[1.1477e-08, 1.0713e-08, 1.1229e-08],\n [9.8059e-09, 1.3507e-08, 1.4864e-08],\n [1.0158e-08, 1.0475e-08, 1.0982e-08]],\n\n [[5.5303e-08, 5.4241e-08, 7.3250e-08],\n [6.0031e-08, 6.7308e-08, 5.1068e-08],\n [6.4088e-08, 6.6494e-08, 4.3325e-08]],\n\n [[4.5338e-08, 3.7940e-08, 5.6414e-08],\n [4.5069e-08, 4.8324e-08, 5.0711e-08],\n [5.2817e-08, 4.6540e-08, 4.0741e-08]],\n\n ...,\n\n [[7.5891e-08, 7.0479e-08, 6.4350e-08],\n [7.1127e-08, 6.4073e-08, 4.3826e-08],\n [7.0734e-08, 5.8378e-08, 4.7887e-08]],\n\n [[1.3183e-07, 1.1989e-07, 1.0546e-07],\n [1.1618e-07, 1.0302e-07, 7.8763e-08],\n [1.0993e-07, 8.9775e-08, 7.8346e-08]],\n\n [[1.3097e-08, 5.4772e-09, 8.2482e-09],\n [7.6117e-09, 5.5824e-09, 4.8403e-09],\n [4.0350e-09, 5.2419e-09, 3.8335e-09]]],\n\n\n [[[6.7958e-08, 6.4168e-08, 7.3235e-08],\n [6.5769e-08, 6.9175e-08, 6.3942e-08],\n [5.6713e-08, 5.3264e-08, 5.8909e-08]],\n\n [[5.9723e-08, 5.8214e-08, 5.0794e-08],\n [6.6037e-08, 6.7673e-08, 5.9569e-08],\n [8.3463e-08, 5.8014e-08, 5.3964e-08]],\n\n [[4.8754e-08, 4.7254e-08, 4.7851e-08],\n [4.4220e-08, 4.8609e-08, 4.6242e-08],\n [4.0783e-08, 4.4349e-08, 4.2950e-08]],\n\n ...,\n\n [[6.4453e-08, 4.4301e-08, 5.3576e-08],\n [5.6991e-08, 4.4610e-08, 5.0459e-08],\n [7.6191e-08, 4.8371e-08, 6.2099e-08]],\n\n [[1.1265e-07, 9.3699e-08, 7.1957e-08],\n [8.5543e-08, 1.1623e-07, 7.5760e-08],\n [8.9540e-08, 8.2369e-08, 8.6573e-08]],\n\n [[2.3867e-08, 3.0129e-08, 3.1414e-08],\n [2.7013e-08, 3.4955e-08, 2.8745e-08],\n [2.8237e-08, 3.1167e-08, 2.3396e-08]]],\n\n\n [[[9.1176e-07, 9.2392e-07, 9.4944e-07],\n [8.8257e-07, 9.0887e-07, 9.0200e-07],\n [8.9741e-07, 8.9704e-07, 9.1039e-07]],\n\n [[2.5799e-07, 3.0103e-07, 2.8790e-07],\n [2.8724e-07, 3.1366e-07, 2.8485e-07],\n [2.4202e-07, 2.7634e-07, 2.6124e-07]],\n\n [[5.1391e-07, 5.6397e-07, 5.3646e-07],\n [5.5488e-07, 5.7457e-07, 5.4567e-07],\n [5.0809e-07, 5.2816e-07, 5.4104e-07]],\n\n ...,\n\n [[3.6445e-07, 3.0436e-07, 3.2851e-07],\n [3.4038e-07, 3.0872e-07, 3.0413e-07],\n [3.7223e-07, 3.3079e-07, 3.3194e-07]],\n\n [[9.2957e-07, 1.0233e-06, 1.0797e-06],\n [8.2659e-07, 8.4816e-07, 8.7534e-07],\n [7.2700e-07, 7.0377e-07, 6.7418e-07]],\n\n [[1.5270e-07, 1.7623e-07, 1.8388e-07],\n [1.4868e-07, 1.8972e-07, 1.8655e-07],\n [1.7195e-07, 1.9386e-07, 1.9300e-07]]],\n\n\n ...,\n\n\n [[[2.0905e-07, 2.0882e-07, 2.1733e-07],\n [1.9653e-07, 2.1801e-07, 2.0267e-07],\n [2.0590e-07, 2.0966e-07, 2.0979e-07]],\n\n [[1.2290e-07, 1.2928e-07, 1.2772e-07],\n [1.1232e-07, 1.3097e-07, 9.6535e-08],\n [1.2151e-07, 1.1266e-07, 1.0861e-07]],\n\n [[1.3665e-07, 1.5235e-07, 1.5863e-07],\n [1.5029e-07, 1.5467e-07, 1.4644e-07],\n [1.8087e-07, 2.1364e-07, 1.4020e-07]],\n\n ...,\n\n [[1.4991e-07, 1.1723e-07, 1.2297e-07],\n [1.1961e-07, 9.5159e-08, 1.2741e-07],\n [1.7574e-07, 1.2177e-07, 1.6692e-07]],\n\n [[2.7944e-07, 2.8967e-07, 3.2946e-07],\n [2.9221e-07, 3.0599e-07, 2.8347e-07],\n [3.3476e-07, 3.4253e-07, 3.1952e-07]],\n\n [[3.3279e-08, 4.2057e-08, 3.1765e-08],\n [3.3181e-08, 4.1660e-08, 3.3033e-08],\n [2.8891e-08, 3.0300e-08, 2.7489e-08]]],\n\n\n [[[9.8137e-08, 9.0452e-08, 9.4542e-08],\n [9.4203e-08, 8.9621e-08, 8.6926e-08],\n [8.5013e-08, 7.8454e-08, 7.9741e-08]],\n\n [[2.7986e-08, 2.8467e-08, 2.7091e-08],\n [3.1072e-08, 3.3067e-08, 2.9706e-08],\n [2.8471e-08, 2.5529e-08, 2.2822e-08]],\n\n [[4.5696e-08, 3.6625e-08, 4.1997e-08],\n [4.1670e-08, 4.1689e-08, 3.9797e-08],\n [3.9383e-08, 3.6678e-08, 3.8132e-08]],\n\n ...,\n\n [[3.8979e-08, 3.7480e-08, 4.5274e-08],\n [2.2598e-08, 2.0314e-08, 2.6327e-08],\n [2.8142e-08, 2.7029e-08, 3.2374e-08]],\n\n [[3.5945e-08, 4.0404e-08, 3.2996e-08],\n [3.7250e-08, 3.9679e-08, 3.4890e-08],\n [2.9890e-08, 2.6677e-08, 2.8849e-08]],\n\n [[1.0392e-08, 1.2691e-08, 1.3318e-08],\n [1.2590e-08, 1.6328e-08, 1.4757e-08],\n [1.1329e-08, 1.3398e-08, 1.1624e-08]]],\n\n\n [[[2.0034e-07, 2.0839e-07, 2.0849e-07],\n [2.0315e-07, 2.1658e-07, 2.0694e-07],\n [1.9282e-07, 1.9483e-07, 2.1302e-07]],\n\n [[1.0556e-07, 9.7682e-08, 9.2018e-08],\n [1.1490e-07, 1.0727e-07, 8.2946e-08],\n [9.5322e-08, 9.4036e-08, 7.5394e-08]],\n\n [[1.6254e-07, 1.5099e-07, 1.5833e-07],\n [1.4672e-07, 1.4329e-07, 1.4089e-07],\n [1.4048e-07, 1.3099e-07, 1.3187e-07]],\n\n ...,\n\n [[1.3504e-07, 9.2294e-08, 9.4796e-08],\n [8.4613e-08, 7.9305e-08, 7.5953e-08],\n [1.0741e-07, 1.0194e-07, 7.3493e-08]],\n\n [[2.7750e-07, 2.5668e-07, 2.3320e-07],\n [2.6515e-07, 2.4400e-07, 2.1989e-07],\n [2.6966e-07, 2.5024e-07, 2.2870e-07]],\n\n [[4.9448e-08, 6.9472e-08, 5.8151e-08],\n [9.0162e-08, 7.5783e-08, 7.2855e-08],\n [5.7719e-08, 6.0583e-08, 6.5783e-08]]]])}, 49: {'step': 7160, 'exp_avg': tensor([ 1.9423e-04, 4.8323e-04, 2.8682e-04, -5.1357e-04, -1.7774e-05,\n -9.8501e-05, -8.0602e-05, -3.0427e-04, 1.2847e-04, 1.4973e-04,\n 1.0833e-04, -1.8775e-04, -2.3771e-06, 4.7504e-06, 4.0525e-04,\n -1.2450e-04, 2.5381e-04, 1.0659e-04, 1.2587e-04, 9.8345e-05,\n -1.0655e-04, 2.0403e-04, -1.5720e-04, 5.6381e-05, 2.8907e-05,\n -1.0628e-04, -6.5355e-05, -2.3445e-04, -2.1202e-04, 2.7044e-04,\n -9.1963e-04, -1.3714e-04, -2.1194e-04, -8.0860e-05, -6.8907e-05,\n 2.7304e-04, 3.0414e-05, -4.4617e-04, 1.8199e-05, 1.5955e-04,\n 1.1319e-04, 8.1711e-06, 7.8760e-05, -1.3647e-04, -5.8959e-06,\n -1.8644e-04, 4.2481e-05, 9.2375e-05, -3.3515e-04, -1.6776e-04,\n 1.2187e-04, -3.6134e-06, -2.1822e-05, 4.5260e-05, -2.0823e-05,\n 2.5421e-05, -1.4518e-05, 1.3171e-04, -4.5207e-05, 6.3566e-04,\n 3.9413e-06, 8.0255e-05, 5.8201e-05, -1.8092e-04, -1.3024e-04,\n -2.9793e-04, 1.9696e-04, -2.3855e-04, 6.1810e-06, 7.4102e-05,\n -2.0161e-04, 4.8107e-04, -2.4813e-04, 7.2047e-04, 2.2885e-06,\n 2.7046e-05, -9.6360e-05, 3.3748e-04, -2.5642e-04, -1.9826e-04,\n -3.2318e-04, 3.9839e-05, 5.2496e-04, -2.1128e-04, -6.2798e-05,\n 6.1061e-05, -1.3210e-04, -3.7997e-04, 2.0155e-04, -3.0020e-04,\n -5.1375e-05, 1.4059e-05, -8.8787e-04, 1.5541e-04, -3.0855e-05,\n -5.5671e-05, -2.0470e-04, 2.0481e-07, 2.5185e-05, 7.5310e-05,\n -1.1588e-04, 1.9865e-04, -7.8849e-05, 1.6800e-04, -1.9116e-04,\n 4.9059e-04, 2.8999e-04, 1.9288e-04, 2.3677e-04, 3.0594e-05,\n 2.4834e-04, 8.9287e-05, -2.5152e-04, 6.4735e-05, -1.9360e-04,\n -2.8872e-05, 1.1713e-04, -2.4417e-04, 1.6932e-04, 2.6014e-04,\n -2.3547e-04, 5.2228e-05, -9.3485e-05, 1.4453e-04, 9.0499e-07,\n -1.4886e-05, -7.9212e-05, 7.9215e-05]), 'exp_avg_sq': tensor([5.9237e-06, 9.8532e-06, 1.6192e-05, 1.2712e-05, 6.1741e-06, 6.1858e-06,\n 5.1852e-06, 9.4188e-06, 3.5211e-06, 4.8488e-06, 4.7965e-06, 3.9524e-06,\n 6.2830e-06, 2.9645e-06, 7.0771e-06, 7.5853e-06, 1.1030e-05, 3.1086e-06,\n 1.0319e-05, 1.3859e-05, 1.2131e-05, 5.9784e-06, 8.7834e-06, 3.5944e-06,\n 1.0836e-05, 1.0343e-05, 3.9537e-06, 1.5858e-05, 3.9373e-06, 1.3587e-05,\n 4.6176e-05, 2.2437e-05, 4.5133e-06, 2.5820e-05, 3.8840e-06, 7.4011e-06,\n 2.2503e-06, 1.0736e-05, 4.7557e-06, 5.3772e-06, 1.2427e-05, 3.4965e-06,\n 6.2379e-06, 6.5876e-06, 1.2274e-06, 1.8911e-05, 1.0075e-05, 1.4006e-05,\n 2.2534e-05, 5.5527e-06, 5.7130e-06, 5.7646e-06, 1.8968e-05, 1.7349e-05,\n 4.4283e-06, 6.7834e-06, 9.6109e-06, 4.8839e-06, 5.3619e-06, 1.0058e-05,\n 9.7935e-06, 9.1980e-06, 3.9168e-06, 3.2717e-06, 9.0558e-06, 6.2793e-06,\n 1.0372e-05, 5.5509e-06, 1.5876e-05, 6.3472e-06, 1.7011e-05, 7.9886e-06,\n 7.3564e-06, 2.0449e-05, 9.7165e-06, 5.8238e-06, 4.1747e-06, 9.0499e-06,\n 4.2251e-06, 1.0981e-05, 1.1869e-05, 3.0044e-06, 1.8420e-05, 1.4033e-05,\n 2.8728e-06, 9.5699e-06, 5.9586e-06, 1.8327e-05, 1.2389e-05, 1.4132e-05,\n 3.9050e-06, 2.8179e-06, 2.0300e-05, 1.2426e-05, 1.0137e-05, 1.3470e-05,\n 3.9460e-06, 7.4066e-06, 8.1320e-06, 3.2494e-06, 8.8980e-06, 7.5070e-06,\n 3.6395e-06, 4.4913e-06, 5.0276e-06, 1.0808e-05, 1.0842e-05, 7.1243e-06,\n 2.2278e-06, 4.4744e-06, 4.6498e-06, 7.5889e-06, 2.7257e-06, 4.2024e-06,\n 6.7113e-06, 2.6507e-06, 3.8311e-06, 8.7478e-06, 8.6190e-06, 6.5656e-06,\n 4.0259e-06, 1.2250e-05, 5.5504e-06, 9.6092e-06, 7.5700e-06, 6.2540e-06,\n 7.6885e-06, 6.8685e-06])}, 50: {'step': 7160, 'exp_avg': tensor([ 1.1477e-04, -6.6006e-05, 8.0197e-05, -2.0693e-04, 2.1065e-06,\n -1.3218e-04, 7.3892e-07, -7.0831e-04, 1.0565e-04, 2.0726e-04,\n 1.6601e-04, -2.2729e-04, 1.4915e-04, -5.3278e-05, 4.5550e-04,\n -2.0301e-04, 2.6680e-04, 1.0700e-04, 4.9636e-06, 5.4000e-06,\n -1.1430e-04, 1.3486e-04, -4.1417e-05, 1.4734e-04, -2.7046e-04,\n 1.1879e-04, -1.0316e-04, -1.6187e-05, -1.8360e-04, 1.0976e-04,\n -6.1910e-04, 2.2023e-04, -1.3258e-04, -2.3605e-04, -3.9423e-06,\n -2.5354e-05, -6.5455e-05, 4.7356e-04, 3.7264e-05, 1.5436e-04,\n -1.1005e-04, 1.2717e-04, 5.2099e-05, 1.4451e-05, 1.6842e-05,\n 7.2151e-05, -1.2996e-05, 3.6551e-05, -2.0231e-04, 5.5011e-06,\n 1.8794e-05, -9.0121e-05, 2.9099e-04, 1.4929e-05, 1.0016e-04,\n -2.2914e-06, 1.1511e-04, 1.4125e-04, 1.8774e-05, 5.9544e-04,\n 8.0917e-05, -4.2385e-05, 1.9883e-05, -1.6640e-04, -1.7232e-04,\n 1.1521e-04, 4.9325e-05, -9.5668e-05, -4.9760e-06, 7.2898e-05,\n -1.7869e-04, -4.3987e-05, -9.2327e-05, -1.2634e-05, -2.8376e-04,\n -8.4578e-05, -2.7072e-05, 3.7775e-04, 1.4171e-04, 4.8381e-05,\n -4.8037e-04, 2.3146e-04, 5.4153e-04, -4.6193e-05, -8.4690e-06,\n 2.9468e-05, -7.2574e-05, 6.0835e-05, -6.1462e-05, 3.9347e-05,\n -7.1546e-05, -1.3417e-06, -3.4373e-04, 6.7177e-05, -9.0370e-05,\n -2.4841e-04, 2.0627e-05, 8.9099e-05, -3.0912e-06, 2.9409e-05,\n 9.0462e-05, 1.2851e-04, -1.2246e-04, -1.7044e-05, -2.0362e-04,\n 1.7778e-04, 2.5025e-04, 2.6231e-04, 2.2637e-04, -6.7270e-05,\n 6.7893e-05, 1.1116e-04, -1.9929e-04, 2.2081e-05, -2.4149e-04,\n -5.7910e-05, 9.1241e-05, -2.2454e-04, -3.3012e-05, 2.6624e-04,\n -1.8050e-04, 1.0322e-04, -4.8053e-05, 1.9293e-04, 1.1958e-04,\n 3.7777e-05, -6.5174e-05, 1.3673e-04]), 'exp_avg_sq': tensor([9.8464e-06, 4.9267e-06, 1.8961e-05, 4.9870e-06, 6.5760e-06, 7.7109e-06,\n 7.8414e-06, 8.5829e-06, 3.2969e-06, 2.4339e-06, 4.2128e-06, 4.5331e-06,\n 8.8510e-06, 2.2773e-06, 8.1608e-06, 1.3989e-05, 1.1025e-05, 2.0265e-06,\n 4.1995e-06, 1.1762e-05, 4.5589e-06, 2.0906e-06, 1.0165e-05, 3.1117e-06,\n 7.4771e-06, 1.4143e-05, 2.7944e-06, 1.0414e-05, 4.6226e-06, 8.5457e-06,\n 2.5351e-05, 2.7683e-05, 1.0963e-06, 1.9946e-05, 5.7270e-06, 6.0525e-06,\n 1.8338e-06, 1.6731e-05, 1.8327e-06, 3.0975e-06, 3.3196e-06, 1.3562e-06,\n 4.1444e-06, 1.8467e-06, 8.0385e-07, 8.8160e-06, 4.9695e-06, 7.9495e-06,\n 1.4581e-05, 1.4007e-06, 1.3146e-06, 1.3850e-06, 1.4751e-05, 1.0707e-05,\n 5.8364e-06, 5.4757e-06, 6.4030e-06, 6.0321e-06, 6.0012e-06, 7.0409e-06,\n 7.1786e-06, 5.6803e-06, 2.3651e-06, 2.9563e-06, 4.6332e-06, 1.1551e-05,\n 5.5241e-07, 4.1265e-06, 1.9727e-06, 8.8837e-06, 1.3934e-05, 2.9628e-06,\n 6.4447e-06, 1.0184e-05, 8.0474e-06, 3.5869e-06, 3.6962e-06, 9.0479e-06,\n 1.0121e-05, 7.5976e-06, 1.7414e-05, 3.2169e-06, 1.7144e-05, 2.0867e-05,\n 1.7278e-06, 5.2420e-06, 4.0208e-06, 2.4273e-05, 5.3712e-06, 1.2898e-05,\n 2.8501e-06, 3.9527e-06, 2.1069e-05, 6.7407e-06, 5.0059e-06, 2.1207e-05,\n 3.6599e-06, 1.1389e-06, 3.2754e-06, 2.8369e-06, 9.6194e-06, 9.6293e-06,\n 2.8957e-06, 1.1222e-06, 3.8429e-06, 5.9982e-06, 1.4907e-05, 1.3221e-05,\n 3.7931e-06, 2.7461e-06, 2.0599e-06, 2.1134e-06, 2.0406e-06, 1.3118e-06,\n 3.3680e-06, 2.3311e-06, 7.1380e-07, 6.5489e-06, 8.9416e-06, 7.4742e-06,\n 2.5663e-06, 1.0590e-05, 3.8196e-06, 4.6655e-06, 9.5690e-06, 5.1419e-06,\n 3.6416e-06, 4.0723e-06])}, 51: {'step': 7160, 'exp_avg': tensor([[[[ 2.2171e-05]],\n\n [[-1.7020e-05]],\n\n [[ 1.8207e-06]],\n\n ...,\n\n [[-4.1987e-05]],\n\n [[-3.2379e-05]],\n\n [[-4.3866e-05]]],\n\n\n [[[ 3.6498e-06]],\n\n [[-1.0013e-05]],\n\n [[-7.5393e-06]],\n\n ...,\n\n [[-3.9972e-07]],\n\n [[-7.9203e-06]],\n\n [[-1.3738e-06]]],\n\n\n [[[-3.3185e-05]],\n\n [[-2.0142e-05]],\n\n [[-2.6757e-05]],\n\n ...,\n\n [[ 6.1646e-05]],\n\n [[-1.2058e-06]],\n\n [[ 4.2904e-06]]],\n\n\n ...,\n\n\n [[[ 6.1597e-05]],\n\n [[-1.6036e-04]],\n\n [[ 8.8198e-05]],\n\n ...,\n\n [[-1.1792e-04]],\n\n [[-7.4972e-06]],\n\n [[-2.2730e-06]]],\n\n\n [[[ 3.6215e-07]],\n\n [[-3.4042e-06]],\n\n [[ 2.0662e-06]],\n\n ...,\n\n [[-3.1762e-06]],\n\n [[-1.1966e-06]],\n\n [[-1.2789e-06]]],\n\n\n [[[ 3.4641e-05]],\n\n [[-3.2639e-05]],\n\n [[-3.5712e-05]],\n\n ...,\n\n [[ 3.6572e-05]],\n\n [[-3.7472e-05]],\n\n [[ 6.1691e-05]]]]), 'exp_avg_sq': tensor([[[[1.2900e-07]],\n\n [[2.7075e-07]],\n\n [[3.4947e-07]],\n\n ...,\n\n [[1.5539e-07]],\n\n [[1.5891e-07]],\n\n [[6.8632e-07]]],\n\n\n [[[2.5099e-09]],\n\n [[4.3278e-09]],\n\n [[4.2746e-09]],\n\n ...,\n\n [[2.2464e-09]],\n\n [[2.4338e-09]],\n\n [[6.1528e-09]]],\n\n\n [[[9.4596e-07]],\n\n [[8.9956e-07]],\n\n [[1.7372e-07]],\n\n ...,\n\n [[3.0259e-07]],\n\n [[4.4874e-07]],\n\n [[5.9637e-07]]],\n\n\n ...,\n\n\n [[[1.3099e-06]],\n\n [[3.3423e-06]],\n\n [[2.7798e-06]],\n\n ...,\n\n [[1.2200e-06]],\n\n [[2.0172e-06]],\n\n [[2.0957e-06]]],\n\n\n [[[1.6977e-09]],\n\n [[2.3414e-09]],\n\n [[2.9021e-09]],\n\n ...,\n\n [[1.2106e-09]],\n\n [[1.2713e-09]],\n\n [[2.4770e-09]]],\n\n\n [[[3.1967e-07]],\n\n [[7.4016e-07]],\n\n [[2.4760e-07]],\n\n ...,\n\n [[2.2271e-07]],\n\n [[3.2928e-07]],\n\n [[2.6743e-07]]]])}, 52: {'step': 7160, 'exp_avg': tensor([-1.7150e-04, -2.5371e-05, 1.3667e-04, -7.0997e-05, 4.4292e-05,\n -4.1982e-04, -3.3992e-05, 7.9082e-05, -1.5029e-05, -2.1395e-04,\n -3.9378e-05, 8.6765e-05, 1.8685e-04, 2.1064e-04, 1.4346e-04,\n -2.4980e-05, 5.7568e-04, -1.2728e-05, 2.0718e-04, 1.7213e-04,\n -8.3377e-05, -1.5616e-04, -5.4690e-05, -7.1833e-04, -1.2063e-04,\n -4.6239e-05, -1.9181e-05, -2.2096e-04, -1.5070e-04, -1.5770e-04,\n 9.0851e-06, 3.6292e-05, -1.1871e-04, 5.9965e-05, 1.4515e-04,\n -1.3342e-05, -1.2079e-04, -7.3313e-05, 0.0000e+00, 1.0208e-04,\n -2.2405e-04, -1.2050e-06, -1.6992e-05, -1.6764e-05, 1.3485e-04,\n -1.0866e-04, 1.4318e-04, 2.9849e-05, 4.3554e-05, 9.1690e-05,\n -1.3661e-04, 0.0000e+00, -6.9197e-05, 1.5645e-04, 9.5833e-06,\n -3.7406e-05, 1.9051e-05, -8.3245e-05, -2.5359e-05, -6.8715e-05,\n 2.1429e-04, -1.0970e-04, 5.2795e-05, 8.4333e-05, -3.0560e-05,\n -4.1705e-05, -1.0328e-04, 5.0573e-05, 0.0000e+00, -9.6180e-06,\n 3.6725e-04, -1.0437e-05, 2.2293e-05, 4.3645e-04, 9.1018e-05,\n 1.6810e-04, -7.3297e-05, -6.1148e-05, 8.2540e-05, 7.8106e-05,\n -1.1657e-04, -2.0360e-05, -6.7238e-05, -1.3791e-04, -1.2711e-04,\n -6.7794e-05, 8.7575e-05, 1.0605e-04, 3.6458e-04, -9.4468e-05,\n 4.3039e-05, -1.2521e-04, -6.5818e-05, -1.0217e-04, 4.6903e-05,\n -2.6831e-05, -1.0610e-05, -5.8244e-06, 3.2270e-05, -1.3678e-04,\n -6.6287e-05, -6.8807e-05, -5.0875e-05, 8.4199e-06, 2.0571e-05,\n -6.2547e-05, -2.0484e-04, -1.6659e-05, 1.0688e-05, -1.5666e-04,\n 1.5091e-04, -7.4993e-05, 9.2311e-05, -4.4197e-05, 4.6425e-04,\n 1.1764e-04, 3.3321e-05, 1.4493e-05, 1.4390e-04, -2.9065e-04,\n 5.6626e-05, 8.9130e-05, 2.0567e-04, 4.1354e-05, 4.7808e-05,\n 1.1197e-04, 6.6468e-06, 1.0436e-04, 4.4752e-05, 1.7507e-04,\n 1.5155e-04, -6.3330e-05, 5.4744e-05, 2.3587e-04, 2.3021e-04,\n 3.8118e-05, 3.1084e-04, 6.6918e-05, -5.9645e-06, 1.3166e-04,\n 2.1202e-04, 1.3619e-04, -1.8565e-04, 4.3165e-05, 3.5493e-05,\n -5.0394e-05, -1.3863e-05, 8.9113e-05, 9.9507e-05, 4.1936e-05,\n -7.0446e-05, -1.1319e-05, 2.2283e-04, -6.7900e-05, 2.3078e-04,\n 1.9982e-04, 1.2633e-05, 3.6538e-06, 1.3899e-04, 4.7453e-05,\n 1.8409e-04, 3.9461e-04, -1.1700e-04, 1.8296e-04, 1.8789e-05,\n -1.8113e-04, 1.8037e-04, -8.9065e-06, -4.5299e-05, 1.1649e-04,\n -7.9092e-05, 3.0798e-04, -1.1730e-04, 1.4457e-04, 1.5294e-04,\n 7.6416e-05, 2.8493e-05, -1.5492e-04, -2.2882e-06, -1.1912e-04,\n -5.8230e-05, 1.9173e-04, -8.0163e-05, 1.7598e-04, 2.7644e-05,\n 9.1260e-05, -2.3902e-04, -2.2677e-04, -1.9253e-04, 1.0486e-04,\n 1.5456e-04, -3.4777e-05, -1.3849e-05, 2.1126e-04, 2.1290e-04,\n 1.9275e-04, -1.1099e-04, 1.1415e-04, 5.0640e-05, 1.5722e-04,\n 0.0000e+00, -1.0705e-05, -7.1367e-05, 8.4604e-05, 1.0360e-04,\n 1.0170e-04, 2.6282e-05, 1.9768e-04, -5.7910e-05, -4.1777e-05,\n 3.1469e-05, -4.3159e-05, 3.3062e-04, -6.2199e-05, -2.4658e-05,\n 3.7614e-05, 7.0215e-06, -2.4085e-04, 1.7889e-04, -1.3342e-04,\n 7.3346e-05, -1.0271e-04, 1.0192e-04, -1.1380e-05, -7.6978e-05,\n 1.2158e-04, -1.1194e-04, 4.8560e-05, -1.2884e-05, -9.6602e-05,\n 3.2364e-05, -9.6587e-05, -2.7891e-05, -5.1172e-06, -7.1990e-05,\n 3.8555e-05, 7.5837e-05, 4.8844e-05, 1.9505e-04, -3.9872e-05,\n -3.1158e-04, 8.9306e-05, -2.7762e-04, -1.9595e-04, -6.6914e-05,\n -8.4464e-05, 1.5333e-04, 1.8615e-04, -8.0218e-05, 2.9335e-05,\n -2.7653e-05, 6.8173e-04, 1.2326e-04, -4.9809e-05, -7.0297e-06,\n 2.3958e-06, 2.1509e-05, 1.2952e-04, 1.6479e-04, 7.5183e-05,\n -6.5835e-05, 1.6130e-04, 3.0559e-05, -5.1395e-06, -3.5558e-05,\n -3.3542e-04, 3.1122e-04, 2.2976e-04, -8.0353e-05, -1.1090e-04,\n -5.8823e-05, 6.0819e-05, -6.0769e-04, -1.8191e-04, -9.0160e-05,\n 2.7301e-04, 9.4857e-05, -1.2047e-04, -3.1040e-06, -2.4810e-05,\n 2.1709e-05, 5.6262e-05, 1.7158e-04, -9.1683e-06, 1.1235e-04,\n 2.6989e-04, -4.0348e-05, -1.2197e-04, 2.7594e-05, 1.7089e-04,\n 2.1266e-05, 1.5229e-04, -8.3421e-05, -2.9251e-05, 2.3075e-05,\n 6.1114e-05, 6.9301e-05, 6.1925e-04, 9.8407e-05, 0.0000e+00,\n 5.8238e-05, 1.1233e-04, 5.5614e-05, 1.8931e-05, -1.0028e-06,\n 9.4966e-06, -8.7666e-05, 3.5666e-05, -8.2726e-05, 3.3218e-06,\n 9.9655e-06, -9.4949e-05, 1.1646e-04, 2.0719e-05, 6.9357e-05,\n -3.8195e-05, 5.6156e-05, 4.7307e-05, 6.8346e-04, 6.1639e-05,\n -8.9889e-05, -6.1468e-05, 2.2952e-05, 1.4745e-04, 6.2332e-05,\n -1.3969e-04, 1.8950e-05, 2.4450e-04, 1.6070e-04, -5.5441e-04,\n -1.4813e-04, -2.7007e-04, -3.9902e-04, 6.9459e-06, -1.1976e-04,\n 2.4535e-04, -1.8358e-05, 9.8394e-05, -3.6025e-05, -1.3793e-04,\n 2.7905e-04, 2.6891e-04, 6.9315e-05, 4.7145e-05, 1.2164e-04,\n -6.6744e-05, -2.0753e-04, 1.2356e-04, 2.6362e-05, 4.0027e-04,\n -2.5542e-04, -1.1565e-04, -8.7514e-06, 6.0418e-06, 1.4057e-04,\n -1.9018e-05, -2.3101e-06, 1.0943e-03, 1.5398e-04, 2.6423e-05,\n 1.0058e-04, 3.5766e-05, 1.3961e-04, 5.1964e-05, 2.8426e-05,\n 8.4077e-07, 2.2341e-05, -5.7273e-05, -3.8882e-06, -3.4991e-05,\n -3.2607e-04, 1.6552e-04, -7.0570e-05, -2.5345e-05, -3.1349e-05,\n -5.7686e-05, 9.2703e-06, -8.8729e-05, 3.3521e-05, 4.2518e-05,\n -1.1332e-04, -1.0243e-04, 2.6781e-05, 4.5463e-05, -5.7651e-05,\n -2.1101e-05, -1.6471e-05, 4.5599e-06, -3.4399e-05, -9.1968e-05,\n 2.4600e-04, 1.7106e-04, 4.0297e-05, 1.6521e-05, 9.2081e-05,\n 2.8438e-05, -1.9812e-04, -5.2165e-05, 2.2950e-05, -5.9552e-04,\n 7.1598e-05, -4.9000e-04, 1.2133e-04, -8.6428e-05, 1.0731e-04,\n 9.9593e-05, -1.9349e-04, -1.1101e-05, 2.9869e-04, 3.5024e-05,\n -4.2527e-05, 9.3480e-05, -1.3016e-04, -3.7117e-05, -2.9352e-04,\n 5.8046e-05, 5.9881e-05, 1.1713e-04, -5.5241e-05, 8.7826e-05,\n 6.1167e-05, -1.2915e-04, -1.2499e-04, 9.5428e-05, -2.9885e-05,\n 1.1838e-04, -8.4385e-05, 9.7858e-05, 2.8742e-04, -1.1840e-04,\n 2.0309e-04, -4.4977e-05, -8.6353e-05, 8.6799e-05, -7.7604e-05,\n -1.9875e-05, 4.9840e-05, -1.0053e-04, -5.8162e-05, 1.1143e-04,\n 1.3601e-04, 8.1973e-05, 8.7670e-05, 5.3726e-04, 2.3127e-04,\n -1.3580e-04, -4.7447e-05, -6.4777e-05, 1.1967e-04, 1.9672e-04,\n 7.0657e-04, 0.0000e+00, -2.9996e-04, -1.0550e-04, -6.6295e-05,\n -4.7187e-05, -3.8584e-04, -2.6533e-04, 3.8795e-05, -1.6709e-04,\n -1.7966e-04, 8.5239e-05, -1.3859e-05, 7.6810e-05, -1.1988e-04,\n -1.3454e-04, 8.2576e-05, -9.1171e-06, 5.5277e-05, 3.6318e-05,\n 7.0300e-05, 6.3444e-04, -5.2967e-05, 2.3793e-04, -6.8516e-05,\n 1.0330e-04, -2.8172e-05, 2.3945e-05, -9.3943e-05, 1.3310e-04,\n -1.2340e-04, -2.7208e-06, 8.5549e-05, -2.0788e-05, 7.4351e-07,\n 7.1164e-05, -2.4076e-05, 8.0363e-05, 1.4347e-04, 5.6349e-06,\n 2.8733e-05, 4.3993e-05, 1.6991e-04, -6.1297e-05, 5.8730e-04,\n 5.6763e-06, 3.0342e-05, 2.0273e-05, -1.2379e-05, 1.9673e-04,\n 8.7649e-06, 6.5060e-05, 1.4585e-05, 7.6196e-05, -2.0150e-05,\n 3.3594e-05, 9.3811e-05, 1.4469e-04, -5.9228e-05, -3.3172e-04,\n 2.7146e-05, 1.1126e-04]), 'exp_avg_sq': tensor([4.6697e-06, 1.8891e-06, 4.6995e-06, 3.4441e-06, 2.0883e-06, 2.0087e-05,\n 2.3566e-06, 3.2268e-06, 7.3244e-07, 2.3698e-06, 1.4666e-06, 2.5184e-06,\n 2.3259e-06, 5.5914e-06, 1.9158e-06, 1.4627e-06, 6.2902e-06, 2.7223e-06,\n 2.8794e-06, 2.5503e-06, 1.8746e-06, 4.3343e-06, 2.5189e-06, 1.1512e-05,\n 2.9856e-06, 2.8715e-06, 2.4331e-06, 4.3629e-06, 3.3739e-06, 3.3833e-06,\n 1.1642e-06, 2.9893e-06, 3.8262e-06, 1.9440e-06, 1.5092e-05, 2.3855e-06,\n 1.3476e-05, 2.1781e-06, 0.0000e+00, 7.4194e-06, 3.1695e-06, 1.5189e-06,\n 2.5444e-06, 1.1518e-06, 3.2639e-06, 1.3190e-06, 6.1529e-06, 1.1411e-06,\n 1.5068e-06, 1.9683e-06, 1.7257e-06, 0.0000e+00, 5.9280e-06, 2.6811e-06,\n 1.8753e-06, 1.4215e-06, 2.0568e-06, 1.6194e-06, 2.9105e-06, 2.3774e-06,\n 2.9500e-06, 1.1260e-06, 1.7405e-06, 6.0267e-07, 1.1634e-06, 3.5279e-06,\n 5.9942e-07, 3.3576e-06, 0.0000e+00, 1.2655e-06, 4.1562e-06, 6.4912e-06,\n 2.0027e-06, 4.3731e-06, 4.3479e-06, 3.3785e-06, 2.6870e-06, 5.1643e-06,\n 1.3941e-05, 8.3702e-07, 2.1649e-06, 1.7302e-06, 1.4087e-06, 1.5261e-06,\n 2.0856e-06, 4.4268e-06, 2.7841e-06, 8.1755e-06, 2.7846e-05, 2.2077e-06,\n 2.9339e-06, 2.1378e-06, 5.7650e-07, 1.0382e-05, 3.6067e-06, 7.8951e-07,\n 2.2180e-06, 6.6391e-06, 3.2862e-06, 1.3839e-05, 1.6944e-06, 4.2273e-07,\n 1.3969e-05, 1.2592e-06, 8.3762e-06, 4.3666e-06, 2.8583e-06, 2.0939e-06,\n 4.6108e-06, 3.7994e-06, 4.2024e-06, 5.7149e-06, 2.8290e-06, 5.6579e-06,\n 8.2099e-06, 8.6825e-06, 1.5057e-06, 1.6983e-06, 4.3228e-06, 3.9539e-06,\n 1.4476e-06, 3.8150e-06, 5.9136e-06, 1.8249e-06, 7.6259e-07, 1.5066e-05,\n 3.1455e-06, 4.8572e-06, 2.8069e-06, 2.9107e-06, 3.3908e-06, 1.6506e-06,\n 3.1657e-06, 3.6017e-06, 3.4662e-06, 1.4610e-06, 4.1110e-06, 2.2363e-06,\n 5.6417e-06, 2.8462e-06, 4.4477e-06, 5.1227e-06, 3.7411e-06, 3.2649e-06,\n 2.7688e-06, 1.5785e-06, 1.1118e-06, 2.8716e-06, 1.1969e-06, 1.2365e-06,\n 3.1531e-06, 5.0560e-06, 3.4767e-06, 1.6547e-06, 5.0827e-06, 4.8838e-06,\n 1.0822e-05, 3.5750e-06, 6.9424e-06, 2.4978e-06, 6.8892e-06, 8.5679e-06,\n 5.3785e-06, 1.2709e-06, 2.1054e-06, 5.9703e-06, 2.1341e-06, 2.0326e-06,\n 9.4747e-07, 4.2759e-06, 1.6943e-05, 7.3504e-06, 1.0975e-05, 9.7559e-06,\n 1.6095e-06, 1.9149e-06, 1.8522e-06, 2.1966e-06, 1.1786e-06, 1.1709e-06,\n 1.5344e-06, 1.9280e-06, 3.5078e-06, 3.2880e-06, 1.3766e-06, 6.2936e-06,\n 5.8834e-06, 4.0154e-06, 5.3110e-06, 2.8690e-06, 5.2159e-06, 2.0627e-06,\n 1.4218e-06, 4.7462e-06, 1.6252e-05, 3.1790e-06, 2.8142e-06, 1.8070e-06,\n 3.1542e-06, 7.7622e-06, 0.0000e+00, 3.1734e-06, 3.6457e-06, 3.8260e-06,\n 4.4820e-06, 8.9219e-07, 7.3675e-06, 3.1613e-06, 6.2248e-06, 9.0133e-07,\n 2.3997e-06, 3.3077e-06, 8.3640e-06, 9.8700e-06, 1.8742e-06, 2.8614e-06,\n 1.7389e-06, 7.7909e-06, 3.2079e-06, 4.6996e-06, 2.2369e-06, 5.9312e-06,\n 1.8844e-06, 1.5065e-06, 4.3118e-06, 1.4658e-06, 3.1323e-06, 5.7453e-06,\n 3.7904e-06, 4.3646e-06, 4.2225e-06, 5.5397e-06, 3.2205e-06, 1.9564e-06,\n 1.5569e-05, 3.5434e-06, 3.1242e-06, 3.4129e-06, 2.6404e-06, 2.7440e-06,\n 1.2058e-05, 6.8248e-06, 5.4173e-06, 3.3070e-06, 2.2561e-06, 5.9338e-07,\n 2.3757e-06, 2.7105e-06, 1.7773e-06, 4.1097e-06, 4.4411e-06, 4.2295e-05,\n 2.6934e-06, 1.0479e-06, 2.3198e-06, 2.3915e-06, 1.1101e-06, 2.2006e-06,\n 6.4589e-06, 4.9095e-06, 4.0445e-07, 2.6074e-06, 2.3896e-06, 4.8104e-06,\n 2.0171e-06, 2.7663e-05, 3.9889e-06, 7.8371e-07, 2.6268e-06, 4.4521e-06,\n 4.6037e-06, 2.5739e-06, 9.7363e-06, 1.0024e-05, 2.7126e-06, 1.4585e-05,\n 1.3669e-06, 1.5158e-06, 1.2174e-06, 1.5749e-06, 1.0625e-06, 1.6862e-06,\n 9.0407e-07, 1.8330e-06, 3.7244e-06, 1.0504e-05, 1.9953e-06, 3.0505e-06,\n 2.1533e-06, 3.7429e-06, 1.1530e-05, 4.9288e-06, 9.2646e-07, 6.6302e-07,\n 9.7704e-07, 2.1818e-06, 2.8571e-06, 3.9645e-06, 3.9717e-06, 0.0000e+00,\n 1.5746e-06, 6.0822e-07, 1.5176e-06, 3.2613e-06, 8.7223e-07, 2.5019e-06,\n 9.2540e-07, 2.6801e-06, 4.9007e-06, 6.6162e-07, 2.3124e-06, 4.6210e-06,\n 4.5088e-06, 8.0919e-06, 4.2315e-06, 3.8355e-06, 5.2885e-06, 4.6632e-06,\n 9.8424e-06, 3.5996e-06, 1.7200e-06, 7.2524e-06, 4.0164e-06, 1.5399e-06,\n 3.5029e-06, 4.8985e-06, 1.5691e-06, 1.6503e-06, 1.5100e-06, 7.8904e-06,\n 3.0344e-06, 8.2166e-06, 3.0156e-06, 6.1239e-06, 4.6000e-07, 3.1288e-06,\n 9.2693e-07, 2.5681e-06, 1.2444e-06, 1.6854e-06, 1.5586e-05, 8.2324e-06,\n 5.7463e-06, 1.4815e-06, 1.6532e-05, 4.2251e-06, 6.0606e-06, 4.2026e-06,\n 2.7804e-06, 1.3487e-05, 4.6874e-06, 3.5990e-06, 7.9961e-07, 1.2373e-06,\n 5.1007e-06, 1.5456e-06, 2.8473e-06, 7.0906e-05, 1.6594e-06, 3.1241e-06,\n 1.5212e-06, 4.9060e-06, 2.1240e-06, 3.5743e-06, 2.1576e-06, 3.9489e-06,\n 4.4091e-06, 1.6833e-06, 3.6041e-06, 2.0227e-06, 4.8442e-06, 2.1587e-06,\n 3.8465e-06, 3.0484e-06, 3.3036e-06, 1.9349e-06, 1.8693e-06, 2.1193e-06,\n 1.1201e-06, 4.1958e-06, 8.6181e-06, 6.4600e-06, 2.9152e-06, 1.5092e-06,\n 3.1143e-06, 1.9599e-06, 3.1057e-06, 1.1181e-05, 4.0933e-06, 1.1958e-06,\n 2.4263e-06, 5.2579e-06, 6.3335e-06, 1.0347e-07, 3.3351e-06, 1.2234e-05,\n 8.6054e-06, 7.3170e-07, 1.9945e-06, 9.6820e-06, 3.8882e-05, 1.7152e-05,\n 2.8001e-06, 1.8565e-06, 2.4830e-06, 1.5330e-06, 2.5738e-06, 1.6850e-06,\n 3.6630e-06, 2.2483e-06, 1.6861e-06, 3.1082e-06, 3.3860e-06, 2.1525e-06,\n 1.3783e-05, 1.3420e-06, 1.3164e-06, 1.3167e-06, 1.4578e-06, 3.4470e-06,\n 2.3665e-06, 7.6533e-06, 9.3498e-07, 1.5471e-06, 1.9650e-06, 9.0833e-07,\n 5.0110e-06, 6.0521e-06, 3.4397e-06, 1.4471e-06, 2.2530e-06, 1.9269e-06,\n 2.0612e-06, 3.5319e-06, 3.1018e-06, 1.4006e-06, 5.4806e-07, 3.1723e-06,\n 1.4644e-06, 3.2136e-06, 1.1732e-06, 3.4476e-06, 5.9502e-07, 4.3204e-05,\n 1.9652e-06, 3.2542e-06, 3.9760e-06, 1.9584e-06, 2.8840e-06, 1.6315e-06,\n 3.5138e-05, 0.0000e+00, 4.0562e-06, 3.7974e-06, 1.4320e-06, 1.0805e-06,\n 6.7773e-06, 3.0327e-06, 1.4629e-05, 5.9415e-06, 1.3419e-06, 2.6721e-06,\n 5.7381e-07, 3.9858e-06, 6.6373e-06, 2.3113e-06, 1.6764e-06, 5.2068e-06,\n 7.6704e-06, 3.5490e-06, 1.0979e-06, 3.0930e-05, 1.7724e-05, 6.7736e-06,\n 1.0271e-06, 1.7559e-06, 5.1985e-06, 5.5784e-07, 3.5050e-06, 2.6849e-06,\n 1.2452e-06, 1.9450e-06, 7.3162e-06, 2.3302e-06, 2.1765e-06, 7.1357e-07,\n 3.3394e-06, 5.4262e-06, 6.8525e-06, 3.1744e-06, 8.2440e-07, 4.3078e-06,\n 2.1205e-06, 2.5858e-06, 9.8119e-06, 1.9844e-06, 3.6007e-06, 3.9261e-06,\n 6.1123e-06, 3.8082e-06, 2.4123e-06, 4.7878e-06, 1.2877e-06, 1.4082e-06,\n 2.6172e-06, 2.4237e-06, 2.5842e-06, 1.5345e-06, 1.5871e-06, 1.0088e-05,\n 2.6731e-06, 9.4260e-06])}, 53: {'step': 7160, 'exp_avg': tensor([-5.2974e-05, 2.7518e-06, 1.1848e-04, -1.3089e-04, 7.1317e-05,\n -1.6492e-04, 2.0880e-05, -9.3230e-05, -8.7078e-05, 2.6536e-05,\n -8.3445e-05, 2.5039e-05, 1.1498e-04, -1.4674e-04, 1.8878e-05,\n -7.7872e-06, -3.4336e-05, 3.7671e-05, 1.8019e-04, 4.4662e-05,\n 4.8625e-05, 5.2134e-06, 3.7176e-05, -3.3856e-04, 5.6333e-05,\n 3.5779e-05, -7.1335e-06, -6.1878e-05, -1.7448e-04, 4.9028e-05,\n 9.7952e-05, -1.3143e-04, -2.4280e-04, -1.0360e-06, -1.3999e-04,\n -4.5139e-05, 1.2081e-10, -7.8212e-05, 0.0000e+00, 8.3922e-05,\n -3.5391e-05, -3.9828e-05, 3.2978e-05, -4.0906e-05, 7.5879e-05,\n 8.9504e-05, 7.9018e-05, -9.7971e-05, -4.3644e-05, 8.9634e-05,\n 5.7402e-06, 0.0000e+00, 2.4371e-05, 1.0119e-04, 2.5147e-06,\n 2.3677e-05, -8.4365e-06, -5.8528e-05, -1.7168e-04, -1.0422e-04,\n 6.0297e-05, -1.6971e-04, 3.0397e-06, 1.2643e-08, 1.3909e-05,\n 9.8242e-06, 1.1496e-04, 4.9538e-05, 0.0000e+00, 4.3575e-05,\n 1.0107e-04, 5.1088e-05, 5.0794e-05, 1.6720e-04, 4.7038e-05,\n -2.8925e-05, -5.2499e-06, -7.1329e-06, 6.8184e-05, 1.1982e-04,\n 1.5829e-05, -6.6561e-05, -5.3866e-06, -2.4078e-05, -8.9538e-05,\n 8.5969e-05, -1.5193e-05, 7.1666e-05, 1.5272e-04, -8.9240e-05,\n 4.3523e-05, -8.7985e-05, -2.1088e-05, -3.8101e-04, 8.0256e-05,\n -4.0789e-06, -3.0947e-05, -4.3587e-05, -2.8738e-05, 7.2580e-06,\n -1.0562e-04, -8.1123e-08, -1.0082e-04, 4.6714e-05, 1.0216e-04,\n -2.1690e-04, 3.7895e-05, -6.2564e-07, -1.1607e-04, -1.6699e-04,\n 3.4891e-05, 1.5485e-04, 2.6983e-05, -4.6323e-05, 1.8751e-04,\n 2.5105e-05, 3.0837e-05, -6.2417e-06, -8.0085e-05, -1.5995e-06,\n -7.5691e-05, 3.9606e-06, -4.7664e-05, -3.7862e-05, 4.4735e-06,\n 1.7567e-05, 1.4279e-04, -1.1922e-04, 8.8234e-06, -3.5969e-05,\n 9.6206e-05, -3.6853e-05, -3.2669e-05, 6.3711e-05, 3.2096e-05,\n 2.2499e-05, 5.6924e-05, 1.3737e-05, 8.3207e-05, 3.4777e-05,\n 7.5285e-06, 1.1242e-04, 1.1734e-04, 1.6358e-05, -1.9715e-05,\n -4.6405e-05, 3.1725e-05, -5.8531e-06, 1.7338e-05, 8.8686e-05,\n 5.8771e-05, 7.1006e-05, 7.6975e-05, -6.1514e-05, 5.4914e-05,\n 4.0772e-05, -1.1531e-04, 5.5868e-05, 1.3251e-04, -2.3673e-05,\n 8.2824e-05, 9.7343e-05, -1.5734e-05, 1.3360e-04, 4.3939e-05,\n -1.9698e-04, 1.2746e-04, 6.9558e-05, -2.1601e-05, -8.6626e-06,\n 1.4441e-05, -1.7028e-06, 7.0629e-08, 2.1892e-05, 1.1620e-04,\n -4.8888e-05, -1.8201e-05, 3.7192e-05, 4.3006e-05, -7.3351e-05,\n 1.0662e-05, -4.2310e-06, -1.0079e-06, 4.4714e-05, -6.5527e-05,\n -6.1117e-06, -2.4636e-06, -1.4779e-04, -1.6067e-04, 5.1309e-05,\n -3.4226e-06, 2.1966e-06, 9.6537e-05, 3.8753e-05, 4.6118e-05,\n 4.8593e-05, 1.9094e-05, 4.8361e-05, 7.4123e-05, -3.5570e-05,\n 0.0000e+00, -4.6328e-05, -5.3712e-05, 3.2292e-05, -5.4476e-06,\n 7.3125e-06, -4.7732e-05, -9.4216e-05, -7.8260e-05, 1.4553e-05,\n -3.2129e-05, -2.2904e-06, -4.8031e-06, 2.3447e-05, 1.4997e-04,\n 5.9658e-05, 1.7481e-05, -2.1251e-04, 9.4280e-05, -3.0907e-05,\n 1.9030e-05, -8.0621e-05, -2.3730e-05, -3.5692e-06, -6.8633e-05,\n -6.6787e-06, 4.1385e-05, 3.7030e-05, 1.1170e-04, 4.7229e-05,\n 1.8597e-05, -3.9381e-06, 1.0948e-05, 9.2043e-05, -2.0715e-04,\n 2.5001e-05, 8.7004e-06, -9.0290e-05, 4.9946e-05, 6.2942e-05,\n -3.1045e-04, -6.0331e-05, -2.2714e-05, 1.3396e-04, 4.4079e-05,\n 1.0252e-04, 8.3572e-05, -3.7556e-05, 5.9997e-06, -6.1631e-05,\n 7.7100e-05, 1.6954e-04, 1.1805e-04, 4.0033e-05, 4.6790e-05,\n -3.8273e-05, 1.1957e-04, -1.7010e-05, -6.3043e-06, 7.7424e-05,\n -1.0197e-04, 5.5319e-05, 1.9198e-04, 6.1305e-05, -8.6335e-05,\n -1.4402e-04, 2.0256e-04, -4.5802e-05, -9.4199e-05, 1.1171e-04,\n 2.6979e-05, -1.9708e-05, -2.7867e-04, -2.3680e-04, -1.5015e-05,\n -1.5860e-05, -1.7704e-06, 1.5338e-06, -1.0277e-04, -3.8411e-05,\n -9.1024e-06, -3.2899e-05, 1.1630e-04, -3.6997e-05, 1.2812e-06,\n 1.8484e-04, 8.7960e-06, 1.8910e-05, -6.1449e-06, -4.3165e-05,\n -1.2868e-06, 7.9192e-05, 3.5614e-05, 3.9948e-05, 9.3599e-05,\n 1.4063e-04, 4.7433e-05, 2.0219e-04, 1.6614e-05, 0.0000e+00,\n -7.2108e-05, -7.0007e-05, -1.3286e-05, 1.4438e-05, 5.7308e-05,\n 1.0597e-04, 4.9384e-05, -1.0635e-05, -6.8402e-06, 3.7661e-05,\n -1.1808e-04, -1.5050e-06, -1.9097e-05, -7.7753e-05, 1.0796e-04,\n -5.1648e-05, -4.9907e-05, -2.6012e-05, 2.5832e-04, 6.6206e-06,\n 2.6954e-05, -1.1882e-04, 3.2287e-05, 1.0894e-04, 9.9173e-05,\n 8.2374e-05, 8.4962e-05, 5.9888e-05, 1.8007e-05, -1.2342e-04,\n -2.8497e-05, -9.5133e-05, -2.4950e-04, -4.2313e-06, -1.1320e-04,\n 5.1261e-05, 5.6130e-05, 6.8848e-05, 9.1317e-05, -1.2432e-04,\n 4.7320e-05, 2.1159e-05, 1.7829e-05, -1.9556e-06, 9.3648e-05,\n 8.8207e-05, -3.4661e-05, 3.0478e-05, 4.8666e-05, -3.6972e-05,\n -1.1325e-04, 3.7085e-07, 3.6121e-05, -1.5131e-04, -3.0003e-06,\n -5.6687e-05, 1.6228e-05, 1.8209e-05, -1.2486e-05, -2.0336e-05,\n -2.1441e-05, -7.2987e-05, -3.5616e-05, 6.5025e-05, 4.2085e-06,\n 5.2227e-05, -3.8577e-05, 1.1237e-05, -6.3367e-05, 5.3801e-05,\n -1.1855e-05, 1.6932e-05, -2.6043e-05, -2.7384e-05, 7.3641e-05,\n -1.3164e-04, -4.4250e-05, -1.4839e-05, 1.7701e-05, -3.6903e-05,\n -1.3799e-04, 7.7382e-05, 3.9798e-05, -4.1231e-05, 9.2251e-05,\n 3.6476e-05, 1.7347e-05, 3.2355e-05, -2.0742e-06, 1.9944e-05,\n -6.7692e-05, -4.7366e-05, -5.7920e-05, 2.6044e-05, 1.7804e-05,\n -2.6806e-06, -1.9576e-04, 8.6898e-05, 6.0268e-05, -2.0991e-04,\n 2.3263e-04, -1.7123e-04, -5.8502e-05, -1.7768e-05, 2.8278e-05,\n -1.0755e-06, 1.6932e-05, 3.4929e-06, 6.1687e-05, 1.4326e-05,\n 1.2763e-04, -1.4854e-05, -2.9936e-05, 2.2520e-05, -7.7341e-05,\n 4.2875e-05, -7.0673e-06, 3.0620e-05, -1.0785e-04, 1.8668e-05,\n 1.5438e-05, 1.2390e-05, -9.5851e-05, -1.3338e-04, 6.1572e-05,\n -9.4144e-06, -7.4253e-05, 1.4526e-04, -1.8665e-05, -5.4313e-05,\n 5.2213e-05, 1.4263e-05, 1.0836e-05, 1.3139e-04, -7.9340e-05,\n -1.4168e-05, -6.0562e-06, -3.2376e-05, 4.3337e-07, 4.3677e-05,\n 1.8677e-05, 6.4847e-05, 1.0237e-04, 1.2765e-04, -2.0893e-05,\n 5.7231e-05, -9.5596e-05, 7.9608e-05, 8.4543e-05, 1.7062e-04,\n 2.2731e-04, 0.0000e+00, -2.1413e-04, 4.4693e-05, -4.2835e-06,\n -4.0159e-05, 1.1087e-04, -5.1086e-05, 1.1960e-04, 7.9746e-05,\n -3.0467e-05, -3.4573e-05, 8.7337e-06, 7.1714e-05, 3.1438e-05,\n 9.5345e-05, 3.7251e-05, 3.4876e-05, -1.4197e-05, -2.5315e-05,\n -1.4156e-04, 1.7539e-04, 1.0194e-04, 1.5849e-04, -3.2723e-05,\n -3.4601e-07, 1.6990e-04, 2.8550e-05, -3.4904e-05, -7.5379e-07,\n -1.2913e-04, 5.2631e-05, -1.0032e-04, -1.8112e-05, -1.9417e-05,\n 7.5140e-05, -3.8133e-05, -1.8804e-05, 1.4077e-05, -2.0535e-05,\n -3.7897e-05, 6.2107e-05, 1.9208e-05, -2.6657e-05, 3.0840e-05,\n 5.4958e-05, -1.0591e-05, 5.2993e-05, 1.4586e-04, 1.0837e-04,\n -3.2669e-06, 3.6393e-05, -1.1881e-05, 1.3724e-04, -5.4926e-05,\n 5.7008e-05, 5.4737e-06, 7.1116e-05, 9.0442e-05, -1.1859e-04,\n 3.9840e-05, 7.3999e-05]), 'exp_avg_sq': tensor([1.2535e-06, 1.2903e-06, 3.0050e-06, 1.0338e-06, 7.9669e-07, 5.7178e-06,\n 9.3575e-07, 1.0833e-06, 4.1385e-07, 1.4963e-06, 1.3030e-06, 8.1162e-07,\n 1.7271e-06, 8.9153e-07, 9.9031e-07, 6.7084e-07, 6.9497e-07, 1.1930e-06,\n 1.3423e-06, 1.1928e-06, 5.3381e-07, 1.3398e-06, 1.2795e-06, 3.8364e-06,\n 1.5504e-06, 1.3090e-06, 1.2905e-06, 8.1083e-07, 1.9038e-06, 1.4882e-06,\n 8.1571e-07, 6.5019e-06, 2.9857e-06, 9.0612e-07, 3.0896e-06, 1.5365e-06,\n 2.7103e-10, 1.3258e-06, 0.0000e+00, 2.5656e-06, 8.7294e-07, 7.5381e-07,\n 2.2270e-06, 9.9696e-07, 1.1542e-06, 6.2908e-07, 2.4513e-06, 9.4972e-07,\n 5.7907e-07, 1.3785e-06, 6.4962e-07, 0.0000e+00, 9.5092e-07, 8.4131e-07,\n 9.4299e-07, 5.5255e-07, 4.6487e-07, 8.8010e-07, 2.4678e-06, 1.5198e-06,\n 1.9241e-06, 8.3858e-07, 7.6916e-07, 7.0286e-07, 5.0764e-07, 1.1119e-06,\n 3.4588e-07, 5.8933e-07, 0.0000e+00, 9.6379e-07, 9.8033e-07, 1.0263e-06,\n 1.1851e-06, 1.3894e-06, 1.5429e-06, 1.8127e-06, 1.1412e-06, 1.4812e-06,\n 2.7643e-06, 6.6507e-07, 1.3458e-06, 6.5544e-07, 8.9153e-07, 9.8408e-07,\n 9.2197e-07, 1.4811e-06, 1.0600e-06, 5.5637e-06, 2.2285e-06, 1.5131e-06,\n 1.7089e-06, 1.0314e-06, 2.5419e-07, 4.7406e-06, 2.2170e-06, 6.8309e-07,\n 1.3766e-06, 2.0838e-06, 1.4443e-06, 1.3548e-06, 1.1805e-06, 3.8985e-07,\n 1.6888e-06, 8.1345e-07, 1.0974e-06, 2.4291e-06, 1.6602e-06, 5.5842e-07,\n 5.8650e-07, 1.8390e-06, 1.1975e-06, 2.2927e-06, 1.7205e-06, 1.4467e-06,\n 1.8019e-06, 2.4142e-06, 9.8047e-07, 1.1916e-06, 1.2894e-06, 1.6149e-06,\n 6.1297e-07, 1.0199e-06, 1.2148e-06, 1.2506e-06, 1.0939e-06, 3.2097e-06,\n 1.3677e-06, 3.0363e-06, 8.7590e-07, 1.7825e-06, 1.2196e-06, 6.0074e-07,\n 9.1997e-07, 1.4841e-06, 2.0996e-06, 1.0138e-06, 1.1175e-06, 1.3507e-06,\n 4.3931e-06, 1.1214e-06, 1.0918e-06, 2.2969e-06, 7.1702e-07, 1.8804e-06,\n 1.4417e-06, 1.7520e-06, 1.0734e-06, 9.1898e-07, 1.4098e-06, 7.8343e-07,\n 1.3732e-06, 3.0148e-06, 1.4250e-06, 1.4681e-06, 1.3162e-06, 1.5830e-06,\n 8.3716e-06, 2.8892e-06, 1.3374e-06, 9.6109e-07, 8.5836e-07, 3.6819e-06,\n 1.1916e-06, 9.6983e-07, 5.2904e-07, 5.2264e-06, 1.1670e-06, 8.1107e-07,\n 5.9515e-07, 2.2357e-06, 7.7987e-06, 2.5325e-06, 1.9029e-08, 1.2546e-07,\n 9.5579e-07, 1.1649e-06, 1.1365e-06, 1.3135e-06, 6.0008e-07, 5.8031e-07,\n 7.2986e-07, 8.8264e-07, 1.2819e-06, 1.4420e-06, 1.0680e-06, 2.2080e-06,\n 4.3662e-06, 1.3064e-06, 2.6400e-06, 1.1695e-07, 2.1309e-06, 7.2643e-07,\n 7.7116e-07, 2.7420e-06, 9.1890e-07, 1.0684e-06, 2.2890e-06, 7.8807e-07,\n 1.6860e-06, 1.2070e-06, 0.0000e+00, 9.1849e-07, 1.4023e-06, 9.3465e-07,\n 4.3051e-06, 5.7835e-07, 1.8984e-06, 1.0507e-06, 5.6730e-06, 9.6522e-08,\n 9.3049e-07, 1.2592e-06, 3.9400e-06, 4.1806e-06, 2.1617e-06, 9.9997e-07,\n 1.0564e-06, 4.8567e-06, 2.8480e-06, 1.5767e-06, 9.3587e-07, 9.6536e-07,\n 1.0879e-06, 1.2232e-06, 8.2950e-07, 1.0163e-06, 1.1373e-06, 6.9701e-07,\n 1.1680e-06, 1.1468e-06, 2.1733e-06, 1.3491e-06, 1.8013e-06, 1.0954e-06,\n 6.9561e-06, 1.1089e-06, 2.0805e-06, 3.4471e-06, 1.8836e-06, 2.9121e-06,\n 4.9974e-06, 6.5508e-07, 9.5911e-07, 1.5937e-06, 9.8483e-07, 8.3344e-07,\n 9.5760e-07, 1.4000e-06, 1.4472e-06, 1.1901e-06, 6.0499e-07, 1.3374e-05,\n 1.3737e-06, 7.1705e-07, 5.0737e-07, 5.9908e-07, 9.8800e-07, 6.6702e-07,\n 1.1458e-06, 9.8801e-07, 2.9142e-07, 1.1008e-06, 1.0739e-06, 1.6443e-06,\n 1.0578e-06, 9.7019e-06, 2.0315e-06, 8.7089e-07, 6.5461e-06, 2.8162e-06,\n 3.0957e-06, 8.1495e-07, 4.5056e-06, 3.1965e-06, 1.0433e-06, 6.5201e-07,\n 1.1657e-06, 5.5876e-07, 5.6297e-07, 8.9881e-07, 7.1719e-07, 9.9795e-07,\n 6.2170e-07, 6.3241e-07, 1.0124e-06, 2.1308e-06, 6.0198e-07, 8.8732e-07,\n 7.3270e-07, 5.5181e-07, 2.9606e-07, 3.1097e-06, 6.3954e-07, 5.3293e-07,\n 6.1159e-07, 1.1061e-06, 9.0419e-07, 2.6851e-06, 1.1956e-06, 0.0000e+00,\n 1.0631e-06, 7.7302e-07, 1.3163e-06, 1.7148e-06, 5.7910e-07, 8.5690e-07,\n 3.5146e-07, 1.0037e-06, 8.4692e-07, 3.3051e-07, 9.5445e-07, 2.1191e-06,\n 3.0056e-06, 5.3450e-06, 1.0846e-06, 3.6867e-06, 1.1593e-06, 2.6598e-06,\n 6.3686e-06, 6.5984e-07, 9.0860e-07, 2.0057e-06, 2.0215e-07, 8.9055e-07,\n 6.7318e-07, 3.6901e-06, 4.9847e-07, 8.6962e-07, 8.3304e-07, 3.7442e-06,\n 1.6510e-06, 9.4165e-07, 2.7636e-06, 4.2323e-06, 7.5409e-07, 9.3983e-07,\n 1.2522e-06, 1.7497e-06, 5.7073e-07, 1.0320e-06, 1.6786e-06, 1.1136e-06,\n 2.1299e-06, 7.4334e-07, 1.9538e-06, 1.6891e-06, 5.5797e-06, 2.1310e-06,\n 5.7050e-07, 5.1317e-06, 1.9371e-06, 8.4271e-07, 1.7449e-06, 6.0114e-07,\n 1.7430e-06, 9.0036e-07, 7.3518e-07, 1.3427e-05, 1.5244e-06, 2.1070e-06,\n 7.8120e-07, 1.4620e-06, 9.1653e-07, 1.8456e-06, 1.3006e-06, 1.5810e-06,\n 2.4893e-07, 1.5191e-06, 9.0161e-07, 1.0922e-06, 3.1022e-06, 2.2867e-06,\n 1.3689e-06, 1.2241e-06, 1.8082e-06, 1.2724e-06, 9.4287e-07, 1.0168e-06,\n 4.7120e-07, 8.2045e-07, 1.8169e-06, 2.8523e-06, 1.6379e-06, 9.9151e-07,\n 9.2442e-07, 8.7699e-07, 1.9298e-06, 2.3333e-06, 4.6976e-07, 1.4066e-06,\n 1.1743e-06, 7.4936e-07, 5.4652e-06, 7.6523e-08, 1.4483e-06, 1.1087e-06,\n 3.1243e-06, 8.6109e-07, 8.9802e-07, 3.9697e-06, 9.5271e-06, 1.1757e-06,\n 1.1262e-06, 4.8524e-06, 9.2254e-07, 1.0724e-06, 1.5297e-06, 5.5943e-07,\n 1.2974e-06, 1.4590e-06, 1.1345e-06, 8.6719e-07, 1.7078e-06, 1.4317e-06,\n 6.1711e-06, 6.8424e-07, 6.2637e-07, 1.0277e-06, 1.0942e-06, 3.2260e-06,\n 7.2753e-07, 3.9133e-06, 4.9802e-07, 1.0393e-06, 1.7292e-06, 6.2158e-07,\n 3.8975e-06, 4.1447e-06, 2.0168e-06, 5.3720e-07, 1.3974e-06, 3.4025e-07,\n 1.1683e-06, 1.8042e-06, 6.4512e-07, 1.3036e-06, 5.8432e-07, 1.3661e-06,\n 7.8503e-07, 1.0714e-06, 1.7379e-06, 3.6610e-06, 3.3488e-07, 1.6132e-06,\n 5.2863e-07, 6.8151e-07, 3.9592e-06, 9.4909e-07, 1.9261e-06, 8.1560e-07,\n 5.9117e-06, 0.0000e+00, 1.5954e-06, 8.1499e-07, 1.0962e-06, 1.0210e-06,\n 1.1067e-06, 1.0752e-06, 1.2993e-06, 3.3870e-06, 9.3277e-07, 8.1123e-07,\n 2.1270e-07, 1.5339e-06, 9.2620e-07, 1.0018e-06, 8.8541e-07, 3.2429e-06,\n 4.6907e-06, 7.8854e-07, 7.4563e-07, 5.5205e-06, 1.2258e-05, 2.5967e-06,\n 1.1785e-06, 1.0497e-06, 3.2897e-06, 3.9178e-07, 1.5420e-06, 1.3562e-06,\n 8.8152e-07, 1.1287e-06, 4.0949e-06, 1.3475e-06, 9.2577e-07, 7.3013e-07,\n 1.9403e-06, 9.7934e-07, 8.6724e-07, 2.3723e-06, 5.3494e-07, 3.5126e-07,\n 9.3782e-07, 1.0473e-06, 3.4805e-06, 7.9232e-07, 2.2400e-06, 1.2863e-06,\n 3.4964e-06, 1.4133e-06, 4.9226e-07, 1.0102e-06, 7.1643e-07, 9.0076e-07,\n 1.1586e-06, 1.5615e-06, 3.1049e-06, 1.1039e-06, 7.3176e-07, 2.4900e-06,\n 9.8116e-07, 1.7010e-06])}, 54: {'step': 7160, 'exp_avg': tensor([[[[ 1.2735e-05]],\n\n [[-6.0588e-06]],\n\n [[-2.5872e-05]],\n\n ...,\n\n [[ 2.5484e-06]],\n\n [[ 3.4118e-05]],\n\n [[ 2.2741e-05]]],\n\n\n [[[ 2.9844e-05]],\n\n [[-6.0611e-06]],\n\n [[-1.0559e-05]],\n\n ...,\n\n [[-2.5459e-05]],\n\n [[-1.3186e-05]],\n\n [[-5.5409e-06]]],\n\n\n [[[ 5.0454e-05]],\n\n [[ 1.5145e-05]],\n\n [[ 2.2064e-05]],\n\n ...,\n\n [[-4.5211e-05]],\n\n [[-1.6798e-05]],\n\n [[-2.7332e-05]]],\n\n\n ...,\n\n\n [[[ 3.5894e-06]],\n\n [[-8.0466e-06]],\n\n [[ 1.6026e-05]],\n\n ...,\n\n [[-8.5409e-05]],\n\n [[-4.1501e-05]],\n\n [[-5.9838e-05]]],\n\n\n [[[ 2.0807e-05]],\n\n [[ 1.7975e-05]],\n\n [[ 3.0480e-05]],\n\n ...,\n\n [[-6.4068e-06]],\n\n [[-2.4485e-05]],\n\n [[ 7.7967e-06]]],\n\n\n [[[-2.5983e-05]],\n\n [[-1.0625e-05]],\n\n [[ 2.1797e-05]],\n\n ...,\n\n [[-6.0883e-05]],\n\n [[-6.5692e-05]],\n\n [[ 1.7688e-05]]]]), 'exp_avg_sq': tensor([[[[1.2737e-07]],\n\n [[5.1786e-08]],\n\n [[2.3042e-07]],\n\n ...,\n\n [[2.1531e-07]],\n\n [[2.0486e-07]],\n\n [[1.4060e-07]]],\n\n\n [[[1.0539e-07]],\n\n [[5.8064e-08]],\n\n [[1.3207e-07]],\n\n ...,\n\n [[4.5759e-07]],\n\n [[1.4243e-07]],\n\n [[1.1295e-07]]],\n\n\n [[[1.8685e-07]],\n\n [[5.2029e-08]],\n\n [[3.1845e-07]],\n\n ...,\n\n [[3.0712e-07]],\n\n [[1.8929e-07]],\n\n [[2.1195e-07]]],\n\n\n ...,\n\n\n [[[1.1027e-07]],\n\n [[4.3086e-08]],\n\n [[1.4267e-07]],\n\n ...,\n\n [[2.8415e-07]],\n\n [[1.3300e-07]],\n\n [[1.5833e-07]]],\n\n\n [[[1.1308e-07]],\n\n [[4.1017e-08]],\n\n [[1.0261e-07]],\n\n ...,\n\n [[1.7713e-07]],\n\n [[1.5394e-07]],\n\n [[9.2195e-08]]],\n\n\n [[[1.3720e-07]],\n\n [[3.2205e-08]],\n\n [[3.1854e-07]],\n\n ...,\n\n [[2.0135e-07]],\n\n [[1.3381e-07]],\n\n [[1.3264e-07]]]])}, 55: {'step': 7160, 'exp_avg': tensor([ 1.7295e-05, -1.7187e-04, -1.0639e-04, 2.1034e-06, 1.0156e-04,\n 1.7409e-04, 1.4821e-05, 6.8799e-05, -3.8356e-06, -2.0740e-04,\n 1.4082e-04, 4.9330e-05, 1.0629e-04, 5.0820e-05, 1.5768e-04,\n -8.2864e-04, -3.7245e-04, 2.2021e-04, -5.0456e-05, 4.0656e-06,\n 1.7184e-04, -1.4167e-04, 6.3008e-05, 4.4970e-05, 6.1078e-05,\n 1.3223e-04, 1.4941e-04, 1.3318e-04, 5.4419e-05, -5.4298e-05,\n -1.6474e-04, 1.2679e-04, -1.3536e-04, 4.1490e-05, 3.3860e-04,\n -2.9493e-04, 2.1198e-04, 2.1288e-04, 3.1551e-04, 5.9030e-04,\n 1.4748e-04, 2.3969e-05, -1.2897e-04, -2.8882e-05, -1.2720e-04,\n -6.2783e-05, 5.8258e-05, -1.2934e-04, -5.2976e-06, 1.1000e-04,\n -5.5684e-05, 3.3589e-05, -6.5359e-05, -2.6782e-05, -4.4666e-05,\n 1.2165e-05, -3.7996e-05, -5.4258e-05, -3.3831e-05, -3.3797e-05,\n -8.1639e-05, -2.6125e-04, -3.5953e-04, 7.3614e-05, 1.0894e-04,\n -6.6580e-05, -8.1360e-05, 3.4478e-05, -1.4204e-05, 1.1325e-04,\n -1.9671e-04, -1.0203e-04, 3.5778e-04, -3.1964e-04, 1.7573e-04,\n -2.5834e-04, -1.5495e-04, -4.8666e-05, -1.1382e-05, -1.0342e-04,\n 1.6120e-04, -4.3583e-05, 3.0560e-04, -2.1221e-04, -1.7182e-04,\n 1.4763e-07, -2.2316e-04, 5.8585e-05, 1.6435e-04, 5.1823e-05,\n -3.0200e-05, -1.3991e-05, -5.8579e-05, -9.9413e-05, -4.9902e-05,\n 2.9897e-05, -1.6356e-05, -1.5727e-04, 1.4382e-04, 2.3045e-05,\n 1.1037e-04, 6.5660e-05, -2.9755e-04, -8.9282e-05, 2.2648e-04,\n -2.6281e-05, -1.9780e-04, 3.8615e-05, -3.1794e-05, -1.8291e-04,\n 1.0247e-04, 5.2771e-05, 1.2161e-04, -1.9043e-04, -2.2577e-05,\n 5.7980e-05, 6.2773e-05, 2.4496e-04, 3.2135e-06, 4.6090e-05,\n 1.0944e-04, 9.1603e-05, 3.7808e-05, 9.2173e-06, 1.3461e-04,\n 2.2314e-04, 2.8473e-05, 2.0639e-05]), 'exp_avg_sq': tensor([6.5334e-06, 1.2913e-05, 4.7961e-06, 7.0041e-06, 2.8483e-06, 4.8739e-06,\n 2.2044e-06, 6.3093e-06, 5.2207e-06, 6.0947e-06, 3.1986e-06, 6.8670e-06,\n 2.0450e-06, 6.6552e-06, 2.5632e-06, 2.4239e-05, 8.6182e-06, 4.4383e-06,\n 1.0372e-05, 3.0252e-06, 1.5852e-05, 5.8452e-06, 2.7230e-06, 4.5169e-06,\n 5.4638e-06, 1.7620e-06, 1.0956e-05, 2.8250e-06, 2.9064e-06, 1.1088e-05,\n 1.1773e-05, 4.1608e-06, 4.7235e-06, 2.0860e-06, 1.1492e-05, 1.2747e-05,\n 5.9467e-06, 7.3623e-06, 4.7763e-06, 2.6871e-05, 3.6954e-06, 1.0388e-05,\n 4.1667e-06, 5.1028e-06, 3.1608e-06, 4.1916e-06, 2.5258e-06, 4.8197e-06,\n 4.1409e-06, 2.1397e-06, 3.0489e-06, 3.3585e-06, 2.5742e-06, 2.7060e-06,\n 1.0189e-05, 6.1283e-06, 6.8379e-06, 4.2562e-06, 5.7397e-06, 2.2916e-06,\n 3.0494e-06, 5.7697e-06, 4.1972e-06, 3.1130e-06, 3.1489e-06, 6.9734e-06,\n 6.3605e-06, 2.7003e-06, 3.8639e-06, 4.3579e-06, 4.2546e-06, 3.9725e-06,\n 1.7761e-05, 1.1098e-05, 6.8822e-06, 2.1716e-06, 6.0180e-06, 2.2756e-06,\n 4.8409e-06, 3.1030e-06, 5.8021e-06, 3.2491e-06, 6.4240e-06, 4.0488e-06,\n 4.6938e-06, 9.0011e-06, 3.8704e-06, 4.8113e-06, 1.7492e-06, 2.7814e-06,\n 3.7179e-06, 2.0537e-05, 2.8304e-06, 4.8694e-06, 2.2112e-06, 3.0899e-06,\n 3.6124e-06, 6.5572e-06, 5.1907e-06, 4.8887e-06, 6.0598e-06, 4.4748e-06,\n 4.8316e-06, 8.2619e-06, 6.1409e-06, 1.5000e-05, 4.2353e-06, 6.1266e-06,\n 4.5572e-06, 4.9136e-06, 2.3564e-06, 3.1572e-06, 2.9611e-06, 1.6470e-06,\n 3.2679e-06, 5.9608e-06, 7.7152e-06, 1.8184e-06, 4.2532e-06, 8.4682e-06,\n 3.5992e-06, 6.1497e-06, 1.8345e-06, 3.4806e-06, 4.2095e-06, 3.8392e-06,\n 2.9095e-06, 3.8616e-06])}, 56: {'step': 7160, 'exp_avg': tensor([-1.6425e-05, -6.9655e-05, -1.2473e-04, 5.0774e-05, 1.0662e-04,\n 9.1588e-05, -3.9447e-06, 8.7773e-05, -1.0835e-04, -2.1184e-04,\n 9.1664e-05, 2.0535e-04, 1.1341e-04, -4.8299e-06, 1.5010e-04,\n 7.6212e-05, -8.5472e-05, 1.0518e-04, 3.1108e-05, -5.7757e-05,\n 4.7036e-05, -8.5673e-05, 1.8617e-04, -9.0894e-05, 3.0726e-05,\n 7.7470e-05, 1.9730e-04, 1.0304e-04, 3.1283e-05, -5.5933e-05,\n -3.5175e-04, 1.7438e-04, -1.1709e-04, -5.2142e-05, 4.5419e-05,\n -6.4438e-06, 1.0884e-04, 1.7124e-04, 2.0627e-04, -3.3892e-06,\n 7.2091e-05, 2.0558e-05, 3.9444e-05, 4.4996e-05, 1.7177e-06,\n -4.9684e-05, 2.4268e-05, 6.4126e-06, -3.2621e-05, 4.4864e-05,\n -9.0881e-05, 7.0286e-05, 8.0954e-06, -4.7637e-05, -1.5440e-04,\n -7.8096e-05, -9.2512e-05, -4.4651e-05, -7.6264e-05, 1.3424e-04,\n -8.7164e-05, -2.0346e-04, -3.9135e-04, 2.6541e-05, 2.8267e-04,\n -7.1565e-05, -3.3452e-05, 2.8215e-05, 4.8794e-05, 2.4302e-04,\n -2.1693e-04, 1.7585e-05, -1.1441e-04, -2.9601e-04, 1.2857e-04,\n -1.6199e-05, -3.6807e-05, -6.3749e-05, -6.3721e-05, -6.6247e-05,\n -4.5900e-05, -7.5505e-05, 5.8075e-05, -2.7200e-04, -1.7645e-04,\n -3.7427e-05, -5.5361e-05, -7.0170e-06, 1.5465e-04, 6.8207e-05,\n -6.7993e-05, 7.8371e-05, 5.5522e-05, -8.9566e-05, -6.1145e-05,\n 2.3162e-05, -1.0021e-05, 1.3781e-04, 9.6033e-05, 9.8074e-06,\n -1.0589e-04, 1.4753e-04, -2.0323e-04, -1.2315e-05, 2.5459e-04,\n 1.5455e-05, -2.3601e-04, -6.8937e-05, 4.6776e-06, -1.7400e-04,\n 1.2057e-04, -3.3807e-05, 3.1263e-05, -1.5090e-04, 1.7304e-05,\n 6.2095e-05, -1.1153e-04, 1.5397e-04, 1.3115e-05, -1.5466e-04,\n 1.3766e-04, 6.3200e-05, 5.0591e-05, -3.8651e-05, 7.2831e-05,\n 1.3476e-05, 2.6892e-05, 2.2267e-05]), 'exp_avg_sq': tensor([1.3502e-06, 3.0492e-06, 2.1677e-06, 5.3900e-06, 2.4826e-06, 9.0588e-06,\n 1.5518e-06, 2.3991e-06, 3.3942e-06, 7.1503e-06, 1.4696e-06, 3.0636e-06,\n 1.6967e-06, 5.0147e-06, 2.5158e-06, 9.7254e-07, 1.0255e-05, 1.4446e-06,\n 2.0731e-06, 2.5912e-06, 8.9589e-06, 3.0706e-06, 3.1107e-06, 2.8713e-06,\n 1.8923e-06, 1.1899e-06, 7.8053e-06, 2.8016e-06, 2.7623e-06, 3.0527e-06,\n 9.4891e-06, 5.6677e-06, 3.1868e-06, 2.0223e-06, 2.0209e-05, 2.2598e-06,\n 1.3165e-06, 9.4190e-07, 3.0942e-06, 8.0578e-07, 1.3804e-06, 4.4819e-06,\n 2.2669e-06, 2.1039e-06, 1.7880e-06, 3.3535e-06, 1.9474e-06, 4.3088e-06,\n 2.7173e-06, 1.7237e-06, 1.8716e-06, 2.0285e-06, 2.1016e-06, 1.8188e-06,\n 4.0149e-06, 7.0191e-06, 3.9262e-06, 2.9235e-06, 4.4940e-06, 2.3065e-06,\n 1.4751e-06, 3.4043e-06, 3.4217e-06, 1.7407e-06, 5.8686e-06, 2.6288e-06,\n 5.5993e-06, 1.5647e-06, 2.1696e-06, 2.2471e-06, 3.1254e-06, 3.4997e-06,\n 2.4880e-06, 1.0254e-05, 2.0915e-06, 2.2735e-06, 2.4224e-06, 2.7753e-06,\n 3.1729e-06, 1.4890e-06, 4.4487e-06, 2.8307e-06, 3.4530e-06, 2.8990e-06,\n 4.6134e-06, 3.7792e-06, 1.3303e-06, 3.4437e-06, 1.1909e-06, 2.4428e-06,\n 2.5202e-06, 4.4952e-06, 1.7168e-06, 4.2129e-06, 1.5366e-06, 2.8227e-06,\n 3.7994e-06, 4.3029e-06, 2.1429e-06, 2.7911e-06, 5.9031e-06, 1.9609e-06,\n 2.1654e-06, 5.2557e-06, 2.1028e-06, 4.8127e-06, 2.4641e-06, 2.7147e-06,\n 1.7131e-06, 3.7789e-06, 2.6212e-06, 1.5466e-06, 2.2921e-06, 1.6734e-06,\n 2.8264e-06, 2.0730e-06, 3.1460e-06, 1.6659e-06, 3.1570e-06, 2.4252e-06,\n 1.8567e-06, 3.4559e-06, 9.5763e-07, 2.3458e-06, 1.6509e-06, 2.9815e-06,\n 1.4805e-06, 2.5308e-06])}, 57: {'step': 7160, 'exp_avg': tensor([[[[ 2.4263e-05, -1.2026e-06, -8.0363e-06],\n [-1.1414e-05, -1.4579e-05, 5.0987e-06],\n [ 1.5707e-06, 9.0642e-06, 7.1541e-06]],\n\n [[ 2.0459e-05, 9.6147e-06, -8.5858e-06],\n [ 4.7222e-05, 3.1981e-05, 2.9725e-05],\n [ 2.1946e-05, 1.0203e-05, 1.1421e-05]],\n\n [[ 5.2486e-05, 5.0532e-05, 2.9707e-05],\n [ 5.9831e-05, 2.9907e-05, 2.3918e-05],\n [ 4.9876e-05, 4.6371e-06, 2.2383e-05]],\n\n ...,\n\n [[-6.9041e-06, -9.3838e-06, 1.7189e-05],\n [ 6.6393e-06, 2.7747e-05, -1.6188e-05],\n [-2.6333e-05, -1.7703e-06, -4.5205e-06]],\n\n [[ 6.0510e-06, 2.9576e-05, 6.0315e-06],\n [-1.1772e-06, -2.5620e-05, 1.6384e-06],\n [ 2.7396e-05, -2.1463e-06, -2.1850e-06]],\n\n [[-3.4464e-05, -2.8592e-05, -7.9250e-06],\n [-4.7967e-05, -4.9419e-05, -1.0857e-05],\n [-1.4856e-05, -7.1553e-06, 1.5269e-05]]],\n\n\n [[[-3.7468e-06, -2.9592e-05, -3.6638e-05],\n [ 8.7073e-06, -5.9186e-06, 1.2526e-06],\n [ 2.4728e-05, 7.5257e-07, 1.0563e-05]],\n\n [[-3.1554e-06, -1.6940e-05, -4.5418e-06],\n [-1.3408e-05, -2.8306e-05, -2.8704e-05],\n [-8.2840e-06, -1.0655e-06, -1.0039e-05]],\n\n [[ 9.2402e-06, 2.2965e-05, 2.3697e-05],\n [-6.3352e-05, -3.9562e-05, -1.4211e-05],\n [ 2.0876e-05, -2.8978e-05, -1.7861e-05]],\n\n ...,\n\n [[ 1.9564e-06, 1.2358e-05, 1.4692e-05],\n [ 1.1551e-05, -5.4953e-06, -2.2728e-05],\n [-1.8248e-06, -5.1754e-06, 4.5034e-06]],\n\n [[-4.2117e-05, -5.5805e-05, -3.5844e-05],\n [-5.6480e-05, -5.2843e-05, 1.2062e-05],\n [-3.2150e-06, -3.1910e-05, -2.0713e-05]],\n\n [[ 1.1171e-05, -3.1245e-06, 6.9215e-06],\n [ 3.1626e-05, 5.8962e-07, -3.6906e-06],\n [ 3.0703e-06, -9.9796e-06, -3.2167e-06]]],\n\n\n [[[ 7.7831e-06, 1.2623e-05, 1.3766e-05],\n [ 4.1044e-06, 1.0404e-05, 7.6676e-06],\n [ 1.8057e-05, 2.4571e-05, -6.2262e-07]],\n\n [[ 1.1003e-05, 2.5711e-06, -9.4458e-07],\n [ 2.1019e-06, 1.9889e-05, 7.3926e-06],\n [ 1.0140e-05, 6.6827e-06, 7.0923e-07]],\n\n [[-1.4997e-05, 8.5694e-06, -2.0970e-05],\n [-1.9399e-06, -7.5618e-06, 1.9676e-05],\n [-1.5503e-05, -2.9883e-05, 6.6096e-06]],\n\n ...,\n\n [[-1.5427e-05, -9.7458e-06, 9.8072e-06],\n [-4.6518e-06, -1.6242e-05, -1.0937e-05],\n [-2.9857e-06, -5.1537e-06, -1.0377e-05]],\n\n [[-7.3707e-06, 5.2054e-06, 8.4226e-06],\n [-1.2040e-05, -3.5530e-07, -3.0813e-06],\n [ 3.8577e-06, -2.0437e-05, -1.1889e-06]],\n\n [[ 7.3579e-06, 1.4364e-06, -8.8122e-06],\n [ 1.1756e-05, 1.2942e-06, -3.5489e-06],\n [-1.0044e-05, -5.6376e-06, 1.1718e-05]]],\n\n\n ...,\n\n\n [[[-2.1171e-05, 4.4767e-07, 1.3540e-05],\n [-4.5587e-06, 9.6606e-07, 1.6606e-06],\n [ 8.4792e-07, -6.3865e-06, 1.8168e-05]],\n\n [[-1.9108e-05, -1.3616e-05, 7.9193e-07],\n [-2.6922e-05, -2.1915e-05, -2.1193e-05],\n [-1.9792e-05, -2.5714e-05, -9.4346e-06]],\n\n [[ 2.0052e-06, -1.0439e-05, -2.3262e-05],\n [-9.8012e-06, -2.4469e-05, -3.1773e-05],\n [-4.5647e-05, -4.8877e-05, -6.5524e-05]],\n\n ...,\n\n [[ 3.0682e-05, 3.8389e-05, 2.5314e-05],\n [ 3.7360e-05, 4.6893e-05, 1.5155e-05],\n [ 4.7570e-05, 4.3621e-05, 2.2086e-05]],\n\n [[ 3.6949e-06, -4.4660e-06, 1.0063e-05],\n [-1.3573e-05, -1.2347e-05, 1.2101e-05],\n [-1.7300e-05, -1.6571e-05, -2.6459e-05]],\n\n [[-4.3024e-06, 5.8555e-06, 7.0086e-06],\n [ 8.2177e-06, 1.0778e-05, 6.2131e-06],\n [ 3.4247e-06, 7.7987e-06, 1.2831e-05]]],\n\n\n [[[ 1.6623e-05, 1.1026e-05, -1.4018e-05],\n [-8.3494e-06, -1.7342e-05, -1.7967e-05],\n [ 9.1442e-06, -4.0981e-06, -1.1881e-05]],\n\n [[ 2.5867e-06, -5.7231e-06, -2.2784e-05],\n [-1.5725e-06, -7.9372e-06, -4.1138e-05],\n [ 3.7033e-06, -2.3233e-05, -2.8805e-05]],\n\n [[-3.4783e-05, -1.1337e-05, 2.1938e-05],\n [ 5.0413e-05, 1.3399e-05, 1.1002e-05],\n [ 1.5854e-05, 6.8158e-06, 2.7426e-06]],\n\n ...,\n\n [[-3.2365e-06, -1.8032e-05, -1.7648e-06],\n [-1.0737e-05, -7.1572e-06, -2.6111e-05],\n [-3.0463e-05, -1.7054e-05, -9.6661e-06]],\n\n [[-2.4421e-05, -2.1505e-06, 1.1587e-05],\n [ 1.5067e-06, -1.2892e-05, 1.3566e-05],\n [ 1.6477e-05, 5.1034e-06, 1.0921e-05]],\n\n [[-2.0629e-06, -9.5679e-06, 1.7095e-05],\n [ 7.9101e-06, 1.6739e-05, 8.5278e-07],\n [-1.1928e-05, -4.4814e-06, -1.5701e-05]]],\n\n\n [[[-1.8677e-05, 4.1920e-06, 3.0468e-06],\n [-1.5803e-05, -1.2459e-05, -1.3945e-05],\n [-3.9873e-05, -3.8221e-05, -3.2663e-05]],\n\n [[ 1.0263e-06, -6.8844e-06, 2.0743e-05],\n [ 2.4816e-05, 2.5228e-05, 1.1538e-05],\n [-7.2876e-06, -5.0245e-06, -7.1809e-06]],\n\n [[-3.3488e-06, -5.5015e-07, -3.5010e-05],\n [ 2.8931e-05, -1.0976e-05, -9.7954e-06],\n [ 1.7159e-05, 9.1977e-07, -1.7871e-07]],\n\n ...,\n\n [[-4.9167e-06, -3.2103e-05, 1.6052e-05],\n [ 1.7768e-05, 3.2305e-05, 2.5429e-05],\n [ 5.9848e-06, 3.5019e-05, 2.4886e-05]],\n\n [[ 1.6755e-05, 2.9960e-06, -1.2450e-05],\n [ 5.7773e-05, 2.7469e-05, -2.3134e-05],\n [ 4.2683e-05, 6.8789e-06, 1.2623e-06]],\n\n [[-1.9446e-05, -2.9716e-05, -1.3777e-05],\n [-1.1504e-05, -6.4666e-06, 2.4202e-05],\n [ 2.9222e-05, -1.3940e-05, 6.6294e-07]]]]), 'exp_avg_sq': tensor([[[[1.7012e-07, 1.4770e-07, 1.1758e-07],\n [1.4034e-07, 8.3465e-08, 9.0900e-08],\n [1.1245e-07, 1.1430e-07, 1.3436e-07]],\n\n [[8.3738e-08, 8.0511e-08, 6.9710e-08],\n [9.1692e-08, 1.0327e-07, 7.2788e-08],\n [8.6326e-08, 1.1874e-07, 7.7515e-08]],\n\n [[9.3672e-08, 1.6562e-07, 1.0124e-07],\n [1.2551e-07, 1.2214e-07, 8.3336e-08],\n [7.0464e-08, 7.5608e-08, 7.9929e-08]],\n\n ...,\n\n [[5.2966e-08, 7.1925e-08, 7.9106e-08],\n [5.8998e-08, 8.7168e-08, 9.3415e-08],\n [1.0382e-07, 1.5229e-07, 1.1242e-07]],\n\n [[8.0561e-08, 9.0916e-08, 7.8722e-08],\n [1.1385e-07, 9.3512e-08, 1.2343e-07],\n [8.7638e-08, 6.5459e-08, 7.4672e-08]],\n\n [[8.6321e-08, 1.0542e-07, 1.0221e-07],\n [9.7893e-08, 1.0771e-07, 1.1646e-07],\n [1.1101e-07, 1.1882e-07, 1.0729e-07]]],\n\n\n [[[7.6563e-08, 1.0489e-07, 1.0248e-07],\n [7.7305e-08, 8.2163e-08, 8.9386e-08],\n [8.7288e-08, 9.0487e-08, 7.2072e-08]],\n\n [[7.6292e-08, 8.8154e-08, 8.2295e-08],\n [1.1660e-07, 1.3348e-07, 1.1834e-07],\n [1.2483e-07, 1.1680e-07, 9.8886e-08]],\n\n [[9.4947e-08, 8.3479e-08, 1.1509e-07],\n [1.0527e-07, 1.0303e-07, 1.0741e-07],\n [1.6141e-07, 1.9331e-07, 1.8623e-07]],\n\n ...,\n\n [[1.0187e-07, 9.4307e-08, 6.1369e-08],\n [7.1429e-08, 8.6653e-08, 6.5743e-08],\n [9.1846e-08, 7.6094e-08, 8.5745e-08]],\n\n [[8.1945e-08, 1.2563e-07, 1.0214e-07],\n [9.1029e-08, 1.0918e-07, 6.1280e-08],\n [8.3437e-08, 1.5245e-07, 1.4872e-07]],\n\n [[8.4856e-08, 7.3981e-08, 1.0613e-07],\n [8.1924e-08, 6.4317e-08, 8.4404e-08],\n [9.1732e-08, 8.6106e-08, 8.1702e-08]]],\n\n\n [[[4.3290e-08, 3.3557e-08, 3.7158e-08],\n [4.0688e-08, 4.1669e-08, 4.2256e-08],\n [5.1315e-08, 4.5121e-08, 4.3949e-08]],\n\n [[2.8404e-08, 4.3203e-08, 2.8452e-08],\n [3.1623e-08, 3.7992e-08, 2.9625e-08],\n [4.3356e-08, 3.7885e-08, 4.1457e-08]],\n\n [[6.4785e-08, 5.6317e-08, 6.5651e-08],\n [3.3836e-08, 3.9017e-08, 4.5337e-08],\n [5.4125e-08, 6.1377e-08, 5.4708e-08]],\n\n ...,\n\n [[3.8268e-08, 7.5146e-08, 4.9633e-08],\n [3.5514e-08, 3.8345e-08, 3.3575e-08],\n [6.8544e-08, 5.7884e-08, 2.7470e-08]],\n\n [[4.5629e-08, 3.8036e-08, 4.3155e-08],\n [3.0749e-08, 3.1847e-08, 4.0859e-08],\n [2.8008e-08, 3.2047e-08, 4.9292e-08]],\n\n [[7.6571e-08, 5.0320e-08, 4.4737e-08],\n [4.7051e-08, 3.1009e-08, 3.5860e-08],\n [3.2651e-08, 3.8197e-08, 4.1867e-08]]],\n\n\n ...,\n\n\n [[[1.2359e-07, 1.3801e-07, 1.2491e-07],\n [1.1060e-07, 1.1322e-07, 1.2549e-07],\n [1.1436e-07, 1.2519e-07, 1.3326e-07]],\n\n [[8.2386e-08, 8.1643e-08, 8.8861e-08],\n [8.9598e-08, 1.2309e-07, 1.0036e-07],\n [1.0135e-07, 1.6448e-07, 1.2657e-07]],\n\n [[9.5429e-08, 8.6506e-08, 9.4346e-08],\n [6.0111e-08, 6.5953e-08, 7.4994e-08],\n [1.1506e-07, 1.0938e-07, 7.5452e-08]],\n\n ...,\n\n [[1.0413e-07, 1.1620e-07, 1.0063e-07],\n [9.4877e-08, 8.3200e-08, 1.1793e-07],\n [9.8801e-08, 9.0168e-08, 7.0957e-08]],\n\n [[1.0724e-07, 8.1431e-08, 9.2543e-08],\n [8.6454e-08, 9.8388e-08, 9.1378e-08],\n [1.3829e-07, 1.2112e-07, 1.0264e-07]],\n\n [[1.1868e-07, 9.2547e-08, 8.6255e-08],\n [1.2586e-07, 1.1803e-07, 9.1046e-08],\n [1.1158e-07, 1.0451e-07, 8.5587e-08]]],\n\n\n [[[1.0758e-07, 6.9964e-08, 9.4243e-08],\n [1.0468e-07, 1.0752e-07, 1.6502e-07],\n [1.1040e-07, 1.2764e-07, 1.6781e-07]],\n\n [[9.7887e-08, 6.9324e-08, 1.1152e-07],\n [8.8813e-08, 1.1242e-07, 1.4242e-07],\n [8.9387e-08, 9.7091e-08, 7.9235e-08]],\n\n [[1.3140e-07, 8.3227e-08, 4.8197e-08],\n [1.7850e-07, 1.2031e-07, 5.8552e-08],\n [1.0040e-07, 9.3897e-08, 7.2980e-08]],\n\n ...,\n\n [[6.5430e-08, 9.7962e-08, 7.3602e-08],\n [6.4245e-08, 7.2167e-08, 7.6992e-08],\n [8.8542e-08, 6.2357e-08, 7.7824e-08]],\n\n [[1.0861e-07, 6.2514e-08, 3.8661e-08],\n [6.5234e-08, 6.5892e-08, 3.9026e-08],\n [5.7825e-08, 4.9865e-08, 9.4390e-08]],\n\n [[6.8276e-08, 6.9458e-08, 1.3996e-07],\n [7.1271e-08, 5.9202e-08, 9.5709e-08],\n [9.0267e-08, 7.9659e-08, 6.7252e-08]]],\n\n\n [[[1.2342e-07, 1.0232e-07, 1.1474e-07],\n [1.4973e-07, 1.1633e-07, 1.3486e-07],\n [1.4779e-07, 2.3396e-07, 1.4024e-07]],\n\n [[1.0313e-07, 1.1185e-07, 9.5604e-08],\n [8.3375e-08, 9.3643e-08, 9.4939e-08],\n [9.2119e-08, 7.4293e-08, 8.1028e-08]],\n\n [[1.2046e-07, 1.5687e-07, 1.2129e-07],\n [1.6605e-07, 2.7738e-07, 2.3217e-07],\n [1.6963e-07, 1.3667e-07, 1.3935e-07]],\n\n ...,\n\n [[1.1127e-07, 1.0040e-07, 9.0019e-08],\n [9.5733e-08, 1.0500e-07, 9.7151e-08],\n [1.1249e-07, 1.3022e-07, 1.1903e-07]],\n\n [[1.0973e-07, 9.8737e-08, 9.7151e-08],\n [1.2699e-07, 1.3944e-07, 1.5837e-07],\n [1.2372e-07, 1.0591e-07, 1.1093e-07]],\n\n [[9.9039e-08, 1.4042e-07, 9.3679e-08],\n [1.2632e-07, 1.2639e-07, 9.9087e-08],\n [1.2625e-07, 1.0547e-07, 7.8552e-08]]]])}, 58: {'step': 7160, 'exp_avg': tensor([ 5.2533e-05, -8.2063e-05, -1.1313e-04, 1.4001e-04, -1.5857e-04,\n 2.5714e-04, 8.8449e-05, -9.9818e-05, -2.3078e-04, -4.7597e-04,\n 4.3564e-04, 3.5090e-04, 9.2970e-05, -3.4249e-05, 1.4041e-04,\n -1.1053e-05, -4.6257e-05, 3.0485e-05, -5.0971e-05, 1.3676e-06,\n -1.4555e-04, -4.0953e-05, -1.6033e-04, 5.4328e-05, -1.2710e-04,\n -1.2412e-04, -3.0549e-06, 2.1220e-04, -4.0289e-04, -1.3453e-05,\n -9.7730e-06, 1.4535e-04, 1.0933e-04, 4.7804e-05, 2.9144e-04,\n 4.8778e-04, -2.0834e-06, 2.2151e-04, -8.8073e-05, 1.0331e-04,\n 5.0845e-05, 2.5557e-04, 2.4218e-04, 3.3345e-04, 1.9858e-04,\n -1.2376e-06, -8.7709e-05, 2.0092e-04, -3.7171e-04, 6.1531e-05,\n -8.2837e-05, 9.3488e-05, -5.9761e-05, -1.5560e-04, -1.8821e-04,\n -7.3090e-04, -2.7072e-04, 4.1316e-05, 2.0854e-04, -1.0784e-04,\n -4.0162e-05, 3.1054e-05, -1.3947e-04, 3.4082e-04, -6.3838e-05,\n -4.5167e-05, 7.2542e-05, -8.4841e-05, -9.0591e-05, 1.9606e-05,\n 3.0434e-04, 1.0432e-05, -8.7221e-05, -1.3313e-04, -5.1667e-04,\n 2.8263e-05, 2.9418e-05, 6.9249e-05, 1.5243e-05, 1.5857e-04,\n -7.7469e-05, 1.7486e-04, -3.6822e-05, 9.7241e-06, -5.1586e-04,\n -7.1054e-05, 2.3735e-04, -1.5002e-04, 5.9120e-05, -1.0153e-04,\n -2.7507e-04, -1.1267e-05, -1.3309e-04, 1.8325e-05, 1.9622e-04,\n 4.1499e-04, -1.5519e-04, 6.8603e-05, 6.3159e-05, -6.4390e-05,\n 3.0354e-04, -1.0741e-04, 4.4911e-06, 3.6870e-05, 9.2611e-06,\n -2.1250e-04, 3.4595e-05, 1.9335e-05, 4.2788e-05, 7.9574e-05,\n -1.1429e-04, -2.1090e-04, -4.2673e-05, -3.6676e-05, -1.7946e-04,\n -4.4040e-04, -1.1007e-04, 3.1241e-05, -1.3074e-04, -1.0014e-04,\n 8.7587e-05, -6.6051e-05, -1.7978e-04, 1.5261e-04, -8.5645e-05,\n -1.1042e-04, -5.3505e-05, 3.1970e-04]), 'exp_avg_sq': tensor([2.0342e-05, 4.9820e-06, 2.9522e-06, 2.7788e-06, 3.8560e-06, 7.1751e-06,\n 4.9255e-06, 4.5078e-06, 3.2961e-06, 7.2758e-06, 8.1678e-06, 5.7011e-06,\n 3.5743e-06, 6.2328e-06, 3.4636e-06, 2.7247e-06, 3.0242e-06, 4.0058e-06,\n 2.2845e-06, 6.2190e-06, 3.3514e-06, 3.5675e-06, 3.4505e-06, 3.3989e-06,\n 5.9352e-06, 4.8408e-06, 3.3386e-06, 5.3998e-06, 2.2540e-05, 1.1267e-05,\n 8.0858e-06, 4.4462e-06, 2.3151e-05, 2.8349e-06, 3.1707e-06, 2.6858e-05,\n 7.1201e-06, 5.9568e-06, 5.4085e-06, 3.4828e-06, 4.3429e-06, 4.5313e-06,\n 1.1860e-05, 3.1790e-06, 3.8689e-06, 3.1170e-06, 4.7214e-06, 3.7788e-06,\n 9.5555e-06, 5.9000e-06, 2.2327e-06, 5.2440e-06, 4.7396e-06, 2.0995e-06,\n 9.8544e-06, 1.0995e-05, 4.5780e-06, 3.7850e-06, 1.0767e-05, 3.5909e-06,\n 5.7444e-06, 4.2645e-06, 2.2786e-06, 1.1202e-05, 2.6134e-06, 4.5569e-06,\n 5.9635e-06, 2.3037e-05, 5.7127e-06, 1.7046e-05, 1.0776e-05, 5.6693e-06,\n 1.0588e-05, 4.9669e-06, 6.5248e-06, 3.9047e-06, 5.9893e-06, 5.2031e-06,\n 6.1381e-06, 3.9816e-06, 3.6825e-06, 5.1431e-06, 5.6550e-06, 7.7736e-06,\n 1.7694e-05, 2.4825e-05, 5.0037e-06, 3.2533e-06, 3.4659e-06, 5.8106e-06,\n 7.6467e-06, 5.0010e-06, 4.1168e-06, 7.3825e-06, 5.9584e-06, 1.4896e-05,\n 4.0550e-06, 5.4686e-06, 5.7656e-06, 6.8164e-06, 5.0594e-06, 5.4847e-06,\n 4.1945e-06, 6.7953e-06, 2.5716e-06, 5.1224e-06, 9.2122e-06, 1.0628e-05,\n 4.7592e-06, 5.2282e-06, 2.9978e-06, 4.6826e-06, 4.0621e-06, 1.1670e-05,\n 3.9011e-06, 1.2765e-05, 4.2674e-06, 7.8979e-06, 2.0880e-06, 4.3577e-06,\n 3.4963e-06, 1.0570e-05, 3.7499e-06, 4.8787e-06, 2.6762e-06, 6.4149e-06,\n 4.3901e-06, 2.4859e-05])}, 59: {'step': 7160, 'exp_avg': tensor([ 1.8547e-04, 1.4562e-06, -9.6517e-05, 4.4507e-05, -2.3680e-04,\n 7.3116e-05, 1.0825e-04, -3.6781e-06, -1.5664e-04, 4.3194e-05,\n 4.2439e-05, 1.0634e-04, 1.6719e-04, 8.7138e-07, 1.3209e-04,\n 1.2440e-05, -7.8220e-05, -2.1816e-05, 7.0857e-05, 5.4192e-05,\n -1.2076e-04, -1.5201e-04, -1.0430e-04, -6.3914e-05, -1.4943e-04,\n 2.3516e-04, 9.8653e-05, 8.5534e-05, -5.3502e-04, -7.8326e-05,\n -1.0519e-04, 2.0104e-05, 4.9469e-05, 2.6843e-05, 2.3747e-04,\n 1.5680e-04, 6.7198e-05, 9.6028e-05, -3.0779e-06, 4.6656e-05,\n 7.0525e-05, 1.8866e-04, 4.7984e-05, 2.6776e-04, 2.6395e-05,\n 9.4255e-05, -3.9917e-05, 8.1427e-05, -3.0095e-04, 2.0710e-04,\n -7.9571e-05, 1.6353e-05, -7.2747e-05, -6.0134e-06, -6.6280e-05,\n -2.6372e-04, -1.1442e-04, 5.8992e-05, -9.1676e-05, 1.4138e-04,\n 1.9482e-05, 7.1882e-05, -2.9366e-05, 2.9139e-04, -4.7388e-05,\n -1.9435e-04, -2.1502e-05, 2.4658e-05, -6.8145e-06, 8.4362e-05,\n 5.4174e-05, 8.1130e-05, 1.8239e-05, -6.6840e-05, -4.5797e-05,\n 1.4243e-05, -1.3450e-05, -4.0037e-05, 1.3249e-04, 2.4702e-05,\n -1.1613e-04, -1.4855e-05, -1.2650e-05, 3.1703e-05, 1.1735e-04,\n 1.2458e-05, 5.8217e-05, -8.5239e-05, -2.3742e-05, -1.8090e-05,\n -1.2733e-04, -5.4341e-05, 1.6387e-05, -3.3652e-04, 2.3618e-04,\n 1.4939e-04, -4.9718e-05, -1.0720e-04, 1.4557e-04, 5.5589e-05,\n 8.0079e-05, -1.6449e-04, 3.8930e-05, 1.4164e-04, -5.7613e-05,\n 3.4705e-06, -8.7099e-05, -1.0458e-04, 8.1773e-05, 7.1583e-05,\n -1.0414e-04, -2.3598e-05, 3.4609e-05, 2.8298e-04, -3.0700e-06,\n -2.6176e-04, 1.4104e-04, 4.2276e-05, -1.1895e-05, -2.3375e-04,\n 8.2068e-05, 1.4882e-04, -1.8424e-04, 9.5137e-05, -8.7097e-05,\n -1.4984e-04, -5.8700e-05, 7.9615e-06]), 'exp_avg_sq': tensor([8.4165e-06, 3.4695e-06, 1.5126e-06, 1.6069e-06, 2.3131e-06, 3.8402e-06,\n 3.6981e-06, 5.7639e-06, 1.7472e-06, 1.2372e-06, 1.5173e-06, 2.6992e-06,\n 3.4685e-06, 9.5261e-07, 4.1815e-06, 1.5540e-06, 1.6598e-06, 1.2840e-06,\n 1.5126e-06, 3.0089e-06, 2.5042e-06, 2.5131e-06, 2.1666e-06, 1.5158e-06,\n 3.0720e-06, 5.8556e-06, 2.5770e-06, 2.9192e-06, 7.3337e-06, 4.7293e-06,\n 7.3176e-07, 3.8301e-06, 8.4870e-06, 1.8469e-06, 2.6560e-06, 7.7567e-06,\n 3.4098e-06, 1.9964e-06, 2.6993e-06, 3.2236e-06, 2.3419e-06, 2.8758e-06,\n 5.6896e-06, 2.9931e-06, 1.8178e-06, 1.8448e-06, 2.8145e-06, 1.6655e-06,\n 4.5776e-06, 2.6444e-06, 1.5979e-06, 2.6193e-06, 4.4991e-06, 1.8356e-06,\n 4.3522e-06, 4.3028e-06, 2.4225e-06, 2.5494e-06, 4.3656e-07, 2.6879e-06,\n 3.7294e-06, 3.0051e-06, 1.0360e-06, 3.8750e-06, 1.7022e-06, 2.7112e-06,\n 2.0523e-06, 2.9467e-07, 4.2979e-06, 3.3350e-06, 3.2266e-06, 4.9524e-06,\n 4.0409e-06, 3.7687e-06, 1.5383e-06, 2.1763e-06, 3.6107e-06, 4.2425e-06,\n 9.1435e-07, 2.7276e-06, 2.5618e-06, 1.7835e-06, 2.8932e-06, 1.7484e-06,\n 2.5811e-06, 6.1679e-06, 3.4696e-06, 2.3143e-06, 1.8432e-06, 1.9404e-06,\n 2.4820e-06, 3.3029e-06, 2.6273e-06, 5.3127e-06, 3.0506e-06, 4.8579e-06,\n 2.3081e-06, 2.1907e-06, 4.3083e-06, 1.2988e-06, 2.1551e-06, 2.6250e-06,\n 3.1287e-06, 3.6851e-06, 1.6843e-06, 1.4975e-06, 2.9801e-06, 4.2171e-06,\n 2.1836e-06, 8.4009e-06, 1.2765e-06, 2.4243e-06, 2.1439e-06, 7.1083e-06,\n 2.0962e-06, 4.3120e-06, 3.4859e-06, 3.9494e-06, 2.1140e-06, 3.3218e-06,\n 2.2002e-06, 3.8297e-06, 3.5473e-06, 2.3281e-06, 2.1594e-06, 3.6871e-06,\n 2.4968e-06, 1.4976e-06])}, 60: {'step': 7160, 'exp_avg': tensor([[[[-1.7921e-05]],\n\n [[-1.7763e-05]],\n\n [[ 5.7368e-05]],\n\n ...,\n\n [[ 1.1285e-05]],\n\n [[-6.8362e-06]],\n\n [[ 1.3623e-05]]],\n\n\n [[[-2.8594e-05]],\n\n [[-1.8719e-05]],\n\n [[-1.2031e-05]],\n\n ...,\n\n [[ 1.4555e-05]],\n\n [[ 1.0282e-05]],\n\n [[-3.2157e-05]]],\n\n\n [[[ 2.6704e-05]],\n\n [[-1.7931e-05]],\n\n [[ 1.9982e-05]],\n\n ...,\n\n [[ 5.3527e-06]],\n\n [[ 3.2408e-05]],\n\n [[ 1.6568e-05]]],\n\n\n ...,\n\n\n [[[ 4.5983e-05]],\n\n [[ 4.5023e-05]],\n\n [[ 6.4409e-05]],\n\n ...,\n\n [[-7.5749e-06]],\n\n [[ 3.5510e-05]],\n\n [[-1.6762e-05]]],\n\n\n [[[ 5.8697e-06]],\n\n [[-1.0118e-06]],\n\n [[-1.8517e-05]],\n\n ...,\n\n [[-1.0588e-05]],\n\n [[-1.9890e-05]],\n\n [[ 1.9937e-05]]],\n\n\n [[[ 2.2057e-05]],\n\n [[ 1.8227e-06]],\n\n [[ 3.3259e-05]],\n\n ...,\n\n [[ 6.1708e-06]],\n\n [[-7.2970e-06]],\n\n [[-6.7806e-06]]]]), 'exp_avg_sq': tensor([[[[7.5338e-08]],\n\n [[1.7897e-07]],\n\n [[1.1918e-07]],\n\n ...,\n\n [[1.1579e-07]],\n\n [[1.5818e-07]],\n\n [[1.8729e-07]]],\n\n\n [[[1.6262e-07]],\n\n [[6.6425e-08]],\n\n [[6.8970e-08]],\n\n ...,\n\n [[9.8353e-08]],\n\n [[9.3008e-08]],\n\n [[2.0483e-07]]],\n\n\n [[[1.8215e-07]],\n\n [[1.4264e-07]],\n\n [[1.4386e-07]],\n\n ...,\n\n [[1.0465e-07]],\n\n [[2.0613e-07]],\n\n [[2.9255e-07]]],\n\n\n ...,\n\n\n [[[2.4770e-07]],\n\n [[2.5317e-07]],\n\n [[1.1580e-07]],\n\n ...,\n\n [[2.9023e-07]],\n\n [[3.5689e-07]],\n\n [[3.9195e-07]]],\n\n\n [[[1.1386e-07]],\n\n [[7.6555e-08]],\n\n [[4.4868e-08]],\n\n ...,\n\n [[6.3944e-08]],\n\n [[7.2673e-08]],\n\n [[1.1563e-07]]],\n\n\n [[[8.5555e-08]],\n\n [[7.7671e-08]],\n\n [[3.4317e-08]],\n\n ...,\n\n [[6.8584e-08]],\n\n [[8.2220e-08]],\n\n [[1.7188e-07]]]])}, 61: {'step': 7160, 'exp_avg': tensor([ 8.3325e-05, 8.5268e-05, -3.5359e-05, -2.1325e-04, -7.6155e-05,\n 5.0323e-05, 6.7999e-05, -2.0337e-04, -3.3255e-05, 1.8642e-04,\n 5.5187e-06, -1.8649e-05, 6.8915e-05, 1.1437e-04, -9.3503e-05,\n 1.6192e-05, -2.8369e-05, 7.1045e-05, 1.1344e-04, 5.6322e-05,\n 9.3255e-05, -1.9031e-04, -1.0889e-04, -2.1555e-04, 1.5493e-04,\n 6.5892e-05, -2.0772e-05, -1.2548e-04, -1.8805e-04, 7.0730e-05,\n -1.2008e-04, 2.0633e-04, 1.2681e-05, 2.8021e-05, 2.0779e-04,\n 7.9636e-05, -3.2700e-04, -8.2633e-05, -1.7353e-05, 5.1238e-05,\n 2.1237e-04, 5.8783e-06, -7.5611e-05, 1.2183e-04, 1.6233e-05,\n 1.2179e-06, -4.0785e-04, -1.6882e-04, 4.1222e-05, 4.5103e-05,\n 7.7327e-05, -6.9673e-05, -7.4376e-05, 7.9138e-05, -1.1591e-04,\n 5.5068e-07, -3.9441e-05, -1.5657e-06, -7.7276e-05, -5.5921e-05,\n 7.3436e-05, 6.2359e-05, 1.1902e-04, -2.0296e-04, -5.2908e-06,\n 1.7236e-04, 3.7169e-05, 6.2388e-05, 1.5569e-05, 4.9203e-05,\n 7.1600e-05, 3.7596e-05, 2.7284e-05, 1.9666e-04, -1.1102e-04,\n -1.0201e-05, -1.1634e-04, 1.8364e-04, 1.9775e-04, -5.6839e-05,\n -1.0234e-05, 5.3435e-05, -9.5686e-05, 1.1288e-04, -6.2457e-05,\n -1.7070e-04, -5.7674e-05, -5.9742e-05, -6.0653e-06, -1.8280e-05,\n 2.6019e-04, -4.1571e-05, -5.4413e-05, -2.4619e-05, -8.7875e-06,\n -7.1722e-06, -1.2198e-04, 1.4608e-05, -5.8754e-05, -2.5503e-04,\n -9.2966e-05, -4.4379e-06, -7.3334e-05, 1.3988e-04, 1.6529e-05,\n 8.8239e-06, -9.9633e-05, 1.1428e-04, -2.2150e-04, -3.6893e-06,\n -2.8814e-08, 1.0628e-04, 2.5851e-05, -2.9858e-07, 1.0916e-04,\n -1.0006e-04, 5.1471e-05, 3.5498e-05, 3.0901e-06, 4.8336e-05,\n -1.2167e-04, 9.2150e-05, 9.9940e-05, -9.5271e-06, -2.0257e-04,\n 1.1039e-04, 1.4228e-04, 1.1538e-04, 5.3823e-05, 7.6718e-05,\n 1.0616e-04, 1.0638e-05, 3.9235e-05, -1.4741e-04, 2.5185e-04,\n -2.5223e-05, -1.5874e-04, -5.0736e-05, 2.0232e-04, 4.3953e-05,\n -4.8358e-06, 1.5143e-04, 7.6195e-05, -2.4385e-05, 9.3226e-05,\n 4.6188e-05, -1.7489e-05, 2.8022e-06, 8.2591e-05, 6.6847e-05,\n -5.8858e-06, 1.4957e-05, -1.4890e-04, -8.8871e-05, -1.8775e-04,\n -3.8959e-05, 1.6364e-04, -3.7451e-05, -1.9224e-06, 1.4744e-05,\n 4.6480e-05, 2.1777e-04, -8.6695e-05, 4.7782e-05, 2.9884e-05,\n -9.1073e-05, -5.7564e-05, -1.6814e-04, -5.0499e-06, -6.5559e-05,\n 5.5064e-05, -1.1109e-04, 2.2772e-05, 1.4526e-05, 1.5955e-04,\n 3.4929e-05, 9.5908e-05, -1.7809e-05, 8.7538e-05, 5.1436e-05,\n -2.4758e-05, -8.9167e-06, -1.0000e-04, -1.9562e-04, -5.6628e-05,\n 5.7016e-05, -1.6855e-04, -8.2920e-05, -1.1660e-04, -1.6971e-04,\n 6.6013e-05, 3.1248e-05, 4.8950e-05, -7.0904e-05, -7.5238e-05,\n 3.9111e-06, 2.8804e-04, 4.4654e-05, 1.3149e-05, -2.2320e-04,\n -1.3104e-04, -9.3878e-05, 2.1733e-05, 4.1068e-05, 2.2816e-04,\n -4.2985e-05, 3.9928e-05, -1.1958e-04, 3.3608e-05, 1.5821e-04,\n 1.4068e-04, 2.9461e-05, -2.0870e-05, 2.8328e-04, -1.2038e-04,\n 7.7048e-05, 1.3078e-04, -3.0740e-04, 2.4851e-04, -3.1869e-05,\n 1.7652e-04, 4.3446e-05, -7.7403e-05, -1.1610e-04, -5.1505e-05,\n 9.0221e-05, 1.4331e-04, -1.1548e-04, 1.6663e-04, -3.2540e-04,\n -3.3455e-05, -4.1155e-05, -2.2681e-05, 5.7458e-06, 3.2043e-04,\n 7.6723e-05, -1.2409e-04, 8.1627e-05, 2.1757e-04, -9.5217e-06,\n 2.6413e-05, -2.6422e-05, -2.7751e-04, -9.9177e-05, -1.5861e-05,\n 1.1374e-04, -7.4865e-05, 9.5629e-05, 6.0140e-05, -8.8675e-05,\n 8.3058e-05, 4.6941e-04, 2.5109e-04, 1.1327e-04, -1.1411e-04,\n 1.9724e-05, 7.3841e-05, -8.6024e-05, -1.9280e-04, 1.3377e-05,\n -2.2763e-04, 1.0234e-05, 1.5758e-04, 9.7702e-05, -4.3601e-05,\n 4.1575e-05, 1.2217e-05, 5.8825e-05, -1.4863e-04, -4.9550e-05,\n 1.0925e-04, 2.4748e-05, 8.8040e-05, -3.1900e-04, 5.8662e-05,\n 6.9038e-05, -1.5257e-05, 2.3718e-05, -9.8952e-05, -1.0921e-04,\n -3.0598e-05, -1.4836e-04, 3.4707e-05, 2.9302e-05, -2.3352e-05,\n -5.2420e-05, -1.1527e-04, 6.0957e-05, -1.6677e-04, -2.3599e-05,\n 1.2893e-04, 1.7699e-04, 1.7654e-04, -7.6522e-06, 1.4985e-05,\n -8.0663e-05, 1.8743e-04, -1.8732e-04, -7.5567e-05, -1.1066e-04,\n -1.3587e-04, 3.9248e-05, -2.9765e-05, -2.2240e-04, -3.2408e-05,\n -1.3750e-04, 2.7900e-08, 5.8505e-05, 9.6535e-05, -2.3492e-05,\n -1.6778e-04, 8.7668e-05, 6.1146e-05, 2.3955e-04, 9.0170e-05,\n 2.1949e-04, -1.3452e-04, -1.8698e-04, 4.1545e-04, -6.9207e-05,\n 2.0250e-04, -1.7069e-04, -1.6363e-05, 5.7343e-05, 4.1995e-05,\n 2.6125e-04, -9.9982e-05, 3.9933e-05, -2.2127e-04, -3.5246e-04,\n -2.0875e-04, -1.8471e-05, -1.7370e-04, -5.6731e-05, -3.1561e-04,\n 6.9799e-05, -2.6276e-04, 9.7888e-05, 4.8318e-06, -8.5830e-05,\n 5.0176e-05, -1.7901e-04, 1.5128e-04, 7.5923e-05, 1.0332e-04,\n -1.4054e-04, -1.4451e-04, -2.5740e-05, 5.7931e-05, -1.1821e-04,\n 3.4623e-05, -2.8031e-05, -7.6138e-05, -1.0115e-04, 5.0356e-05,\n 5.7936e-05, 9.2105e-06, 1.0822e-03, -8.0547e-05, 1.1445e-04,\n -2.3484e-04, -1.5540e-04, -1.1559e-04, -2.2947e-05, 2.7058e-05,\n -5.3845e-05, -6.2949e-05, 1.6148e-05, 1.4249e-04, -8.1989e-05,\n -1.2662e-04, -1.0536e-04, -7.1571e-06, 5.7073e-05, -1.1226e-04,\n -5.4508e-05, 2.5596e-05, -8.3674e-05, 1.3687e-04, -8.7749e-06,\n 4.5193e-04, 1.0241e-04, 1.0466e-04, -8.9433e-05, -8.6210e-06,\n -7.6245e-05, -1.1759e-04, 6.2867e-05, -5.5216e-06, 8.6606e-05,\n 1.2237e-04, -1.2847e-04, -2.3463e-05, 1.9765e-05, 3.1973e-04,\n 1.7024e-04, -1.0831e-04, -5.0828e-06, -1.4393e-04, -8.5577e-05,\n 3.4006e-04, 4.3825e-04, -1.2640e-04, -1.4949e-04, -2.6076e-05,\n -7.4270e-05, 2.6637e-04, -1.2290e-04, 4.3987e-05, -3.2634e-05,\n 2.8038e-05, -4.2825e-07, 1.9293e-05, 1.1781e-04, -3.9609e-04,\n -9.4400e-05, 9.2712e-05, -4.0540e-05, -1.6124e-04, -1.5911e-04,\n 8.7568e-05, 3.1989e-04, 5.2824e-05, 6.7374e-05, 1.1102e-04,\n 7.3833e-05, 7.5705e-05, 2.2210e-05, -9.0724e-05, -4.8057e-05,\n 7.2508e-05, 2.0033e-04, -4.8385e-06, -7.2683e-05, -3.0181e-05,\n 7.8429e-06, 5.3387e-06, 7.5256e-06, 5.5932e-05, -1.3801e-04,\n -1.3252e-04, 7.8023e-05, 1.9923e-05, 2.0321e-04, 7.1561e-06,\n 9.4525e-05, -2.2442e-04, 8.4561e-05, 2.0277e-04, 9.0214e-05,\n 3.2699e-04, 9.6161e-05, -1.5834e-05, 7.0249e-05, -1.4287e-04,\n -2.3164e-05, -9.4388e-05, -8.2362e-05, 5.1143e-05, -1.5051e-05,\n -1.4709e-04, -2.2096e-05, 4.3645e-05, -1.2559e-05, 1.9696e-04,\n 7.7289e-05, -5.8942e-05, -6.6577e-05, -1.6098e-06, 6.9234e-05,\n -1.1049e-04, 7.3486e-04, 3.5854e-05, -1.3875e-05, -6.9731e-05,\n -2.4437e-04, -1.0057e-04, -6.8854e-05, -1.4151e-04, -1.2130e-06,\n -2.2537e-05, 5.4450e-05, -1.6104e-04, 9.9374e-05, 6.4394e-05,\n 2.9565e-05, 1.3382e-04, -2.4262e-04, 1.2949e-04, 4.2367e-05,\n -1.7782e-04, -9.0305e-06, -3.9414e-05, -7.2232e-05, 5.2908e-07,\n -1.7376e-05, -4.3928e-05, 3.3602e-04, -2.7873e-04, -8.9139e-05,\n 6.7158e-06, 1.6314e-05, -1.6356e-04, 1.1468e-04, -2.4861e-06,\n 1.3802e-04, -5.1061e-05, 1.6221e-04, 1.1148e-04, -8.7174e-05,\n -4.2504e-05, 4.2551e-05]), 'exp_avg_sq': tensor([2.2339e-06, 2.9114e-06, 2.5441e-06, 2.8251e-06, 1.1965e-06, 1.7726e-05,\n 2.1724e-06, 1.8207e-06, 5.3218e-07, 1.5383e-06, 1.5338e-06, 1.3231e-06,\n 1.8873e-06, 3.8836e-06, 1.4054e-06, 1.2125e-06, 4.5928e-06, 3.8487e-06,\n 2.1134e-06, 1.9496e-06, 1.6085e-06, 3.5451e-06, 1.6365e-06, 8.1756e-06,\n 2.6607e-06, 2.0578e-06, 1.2147e-06, 2.8647e-06, 1.6694e-06, 4.0807e-06,\n 1.1119e-06, 8.2747e-06, 4.5705e-06, 1.4859e-06, 3.0897e-06, 1.8393e-06,\n 3.1841e-05, 1.7755e-06, 2.8868e-06, 7.0880e-06, 2.9756e-06, 2.4143e-06,\n 2.9980e-06, 8.3912e-07, 2.0482e-06, 2.5611e-06, 9.8423e-06, 2.1266e-06,\n 1.8709e-06, 1.9191e-06, 6.3417e-07, 1.6116e-06, 2.7144e-06, 2.0776e-06,\n 1.0163e-06, 1.8071e-06, 1.8649e-06, 2.1903e-06, 4.2035e-06, 1.6572e-06,\n 2.1564e-06, 2.7579e-06, 1.7452e-06, 5.5125e-06, 9.2046e-07, 3.2915e-06,\n 1.0467e-06, 1.3710e-06, 1.3802e-06, 1.7495e-06, 2.1277e-06, 5.0876e-06,\n 3.2229e-06, 2.6142e-06, 2.2747e-06, 1.6621e-06, 2.8599e-06, 1.7790e-06,\n 1.0312e-05, 2.0170e-06, 3.1252e-06, 1.6803e-06, 1.2397e-06, 2.1396e-06,\n 2.5013e-06, 3.9730e-06, 1.6872e-06, 9.4012e-06, 3.6036e-06, 2.2269e-06,\n 2.7864e-06, 2.2171e-06, 1.2056e-06, 3.7648e-06, 2.6314e-06, 1.5576e-06,\n 1.9598e-06, 2.9481e-06, 1.1847e-06, 5.3781e-06, 2.3842e-06, 8.9537e-07,\n 1.6032e-06, 2.1649e-06, 4.4276e-06, 5.4790e-06, 2.4234e-06, 1.7607e-06,\n 5.2221e-06, 3.4116e-06, 2.0399e-06, 2.4748e-06, 1.4163e-06, 2.5617e-06,\n 3.6851e-06, 4.1057e-06, 1.8582e-06, 1.2197e-06, 5.2683e-06, 1.7740e-06,\n 1.9240e-06, 1.8247e-06, 2.6181e-06, 1.6712e-06, 1.9244e-06, 9.8450e-06,\n 2.6761e-06, 4.7489e-06, 1.9786e-06, 2.2571e-06, 3.8088e-06, 1.6800e-06,\n 3.1035e-06, 5.9765e-06, 4.6885e-06, 1.7147e-06, 1.9195e-06, 1.2957e-06,\n 1.0605e-05, 1.5998e-06, 1.8074e-06, 3.9371e-06, 1.1247e-06, 1.6264e-06,\n 4.0524e-06, 1.0212e-06, 1.3277e-06, 1.1759e-06, 2.2112e-06, 8.2892e-07,\n 2.1850e-06, 2.3552e-06, 2.8546e-06, 2.2683e-06, 4.6332e-06, 3.9083e-06,\n 6.5257e-06, 2.4312e-06, 2.2560e-06, 1.5845e-06, 3.8363e-06, 1.1563e-05,\n 2.7580e-06, 1.1666e-06, 5.5080e-06, 6.4871e-06, 1.1203e-06, 1.9203e-06,\n 2.0446e-06, 2.5848e-06, 1.9451e-05, 1.1091e-05, 7.7272e-06, 9.0823e-06,\n 1.9672e-06, 1.8859e-06, 1.6806e-06, 1.6946e-06, 7.4865e-07, 1.4735e-06,\n 1.2143e-06, 4.3134e-06, 7.4236e-06, 3.2815e-06, 1.9250e-06, 4.1405e-06,\n 4.5572e-06, 4.2890e-06, 5.5846e-06, 4.0504e-06, 3.0218e-06, 2.0914e-06,\n 1.1239e-06, 7.9701e-06, 3.3454e-06, 1.9948e-06, 2.2693e-06, 1.5234e-06,\n 1.8681e-06, 3.8772e-06, 5.9858e-06, 4.2446e-06, 1.7031e-06, 1.3887e-06,\n 2.6502e-06, 1.7652e-06, 2.0938e-06, 2.0309e-06, 8.1567e-06, 2.5394e-06,\n 2.4738e-06, 3.8525e-06, 4.5527e-06, 9.6498e-06, 2.4513e-06, 1.6767e-06,\n 2.1105e-06, 1.3360e-05, 4.3066e-06, 1.6424e-06, 1.4494e-06, 1.8530e-06,\n 3.0346e-06, 1.9552e-06, 3.1749e-06, 1.6231e-06, 1.7284e-06, 2.1263e-06,\n 2.8605e-06, 2.9130e-06, 4.3857e-06, 2.4488e-06, 4.9646e-06, 1.3093e-06,\n 1.4329e-05, 4.1394e-06, 2.3903e-06, 4.0148e-06, 2.8491e-06, 2.8725e-06,\n 1.8557e-05, 1.5613e-06, 3.8152e-06, 2.1275e-06, 5.2723e-06, 9.8342e-07,\n 2.0004e-06, 2.2193e-06, 2.8672e-06, 2.0843e-06, 1.6443e-06, 3.5165e-05,\n 2.7965e-06, 1.5102e-06, 1.7336e-06, 2.7146e-06, 1.3191e-06, 1.9859e-06,\n 3.1839e-06, 2.0122e-06, 1.7977e-06, 2.7957e-06, 1.5853e-06, 1.4395e-06,\n 2.2339e-06, 1.8282e-05, 6.4896e-06, 7.4487e-07, 5.1092e-06, 2.2739e-06,\n 7.2443e-06, 4.0698e-06, 4.7741e-06, 4.7894e-06, 2.4461e-06, 4.2495e-06,\n 2.5742e-06, 1.7376e-06, 1.4547e-06, 2.8728e-06, 6.9342e-07, 3.6370e-06,\n 1.9822e-06, 1.9695e-06, 1.1995e-06, 3.2525e-06, 1.6779e-06, 2.0229e-06,\n 1.7553e-06, 1.4311e-06, 7.5564e-06, 3.5347e-06, 1.1482e-06, 7.4083e-07,\n 1.4902e-06, 1.4065e-06, 2.3349e-06, 3.7851e-06, 3.0615e-06, 1.0402e-06,\n 2.0397e-06, 1.2921e-06, 1.3985e-06, 3.0088e-06, 8.0468e-07, 2.0381e-06,\n 1.0570e-06, 1.2505e-06, 2.0218e-06, 3.7744e-07, 2.1594e-06, 4.4848e-06,\n 4.1242e-06, 1.2072e-05, 1.5974e-06, 4.0868e-06, 3.2057e-06, 1.3733e-05,\n 7.5258e-06, 1.4234e-06, 2.5334e-06, 4.1686e-06, 3.6216e-06, 2.5896e-06,\n 2.9807e-06, 5.7554e-06, 1.9792e-06, 1.0825e-06, 3.0327e-06, 1.1021e-05,\n 3.5798e-06, 9.4937e-06, 1.3180e-06, 1.6336e-06, 2.5661e-06, 2.7671e-06,\n 2.1282e-06, 1.3050e-06, 1.3691e-06, 1.1653e-06, 7.9828e-06, 6.2367e-06,\n 3.7088e-06, 1.9975e-06, 5.0387e-06, 3.4353e-06, 8.7882e-06, 2.1310e-06,\n 2.3288e-06, 7.9227e-06, 1.9380e-06, 2.0787e-06, 3.8951e-06, 8.0799e-07,\n 5.9016e-06, 1.5803e-06, 1.5819e-06, 2.9874e-05, 2.1784e-06, 3.3706e-06,\n 2.0561e-06, 1.9290e-06, 1.5495e-06, 3.1366e-06, 1.6712e-06, 1.3408e-06,\n 2.8418e-06, 2.0700e-06, 3.4649e-06, 1.8343e-06, 4.8777e-06, 1.9071e-06,\n 2.6364e-06, 2.3483e-06, 4.8920e-06, 2.0055e-06, 1.2156e-06, 3.3759e-06,\n 1.8662e-06, 9.7681e-07, 5.2126e-06, 1.9525e-06, 1.2445e-06, 2.3380e-06,\n 3.6819e-06, 1.4881e-06, 1.9452e-06, 1.5737e-06, 5.6448e-06, 2.1457e-06,\n 1.9284e-06, 2.7115e-06, 3.5420e-06, 9.5347e-07, 4.3487e-06, 3.1644e-06,\n 4.3194e-06, 1.0903e-06, 1.9838e-06, 4.6700e-06, 1.3006e-05, 1.1449e-05,\n 3.9999e-06, 2.3408e-06, 1.7935e-06, 3.2122e-06, 6.2864e-06, 2.3825e-06,\n 1.4414e-06, 2.6062e-06, 1.2007e-06, 2.8900e-06, 1.4455e-06, 1.5378e-06,\n 1.0094e-05, 2.4700e-06, 1.0109e-06, 2.9892e-06, 1.9473e-06, 9.6532e-06,\n 1.4977e-06, 5.7934e-06, 9.0607e-07, 1.7520e-06, 5.0360e-06, 1.4329e-06,\n 3.8105e-06, 3.5641e-06, 6.6102e-06, 9.1954e-07, 2.8121e-06, 1.5464e-06,\n 2.7813e-06, 3.3619e-06, 3.7976e-06, 1.3323e-06, 1.1723e-06, 2.7030e-06,\n 1.0267e-06, 2.4956e-06, 2.3281e-06, 3.1350e-06, 1.0520e-06, 8.1206e-06,\n 1.8333e-06, 2.5591e-06, 1.6243e-06, 2.1913e-06, 3.2892e-06, 1.2476e-06,\n 6.3141e-06, 2.1549e-06, 2.3115e-06, 2.9934e-06, 1.4141e-06, 1.2575e-06,\n 3.0836e-06, 2.3830e-06, 3.5891e-06, 1.2513e-05, 1.3686e-06, 2.9877e-06,\n 7.0590e-07, 1.8209e-06, 4.1788e-06, 4.0238e-06, 2.5006e-06, 5.5025e-06,\n 1.4145e-06, 1.7974e-06, 1.2214e-06, 1.3663e-05, 2.3412e-05, 6.4183e-06,\n 1.7433e-06, 2.0418e-06, 4.1548e-06, 9.2831e-07, 5.0945e-06, 2.7061e-06,\n 1.6298e-06, 2.9143e-06, 4.5387e-06, 2.7008e-06, 2.4546e-06, 2.1238e-06,\n 2.3426e-06, 2.4422e-06, 1.1042e-06, 5.7653e-06, 1.9141e-06, 5.4487e-06,\n 2.2096e-06, 2.4248e-06, 2.9331e-06, 1.0184e-06, 3.2771e-06, 2.5316e-06,\n 9.2642e-06, 5.1482e-06, 1.0272e-06, 2.6678e-06, 1.8617e-06, 1.2431e-06,\n 2.2579e-06, 1.3267e-06, 1.0985e-06, 2.0881e-06, 2.2842e-06, 7.9688e-06,\n 1.9446e-06, 2.0791e-06])}, 62: {'step': 7160, 'exp_avg': tensor([-2.1911e-05, 3.9180e-05, 6.8094e-05, -1.3725e-04, 2.3010e-06,\n -7.2801e-05, 7.6999e-06, -1.0191e-04, -4.5289e-05, 4.0109e-05,\n -3.9897e-05, 4.2593e-05, 6.7750e-05, -3.5313e-05, 5.5807e-06,\n -6.3669e-05, -3.5422e-05, 7.1237e-06, 1.5545e-04, 5.8091e-05,\n 3.8677e-05, -8.7419e-05, 2.6018e-05, -2.4252e-04, 5.6333e-05,\n -1.9988e-05, -3.8007e-05, -6.1874e-05, -2.4268e-04, 4.9028e-05,\n 7.2604e-05, -6.8596e-05, -5.3244e-05, -4.2440e-06, -9.3975e-05,\n -5.4424e-05, 8.6556e-11, -7.7635e-05, 9.8887e-05, 8.4845e-05,\n -1.4114e-05, -3.9917e-05, -1.5534e-05, -1.0730e-05, 7.2391e-05,\n -2.4698e-05, -7.1527e-05, -7.3336e-05, -4.3644e-05, 3.3500e-05,\n 3.4651e-05, 2.8353e-05, 2.4371e-05, 5.3440e-05, -1.3110e-05,\n 2.6129e-05, 1.1555e-05, -4.4896e-05, -1.3696e-04, -3.4422e-05,\n 7.3710e-05, -1.2586e-04, 6.7228e-05, -5.2475e-05, 3.1498e-06,\n 5.0550e-05, 2.8487e-05, 4.9604e-05, 3.7620e-05, 4.6606e-05,\n 1.0389e-04, 5.1088e-05, 5.4418e-05, 8.8424e-05, -3.4652e-05,\n -1.5547e-05, 4.1039e-06, -9.5691e-06, -1.5216e-05, 6.7788e-05,\n -1.5113e-05, -7.6775e-05, -4.4946e-05, -1.6823e-05, -1.7001e-04,\n 7.8649e-05, -1.1254e-05, 2.3361e-05, 1.6677e-04, -2.2419e-05,\n 1.2953e-04, -1.8389e-05, -2.0990e-05, -3.2243e-04, 5.0716e-05,\n 1.6055e-05, -4.6499e-05, -3.3646e-05, -1.5313e-05, -1.5348e-05,\n -1.5137e-04, 5.3065e-05, -8.3719e-05, 6.3644e-05, 1.4002e-04,\n -1.0226e-04, 3.8008e-05, 6.1092e-06, -1.1607e-04, -8.7194e-05,\n -8.4663e-06, 2.0871e-04, 1.6704e-05, -1.7419e-05, 1.8896e-04,\n 9.6803e-05, 1.9432e-05, -4.0903e-05, -8.4157e-05, 5.8913e-05,\n -1.1021e-04, 2.6190e-06, -3.3129e-05, -7.4663e-05, -1.2414e-04,\n -4.6866e-05, 1.2902e-04, -1.1476e-05, 3.5767e-05, 4.5390e-05,\n 1.4032e-04, -6.2861e-05, -3.2225e-05, -6.3101e-06, 6.2726e-05,\n -4.6559e-05, 2.1537e-06, 4.9015e-05, 3.9454e-05, 2.2441e-05,\n 5.0856e-05, 1.0072e-04, 1.2967e-04, 2.1477e-05, 2.8163e-06,\n 6.6761e-06, 4.1439e-05, -2.8190e-05, 1.3883e-05, 9.5957e-05,\n 3.0033e-05, -4.6092e-05, 2.7456e-05, -5.8302e-05, 2.9144e-05,\n 4.5342e-05, -8.7037e-05, 8.6677e-05, 3.7159e-05, -8.4929e-06,\n 5.6206e-05, 9.9826e-05, 6.1523e-05, 1.3316e-04, 4.3939e-05,\n -2.4758e-04, 1.2257e-04, 2.5985e-05, -2.7107e-05, 2.7632e-05,\n 1.0311e-04, -4.6178e-05, 7.0639e-08, 2.1892e-05, 1.2883e-04,\n -7.3675e-05, 1.0868e-05, 5.2382e-05, 2.6592e-05, -5.5809e-06,\n 6.9104e-06, -5.9631e-05, -2.7352e-05, 3.8981e-06, -8.4553e-05,\n 1.8936e-05, -8.5153e-05, -1.3332e-04, -1.3479e-04, 3.8059e-05,\n -8.1515e-05, 1.5635e-05, 9.5034e-05, -1.6551e-05, 3.2729e-05,\n 1.0061e-04, 4.3764e-05, -1.1986e-05, 2.4997e-05, -8.8428e-06,\n 7.9952e-06, -7.6050e-05, -5.3712e-05, 6.7630e-05, 1.0951e-04,\n -4.8138e-05, -5.3140e-05, -9.9787e-05, 1.8689e-05, 2.0086e-05,\n 2.4289e-06, -2.1727e-06, 2.9037e-06, 9.6915e-05, 6.8819e-05,\n 4.5836e-05, 3.4506e-05, -2.2708e-04, 8.3904e-05, -4.6523e-05,\n -6.9269e-05, -1.9912e-05, -1.0549e-05, -6.2879e-05, -6.8633e-05,\n -6.8817e-06, 6.0166e-05, 1.0398e-05, 1.1167e-04, 5.2409e-05,\n 9.0679e-06, 1.0908e-04, 1.7728e-06, 6.6199e-05, -8.4993e-05,\n 2.5001e-05, -2.0743e-05, -1.1363e-04, 3.0511e-05, 8.5002e-05,\n -1.5986e-04, -3.6140e-05, -2.0430e-05, 1.2805e-04, 3.3077e-05,\n 1.0548e-04, -5.5677e-06, -4.8589e-05, 6.7006e-05, -4.5622e-05,\n 7.2925e-05, 1.3422e-04, 1.1475e-04, 5.8576e-05, -8.7912e-06,\n -4.2757e-05, 9.5382e-05, 4.4247e-06, -3.4364e-06, 7.6642e-05,\n -1.4272e-04, 5.1098e-06, 1.4854e-04, 8.2511e-05, -7.8451e-05,\n -1.5765e-04, 2.0256e-04, -6.1366e-05, -6.2686e-05, 7.7536e-05,\n -1.6432e-05, -7.4246e-05, -1.4610e-04, -1.6543e-04, 2.7470e-05,\n 1.4375e-05, 1.4129e-05, 3.6172e-05, -1.0602e-04, -8.7734e-05,\n -1.5853e-05, -1.2039e-04, 1.0303e-04, 9.0646e-06, -2.1354e-06,\n 1.8847e-04, -3.4263e-06, 5.7999e-05, -5.9562e-05, 2.7368e-06,\n 7.7085e-06, 9.8858e-05, 5.8886e-05, 3.3562e-05, 9.4193e-05,\n 1.2497e-04, 4.7433e-05, 1.3861e-04, -1.1023e-05, -8.0421e-05,\n -8.1645e-05, -3.1326e-05, -1.0265e-05, -4.6640e-05, 4.6139e-05,\n 1.0509e-04, 2.0110e-05, -6.1963e-06, 5.6487e-05, 3.2389e-05,\n -1.1996e-04, 1.1857e-05, -2.3692e-05, -1.2542e-05, 4.6038e-05,\n 8.8232e-06, -1.0158e-04, -1.0506e-04, 2.8952e-04, 2.3536e-05,\n 2.2125e-05, -8.0693e-05, 3.2288e-05, 5.9815e-05, 9.9173e-05,\n 7.5593e-05, 4.1155e-05, 5.8342e-05, -1.5101e-05, -5.8513e-05,\n -3.3301e-05, -5.7416e-05, -1.2777e-04, -4.0679e-05, -1.4800e-04,\n 4.2765e-05, -2.4229e-06, 6.8486e-05, 2.7493e-05, -1.5570e-04,\n 6.0268e-05, -5.3001e-05, 7.5440e-05, 6.7262e-05, 1.6184e-04,\n 8.3081e-05, -5.6269e-05, 5.5503e-05, 4.7176e-05, -5.0366e-05,\n -1.1197e-04, 4.9100e-05, -1.4704e-05, -1.1877e-04, -3.2682e-05,\n 7.6039e-06, 5.4332e-06, 1.4037e-04, -3.7005e-05, -6.9020e-06,\n -2.6181e-05, -9.5357e-05, -9.2039e-05, 2.0454e-05, -4.4048e-05,\n 2.1421e-05, -3.8577e-05, 4.8427e-05, -2.8295e-05, 5.0793e-05,\n -1.0451e-04, -2.3005e-05, -4.3928e-06, -4.9071e-05, 8.3118e-05,\n -1.2053e-04, -7.8626e-06, 7.5282e-06, 1.3374e-04, 2.7331e-06,\n -9.1182e-05, 9.3468e-05, 6.4736e-05, -3.2384e-05, 3.9881e-05,\n -2.7657e-05, -1.9216e-06, 3.4449e-05, 3.4108e-05, 3.6911e-05,\n 3.5748e-05, -4.7282e-05, -5.1918e-05, 6.0666e-06, 8.4267e-05,\n 1.1166e-05, -1.7557e-04, 2.8899e-05, 5.2606e-05, -1.2248e-04,\n 1.9382e-04, -1.5573e-04, -7.8096e-05, -1.8758e-05, 4.8366e-05,\n 2.8893e-05, -2.9465e-05, -6.1084e-05, 9.1893e-05, -4.6092e-05,\n 7.2916e-05, 1.2454e-05, 7.1832e-06, 7.8001e-06, -8.7619e-05,\n -1.5440e-05, 5.6491e-05, -4.1573e-05, -8.6738e-05, -8.0619e-05,\n -1.3979e-05, 6.3068e-05, -5.6310e-05, -3.3782e-05, 7.3226e-05,\n -5.6026e-06, -6.5305e-05, 1.2338e-04, 1.3339e-05, -7.4486e-05,\n 5.2348e-05, 1.9453e-05, 1.0836e-05, 8.3434e-05, -5.8748e-05,\n -2.9612e-05, 2.8267e-06, 2.3921e-05, -5.5093e-06, 4.9334e-05,\n 2.4286e-05, 3.1555e-05, 8.5583e-05, 1.0715e-04, -1.1935e-05,\n 5.7231e-05, -2.7518e-05, 6.5023e-05, 3.5179e-05, 1.2131e-04,\n 1.6990e-04, 5.3539e-05, -7.8427e-05, 4.4693e-05, -6.0584e-06,\n -3.7311e-05, 1.1227e-04, -1.4603e-05, 7.5079e-05, 5.9122e-05,\n -4.9987e-05, -3.4573e-05, -2.0432e-05, -3.9505e-05, 2.9087e-05,\n 6.2882e-05, -1.7059e-05, 2.7740e-05, -1.4011e-05, -3.1079e-06,\n -1.2626e-04, 1.4617e-04, 3.6503e-06, 1.3067e-04, -5.1966e-05,\n -4.8470e-06, 9.3120e-05, -1.9521e-05, -3.4904e-05, -2.0141e-05,\n -4.1698e-05, 4.2110e-05, -1.7306e-04, -4.2352e-05, -3.4392e-05,\n 2.9817e-05, 3.3327e-05, 1.1895e-06, 2.7267e-05, -2.2043e-06,\n -5.7167e-05, 6.4602e-05, -1.1621e-05, -3.7932e-05, -7.4771e-06,\n -3.4223e-05, -3.1059e-05, 1.1828e-04, 6.6148e-05, 1.0465e-04,\n 1.5357e-05, 6.9370e-05, -5.8218e-05, 1.2786e-04, -3.7778e-05,\n 4.9341e-05, 1.6626e-05, 1.3618e-04, 5.6837e-05, -9.6539e-05,\n -2.2936e-05, 8.4471e-05]), 'exp_avg_sq': tensor([9.6294e-07, 4.4486e-07, 1.6109e-06, 1.0848e-06, 5.7690e-07, 1.1302e-06,\n 9.3522e-07, 8.8218e-07, 2.5746e-07, 1.4134e-06, 5.6485e-07, 6.5060e-07,\n 9.1880e-07, 2.1319e-07, 6.5308e-07, 6.5773e-07, 4.0059e-07, 8.4299e-07,\n 9.9059e-07, 1.2597e-06, 4.2301e-07, 8.0167e-07, 1.1253e-06, 2.7586e-06,\n 1.5504e-06, 9.7750e-07, 7.1795e-07, 8.1078e-07, 1.4218e-06, 1.4882e-06,\n 6.1867e-07, 5.0453e-06, 1.9063e-06, 6.1193e-07, 2.5203e-06, 9.7022e-07,\n 2.6606e-10, 1.3839e-06, 9.1946e-07, 2.5642e-06, 1.0868e-06, 7.2120e-07,\n 1.4643e-06, 6.3799e-07, 9.2667e-07, 6.8351e-07, 2.3100e-06, 1.0193e-06,\n 5.7906e-07, 1.0099e-06, 3.7997e-07, 1.3131e-06, 9.5092e-07, 6.9118e-07,\n 9.3398e-07, 5.2057e-07, 4.5451e-07, 1.0829e-06, 2.2367e-06, 1.2865e-06,\n 1.1295e-06, 7.7612e-07, 7.9092e-07, 7.8114e-07, 6.0560e-07, 1.0829e-06,\n 5.5806e-07, 5.8946e-07, 9.2521e-07, 7.6989e-07, 7.4382e-07, 1.0256e-06,\n 1.1267e-06, 1.3043e-06, 1.0096e-06, 1.4275e-06, 1.1979e-06, 1.4091e-06,\n 2.2198e-06, 8.0730e-07, 1.2799e-06, 8.2450e-07, 7.1370e-07, 6.7945e-07,\n 9.2225e-07, 1.1488e-06, 8.2639e-07, 3.7347e-06, 1.8927e-06, 1.2465e-06,\n 1.1734e-06, 9.6641e-07, 4.9237e-07, 3.2612e-06, 1.5490e-06, 7.6384e-07,\n 1.4767e-06, 1.4501e-06, 7.0621e-07, 2.4312e-07, 8.9204e-07, 5.7021e-07,\n 1.4174e-06, 7.5217e-07, 1.1181e-06, 1.1770e-06, 1.6557e-06, 6.2548e-07,\n 5.8649e-07, 1.4710e-06, 1.2859e-06, 1.7391e-06, 1.3118e-06, 1.3084e-06,\n 1.8437e-06, 1.5739e-06, 9.4157e-07, 7.1107e-07, 1.2902e-06, 8.8461e-07,\n 8.3993e-07, 1.1359e-06, 1.3530e-06, 9.9141e-07, 1.0808e-06, 2.3217e-06,\n 1.3714e-06, 2.4398e-06, 6.9475e-07, 8.4000e-07, 1.2700e-06, 5.6912e-07,\n 4.8131e-07, 7.7878e-07, 1.4588e-07, 1.3477e-06, 7.9093e-07, 9.0580e-07,\n 3.1175e-06, 8.7184e-07, 8.1788e-07, 1.7789e-06, 5.7047e-07, 1.3650e-06,\n 7.3564e-08, 1.6060e-06, 7.7614e-07, 7.5306e-07, 1.1327e-06, 6.6508e-07,\n 1.2495e-06, 1.5222e-06, 1.2911e-06, 8.4911e-07, 7.8215e-07, 1.1755e-06,\n 7.4155e-06, 1.6693e-06, 7.4804e-07, 7.7926e-07, 9.3408e-07, 3.6266e-06,\n 1.2733e-06, 7.7255e-07, 5.2904e-07, 2.6929e-06, 9.2120e-07, 1.4848e-06,\n 6.8608e-07, 9.6795e-07, 8.0469e-06, 1.4579e-06, 1.8460e-08, 1.2525e-07,\n 7.8988e-07, 1.1561e-06, 9.2532e-07, 1.3190e-06, 4.9670e-07, 5.2617e-07,\n 5.0734e-07, 8.7776e-07, 1.5439e-06, 1.1300e-06, 1.0696e-06, 1.9235e-06,\n 1.9175e-06, 1.0804e-06, 2.9615e-06, 6.1303e-08, 1.8471e-06, 6.0389e-07,\n 5.4868e-07, 2.4992e-06, 7.4046e-07, 9.0802e-07, 1.6684e-06, 7.3831e-07,\n 1.8383e-06, 3.9669e-07, 2.1368e-06, 9.9042e-07, 1.4024e-06, 6.9785e-07,\n 1.7965e-06, 8.6192e-07, 1.7081e-06, 9.2685e-07, 2.2777e-06, 1.2040e-06,\n 6.5308e-07, 1.2663e-06, 2.6832e-06, 2.5934e-06, 9.4442e-07, 9.9602e-07,\n 1.1692e-06, 4.3012e-06, 2.0330e-06, 1.1814e-06, 6.1743e-07, 8.4433e-07,\n 7.7613e-07, 1.1614e-06, 8.2789e-07, 9.5018e-07, 1.0108e-06, 4.9534e-07,\n 1.1789e-06, 1.0921e-06, 2.0624e-06, 1.3024e-06, 1.5037e-06, 9.5463e-07,\n 3.3329e-06, 1.1090e-06, 1.8400e-06, 3.3294e-06, 1.7373e-06, 2.4419e-06,\n 3.0765e-06, 6.5082e-07, 7.9642e-07, 1.5288e-06, 1.1417e-06, 7.2983e-07,\n 6.8342e-07, 1.3732e-06, 1.3587e-06, 1.1685e-06, 6.0321e-07, 9.3636e-06,\n 1.2997e-06, 6.2429e-07, 6.1861e-07, 6.0341e-07, 7.8461e-07, 6.4728e-07,\n 1.1487e-06, 9.7893e-07, 5.9388e-07, 1.0283e-06, 9.0649e-07, 1.4323e-06,\n 1.0363e-06, 8.4832e-06, 2.0315e-06, 8.3100e-07, 5.6820e-06, 2.7022e-06,\n 1.3924e-06, 8.3936e-07, 3.5409e-06, 2.2532e-06, 1.2448e-06, 4.0663e-07,\n 8.9006e-07, 4.4269e-07, 6.1217e-07, 1.2365e-06, 5.2588e-07, 7.5638e-07,\n 5.6068e-07, 4.0943e-07, 5.5134e-07, 1.5213e-06, 6.8891e-07, 7.5883e-07,\n 5.3872e-07, 5.7409e-07, 1.4582e-08, 2.6997e-06, 5.9854e-07, 4.5652e-07,\n 6.5891e-07, 8.9332e-07, 9.0419e-07, 2.0069e-06, 1.0617e-06, 6.8385e-07,\n 9.0074e-07, 5.9461e-07, 8.1996e-07, 1.4781e-06, 4.4044e-07, 8.2392e-07,\n 7.9372e-07, 6.8047e-07, 6.6151e-07, 2.3346e-07, 8.4593e-07, 1.3130e-06,\n 2.1306e-06, 3.6975e-06, 8.4059e-07, 2.9513e-06, 1.0048e-06, 2.6264e-06,\n 3.7618e-06, 5.1533e-07, 9.2795e-07, 1.4132e-06, 2.0215e-07, 1.0185e-06,\n 6.7315e-07, 2.3602e-06, 5.2437e-07, 4.6304e-07, 6.9158e-07, 3.4926e-06,\n 1.3369e-06, 8.2076e-07, 1.2562e-06, 3.1309e-06, 8.3698e-07, 7.6074e-07,\n 1.0842e-06, 1.3816e-06, 4.3956e-07, 1.0183e-06, 1.2195e-06, 1.1434e-06,\n 1.5897e-06, 7.9125e-07, 1.2905e-06, 1.1663e-06, 5.0091e-06, 2.2431e-06,\n 5.4878e-07, 4.6411e-06, 1.6366e-06, 5.6249e-07, 1.6350e-06, 5.6179e-07,\n 1.6034e-06, 6.2137e-07, 6.1486e-07, 1.1295e-05, 1.1038e-06, 1.4306e-06,\n 8.0353e-07, 1.4225e-06, 1.0897e-06, 1.8088e-06, 1.1549e-06, 1.0635e-06,\n 2.4893e-07, 1.3607e-06, 8.5244e-07, 1.0521e-06, 3.2868e-06, 1.9397e-06,\n 1.1120e-06, 9.8957e-07, 1.8309e-06, 1.0733e-06, 7.6486e-07, 1.0038e-06,\n 5.4158e-07, 6.7765e-07, 1.5004e-06, 2.1315e-06, 1.3753e-06, 5.3902e-07,\n 8.5493e-07, 7.1659e-07, 9.7342e-07, 2.4856e-06, 7.5384e-08, 1.4706e-06,\n 9.9258e-07, 7.6151e-07, 4.4721e-06, 3.8617e-07, 1.2250e-06, 8.9205e-07,\n 2.4901e-06, 8.2298e-07, 7.5363e-07, 2.6506e-06, 7.4464e-06, 9.7498e-07,\n 1.1342e-06, 2.5720e-06, 8.2922e-07, 9.2896e-07, 1.0630e-06, 5.0596e-07,\n 9.8853e-07, 1.4418e-06, 8.5947e-07, 8.8922e-07, 1.5864e-06, 9.8874e-07,\n 5.8509e-06, 6.3384e-07, 7.0125e-07, 1.2186e-06, 1.1209e-06, 4.0509e-06,\n 5.5766e-07, 3.5551e-06, 4.4265e-07, 6.1004e-07, 1.8118e-06, 6.8327e-07,\n 3.0977e-06, 3.6982e-06, 1.3717e-06, 4.6852e-07, 1.5462e-06, 3.2901e-07,\n 1.1579e-06, 1.4039e-06, 1.2909e-06, 9.1719e-07, 5.9542e-07, 7.1526e-07,\n 5.7692e-07, 1.0433e-06, 7.7596e-07, 2.8279e-06, 2.5688e-07, 1.1868e-06,\n 5.6524e-07, 6.7822e-07, 1.1695e-06, 9.1762e-07, 1.5211e-06, 9.1178e-07,\n 4.4737e-06, 1.0537e-06, 1.3297e-06, 8.1499e-07, 8.7655e-07, 7.4105e-07,\n 1.1091e-06, 1.0657e-06, 1.0034e-06, 3.1104e-06, 7.7785e-07, 8.1976e-07,\n 6.0604e-07, 7.7374e-07, 9.2735e-07, 9.0191e-07, 1.5353e-06, 2.3459e-06,\n 4.0326e-06, 6.8023e-07, 7.7599e-07, 4.2699e-06, 1.1375e-05, 2.0972e-06,\n 1.2686e-06, 6.3328e-07, 2.1276e-06, 6.4004e-07, 1.5420e-06, 1.2030e-06,\n 9.7211e-07, 1.3134e-06, 2.5237e-06, 1.0608e-06, 9.8549e-07, 6.3991e-07,\n 1.4920e-06, 6.2869e-07, 6.9260e-07, 1.6684e-06, 7.9616e-07, 3.4445e-07,\n 8.2977e-07, 1.0648e-06, 3.0457e-06, 4.8813e-07, 1.6020e-06, 1.2127e-06,\n 2.6119e-06, 1.4383e-06, 3.5619e-07, 6.1803e-07, 6.2255e-07, 1.0308e-06,\n 1.0379e-06, 1.1699e-06, 2.5314e-06, 1.4779e-06, 5.8078e-07, 1.7434e-06,\n 9.0067e-07, 1.5537e-06])}, 63: {'step': 7160, 'exp_avg': tensor([[[[ 9.6133e-06]],\n\n [[-2.6396e-05]],\n\n [[-4.8951e-05]],\n\n ...,\n\n [[ 1.9233e-07]],\n\n [[ 3.0161e-05]],\n\n [[ 1.4972e-06]]],\n\n\n [[[-1.4643e-05]],\n\n [[-1.4471e-06]],\n\n [[-3.0475e-05]],\n\n ...,\n\n [[ 1.2500e-05]],\n\n [[-1.9942e-05]],\n\n [[-8.9034e-06]]],\n\n\n [[[ 2.6007e-05]],\n\n [[ 5.1775e-06]],\n\n [[-5.2743e-05]],\n\n ...,\n\n [[ 4.0040e-05]],\n\n [[-2.7054e-06]],\n\n [[-5.9925e-07]]],\n\n\n ...,\n\n\n [[[ 3.7967e-06]],\n\n [[ 1.0695e-05]],\n\n [[ 3.3397e-06]],\n\n ...,\n\n [[-5.7047e-05]],\n\n [[ 9.5830e-06]],\n\n [[ 1.5835e-05]]],\n\n\n [[[ 1.5246e-05]],\n\n [[ 1.2091e-06]],\n\n [[-1.3581e-05]],\n\n ...,\n\n [[ 4.7135e-05]],\n\n [[ 2.6632e-05]],\n\n [[ 7.3005e-06]]],\n\n\n [[[-3.0780e-05]],\n\n [[-3.1239e-05]],\n\n [[ 1.0868e-05]],\n\n ...,\n\n [[-9.2842e-06]],\n\n [[ 3.2728e-05]],\n\n [[-7.2400e-06]]]]), 'exp_avg_sq': tensor([[[[9.2376e-08]],\n\n [[8.1152e-08]],\n\n [[1.5899e-07]],\n\n ...,\n\n [[2.3889e-07]],\n\n [[1.6074e-07]],\n\n [[1.1774e-07]]],\n\n\n [[[6.7831e-08]],\n\n [[7.6811e-08]],\n\n [[8.7862e-08]],\n\n ...,\n\n [[2.1047e-07]],\n\n [[1.6322e-07]],\n\n [[1.0865e-07]]],\n\n\n [[[1.2885e-07]],\n\n [[3.7363e-08]],\n\n [[1.8469e-07]],\n\n ...,\n\n [[2.1395e-07]],\n\n [[1.7231e-07]],\n\n [[1.3189e-07]]],\n\n\n ...,\n\n\n [[[1.8704e-07]],\n\n [[7.2155e-08]],\n\n [[1.6702e-07]],\n\n ...,\n\n [[3.2416e-07]],\n\n [[3.0334e-07]],\n\n [[2.7962e-07]]],\n\n\n [[[8.8708e-08]],\n\n [[7.5142e-08]],\n\n [[1.2916e-07]],\n\n ...,\n\n [[2.1310e-07]],\n\n [[1.4962e-07]],\n\n [[1.0935e-07]]],\n\n\n [[[9.4073e-08]],\n\n [[5.9709e-08]],\n\n [[8.3882e-08]],\n\n ...,\n\n [[1.7488e-07]],\n\n [[1.4324e-07]],\n\n [[6.6618e-08]]]])}, 64: {'step': 7160, 'exp_avg': tensor([-1.6982e-04, 1.9374e-05, -1.8954e-04, -3.7338e-05, -3.8797e-05,\n -3.0222e-05, -1.2438e-05, 1.0507e-04, -1.1628e-04, 1.0225e-04,\n 1.1514e-04, 1.4703e-04, -3.8438e-05, 3.4851e-04, -8.2002e-05,\n -4.1648e-04, -4.0063e-05, -3.8425e-05, -2.1929e-04, -1.5301e-04,\n -2.1196e-04, 1.2323e-04, 4.9589e-05, 1.2773e-04, 1.3377e-04,\n -2.4609e-04, -1.6851e-04, -8.4515e-05, 1.6932e-04, -1.8416e-04,\n -5.0254e-05, 1.6177e-04, 1.1588e-04, -6.6320e-05, 5.3313e-05,\n -9.8597e-05, 8.8660e-05, 1.2114e-04, 8.7099e-05, 6.5468e-05,\n -1.0640e-04, -1.7554e-04, 1.5228e-04, 1.1245e-04, -7.6447e-05,\n 2.8699e-05, 6.2378e-05, -2.2557e-04, 2.6899e-05, -2.0609e-04,\n -2.7611e-05, -2.0372e-04, -1.3414e-04, 1.3169e-04, -1.2287e-04,\n 7.9870e-06, -1.5364e-04, -1.0373e-05, -5.4812e-05, -8.1950e-05,\n 3.8159e-04, 2.5035e-05, -1.0175e-04, -9.5030e-06, -3.1736e-05,\n 8.3713e-05, -4.4402e-05, 4.8979e-05, 8.2768e-06, 2.5416e-04,\n 1.2781e-04, -6.7396e-05, -2.3429e-04, -1.3514e-04, 7.9903e-05,\n -4.9384e-05, -8.3450e-05, 1.1400e-04, -1.9308e-04, -6.2282e-05,\n 5.8990e-05, 2.4521e-04, 6.8070e-05, 1.3170e-05, -1.9420e-04,\n -6.8084e-05, 2.1698e-04, -7.9611e-05, -7.8118e-05, 1.2564e-04,\n 2.1502e-04, 6.1264e-05, 3.0094e-05, 1.0213e-04, -1.2857e-04,\n -7.9862e-05, 2.4603e-04, -1.0682e-04, -3.1934e-04, 1.1402e-04,\n 8.7966e-05, -1.1248e-04, 1.8649e-04, 1.6153e-05, 3.3067e-04,\n -4.5654e-05, -7.5774e-05, 1.6093e-04, 2.7776e-04, -1.9262e-06,\n -3.3252e-04, 1.2496e-04, 9.1078e-05, 3.7370e-05, 2.1313e-04,\n 5.3954e-05, -1.5328e-05, -3.9083e-05, 1.2458e-04, 4.6772e-05,\n 4.2560e-05, 2.4483e-04, -1.0416e-04, -5.4272e-05, 2.0438e-05,\n -3.2664e-04, 1.6482e-05, 1.2593e-04]), 'exp_avg_sq': tensor([6.0593e-06, 5.7169e-06, 4.1600e-06, 4.4597e-06, 4.1908e-06, 3.7389e-06,\n 2.2945e-06, 3.7538e-06, 5.2037e-06, 5.7045e-06, 4.3229e-06, 5.1690e-06,\n 3.8758e-06, 6.8654e-06, 4.3436e-06, 5.1847e-06, 3.7268e-06, 4.1292e-06,\n 6.1788e-06, 3.1755e-06, 2.9702e-06, 2.8835e-06, 4.3429e-06, 3.8235e-06,\n 1.0010e-05, 4.4696e-06, 5.3950e-06, 4.1276e-06, 5.9133e-06, 2.3309e-06,\n 4.9582e-06, 4.2863e-06, 1.9149e-06, 5.2317e-06, 2.4873e-06, 5.4705e-06,\n 6.3974e-06, 4.2967e-06, 3.8668e-06, 2.9828e-06, 6.3474e-06, 3.0854e-06,\n 3.5626e-06, 3.6612e-06, 5.6569e-06, 3.8226e-06, 3.7578e-06, 3.9325e-06,\n 1.8010e-06, 5.1329e-06, 3.2224e-06, 3.4691e-06, 4.0505e-06, 3.6017e-06,\n 2.0580e-06, 3.5830e-06, 5.1006e-06, 3.8470e-06, 4.2131e-06, 3.3330e-06,\n 5.3094e-06, 2.2982e-06, 4.9221e-06, 3.0912e-06, 3.5609e-06, 6.0301e-06,\n 6.3352e-06, 6.3283e-06, 5.2681e-06, 1.0586e-05, 3.1360e-06, 3.0279e-06,\n 7.9318e-06, 3.9890e-06, 3.6239e-06, 2.1168e-06, 5.1904e-06, 5.2941e-06,\n 3.4231e-06, 4.1306e-06, 4.2189e-06, 5.3140e-06, 6.1950e-06, 2.1229e-06,\n 3.3263e-06, 2.7170e-06, 5.2425e-06, 4.0622e-06, 4.1528e-06, 3.0298e-06,\n 4.1085e-06, 4.8702e-06, 3.0310e-06, 4.2017e-06, 4.5086e-06, 3.2974e-06,\n 3.4810e-06, 5.0267e-06, 1.1375e-05, 2.7246e-06, 3.3129e-06, 2.8467e-06,\n 4.3665e-06, 6.0192e-06, 5.4350e-06, 5.3612e-06, 2.9030e-06, 3.4035e-06,\n 3.2658e-06, 4.6111e-06, 6.0427e-06, 3.9448e-06, 3.3873e-06, 3.5671e-06,\n 5.9685e-06, 4.6486e-06, 1.1913e-05, 3.3288e-06, 6.2176e-06, 5.2926e-06,\n 3.7024e-06, 3.3633e-06, 6.1640e-06, 3.5273e-06, 5.7930e-06, 4.0824e-06,\n 3.4652e-06, 8.9979e-06])}, 65: {'step': 7160, 'exp_avg': tensor([-4.4927e-05, -9.3724e-05, -1.0415e-04, 2.2864e-05, -8.9379e-05,\n -3.6971e-05, -3.8603e-07, 1.1731e-04, -1.5499e-04, 1.3416e-04,\n 3.1514e-05, 2.0919e-04, -6.6148e-05, 1.6371e-04, 2.2006e-04,\n -2.7179e-04, -1.0731e-04, 4.9949e-05, -1.3090e-04, -5.0200e-05,\n -1.0253e-04, 8.7462e-05, 1.7162e-05, 2.6288e-05, -3.3042e-05,\n -2.1208e-04, -1.9804e-04, -8.8136e-05, -2.1445e-04, -1.4317e-04,\n 6.3566e-06, 7.6856e-05, 1.4527e-05, -1.7437e-05, 1.4966e-04,\n -9.0973e-05, 3.4060e-05, 8.7207e-05, 4.0639e-05, 4.3152e-05,\n 8.9238e-05, -5.7984e-05, -3.2628e-05, -1.3461e-04, -1.0368e-05,\n -6.2234e-06, -5.1152e-05, -1.4701e-04, -4.7083e-05, -9.8756e-05,\n 6.0770e-05, -2.6731e-04, -5.8522e-05, -1.1544e-04, 6.2249e-05,\n 1.7058e-05, -1.2807e-04, -7.9487e-05, -6.1703e-05, -1.0362e-04,\n 1.4211e-04, 8.4207e-05, -2.6267e-05, 3.2750e-05, -8.1144e-05,\n 1.1349e-04, 7.0772e-06, -8.7029e-05, -7.2567e-05, 1.2833e-04,\n 5.5815e-05, 1.4154e-04, -1.6079e-04, -1.0720e-04, 5.2998e-05,\n -9.0484e-05, 5.1305e-05, 1.6192e-04, -7.6755e-05, 2.5416e-06,\n 5.8440e-05, 5.2634e-05, -2.2650e-04, 1.5367e-04, -1.7092e-04,\n -5.4559e-05, 7.8881e-05, 2.3155e-05, -1.2039e-04, 1.9752e-04,\n 2.0262e-04, -6.1751e-05, -1.6619e-05, 7.8745e-05, -1.4596e-04,\n -6.9433e-05, 1.6846e-04, -4.8178e-05, -2.4843e-04, 8.6224e-05,\n 6.6578e-05, -2.0728e-05, 5.2036e-05, -5.3449e-05, 1.4293e-04,\n 8.2353e-05, 2.0311e-04, 8.1950e-06, 2.1356e-04, -1.2326e-04,\n -5.1038e-04, 1.5963e-04, 6.4833e-05, -2.3164e-05, 1.5106e-04,\n 9.4207e-05, -3.7270e-05, -2.3866e-04, 2.8002e-06, 2.9491e-05,\n 8.2197e-05, 1.6530e-04, -6.9664e-05, 7.0993e-05, 1.7350e-04,\n -2.0639e-04, 1.3049e-04, -2.5256e-05]), 'exp_avg_sq': tensor([1.9128e-06, 3.2560e-06, 1.9359e-06, 4.1682e-06, 1.7829e-06, 2.0658e-06,\n 2.3487e-06, 2.2305e-06, 2.8433e-06, 2.2769e-06, 3.3117e-06, 3.4025e-06,\n 2.0475e-06, 4.1591e-06, 2.3778e-06, 2.5295e-06, 2.5199e-06, 1.9465e-06,\n 2.5378e-06, 1.8288e-06, 3.1542e-06, 2.9889e-06, 2.9620e-06, 9.9703e-07,\n 4.5004e-06, 2.9685e-06, 2.6536e-06, 2.3766e-06, 1.7124e-06, 9.5573e-07,\n 2.1034e-06, 2.1801e-06, 2.0485e-06, 2.6141e-06, 2.2510e-06, 2.6489e-06,\n 3.1692e-06, 1.8407e-06, 3.5478e-06, 9.9616e-07, 4.5108e-06, 8.2403e-07,\n 1.7968e-06, 3.6245e-06, 1.8772e-06, 2.0038e-06, 2.7762e-06, 3.3037e-06,\n 1.2343e-06, 2.5519e-06, 2.2863e-06, 3.2455e-06, 2.2240e-06, 2.2077e-06,\n 1.8353e-06, 3.4004e-06, 4.2306e-06, 4.3634e-06, 1.9759e-06, 1.2804e-06,\n 2.7333e-06, 1.4046e-06, 2.2569e-06, 2.1658e-06, 2.2834e-06, 3.4691e-06,\n 3.3355e-06, 3.7603e-06, 2.1023e-06, 4.1375e-06, 1.9569e-06, 2.1816e-06,\n 2.7333e-06, 3.5572e-06, 1.5773e-06, 1.9803e-06, 4.3316e-06, 1.6521e-06,\n 1.7996e-06, 1.7596e-06, 2.9965e-06, 6.1806e-06, 4.2609e-06, 1.9095e-06,\n 3.0165e-06, 2.0312e-06, 3.0296e-06, 2.6048e-06, 4.8345e-06, 3.3268e-06,\n 2.0897e-06, 2.0037e-06, 2.2559e-06, 2.9558e-06, 5.9296e-06, 1.7014e-06,\n 2.3364e-06, 2.1746e-06, 3.6431e-06, 3.0048e-06, 2.5932e-06, 1.8002e-06,\n 2.4511e-06, 2.5356e-06, 2.9741e-06, 3.3323e-06, 2.4332e-06, 3.1523e-06,\n 2.4678e-06, 3.2409e-06, 6.3782e-06, 2.4474e-06, 1.2262e-06, 2.6680e-06,\n 4.5614e-06, 2.0066e-06, 3.5848e-06, 2.3619e-06, 2.6478e-06, 2.0199e-06,\n 1.6463e-06, 2.7161e-06, 3.9749e-06, 2.0364e-06, 2.9503e-06, 2.3681e-06,\n 3.3007e-06, 4.5030e-06])}, 66: {'step': 7160, 'exp_avg': tensor([[[[-4.5330e-05, -2.2534e-05, -3.5844e-05],\n [-3.9543e-05, -2.5182e-07, -1.3444e-05],\n [-4.9598e-06, -7.4878e-06, 1.2017e-05]],\n\n [[-1.3527e-05, 1.1188e-06, -8.5524e-06],\n [ 6.2747e-06, 6.5047e-06, -5.8523e-06],\n [-7.8528e-06, -1.0851e-05, -1.2809e-05]],\n\n [[ 4.3780e-06, -1.3770e-05, -8.8798e-06],\n [-8.3043e-06, 3.5924e-07, 7.9132e-06],\n [ 6.6334e-06, 2.1140e-05, -4.6055e-06]],\n\n ...,\n\n [[-6.3240e-05, -4.5788e-05, -3.1162e-05],\n [-4.2944e-05, -4.1936e-06, -1.5266e-05],\n [-3.9645e-05, -2.0075e-05, -2.1994e-05]],\n\n [[-2.9956e-05, -2.8164e-05, 2.9294e-06],\n [-2.8317e-05, 3.0272e-06, 1.5332e-05],\n [-3.7704e-06, 2.1707e-05, 5.7425e-06]],\n\n [[ 1.5519e-05, 7.3165e-06, 2.9089e-05],\n [ 2.6968e-05, -7.3829e-07, 1.6405e-05],\n [ 2.7118e-05, 1.6639e-05, 3.2298e-05]]],\n\n\n [[[-1.0556e-05, -1.6784e-05, -6.6700e-06],\n [-2.2875e-05, 9.8545e-06, -1.9299e-05],\n [-3.1439e-05, 7.8272e-06, 2.8394e-05]],\n\n [[ 9.9509e-06, -8.6471e-06, -3.6092e-05],\n [-3.6720e-05, -3.2697e-05, -4.4860e-05],\n [ 1.3022e-07, -5.1743e-05, -8.6319e-06]],\n\n [[ 7.8472e-05, 7.9530e-05, 1.7033e-06],\n [ 2.3170e-05, 6.1118e-06, 4.1554e-05],\n [-6.3943e-05, 1.6819e-05, -2.4903e-05]],\n\n ...,\n\n [[-1.4147e-05, -2.0759e-05, -3.6274e-05],\n [ 7.7430e-06, 7.3175e-06, -7.4552e-05],\n [ 2.2111e-05, -2.4869e-05, -4.7299e-05]],\n\n [[-7.7904e-06, -3.3512e-05, -5.4392e-05],\n [ 6.3238e-07, -1.8907e-05, -5.4560e-05],\n [-3.7642e-06, -1.9924e-05, -2.6214e-05]],\n\n [[ 4.9778e-05, 8.0045e-05, 5.8939e-05],\n [-2.3249e-05, -3.4539e-06, 5.7748e-05],\n [-2.3345e-05, -4.4991e-05, 4.6336e-05]]],\n\n\n [[[-3.3740e-06, -8.1911e-06, -1.2610e-05],\n [-9.1957e-06, 2.5514e-05, -6.5413e-06],\n [-1.4213e-05, -1.5131e-05, -2.3493e-05]],\n\n [[-7.6446e-06, 4.2871e-06, 9.3209e-06],\n [ 6.1602e-06, 2.1267e-05, 3.1209e-05],\n [-1.5247e-05, 1.1967e-05, -1.6804e-06]],\n\n [[ 8.6640e-07, 7.2844e-06, 1.0478e-05],\n [ 5.4560e-06, 5.5687e-07, 1.2602e-05],\n [ 5.0504e-06, 4.0914e-06, -2.6374e-07]],\n\n ...,\n\n [[-1.0460e-05, -2.3010e-05, -1.7712e-05],\n [-1.8195e-05, -8.7650e-06, -1.5844e-05],\n [-9.0025e-06, 1.2027e-05, 4.3584e-05]],\n\n [[-1.2904e-05, -6.6862e-06, 1.1466e-05],\n [-1.9327e-05, -5.8304e-07, 1.0216e-06],\n [ 3.0735e-07, 8.4970e-07, 3.3401e-06]],\n\n [[ 8.8517e-06, -4.3812e-06, 1.8546e-05],\n [-1.6999e-05, -1.6864e-05, -2.8405e-06],\n [ 1.6909e-05, 3.5015e-05, 4.4554e-05]]],\n\n\n ...,\n\n\n [[[ 6.0777e-06, 8.2178e-06, -1.0296e-05],\n [ 4.1903e-06, -8.7147e-06, -7.6936e-06],\n [ 8.5118e-06, -4.7933e-06, -8.0282e-06]],\n\n [[ 1.3446e-05, -3.1789e-06, 1.0063e-05],\n [-1.4038e-05, 3.2410e-05, -1.6625e-05],\n [ 2.0178e-05, 3.1299e-07, -1.4885e-05]],\n\n [[-5.8884e-07, -3.0341e-05, -2.7428e-05],\n [ 3.4460e-05, -2.0580e-05, -1.8464e-05],\n [-2.8555e-06, 4.6546e-05, -8.9318e-06]],\n\n ...,\n\n [[ 5.0869e-06, -2.4596e-05, -5.1216e-05],\n [-1.0630e-05, -1.3570e-05, -4.8942e-05],\n [-2.0611e-05, 2.3407e-05, -2.8761e-05]],\n\n [[ 3.1118e-06, -9.1604e-07, -2.7207e-05],\n [-2.5210e-05, 3.3333e-06, -2.9794e-05],\n [-3.1257e-05, -7.4586e-06, -3.6540e-05]],\n\n [[-1.2375e-06, 6.3786e-06, 2.3326e-05],\n [ 1.1380e-05, 8.2388e-06, 7.3472e-05],\n [ 3.3925e-05, 8.0182e-06, 1.7742e-05]]],\n\n\n [[[-7.5517e-06, 2.8465e-06, 1.2499e-06],\n [ 1.4919e-05, 7.0800e-07, -2.2634e-07],\n [-9.6952e-06, 5.8626e-06, 1.8606e-06]],\n\n [[-2.7330e-05, -1.3081e-05, 9.6573e-06],\n [-5.8930e-06, 1.5880e-05, 7.5228e-06],\n [ 1.0592e-05, 2.7896e-05, 1.6451e-05]],\n\n [[ 1.6945e-05, 7.5692e-06, 1.1836e-05],\n [ 1.7461e-05, 1.1896e-06, -6.5116e-06],\n [ 1.5364e-05, 5.0275e-06, -9.4470e-06]],\n\n ...,\n\n [[ 1.3903e-05, -4.1904e-06, -2.6440e-06],\n [-9.8021e-06, 3.3278e-06, -2.6909e-06],\n [-2.7974e-07, 1.9881e-05, 2.6750e-05]],\n\n [[-1.4027e-06, 1.3374e-06, -2.2690e-05],\n [-4.5152e-06, -1.4455e-05, -1.4228e-05],\n [-7.1567e-06, -1.0910e-05, -1.0972e-06]],\n\n [[ 9.8447e-06, 1.6688e-06, -4.7171e-06],\n [-6.0685e-06, -1.1366e-05, -1.1716e-05],\n [ 8.0577e-06, -4.5505e-06, -1.4139e-05]]],\n\n\n [[[-1.3897e-05, 4.6866e-06, -1.7357e-05],\n [ 1.1198e-05, -9.6458e-06, 5.7701e-06],\n [ 2.7823e-05, 2.5784e-06, 1.9281e-05]],\n\n [[-7.4978e-06, -2.1688e-05, -5.2427e-06],\n [ 1.3257e-05, -1.6004e-05, -1.7301e-05],\n [ 4.1481e-05, 5.1224e-06, 8.8219e-06]],\n\n [[-1.9441e-05, -1.0637e-05, 5.7794e-06],\n [-7.8852e-06, -4.0327e-05, -4.3703e-06],\n [-4.5636e-06, -1.5548e-05, -3.2453e-05]],\n\n ...,\n\n [[ 9.6652e-06, 7.6238e-06, -8.0961e-06],\n [ 1.2433e-05, 4.3529e-06, 1.6626e-05],\n [ 3.7152e-06, 8.0987e-06, -5.4064e-06]],\n\n [[-1.1980e-05, -7.7106e-06, 3.0783e-06],\n [ 1.4666e-05, 1.0078e-05, 1.0012e-05],\n [ 2.4789e-05, 2.1880e-05, -1.0428e-06]],\n\n [[-1.2354e-05, 5.1021e-06, 6.3523e-06],\n [-2.4383e-05, -1.6754e-05, -2.5802e-05],\n [-2.7380e-05, -7.2089e-06, -9.8589e-06]]]]), 'exp_avg_sq': tensor([[[[1.2106e-07, 1.1726e-07, 9.1026e-08],\n [1.7175e-07, 1.0403e-07, 9.1143e-08],\n [1.7748e-07, 7.9351e-08, 1.1413e-07]],\n\n [[4.0772e-07, 5.9965e-07, 4.1364e-07],\n [2.8074e-07, 1.6724e-07, 1.7891e-07],\n [1.3561e-07, 1.9103e-07, 1.2182e-07]],\n\n [[1.8562e-07, 1.3771e-07, 1.2081e-07],\n [2.1064e-07, 2.1164e-07, 1.4346e-07],\n [9.0587e-08, 1.3476e-07, 1.1940e-07]],\n\n ...,\n\n [[2.5509e-07, 3.3939e-07, 1.8910e-07],\n [2.2224e-07, 1.7263e-07, 1.7175e-07],\n [2.2339e-07, 1.8496e-07, 2.2485e-07]],\n\n [[1.1541e-07, 1.1478e-07, 1.0688e-07],\n [1.1812e-07, 1.2653e-07, 1.0087e-07],\n [8.5185e-08, 1.1356e-07, 8.9180e-08]],\n\n [[8.8854e-08, 1.3341e-07, 1.4604e-07],\n [1.6242e-07, 1.3541e-07, 1.2804e-07],\n [1.3236e-07, 1.7278e-07, 2.1363e-07]]],\n\n\n [[[1.8974e-07, 1.3779e-07, 1.7199e-07],\n [3.3723e-07, 1.2590e-07, 1.3424e-07],\n [2.4078e-07, 1.8992e-07, 1.1852e-07]],\n\n [[2.6561e-07, 1.8591e-07, 2.2467e-07],\n [3.1051e-07, 2.2183e-07, 1.4951e-07],\n [2.6696e-07, 3.8432e-07, 1.6268e-07]],\n\n [[1.6257e-07, 1.0460e-07, 1.1847e-07],\n [2.0783e-07, 1.0075e-07, 6.4233e-08],\n [3.6640e-07, 2.7500e-07, 1.1088e-07]],\n\n ...,\n\n [[4.2772e-07, 2.3287e-07, 2.4241e-07],\n [2.8332e-07, 2.7688e-07, 2.0221e-07],\n [2.6726e-07, 1.9258e-07, 2.1122e-07]],\n\n [[1.2126e-07, 1.6655e-07, 1.5909e-07],\n [1.7538e-07, 1.1419e-07, 1.5206e-07],\n [2.2925e-07, 1.0557e-07, 1.1354e-07]],\n\n [[1.5947e-07, 1.6927e-07, 1.4146e-07],\n [1.1134e-07, 1.5055e-07, 1.7655e-07],\n [1.6634e-07, 1.8015e-07, 1.6430e-07]]],\n\n\n [[[4.2118e-08, 6.6718e-08, 6.9665e-08],\n [5.7441e-08, 4.2237e-08, 5.8170e-08],\n [5.6820e-08, 5.1648e-08, 5.3992e-08]],\n\n [[8.8200e-08, 7.6073e-08, 7.0915e-08],\n [5.5686e-08, 4.4221e-08, 5.1430e-08],\n [4.9647e-08, 4.1731e-08, 7.3968e-08]],\n\n [[4.3922e-08, 4.4780e-08, 4.1106e-08],\n [3.8856e-08, 6.7237e-08, 5.9306e-08],\n [3.8341e-08, 6.5351e-08, 4.5025e-08]],\n\n ...,\n\n [[6.7475e-08, 9.4783e-08, 9.2684e-08],\n [9.2117e-08, 7.5507e-08, 6.8189e-08],\n [7.0055e-08, 7.1430e-08, 7.6528e-08]],\n\n [[5.2729e-08, 6.2553e-08, 6.2378e-08],\n [4.7854e-08, 4.5040e-08, 3.7989e-08],\n [4.2922e-08, 4.5822e-08, 3.2717e-08]],\n\n [[4.0004e-08, 4.0817e-08, 3.9146e-08],\n [6.1768e-08, 5.4836e-08, 8.0844e-08],\n [7.7146e-08, 5.9756e-08, 6.9300e-08]]],\n\n\n ...,\n\n\n [[[1.1780e-07, 1.1987e-07, 5.7300e-08],\n [9.8319e-08, 9.4103e-08, 8.9630e-08],\n [9.4169e-08, 7.8122e-08, 5.8226e-08]],\n\n [[9.7390e-08, 1.1482e-07, 1.0221e-07],\n [1.1646e-07, 1.4070e-07, 1.0157e-07],\n [7.9923e-08, 1.3135e-07, 1.2522e-07]],\n\n [[9.7249e-08, 5.5429e-08, 6.1318e-08],\n [1.5423e-07, 1.6546e-07, 6.5623e-08],\n [1.3050e-07, 1.0544e-07, 7.5060e-08]],\n\n ...,\n\n [[1.3787e-07, 1.5085e-07, 1.6014e-07],\n [1.2418e-07, 1.4502e-07, 1.7233e-07],\n [1.9116e-07, 1.8106e-07, 1.6398e-07]],\n\n [[9.0488e-08, 8.5162e-08, 9.0213e-08],\n [9.7546e-08, 8.4203e-08, 6.6688e-08],\n [9.7360e-08, 8.7628e-08, 8.4639e-08]],\n\n [[1.8452e-07, 7.6072e-08, 7.6125e-08],\n [1.3116e-07, 7.6753e-08, 1.2447e-07],\n [8.5643e-08, 8.3708e-08, 1.4777e-07]]],\n\n\n [[[5.2986e-08, 6.6690e-08, 6.2048e-08],\n [4.2052e-08, 4.5219e-08, 5.1743e-08],\n [5.5991e-08, 5.9739e-08, 4.3533e-08]],\n\n [[2.1196e-07, 7.7822e-08, 8.5419e-08],\n [6.8061e-08, 6.1057e-08, 6.8783e-08],\n [9.8283e-08, 5.4123e-08, 5.2942e-08]],\n\n [[8.4979e-08, 8.6745e-08, 4.3153e-08],\n [3.8850e-08, 4.4769e-08, 4.6838e-08],\n [3.0915e-08, 4.0040e-08, 3.2778e-08]],\n\n ...,\n\n [[9.3917e-08, 9.6613e-08, 1.3023e-07],\n [8.0546e-08, 7.4786e-08, 8.4515e-08],\n [7.6953e-08, 1.0430e-07, 1.6758e-07]],\n\n [[3.9899e-08, 5.2495e-08, 7.1523e-08],\n [4.6481e-08, 5.2472e-08, 4.8812e-08],\n [6.1006e-08, 4.8360e-08, 5.3623e-08]],\n\n [[6.7362e-08, 3.5282e-08, 4.5914e-08],\n [3.8971e-08, 3.5899e-08, 4.3271e-08],\n [8.8049e-08, 4.4096e-08, 3.8817e-08]]],\n\n\n [[[6.0274e-08, 3.1585e-08, 6.1121e-08],\n [4.6067e-08, 2.3826e-08, 6.7149e-08],\n [4.2075e-08, 2.8575e-08, 4.5962e-08]],\n\n [[8.8025e-08, 1.1122e-07, 9.8044e-08],\n [9.9917e-08, 1.1387e-07, 7.0172e-08],\n [3.2133e-07, 1.4143e-07, 1.2313e-07]],\n\n [[6.8756e-08, 5.7667e-08, 7.8181e-08],\n [1.2971e-07, 9.8242e-08, 1.2663e-07],\n [1.2469e-07, 1.2981e-07, 9.6075e-08]],\n\n ...,\n\n [[1.4705e-07, 7.2000e-08, 6.8115e-08],\n [8.3829e-08, 8.1442e-08, 6.4865e-08],\n [1.0463e-07, 8.2094e-08, 7.5490e-08]],\n\n [[6.3978e-08, 5.4188e-08, 5.3115e-08],\n [7.7051e-08, 5.7785e-08, 6.3850e-08],\n [8.8214e-08, 7.9328e-08, 6.6819e-08]],\n\n [[5.6948e-08, 1.7483e-07, 1.2529e-07],\n [6.4893e-08, 1.2502e-07, 1.0501e-07],\n [7.1986e-08, 6.9296e-08, 9.8617e-08]]]])}, 67: {'step': 7160, 'exp_avg': tensor([ 3.2657e-04, 1.6032e-04, 6.7266e-05, 1.9457e-04, 9.7953e-06,\n -8.3786e-05, -3.1202e-04, 4.0376e-05, -1.0196e-04, -1.1662e-04,\n -6.0675e-04, -7.4839e-05, 2.2168e-04, 2.5388e-04, 3.7983e-05,\n 6.0083e-05, -1.0241e-04, 3.4083e-06, -2.1500e-04, -3.7644e-05,\n 6.3841e-05, -1.2534e-04, 3.1753e-04, 1.3466e-04, -7.4966e-05,\n 2.2778e-04, 2.8420e-05, -6.0087e-05, 2.7605e-04, -1.8082e-04,\n 1.7193e-04, -4.0409e-04, -3.6472e-05, -4.6728e-04, 2.1803e-04,\n -7.2971e-05, 2.0084e-04, 5.1669e-05, -1.9149e-04, 8.9582e-06,\n 1.3743e-04, 9.8750e-06, -1.9945e-04, 1.8019e-04, -8.0160e-05,\n -1.3001e-05, 2.6765e-04, 4.1125e-05, 1.9098e-04, 1.1415e-04,\n 9.0570e-05, 1.4966e-04, 1.7912e-04, 3.9347e-05, -2.9536e-04,\n -1.3952e-04, 2.9277e-05, 1.4912e-05, -1.2533e-06, 8.7654e-05,\n -1.2572e-04, -6.0403e-06, 1.4031e-04, 5.7013e-05, -2.4514e-04,\n -2.1921e-04, -2.2570e-05, -1.1722e-06, 9.9586e-05, -2.2793e-05,\n -1.3742e-04, -9.9426e-06, 2.0921e-04, -2.9406e-05, 2.1103e-04,\n 4.0466e-05, -9.9465e-05, -1.0013e-04, 8.5915e-05, 4.6037e-05,\n -2.8028e-04, -4.3853e-05, 2.1490e-05, 1.2230e-05, -1.1748e-04,\n 2.7835e-04, 1.9491e-04, 1.7249e-04, -1.8467e-04, -7.4841e-05,\n 1.9062e-04, 5.9031e-05, -1.1206e-04, 1.3442e-04, -1.0345e-04,\n -3.7383e-05, 4.8640e-05, -2.7297e-04, -1.0905e-04, -1.4439e-04,\n -2.1982e-04, 8.8684e-05, 1.3184e-04, -4.4257e-04, -1.9311e-04,\n -8.2443e-05, 1.5096e-04, 1.6499e-04, 1.6349e-05, -3.3125e-05,\n -9.4535e-05, 4.7635e-05, 1.3962e-04, -1.5514e-05, 2.5505e-05,\n -8.3670e-05, 2.6432e-04, -9.7639e-05, -1.0720e-04, -4.2851e-05,\n -3.3090e-05, 7.5681e-05, 3.0772e-04, 3.0965e-04, -8.8452e-05,\n 1.5902e-05, 2.4389e-06, -2.5921e-06]), 'exp_avg_sq': tensor([1.8636e-05, 6.6078e-06, 2.7414e-06, 5.6098e-06, 4.3107e-06, 5.3804e-06,\n 6.6062e-06, 6.3617e-06, 5.9331e-06, 2.8344e-06, 1.9423e-05, 9.3258e-06,\n 3.1119e-06, 3.7943e-06, 4.2668e-06, 2.8447e-06, 4.6093e-06, 8.7585e-06,\n 9.6961e-06, 1.2577e-05, 1.0153e-05, 1.5701e-05, 4.9163e-06, 4.1303e-06,\n 5.4842e-06, 1.5307e-05, 4.6908e-06, 4.5362e-06, 3.0406e-06, 3.8564e-06,\n 4.7620e-06, 7.6568e-06, 2.9475e-06, 9.9352e-06, 4.0660e-06, 3.0934e-06,\n 6.9187e-06, 3.2933e-06, 5.5642e-06, 2.8913e-06, 7.0828e-06, 3.4506e-06,\n 5.0915e-06, 5.9750e-06, 6.2863e-06, 3.9986e-06, 4.2693e-06, 7.2329e-06,\n 2.5671e-06, 8.2562e-06, 5.3141e-06, 2.9423e-06, 5.0426e-06, 1.5128e-05,\n 1.2247e-05, 3.5469e-06, 3.2058e-06, 8.0384e-06, 4.5078e-06, 7.0563e-06,\n 6.5897e-06, 4.0976e-06, 7.5324e-06, 4.6554e-06, 5.8991e-06, 1.0584e-05,\n 2.6882e-06, 2.7144e-06, 5.2723e-06, 2.4271e-06, 2.0180e-06, 2.1465e-06,\n 3.6813e-06, 1.0316e-05, 4.1382e-06, 7.8511e-06, 1.0150e-05, 6.5635e-06,\n 3.9948e-06, 5.8843e-06, 6.1049e-06, 7.1837e-06, 7.8776e-06, 3.2528e-06,\n 4.2017e-06, 8.1300e-06, 2.1956e-05, 1.2855e-05, 7.6608e-06, 5.5017e-06,\n 5.3497e-06, 5.0866e-06, 1.7300e-05, 5.5249e-06, 3.1866e-06, 6.2252e-06,\n 4.6572e-06, 2.4878e-06, 8.2056e-06, 4.0827e-06, 4.1491e-06, 3.1325e-06,\n 5.4616e-06, 1.0449e-05, 6.4589e-06, 5.2299e-06, 4.8879e-06, 5.4273e-06,\n 1.8859e-06, 3.7130e-06, 6.6268e-06, 6.0134e-06, 7.0298e-06, 5.1071e-06,\n 3.9497e-06, 6.9666e-06, 8.4537e-06, 8.0379e-06, 3.5239e-06, 1.6829e-06,\n 2.5238e-06, 4.6873e-06, 5.7560e-06, 6.4318e-06, 8.2367e-06, 3.7127e-06,\n 2.5178e-06, 7.0054e-06])}, 68: {'step': 7160, 'exp_avg': tensor([ 2.8735e-04, 8.0811e-05, 7.1888e-05, 1.7178e-04, -1.0993e-04,\n -3.8877e-07, -1.0382e-04, 6.9916e-05, -3.0229e-05, -1.1165e-05,\n -2.9232e-04, -4.2898e-05, 7.6255e-05, 2.0507e-04, -6.8020e-06,\n -1.0501e-05, -2.3074e-05, -8.1803e-05, -2.0572e-04, 1.9554e-04,\n -2.8381e-05, -1.6452e-05, 1.9618e-04, 6.7775e-05, -6.6430e-05,\n 2.0225e-04, 1.7490e-05, -1.0886e-04, 1.9930e-04, -8.9227e-05,\n 1.0480e-04, -3.2393e-04, -9.0722e-05, -7.5118e-05, 1.2390e-04,\n -5.9798e-05, 5.7053e-05, -4.5389e-05, -8.8872e-06, 2.6278e-05,\n 1.0147e-04, -1.1625e-04, -1.0548e-04, 1.4119e-04, 1.4371e-05,\n 3.5761e-05, 1.4623e-04, 2.0960e-04, 1.7063e-05, 5.8707e-05,\n -8.8625e-06, 1.4052e-04, 1.2615e-04, -6.1354e-06, -1.7818e-04,\n -1.7892e-04, -1.1760e-04, 5.2793e-05, -3.4362e-06, 9.5043e-05,\n 2.0194e-05, -2.0700e-05, 1.6241e-04, 3.0432e-05, -3.0695e-04,\n -2.4058e-04, -1.1026e-04, -6.5698e-06, -1.1394e-05, -4.3104e-05,\n -2.3032e-05, -4.4167e-05, 6.4836e-05, 2.5290e-05, 1.6689e-06,\n -6.5723e-05, -6.4141e-05, -5.4649e-05, -2.9936e-04, 8.8716e-05,\n -2.1092e-04, 4.6543e-05, -2.0427e-05, -9.6360e-06, -1.5222e-04,\n 1.7873e-04, -8.4638e-06, -2.5927e-04, -1.0291e-04, 3.2587e-05,\n 5.9395e-05, -8.2627e-05, -3.1686e-05, 1.4472e-04, -1.6278e-05,\n -2.3040e-05, 1.3505e-04, -1.2061e-04, -5.3829e-06, -2.0958e-05,\n -1.8041e-04, 1.0367e-04, 9.5227e-05, 1.8818e-04, -1.1389e-04,\n -2.4063e-05, 1.1612e-04, 7.0342e-05, 5.1189e-05, 5.3895e-05,\n -1.3199e-04, -2.4723e-05, 4.3496e-05, -4.3611e-05, -3.2793e-05,\n -9.3449e-05, 2.4295e-04, 2.6573e-05, 1.0247e-04, -1.0079e-04,\n -1.4518e-04, -2.3342e-05, 3.4319e-04, 1.3143e-04, 7.5456e-06,\n 5.7456e-05, -6.5591e-05, -7.1979e-05]), 'exp_avg_sq': tensor([9.8874e-06, 2.5702e-06, 1.4681e-06, 3.6339e-06, 3.7632e-06, 3.2412e-06,\n 2.6502e-06, 2.2020e-06, 2.5567e-06, 1.4934e-06, 8.7052e-06, 5.5510e-06,\n 2.7269e-06, 1.4904e-06, 2.0920e-06, 1.7159e-06, 2.4249e-06, 4.2375e-06,\n 5.1441e-06, 3.2353e-06, 4.1880e-06, 5.5719e-06, 2.6645e-06, 1.7019e-06,\n 3.0201e-06, 3.1257e-06, 1.7644e-06, 2.6051e-06, 1.6673e-06, 1.9211e-06,\n 1.8840e-06, 4.4163e-06, 1.8507e-06, 2.3215e-06, 2.1225e-06, 2.2142e-06,\n 6.3073e-06, 1.9713e-06, 2.0928e-06, 1.3567e-06, 2.6669e-06, 1.5931e-06,\n 1.8645e-06, 2.0367e-06, 2.5378e-06, 1.8070e-06, 2.0893e-06, 2.4814e-06,\n 1.8792e-06, 5.3516e-06, 2.2042e-06, 1.4978e-06, 2.3249e-06, 6.0809e-06,\n 7.0263e-06, 2.1643e-06, 2.8545e-06, 4.4179e-06, 2.2283e-06, 4.5604e-06,\n 4.1992e-06, 1.6994e-06, 3.2731e-06, 2.5513e-06, 3.4771e-06, 5.4923e-06,\n 1.8440e-06, 9.9458e-07, 2.4123e-06, 1.4603e-06, 1.6111e-06, 1.1887e-06,\n 1.8827e-06, 4.8464e-06, 2.2061e-06, 2.4335e-06, 3.5743e-06, 2.6659e-06,\n 2.7498e-06, 3.0126e-06, 2.8855e-06, 6.0280e-07, 4.7131e-06, 1.6683e-06,\n 3.2078e-06, 4.2822e-06, 1.8209e-07, 3.0977e-06, 3.8466e-06, 2.1271e-06,\n 2.6850e-06, 3.1442e-06, 8.0956e-08, 3.2838e-06, 2.3159e-06, 2.9868e-06,\n 4.2035e-06, 1.4763e-06, 4.2682e-06, 1.6819e-06, 2.5656e-06, 1.4991e-06,\n 3.3951e-06, 4.8493e-06, 5.0865e-06, 1.5033e-06, 2.1647e-06, 5.0971e-06,\n 1.1125e-06, 1.5177e-06, 2.6884e-06, 1.5505e-06, 2.4838e-06, 2.7001e-06,\n 2.3904e-06, 2.4601e-06, 2.9579e-06, 3.8245e-06, 2.6456e-06, 1.1633e-06,\n 1.8062e-06, 2.6958e-06, 4.8808e-06, 3.4953e-06, 3.7485e-06, 2.5200e-06,\n 1.7860e-06, 2.7412e-06])}, 69: {'step': 7160, 'exp_avg': tensor([[[[ 3.2437e-05]],\n\n [[-1.3679e-05]],\n\n [[ 7.9118e-06]],\n\n ...,\n\n [[-1.9232e-05]],\n\n [[-1.3551e-05]],\n\n [[ 5.9378e-06]]],\n\n\n [[[-3.6502e-05]],\n\n [[-5.3390e-06]],\n\n [[-6.5631e-06]],\n\n ...,\n\n [[-3.2243e-05]],\n\n [[-3.0195e-05]],\n\n [[ 3.2550e-05]]],\n\n\n [[[-8.1936e-07]],\n\n [[-1.0338e-06]],\n\n [[ 4.1720e-07]],\n\n ...,\n\n [[-6.4295e-07]],\n\n [[-2.4906e-06]],\n\n [[-4.7709e-07]]],\n\n\n ...,\n\n\n [[[-6.0847e-06]],\n\n [[-5.9357e-06]],\n\n [[-3.2604e-06]],\n\n ...,\n\n [[-2.4193e-06]],\n\n [[ 2.1000e-07]],\n\n [[ 4.4045e-07]]],\n\n\n [[[-4.8725e-06]],\n\n [[-6.2282e-05]],\n\n [[-3.5624e-06]],\n\n ...,\n\n [[ 1.1139e-05]],\n\n [[ 1.6556e-05]],\n\n [[ 2.0036e-05]]],\n\n\n [[[ 1.1879e-05]],\n\n [[ 9.3803e-06]],\n\n [[ 1.8868e-06]],\n\n ...,\n\n [[-1.0774e-05]],\n\n [[-3.3358e-06]],\n\n [[ 4.7614e-06]]]]), 'exp_avg_sq': tensor([[[[7.0271e-08]],\n\n [[1.8057e-08]],\n\n [[1.3743e-08]],\n\n ...,\n\n [[3.7013e-08]],\n\n [[2.4039e-08]],\n\n [[2.7787e-08]]],\n\n\n [[[4.6975e-07]],\n\n [[4.1432e-07]],\n\n [[1.7687e-07]],\n\n ...,\n\n [[5.9756e-07]],\n\n [[1.1895e-07]],\n\n [[2.7142e-07]]],\n\n\n [[[2.3560e-09]],\n\n [[7.8558e-10]],\n\n [[7.4766e-10]],\n\n ...,\n\n [[1.4861e-09]],\n\n [[4.8356e-10]],\n\n [[9.7830e-10]]],\n\n\n ...,\n\n\n [[[6.9477e-09]],\n\n [[2.8822e-09]],\n\n [[3.7472e-09]],\n\n ...,\n\n [[4.7238e-09]],\n\n [[1.9581e-09]],\n\n [[8.1700e-09]]],\n\n\n [[[1.5770e-07]],\n\n [[1.4309e-07]],\n\n [[9.5355e-08]],\n\n ...,\n\n [[1.1148e-07]],\n\n [[6.8639e-08]],\n\n [[9.3302e-08]]],\n\n\n [[[8.7363e-08]],\n\n [[6.4646e-08]],\n\n [[5.3486e-08]],\n\n ...,\n\n [[5.8045e-08]],\n\n [[4.3636e-08]],\n\n [[1.3330e-07]]]])}, 70: {'step': 7160, 'exp_avg': tensor([-1.8291e-05, -5.2216e-05, -7.2844e-05, -1.9464e-05, -5.8909e-05,\n -6.5838e-05, -1.2547e-04, -9.4683e-05, 1.3986e-05, -1.2058e-05,\n 7.7029e-05, 1.2815e-04, -2.4280e-05, 3.5532e-05, 3.5452e-05,\n -1.4507e-04, -1.7074e-05, -9.4647e-05, 1.1747e-04, 8.4923e-06,\n -8.8255e-05, -1.9347e-05, -1.1511e-04, -1.6567e-04, -7.9583e-05,\n -1.9477e-05, -6.0722e-05, -4.5251e-05, 3.5000e-05, 7.2619e-06,\n -1.2466e-04, -6.0579e-05, -1.6363e-04, -3.9297e-05, 7.6261e-05,\n -1.1000e-04, 1.6027e-04, 1.4413e-04, -7.9806e-05, 6.9938e-06,\n 2.5905e-05, -6.0801e-05, 2.3837e-04, 6.9228e-05, -1.4092e-04,\n -6.2168e-05, -8.6846e-05, -1.9694e-05, -9.8804e-05, 4.2857e-05,\n -4.0253e-05, -6.2965e-05, -4.2756e-05, 6.6349e-05, -8.4009e-06,\n 7.4315e-06, 9.6174e-05, 5.9218e-06, 2.4532e-05, 1.3088e-04,\n 2.6102e-05, -1.3692e-04, 1.5946e-06, 5.2024e-05, -7.0783e-06,\n 5.1232e-05, 5.4403e-05, 1.2373e-04, 1.7751e-04, 6.2104e-05,\n -3.9665e-06, 3.2828e-05, -2.9494e-05, 1.0076e-04, 2.9841e-05,\n 5.9900e-05, -1.2100e-05, -2.2756e-04, 9.3397e-05, -3.5949e-05,\n 5.2495e-06, -7.9069e-05, -8.3122e-06, 1.8192e-05, -1.7215e-04,\n -2.0339e-04, -8.3709e-05, -6.7853e-05, -7.6190e-05, -7.7440e-05,\n 2.3652e-06, -1.8514e-05, 4.4459e-05, -4.8499e-05, -2.4286e-04,\n -9.8249e-05, -1.2631e-04, -4.3572e-06, 5.1328e-05, 1.0731e-04,\n -1.3523e-04, -3.6189e-05, 2.3797e-04, 2.8785e-05, 1.3585e-05,\n -4.1591e-04, 5.5737e-05, 1.5269e-04, 5.1231e-05, 8.9630e-05,\n -2.3291e-05, -1.3405e-05, -9.7984e-05, 6.6028e-06, -1.1652e-04,\n -1.4720e-04, 1.1136e-05, -4.6953e-05, 3.6314e-05, -9.6421e-05,\n 1.5828e-04, -6.9020e-06, -4.0702e-05, -3.3370e-05, -5.5405e-05,\n -1.3701e-04, -1.8258e-04, -3.6248e-05, -1.2601e-04, -2.2332e-06,\n 8.9767e-05, -4.5639e-05, -5.9903e-05, 2.2922e-04, 3.2361e-05,\n 3.3990e-06, 1.8056e-04, 8.0648e-06, 4.1617e-05, -7.0244e-05,\n -2.9748e-05, -4.2734e-05, -4.4497e-05, 6.4775e-05, 1.4116e-04,\n -2.9348e-06, -6.2331e-05, 1.3340e-04, 1.1803e-04, -2.3584e-06,\n -8.7806e-05, 3.6776e-05, 9.1813e-05, -8.8529e-05, 6.7560e-05,\n -1.6234e-04, 8.3386e-05, 1.3330e-04, 3.3415e-05, 4.6235e-05,\n 5.1126e-05, -3.3976e-05, -3.3428e-05, -6.2090e-05, -4.4386e-05,\n -1.0465e-05, -6.7627e-06, -6.2891e-06, -7.7159e-05, -8.7338e-07,\n 9.9675e-05, 3.3865e-05, -3.8539e-04, 7.9615e-05, -4.1223e-05,\n 6.4385e-05, 6.2399e-05, 1.6794e-04, -4.2566e-05, -1.4412e-05,\n -1.7969e-05, -1.8626e-04, 5.1260e-05, -9.9701e-05, -9.2950e-05,\n 1.3884e-05, 1.7448e-04, -9.1425e-06, 3.8349e-05, 5.5914e-06,\n 1.0098e-04, 1.4959e-04, 3.5664e-05, -3.4414e-05, 5.6446e-05,\n -1.2018e-04, -1.1727e-04, 1.3439e-04, -5.2063e-05, -1.9087e-05,\n 5.8895e-05, 4.7257e-05, 1.2684e-04, 3.4585e-06, -1.3961e-05,\n -2.1238e-05, -3.9988e-05, -1.2257e-04, -3.4813e-04, 1.8987e-04,\n -1.3721e-04, 4.0638e-05, 3.2419e-04, 2.1577e-05, 3.4221e-05,\n -1.0881e-04, -2.6401e-04, 6.5903e-05, -5.8694e-05, 5.1051e-05,\n -1.1504e-04, -1.0314e-04, 3.7524e-05, -5.4668e-05, 3.4773e-05,\n -1.4073e-04, -1.1703e-04, 4.6049e-05, 4.7514e-05, 7.1432e-05,\n -1.8005e-04, 1.6930e-05, -1.5299e-05, 5.0264e-05, 2.2807e-04,\n -5.1787e-06, 1.1892e-04, 1.0427e-04, 1.4540e-04, -9.8137e-05,\n 1.2415e-04, -2.7720e-05, -4.1917e-06, 1.1989e-04, 9.0063e-05,\n 1.7785e-04, -8.5764e-05, 6.2992e-05, -7.5636e-05, -9.1613e-05,\n 1.0967e-05, 6.9580e-04, 5.6227e-05, 1.3281e-07, -4.9165e-06,\n 4.2966e-05, -9.3338e-05, 4.7268e-05, -1.0659e-05, -5.3482e-05,\n -6.0922e-05, 3.7979e-05, 5.7317e-05, -9.4114e-05, -1.5186e-05,\n -1.0530e-05, -7.2750e-05, -1.1060e-04, 6.9138e-05, -3.7013e-05,\n 1.3032e-04, -1.6172e-04, -3.3576e-04, -2.0428e-04, 1.8467e-04,\n 2.3455e-04, 5.3556e-05, -2.0218e-05, -5.2688e-05, 5.0671e-05,\n 6.7452e-05, -1.7206e-05, 2.8895e-05, -5.5727e-05, 1.3454e-06,\n -3.6298e-05, -5.3914e-05, 4.1864e-05, -1.0387e-04, 8.9460e-06,\n -2.4409e-04, 1.6783e-04, 1.5466e-05, 9.5193e-05, 8.4748e-05,\n 1.5014e-04, 2.3180e-05, 8.7513e-06, -1.0517e-05, -7.5610e-06,\n -5.1765e-05, 6.6838e-05, 4.3192e-05, 6.9077e-06, -1.1339e-04,\n 8.6092e-05, -3.4203e-05, -1.1610e-04, 5.0058e-05, -6.7820e-05,\n 8.2158e-05, 7.4566e-05, 6.9103e-05, 8.4545e-05, -3.1220e-05,\n -2.9153e-05, -7.3964e-05, -1.0255e-04, -7.4317e-05, 7.7416e-05,\n 5.4939e-06, 1.2380e-05, 1.8715e-04, 6.3384e-05, -1.0816e-04,\n -5.5735e-06, -6.1928e-06, 2.3353e-05, -4.3284e-05, 2.9646e-04,\n 9.1680e-05, -5.8914e-05, -8.4180e-05, 4.9474e-05, 4.5368e-05,\n -6.9722e-05, 2.0961e-04, 2.7776e-07, -3.3757e-05, -1.0513e-04,\n 2.2773e-05, -2.1227e-05, 8.2700e-05, 3.1924e-06, 5.9073e-06,\n -4.1561e-05, -3.4725e-05, -1.8087e-05, 7.7209e-05, -2.0906e-04,\n -5.3982e-05, -6.7954e-06, -8.1903e-05, -1.1424e-04, 9.0850e-05,\n 1.0670e-05, 4.4018e-05, -8.8697e-05, 9.1036e-05, 1.3953e-04,\n -2.0458e-05, -1.0872e-04, -1.1589e-04, -8.9125e-05, 2.2785e-05,\n 1.5171e-04, 3.8246e-05, 1.2882e-04, -3.1785e-05, -5.0403e-07,\n 1.4668e-04, -1.0805e-04, -5.4874e-05, -5.0443e-05, -1.4823e-04,\n -1.8735e-04, -1.3734e-05, -7.8399e-05, 1.2244e-04, -6.1367e-06,\n -1.4072e-04, -1.4298e-05, 3.7133e-05, 7.8746e-05, -1.3393e-04,\n 6.1076e-06, -3.3087e-05, 4.6957e-05, 1.3791e-04, -9.5080e-05,\n -1.3632e-04, 3.9082e-05, -9.5616e-05, 1.8249e-05, 9.5975e-05,\n -1.2255e-04, 1.5278e-05, -1.8535e-04, 1.7163e-04, -1.6562e-04,\n 2.7584e-04, 1.1222e-04, -1.1057e-04, -1.5646e-05, -6.1884e-05,\n 7.8174e-05, -1.1816e-04, 4.6056e-05, 1.5411e-05, 4.2599e-05,\n -6.5317e-06, -1.1171e-04, -3.2819e-05, 5.0729e-05, 2.0825e-04,\n -1.0314e-04, -8.2079e-05, 5.8735e-07, -9.9120e-05, -6.3600e-05,\n 6.5823e-05, 1.7238e-04, -7.9821e-06, -7.2457e-05, 9.4220e-05,\n 6.4310e-05, 1.8898e-04, 1.5114e-05, 8.8912e-05, 7.1761e-05,\n -9.7784e-05, -3.5698e-05, -2.0938e-05, 1.0688e-04, -1.3577e-05,\n -1.8627e-04, 1.0809e-04, 1.1632e-06, 1.2452e-04, -1.8190e-05,\n 8.6250e-05, -7.6690e-05, -7.0865e-05, -2.3936e-04, 6.0124e-05,\n -5.9507e-05, -2.3281e-05, 1.1187e-04, 6.8612e-06, -1.9404e-04,\n 8.8257e-05, -2.0736e-06, -1.2287e-04, 9.0850e-05, -2.8113e-05,\n 6.7624e-05, -6.5054e-05, 1.3837e-04, -3.8310e-05, -2.5051e-05,\n -4.0407e-05, -8.9265e-05, -4.9160e-05, 2.3272e-05, -2.9756e-05,\n -9.2823e-05, -1.7432e-05, 6.8952e-05, 9.3879e-05, -1.6039e-05,\n 1.2698e-04, -4.0954e-04, -2.3735e-05, 2.0750e-05, -8.3282e-05,\n -1.5129e-04, 2.0444e-04, 8.7524e-05, -5.6388e-05, 5.3539e-05,\n -1.0483e-04, 2.6556e-05, -5.5393e-05, 6.0377e-05, 1.1090e-04,\n -1.8132e-05, 1.7691e-04, 2.4657e-05, 1.0157e-04, 1.5878e-05,\n -3.7788e-05, 2.7449e-06, -9.4840e-06, 6.4240e-05, 4.0122e-05,\n -8.2595e-05, -2.6512e-06, 1.2108e-04, 8.6350e-05, 9.0151e-05,\n -3.9805e-05, -7.9014e-06, -5.2899e-05, 5.0299e-05, -2.0053e-04,\n -8.4407e-05, 5.4618e-05, -7.8536e-05, -2.4467e-06, -1.1151e-04,\n 1.2030e-04, -6.7326e-05]), 'exp_avg_sq': tensor([1.3299e-06, 2.0549e-06, 2.2973e-06, 1.8525e-06, 1.1694e-06, 8.0312e-06,\n 1.9138e-06, 7.7872e-07, 5.8120e-07, 1.5528e-06, 6.2776e-07, 1.6208e-06,\n 2.0191e-06, 2.7417e-06, 1.0276e-06, 4.3069e-06, 3.4206e-06, 1.4537e-06,\n 7.8182e-07, 1.6483e-06, 1.3702e-06, 1.1652e-06, 1.2274e-06, 4.8117e-06,\n 2.2365e-06, 9.4511e-07, 1.1715e-06, 1.2194e-06, 3.2768e-06, 2.2557e-06,\n 1.1151e-06, 5.9091e-06, 3.6926e-06, 1.0302e-06, 2.8398e-06, 1.3490e-06,\n 5.7927e-06, 1.5737e-06, 2.7410e-06, 4.6922e-06, 2.9912e-06, 6.0369e-07,\n 1.9683e-06, 8.0529e-07, 1.4150e-06, 1.7413e-06, 2.5861e-06, 2.9147e-06,\n 9.1202e-07, 1.1727e-06, 3.5796e-07, 1.7217e-06, 2.4542e-06, 1.7310e-06,\n 5.8995e-07, 1.1166e-06, 8.2093e-07, 1.2816e-06, 8.4386e-06, 1.0161e-06,\n 1.0033e-06, 9.1658e-07, 9.2699e-07, 5.5314e-07, 6.0186e-07, 1.8164e-06,\n 1.1801e-06, 1.2494e-06, 1.1144e-06, 1.4407e-06, 2.7478e-06, 3.0972e-06,\n 1.9279e-06, 2.2419e-06, 1.8402e-06, 2.0824e-06, 1.5738e-06, 2.0581e-06,\n 5.9651e-06, 1.2567e-06, 2.1202e-06, 8.7935e-07, 5.4522e-07, 1.6147e-06,\n 1.7827e-06, 2.3070e-06, 1.3851e-06, 2.9110e-06, 1.6440e-06, 2.1333e-06,\n 3.6987e-06, 1.2848e-06, 7.6430e-07, 3.3633e-06, 1.9507e-06, 1.8413e-06,\n 1.8432e-06, 1.6399e-06, 7.9969e-07, 2.5078e-06, 1.6962e-06, 8.0584e-07,\n 1.8444e-06, 1.3057e-06, 4.4664e-06, 4.3428e-06, 9.7625e-07, 1.4894e-06,\n 2.3306e-06, 1.1815e-06, 1.8287e-06, 2.8063e-06, 1.1424e-06, 1.8570e-06,\n 3.2293e-06, 2.1989e-06, 1.5175e-06, 1.4591e-06, 3.5781e-06, 1.5847e-06,\n 1.3525e-06, 1.1381e-06, 1.4444e-06, 1.1451e-06, 1.5981e-06, 2.7799e-06,\n 3.4018e-06, 3.6470e-06, 1.2471e-06, 1.9134e-06, 3.1933e-06, 1.4731e-06,\n 7.1121e-07, 4.1539e-06, 3.7271e-06, 2.2280e-06, 1.7772e-06, 2.4458e-06,\n 3.6217e-06, 1.1124e-06, 2.1219e-06, 2.5968e-06, 1.4266e-06, 1.0471e-06,\n 1.9130e-06, 1.2843e-06, 1.3807e-06, 2.7780e-06, 1.1142e-06, 3.6288e-07,\n 1.7599e-06, 1.4144e-06, 1.2091e-06, 8.9344e-07, 1.8573e-06, 2.5197e-06,\n 2.9786e-06, 2.4426e-06, 1.7039e-06, 1.3005e-06, 1.7934e-06, 7.6803e-06,\n 2.6596e-06, 7.7124e-07, 1.7179e-06, 2.9397e-06, 1.9323e-06, 1.4700e-06,\n 1.6015e-06, 7.9672e-07, 2.7059e-06, 5.6977e-06, 5.3253e-06, 5.5909e-06,\n 1.5401e-06, 1.9902e-06, 9.9043e-07, 1.9513e-06, 4.9615e-07, 1.0634e-06,\n 2.4982e-06, 1.8112e-06, 2.4479e-06, 1.3972e-06, 8.9825e-07, 2.2759e-06,\n 3.0449e-06, 1.1319e-06, 2.9496e-06, 3.2138e-06, 2.1653e-06, 1.4750e-06,\n 5.5423e-07, 3.6308e-06, 3.4697e-06, 2.1323e-06, 1.8618e-06, 1.2534e-06,\n 1.7958e-06, 3.7303e-06, 2.0504e-06, 2.1705e-06, 2.1866e-06, 1.3432e-06,\n 1.3980e-06, 1.0519e-06, 1.9706e-06, 2.8798e-06, 9.4867e-06, 3.0888e-06,\n 1.9998e-06, 2.2318e-06, 4.6889e-06, 2.4569e-06, 1.1162e-06, 2.0627e-06,\n 3.2065e-06, 1.1639e-05, 3.2895e-06, 9.3634e-07, 2.1707e-06, 1.7437e-06,\n 6.9757e-07, 1.4696e-06, 8.8613e-07, 1.5805e-06, 1.1009e-06, 1.9304e-06,\n 3.0438e-06, 4.3809e-06, 2.6632e-06, 1.5423e-06, 3.1147e-06, 7.7127e-07,\n 1.0950e-05, 1.9439e-06, 1.3398e-06, 6.5913e-06, 1.2863e-06, 1.1695e-06,\n 4.5513e-06, 9.4136e-07, 1.0376e-06, 2.2674e-06, 2.1357e-06, 8.5297e-07,\n 1.1987e-06, 2.1995e-06, 1.7403e-06, 1.4533e-06, 6.4635e-07, 1.5196e-05,\n 9.4548e-07, 1.9036e-06, 1.7558e-06, 1.1580e-06, 1.2920e-06, 9.6207e-07,\n 1.7040e-06, 2.2526e-06, 1.2629e-06, 1.4687e-06, 2.1741e-06, 1.6457e-06,\n 1.3115e-06, 1.5318e-05, 3.6029e-06, 1.2763e-06, 5.5129e-06, 1.9810e-06,\n 5.2893e-06, 2.4021e-06, 2.0317e-06, 2.7313e-06, 1.3204e-06, 2.0496e-06,\n 1.7914e-06, 7.5597e-07, 7.1577e-07, 1.5591e-06, 1.1947e-06, 1.1558e-06,\n 1.3317e-06, 1.1225e-06, 1.0883e-06, 4.4792e-06, 1.4311e-06, 1.8000e-06,\n 8.3772e-07, 1.6995e-06, 3.8088e-06, 1.6033e-06, 2.0377e-06, 9.4433e-07,\n 1.1550e-06, 1.6103e-06, 1.0153e-06, 3.4217e-06, 1.7314e-06, 8.8333e-07,\n 1.0993e-06, 1.4509e-06, 9.4435e-07, 1.2642e-06, 1.0338e-06, 2.0564e-06,\n 8.2790e-07, 9.2317e-07, 8.9757e-07, 1.0674e-07, 1.8713e-06, 3.7143e-06,\n 2.5524e-06, 2.7617e-06, 9.8383e-07, 4.3374e-06, 1.9111e-06, 3.0796e-06,\n 3.2569e-06, 2.0243e-06, 9.4089e-07, 2.2196e-06, 2.8972e-06, 1.8491e-06,\n 2.8188e-06, 1.2376e-06, 1.1143e-06, 5.6246e-07, 9.6146e-07, 4.1814e-06,\n 2.7929e-06, 2.1617e-06, 1.3116e-06, 1.1355e-06, 1.3631e-06, 2.2675e-06,\n 2.1977e-06, 1.2843e-06, 1.9440e-06, 1.2467e-06, 2.4343e-06, 2.5932e-06,\n 1.6925e-06, 1.2984e-06, 2.5282e-06, 2.3643e-06, 2.6187e-06, 1.8343e-06,\n 1.0703e-06, 1.1640e-05, 1.4709e-06, 3.5408e-06, 1.8098e-06, 1.0612e-06,\n 1.4427e-06, 7.8539e-07, 8.6223e-07, 7.8345e-06, 1.3793e-06, 2.7314e-06,\n 1.8260e-06, 1.7406e-06, 1.7075e-06, 1.6121e-06, 1.9702e-06, 1.6307e-06,\n 1.7192e-06, 1.5868e-06, 2.3046e-06, 2.1014e-06, 6.1202e-06, 2.5108e-06,\n 1.2543e-06, 1.4136e-06, 2.1216e-06, 2.1204e-06, 1.7607e-06, 1.3318e-06,\n 1.0761e-06, 9.2316e-07, 6.8221e-06, 2.8054e-06, 8.2893e-07, 1.2522e-06,\n 2.7239e-06, 1.0851e-06, 1.1995e-06, 1.1064e-06, 1.6317e-06, 2.0394e-06,\n 1.4619e-06, 1.8358e-06, 3.0519e-06, 1.9349e-06, 2.3185e-06, 2.8554e-06,\n 2.5911e-06, 9.5240e-07, 1.5435e-06, 4.0114e-06, 8.3678e-06, 4.6031e-06,\n 2.0369e-06, 1.9591e-06, 1.2232e-06, 4.0851e-06, 3.4896e-06, 1.1091e-06,\n 1.6305e-06, 1.4220e-06, 1.6651e-06, 1.5817e-06, 1.4522e-06, 1.3697e-06,\n 7.2508e-06, 1.8759e-06, 1.4113e-06, 1.5976e-06, 7.0372e-07, 3.2506e-06,\n 1.7217e-06, 3.7904e-06, 8.3938e-07, 1.1342e-06, 3.2222e-06, 7.8509e-07,\n 4.0814e-06, 3.7511e-06, 2.5700e-06, 7.1571e-07, 2.7414e-06, 2.1769e-06,\n 2.0750e-06, 1.7194e-06, 1.3465e-06, 1.7135e-06, 1.1880e-06, 8.7220e-07,\n 1.0279e-06, 7.4014e-07, 2.2849e-06, 4.1222e-06, 6.6645e-07, 5.3532e-06,\n 1.2620e-06, 9.9105e-07, 1.1930e-06, 1.2763e-06, 1.4227e-06, 1.1014e-06,\n 2.2425e-06, 7.4892e-07, 1.1388e-06, 2.2011e-06, 1.3172e-06, 7.6817e-07,\n 1.7453e-06, 1.2219e-06, 2.6786e-06, 3.8154e-06, 2.5222e-06, 1.4189e-06,\n 1.0658e-06, 8.4956e-07, 2.4697e-06, 1.7517e-06, 3.1507e-06, 4.0503e-06,\n 2.1829e-06, 1.4947e-06, 1.4151e-06, 7.3784e-06, 7.2816e-06, 2.2794e-06,\n 3.1480e-06, 1.1115e-06, 3.8499e-06, 8.9316e-07, 2.0788e-06, 2.0388e-06,\n 1.5712e-06, 2.4287e-06, 6.3652e-06, 3.1326e-06, 2.0246e-06, 1.4919e-06,\n 2.2386e-06, 8.1060e-07, 8.9059e-07, 1.5271e-06, 1.6145e-06, 2.8189e-06,\n 1.2325e-06, 2.4211e-06, 5.3187e-06, 7.6317e-07, 1.3677e-06, 2.5783e-06,\n 5.3088e-06, 4.0202e-06, 6.2207e-07, 1.0774e-06, 2.5453e-06, 6.3274e-07,\n 9.8205e-07, 7.7768e-07, 9.3381e-07, 2.7678e-06, 1.0318e-06, 5.6249e-06,\n 1.4643e-06, 1.1047e-06])}, 71: {'step': 7160, 'exp_avg': tensor([-2.8449e-05, 3.6936e-05, -3.3814e-11, -6.1734e-05, 1.4056e-05,\n -6.3362e-12, 1.3996e-06, -8.8662e-05, -9.5367e-06, 4.0596e-05,\n -2.5225e-05, 3.5301e-05, 4.6631e-06, -6.6516e-05, 2.6290e-07,\n -1.2445e-04, -2.7963e-05, -1.9651e-05, 1.3955e-04, 3.1637e-05,\n 7.9097e-07, -9.5119e-05, 5.5759e-05, -9.0496e-06, 3.6396e-05,\n 2.2636e-06, -3.0767e-05, -5.3554e-05, -4.2085e-05, 3.7816e-05,\n 7.9635e-05, 3.2202e-09, -6.0700e-05, -1.5262e-05, -8.7384e-05,\n -3.8239e-05, 7.4412e-11, -2.3614e-06, 8.1008e-06, 8.8660e-05,\n 6.5505e-05, -8.2883e-05, 1.6352e-05, -4.4820e-05, -1.0606e-05,\n -7.9321e-05, -2.0511e-04, -4.3604e-05, -8.3502e-05, 1.6218e-05,\n 9.1775e-06, -8.9183e-05, -6.4308e-07, 7.3000e-05, -1.2604e-07,\n -1.4772e-05, 2.3502e-05, -1.9397e-05, -3.4535e-11, 4.2152e-06,\n 9.3004e-05, -1.1153e-04, -3.4200e-07, -6.5459e-05, -1.7721e-05,\n 1.0297e-04, 1.3847e-05, 1.5679e-05, 1.8401e-05, 8.2972e-05,\n 9.2477e-05, 6.8602e-05, 6.0815e-06, 1.3585e-04, 5.2228e-05,\n -1.0199e-05, 3.2608e-05, -9.3478e-05, 3.7555e-05, -3.7601e-05,\n -3.0159e-05, -3.0969e-05, -2.9311e-05, -1.8034e-05, -1.7864e-04,\n 7.5901e-05, 2.5345e-05, 4.0078e-05, 1.5501e-04, 3.5567e-05,\n 7.0268e-06, 1.3431e-05, -2.4509e-05, -1.0152e-04, 5.0253e-05,\n 3.4463e-05, -4.2003e-05, -3.5596e-05, -1.3481e-05, 7.9310e-06,\n -2.0417e-04, -3.6533e-05, -1.5409e-05, 2.1766e-05, 1.3712e-04,\n 2.1893e-10, 5.3898e-05, -8.7255e-07, -1.1972e-04, -1.0435e-05,\n -3.4199e-05, 1.1416e-04, 1.3036e-05, 2.0181e-05, 1.3118e-10,\n -9.1085e-06, 1.4255e-05, 1.4562e-05, -7.4386e-05, 1.1420e-05,\n 8.1752e-06, 3.1676e-05, 6.9451e-06, -6.5540e-05, -1.2575e-04,\n -7.3794e-05, -4.0187e-05, -6.7746e-07, 2.4793e-05, 1.4298e-05,\n 1.5677e-04, -2.7911e-05, 8.2052e-06, 4.1546e-11, 6.2726e-05,\n 4.5029e-05, 1.1037e-05, -1.8421e-05, 1.2524e-04, -2.6943e-05,\n 1.5469e-05, 8.7777e-05, 5.6524e-05, -8.0213e-06, 3.6580e-07,\n 2.2014e-05, 3.3366e-05, 7.4710e-06, -8.1192e-07, 9.3252e-05,\n 8.0494e-05, 3.8815e-05, 1.4498e-05, 2.7146e-06, 3.1248e-05,\n -5.7150e-05, -7.7154e-05, 2.7122e-05, 2.3968e-05, 1.9212e-05,\n 6.0517e-05, 1.3276e-07, 1.5433e-05, 1.0602e-04, 5.0872e-05,\n -2.2865e-04, 4.3222e-05, 3.1124e-05, 2.3144e-05, 2.9253e-06,\n 9.7555e-05, -4.6178e-05, 7.0627e-08, -9.2618e-12, 7.7156e-05,\n -6.9308e-05, -9.5558e-06, 2.1616e-05, 1.5835e-05, -3.3533e-05,\n -1.4448e-05, -8.4039e-05, -2.0809e-05, 3.4067e-05, -8.1331e-05,\n 3.6758e-05, -6.4780e-05, -4.2708e-06, -1.2127e-05, 1.6201e-05,\n -1.1731e-05, 1.9411e-05, 8.6576e-05, -1.1631e-06, 4.4671e-05,\n 4.9746e-05, -5.9219e-06, 9.8264e-05, 9.3134e-06, -3.5983e-11,\n -4.3437e-05, -7.4631e-05, -3.6587e-05, 1.6051e-05, 5.4755e-05,\n -7.3216e-05, -2.3605e-05, -8.6063e-05, 9.9774e-06, 1.2416e-04,\n -2.8106e-05, -2.0437e-05, 2.4423e-07, 9.9991e-05, 2.5382e-05,\n -1.6991e-05, 3.6352e-05, -2.2036e-04, 5.7340e-05, -3.3570e-05,\n -4.2351e-05, 1.8672e-05, -6.6169e-06, -5.5457e-06, -1.4131e-05,\n -1.5257e-05, 4.2217e-06, 2.1416e-05, 5.7901e-05, 3.7041e-05,\n -1.5584e-05, 3.8020e-05, 5.3505e-06, 5.5307e-05, 3.2787e-11,\n 1.1155e-05, -4.4191e-06, -2.6598e-05, 6.2263e-05, 6.8997e-05,\n -9.9694e-06, -1.0900e-05, 8.8899e-06, 1.3625e-04, 1.7052e-05,\n 1.3538e-04, 3.4791e-05, -1.8630e-05, -2.7585e-05, -4.2715e-05,\n -1.9637e-05, -6.9915e-07, 1.2601e-05, 1.6544e-05, -1.1942e-05,\n -2.7339e-05, 4.2632e-05, -7.6277e-06, -5.8316e-05, 9.3537e-05,\n -1.2934e-04, 2.5373e-05, 8.5446e-05, 2.2494e-05, -5.7454e-05,\n -9.1609e-11, 7.1762e-05, -6.1129e-05, 2.0663e-06, 7.1166e-05,\n -2.3312e-05, -6.0150e-05, -1.5266e-04, -2.0385e-04, 7.8323e-05,\n -3.7968e-07, -3.5471e-05, -4.7694e-06, -4.3857e-05, -6.7062e-05,\n 1.6061e-05, -4.4194e-05, 1.0171e-04, 1.1606e-05, -1.2710e-05,\n -1.4281e-06, -3.2557e-05, 6.0546e-05, -3.6289e-05, 3.1129e-05,\n 2.9442e-08, 8.0244e-05, 3.7502e-05, 7.7342e-05, 3.9826e-05,\n 1.6425e-04, 2.8367e-05, -3.9677e-06, 2.1291e-06, -7.1381e-05,\n -6.8949e-05, -2.4151e-06, 5.6255e-05, -4.2562e-05, -4.9648e-05,\n 7.7864e-05, -4.3763e-05, -4.5582e-05, 6.0077e-05, 2.2431e-05,\n 6.4998e-05, -2.4597e-05, -2.1933e-05, 2.3719e-05, 5.9415e-05,\n 2.0282e-05, -7.5388e-05, -8.1880e-05, 3.3178e-04, 6.8256e-06,\n 1.8316e-05, -5.7977e-05, -1.1715e-05, 5.3224e-05, 2.5573e-09,\n 7.5438e-05, 3.4800e-05, -1.3417e-05, -3.6901e-05, -3.2875e-05,\n -4.7939e-05, -2.5287e-05, -8.8941e-05, -1.6219e-05, 3.9916e-05,\n 2.7340e-05, 8.5087e-05, 6.8882e-05, 6.3441e-06, -1.0748e-04,\n 8.4149e-06, -1.9983e-05, 6.2012e-05, 1.3646e-05, 1.0241e-04,\n 8.2392e-05, -7.1241e-05, 6.4892e-05, 4.8103e-05, -1.0047e-07,\n -1.2279e-04, -1.6065e-06, -1.7679e-05, -1.3378e-04, -1.7979e-05,\n 4.9004e-05, 2.8095e-05, 7.6069e-05, -4.8019e-05, 7.5511e-05,\n -4.4540e-05, -5.8754e-05, -5.7734e-05, 4.4389e-05, -3.1340e-05,\n 6.2631e-05, -3.2589e-05, 1.6081e-05, -5.1302e-05, 2.5090e-05,\n 4.5625e-06, -8.0194e-05, 4.6320e-05, -1.0875e-04, 9.9474e-05,\n -1.1390e-04, 8.9098e-06, -4.9309e-05, 7.2454e-05, 3.2903e-05,\n -9.1181e-05, 6.9556e-05, 4.4563e-05, 8.3627e-05, 5.2486e-05,\n -1.4506e-05, 2.8738e-05, 5.7763e-05, 3.1991e-05, -3.6871e-05,\n -7.3238e-06, -4.5794e-05, 2.7023e-05, 4.0654e-05, 8.8207e-05,\n 7.2679e-06, -1.5858e-04, 8.3916e-06, 1.0651e-04, -1.1049e-04,\n 1.4923e-07, -3.1438e-06, -5.5582e-05, -1.7985e-06, 5.0674e-05,\n -1.0333e-08, -8.2206e-05, -1.3878e-05, 4.5375e-05, -2.3164e-05,\n 2.7228e-05, -2.8936e-05, 8.7698e-06, 3.2353e-06, 3.9052e-05,\n -8.2656e-05, -4.2811e-05, 1.3362e-05, -9.3938e-05, 5.7443e-05,\n 3.2187e-05, 2.1639e-05, -7.3040e-05, -6.8203e-05, 2.7871e-05,\n 5.1207e-05, 6.3526e-06, 6.6393e-05, 8.3524e-05, -7.2274e-05,\n -2.8777e-05, -3.1686e-05, 6.4145e-05, 1.2220e-05, -7.4247e-05,\n -1.0971e-04, 6.1788e-05, -4.5137e-05, 4.1546e-05, 2.0844e-05,\n 1.9984e-05, -1.2050e-07, -2.1348e-05, -3.1972e-11, -1.3788e-06,\n 6.8437e-05, -5.3955e-05, 4.9475e-05, 6.7437e-05, -5.3648e-05,\n 1.2144e-04, 3.7770e-05, -1.1021e-05, 2.5115e-05, 1.9091e-05,\n -4.9706e-05, -1.2221e-05, 1.9522e-05, 2.9064e-05, 6.4837e-05,\n 6.8053e-06, -7.4304e-06, -2.7758e-05, -3.6986e-06, 4.5465e-05,\n 1.6506e-05, -5.7616e-05, 1.6182e-05, -5.3723e-05, 2.2960e-05,\n -3.3480e-05, 6.3533e-05, -1.3823e-05, 1.5317e-04, -4.9527e-05,\n -2.9564e-05, 5.3630e-06, 4.6620e-05, -6.1409e-05, -4.3616e-05,\n -2.8495e-05, 4.5430e-05, -6.3370e-06, -6.0038e-05, 1.5026e-05,\n 2.7312e-05, -3.2563e-05, -8.1112e-06, -6.9690e-06, 2.4757e-05,\n -5.6151e-05, 3.8618e-05, -3.2450e-05, -5.3524e-06, 4.3644e-07,\n -2.4210e-05, -9.0178e-06, 1.3781e-04, 1.3986e-04, 1.0515e-04,\n -1.8173e-05, 4.2535e-05, -2.2118e-05, 8.8958e-05, -7.8128e-05,\n -1.7088e-05, 2.1751e-05, 7.7099e-05, 1.4342e-05, -6.0744e-05,\n 1.6114e-05, 7.8586e-05]), 'exp_avg_sq': tensor([7.7734e-07, 2.0958e-07, 2.6500e-10, 7.9091e-07, 4.0809e-07, 2.9087e-15,\n 6.9987e-07, 6.0926e-07, 2.4623e-07, 1.0635e-06, 4.1475e-07, 4.7394e-07,\n 8.6273e-08, 1.4692e-07, 4.8973e-07, 9.4028e-07, 3.2902e-07, 6.0598e-07,\n 5.7052e-07, 9.7318e-07, 3.0375e-07, 8.0504e-07, 1.0246e-06, 1.5203e-07,\n 1.2915e-06, 6.9111e-07, 6.4703e-07, 4.3756e-07, 6.1770e-08, 5.9145e-07,\n 4.9894e-07, 3.3165e-13, 1.4699e-06, 5.5823e-07, 2.3884e-06, 4.9972e-07,\n 1.0591e-10, 1.0028e-06, 7.2352e-08, 2.6135e-06, 9.5064e-07, 4.3655e-07,\n 9.6282e-07, 4.2489e-07, 3.3372e-07, 5.1484e-07, 1.8853e-06, 8.4937e-07,\n 6.1234e-07, 7.6356e-07, 2.6692e-07, 1.0026e-06, 6.2475e-07, 5.7039e-07,\n 9.8813e-07, 4.4422e-07, 2.8008e-07, 6.6259e-07, 3.2707e-11, 1.0597e-06,\n 9.6787e-07, 5.2082e-07, 6.1413e-07, 7.3976e-07, 4.2550e-07, 9.8704e-07,\n 6.1222e-07, 4.5348e-07, 4.5637e-07, 7.5063e-07, 7.0089e-07, 7.0737e-07,\n 9.1752e-07, 8.9229e-07, 7.3872e-07, 1.6018e-06, 7.4581e-07, 1.3186e-06,\n 5.2561e-07, 5.3725e-07, 1.2505e-06, 3.6034e-07, 6.0530e-07, 5.6740e-07,\n 7.9618e-07, 1.0254e-06, 6.7061e-07, 3.2333e-06, 1.4732e-06, 1.3219e-07,\n 3.0623e-08, 8.9969e-07, 2.6837e-07, 5.3529e-07, 4.6810e-07, 3.9173e-07,\n 1.3147e-06, 1.4401e-06, 8.0750e-07, 8.3512e-08, 9.0106e-07, 3.4427e-07,\n 4.7736e-07, 4.1165e-07, 1.0599e-06, 1.0105e-13, 5.9268e-07, 5.7078e-07,\n 6.4874e-07, 8.1052e-07, 1.1714e-06, 1.1552e-06, 8.4214e-07, 5.3847e-07,\n 1.7837e-10, 8.1205e-07, 5.3770e-07, 7.3151e-07, 1.2291e-06, 5.7070e-07,\n 6.6577e-07, 3.4122e-07, 8.4896e-07, 7.4369e-07, 1.0271e-06, 1.9652e-06,\n 5.4339e-07, 6.7519e-10, 4.2218e-07, 5.6076e-07, 9.4958e-07, 4.8317e-07,\n 3.7521e-07, 2.0881e-11, 1.4515e-07, 3.6573e-07, 6.3666e-07, 5.9026e-07,\n 1.4257e-06, 3.8752e-07, 9.3764e-07, 1.2685e-06, 5.9788e-07, 8.6406e-07,\n 2.4624e-10, 1.2398e-06, 7.0896e-07, 5.9476e-07, 1.0310e-06, 6.2250e-07,\n 7.6385e-07, 1.1168e-06, 7.2810e-07, 5.8860e-07, 6.4847e-07, 4.0290e-07,\n 6.4954e-06, 2.5942e-07, 5.8862e-07, 4.5138e-07, 9.3533e-07, 3.5856e-09,\n 9.4942e-07, 7.4086e-07, 3.5536e-07, 2.6971e-06, 5.9703e-07, 6.6289e-07,\n 6.6386e-07, 6.0425e-07, 6.7800e-06, 1.4543e-06, 1.8476e-08, 1.2359e-17,\n 4.7729e-07, 7.7733e-07, 8.8614e-07, 9.5753e-07, 3.8063e-07, 4.0606e-07,\n 7.7762e-07, 6.4933e-07, 1.1713e-06, 5.9110e-07, 9.1703e-07, 1.8780e-06,\n 1.0564e-06, 6.7086e-07, 4.1992e-07, 3.2917e-08, 1.0842e-06, 5.7331e-07,\n 4.4159e-07, 2.2798e-06, 6.6003e-07, 7.9075e-07, 2.6858e-07, 6.6655e-07,\n 1.1221e-06, 5.9627e-12, 1.0965e-06, 7.6387e-07, 1.1575e-06, 6.5797e-07,\n 1.2395e-06, 9.0340e-07, 8.1380e-07, 7.6375e-07, 2.2796e-06, 8.9256e-07,\n 6.5353e-08, 1.1239e-06, 7.9851e-09, 2.4814e-06, 4.9982e-07, 6.2285e-07,\n 4.3767e-07, 4.3236e-06, 1.6039e-06, 6.8319e-07, 5.3173e-07, 2.8971e-07,\n 6.9984e-07, 7.3978e-07, 5.1870e-07, 7.4820e-07, 7.5831e-07, 4.3049e-07,\n 1.0531e-06, 1.0187e-06, 1.4684e-06, 9.7844e-07, 1.1850e-06, 6.0212e-07,\n 1.3604e-11, 5.6455e-07, 1.6650e-07, 1.7597e-06, 1.1250e-06, 1.2627e-06,\n 4.9470e-07, 5.6761e-07, 6.4304e-07, 8.1459e-07, 6.8696e-07, 4.6471e-07,\n 5.7497e-07, 1.2370e-06, 6.4219e-07, 1.0131e-06, 3.7997e-07, 6.3308e-12,\n 4.3770e-07, 4.7356e-07, 4.2231e-07, 6.0636e-07, 6.4492e-07, 4.3845e-07,\n 7.9835e-07, 7.1652e-07, 6.6438e-07, 9.9970e-07, 6.3620e-07, 1.9843e-07,\n 5.3746e-07, 1.6725e-09, 8.1799e-07, 1.0596e-06, 5.4783e-08, 2.3497e-06,\n 9.4123e-08, 6.2806e-07, 3.1117e-06, 2.1004e-06, 8.4484e-07, 2.6691e-09,\n 6.4561e-07, 3.1022e-07, 4.3887e-07, 6.0180e-07, 3.6645e-07, 5.9159e-07,\n 4.0925e-07, 4.2576e-07, 4.4249e-07, 1.9561e-08, 3.9690e-07, 9.3719e-07,\n 3.3730e-07, 4.4948e-07, 7.5896e-10, 2.3856e-06, 1.0474e-06, 3.8528e-07,\n 5.4758e-07, 7.8235e-07, 4.6295e-07, 1.0404e-07, 1.0848e-06, 7.0538e-07,\n 5.5248e-07, 3.0083e-07, 5.5574e-07, 7.7749e-07, 4.6486e-07, 8.1882e-07,\n 4.3623e-07, 4.8285e-07, 4.1364e-07, 1.9685e-07, 8.1273e-07, 3.9172e-07,\n 2.0126e-06, 2.9410e-06, 5.8444e-07, 1.5662e-07, 6.5895e-07, 2.2634e-06,\n 2.3682e-06, 5.6701e-07, 5.4061e-07, 8.1087e-07, 2.2910e-08, 6.6483e-07,\n 6.8425e-13, 1.9113e-06, 3.5230e-07, 4.2170e-07, 4.6285e-07, 5.7278e-07,\n 1.2456e-06, 8.1194e-07, 9.7058e-07, 2.0954e-06, 4.8800e-07, 6.3344e-07,\n 1.0145e-06, 1.4994e-06, 3.6194e-07, 8.4026e-07, 8.9545e-07, 7.9946e-07,\n 1.3228e-06, 5.5726e-07, 9.5021e-07, 8.6948e-07, 4.8289e-06, 2.2381e-06,\n 3.7642e-07, 4.0240e-09, 1.2359e-06, 2.9769e-08, 1.6835e-06, 8.3066e-07,\n 1.0981e-06, 5.9870e-07, 4.0977e-07, 6.2980e-07, 7.0484e-07, 8.4232e-07,\n 6.6396e-07, 1.2792e-06, 9.1271e-07, 1.6493e-06, 9.6825e-07, 8.9541e-07,\n 2.3783e-07, 7.7591e-07, 6.3256e-07, 8.3275e-07, 4.4992e-08, 6.3709e-08,\n 7.0596e-07, 1.0499e-06, 1.6084e-06, 9.3369e-07, 5.2930e-07, 6.4753e-07,\n 4.1052e-07, 6.3783e-07, 1.5004e-06, 1.6621e-06, 1.1686e-06, 4.8027e-07,\n 8.4689e-07, 5.1627e-07, 7.2901e-07, 2.1578e-06, 7.8087e-08, 5.8374e-07,\n 6.7658e-07, 8.6113e-07, 2.6368e-07, 6.4394e-07, 3.3572e-07, 7.8014e-08,\n 1.9604e-06, 5.4261e-07, 4.4710e-07, 2.1938e-06, 1.2333e-08, 2.2864e-08,\n 9.0889e-07, 2.1233e-06, 7.2893e-07, 1.0115e-09, 1.0662e-06, 2.0915e-07,\n 6.8699e-07, 3.6916e-07, 6.8583e-07, 5.7316e-07, 1.4029e-06, 7.8516e-08,\n 1.2279e-06, 5.1369e-07, 5.7461e-07, 7.7720e-07, 1.0976e-06, 3.5254e-07,\n 3.2115e-07, 3.2302e-07, 5.1481e-07, 4.7184e-07, 1.5797e-06, 4.3421e-07,\n 1.3328e-06, 6.1076e-07, 8.3610e-07, 4.1639e-07, 3.9712e-07, 2.3038e-07,\n 9.6477e-07, 4.9481e-08, 8.5389e-07, 1.0018e-06, 3.5884e-07, 6.7708e-07,\n 4.6165e-07, 7.6691e-07, 3.2439e-07, 1.2183e-09, 4.0567e-07, 2.2493e-09,\n 3.3788e-07, 7.2504e-07, 6.8220e-07, 6.5782e-07, 1.4073e-06, 5.3642e-07,\n 3.0320e-06, 6.1480e-07, 1.0715e-06, 9.3067e-07, 6.2953e-07, 3.7777e-07,\n 5.4089e-07, 8.4857e-07, 3.5473e-07, 2.6656e-06, 1.3127e-06, 7.1265e-07,\n 2.3267e-07, 5.3944e-07, 8.2594e-07, 9.7954e-07, 7.2642e-07, 1.2855e-07,\n 2.7625e-06, 4.2432e-07, 3.9650e-07, 1.9285e-06, 2.2414e-06, 1.9527e-06,\n 1.3128e-06, 5.1634e-07, 5.9920e-09, 5.1121e-07, 1.4116e-06, 1.5255e-06,\n 7.2139e-07, 7.8265e-07, 1.2580e-08, 7.9548e-07, 6.2735e-07, 7.6976e-07,\n 2.1724e-07, 4.3403e-07, 6.3098e-07, 1.1838e-06, 6.3077e-07, 9.1478e-08,\n 7.3547e-07, 8.9201e-07, 2.5155e-07, 5.0178e-07, 1.2595e-06, 6.9825e-07,\n 1.3124e-06, 1.3762e-06, 3.5375e-07, 1.9611e-07, 4.8149e-07, 4.8608e-07,\n 5.3042e-07, 1.2165e-06, 2.3191e-06, 5.0965e-07, 3.5212e-07, 1.1071e-06,\n 7.9629e-07, 1.4769e-06])}, 72: {'step': 7160, 'exp_avg': tensor([[[[-3.4903e-05]],\n\n [[-7.7851e-05]],\n\n [[-1.5429e-05]],\n\n ...,\n\n [[ 8.1837e-05]],\n\n [[ 5.6906e-05]],\n\n [[ 3.8417e-05]]],\n\n\n [[[ 3.0747e-05]],\n\n [[-2.8469e-05]],\n\n [[ 3.4001e-05]],\n\n ...,\n\n [[ 1.0651e-05]],\n\n [[ 1.2886e-05]],\n\n [[-1.5322e-05]]],\n\n\n [[[-7.0170e-05]],\n\n [[-2.0208e-05]],\n\n [[-6.1571e-05]],\n\n ...,\n\n [[-5.6242e-05]],\n\n [[-1.8494e-05]],\n\n [[-5.8229e-06]]],\n\n\n ...,\n\n\n [[[-2.9464e-05]],\n\n [[-1.3103e-05]],\n\n [[-4.7468e-06]],\n\n ...,\n\n [[ 1.4318e-05]],\n\n [[ 2.8203e-05]],\n\n [[ 1.8745e-05]]],\n\n\n [[[ 1.2745e-05]],\n\n [[ 1.5111e-05]],\n\n [[-1.6036e-05]],\n\n ...,\n\n [[-2.2404e-05]],\n\n [[-1.4037e-05]],\n\n [[-7.4356e-06]]],\n\n\n [[[-3.2011e-05]],\n\n [[ 1.5919e-05]],\n\n [[-2.5651e-05]],\n\n ...,\n\n [[-8.2975e-05]],\n\n [[-7.3086e-05]],\n\n [[-7.2306e-06]]]]), 'exp_avg_sq': tensor([[[[1.7960e-07]],\n\n [[2.6229e-07]],\n\n [[1.0274e-07]],\n\n ...,\n\n [[4.2477e-07]],\n\n [[1.3499e-07]],\n\n [[7.1173e-08]]],\n\n\n [[[5.9019e-08]],\n\n [[7.3712e-08]],\n\n [[8.8422e-08]],\n\n ...,\n\n [[2.1261e-07]],\n\n [[1.4779e-07]],\n\n [[3.7770e-08]]],\n\n\n [[[2.9817e-07]],\n\n [[1.1923e-07]],\n\n [[2.5002e-07]],\n\n ...,\n\n [[4.2619e-07]],\n\n [[1.1313e-07]],\n\n [[4.9305e-08]]],\n\n\n ...,\n\n\n [[[3.0764e-07]],\n\n [[1.8731e-07]],\n\n [[1.5076e-07]],\n\n ...,\n\n [[3.3580e-07]],\n\n [[2.2828e-07]],\n\n [[7.7679e-08]]],\n\n\n [[[2.9106e-08]],\n\n [[4.0129e-08]],\n\n [[6.1826e-08]],\n\n ...,\n\n [[1.9140e-07]],\n\n [[4.8030e-08]],\n\n [[3.5369e-08]]],\n\n\n [[[2.4278e-07]],\n\n [[6.3123e-08]],\n\n [[1.1008e-07]],\n\n ...,\n\n [[3.4328e-07]],\n\n [[8.6963e-08]],\n\n [[9.5926e-08]]]])}, 73: {'step': 7160, 'exp_avg': tensor([ 1.5306e-04, 1.9747e-04, -1.3905e-04, -2.4394e-05, -1.1887e-04,\n 2.7321e-04, -3.9817e-04, -2.2289e-04, 3.3128e-05, 5.7116e-05,\n 1.2130e-04, -9.8228e-05, -2.7743e-05, -1.0366e-04, 2.7208e-04,\n -3.1311e-04, -1.1049e-05, 1.0934e-04, 2.5022e-05, -9.8851e-05,\n -1.4333e-04, -9.3054e-05, 1.1359e-04, 3.0155e-05, 3.4777e-04,\n -3.9280e-05, 9.5903e-05, -9.9894e-05, -3.5263e-05, 1.1262e-04,\n -7.8268e-05, 2.7947e-04, -6.1579e-05, -3.2674e-05, 2.9465e-05,\n 6.1436e-05, -2.3949e-05, -8.6933e-06, -1.3900e-04, -2.0246e-05,\n 2.6442e-04, 5.1211e-05, 1.0873e-04, 9.3372e-05, -2.4779e-04,\n 1.1718e-04, 1.4698e-04, -1.9342e-04, 2.1904e-04, 6.9315e-06,\n 3.3034e-05, -1.9388e-05, 2.1733e-04, 2.8069e-04, -1.6460e-04,\n 4.0544e-05, 1.1806e-04, -2.3209e-04, 6.0196e-05, -1.0522e-04,\n 1.4791e-04, -1.2449e-04, -1.1373e-04, -1.7375e-04, -5.3657e-05,\n -5.7323e-05, -1.4081e-04, -1.1802e-04, 8.1359e-05, 1.2788e-04,\n 3.2680e-04, 3.9651e-05, -4.3765e-05, 3.0479e-04, 3.5639e-04,\n 5.6886e-06, -1.9559e-04, -3.9555e-04, 6.0638e-05, -1.2142e-04,\n 4.3550e-04, -1.8868e-04, -2.3136e-04, -6.0413e-06, 5.3919e-05,\n 2.6507e-04, -7.0685e-05, 3.8393e-04, 1.7601e-04, -1.0358e-04,\n 1.5472e-04, -1.2205e-04, 1.9086e-07, 5.5886e-05, -1.0308e-04,\n -4.0412e-05, -8.7323e-05, -1.6594e-05, -5.2625e-05, -7.2041e-05,\n -2.6746e-04, -3.1500e-04, 3.3372e-05, 4.4041e-05, 1.4353e-04,\n 2.9017e-04, -7.2272e-05, -5.6500e-04, 1.7112e-04, -2.5952e-04,\n -7.3285e-05, -7.3477e-05, 2.7817e-04, 1.7376e-04, 1.4276e-04,\n -2.3851e-04, -1.4852e-04, -6.7882e-06, 4.9128e-05, 7.2158e-05,\n 1.5410e-05, -6.2367e-04, 1.3156e-04, -4.5704e-04, -1.6019e-04,\n 1.3022e-04, 2.0907e-04, -1.1489e-04, 1.9182e-04, 1.7466e-04,\n 6.8602e-05, -2.8921e-04, 8.5575e-05, 1.0992e-04, 9.4628e-05,\n -1.6167e-04, 1.8327e-04, -3.2835e-04, 2.6299e-04, 8.4643e-05,\n 6.1261e-06, 5.5978e-05, -2.3871e-04, -2.8958e-05, -7.7339e-06,\n -2.9755e-04, -2.0776e-05, 3.1318e-05, 1.6863e-04, 9.1334e-05,\n 1.3319e-04, 7.3569e-05, 1.2883e-04, -3.6440e-04, 2.6651e-04,\n 1.1155e-04, 5.5252e-05, 3.4528e-04, -1.2687e-04, -1.0669e-05,\n -3.1249e-04, -2.0508e-05, -5.1765e-05, 9.1009e-05, 1.9556e-04,\n 2.0971e-04, -2.0214e-04, 1.0436e-04, -1.1011e-05, -2.2096e-04,\n -7.0061e-05, 7.9693e-05, 1.2820e-04, 1.3536e-04, 1.1614e-04,\n 2.4017e-04, 3.3654e-05, -3.4831e-04, 2.2653e-04, 1.2121e-04,\n -2.6734e-05, -4.9565e-05, 6.2457e-05, -2.5427e-05, 3.2816e-04,\n 3.1128e-04, -5.2824e-05, 1.1950e-04, 2.1260e-04, -5.9100e-04,\n -3.3098e-05, 1.6450e-05, 2.2742e-04, -9.6374e-05, 6.7713e-05,\n 7.9706e-05, -2.3791e-04, 2.1110e-05, 8.2287e-05, -1.9913e-04,\n 1.8842e-04, -5.1257e-05, -1.8529e-05, -1.3003e-04, -6.1987e-05,\n -6.6667e-05, -3.0055e-05, -7.1123e-05, 1.4220e-04, 1.0826e-05,\n 1.4337e-04, 2.4659e-04, 6.2677e-04, -8.2221e-05, 7.7614e-05,\n -2.1782e-05, -2.8663e-04, -5.7719e-05, 2.6525e-04, 2.3142e-05,\n 8.2409e-05, -1.3327e-04, -8.9324e-05, 1.8772e-05, 1.3652e-05,\n -3.3745e-04, -1.0567e-04, -2.7673e-05, -1.0455e-04, -3.5995e-04,\n 2.5376e-04, 2.6860e-04, -6.3047e-05, 3.3493e-04, 2.3480e-05,\n 6.3195e-05, 6.0100e-06, 1.3103e-04, 1.6365e-05, -2.1755e-04,\n -2.1315e-04, 2.0363e-04, -1.6353e-04, 3.5655e-04, -4.1477e-05,\n 9.1346e-05, 1.0448e-04, -1.9010e-04, 2.4975e-05, -1.3893e-04,\n -1.5997e-04, 2.7106e-05, -4.9726e-05, -6.7514e-05, -2.0859e-04,\n -1.7539e-04]), 'exp_avg_sq': tensor([6.5967e-06, 2.2019e-06, 1.1830e-05, 4.7355e-06, 5.9781e-06, 4.9783e-06,\n 1.4784e-05, 4.2755e-06, 3.6313e-06, 3.9883e-06, 2.2889e-06, 9.3099e-06,\n 7.1537e-06, 4.0473e-06, 4.8096e-06, 9.5249e-06, 2.9119e-06, 6.9880e-06,\n 2.9255e-06, 5.4672e-06, 1.9826e-05, 3.8600e-06, 9.9753e-06, 1.9962e-05,\n 9.7341e-06, 5.0498e-06, 3.1751e-06, 2.8129e-06, 5.3144e-06, 2.7769e-06,\n 2.6155e-06, 3.4720e-06, 3.9303e-06, 2.1525e-06, 3.3767e-06, 1.1331e-05,\n 4.2806e-06, 5.8113e-06, 5.4882e-06, 6.3065e-06, 4.9351e-06, 1.5121e-05,\n 3.1617e-06, 7.8569e-06, 3.4315e-06, 7.6527e-06, 6.8472e-06, 8.8373e-06,\n 5.1114e-06, 3.3025e-06, 5.4291e-06, 9.5112e-06, 1.1511e-05, 3.8512e-06,\n 4.3822e-06, 2.8266e-06, 3.6773e-06, 4.6698e-06, 3.7141e-06, 4.1883e-06,\n 2.5309e-06, 4.3055e-06, 6.1501e-06, 4.3969e-06, 4.1207e-06, 5.6850e-06,\n 4.1765e-06, 5.1642e-06, 3.2265e-06, 5.7221e-06, 5.9439e-06, 1.3235e-05,\n 2.9262e-06, 4.6567e-06, 2.9716e-06, 1.5854e-05, 1.4657e-05, 6.0554e-06,\n 3.7970e-06, 3.7486e-06, 3.9411e-05, 3.4485e-06, 6.9759e-06, 2.3244e-06,\n 3.8064e-06, 2.8628e-06, 3.2370e-06, 7.6292e-06, 3.8276e-06, 9.2432e-06,\n 6.0304e-06, 9.4823e-06, 1.5361e-06, 6.0316e-06, 4.1900e-06, 4.2705e-06,\n 4.0364e-06, 5.8614e-06, 9.2115e-06, 4.0766e-06, 4.7009e-06, 7.4075e-06,\n 4.9557e-06, 8.2562e-06, 4.2178e-06, 6.1325e-06, 5.3856e-06, 1.7770e-05,\n 6.7061e-06, 5.0643e-06, 3.7390e-06, 2.8520e-06, 5.5994e-06, 6.0695e-06,\n 7.7773e-06, 3.5703e-06, 9.7548e-06, 2.9425e-06, 3.2769e-06, 2.6532e-06,\n 6.8867e-06, 4.8173e-06, 2.3828e-06, 9.0650e-06, 9.0595e-06, 4.5402e-06,\n 2.6516e-06, 6.5486e-06, 5.7664e-06, 4.2337e-06, 7.7727e-06, 8.8663e-06,\n 2.1212e-05, 5.9267e-06, 4.5576e-06, 6.3670e-06, 3.3793e-06, 1.2441e-05,\n 3.7381e-06, 7.6448e-06, 7.2082e-06, 1.4754e-06, 4.4260e-06, 4.8674e-06,\n 6.1275e-06, 4.4084e-06, 3.8162e-06, 4.0457e-06, 2.1851e-06, 1.1431e-05,\n 6.5284e-06, 3.4689e-06, 4.3647e-06, 3.2419e-05, 8.6386e-06, 5.0054e-06,\n 4.1283e-06, 4.9142e-06, 5.6683e-06, 5.7381e-06, 6.8158e-06, 3.3959e-06,\n 2.9850e-06, 3.8169e-06, 6.5502e-06, 7.8520e-06, 1.2620e-05, 6.0257e-06,\n 9.2050e-06, 3.5321e-06, 2.3472e-06, 6.7887e-06, 5.0268e-06, 1.0501e-05,\n 2.7556e-06, 7.4032e-06, 3.2853e-06, 1.1647e-05, 1.0689e-05, 3.3037e-06,\n 4.5352e-06, 8.5177e-06, 2.4323e-06, 6.3542e-06, 5.3102e-06, 5.9522e-06,\n 7.2371e-06, 3.9850e-06, 3.8309e-06, 7.2718e-06, 1.0746e-05, 5.3121e-06,\n 5.6260e-06, 3.4859e-06, 4.1856e-06, 4.3286e-06, 9.6267e-06, 5.0671e-06,\n 5.6910e-06, 5.0281e-06, 2.5635e-06, 5.7238e-06, 4.0102e-06, 4.9306e-06,\n 3.8595e-06, 1.7025e-05, 4.2710e-06, 2.9304e-06, 5.8193e-06, 2.2082e-06,\n 1.0341e-05, 7.6353e-06, 3.4696e-06, 4.5398e-06, 4.2819e-06, 5.8323e-06,\n 2.0005e-05, 7.3129e-06, 3.0624e-06, 5.6518e-06, 2.0646e-06, 2.5871e-06,\n 4.4634e-06, 5.2984e-06, 3.9193e-06, 2.8434e-06, 5.6571e-06, 5.5369e-06,\n 4.6098e-06, 7.3328e-06, 5.0241e-06, 4.2406e-06, 1.1898e-05, 1.2488e-05,\n 1.0625e-05, 6.3942e-06, 7.4222e-06, 4.0279e-06, 3.2195e-06, 4.9483e-06,\n 3.4690e-06, 4.5483e-06, 3.7516e-06, 4.8874e-06, 3.3421e-06, 3.1178e-06,\n 1.0248e-05, 4.0837e-06, 3.5084e-06, 5.2156e-06, 3.7860e-06, 3.0013e-06,\n 7.1553e-06, 7.3722e-06, 3.6654e-06, 5.0795e-06])}, 74: {'step': 7160, 'exp_avg': tensor([ 9.9398e-05, 1.0809e-04, -7.8207e-05, -4.7608e-05, -3.9320e-05,\n 1.6137e-04, -1.8382e-04, -2.8712e-04, 4.8953e-05, -9.0709e-06,\n 1.3729e-04, -3.8788e-05, -3.6123e-05, -7.1478e-05, 2.9519e-04,\n -9.5798e-05, -6.8338e-05, 6.2355e-05, -5.3117e-05, 8.1372e-05,\n -6.8819e-05, -3.8086e-05, 7.7142e-05, 6.0526e-05, 1.8595e-04,\n -7.1304e-05, 9.7747e-05, -9.6842e-05, -2.6637e-05, 4.5666e-05,\n -4.8462e-05, 1.6073e-04, -2.2249e-06, 4.7461e-06, 6.6920e-05,\n 7.9498e-05, 1.0828e-05, -3.5690e-05, -1.0517e-04, 4.5991e-05,\n 1.3530e-04, 5.6144e-05, 8.4121e-05, -2.5361e-05, -1.5856e-04,\n 1.3360e-04, 5.1839e-05, -5.1438e-05, 1.2565e-04, 2.5395e-05,\n -2.9377e-06, 5.8641e-05, 6.3933e-05, 1.9307e-04, -1.1229e-04,\n -1.3663e-05, 1.1100e-04, -2.7040e-04, 1.2281e-04, -1.0399e-04,\n 8.8563e-05, -1.4912e-04, -5.6448e-05, -1.2134e-04, -7.5768e-05,\n -3.4351e-05, -8.0100e-05, -6.1229e-05, -1.3521e-04, 6.5333e-05,\n 2.1823e-04, 1.4027e-04, -1.1848e-05, 3.3486e-04, 1.9707e-04,\n 1.1265e-04, -8.4744e-05, -2.2085e-04, 6.2583e-05, -7.6974e-05,\n 2.1868e-04, -1.4339e-05, -1.9510e-04, -3.2706e-05, 2.0942e-05,\n 1.6003e-04, -2.8708e-05, 1.4756e-04, 1.1665e-04, -1.7414e-05,\n 1.0649e-04, -7.7479e-05, 1.5709e-05, -2.4144e-05, -1.0028e-04,\n -5.0820e-05, -5.1477e-05, -1.7104e-05, 3.4105e-06, -4.8571e-05,\n -2.4404e-04, -9.6919e-05, 1.3476e-04, 6.5397e-06, 8.4774e-05,\n 1.6426e-04, -9.2905e-05, -3.0575e-04, 3.2809e-05, -2.4241e-05,\n -7.8969e-06, -8.0243e-05, 2.1482e-04, 8.4259e-05, 8.5658e-05,\n -1.4671e-04, -4.5615e-06, 1.5478e-05, 2.5944e-05, 5.7239e-05,\n -3.7696e-05, -5.0944e-04, 1.6761e-05, -1.0829e-04, -2.0803e-04,\n 7.2941e-05, 1.0408e-04, -2.1343e-04, 1.0605e-04, 1.2315e-04,\n 3.0033e-04, -1.4026e-04, -2.8430e-05, -1.3752e-05, 3.7684e-05,\n -1.3790e-04, 9.3514e-05, -1.7261e-04, 6.8107e-05, 1.1154e-04,\n -7.4592e-06, 3.6100e-05, -2.5674e-04, -5.6330e-05, -5.3606e-06,\n -2.2481e-04, 5.5715e-05, -2.1377e-05, 1.0598e-04, 3.4616e-05,\n 2.2107e-05, 1.4062e-06, 6.3387e-05, -2.7890e-04, 2.0209e-04,\n 2.1266e-05, 4.9127e-05, 1.2749e-04, -1.3168e-04, -2.0031e-05,\n -2.5282e-04, -2.4235e-05, -2.6640e-05, -3.9725e-05, 1.4811e-04,\n 1.4538e-04, -9.4133e-05, -1.0531e-05, 5.5505e-05, -1.1778e-04,\n -3.4901e-05, 4.9459e-05, 1.0313e-04, 6.2648e-05, 8.6721e-05,\n 1.8988e-04, 7.5206e-05, -1.0789e-04, 7.1701e-05, 1.2002e-04,\n -5.4289e-05, 6.5590e-05, 2.5068e-05, 4.5811e-05, 1.5959e-04,\n 2.4209e-04, -2.6419e-05, 1.2051e-04, 1.1237e-04, -3.9255e-04,\n -5.1786e-05, 7.4360e-05, 1.3433e-04, -3.5306e-05, 5.2324e-06,\n 5.8273e-05, -1.4135e-04, 2.7411e-06, 1.4612e-04, -3.5027e-05,\n 8.3384e-05, -9.3581e-05, 6.9037e-05, -8.1359e-05, -9.9376e-05,\n -7.8832e-06, 5.9327e-05, -3.7657e-05, 1.3602e-04, -1.5482e-05,\n 1.7610e-04, 1.3364e-04, 3.1949e-04, -4.3606e-05, 5.5670e-05,\n 1.8363e-05, -7.2670e-05, 4.2691e-05, 1.8175e-04, -7.9777e-05,\n 5.0275e-05, -1.6444e-04, -2.3041e-05, 9.7284e-05, 1.8099e-05,\n -2.3548e-04, -1.5407e-04, -7.6504e-05, -1.0737e-04, -1.5814e-04,\n 1.9421e-04, 1.7039e-04, -5.7524e-05, 7.0009e-05, 1.0585e-04,\n 3.3748e-05, -2.9878e-05, 8.8268e-05, 7.9172e-06, -1.3599e-04,\n -1.4374e-04, 9.0102e-05, -1.2006e-04, 1.5765e-04, -1.1619e-04,\n 9.2734e-05, 7.5408e-05, -1.2279e-04, 1.3264e-04, -1.4174e-04,\n 1.9379e-06, 1.0714e-04, -5.8945e-05, 6.8562e-06, -9.0426e-05,\n -2.7356e-05]), 'exp_avg_sq': tensor([3.2123e-06, 9.4203e-07, 3.9648e-06, 2.3520e-06, 2.3180e-06, 1.7178e-06,\n 2.4565e-06, 3.4025e-06, 1.7213e-06, 2.0914e-06, 9.5034e-07, 2.9959e-06,\n 3.8426e-06, 1.3849e-06, 3.6533e-06, 2.4775e-06, 2.7940e-06, 3.9311e-06,\n 1.1806e-06, 2.0424e-06, 9.3174e-06, 2.3033e-06, 3.2300e-06, 8.3041e-06,\n 2.8038e-06, 2.7795e-06, 1.7347e-06, 1.0228e-06, 4.2009e-06, 1.6875e-06,\n 1.5681e-06, 2.6227e-06, 2.9044e-06, 1.0317e-06, 2.8430e-06, 6.4411e-06,\n 2.4239e-06, 2.8713e-06, 2.1704e-06, 3.6043e-06, 3.8342e-06, 9.0611e-06,\n 1.0010e-06, 4.2381e-06, 2.4784e-06, 4.2655e-06, 3.0102e-06, 4.9488e-06,\n 2.3080e-06, 1.9670e-06, 2.6146e-06, 5.1818e-06, 2.8845e-06, 1.5781e-06,\n 2.2828e-06, 1.1022e-06, 2.3041e-06, 2.8304e-06, 1.7571e-06, 2.6369e-06,\n 1.1297e-06, 2.9425e-06, 1.3817e-06, 1.4458e-06, 2.1726e-06, 1.7543e-06,\n 1.5550e-06, 2.1033e-06, 1.7384e-06, 1.8457e-06, 2.3976e-06, 5.8988e-06,\n 9.7537e-07, 2.4779e-06, 7.9870e-07, 1.0112e-05, 4.0523e-06, 1.9175e-06,\n 3.0629e-06, 1.3770e-06, 6.4502e-06, 1.5279e-06, 2.2477e-06, 1.0567e-06,\n 2.3609e-06, 1.6224e-06, 7.9581e-07, 3.5985e-06, 1.6894e-06, 2.8852e-06,\n 2.9730e-06, 3.6293e-06, 8.5584e-07, 2.0682e-06, 2.8521e-06, 1.2828e-06,\n 1.6802e-06, 1.8227e-06, 4.5840e-06, 1.2449e-06, 3.3844e-06, 2.4578e-06,\n 3.4143e-06, 2.8464e-06, 1.7264e-06, 1.8114e-06, 2.5283e-06, 6.4224e-06,\n 2.4216e-06, 2.3441e-06, 9.7907e-07, 1.6958e-06, 3.3499e-06, 4.6532e-06,\n 2.9498e-06, 1.6617e-06, 5.8761e-06, 1.8532e-06, 2.6518e-06, 1.4824e-06,\n 3.6957e-06, 3.2107e-06, 1.6116e-06, 5.1453e-06, 4.9664e-06, 1.2317e-06,\n 7.9515e-07, 3.9826e-06, 2.5862e-06, 1.1577e-06, 3.6094e-06, 2.7816e-06,\n 1.4032e-05, 3.2659e-06, 1.0117e-06, 2.6765e-06, 1.9532e-06, 7.3144e-06,\n 1.1945e-06, 5.2592e-06, 2.6991e-06, 9.1984e-07, 2.8137e-06, 2.1133e-06,\n 2.9098e-06, 1.4109e-06, 2.2733e-06, 8.8010e-07, 1.0897e-06, 4.6429e-06,\n 1.7434e-06, 1.6607e-06, 1.2392e-06, 1.7168e-05, 4.1886e-06, 2.6792e-06,\n 1.3255e-06, 2.2804e-06, 2.0840e-06, 2.6262e-06, 4.0328e-06, 1.7439e-06,\n 1.2373e-06, 1.8335e-06, 6.0275e-06, 2.8574e-06, 3.0319e-06, 3.0032e-06,\n 4.4355e-06, 1.6561e-06, 1.3003e-06, 2.3608e-06, 2.2893e-06, 3.0278e-06,\n 1.6680e-06, 1.8670e-06, 1.8227e-06, 5.1991e-06, 4.2007e-06, 1.6149e-06,\n 3.6530e-06, 4.5971e-06, 1.6988e-06, 2.3117e-06, 2.1861e-06, 2.8752e-06,\n 3.2999e-06, 2.0281e-06, 1.5898e-06, 4.0384e-06, 4.2747e-06, 2.2531e-06,\n 2.1823e-06, 1.4456e-06, 1.0508e-06, 2.1314e-06, 4.1427e-06, 2.2448e-06,\n 4.0987e-06, 3.1195e-06, 1.4970e-06, 2.2136e-06, 2.1946e-06, 3.0135e-06,\n 2.4670e-06, 3.9362e-06, 1.5877e-06, 1.1418e-06, 4.8242e-06, 1.3259e-06,\n 6.7160e-06, 2.6541e-06, 1.4610e-06, 2.0055e-06, 2.1535e-06, 4.3809e-06,\n 1.1825e-05, 2.2087e-06, 2.0413e-06, 2.7550e-06, 8.6740e-07, 2.1238e-06,\n 2.0445e-06, 2.8216e-06, 1.3154e-06, 1.2964e-06, 2.2218e-06, 4.6541e-06,\n 1.6040e-06, 1.4516e-06, 2.3632e-06, 1.9855e-06, 5.2138e-06, 6.5677e-06,\n 6.3494e-06, 1.1867e-06, 3.3558e-06, 1.8744e-06, 1.5002e-06, 2.3169e-06,\n 1.1569e-06, 1.8405e-06, 1.6482e-06, 2.1392e-06, 1.4636e-06, 1.6418e-06,\n 5.2331e-06, 1.9024e-06, 2.5500e-06, 3.3278e-06, 2.1617e-06, 1.9184e-06,\n 3.3096e-06, 2.9216e-06, 1.2291e-06, 1.8068e-06])}, 75: {'step': 7160, 'exp_avg': tensor([[[[-8.3589e-06, -9.4798e-06, 2.1344e-05],\n [-2.1260e-05, 3.9848e-06, 2.3896e-05],\n [-8.2388e-06, -4.3885e-06, -4.4338e-07]],\n\n [[-8.3598e-06, -2.3023e-05, -9.1194e-06],\n [-2.2775e-05, -2.6460e-05, -1.3186e-05],\n [-2.1231e-06, -7.2822e-06, -5.3064e-06]],\n\n [[-7.7731e-06, -1.3269e-06, -1.6035e-05],\n [ 1.7867e-05, 9.4936e-06, 1.0145e-05],\n [ 2.0836e-05, 1.0710e-05, 2.1112e-05]],\n\n ...,\n\n [[-1.3539e-05, 2.3670e-05, -1.1183e-05],\n [-1.7104e-05, 1.7524e-05, -1.8128e-05],\n [-1.0998e-05, 1.1372e-05, -3.5438e-06]],\n\n [[-6.3376e-06, 1.6371e-05, 1.1094e-05],\n [ 9.3328e-06, 2.6025e-05, 4.6632e-07],\n [-9.7903e-06, 1.6482e-06, -5.4076e-07]],\n\n [[-7.4790e-06, -2.4911e-05, -1.1538e-05],\n [-1.2231e-05, 8.2163e-06, 5.6579e-06],\n [ 4.8553e-06, 1.8727e-06, 1.5455e-06]]],\n\n\n [[[ 1.2931e-05, 1.8457e-07, 3.4682e-06],\n [-4.9954e-06, 1.0204e-05, 1.7527e-05],\n [ 2.2787e-05, 7.6442e-06, 3.3475e-05]],\n\n [[-5.7447e-06, 1.5678e-05, 1.1549e-05],\n [-1.9806e-05, -2.5633e-06, 9.0767e-06],\n [ 9.2844e-06, 4.3584e-07, 1.8963e-05]],\n\n [[ 7.9647e-06, 8.8592e-06, 1.2254e-05],\n [ 1.5619e-05, 9.1780e-06, -1.1387e-05],\n [-9.7506e-07, 4.9895e-06, 8.9608e-06]],\n\n ...,\n\n [[ 5.4645e-06, 1.8924e-05, 1.6659e-05],\n [ 1.6540e-05, 9.9510e-06, -1.0957e-05],\n [ 1.1568e-05, 2.1495e-06, 8.1691e-06]],\n\n [[-1.4389e-06, -3.0572e-06, 1.7174e-05],\n [ 1.6580e-06, 8.6593e-06, 7.4039e-06],\n [-4.6908e-06, 2.1734e-05, 1.4977e-06]],\n\n [[ 8.6947e-06, 8.4631e-06, 3.7819e-06],\n [ 6.9649e-06, 9.0601e-08, -3.1821e-06],\n [-6.4436e-06, -1.7433e-05, -1.6326e-05]]],\n\n\n [[[-2.2076e-07, -1.0860e-05, 5.4117e-06],\n [ 8.2336e-06, -1.3550e-06, 1.2446e-05],\n [ 2.1904e-06, -2.7102e-05, 1.2659e-05]],\n\n [[ 5.3611e-06, 4.5369e-06, 9.3403e-06],\n [-9.9146e-06, 2.9222e-06, -1.7524e-06],\n [-1.2727e-05, 2.6448e-06, 1.9956e-05]],\n\n [[-2.3505e-06, -5.7678e-07, 1.1862e-05],\n [-1.0340e-06, 5.5562e-06, 8.2281e-06],\n [ 3.1047e-06, 2.7121e-06, 6.6251e-06]],\n\n ...,\n\n [[ 2.1525e-06, -6.3527e-07, 9.8126e-06],\n [-5.4695e-06, 1.8920e-06, 4.4530e-07],\n [-6.5336e-06, -1.3036e-06, 2.0031e-05]],\n\n [[-1.0258e-05, 1.0257e-06, -1.5405e-05],\n [-4.0508e-06, -6.3804e-06, 1.4959e-06],\n [-3.4681e-05, 7.7448e-07, -2.5925e-05]],\n\n [[ 2.9354e-06, -7.2580e-06, 6.0255e-06],\n [ 1.4819e-05, 2.4734e-06, 7.2997e-06],\n [ 7.4257e-06, 9.3205e-06, 6.3598e-07]]],\n\n\n ...,\n\n\n [[[ 1.2146e-05, 1.2711e-05, -3.5242e-06],\n [ 8.2379e-06, 6.2211e-06, 6.6267e-07],\n [ 3.7864e-06, -1.2575e-06, 1.2624e-06]],\n\n [[ 2.0749e-06, -5.1270e-06, -4.9651e-06],\n [-4.5450e-07, 2.4589e-06, -3.4049e-06],\n [ 3.6762e-06, 1.1667e-06, 6.6908e-06]],\n\n [[ 4.1992e-06, -5.6336e-07, -1.0848e-06],\n [ 1.0786e-05, 2.2855e-05, -7.0534e-08],\n [-3.2238e-06, -3.1324e-07, 3.1895e-06]],\n\n ...,\n\n [[-1.2366e-06, 6.6073e-06, -4.3553e-07],\n [-7.3555e-06, -3.3126e-06, 3.5813e-06],\n [-2.8770e-06, -1.5186e-05, 7.2165e-06]],\n\n [[-6.9229e-06, 5.5234e-06, -5.3069e-06],\n [-6.9869e-06, -9.2964e-06, -2.6167e-06],\n [-1.0745e-05, -6.2437e-06, -1.0603e-05]],\n\n [[-6.5922e-06, -2.9786e-07, -1.5978e-05],\n [ 1.0126e-05, -1.9999e-06, -1.7110e-05],\n [ 2.7246e-07, 8.8350e-07, 1.3585e-05]]],\n\n\n [[[ 2.3311e-06, -1.2168e-05, -1.4904e-05],\n [ 2.5238e-06, -9.4467e-06, -8.2467e-06],\n [ 5.8450e-06, -1.1510e-05, -3.2082e-06]],\n\n [[ 3.9294e-06, 2.2329e-06, 1.1131e-06],\n [-6.5229e-06, -1.1387e-07, -4.5862e-06],\n [-1.1582e-05, 5.7063e-06, 1.1310e-05]],\n\n [[-5.7293e-06, -6.0758e-06, -3.0333e-06],\n [-7.0435e-06, -8.6848e-06, 9.4285e-07],\n [-8.9431e-06, -6.2734e-06, -4.8017e-06]],\n\n ...,\n\n [[ 4.2905e-07, 1.3842e-05, 3.3372e-06],\n [ 4.5497e-06, 7.7345e-06, 8.4608e-06],\n [-6.3517e-06, 1.6767e-06, 6.7642e-06]],\n\n [[ 1.4593e-06, -6.3741e-06, 4.7223e-06],\n [ 7.2485e-08, -3.3951e-06, 8.3034e-07],\n [-1.9523e-05, 3.5276e-06, -8.8049e-06]],\n\n [[-1.1569e-06, -3.2516e-06, -2.6040e-06],\n [-1.0505e-05, -9.1791e-06, 3.2418e-06],\n [-2.2646e-06, -7.7857e-06, -8.1993e-06]]],\n\n\n [[[-9.0039e-06, -7.5798e-06, -1.7575e-06],\n [-1.9345e-06, -6.3844e-06, -6.0641e-06],\n [-7.8819e-06, -1.5793e-05, -1.2089e-05]],\n\n [[-9.1324e-06, 5.8024e-06, 2.3745e-05],\n [-6.3449e-06, 2.0166e-06, 9.7830e-06],\n [ 1.7110e-05, 1.3764e-05, 2.3430e-05]],\n\n [[-2.6130e-07, -1.7142e-05, -2.1814e-05],\n [ 8.2194e-07, -2.1588e-06, 1.9037e-06],\n [ 4.8228e-06, -2.3431e-06, 2.3104e-05]],\n\n ...,\n\n [[ 1.0776e-05, 8.5439e-06, 5.8045e-06],\n [-1.6388e-05, 6.3397e-06, 1.2224e-05],\n [ 1.0399e-05, 9.8350e-06, 4.7612e-06]],\n\n [[ 3.3179e-06, 1.2452e-05, -1.0720e-06],\n [-1.6678e-06, 7.1055e-06, -6.1812e-06],\n [-6.5941e-06, -3.9440e-06, -7.8876e-06]],\n\n [[-6.8817e-07, -2.0763e-05, -2.0467e-05],\n [-4.7592e-06, -7.0239e-06, 1.2324e-05],\n [ 9.9099e-06, 2.3861e-05, 3.5250e-06]]]]), 'exp_avg_sq': tensor([[[[3.9654e-08, 4.3859e-08, 9.3135e-08],\n [7.0702e-08, 9.4054e-08, 5.3707e-08],\n [5.2199e-08, 4.9423e-08, 5.1160e-08]],\n\n [[5.2167e-08, 3.4667e-08, 6.1926e-08],\n [9.5373e-08, 3.4307e-08, 5.1676e-08],\n [4.0703e-08, 3.6389e-08, 4.9529e-08]],\n\n [[6.5323e-08, 8.7446e-08, 6.9730e-08],\n [5.6181e-08, 6.5177e-08, 5.5173e-08],\n [4.1261e-08, 4.1632e-08, 4.6885e-08]],\n\n ...,\n\n [[9.0213e-08, 7.8313e-08, 9.1890e-08],\n [1.4570e-07, 1.1142e-07, 9.1475e-08],\n [8.7021e-08, 7.9672e-08, 8.1502e-08]],\n\n [[2.9124e-08, 2.2580e-08, 2.8549e-08],\n [3.2486e-08, 2.5308e-08, 6.3902e-08],\n [2.7733e-08, 2.7733e-08, 3.8984e-08]],\n\n [[8.7963e-08, 6.2908e-08, 5.9994e-08],\n [5.3097e-08, 6.3538e-08, 6.1199e-08],\n [5.1894e-08, 4.6617e-08, 5.3559e-08]]],\n\n\n [[[2.9613e-08, 2.9463e-08, 2.9020e-08],\n [3.0264e-08, 2.9733e-08, 9.4297e-08],\n [2.6735e-08, 2.2658e-08, 4.7719e-08]],\n\n [[1.3854e-08, 1.7229e-08, 2.2029e-08],\n [3.3995e-08, 2.5018e-08, 3.4493e-08],\n [1.7529e-08, 2.1973e-08, 1.4746e-08]],\n\n [[3.1227e-08, 2.8764e-08, 2.8740e-08],\n [3.2021e-08, 2.6968e-08, 2.6173e-08],\n [2.6006e-08, 3.8522e-08, 5.2802e-08]],\n\n ...,\n\n [[5.9394e-08, 2.7457e-08, 3.2668e-08],\n [2.8941e-08, 3.0417e-08, 6.0056e-08],\n [4.0622e-08, 4.6891e-08, 8.3687e-08]],\n\n [[9.6401e-09, 9.9602e-09, 1.1968e-08],\n [1.0693e-08, 1.7981e-08, 1.2819e-08],\n [1.0037e-08, 2.3930e-08, 2.4389e-08]],\n\n [[2.9216e-08, 2.7553e-08, 4.1207e-08],\n [2.0612e-08, 2.8537e-08, 2.8702e-08],\n [2.2508e-08, 2.9260e-08, 6.4810e-08]]],\n\n\n [[[2.3057e-08, 1.6789e-08, 3.7013e-08],\n [3.8192e-08, 1.8747e-08, 2.3852e-08],\n [2.6752e-08, 2.4156e-08, 2.9187e-08]],\n\n [[6.5802e-09, 1.3579e-08, 1.3487e-08],\n [1.5016e-08, 1.4543e-08, 1.1583e-08],\n [2.5967e-08, 1.5533e-08, 1.7154e-08]],\n\n [[4.8360e-08, 1.4355e-08, 2.2052e-08],\n [1.7442e-08, 2.8425e-08, 3.0642e-08],\n [1.8491e-08, 2.4879e-08, 4.9910e-08]],\n\n ...,\n\n [[3.2922e-08, 3.1982e-08, 3.3097e-08],\n [2.4152e-08, 4.7919e-08, 3.5983e-08],\n [2.9557e-08, 4.1699e-08, 5.4119e-08]],\n\n [[7.7118e-09, 6.9130e-09, 9.2921e-09],\n [8.9125e-09, 1.7150e-08, 1.7211e-08],\n [1.5367e-08, 1.7097e-08, 2.1439e-08]],\n\n [[5.4012e-08, 1.6955e-08, 2.4881e-08],\n [2.0815e-08, 3.1664e-08, 7.5725e-08],\n [1.6043e-08, 2.4956e-08, 5.0615e-08]]],\n\n\n ...,\n\n\n [[[2.6862e-08, 2.7164e-08, 3.2266e-08],\n [2.0725e-08, 1.4106e-08, 1.7841e-08],\n [2.3773e-08, 1.3337e-08, 1.9007e-08]],\n\n [[1.5688e-08, 1.2370e-08, 2.5393e-08],\n [4.5423e-09, 2.9036e-09, 5.5120e-09],\n [1.8111e-08, 1.3956e-08, 1.9178e-08]],\n\n [[4.5585e-08, 2.8477e-08, 2.5226e-08],\n [2.9140e-08, 3.8469e-08, 3.2864e-08],\n [3.1866e-08, 3.9386e-08, 4.0407e-08]],\n\n ...,\n\n [[1.6329e-08, 1.4875e-08, 2.4915e-08],\n [1.6216e-08, 2.0726e-08, 1.9080e-08],\n [2.1178e-08, 2.6589e-08, 3.0981e-08]],\n\n [[1.2348e-08, 9.6061e-09, 1.2411e-08],\n [9.3816e-09, 7.0210e-09, 8.6141e-09],\n [1.2241e-08, 2.3979e-08, 8.1033e-09]],\n\n [[2.9436e-08, 2.3113e-08, 2.1597e-08],\n [5.8155e-08, 4.7016e-08, 4.5405e-08],\n [1.9534e-08, 2.6114e-08, 2.5457e-08]]],\n\n\n [[[1.7725e-08, 1.9761e-08, 1.8118e-08],\n [2.1898e-08, 2.2470e-08, 1.7043e-08],\n [1.8134e-08, 1.7139e-08, 2.0677e-08]],\n\n [[7.0296e-09, 7.6124e-09, 1.0865e-08],\n [9.4974e-09, 5.4144e-09, 8.2004e-09],\n [1.2091e-08, 1.6892e-08, 1.8396e-08]],\n\n [[1.8312e-08, 1.6528e-08, 1.9318e-08],\n [1.9125e-08, 1.9025e-08, 2.1200e-08],\n [1.5699e-08, 1.9931e-08, 4.5936e-08]],\n\n ...,\n\n [[2.9718e-08, 1.8096e-08, 1.9976e-08],\n [1.8404e-08, 2.2963e-08, 2.0678e-08],\n [2.0097e-08, 2.8239e-08, 2.7772e-08]],\n\n [[6.1005e-09, 7.5408e-09, 4.8409e-09],\n [8.7584e-09, 1.2577e-08, 1.0338e-08],\n [1.3084e-08, 1.1204e-08, 1.4759e-08]],\n\n [[1.5285e-08, 1.5974e-08, 1.9213e-08],\n [1.2312e-08, 1.7220e-08, 2.1462e-08],\n [1.2839e-08, 1.3987e-08, 2.0976e-08]]],\n\n\n [[[3.2841e-08, 2.9749e-08, 1.6813e-08],\n [3.9533e-08, 1.5873e-08, 3.1242e-08],\n [4.0601e-08, 2.2066e-08, 2.0702e-08]],\n\n [[2.7833e-08, 2.4134e-08, 1.4563e-08],\n [2.2874e-08, 2.3398e-08, 1.4702e-08],\n [2.2114e-08, 2.6460e-08, 3.3931e-08]],\n\n [[2.3564e-08, 2.9507e-08, 3.0643e-08],\n [3.6242e-08, 3.1855e-08, 2.7584e-08],\n [2.3956e-08, 3.7325e-08, 2.5920e-08]],\n\n ...,\n\n [[5.2673e-08, 2.2803e-08, 3.0983e-08],\n [3.4068e-08, 5.2482e-08, 4.8280e-08],\n [4.3686e-08, 4.2895e-08, 6.3568e-08]],\n\n [[1.2242e-08, 9.7056e-09, 1.3402e-08],\n [1.1737e-08, 9.5546e-09, 9.8714e-09],\n [1.1490e-08, 1.8704e-08, 1.3613e-08]],\n\n [[2.1080e-08, 3.9413e-08, 3.3727e-08],\n [2.0541e-08, 4.7977e-08, 8.1648e-08],\n [2.2990e-08, 5.3158e-08, 3.1702e-08]]]])}, 76: {'step': 7160, 'exp_avg': tensor([ 1.6407e-04, -3.4701e-05, -3.5071e-05, -6.9738e-05, 7.7841e-05,\n 6.6411e-05, -7.9257e-05, -5.1362e-05, 6.9837e-05, -2.2176e-04,\n 6.3162e-05, -8.6682e-05, -1.3758e-04, -3.1312e-05, -8.5830e-05,\n 3.9319e-05, 2.5604e-04, -4.3850e-05, 2.6434e-05, -1.5827e-05,\n -9.0682e-05, 1.4280e-05, 1.2371e-04, -9.6009e-06, -2.1958e-04,\n -5.0858e-05, 1.7563e-04, -6.1888e-05, 5.7658e-05, -2.8758e-04,\n 7.5812e-05, -1.2574e-04, -1.1403e-04, 3.3187e-04, -8.1412e-05,\n 5.6405e-05, -9.0464e-05, -1.4046e-05, 2.4259e-05, 1.0680e-04,\n -1.4985e-04, -9.0294e-06, 7.0036e-05, 3.1219e-05, -2.1167e-05,\n -1.5101e-04, -5.3302e-04, -1.4287e-04, -6.8587e-05, 1.0150e-05,\n -4.2272e-05, -1.4364e-04, 3.3446e-05, 8.8466e-05, -1.6620e-04,\n 1.2727e-04, -2.6752e-04, -1.6911e-04, 5.0714e-05, 4.9386e-05,\n 1.0846e-04, 5.2809e-05, -4.4600e-05, -1.8340e-04, -4.6394e-05,\n 4.9044e-05, -6.4807e-04, -1.6484e-04, -3.8051e-05, 6.6649e-05,\n -1.3237e-04, 2.1241e-04, 9.5598e-05, -1.2055e-04, 5.3701e-05,\n 1.4608e-04, 3.6853e-05, -2.9303e-04, 1.3132e-04, 7.5818e-05,\n 1.6326e-04, 1.3309e-04, -3.8848e-05, 2.1335e-04, -7.4385e-06,\n -2.2680e-05, -1.2348e-05, -8.2304e-05, 2.8213e-05, -1.7159e-04,\n -6.0342e-05, -2.5426e-05, 8.7498e-05, 6.3766e-05, -4.3413e-05,\n 3.9531e-05, -6.3272e-05, 5.6650e-05, 1.7761e-05, 6.8615e-05,\n 9.1531e-05, -3.6649e-05, 2.1172e-04, 1.2520e-04, -3.0235e-05,\n -3.2773e-05, 6.7664e-05, -1.2590e-05, 6.0565e-05, -1.0529e-04,\n 1.2673e-04, 1.1106e-04, -1.0639e-04, -1.1563e-04, 1.4586e-05,\n 6.0191e-05, 1.0272e-05, -2.4992e-04, 7.5725e-05, 8.1177e-05,\n 4.7571e-05, 5.1845e-05, 1.9510e-04, -9.8829e-05, -1.6020e-04,\n -6.8779e-05, -6.9305e-05, -1.0876e-04, -7.6869e-05, -4.0594e-05,\n 1.0486e-04, -1.0245e-04, -2.2773e-04, -9.2963e-05, 8.1712e-05,\n -2.0050e-04, 2.1227e-05, -9.9654e-06, -1.6294e-05, 2.4699e-05,\n -4.5195e-05, -1.4430e-04, 1.2919e-04, 1.0086e-04, -1.2151e-04,\n -3.5106e-05, 1.6732e-04, -1.6290e-04, -6.3475e-05, -9.0396e-05,\n 9.9330e-05, -1.6549e-04, 1.4815e-05, -3.0011e-04, 2.6294e-05,\n -9.8734e-05, 2.7311e-05, 1.3237e-04, 5.7666e-05, 8.8688e-05,\n -2.4193e-04, -2.4922e-04, 6.6536e-05, 3.2852e-04, -8.5282e-05,\n -6.9785e-05, 6.0978e-05, -1.0567e-04, -1.2233e-04, -1.4188e-04,\n 2.9119e-04, -1.3431e-05, 1.7920e-04, 4.2821e-05, 3.9170e-05,\n 1.5474e-04, 6.8762e-05, 5.9689e-06, 2.4868e-05, 8.1543e-05,\n 4.1100e-05, -1.5015e-05, -1.5133e-04, 8.9572e-05, -1.9098e-05,\n -2.6547e-04, -1.5560e-04, -8.7459e-05, 1.7090e-04, -1.5985e-04,\n 2.2147e-04, 1.6064e-04, -3.1885e-04, 4.1274e-05, -1.0150e-06,\n -2.0353e-05, -4.4095e-05, 3.3485e-05, 2.0984e-05, 3.0283e-05,\n -2.0008e-04, -3.1998e-05, 6.9241e-05, -1.9954e-05, -1.0168e-05,\n 1.8843e-05, -1.6317e-04, -7.0333e-05, 1.7531e-04, -1.8578e-05,\n 2.9123e-05, -9.4763e-05, -2.6246e-05, -6.5419e-05, -6.3453e-05,\n -8.6120e-06, 1.2585e-04, 4.8538e-05, 1.3415e-04, 1.5008e-04,\n 3.0096e-05, 1.3888e-04, 2.9758e-05, 4.4927e-05, 1.1455e-04,\n 2.0079e-04, 1.3564e-04, -9.7643e-05, -1.5233e-04, -2.7059e-04,\n 1.0428e-05, 6.0986e-05, 1.0110e-04, -4.9502e-06, -6.4180e-05,\n -4.8954e-05, 4.4385e-05, 3.8762e-04, -4.0212e-05, 9.4115e-06,\n 4.6123e-04, 2.3478e-04, 8.7253e-06, -8.3245e-06, 7.4746e-05,\n -7.3161e-05, -2.1342e-04, -5.4182e-05, 7.6826e-05, 3.0076e-05,\n 1.2592e-04, -3.1272e-05, 1.4881e-04, -7.5911e-05, 1.1129e-04,\n 9.5340e-05]), 'exp_avg_sq': tensor([2.6811e-06, 1.4089e-06, 1.8750e-06, 8.5867e-06, 1.0673e-06, 2.9044e-06,\n 1.2771e-06, 3.5257e-06, 1.4208e-06, 1.6037e-06, 5.7094e-06, 1.3651e-06,\n 2.0539e-06, 2.5262e-06, 1.5923e-06, 2.7854e-06, 2.1234e-06, 6.7097e-06,\n 1.0415e-05, 1.6373e-06, 8.2850e-06, 1.7959e-06, 1.3219e-06, 2.5231e-06,\n 1.0468e-06, 1.0375e-06, 2.5839e-06, 2.1268e-06, 7.5774e-06, 8.3033e-06,\n 8.2297e-06, 4.5221e-06, 1.3178e-06, 9.9622e-06, 3.5950e-06, 3.2300e-06,\n 1.7116e-06, 1.3059e-06, 2.8507e-06, 9.6932e-07, 3.0439e-06, 1.9135e-06,\n 3.1929e-06, 1.6657e-06, 2.1405e-06, 1.7468e-06, 3.9794e-05, 1.9324e-06,\n 7.5402e-06, 1.8086e-06, 2.3031e-06, 4.1433e-06, 1.0890e-06, 4.6051e-06,\n 3.0957e-06, 1.2844e-06, 3.6582e-06, 3.2045e-06, 2.3518e-06, 1.2424e-06,\n 1.6644e-06, 1.5222e-06, 2.6113e-06, 1.1303e-05, 2.0327e-06, 3.0145e-06,\n 1.2806e-05, 3.1485e-06, 2.3734e-06, 1.8428e-06, 3.4787e-06, 2.7631e-06,\n 3.2232e-06, 2.0227e-06, 3.5355e-06, 1.8571e-06, 3.6753e-06, 2.0043e-06,\n 3.3961e-06, 3.2048e-06, 2.1782e-06, 3.1561e-06, 1.3451e-06, 3.9232e-06,\n 2.5510e-06, 2.4652e-06, 6.6036e-06, 4.0496e-06, 3.1755e-06, 2.3363e-06,\n 1.2168e-06, 1.9951e-06, 4.2529e-06, 1.1910e-06, 1.8410e-06, 7.2983e-07,\n 2.9609e-06, 2.0918e-06, 1.0955e-06, 1.2014e-06, 7.7934e-06, 2.2161e-06,\n 2.5316e-06, 2.7776e-06, 3.8054e-06, 6.5789e-06, 1.4093e-06, 1.5259e-06,\n 2.3016e-06, 2.4830e-06, 3.9010e-06, 5.1615e-06, 2.4818e-06, 2.1382e-06,\n 3.2521e-06, 4.6717e-06, 2.1480e-06, 2.6801e-06, 1.6105e-06, 4.2579e-06,\n 2.0946e-06, 1.6539e-06, 2.2203e-06, 1.7189e-06, 4.1006e-06, 3.9269e-06,\n 2.9850e-06, 2.5641e-06, 1.6099e-06, 5.7238e-06, 1.7454e-06, 2.8020e-06,\n 7.6038e-06, 3.7610e-06, 2.4094e-06, 2.0727e-06, 1.2825e-06, 1.4583e-06,\n 1.7465e-06, 1.5910e-06, 3.2449e-06, 4.6320e-06, 1.4613e-06, 1.4611e-06,\n 2.9633e-06, 3.0810e-06, 1.5151e-06, 1.8161e-06, 1.5612e-06, 2.0673e-06,\n 1.5787e-06, 1.8993e-06, 1.8241e-06, 2.4795e-06, 2.7781e-06, 3.0339e-06,\n 1.3345e-06, 9.0929e-07, 1.5288e-06, 1.8308e-06, 1.6487e-06, 2.3789e-06,\n 1.6251e-06, 7.8042e-06, 2.3228e-06, 4.8632e-06, 3.9631e-06, 3.2419e-06,\n 2.4512e-06, 1.1393e-06, 3.5962e-06, 2.0233e-06, 2.6072e-06, 2.2320e-06,\n 7.5823e-06, 3.2138e-06, 2.0134e-06, 1.5191e-06, 8.7583e-07, 2.3427e-06,\n 5.6567e-06, 3.9260e-06, 2.6800e-06, 3.5237e-06, 1.7576e-06, 4.9261e-06,\n 2.1858e-06, 3.0578e-06, 4.6888e-06, 9.8551e-06, 4.4082e-06, 1.8803e-06,\n 6.7103e-06, 6.2872e-06, 1.6100e-06, 2.4259e-06, 2.4113e-06, 2.3761e-06,\n 3.6222e-06, 2.4998e-06, 5.0184e-06, 2.3581e-06, 3.6407e-06, 4.5186e-06,\n 1.7733e-06, 2.5195e-06, 3.9875e-06, 1.3748e-06, 2.6840e-06, 1.3291e-06,\n 8.7482e-07, 4.1343e-06, 1.4553e-06, 3.5611e-06, 3.0119e-06, 2.3416e-06,\n 9.3533e-07, 4.2215e-06, 2.9796e-06, 1.6785e-06, 2.4816e-06, 2.2698e-06,\n 4.2490e-06, 2.2018e-06, 2.1968e-06, 1.1416e-06, 2.3033e-06, 1.5698e-06,\n 6.8912e-06, 2.6715e-06, 4.0551e-06, 3.2307e-06, 2.8064e-06, 1.6825e-06,\n 2.3778e-06, 2.7733e-06, 1.2612e-06, 8.6116e-06, 1.5337e-06, 4.4224e-06,\n 3.7716e-06, 2.8713e-06, 1.3411e-06, 2.7033e-06, 7.0744e-07, 1.9093e-06,\n 2.5219e-06, 1.0451e-06, 1.6947e-06, 2.2424e-06, 2.6614e-06, 2.0636e-06,\n 2.9977e-06, 1.8839e-06, 2.1512e-06, 1.5487e-06])}, 77: {'step': 7160, 'exp_avg': tensor([-8.4505e-05, -1.0300e-04, -1.2337e-05, 3.9773e-05, 1.6877e-05,\n 7.8230e-05, -2.7548e-05, 2.7446e-06, -2.8600e-05, -9.0855e-05,\n -1.2559e-05, -4.7272e-05, -9.1404e-05, -5.6337e-05, -1.3216e-04,\n 3.5125e-05, 2.1855e-04, -5.9415e-06, 1.6704e-04, -7.7912e-05,\n 1.6470e-05, 3.5601e-05, 2.9202e-05, -2.5099e-05, -1.3995e-04,\n -2.4922e-05, -6.9641e-07, -3.7881e-05, 1.0815e-05, -3.5066e-04,\n 1.4484e-05, -3.2970e-05, -1.1335e-05, 3.7240e-04, 7.4813e-05,\n 6.1431e-05, -1.0440e-04, 1.7420e-05, -2.7643e-06, 3.1759e-05,\n 4.7894e-05, -2.6025e-05, 4.5999e-05, -4.6608e-05, -2.9375e-05,\n 4.3363e-05, 1.8053e-05, -2.4705e-04, -3.7566e-05, -3.2040e-05,\n -9.0427e-05, 7.9725e-05, 4.1095e-05, 1.5023e-04, -1.5963e-04,\n 4.9615e-05, -1.2398e-04, -2.8520e-04, -1.3397e-05, 6.6444e-05,\n 1.2058e-04, 1.8509e-05, 8.5538e-05, 7.1337e-06, -3.6932e-07,\n 6.6749e-05, -7.5002e-05, 4.2268e-05, -5.1501e-05, 8.7596e-05,\n 1.1417e-04, 1.6477e-05, -6.8111e-06, -1.2067e-04, 4.6327e-05,\n 9.6298e-05, -1.1450e-04, -1.8573e-04, 1.5863e-04, 5.4126e-07,\n 6.1536e-05, 2.0699e-05, -4.7035e-05, -1.2379e-04, -1.4653e-04,\n -7.7499e-05, 3.2671e-05, -4.2635e-05, 4.2087e-05, -1.4978e-04,\n -9.3423e-05, -6.0030e-05, -1.9724e-05, -8.2921e-05, 2.2414e-05,\n 9.3516e-06, -3.2197e-05, 1.1674e-04, -1.4155e-05, -2.3248e-05,\n -8.4649e-06, -5.7526e-05, 1.7236e-04, 7.8007e-05, -3.1689e-05,\n -4.7780e-05, 1.0505e-04, 7.0202e-05, -3.7254e-06, -1.1946e-05,\n 1.3703e-05, 5.2499e-05, -9.8782e-05, -5.1385e-05, 8.4603e-05,\n 6.3601e-05, -3.8363e-05, -9.3239e-05, 2.6568e-05, 5.4557e-05,\n -1.3229e-04, -3.8922e-05, 2.1315e-04, 3.7220e-05, -2.7042e-06,\n 8.4058e-05, 1.0643e-05, 5.4097e-05, 1.4957e-06, 5.7983e-06,\n 1.0023e-04, 1.4261e-04, -8.4610e-05, 1.2285e-05, -4.1998e-06,\n -1.5709e-04, 6.2720e-05, -1.9991e-06, 6.6298e-05, 2.7639e-05,\n -3.6619e-05, -1.3637e-04, 6.3808e-05, 8.1103e-05, -2.6458e-05,\n -1.0912e-04, 4.3718e-05, -1.2473e-04, -7.8330e-05, -9.7496e-05,\n 7.1275e-05, -3.6853e-05, 3.6065e-05, -1.0853e-04, -5.3758e-05,\n -1.9655e-06, 4.1914e-05, 6.3266e-05, 5.7129e-05, 8.1144e-05,\n -3.0385e-04, 6.9782e-05, -2.3228e-05, -2.3140e-05, -8.3375e-05,\n -3.8582e-05, 5.7136e-05, -8.4409e-05, 9.8895e-05, -5.0838e-05,\n 2.4698e-04, 8.1502e-05, 1.1242e-04, -6.6093e-06, 1.2908e-05,\n 1.6637e-04, -6.2237e-05, -1.6178e-05, -3.3209e-05, -3.0852e-05,\n 2.0960e-05, -5.4701e-05, -2.1535e-05, 8.9459e-05, -1.7194e-05,\n -1.3145e-04, -7.8569e-05, 1.0987e-04, 1.4679e-05, 7.9882e-05,\n -1.9877e-04, 2.9810e-05, -1.9776e-04, 1.1224e-06, 4.0488e-05,\n 7.1264e-05, -3.4127e-06, 5.5310e-05, 1.6312e-05, 1.5976e-05,\n -3.3356e-05, 1.9856e-06, -4.4953e-06, 3.8171e-05, 1.2620e-05,\n 6.2013e-05, -3.6403e-05, 1.4224e-05, 1.5493e-04, -2.3507e-05,\n -2.6176e-05, 5.1692e-05, -3.4427e-05, -1.6443e-05, -1.7428e-05,\n -6.4832e-05, 1.0341e-05, -1.3342e-05, 3.3596e-05, 9.7683e-05,\n -1.4777e-05, 1.0182e-04, 6.0440e-05, -8.8401e-05, -3.5624e-05,\n 1.2914e-04, 8.7904e-06, -1.0078e-04, 2.1186e-05, 4.6472e-05,\n 4.6460e-05, -1.2128e-04, 9.4548e-05, -3.2874e-05, -2.5617e-05,\n 1.2015e-05, 4.2247e-05, 5.7789e-05, -3.7524e-05, -7.3798e-05,\n 1.6374e-04, 1.5082e-05, -1.2490e-05, -3.3403e-05, 3.6883e-06,\n -4.5113e-05, -1.1538e-04, -1.7101e-05, 1.4330e-05, -2.2733e-05,\n 1.2299e-04, 3.5495e-05, -5.6918e-06, -9.8964e-06, 1.6606e-05,\n 2.1594e-05]), 'exp_avg_sq': tensor([2.4273e-06, 1.3532e-06, 1.3799e-06, 9.8353e-07, 4.8296e-07, 1.6889e-06,\n 1.0478e-06, 8.6896e-07, 8.6500e-07, 1.4781e-06, 1.2836e-06, 8.8514e-07,\n 1.0471e-06, 1.1333e-06, 7.1555e-07, 1.2606e-06, 2.1976e-06, 1.2731e-06,\n 2.1105e-06, 1.3892e-06, 6.3155e-07, 1.1294e-06, 7.7749e-07, 1.2338e-06,\n 7.4036e-07, 5.3089e-07, 1.5173e-06, 8.3538e-07, 3.5119e-06, 1.6290e-06,\n 1.9048e-07, 7.6948e-07, 1.1883e-06, 2.8706e-06, 3.3743e-07, 2.7313e-06,\n 8.2282e-07, 1.0647e-06, 1.4325e-06, 7.1293e-07, 8.4528e-07, 1.1666e-06,\n 1.5099e-06, 5.9186e-07, 1.3095e-06, 9.3033e-07, 3.1351e-07, 7.5973e-07,\n 8.2603e-07, 1.4195e-06, 2.9226e-06, 1.9344e-06, 5.4453e-07, 2.4852e-06,\n 1.5784e-06, 8.0968e-07, 2.1401e-06, 2.3601e-06, 8.7695e-07, 7.9781e-07,\n 1.5376e-06, 1.2178e-06, 2.2247e-06, 7.6176e-07, 9.1794e-07, 8.4277e-07,\n 6.6707e-07, 2.3871e-07, 1.6400e-06, 1.2542e-06, 1.0588e-06, 1.1645e-06,\n 5.8156e-07, 1.2949e-06, 1.0477e-06, 1.2183e-06, 3.2877e-06, 1.1780e-06,\n 8.5957e-07, 2.3240e-06, 9.5008e-07, 2.1809e-06, 1.6380e-06, 1.3072e-06,\n 1.1989e-06, 1.1419e-06, 2.9197e-06, 1.6063e-06, 7.0351e-07, 6.1814e-07,\n 1.2751e-06, 1.6520e-06, 1.4692e-06, 6.2724e-07, 1.5962e-06, 4.4217e-07,\n 1.4452e-06, 2.2575e-06, 6.6823e-07, 9.2560e-07, 3.9713e-06, 9.4169e-07,\n 1.0582e-06, 1.4993e-06, 1.1598e-06, 2.9724e-06, 8.1525e-07, 7.2082e-07,\n 2.3747e-06, 1.4750e-06, 1.6259e-06, 1.1230e-06, 1.6576e-06, 7.5215e-07,\n 1.4497e-06, 1.3773e-06, 1.0458e-06, 1.2723e-06, 9.5066e-07, 1.5763e-06,\n 1.1776e-06, 5.9415e-07, 7.4527e-07, 1.5079e-06, 1.0085e-06, 1.0465e-06,\n 1.8554e-06, 1.0871e-06, 7.3188e-07, 8.6834e-07, 1.2636e-06, 3.7094e-06,\n 2.5132e-06, 2.0656e-06, 1.9215e-06, 1.0455e-06, 1.2194e-06, 8.2235e-07,\n 1.0559e-06, 7.3322e-07, 2.1419e-06, 1.8039e-06, 5.9334e-07, 1.4101e-06,\n 7.7275e-07, 7.1948e-07, 7.4787e-07, 9.2431e-07, 8.2735e-07, 1.3511e-06,\n 9.3219e-07, 9.4840e-07, 1.9183e-06, 1.0725e-06, 1.9918e-06, 9.3520e-07,\n 7.3105e-07, 7.1507e-07, 1.4243e-06, 1.0386e-06, 1.0932e-06, 6.7852e-07,\n 8.2909e-07, 6.2742e-07, 1.0469e-06, 1.4034e-06, 1.0660e-06, 1.0480e-06,\n 1.6835e-06, 6.6817e-07, 1.5825e-06, 6.7105e-07, 1.6353e-06, 1.2410e-06,\n 9.1212e-07, 2.5391e-06, 5.7029e-07, 8.9048e-07, 1.0571e-06, 1.8898e-06,\n 4.5195e-07, 8.2260e-07, 1.0067e-06, 1.8688e-06, 1.4089e-06, 4.5643e-06,\n 1.2627e-06, 1.3411e-06, 2.1992e-06, 6.7276e-07, 3.3393e-06, 8.2453e-07,\n 3.0824e-06, 8.0517e-07, 6.4328e-07, 8.4982e-07, 1.1764e-06, 1.0955e-06,\n 1.8424e-06, 7.8926e-07, 1.2950e-06, 7.1085e-07, 1.5651e-06, 7.8537e-07,\n 6.4687e-07, 1.6173e-06, 1.2896e-06, 5.7265e-07, 1.5910e-06, 6.7439e-07,\n 6.7437e-07, 1.2859e-06, 1.1958e-06, 1.5345e-06, 1.3064e-06, 1.9017e-06,\n 7.6918e-07, 4.8597e-07, 1.4352e-06, 8.0155e-07, 8.3467e-07, 1.8744e-06,\n 1.4831e-06, 1.3280e-06, 1.3174e-06, 1.3346e-06, 8.6611e-07, 1.1687e-06,\n 3.3335e-06, 1.0534e-06, 1.2840e-06, 3.2561e-06, 1.4083e-06, 8.0482e-07,\n 1.4911e-06, 3.9522e-07, 1.0589e-06, 3.4417e-06, 1.1267e-06, 1.3073e-06,\n 1.8105e-06, 7.4156e-07, 7.3330e-07, 1.4642e-06, 5.2301e-07, 7.8707e-07,\n 1.1094e-06, 4.7598e-07, 1.2628e-06, 1.7110e-06, 1.3149e-06, 1.2456e-06,\n 2.1418e-06, 7.5393e-07, 8.5775e-07, 1.2981e-06])}, 78: {'step': 7160, 'exp_avg': tensor([[[[ 2.4969e-05]],\n\n [[ 4.3889e-05]],\n\n [[-2.0949e-05]],\n\n ...,\n\n [[ 2.1477e-06]],\n\n [[ 6.5119e-08]],\n\n [[-7.1036e-06]]],\n\n\n [[[-4.4914e-06]],\n\n [[-6.5388e-06]],\n\n [[ 3.5764e-06]],\n\n ...,\n\n [[-5.1412e-08]],\n\n [[-3.4915e-06]],\n\n [[ 8.8049e-06]]],\n\n\n [[[-1.2808e-05]],\n\n [[ 3.6812e-06]],\n\n [[ 1.8098e-06]],\n\n ...,\n\n [[ 6.9782e-07]],\n\n [[-1.1074e-08]],\n\n [[-8.9438e-06]]],\n\n\n ...,\n\n\n [[[-3.1377e-05]],\n\n [[-2.7571e-06]],\n\n [[ 3.3182e-06]],\n\n ...,\n\n [[-1.0861e-07]],\n\n [[ 8.7458e-07]],\n\n [[ 7.1435e-06]]],\n\n\n [[[-7.5852e-06]],\n\n [[-3.4630e-05]],\n\n [[ 4.1545e-07]],\n\n ...,\n\n [[ 7.1741e-06]],\n\n [[ 6.7808e-06]],\n\n [[-3.9620e-06]]],\n\n\n [[[ 9.9285e-06]],\n\n [[-2.9369e-05]],\n\n [[ 6.4003e-06]],\n\n ...,\n\n [[ 2.5446e-05]],\n\n [[ 2.9524e-06]],\n\n [[ 8.8106e-06]]]]), 'exp_avg_sq': tensor([[[[1.1598e-07]],\n\n [[7.8842e-08]],\n\n [[8.1875e-08]],\n\n ...,\n\n [[1.5871e-08]],\n\n [[4.0924e-08]],\n\n [[4.3713e-08]]],\n\n\n [[[3.1156e-08]],\n\n [[2.0966e-08]],\n\n [[2.8968e-08]],\n\n ...,\n\n [[1.4136e-08]],\n\n [[1.5009e-08]],\n\n [[1.7518e-08]]],\n\n\n [[[1.5207e-08]],\n\n [[1.1734e-08]],\n\n [[1.0784e-08]],\n\n ...,\n\n [[4.7696e-09]],\n\n [[1.0866e-08]],\n\n [[1.1049e-08]]],\n\n\n ...,\n\n\n [[[2.7012e-08]],\n\n [[2.4817e-08]],\n\n [[1.0898e-08]],\n\n ...,\n\n [[9.5949e-09]],\n\n [[9.3803e-09]],\n\n [[3.8795e-08]]],\n\n\n [[[6.1037e-08]],\n\n [[2.5591e-08]],\n\n [[1.6791e-08]],\n\n ...,\n\n [[8.1740e-09]],\n\n [[1.7698e-08]],\n\n [[2.4094e-08]]],\n\n\n [[[1.0102e-07]],\n\n [[6.4971e-08]],\n\n [[2.0594e-07]],\n\n ...,\n\n [[6.1523e-08]],\n\n [[6.3395e-08]],\n\n [[6.8168e-08]]]])}, 79: {'step': 7160, 'exp_avg': tensor([ 7.9163e-05, 6.5002e-05, -3.2117e-05, ..., -3.0997e-05,\n 5.9767e-05, 1.9699e-04]), 'exp_avg_sq': tensor([1.2887e-06, 4.0203e-07, 2.5832e-07, ..., 5.5468e-07, 7.7114e-07,\n 5.0810e-06])}, 80: {'step': 7160, 'exp_avg': tensor([ 1.9275e-05, 3.6831e-05, -4.8017e-05, ..., -2.9539e-06,\n 2.9935e-05, 1.6036e-04]), 'exp_avg_sq': tensor([7.0415e-07, 2.0806e-07, 1.2052e-07, ..., 2.8363e-07, 4.1515e-07,\n 3.8672e-06])}, 81: {'step': 7160, 'exp_avg': tensor([[[[ 1.3104e-05]],\n\n [[ 4.1505e-06]],\n\n [[-1.0391e-05]],\n\n ...,\n\n [[ 5.1754e-06]],\n\n [[ 1.7632e-05]],\n\n [[-3.7859e-05]]],\n\n\n [[[-1.0756e-05]],\n\n [[-8.1767e-06]],\n\n [[ 9.6705e-06]],\n\n ...,\n\n [[ 1.8498e-06]],\n\n [[ 1.5434e-05]],\n\n [[ 1.2260e-05]]],\n\n\n [[[-1.1581e-05]],\n\n [[ 6.1710e-06]],\n\n [[ 4.1967e-06]],\n\n ...,\n\n [[-7.9355e-06]],\n\n [[-6.9282e-06]],\n\n [[ 5.6285e-07]]],\n\n\n ...,\n\n\n [[[-8.1097e-06]],\n\n [[-3.0938e-06]],\n\n [[-1.6785e-06]],\n\n ...,\n\n [[-1.1015e-05]],\n\n [[ 3.9986e-06]],\n\n [[-4.8090e-06]]],\n\n\n [[[-1.4236e-05]],\n\n [[-4.1504e-06]],\n\n [[ 6.4634e-06]],\n\n ...,\n\n [[-5.3830e-06]],\n\n [[-6.0275e-06]],\n\n [[ 5.7071e-06]]],\n\n\n [[[ 1.1869e-05]],\n\n [[-6.2499e-06]],\n\n [[ 3.1735e-05]],\n\n ...,\n\n [[ 1.0004e-05]],\n\n [[-1.9567e-05]],\n\n [[ 4.2638e-06]]]]), 'exp_avg_sq': tensor([[[[2.4585e-08]],\n\n [[4.0755e-08]],\n\n [[2.6678e-08]],\n\n ...,\n\n [[4.9850e-08]],\n\n [[2.7195e-08]],\n\n [[2.2250e-08]]],\n\n\n [[[6.3431e-09]],\n\n [[1.0761e-08]],\n\n [[7.6956e-09]],\n\n ...,\n\n [[1.7650e-08]],\n\n [[9.4839e-09]],\n\n [[7.9391e-09]]],\n\n\n [[[4.7338e-09]],\n\n [[4.6405e-09]],\n\n [[4.7332e-09]],\n\n ...,\n\n [[4.7631e-09]],\n\n [[2.9913e-09]],\n\n [[2.4294e-09]]],\n\n\n ...,\n\n\n [[[6.3701e-09]],\n\n [[7.1647e-09]],\n\n [[1.0523e-08]],\n\n ...,\n\n [[1.5740e-08]],\n\n [[8.9130e-09]],\n\n [[6.8682e-09]]],\n\n\n [[[6.7136e-09]],\n\n [[8.5962e-09]],\n\n [[1.0467e-08]],\n\n ...,\n\n [[1.3439e-08]],\n\n [[8.8679e-09]],\n\n [[8.2212e-09]]],\n\n\n [[[1.1899e-07]],\n\n [[1.5618e-07]],\n\n [[1.4984e-07]],\n\n ...,\n\n [[1.3482e-07]],\n\n [[8.0939e-08]],\n\n [[2.9936e-08]]]])}, 82: {'step': 7160, 'exp_avg': tensor([ 1.0001e-04, 2.4931e-05, -6.0984e-05, ..., -1.3231e-05,\n 2.1750e-05, 8.9640e-05]), 'exp_avg_sq': tensor([1.5956e-06, 3.4896e-07, 1.9584e-07, ..., 4.6035e-07, 7.1016e-07,\n 4.6885e-06])}, 83: {'step': 7160, 'exp_avg': tensor([ 1.9275e-05, 3.6831e-05, -4.8017e-05, ..., -2.9539e-06,\n 2.9935e-05, 1.6036e-04]), 'exp_avg_sq': tensor([7.0415e-07, 2.0806e-07, 1.2052e-07, ..., 2.8363e-07, 4.1515e-07,\n 3.8672e-06])}, 84: {'step': 7160, 'exp_avg': tensor([[[[ 1.0179e-05]],\n\n [[ 1.9519e-07]],\n\n [[ 8.0107e-06]],\n\n ...,\n\n [[ 1.1061e-05]],\n\n [[-7.4848e-07]],\n\n [[-2.5603e-06]]],\n\n\n [[[ 6.6041e-08]],\n\n [[-5.7798e-06]],\n\n [[-1.1588e-06]],\n\n ...,\n\n [[ 1.5797e-05]],\n\n [[-4.6341e-06]],\n\n [[-1.0345e-06]]],\n\n\n [[[-2.0992e-05]],\n\n [[-5.2045e-06]],\n\n [[-4.5150e-06]],\n\n ...,\n\n [[-4.0896e-06]],\n\n [[-2.2614e-06]],\n\n [[-2.4573e-05]]],\n\n\n ...,\n\n\n [[[ 5.4822e-06]],\n\n [[ 2.4425e-06]],\n\n [[ 5.3425e-06]],\n\n ...,\n\n [[-2.0256e-06]],\n\n [[-1.1460e-06]],\n\n [[ 1.1254e-06]]],\n\n\n [[[ 2.7142e-05]],\n\n [[ 4.1893e-06]],\n\n [[-1.4613e-05]],\n\n ...,\n\n [[ 5.0210e-06]],\n\n [[-6.4557e-06]],\n\n [[-1.3701e-05]]],\n\n\n [[[ 4.8277e-05]],\n\n [[ 1.2276e-05]],\n\n [[ 5.6225e-06]],\n\n ...,\n\n [[ 1.4561e-05]],\n\n [[ 5.8433e-06]],\n\n [[ 4.7693e-06]]]]), 'exp_avg_sq': tensor([[[[2.6983e-08]],\n\n [[4.7580e-09]],\n\n [[3.8068e-09]],\n\n ...,\n\n [[1.2015e-08]],\n\n [[1.3441e-08]],\n\n [[3.4959e-08]]],\n\n\n [[[2.0764e-08]],\n\n [[7.5733e-09]],\n\n [[7.1992e-09]],\n\n ...,\n\n [[1.6906e-08]],\n\n [[1.7124e-08]],\n\n [[7.0946e-08]]],\n\n\n [[[3.6302e-08]],\n\n [[6.2470e-09]],\n\n [[7.3038e-09]],\n\n ...,\n\n [[1.6275e-08]],\n\n [[1.9716e-08]],\n\n [[6.0923e-08]]],\n\n\n ...,\n\n\n [[[1.5972e-08]],\n\n [[4.1620e-09]],\n\n [[3.6237e-09]],\n\n ...,\n\n [[1.2592e-08]],\n\n [[1.0985e-08]],\n\n [[5.9743e-08]]],\n\n\n [[[4.9637e-08]],\n\n [[1.4568e-08]],\n\n [[1.0671e-08]],\n\n ...,\n\n [[2.9657e-08]],\n\n [[2.4799e-08]],\n\n [[9.9487e-08]]],\n\n\n [[[8.7838e-08]],\n\n [[2.4295e-08]],\n\n [[1.1047e-08]],\n\n ...,\n\n [[3.4970e-08]],\n\n [[5.5829e-08]],\n\n [[1.3424e-07]]]])}, 85: {'step': 7160, 'exp_avg': tensor([ 7.9440e-06, -1.7957e-04, 2.0062e-04, -1.4002e-06, -5.4102e-05,\n -1.2472e-04, 3.0767e-05, 6.3288e-05, -7.9200e-06, 1.7336e-04,\n 1.8989e-04, -1.2801e-04, -1.8205e-05, 4.4763e-05, -4.8090e-05,\n -4.8274e-05, 6.2042e-05, 4.4538e-05, -8.1444e-05, -5.4976e-05,\n -9.1582e-05, 2.2158e-04, -7.6347e-05, 1.2087e-04, -8.3409e-06,\n 6.5225e-06, -1.5172e-04, -9.0917e-06, -6.0352e-05, 1.7428e-04,\n 9.1955e-05, -1.7445e-04, 1.3541e-04, 7.5164e-05, -4.1014e-05,\n -1.4259e-04, -8.2359e-05, 9.2057e-05, -1.4878e-04, 8.0237e-05,\n 2.4957e-04, -6.7286e-05, -2.3979e-05, -4.7983e-05, 1.8989e-05,\n 2.2280e-04, -8.0106e-05, -2.3385e-04, 8.1411e-05, 6.6950e-05,\n -1.2661e-04, -1.6914e-04, -5.3329e-05, 2.8445e-04, 1.1911e-05,\n 1.3442e-04, 2.5396e-04, -1.6407e-04, -1.2159e-04, -3.6259e-05,\n -9.3734e-06, 8.8410e-05, -2.8997e-05, 3.0773e-05, 2.6569e-04,\n 1.2900e-04, 2.0329e-04, 1.1850e-04, -2.5488e-07, 3.6500e-05,\n -1.0709e-05, -6.6304e-05, -2.2261e-04, 5.3082e-05, -7.5523e-05,\n 8.4240e-06, -1.2518e-04, -3.7764e-05, -1.3283e-05, 2.8327e-04,\n 7.2569e-05, -7.9273e-05, -3.1388e-05, -1.1293e-05, 8.0658e-06,\n 3.7908e-04, 2.2481e-05, 1.0585e-04, -6.7562e-05, 1.0501e-04,\n -2.2453e-06, -8.2542e-05, -2.9998e-05, -1.1007e-04, -1.0705e-04,\n -2.3518e-04, 1.5849e-04, -3.8068e-05, 4.7994e-05, 1.3158e-04,\n -1.1443e-04, 1.1417e-04, 2.1925e-06, -6.1843e-05, 2.6959e-05,\n -6.4927e-05, 1.0750e-05, -2.4109e-04, 1.3359e-04, 7.8817e-05,\n -7.9302e-05, -1.0666e-05, 1.4279e-04, -1.1672e-04, -1.3102e-05,\n -1.3625e-05, 1.7150e-04, -2.2104e-05, 1.6723e-04, 1.4462e-05,\n 8.5101e-05, -4.3279e-05, -1.7502e-04, 4.7534e-05, 1.9332e-04,\n 6.0574e-04, 6.8344e-05, -1.3960e-04, -1.0211e-04, 5.0630e-08,\n 1.0911e-05, -1.0484e-04, 1.0782e-05, -2.8890e-04, -5.1330e-05,\n -6.7220e-05, 1.0591e-04, -8.0560e-05, 3.8087e-05, -4.1869e-05,\n -4.3736e-04, -3.3266e-05, -3.1628e-05, 1.4249e-04, 2.3150e-05,\n -1.6573e-04, -1.1472e-05, 9.9635e-05, -8.9324e-05, -6.0729e-05,\n 3.0408e-05, -1.2871e-04, 1.5889e-04, -3.8028e-05, 1.6967e-04,\n -1.9675e-05, -2.1655e-05, 3.1803e-05, 3.3338e-05, -2.0111e-04,\n -1.9744e-05, -9.8717e-05, 9.6227e-05, -9.0743e-05, 2.0279e-04,\n 6.9151e-05, 8.4788e-05, -2.2941e-04, -1.3435e-04, 7.8713e-05,\n -1.5105e-04, 2.1838e-04, 5.1627e-05, 2.0473e-05, -7.0340e-05,\n -9.7500e-05, -4.5322e-05, -3.4129e-04, -9.0316e-05, 5.9226e-06,\n 1.1024e-04, -1.2166e-04, -5.4630e-06, -2.8270e-05, 2.9750e-05,\n -1.4971e-04, -3.5768e-05, -1.0261e-04, 9.3596e-05, -2.3417e-05,\n -1.4509e-04, -1.0642e-04, 1.8743e-05, 8.5265e-05, 9.0861e-06,\n -5.4566e-06, 4.9018e-05, 2.1534e-05, 5.5115e-05, 4.1690e-05,\n 1.5871e-04, 5.3605e-05, -1.2104e-04, -9.0109e-06, 3.2834e-05,\n -1.2995e-04, 2.0722e-04, -7.9953e-05, 3.9166e-05, -4.6345e-05,\n -5.7700e-05, 1.1967e-04, -1.4209e-04, 5.9480e-05, -2.5565e-05,\n -4.9969e-05, -1.2786e-04, 1.3338e-04, 6.5769e-05, 8.1914e-06,\n -6.6110e-05, -4.9719e-05, 8.8816e-05, 5.4189e-05, 9.7417e-05,\n -4.8195e-05, 7.1509e-05, -6.7679e-05, 6.6436e-05, -9.8531e-05,\n 1.3537e-05, -6.3680e-05, 5.1567e-05, 1.0692e-04, 3.3930e-05,\n 1.6812e-04, 6.3916e-05, -2.2821e-05, -1.6740e-04, -8.9912e-05,\n 1.7956e-04, 5.0380e-05, 2.1924e-05, -6.3809e-05, -8.7868e-05,\n -4.7878e-06, 8.9662e-05, -1.8075e-05, 2.4776e-05, 8.1686e-05,\n 7.8236e-05, -8.5974e-05, 1.0366e-04, -1.0077e-04, 6.8950e-05,\n -1.6051e-04]), 'exp_avg_sq': tensor([1.9368e-06, 2.3212e-06, 1.6950e-06, 1.3786e-06, 1.0515e-06, 1.8120e-06,\n 1.5043e-06, 2.3556e-06, 5.7408e-06, 3.5288e-06, 1.5539e-06, 7.5123e-07,\n 1.4257e-06, 1.8549e-06, 9.0666e-07, 2.8821e-06, 1.2824e-06, 1.2979e-06,\n 1.1911e-06, 2.7350e-06, 2.1207e-06, 4.8289e-06, 2.7603e-06, 2.5362e-06,\n 1.0474e-06, 1.4830e-06, 4.0661e-06, 1.6311e-06, 1.4162e-06, 3.1607e-06,\n 1.3674e-06, 1.2201e-06, 1.3035e-06, 1.8914e-06, 9.5429e-07, 1.5605e-05,\n 3.4809e-06, 3.8547e-06, 3.3337e-06, 2.0298e-06, 7.6655e-06, 1.4275e-06,\n 1.7944e-06, 9.4838e-07, 2.4001e-06, 4.4906e-06, 2.1076e-06, 3.7584e-06,\n 1.4076e-06, 2.0698e-06, 4.4765e-06, 1.0447e-06, 2.4588e-06, 2.5984e-06,\n 9.5960e-07, 2.4879e-06, 3.0556e-06, 2.5992e-06, 2.1150e-06, 1.4473e-06,\n 1.2958e-06, 1.1720e-06, 1.6048e-06, 1.1622e-06, 5.0376e-06, 1.3320e-06,\n 2.0963e-06, 1.3763e-05, 7.2410e-07, 4.2299e-06, 5.8511e-07, 1.6160e-06,\n 4.9048e-06, 9.1844e-07, 9.5057e-07, 1.1931e-06, 1.4098e-06, 2.3932e-06,\n 7.7506e-07, 1.3205e-05, 3.4872e-06, 1.0193e-06, 2.1739e-06, 1.1994e-06,\n 1.0980e-06, 5.1583e-06, 1.3033e-06, 2.2219e-06, 1.2304e-06, 6.7992e-06,\n 1.8936e-06, 1.8474e-06, 1.6346e-06, 1.7764e-06, 1.0081e-06, 2.6615e-06,\n 4.4551e-06, 5.5344e-06, 4.9619e-06, 1.6531e-06, 5.5914e-06, 2.7605e-06,\n 2.5177e-06, 1.3631e-06, 7.7752e-07, 1.3578e-06, 9.1159e-07, 8.8464e-06,\n 5.3239e-06, 2.3071e-06, 6.7178e-07, 2.5253e-06, 9.6865e-07, 1.3068e-05,\n 1.3930e-06, 1.3950e-06, 3.4605e-06, 1.7410e-06, 3.3091e-06, 2.6654e-06,\n 1.7176e-06, 2.2658e-06, 1.6719e-06, 6.0168e-07, 2.6448e-06, 7.2255e-06,\n 1.8528e-06, 9.5151e-06, 2.9607e-06, 1.7757e-06, 8.2971e-07, 2.2003e-06,\n 2.4109e-06, 3.1896e-06, 3.9109e-06, 1.1525e-06, 4.8579e-06, 1.3935e-06,\n 2.3417e-06, 9.4657e-07, 1.4471e-05, 2.8342e-06, 1.4653e-06, 2.1753e-06,\n 3.3376e-06, 3.5298e-06, 7.2868e-07, 1.9072e-06, 3.0450e-06, 5.5046e-06,\n 4.8924e-06, 4.4340e-06, 2.1427e-06, 8.3459e-07, 1.5055e-06, 1.0760e-05,\n 1.3990e-06, 1.0283e-06, 1.2108e-06, 2.7764e-06, 2.4477e-06, 1.2765e-06,\n 1.2058e-06, 1.0693e-06, 1.8661e-06, 1.1427e-06, 1.3340e-06, 1.9182e-06,\n 1.4307e-06, 1.6603e-06, 8.3473e-06, 2.9521e-06, 1.3059e-06, 1.6903e-06,\n 2.1798e-06, 9.5987e-06, 8.1790e-07, 2.5237e-06, 8.1783e-06, 1.2874e-06,\n 7.5943e-07, 2.5592e-06, 1.1468e-06, 1.2894e-06, 1.7587e-06, 3.1098e-06,\n 3.1706e-06, 1.3498e-06, 8.4119e-06, 1.2626e-06, 9.6604e-07, 3.1997e-06,\n 1.8993e-06, 1.5836e-06, 1.6721e-06, 1.1772e-06, 1.5705e-06, 1.3624e-06,\n 8.3525e-06, 1.1148e-06, 1.4900e-06, 1.9050e-06, 1.3472e-06, 1.4381e-06,\n 1.9019e-06, 2.4455e-06, 1.9161e-06, 3.8650e-06, 4.1006e-06, 1.6862e-06,\n 2.8491e-06, 1.5012e-06, 2.0634e-06, 1.2637e-06, 1.1714e-06, 9.7420e-07,\n 4.2886e-06, 4.7550e-06, 1.2057e-06, 2.2704e-06, 2.1326e-06, 7.7766e-07,\n 2.3174e-06, 2.1521e-06, 7.2098e-06, 1.0765e-06, 2.6009e-06, 2.0085e-06,\n 1.3392e-06, 1.0995e-06, 1.2691e-06, 1.5570e-06, 2.2827e-06, 9.8321e-07,\n 1.3459e-06, 1.3794e-06, 1.2660e-06, 2.7914e-06, 2.4412e-06, 2.5087e-06,\n 1.8052e-06, 3.1971e-06, 1.3702e-06, 9.9595e-07, 3.0251e-06, 2.4046e-06,\n 2.8513e-06, 1.1118e-06, 2.1968e-06, 1.5381e-06, 4.1970e-06, 1.4395e-06,\n 3.2536e-06, 1.1555e-06, 1.3224e-06, 1.1196e-05])}, 86: {'step': 7160, 'exp_avg': tensor([ 3.2068e-05, 1.3563e-04, 1.7285e-04, -7.4606e-05, 3.2845e-05,\n 1.9479e-05, -2.3887e-05, -5.2854e-05, -4.5307e-05, -4.3872e-06,\n 1.6466e-04, -8.1527e-05, -4.5903e-05, -8.2748e-05, -2.0503e-05,\n 7.9200e-05, 3.7694e-05, 6.9044e-05, -4.7709e-05, -1.0904e-05,\n -8.1283e-05, 7.8304e-05, 1.8691e-05, 3.0442e-05, -9.3993e-05,\n 6.0631e-05, -1.1485e-04, -3.6014e-06, -7.0406e-05, -2.9589e-05,\n 5.1322e-05, -1.3332e-04, -2.8606e-05, 5.5566e-05, -7.7369e-05,\n 1.3187e-04, 7.2418e-06, 8.7683e-05, -2.4988e-04, 7.9492e-06,\n 1.1879e-04, 4.2952e-05, -1.6561e-05, 5.1843e-06, 4.2039e-05,\n 1.2670e-04, -8.9932e-05, -1.0475e-04, -1.6433e-05, 5.4573e-05,\n -2.7135e-05, -1.2880e-04, 2.4513e-05, 3.9165e-05, 5.3106e-05,\n 1.4518e-04, 1.5413e-04, -1.0080e-04, -1.3746e-04, -4.0401e-05,\n -4.4956e-05, 9.8790e-05, -5.3416e-06, -1.2084e-04, 2.3309e-05,\n 5.2374e-05, 2.2775e-04, 2.5651e-04, -9.6803e-06, -6.6265e-05,\n -1.5686e-05, -1.4541e-04, -6.3216e-05, 1.4689e-05, -2.1798e-05,\n 3.6028e-05, -8.0529e-05, 4.8709e-05, -5.2077e-06, 2.7365e-04,\n -4.1221e-05, -1.2488e-04, 2.9566e-06, 6.0167e-05, 3.9569e-05,\n 3.1850e-04, 5.8981e-06, 9.0798e-05, -5.3919e-05, 1.3569e-05,\n 3.6358e-05, -3.0691e-05, 5.0797e-05, -3.8966e-05, -7.8885e-05,\n -8.3023e-05, 2.1568e-04, -4.2005e-05, 4.6945e-05, 7.5518e-05,\n -1.1069e-04, 6.6648e-05, -2.0823e-05, -4.9798e-05, 1.5013e-05,\n 2.5264e-05, -9.3123e-05, -3.0750e-04, 9.7607e-05, 1.0318e-05,\n -2.8335e-05, 7.4023e-05, 2.2347e-04, 2.4739e-05, 1.6892e-05,\n -3.1633e-05, 1.7245e-04, -5.8022e-05, 3.0972e-04, -8.1444e-05,\n -1.2522e-05, -5.7729e-05, -1.5674e-04, 1.0112e-05, 1.2913e-04,\n 2.8210e-04, 1.2364e-04, -1.6805e-05, -9.6624e-05, -1.7042e-05,\n -2.4777e-05, -6.6870e-05, 1.2138e-04, -4.9405e-05, 3.8715e-05,\n -1.6429e-04, 1.6362e-04, -2.0020e-06, -3.6176e-05, -2.3201e-06,\n -3.4647e-04, -1.4969e-04, -6.8192e-05, 3.1224e-04, 1.2801e-05,\n 2.4688e-05, -7.7053e-05, -1.4777e-04, -1.9747e-04, 3.6077e-06,\n -1.7570e-05, -1.0051e-04, 1.1306e-04, -8.0574e-05, 4.4555e-05,\n -5.6253e-05, -1.2793e-05, 4.9273e-05, 2.4546e-05, -9.0445e-05,\n -3.0679e-06, -7.1375e-05, 9.9528e-05, -6.2265e-05, 1.3894e-04,\n -1.3204e-05, 8.6974e-05, -2.3419e-04, -5.7078e-05, 5.6407e-05,\n -7.7066e-05, 1.1698e-04, 1.1352e-05, 2.6186e-05, 2.0736e-05,\n -1.1328e-04, -1.2838e-04, -1.0370e-04, -8.2462e-05, 3.9315e-05,\n 7.6780e-05, -1.0641e-04, 1.5757e-06, 1.1174e-04, -1.8549e-04,\n -1.3809e-04, -6.8685e-05, -8.9321e-05, 1.0320e-04, -1.5802e-05,\n -1.2873e-04, -1.5462e-04, -2.9080e-05, 3.2051e-05, 3.1096e-05,\n 1.3040e-04, -9.7515e-05, 7.2936e-05, -3.7753e-04, -6.7949e-06,\n 4.9188e-05, 6.2079e-05, -1.8228e-04, -7.5555e-05, 1.5065e-05,\n -3.2934e-05, -9.3605e-05, 5.9559e-05, 1.1689e-04, -6.7145e-06,\n 3.0204e-05, 7.4751e-05, -1.4354e-04, 3.1333e-05, -7.0072e-05,\n -2.2170e-05, -9.1443e-05, 4.6977e-05, 3.5814e-05, -2.5392e-05,\n -3.3175e-05, -4.1577e-05, 3.9835e-05, 8.9729e-06, 9.3692e-05,\n 1.1794e-05, 4.9741e-05, -2.5792e-05, 5.8543e-06, -6.9745e-05,\n -3.5192e-05, -8.7901e-05, 4.0734e-06, 9.2867e-05, 2.9316e-05,\n 1.1926e-04, 9.2617e-05, -3.5409e-05, -7.3950e-05, -7.5536e-05,\n -1.5890e-05, 5.9807e-05, 4.8906e-05, -2.2563e-05, -8.8372e-05,\n 6.7859e-05, -5.6295e-05, 1.2335e-06, 6.6227e-05, 2.9300e-05,\n 6.3259e-05, -9.4433e-05, 5.0638e-05, -5.0142e-05, 6.7138e-05,\n -1.0309e-04]), 'exp_avg_sq': tensor([6.9651e-07, 1.2907e-06, 1.1368e-06, 1.1266e-06, 6.8067e-07, 1.0773e-06,\n 1.6234e-06, 1.8612e-06, 2.9917e-06, 6.2257e-07, 1.3381e-06, 2.4822e-07,\n 1.6022e-06, 2.1165e-06, 1.0361e-06, 2.0098e-06, 8.9170e-07, 9.8479e-07,\n 8.3681e-07, 1.8327e-06, 1.2551e-06, 1.5170e-06, 2.2852e-06, 2.6341e-06,\n 7.8858e-07, 5.6103e-07, 1.0887e-06, 1.3745e-06, 1.0213e-06, 1.4072e-06,\n 9.5320e-07, 9.7924e-07, 9.2482e-07, 1.2527e-06, 8.1041e-07, 4.1683e-06,\n 1.5770e-06, 2.1626e-06, 1.6330e-06, 1.7138e-06, 3.9202e-06, 1.0840e-06,\n 1.0110e-06, 1.0146e-06, 1.3645e-06, 1.5342e-06, 1.9082e-06, 2.5675e-06,\n 1.3921e-06, 1.5261e-06, 1.9036e-06, 9.1994e-07, 1.8838e-06, 1.1790e-06,\n 8.8814e-07, 1.5936e-06, 1.2354e-06, 1.4757e-06, 1.5805e-06, 1.2024e-06,\n 1.1946e-06, 6.3169e-07, 2.1992e-06, 1.7791e-06, 2.6690e-06, 6.3929e-07,\n 1.5182e-06, 6.4779e-06, 5.3233e-07, 1.5681e-06, 4.3910e-07, 1.9665e-06,\n 2.0317e-06, 4.5055e-07, 8.7704e-07, 7.5667e-07, 5.1082e-07, 8.5017e-07,\n 4.8655e-07, 3.8025e-06, 1.7771e-06, 8.7032e-07, 1.2085e-06, 1.4376e-06,\n 7.6405e-07, 3.3708e-06, 9.2701e-07, 1.2555e-06, 9.8916e-07, 3.6247e-06,\n 1.0511e-06, 8.9634e-07, 1.2379e-06, 7.6474e-07, 6.5757e-07, 1.5486e-06,\n 1.6059e-06, 1.6679e-06, 1.0760e-06, 8.7486e-07, 1.7859e-06, 1.3777e-06,\n 1.5933e-06, 4.9746e-07, 8.0292e-07, 1.0790e-06, 1.0278e-06, 3.9652e-06,\n 2.7345e-06, 1.3238e-06, 1.1359e-06, 9.4272e-07, 1.2288e-06, 4.2813e-06,\n 8.8794e-07, 7.7282e-07, 2.3514e-06, 1.2848e-06, 2.4391e-06, 1.2811e-06,\n 1.0231e-06, 1.0562e-06, 1.0818e-06, 3.9868e-07, 1.2467e-06, 3.8099e-06,\n 1.2012e-06, 5.9501e-06, 1.1306e-06, 1.0327e-06, 8.5489e-07, 1.6097e-06,\n 1.2561e-06, 2.1227e-06, 1.4073e-06, 1.4061e-06, 4.2051e-06, 1.0481e-06,\n 1.8164e-06, 1.0305e-06, 4.2399e-06, 1.3005e-06, 1.0994e-06, 1.6677e-06,\n 1.6991e-06, 9.0467e-07, 6.2244e-07, 7.6692e-07, 8.8046e-07, 3.9357e-06,\n 2.8195e-06, 1.8801e-06, 9.4422e-07, 1.1695e-06, 9.6684e-07, 4.2473e-06,\n 1.0761e-06, 7.8621e-07, 1.3717e-06, 1.1748e-06, 1.2379e-06, 1.1656e-06,\n 1.0201e-06, 6.3035e-07, 1.0021e-06, 7.3274e-07, 9.6584e-07, 2.0639e-06,\n 6.0376e-07, 7.1167e-07, 4.2480e-06, 1.5327e-06, 5.3136e-07, 1.0131e-06,\n 1.6561e-06, 4.7864e-06, 1.0271e-06, 8.8247e-07, 3.3558e-06, 1.1903e-06,\n 8.2709e-07, 7.8793e-07, 1.1781e-06, 9.3538e-07, 1.6005e-06, 1.8430e-06,\n 2.0769e-06, 7.6777e-07, 2.2128e-06, 9.9781e-07, 8.7552e-07, 1.4630e-06,\n 1.0354e-06, 1.0751e-06, 1.1763e-06, 1.1597e-06, 1.5463e-06, 7.6592e-07,\n 3.0868e-06, 4.7012e-07, 1.1324e-06, 1.3730e-06, 1.9308e-06, 1.5390e-06,\n 3.9574e-07, 1.5315e-06, 8.1270e-07, 1.8549e-06, 1.3604e-06, 1.0184e-06,\n 1.1455e-06, 6.0312e-07, 1.6635e-06, 7.5529e-07, 9.9011e-07, 6.3617e-07,\n 2.5300e-06, 1.9592e-06, 6.0034e-07, 7.1224e-07, 1.0205e-06, 5.1006e-07,\n 1.8162e-06, 1.2597e-06, 3.7317e-06, 8.2027e-07, 7.8581e-07, 1.7302e-06,\n 7.9169e-07, 9.6396e-07, 5.1806e-07, 1.1221e-06, 1.3350e-06, 8.5811e-07,\n 5.6934e-07, 5.1428e-07, 5.1178e-07, 1.3107e-06, 1.1991e-06, 1.5965e-06,\n 1.0467e-06, 1.9183e-06, 6.7186e-07, 8.9781e-07, 2.2374e-06, 9.6464e-07,\n 1.1752e-06, 5.6896e-07, 1.6015e-06, 9.6735e-07, 1.4669e-06, 9.1779e-07,\n 1.4469e-06, 6.8076e-07, 8.3456e-07, 4.1681e-06])}, 87: {'step': 7160, 'exp_avg': tensor([[[[-1.2462e-07, -2.4189e-06, 1.6343e-06],\n [ 2.3191e-06, -7.2801e-07, 3.1084e-06],\n [-7.4474e-06, 1.0258e-06, -1.0423e-05]],\n\n [[ 1.3860e-06, -3.8063e-06, -2.7632e-06],\n [-7.2934e-06, -1.3897e-05, 2.2799e-06],\n [-1.3219e-05, -4.8615e-06, -7.1733e-06]],\n\n [[ 3.5120e-06, 5.8866e-06, 2.5346e-06],\n [ 1.8968e-06, 5.2546e-07, 2.5302e-06],\n [ 5.5318e-06, 5.6391e-06, 4.2667e-06]],\n\n ...,\n\n [[ 1.2176e-06, 5.6689e-06, -5.0883e-07],\n [-4.9773e-06, -2.8825e-06, 1.8576e-06],\n [-3.4467e-06, -6.7944e-06, -8.7337e-06]],\n\n [[ 5.3015e-06, -2.7162e-06, -8.7876e-07],\n [-3.3837e-06, -1.0800e-06, -1.1254e-06],\n [-1.6313e-06, -1.9696e-06, 3.1469e-07]],\n\n [[ 7.5172e-06, 6.9655e-06, 8.3983e-06],\n [ 3.3207e-05, 1.2861e-06, -8.6071e-06],\n [-5.1636e-06, -1.8181e-06, -3.1373e-06]]],\n\n\n [[[-2.5420e-05, -2.2113e-05, -2.1348e-05],\n [-1.7473e-05, -1.3129e-05, -7.7115e-06],\n [-3.6016e-06, 2.2251e-05, -1.6560e-05]],\n\n [[ 5.7603e-07, -1.2352e-05, -1.6041e-06],\n [ 1.8666e-06, -1.3271e-06, 8.0923e-06],\n [ 6.3033e-06, -1.1451e-05, -3.1713e-05]],\n\n [[-3.2994e-05, -2.5384e-05, -2.5334e-05],\n [-2.2710e-05, -9.7955e-06, -1.4366e-05],\n [-9.6103e-06, 1.4043e-05, 6.0404e-06]],\n\n ...,\n\n [[-1.0056e-05, -2.0230e-05, -4.1224e-06],\n [ 1.3482e-06, 2.5734e-06, 2.3291e-05],\n [ 1.7096e-07, -1.3500e-05, -1.5257e-05]],\n\n [[-3.3040e-05, -1.6691e-05, -3.0322e-05],\n [-1.9534e-05, -9.1708e-06, -2.3039e-05],\n [-1.7627e-05, -1.5896e-05, -2.7173e-05]],\n\n [[ 2.5075e-05, 3.0585e-05, 2.5795e-07],\n [ 3.7141e-05, 2.2702e-05, 4.3484e-06],\n [ 2.1654e-05, 6.7459e-06, 7.0631e-06]]],\n\n\n [[[ 1.2664e-06, 9.3933e-07, 9.3393e-06],\n [-1.4010e-05, 6.3226e-06, -7.6839e-06],\n [-1.0530e-05, -3.5482e-06, -3.0223e-07]],\n\n [[ 6.9929e-06, -2.0281e-05, 1.3816e-06],\n [-7.5871e-06, -3.8586e-07, -2.5575e-05],\n [ 1.2563e-05, -5.5926e-06, -5.7153e-06]],\n\n [[-7.2134e-06, 2.0502e-06, -3.5908e-07],\n [-2.3986e-06, 1.0354e-05, -1.5205e-07],\n [ 5.9664e-06, 3.8798e-06, -1.0618e-06]],\n\n ...,\n\n [[-7.9528e-06, -1.5368e-05, -2.5127e-06],\n [-4.7352e-06, -7.0200e-06, -8.2767e-06],\n [-1.3081e-06, -5.9097e-06, -5.3686e-06]],\n\n [[-5.8562e-06, -9.3836e-06, 1.0105e-05],\n [-9.5455e-06, 8.6017e-08, -5.8799e-06],\n [ 2.6175e-06, -2.2813e-06, -3.0540e-06]],\n\n [[ 2.7099e-05, -4.8583e-06, 1.6576e-05],\n [ 3.9020e-06, 1.1029e-05, 1.6885e-05],\n [ 6.3145e-06, 6.6589e-06, 2.0760e-05]]],\n\n\n ...,\n\n\n [[[ 1.8316e-05, -4.3700e-06, -1.3315e-05],\n [ 2.2264e-07, 2.9088e-08, -1.5634e-05],\n [-6.1276e-06, -1.8747e-05, 1.0371e-05]],\n\n [[ 8.1835e-06, 5.5912e-06, -7.6932e-06],\n [ 3.7279e-06, 9.8559e-06, -2.7288e-05],\n [ 6.3504e-06, -8.9483e-06, 1.3677e-05]],\n\n [[ 1.1422e-05, -3.9726e-06, 5.8101e-06],\n [ 1.7503e-05, -1.0677e-05, 4.4082e-06],\n [ 2.4060e-05, 5.0884e-06, 1.4526e-05]],\n\n ...,\n\n [[ 5.7627e-06, 4.3940e-06, 5.8966e-06],\n [ 9.1977e-06, 6.5276e-06, -1.8924e-05],\n [ 7.8261e-06, 6.4524e-06, 1.1387e-05]],\n\n [[ 1.7737e-05, 2.1510e-05, 2.4437e-05],\n [ 1.5926e-05, 2.2214e-05, 2.0510e-05],\n [ 1.0031e-05, 1.4562e-05, 8.5125e-06]],\n\n [[ 1.7265e-05, -2.2315e-05, -2.4952e-05],\n [-1.4350e-05, 3.0630e-06, 6.2367e-06],\n [-1.7619e-05, -5.3522e-06, 1.3414e-05]]],\n\n\n [[[ 1.4758e-05, 9.2877e-06, 1.9186e-05],\n [ 2.0224e-05, 3.3610e-06, 1.9253e-05],\n [ 4.8787e-06, -3.6153e-06, 3.8690e-06]],\n\n [[ 6.7213e-06, -4.8608e-06, 1.3467e-05],\n [ 7.3960e-06, 3.7179e-06, 1.2195e-06],\n [-1.3050e-05, -2.0945e-05, -5.7844e-06]],\n\n [[ 9.0734e-07, 9.9413e-06, -1.1935e-05],\n [-1.4972e-05, -1.0583e-05, -9.7455e-06],\n [-9.0022e-06, 7.3108e-06, 9.2800e-06]],\n\n ...,\n\n [[-2.7361e-06, -1.0593e-05, -8.5388e-06],\n [ 7.3269e-06, 7.1324e-06, -3.3993e-07],\n [ 4.8974e-06, -2.7958e-06, 4.9295e-06]],\n\n [[ 8.8257e-06, -8.9291e-06, 3.7753e-06],\n [ 4.0733e-07, -1.1618e-05, -1.2293e-05],\n [-5.8486e-07, -7.9378e-06, -9.1607e-06]],\n\n [[-1.0297e-05, 2.8203e-06, 3.2955e-05],\n [-2.4879e-07, -3.7488e-06, -7.0722e-06],\n [-4.3003e-06, 2.5835e-06, 1.2749e-05]]],\n\n\n [[[-2.2011e-06, -3.3129e-06, 3.6850e-07],\n [-5.3803e-06, -1.6128e-05, -1.2580e-05],\n [-5.7928e-06, -2.1478e-05, -1.2584e-05]],\n\n [[-2.2375e-07, -1.5613e-05, -9.8206e-06],\n [-3.7349e-06, -8.4444e-06, -6.1238e-06],\n [-5.2271e-06, -1.4449e-05, -1.7905e-05]],\n\n [[ 2.1142e-06, 5.0719e-07, 5.2781e-06],\n [-1.4962e-05, -1.3634e-05, -4.3874e-06],\n [-1.1678e-05, -2.4548e-06, 6.3136e-06]],\n\n ...,\n\n [[ 5.7788e-06, -2.2294e-07, -2.6658e-06],\n [-6.6631e-06, -5.9622e-06, -7.9166e-07],\n [-8.3589e-06, -4.0054e-07, -3.7849e-06]],\n\n [[ 3.5370e-06, -2.3673e-05, -1.7636e-05],\n [ 1.6865e-05, -1.0474e-05, -7.8589e-06],\n [ 4.2558e-06, -7.1814e-06, -2.1575e-05]],\n\n [[-8.4338e-07, -6.2628e-06, -1.1489e-05],\n [ 1.4448e-06, 4.7780e-06, -2.0695e-05],\n [ 1.7370e-05, -2.0556e-05, -1.0953e-05]]]]), 'exp_avg_sq': tensor([[[[1.5348e-08, 1.3357e-08, 1.3897e-08],\n [1.5432e-08, 1.2513e-08, 1.2110e-08],\n [1.4406e-08, 1.2361e-08, 1.7579e-08]],\n\n [[1.0909e-08, 1.4362e-08, 7.9052e-09],\n [1.1440e-08, 8.2718e-09, 1.0145e-08],\n [9.1891e-09, 8.4748e-09, 1.2001e-08]],\n\n [[8.4862e-09, 6.8077e-09, 1.0486e-08],\n [9.0600e-09, 7.9094e-09, 9.4106e-09],\n [8.2196e-09, 7.7240e-09, 9.1499e-09]],\n\n ...,\n\n [[4.8978e-09, 5.7917e-09, 1.3554e-08],\n [5.6787e-09, 1.9132e-08, 5.2051e-09],\n [6.5386e-09, 7.4167e-09, 5.0685e-09]],\n\n [[8.8995e-09, 1.1708e-08, 1.4742e-08],\n [1.0350e-08, 1.2245e-08, 9.8420e-09],\n [8.7543e-09, 9.4934e-09, 1.0245e-08]],\n\n [[1.4679e-08, 1.4319e-08, 1.8419e-08],\n [1.5022e-08, 1.7354e-08, 1.9426e-08],\n [3.2379e-08, 3.2683e-08, 2.2826e-08]]],\n\n\n [[[1.0309e-07, 1.3045e-07, 1.4472e-07],\n [1.3650e-07, 1.2513e-07, 1.3496e-07],\n [1.1279e-07, 1.3841e-07, 1.2721e-07]],\n\n [[8.4887e-08, 1.1280e-07, 9.9306e-08],\n [7.4468e-08, 9.3603e-08, 9.8095e-08],\n [8.5475e-08, 9.7144e-08, 1.0074e-07]],\n\n [[6.5833e-08, 4.2819e-08, 4.2982e-08],\n [6.3378e-08, 4.8638e-08, 4.7158e-08],\n [7.5710e-08, 7.0096e-08, 5.8792e-08]],\n\n ...,\n\n [[3.9062e-08, 4.6820e-08, 3.9565e-08],\n [4.5327e-08, 4.8350e-08, 2.7996e-08],\n [3.9067e-08, 4.9815e-08, 4.2721e-08]],\n\n [[6.2042e-08, 1.1324e-07, 9.7085e-08],\n [8.8043e-08, 9.2420e-08, 1.1028e-07],\n [8.5727e-08, 7.6479e-08, 7.5336e-08]],\n\n [[1.6088e-07, 2.0620e-07, 2.7458e-07],\n [1.1221e-07, 1.1746e-07, 1.5767e-07],\n [8.9034e-08, 9.5718e-08, 1.6136e-07]]],\n\n\n [[[2.1285e-08, 3.1498e-08, 1.5960e-08],\n [1.9830e-08, 1.7036e-08, 2.4418e-08],\n [1.9826e-08, 1.6658e-08, 2.9095e-08]],\n\n [[1.1354e-08, 1.4261e-08, 1.3696e-08],\n [1.4373e-08, 1.4667e-08, 1.4962e-08],\n [1.0687e-08, 1.2704e-08, 2.5595e-08]],\n\n [[1.3317e-08, 1.2349e-08, 1.5311e-08],\n [1.7889e-08, 1.3726e-08, 1.2333e-08],\n [9.8319e-09, 1.3478e-08, 1.2090e-08]],\n\n ...,\n\n [[7.7921e-09, 7.1472e-09, 5.7270e-09],\n [7.5525e-09, 5.7465e-09, 6.0435e-09],\n [4.2289e-09, 5.7112e-09, 6.4894e-09]],\n\n [[1.2732e-08, 1.3398e-08, 2.1821e-08],\n [1.2400e-08, 1.3155e-08, 1.6247e-08],\n [1.0496e-08, 7.9095e-09, 1.1578e-08]],\n\n [[1.7973e-08, 1.6605e-08, 2.2961e-08],\n [1.9110e-08, 2.2784e-08, 2.2654e-08],\n [2.0581e-08, 2.1711e-08, 1.8622e-08]]],\n\n\n ...,\n\n\n [[[3.1463e-08, 2.0839e-08, 2.3011e-08],\n [2.6900e-08, 2.2047e-08, 2.0125e-08],\n [2.1517e-08, 2.3100e-08, 1.9475e-08]],\n\n [[2.4909e-08, 2.6972e-08, 2.3194e-08],\n [1.9508e-08, 2.5142e-08, 1.9548e-08],\n [1.4436e-08, 1.4556e-08, 1.2260e-08]],\n\n [[1.9184e-08, 1.5986e-08, 1.1824e-08],\n [2.1162e-08, 1.8153e-08, 1.8854e-08],\n [2.1032e-08, 1.6141e-08, 1.4798e-08]],\n\n ...,\n\n [[7.7946e-09, 7.2475e-09, 6.1076e-09],\n [5.5374e-09, 6.0763e-09, 6.5988e-09],\n [5.6305e-09, 4.4596e-09, 5.6259e-09]],\n\n [[2.3079e-08, 1.9717e-08, 2.1969e-08],\n [1.9912e-08, 2.8069e-08, 2.3516e-08],\n [1.7144e-08, 2.5722e-08, 1.9245e-08]],\n\n [[5.2446e-08, 4.5937e-08, 6.1034e-08],\n [6.1118e-08, 5.0843e-08, 7.6974e-08],\n [6.2248e-08, 6.6967e-08, 8.5257e-08]]],\n\n\n [[[3.4349e-08, 3.9758e-08, 4.7471e-08],\n [3.2814e-08, 3.3993e-08, 4.5545e-08],\n [4.6609e-08, 3.1044e-08, 4.0702e-08]],\n\n [[2.2800e-08, 4.1554e-08, 3.1081e-08],\n [3.2443e-08, 3.3222e-08, 3.5605e-08],\n [3.1294e-08, 3.1954e-08, 4.1129e-08]],\n\n [[3.2215e-08, 2.2313e-08, 2.9925e-08],\n [2.5773e-08, 2.3897e-08, 2.3234e-08],\n [3.2011e-08, 2.9162e-08, 2.8522e-08]],\n\n ...,\n\n [[1.6251e-08, 1.8839e-08, 1.5009e-08],\n [1.7664e-08, 1.3852e-08, 2.1854e-08],\n [1.7963e-08, 1.8654e-08, 1.8281e-08]],\n\n [[2.9174e-08, 3.4586e-08, 2.9913e-08],\n [4.4515e-08, 3.1174e-08, 2.8428e-08],\n [2.9984e-08, 3.2221e-08, 3.3778e-08]],\n\n [[3.8119e-08, 6.6687e-08, 6.0436e-08],\n [3.1746e-08, 5.1125e-08, 4.9100e-08],\n [2.7309e-08, 3.2710e-08, 3.1190e-08]]],\n\n\n [[[1.8567e-08, 2.0911e-08, 1.9513e-08],\n [3.6400e-08, 4.0879e-08, 2.5816e-08],\n [1.4503e-08, 2.2004e-08, 1.9954e-08]],\n\n [[1.2912e-08, 1.4916e-08, 1.2244e-08],\n [1.2317e-08, 1.5758e-08, 1.4610e-08],\n [1.6853e-08, 1.4970e-08, 1.8971e-08]],\n\n [[1.1522e-08, 1.2490e-08, 1.2375e-08],\n [2.1066e-08, 1.5078e-08, 1.5851e-08],\n [1.1833e-08, 1.2287e-08, 1.3934e-08]],\n\n ...,\n\n [[1.2742e-08, 9.5662e-09, 6.0481e-09],\n [1.4567e-08, 7.6653e-09, 1.1200e-08],\n [9.1021e-09, 7.6713e-09, 8.9827e-09]],\n\n [[1.2425e-08, 1.3316e-08, 1.9361e-08],\n [1.5266e-08, 1.3585e-08, 1.0710e-08],\n [1.3591e-08, 1.4623e-08, 1.5483e-08]],\n\n [[2.1493e-08, 2.6661e-08, 2.6113e-08],\n [2.2922e-08, 2.8975e-08, 2.5634e-08],\n [2.8315e-08, 2.9364e-08, 2.5889e-08]]]])}, 88: {'step': 7160, 'exp_avg': tensor([-1.1991e-05, -2.3510e-04, 1.2831e-04, 1.5101e-04, 6.9279e-05,\n 1.1380e-04, -3.5781e-05, 7.4051e-06, -7.6471e-05, 4.3193e-05,\n 5.9193e-06, -1.3713e-05, -8.1959e-05, -7.8181e-05, 3.9568e-05,\n 2.8907e-05, 1.4331e-04, 7.4819e-05, 4.3436e-05, -1.7805e-04,\n -3.1828e-04, 2.1098e-04, 6.4188e-06, -5.3996e-05, 1.1976e-05,\n 5.2680e-05, 1.5765e-04, -7.3873e-05, 1.8716e-05, -1.9233e-04,\n -3.1214e-05, 6.3920e-05, -1.7904e-04, 4.7437e-06, -9.9523e-05,\n 1.8000e-05, -5.7126e-05, 7.1026e-05, 1.0778e-05, -1.0205e-04,\n -9.4650e-05, 1.2318e-04, 1.3918e-04, 1.4723e-04, -2.3196e-05,\n -1.3962e-04, -6.7419e-05, -1.3340e-05, -3.1432e-05, -5.9342e-05,\n -5.4006e-05, -7.2744e-06, 1.1714e-07, -2.3757e-04, -1.0193e-04,\n -2.2823e-04, -4.4417e-05, -1.4850e-05, 9.0547e-05, -3.0423e-05,\n 7.6993e-05, -1.0689e-04, -5.0330e-05, -1.5127e-04, -3.2473e-05,\n -1.4525e-04, 8.6361e-05, 7.8392e-05, -1.5899e-05, 7.6456e-05,\n -6.9134e-05, -3.6405e-05, 4.5897e-06, 3.2192e-05, -2.7971e-04,\n 1.3987e-04, 1.3157e-04, -6.6807e-05, 8.2397e-05, -1.0895e-04,\n 5.5058e-05, 6.9170e-06, 8.0056e-05, 1.3254e-04, 2.1563e-05,\n -8.9737e-04, -4.3561e-05, 4.4253e-05, 5.0623e-05, -2.2652e-04,\n 4.6690e-05, 1.2218e-04, -4.9050e-04, -1.3494e-04, -6.1679e-06,\n 1.2653e-04, -5.6214e-05, 7.2476e-05, -1.4499e-04, -1.3613e-05,\n -1.4420e-04, -1.0228e-04, -9.3935e-06, -7.4062e-05, -1.3804e-04,\n 1.1596e-04, -1.8589e-04, 1.1312e-04, 4.3183e-06, -2.0128e-05,\n -1.2116e-05, -1.4465e-05, 2.1310e-04, 4.3772e-05, 1.9718e-04,\n 1.7728e-04, -7.2705e-05, 1.1042e-04, 1.4486e-05, 2.4789e-04,\n 4.5501e-05, 8.1899e-05, 3.1307e-05, -1.9348e-04, 2.6728e-04,\n -2.1255e-05, -1.6908e-05, 1.3213e-04, 1.6444e-04, 8.5377e-05,\n -5.2729e-05, 2.2698e-05, 1.7395e-04, 6.2482e-05, 3.3877e-05,\n -5.0887e-06, 1.1652e-04, 1.6164e-05, 7.3336e-05, 7.3342e-06,\n -2.7183e-06, 7.5343e-05, 5.9185e-05, -1.0522e-04, -5.9486e-05,\n 1.4912e-05, 1.7206e-04, 1.1991e-04, -1.3422e-04, 1.6252e-05,\n 6.6968e-05, 1.0802e-05, -4.4665e-05, 1.6769e-04, 5.4360e-05,\n 4.6397e-05, 1.4927e-03, 2.6263e-05, -5.8407e-05, 4.0798e-05,\n -1.8411e-05, -3.7440e-04, 2.4067e-05, 1.5528e-04, -7.3449e-05,\n -1.9780e-05, 1.6578e-04, -5.2054e-05, 3.3242e-05, -2.9891e-06,\n -3.0255e-06, -8.4152e-05, 4.9316e-05, -6.6454e-06, 6.7822e-05,\n 1.7085e-04, 9.4123e-05, -2.0064e-04, -4.0772e-05, -5.5600e-05,\n 2.9312e-04, 6.2229e-05, -3.2229e-06, 1.1588e-04, -2.7130e-04,\n 3.3087e-05, 3.8401e-05, -1.7458e-04, -1.5547e-04, 1.5517e-04,\n -1.1181e-04, 9.4945e-05, -2.4336e-04, -1.2782e-04, 1.5116e-05,\n -2.7067e-05, -1.0479e-04, 7.0152e-05, 1.0996e-04, -7.6974e-05,\n -1.8250e-04, 2.0067e-04, 3.8990e-04, -2.7307e-05, -3.9870e-05,\n -1.1379e-05, 5.5397e-05, 7.2488e-05, 3.4704e-05, -7.7831e-05,\n 2.6913e-04, 1.0726e-05, 1.2771e-04, -7.3932e-06, -1.6515e-05,\n -8.6930e-05, -1.1171e-04, -3.9136e-05, -2.6723e-05, -1.7947e-04,\n -2.3428e-05, -6.3883e-05, 9.3693e-05, 4.9606e-05, -2.5897e-06,\n -3.2913e-05, 3.6393e-05, -2.7210e-04, 6.2205e-05, 6.7259e-05,\n -1.9790e-04, -2.1109e-04, -1.3351e-04, 1.7592e-04, 1.5020e-04,\n 8.0165e-05, 4.9442e-06, -9.0575e-05, 2.4024e-04, -4.7121e-05,\n 2.0759e-04, -1.2065e-04, 4.8566e-05, -3.9657e-05, 4.3911e-05,\n -1.4457e-04, 2.4060e-04, -5.4749e-05, -7.7245e-05, 9.0552e-06,\n 1.0478e-04, 5.3535e-05, 4.9131e-05, -1.2897e-04, 1.5590e-04,\n 1.2161e-04]), 'exp_avg_sq': tensor([1.3660e-06, 1.1997e-05, 1.8691e-06, 2.2317e-06, 1.3508e-06, 3.5054e-06,\n 1.8426e-06, 1.1027e-06, 3.4654e-06, 2.3515e-06, 1.3109e-06, 6.7475e-07,\n 1.5687e-06, 3.0454e-06, 2.6371e-06, 2.3186e-06, 2.7710e-06, 1.7601e-06,\n 2.7876e-06, 1.7857e-06, 5.0767e-06, 3.9234e-06, 1.2915e-06, 1.8032e-06,\n 1.0650e-06, 1.1472e-06, 9.7517e-06, 1.3021e-06, 8.7147e-07, 8.2568e-06,\n 5.1554e-06, 1.9647e-06, 1.4693e-06, 5.7064e-06, 8.5228e-07, 2.0581e-06,\n 2.6366e-06, 1.9827e-06, 2.9315e-06, 1.3094e-06, 2.5126e-06, 2.2781e-06,\n 2.0724e-06, 3.1760e-06, 2.0354e-06, 1.9538e-06, 1.4006e-06, 1.2127e-06,\n 7.8553e-07, 2.3470e-06, 4.8616e-06, 2.8114e-06, 9.8936e-07, 6.7681e-06,\n 4.4852e-06, 2.7670e-06, 1.1955e-06, 4.2246e-06, 1.8852e-06, 1.0421e-06,\n 1.0976e-06, 5.3268e-06, 3.1292e-06, 2.9540e-06, 1.2034e-06, 2.1441e-06,\n 1.2167e-06, 2.0622e-06, 1.4360e-06, 2.3477e-06, 1.5279e-06, 2.3547e-06,\n 1.2331e-06, 9.8440e-07, 2.3145e-06, 2.4748e-06, 2.7277e-06, 2.2827e-06,\n 2.2820e-06, 4.2637e-06, 1.0041e-06, 1.4219e-06, 7.4385e-07, 1.4176e-06,\n 1.1220e-06, 2.9651e-05, 2.8698e-06, 5.6456e-06, 8.0722e-07, 3.6071e-06,\n 7.0705e-07, 2.7150e-06, 8.8074e-06, 9.1203e-07, 2.0430e-06, 1.5585e-06,\n 1.2513e-05, 8.1426e-07, 1.5055e-06, 1.0294e-06, 2.9059e-06, 1.5629e-06,\n 5.0512e-06, 6.1616e-06, 4.4415e-06, 3.5981e-06, 8.1560e-06, 1.5836e-06,\n 1.4735e-06, 9.6942e-07, 7.0592e-07, 3.9330e-06, 5.3243e-06, 3.6927e-06,\n 2.3705e-06, 1.0441e-06, 5.0905e-06, 5.2855e-06, 1.2628e-06, 1.1225e-06,\n 1.1011e-06, 9.3707e-07, 2.9876e-06, 4.0279e-06, 3.8709e-06, 2.1889e-06,\n 1.0965e-06, 3.7886e-06, 3.3009e-06, 2.2715e-05, 1.9857e-06, 9.1423e-07,\n 1.0784e-06, 6.7139e-06, 2.0411e-06, 6.3545e-07, 1.4054e-06, 2.2500e-06,\n 6.8597e-07, 1.2640e-06, 2.0319e-06, 4.4527e-06, 1.5252e-06, 4.7613e-06,\n 3.2083e-06, 3.1930e-06, 2.4497e-06, 6.9104e-06, 6.6595e-06, 2.5604e-06,\n 1.9608e-06, 7.3383e-07, 2.8354e-06, 1.9507e-06, 2.8881e-06, 3.6940e-06,\n 4.9296e-05, 3.5146e-06, 1.8657e-06, 7.6778e-06, 3.8621e-06, 1.3788e-05,\n 1.2817e-06, 4.6688e-06, 2.0353e-06, 1.4314e-06, 2.6070e-06, 1.6792e-06,\n 1.6804e-06, 5.5616e-07, 2.7762e-06, 9.4794e-07, 1.0097e-06, 1.1492e-06,\n 3.0428e-06, 5.0302e-06, 7.8814e-07, 4.6730e-06, 1.8978e-06, 1.5584e-06,\n 1.7820e-05, 1.0064e-06, 2.1020e-06, 3.7368e-06, 2.8904e-06, 5.4738e-06,\n 1.7315e-06, 8.0200e-06, 2.3160e-06, 1.4756e-06, 5.8390e-06, 8.7115e-07,\n 5.4257e-06, 7.5704e-07, 1.7684e-06, 1.1916e-06, 9.9563e-07, 1.4069e-06,\n 2.9488e-06, 1.7990e-06, 3.7027e-06, 8.3877e-06, 2.9300e-05, 8.1729e-06,\n 1.5658e-06, 5.3976e-07, 1.2319e-06, 6.9153e-07, 9.5493e-07, 1.4370e-06,\n 2.2001e-06, 1.7388e-06, 1.8252e-06, 1.6527e-06, 1.1944e-06, 8.5245e-06,\n 6.6030e-07, 1.2054e-06, 1.9267e-06, 1.6070e-06, 1.1653e-06, 5.4011e-06,\n 1.0956e-06, 4.4953e-06, 1.7198e-06, 2.8765e-06, 7.3760e-07, 2.7463e-05,\n 3.0081e-06, 3.6438e-06, 5.5766e-06, 2.9872e-06, 2.4125e-06, 2.0847e-06,\n 2.6792e-06, 2.8442e-06, 1.0585e-06, 7.3079e-06, 3.8388e-06, 2.0932e-06,\n 1.7915e-06, 1.7334e-06, 6.7126e-07, 1.3468e-06, 7.4246e-06, 7.8564e-06,\n 2.0094e-06, 1.6627e-06, 1.8794e-06, 2.0836e-06, 1.3595e-06, 1.5442e-06,\n 2.7230e-06, 6.5031e-06, 2.7513e-06, 2.1888e-06])}, 89: {'step': 7160, 'exp_avg': tensor([ 2.9581e-06, -7.4730e-05, 1.3122e-04, 8.9659e-05, 5.1535e-05,\n 1.6158e-05, 4.4514e-05, 4.6265e-05, -5.7829e-05, -1.8841e-05,\n -3.1984e-05, -5.3845e-05, 2.3580e-05, -2.6225e-06, 1.5079e-07,\n 7.9874e-06, 1.4233e-04, 1.1839e-04, -1.6682e-05, -1.7221e-04,\n -1.1378e-04, 1.5290e-04, -2.7999e-05, 5.5402e-05, 3.7657e-05,\n -7.1082e-06, 7.2107e-05, -9.4495e-05, 1.7870e-05, -8.1695e-05,\n -1.3387e-04, 7.8916e-05, -1.1800e-04, -8.6864e-05, -9.0325e-05,\n 1.4972e-05, -5.8831e-05, 1.4365e-04, 6.4302e-05, -8.6324e-05,\n -6.9126e-05, 2.9992e-05, 1.4294e-04, 1.1440e-04, -3.9548e-05,\n -6.9464e-05, -4.8310e-05, -2.0687e-05, -3.4977e-06, -2.4431e-05,\n 3.8348e-05, -1.1365e-05, 2.2520e-05, -8.2898e-06, 1.0187e-05,\n -1.2261e-04, -5.0213e-05, -2.4559e-05, 7.2731e-05, -3.0796e-07,\n 6.7874e-05, -1.6498e-04, -2.3133e-05, -1.2603e-04, -4.3011e-05,\n -7.4524e-05, 5.2038e-05, -1.3153e-05, -6.0774e-05, 8.0966e-05,\n 3.6685e-05, -1.9825e-05, -3.6983e-05, 6.3180e-05, -2.2255e-04,\n 1.2284e-04, 9.5845e-05, -2.1587e-06, 4.4660e-05, -5.8660e-05,\n -2.2581e-06, 3.2589e-05, 2.3219e-05, 5.6405e-05, 2.9088e-05,\n -9.0170e-04, -1.5097e-04, -2.0766e-05, 6.6473e-05, -1.3526e-04,\n -1.4575e-05, 9.5680e-05, -2.8213e-04, -1.6940e-04, -3.9535e-05,\n 8.4007e-05, 9.1556e-05, 1.7983e-05, -1.4934e-04, 6.8048e-05,\n -7.9467e-05, -9.2055e-05, -2.4511e-05, -1.2715e-04, -9.9791e-05,\n 6.3971e-05, -1.1289e-04, 9.9633e-05, 2.1240e-05, 2.8170e-05,\n -1.1008e-04, -5.5660e-05, 1.9797e-04, -3.2111e-05, 8.7778e-05,\n 1.6662e-04, 1.0173e-04, -2.0826e-06, 2.7583e-05, 1.4218e-04,\n 3.2931e-06, 4.9074e-05, -1.4298e-05, -1.5336e-04, 2.2837e-04,\n -3.1354e-05, -3.2358e-05, 1.3988e-04, -3.7776e-05, 4.1556e-05,\n -4.9936e-05, -3.5578e-05, 1.6209e-04, 5.1236e-06, 2.0128e-06,\n -3.0162e-05, 1.2145e-04, 1.1212e-05, 7.4760e-05, 8.2226e-05,\n -7.5772e-05, 1.6740e-04, 9.4102e-06, -6.2535e-05, -1.4786e-04,\n 9.1113e-05, 1.4744e-04, 5.7640e-05, -1.3782e-04, 2.9429e-05,\n 7.1036e-05, 8.1012e-06, 1.6276e-05, 1.3514e-04, 4.5017e-05,\n 6.6741e-05, 2.4571e-05, 1.4057e-04, 4.6851e-05, 9.4357e-05,\n -4.2537e-05, -2.1913e-04, 2.3386e-05, 1.3519e-04, -4.1502e-05,\n 1.0075e-05, 8.2458e-05, -2.3294e-06, -8.0224e-06, 6.6757e-05,\n 7.7152e-06, -1.3136e-04, 6.5408e-05, 5.5250e-05, 8.7127e-05,\n 1.0650e-04, 7.3369e-05, -3.3951e-04, -4.5209e-05, -6.5269e-05,\n 1.4328e-04, 1.5370e-05, -2.1951e-05, 3.6247e-05, -1.4861e-04,\n 3.4491e-05, 4.1273e-05, -5.9104e-05, -1.0306e-04, 1.7438e-04,\n 3.9145e-05, 3.6427e-05, -1.4426e-04, -7.4770e-05, -2.8194e-05,\n 8.4677e-06, -6.2344e-05, -4.1396e-05, 7.3307e-05, -4.2090e-05,\n -1.0364e-04, 1.6560e-04, 2.0827e-04, -7.4922e-05, -1.0316e-04,\n -5.2879e-05, 8.1636e-05, -8.7886e-05, -4.9148e-06, -5.8231e-05,\n 2.2917e-04, -8.7683e-05, 1.0729e-04, -3.8645e-05, 1.1304e-05,\n 6.8585e-06, -6.5084e-05, 1.5187e-05, -1.4185e-05, -4.6429e-05,\n -6.4067e-05, -1.2717e-05, 1.8226e-06, -1.0713e-04, -2.8926e-05,\n 3.3359e-05, -2.7604e-06, -1.5911e-04, -2.0325e-05, 5.6783e-05,\n -2.3288e-04, -2.4938e-04, -7.7709e-05, 7.1032e-05, 9.5114e-05,\n 5.1468e-05, 3.7469e-06, -2.8824e-05, 1.3700e-04, 1.4520e-06,\n 4.4715e-05, -1.1518e-04, 3.5380e-05, -3.3011e-05, 5.3544e-05,\n 1.7587e-04, 1.1631e-04, -3.5048e-05, -8.6117e-05, -3.8553e-05,\n 5.4085e-05, 6.2491e-05, 4.1310e-05, -8.2088e-05, 1.2188e-04,\n 6.0637e-05]), 'exp_avg_sq': tensor([8.9022e-07, 3.6650e-06, 1.4558e-06, 1.0154e-06, 9.3024e-07, 2.3087e-06,\n 9.4546e-07, 8.5744e-07, 1.2547e-06, 1.7073e-06, 7.5073e-07, 2.2936e-07,\n 1.0729e-06, 1.1421e-06, 2.0920e-06, 1.6325e-06, 1.8609e-06, 1.4380e-06,\n 1.6789e-06, 1.5412e-06, 4.6693e-06, 3.9629e-06, 5.9652e-07, 1.1126e-06,\n 1.1680e-06, 8.6618e-07, 5.3445e-06, 1.3514e-06, 1.6443e-07, 2.8911e-06,\n 1.4769e-06, 1.1821e-06, 1.1571e-06, 2.3042e-06, 6.6935e-07, 1.4742e-06,\n 7.6244e-07, 1.5609e-06, 2.4964e-06, 9.7513e-07, 1.8235e-06, 2.1154e-06,\n 1.3818e-06, 2.1797e-06, 1.3337e-06, 9.7114e-07, 1.0788e-06, 7.0777e-07,\n 4.3413e-07, 1.2873e-06, 2.3655e-06, 1.1567e-06, 8.1141e-07, 1.9912e-06,\n 3.9902e-06, 1.0271e-06, 5.8008e-07, 1.9423e-06, 1.3441e-06, 5.7506e-07,\n 8.1284e-07, 2.8887e-06, 1.9267e-06, 1.4182e-06, 5.6882e-07, 1.3688e-06,\n 7.4563e-07, 1.7714e-06, 2.0545e-06, 9.6333e-07, 4.9587e-07, 1.2573e-06,\n 8.9423e-07, 1.4923e-06, 1.2871e-06, 1.8707e-06, 1.3894e-06, 1.1005e-06,\n 1.0519e-06, 1.7108e-06, 1.0319e-06, 6.2541e-07, 4.2882e-07, 1.6382e-06,\n 8.0865e-07, 2.8086e-05, 1.6925e-06, 3.1165e-06, 5.7208e-07, 3.4015e-06,\n 5.7436e-07, 1.0192e-06, 4.7654e-06, 5.6789e-07, 1.3158e-06, 8.1701e-07,\n 5.1996e-06, 4.2132e-07, 7.2178e-07, 7.2854e-07, 1.3869e-06, 7.7706e-07,\n 2.2550e-06, 2.3343e-06, 1.6379e-06, 2.9225e-06, 2.8748e-06, 1.2647e-06,\n 6.8381e-07, 5.7948e-07, 8.9823e-07, 2.4422e-06, 3.7696e-06, 1.5811e-06,\n 1.3875e-06, 7.4056e-07, 1.0752e-06, 5.3839e-07, 9.4588e-07, 8.7171e-07,\n 7.6154e-07, 5.9149e-07, 1.8769e-06, 1.8257e-06, 1.9072e-06, 8.6249e-07,\n 7.9139e-07, 2.3681e-06, 7.1167e-07, 8.4124e-06, 1.2020e-06, 5.8846e-07,\n 7.6152e-07, 2.4585e-06, 1.3962e-06, 4.5881e-07, 1.3413e-06, 1.4595e-06,\n 5.6333e-07, 1.2782e-06, 1.1685e-06, 8.6249e-07, 9.1001e-07, 2.3454e-06,\n 2.1481e-06, 1.5377e-06, 1.8788e-06, 2.3457e-06, 3.0235e-06, 1.3375e-06,\n 1.1649e-06, 4.6721e-07, 1.8333e-06, 1.7650e-06, 1.3812e-06, 2.2940e-06,\n 4.2595e-06, 1.5768e-06, 1.0683e-06, 5.5931e-06, 2.9749e-06, 6.4197e-06,\n 4.9471e-07, 4.1098e-06, 1.3438e-06, 3.6873e-07, 2.3232e-06, 6.3279e-07,\n 7.5996e-07, 4.3476e-07, 1.3848e-06, 1.0456e-06, 9.0958e-07, 7.3396e-07,\n 1.5604e-06, 2.0047e-06, 4.9884e-07, 2.8738e-06, 9.6334e-07, 1.0135e-06,\n 5.7035e-06, 6.3769e-07, 1.7865e-06, 2.0225e-06, 1.4977e-06, 1.7812e-06,\n 1.0419e-06, 3.8575e-06, 1.5943e-06, 1.0609e-06, 6.6687e-07, 8.1152e-07,\n 2.4052e-06, 6.1499e-07, 1.4670e-06, 1.0971e-06, 7.2206e-07, 1.2608e-06,\n 4.5195e-06, 5.0780e-07, 1.6649e-06, 3.8224e-06, 9.5746e-06, 4.7559e-06,\n 9.6104e-07, 4.7021e-07, 9.2282e-07, 5.9660e-07, 6.1856e-07, 8.1758e-07,\n 1.5019e-06, 1.1383e-06, 1.1969e-06, 9.9532e-07, 8.2803e-07, 2.3977e-06,\n 7.0776e-07, 7.7484e-07, 1.3021e-06, 1.1436e-06, 7.9741e-07, 1.6095e-06,\n 5.5614e-07, 2.9677e-06, 9.7761e-07, 1.5139e-06, 7.8355e-07, 5.1435e-06,\n 1.6798e-06, 2.2542e-06, 3.5770e-06, 1.5674e-06, 7.7299e-07, 1.2613e-06,\n 1.1702e-06, 1.8679e-06, 7.5594e-07, 4.0202e-06, 2.2480e-06, 9.2375e-07,\n 1.0026e-06, 9.3450e-07, 6.1904e-07, 9.1198e-07, 3.4506e-06, 9.8836e-06,\n 1.4868e-06, 9.7437e-07, 1.4735e-06, 1.2581e-06, 7.5358e-07, 8.1048e-07,\n 1.8091e-06, 2.3153e-06, 1.8005e-06, 7.8766e-07])}, 90: {'step': 7160, 'exp_avg': tensor([[[[-3.7075e-06]],\n\n [[-8.9084e-07]],\n\n [[-1.2693e-05]],\n\n ...,\n\n [[ 2.0373e-06]],\n\n [[ 5.9803e-06]],\n\n [[ 1.7889e-05]]],\n\n\n [[[ 3.3909e-06]],\n\n [[-4.7005e-06]],\n\n [[-7.5217e-06]],\n\n ...,\n\n [[-4.3519e-06]],\n\n [[ 3.7778e-06]],\n\n [[ 1.8225e-05]]],\n\n\n [[[ 1.6701e-06]],\n\n [[ 1.9399e-06]],\n\n [[-3.7910e-06]],\n\n ...,\n\n [[ 1.2694e-05]],\n\n [[ 5.4070e-07]],\n\n [[-8.8827e-06]]],\n\n\n ...,\n\n\n [[[-5.8695e-07]],\n\n [[-8.3422e-06]],\n\n [[-1.3330e-05]],\n\n ...,\n\n [[ 1.2211e-05]],\n\n [[ 1.0026e-05]],\n\n [[-5.2490e-06]]],\n\n\n [[[ 1.9812e-06]],\n\n [[ 1.5463e-06]],\n\n [[ 4.5568e-06]],\n\n ...,\n\n [[ 1.1070e-06]],\n\n [[ 3.3943e-06]],\n\n [[ 5.1786e-06]]],\n\n\n [[[ 1.7723e-05]],\n\n [[ 1.1987e-05]],\n\n [[ 6.5980e-06]],\n\n ...,\n\n [[-2.1032e-05]],\n\n [[ 6.8686e-06]],\n\n [[ 5.6064e-05]]]]), 'exp_avg_sq': tensor([[[[5.0591e-09]],\n\n [[7.8071e-09]],\n\n [[5.9519e-09]],\n\n ...,\n\n [[1.2977e-08]],\n\n [[1.0732e-08]],\n\n [[1.4914e-08]]],\n\n\n [[[5.4428e-09]],\n\n [[1.3149e-08]],\n\n [[8.8188e-09]],\n\n ...,\n\n [[1.0016e-08]],\n\n [[1.2122e-08]],\n\n [[2.7352e-08]]],\n\n\n [[[1.2789e-08]],\n\n [[5.0749e-09]],\n\n [[7.7099e-09]],\n\n ...,\n\n [[8.0288e-09]],\n\n [[8.7676e-09]],\n\n [[9.6677e-09]]],\n\n\n ...,\n\n\n [[[1.7140e-08]],\n\n [[2.0074e-08]],\n\n [[2.9360e-08]],\n\n ...,\n\n [[1.9299e-08]],\n\n [[1.9920e-08]],\n\n [[3.1124e-08]]],\n\n\n [[[8.8921e-09]],\n\n [[1.5457e-08]],\n\n [[1.1645e-08]],\n\n ...,\n\n [[1.7015e-08]],\n\n [[1.3787e-08]],\n\n [[1.5223e-08]]],\n\n\n [[[9.1309e-08]],\n\n [[6.5576e-08]],\n\n [[5.7819e-08]],\n\n ...,\n\n [[1.4155e-07]],\n\n [[6.3040e-08]],\n\n [[1.0575e-07]]]])}, 91: {'step': 7160, 'exp_avg': tensor([-2.8468e-05, 8.5146e-05, -1.8292e-05, ..., -9.2639e-06,\n -6.3192e-06, 3.5414e-05]), 'exp_avg_sq': tensor([5.4352e-07, 2.6074e-07, 1.6310e-07, ..., 3.4492e-07, 3.5428e-07,\n 2.3630e-06])}, 92: {'step': 7160, 'exp_avg': tensor([ 3.3136e-05, 4.6914e-05, -2.2476e-05, ..., -1.5549e-05,\n 3.9843e-05, 9.4026e-05]), 'exp_avg_sq': tensor([6.0772e-07, 1.4366e-07, 1.1301e-07, ..., 2.3336e-07, 4.1397e-07,\n 3.1786e-06])}, 93: {'step': 7160, 'exp_avg': tensor([[[[-1.5383e-06]],\n\n [[-3.9948e-06]],\n\n [[-1.0308e-05]],\n\n ...,\n\n [[ 1.3867e-06]],\n\n [[-5.6348e-06]],\n\n [[-8.0629e-06]]],\n\n\n [[[-3.5462e-06]],\n\n [[ 2.8104e-06]],\n\n [[ 6.2843e-06]],\n\n ...,\n\n [[-6.8823e-06]],\n\n [[-4.4314e-06]],\n\n [[ 1.2498e-05]]],\n\n\n [[[ 1.3238e-06]],\n\n [[ 7.2928e-06]],\n\n [[-1.3717e-05]],\n\n ...,\n\n [[ 1.5184e-05]],\n\n [[-1.0451e-05]],\n\n [[ 1.5550e-05]]],\n\n\n ...,\n\n\n [[[ 1.3037e-05]],\n\n [[ 3.2864e-07]],\n\n [[-2.9493e-06]],\n\n ...,\n\n [[ 3.4779e-06]],\n\n [[ 2.0982e-06]],\n\n [[ 3.5241e-06]]],\n\n\n [[[ 2.4673e-05]],\n\n [[-9.3700e-06]],\n\n [[-8.3342e-07]],\n\n ...,\n\n [[ 2.4273e-06]],\n\n [[ 8.6593e-06]],\n\n [[ 5.3030e-06]]],\n\n\n [[[-5.1435e-05]],\n\n [[-4.7197e-05]],\n\n [[ 8.8035e-06]],\n\n ...,\n\n [[-3.2227e-05]],\n\n [[ 5.9391e-06]],\n\n [[ 3.4359e-05]]]]), 'exp_avg_sq': tensor([[[[1.9158e-08]],\n\n [[8.2139e-09]],\n\n [[7.6751e-09]],\n\n ...,\n\n [[1.8908e-08]],\n\n [[1.2618e-08]],\n\n [[3.9128e-08]]],\n\n\n [[[1.8033e-08]],\n\n [[5.9909e-09]],\n\n [[7.4349e-09]],\n\n ...,\n\n [[1.4749e-08]],\n\n [[5.8644e-09]],\n\n [[5.4036e-08]]],\n\n\n [[[2.3446e-08]],\n\n [[1.2527e-08]],\n\n [[1.0703e-08]],\n\n ...,\n\n [[2.9958e-08]],\n\n [[1.4505e-08]],\n\n [[4.8675e-08]]],\n\n\n ...,\n\n\n [[[1.8672e-08]],\n\n [[9.5975e-09]],\n\n [[1.1094e-08]],\n\n ...,\n\n [[1.5949e-08]],\n\n [[7.8060e-09]],\n\n [[3.5891e-08]]],\n\n\n [[[3.3106e-08]],\n\n [[9.4238e-09]],\n\n [[9.1049e-09]],\n\n ...,\n\n [[4.3819e-08]],\n\n [[1.3402e-08]],\n\n [[5.7521e-08]]],\n\n\n [[[8.8080e-08]],\n\n [[4.7604e-08]],\n\n [[2.2109e-08]],\n\n ...,\n\n [[1.0870e-07]],\n\n [[3.9190e-08]],\n\n [[1.1053e-07]]]])}, 94: {'step': 7160, 'exp_avg': tensor([ 2.0501e-05, -7.3750e-05, -1.6509e-04, -8.1620e-05, 2.5365e-05,\n 6.0423e-05, 9.0786e-07, -4.2578e-05, 1.7624e-05, -5.6635e-05,\n -7.8048e-05, -9.4371e-05, 3.3066e-05, 6.4787e-05, 7.2052e-06,\n 1.4421e-05, -1.3365e-05, 4.0677e-05, 8.1867e-05, -4.0723e-05,\n -8.6748e-05, 8.4793e-05, -3.4582e-05, 5.0982e-05, 1.6220e-04,\n 1.2585e-05, -5.5354e-05, 7.1405e-05, 4.1522e-05, -5.2967e-05,\n -1.0705e-04, -6.6251e-05, -9.8542e-05, -1.3725e-04, 1.4735e-05,\n -7.1101e-05, 2.6641e-05, 5.4487e-05, 4.0072e-05, 1.0948e-04,\n 4.4599e-06, -6.0801e-05, -2.3196e-05, -7.7914e-05, 8.1762e-05,\n 4.6517e-06, 7.1192e-05, 7.4937e-05, 1.2713e-04, 2.6407e-05,\n -1.1457e-04, -8.6428e-05, -3.2161e-05, -3.0801e-05, 1.6197e-04,\n -1.1394e-04, 7.1692e-05, 8.0717e-05, 1.2812e-05, 1.1049e-05,\n -1.3388e-05, -5.1891e-05, -2.9386e-05, -8.7345e-06, -6.7426e-05,\n -4.0561e-05, -1.4318e-05, -3.0994e-05, 3.3850e-06, 1.2665e-06,\n -1.5839e-04, -9.2794e-06, -2.6622e-05, 5.5113e-05, -5.6888e-05,\n -5.6179e-05, 6.3691e-05, 1.0997e-04, -8.2982e-05, 3.4283e-05,\n -9.4982e-05, -6.3258e-05, 7.1866e-05, 3.2860e-05, 8.3091e-05,\n -2.2606e-05, 7.0899e-05, 1.3075e-04, -4.9394e-05, 2.0427e-04,\n -1.0623e-04, -5.8057e-05, 7.1925e-05, -6.8865e-05, 3.7594e-05,\n 1.0221e-05, 1.2763e-05, -4.4520e-06, -3.9615e-05, -3.6919e-05,\n 1.5823e-05, 8.6163e-05, 6.8197e-05, 3.4899e-05, 7.0373e-05,\n -3.1661e-05, -2.0981e-05, -3.1917e-05, 2.8132e-04, 6.6409e-05,\n 2.2086e-05, -4.8542e-05, 9.4433e-05, -8.9448e-06, 3.0084e-05,\n -4.3090e-05, 5.4641e-05, -2.5055e-04, -1.9614e-04, 1.2961e-04,\n 4.9196e-05, 2.3469e-05, -9.1006e-05, -1.6390e-05, -2.0994e-05,\n 6.7325e-05, -2.2605e-05, -3.3577e-06, -8.0238e-05, 8.9023e-05,\n -7.1341e-05, 4.8627e-05, -1.8003e-05, 3.5272e-05, -2.0992e-05,\n -1.3818e-04, 1.5647e-05, -4.4340e-05, 3.4082e-05, -4.0702e-05,\n 7.0543e-05, 1.0186e-05, -3.1419e-05, -2.9847e-05, -1.4232e-04,\n 1.0791e-04, -1.6499e-05, -1.3408e-04, 1.1441e-04, -7.6413e-05,\n -1.8966e-05, -3.8711e-05, -1.7403e-05, 7.6980e-05, 8.8351e-05,\n 7.2392e-05, -4.3903e-05, -6.4928e-05, -3.4566e-05, 1.4870e-05,\n -4.4533e-05, -7.4242e-06, 8.3612e-05, 4.2788e-05, -4.2072e-05,\n -1.6059e-04, 5.3620e-05, -1.0901e-04, -1.1193e-04, 4.1607e-05,\n -1.5453e-04, -2.0828e-05, 1.7848e-05, 4.8014e-05, -1.1110e-04,\n -3.3605e-05, 9.8889e-05, -3.9042e-05, 2.7249e-05, 1.9273e-04,\n 5.8834e-06, 7.1067e-06, 5.4327e-05, -7.3109e-05, 2.5248e-05,\n 2.3862e-05, -9.3071e-05, 2.1328e-04, 7.7514e-05, 3.0108e-05,\n 2.8647e-04, -3.6335e-04, 4.9422e-05, -1.4684e-05, -4.9900e-05,\n -5.5966e-05, -7.4744e-05, 4.1503e-05, 2.7046e-05, 6.1372e-05,\n -4.5040e-05, 3.4886e-05, 1.9008e-04, 2.0656e-05, 1.3501e-05,\n 1.5242e-04, 1.8332e-04, 8.5593e-05, -6.3765e-05, 4.3154e-05,\n -1.8923e-04, -4.2903e-05, -1.4715e-04, -1.0955e-04, -9.2557e-07,\n 6.7585e-06, -4.5554e-05, 9.3011e-05, 9.3236e-05, 1.0671e-05,\n -7.2248e-05, -1.3788e-04, 1.6592e-04, -8.7707e-05, 6.4986e-05,\n 9.8693e-05, -6.1764e-05, -5.5057e-05, -1.0797e-04, -1.5395e-05,\n 4.3430e-07, -6.4350e-05, -4.1672e-05, 2.0340e-05, -4.3126e-05,\n 1.8405e-06, 6.0870e-05, -6.2662e-05, -3.5844e-05, -2.3765e-05,\n -5.8457e-05, -6.7691e-06, 1.2852e-04, -1.8432e-04, 1.8313e-04,\n -1.4243e-04, -7.9198e-06, -7.3253e-05, 6.4635e-05, 5.2624e-05,\n 5.5370e-05, 4.9348e-06, 6.9964e-06, -1.8690e-05, 7.4849e-05,\n -4.1828e-04]), 'exp_avg_sq': tensor([1.4704e-06, 1.2400e-06, 2.0426e-06, 8.0682e-07, 3.8139e-07, 1.5581e-06,\n 1.7365e-06, 1.8806e-06, 8.9972e-07, 1.2095e-06, 1.6549e-06, 1.1276e-06,\n 3.2623e-06, 1.0765e-06, 9.1423e-07, 1.4986e-06, 1.3346e-06, 6.5379e-07,\n 3.0380e-06, 9.8000e-07, 9.6755e-07, 8.8069e-07, 6.1474e-07, 8.1619e-07,\n 2.1968e-06, 3.8739e-07, 9.9725e-07, 9.8479e-07, 1.0182e-06, 1.2398e-06,\n 5.1359e-07, 1.4167e-06, 2.8011e-06, 8.7912e-07, 1.2474e-06, 1.0116e-06,\n 9.6514e-07, 2.4965e-06, 1.0226e-06, 1.5011e-06, 1.4105e-06, 3.9806e-06,\n 1.5068e-06, 7.3974e-07, 8.4489e-07, 1.2855e-06, 1.3301e-06, 6.9912e-07,\n 1.1513e-06, 1.1243e-06, 1.4230e-06, 1.5109e-06, 1.3574e-06, 1.4469e-06,\n 2.3357e-06, 1.5359e-06, 1.3824e-06, 5.9991e-06, 1.0745e-06, 1.2445e-06,\n 8.9393e-07, 1.8683e-06, 5.2745e-07, 1.9557e-06, 1.8704e-06, 6.6004e-07,\n 9.6431e-07, 1.1178e-06, 9.7893e-07, 7.0854e-07, 1.7485e-06, 3.2741e-06,\n 7.5582e-07, 2.1777e-06, 7.6616e-07, 6.8099e-07, 7.6202e-07, 1.2084e-06,\n 2.1377e-06, 8.5471e-07, 1.8490e-06, 1.5977e-06, 1.2446e-06, 8.0819e-07,\n 1.1253e-06, 9.6841e-07, 6.8161e-07, 2.9987e-06, 9.8683e-07, 3.7180e-06,\n 1.0153e-06, 7.2030e-07, 9.8380e-07, 1.6414e-06, 8.8255e-07, 6.3590e-07,\n 1.0209e-06, 1.1856e-06, 9.4868e-07, 2.5655e-06, 1.4505e-06, 5.5966e-07,\n 4.7393e-07, 1.2330e-06, 4.0220e-06, 2.5891e-06, 1.8920e-06, 1.1829e-06,\n 2.1253e-06, 7.7346e-07, 1.3513e-06, 1.4201e-06, 1.3091e-06, 2.0610e-06,\n 1.7625e-06, 1.0789e-06, 1.3050e-06, 2.0822e-06, 2.3458e-06, 1.3423e-06,\n 1.0500e-06, 1.4529e-06, 7.9927e-07, 1.1933e-06, 1.1037e-06, 1.4727e-06,\n 4.9635e-07, 1.5994e-06, 1.0283e-06, 7.2016e-07, 1.0025e-06, 6.4198e-07,\n 8.8276e-07, 8.6776e-07, 1.1970e-06, 1.5986e-06, 5.4063e-07, 8.6672e-07,\n 9.9583e-07, 2.1807e-06, 1.2907e-06, 9.1402e-07, 7.1595e-07, 1.0964e-06,\n 2.1061e-06, 9.8667e-07, 7.7794e-07, 9.4274e-07, 3.6809e-07, 1.0420e-06,\n 2.0026e-06, 6.2213e-07, 4.6158e-07, 1.2927e-06, 1.0189e-06, 1.5660e-06,\n 1.3015e-06, 2.3785e-06, 1.9719e-06, 4.6896e-07, 1.6990e-06, 1.7837e-06,\n 1.0279e-06, 7.4894e-07, 2.9096e-06, 1.4361e-06, 1.3164e-06, 1.6399e-06,\n 2.2089e-06, 2.7946e-06, 1.8867e-06, 1.4572e-06, 8.8766e-07, 1.0794e-06,\n 2.5020e-06, 1.6078e-06, 8.3248e-07, 1.4069e-06, 1.0256e-06, 1.9083e-06,\n 5.8343e-07, 9.5064e-07, 1.1936e-06, 5.8456e-07, 1.1303e-06, 9.2083e-07,\n 3.8346e-06, 6.6979e-07, 1.2625e-06, 6.0711e-07, 1.5173e-06, 4.0365e-06,\n 1.3985e-06, 5.6639e-07, 7.8679e-07, 1.7285e-06, 5.6637e-06, 4.4969e-07,\n 1.6454e-06, 7.0212e-07, 6.0085e-07, 1.2065e-06, 1.9271e-06, 1.0483e-06,\n 7.6577e-07, 1.4155e-06, 1.0454e-06, 2.4091e-06, 8.5300e-07, 7.5384e-07,\n 2.8631e-06, 9.0987e-07, 2.6016e-06, 7.0141e-07, 1.5068e-06, 7.3643e-07,\n 1.0930e-06, 2.8840e-06, 1.6242e-06, 1.4652e-06, 3.4479e-06, 1.3098e-06,\n 7.4842e-07, 9.7866e-07, 2.9353e-06, 1.1274e-06, 2.3613e-06, 8.4661e-07,\n 8.1515e-07, 6.4971e-07, 1.0117e-06, 1.4711e-06, 7.6627e-07, 5.4514e-06,\n 6.4267e-07, 8.9064e-07, 9.7132e-07, 1.5828e-06, 8.9576e-07, 1.7171e-06,\n 8.3880e-07, 1.1092e-06, 2.8963e-06, 6.1295e-06, 2.0427e-06, 6.6727e-07,\n 7.2026e-07, 2.4548e-06, 1.0860e-06, 2.2142e-06, 1.3030e-06, 4.6386e-07,\n 1.7072e-06, 1.2579e-06, 1.4189e-06, 9.3960e-06])}, 95: {'step': 7160, 'exp_avg': tensor([-6.6605e-06, -4.0428e-05, 5.5742e-05, -2.4440e-05, 2.1971e-05,\n 6.1508e-05, 2.3799e-05, -1.6305e-05, 6.8550e-05, -4.3919e-05,\n -1.9808e-05, -3.9472e-05, -1.2319e-05, 3.9262e-05, 1.4606e-05,\n -8.1900e-06, 2.0486e-05, 3.5493e-05, 1.0237e-04, 8.4074e-06,\n -5.3974e-05, 7.3130e-05, -1.4156e-04, 4.1699e-05, 4.5498e-05,\n -2.1042e-06, 7.2461e-06, 7.0861e-05, 4.8375e-05, -5.0070e-05,\n -3.9875e-05, -4.0935e-05, -2.7381e-05, -7.5800e-05, 2.0277e-06,\n -1.1580e-04, -6.3168e-05, 1.8524e-04, -2.5189e-05, 4.6771e-05,\n 1.0833e-04, -1.8244e-05, 1.1680e-04, -9.0934e-05, 8.9963e-05,\n -1.0555e-04, 1.3126e-05, 6.3605e-05, -2.7019e-05, 5.7036e-05,\n -9.6394e-05, -2.3000e-05, -1.5751e-05, -1.9257e-05, 5.5280e-05,\n -7.5938e-05, 3.7320e-05, 6.5691e-05, -2.0948e-05, -1.7011e-05,\n 3.0581e-06, -4.0810e-05, -2.4185e-05, 3.0100e-05, -9.5372e-05,\n 6.7188e-06, 5.0244e-05, 1.8259e-05, 4.7563e-05, 5.5843e-05,\n -1.1055e-04, -1.2592e-05, 1.7154e-05, 3.6016e-05, -6.0741e-05,\n -2.1036e-05, 1.0932e-04, 5.0107e-05, -3.4750e-05, 4.2260e-05,\n -1.1968e-04, -3.4291e-05, -1.8925e-05, -4.4502e-05, 4.6986e-05,\n 1.0266e-05, 3.5716e-05, 9.7791e-05, -5.9480e-05, 3.2868e-05,\n 3.8103e-05, -5.0457e-05, 5.3965e-05, -8.0968e-05, -1.4633e-05,\n 2.0392e-05, 6.4106e-05, 7.0383e-07, -2.2294e-05, -1.2538e-05,\n 2.6145e-05, 9.4457e-05, 6.3760e-05, 2.6702e-06, -5.6220e-05,\n -8.1721e-06, -6.8662e-05, 5.1689e-05, 1.6084e-04, 3.7599e-05,\n 3.1963e-05, 9.4555e-06, 1.2837e-04, 5.7021e-06, -4.6332e-06,\n -4.9337e-05, 6.3867e-05, 6.3826e-05, 2.0524e-05, 4.7271e-05,\n 7.9102e-05, -4.1262e-05, -4.1825e-05, -5.9679e-05, 1.9600e-05,\n 7.1399e-05, -3.1420e-05, 2.1323e-05, -4.8042e-05, 2.7346e-05,\n -5.9357e-05, 1.0600e-04, 1.4313e-05, 2.1898e-05, 2.8340e-05,\n -1.0395e-04, -3.2393e-06, -7.6815e-05, 3.7551e-05, -4.6654e-05,\n 5.0113e-05, 4.2967e-06, -5.6730e-05, -1.5062e-06, -1.2289e-04,\n 1.0795e-04, -2.9729e-05, -1.0136e-04, 7.5393e-05, -1.0311e-04,\n -5.7509e-06, 4.4375e-06, -5.6657e-05, 7.3747e-05, 2.7134e-06,\n 2.5238e-05, 3.6438e-05, -2.4309e-05, -1.2881e-05, 1.8181e-05,\n -1.2803e-05, 2.1226e-06, 7.4574e-05, 3.4115e-05, -1.5584e-05,\n -1.0278e-04, 1.4093e-05, 1.2149e-05, -7.5026e-05, 1.7129e-04,\n -1.0779e-04, -2.6029e-05, -1.0343e-05, 7.1991e-05, -1.4831e-05,\n 1.5678e-05, 4.9659e-05, -1.2575e-05, 4.0258e-05, 7.2790e-05,\n 1.4884e-05, -9.4223e-06, 7.4408e-05, -8.0903e-05, -2.4536e-05,\n 5.6917e-05, -4.8732e-06, 5.8525e-05, 4.3164e-05, 1.1135e-05,\n 1.4225e-04, -2.8246e-04, 2.4692e-05, -9.9485e-06, -4.5385e-05,\n -4.2559e-05, -5.7577e-05, -5.9568e-06, 1.0256e-05, 2.1085e-05,\n -2.9833e-05, 5.5312e-05, 9.6100e-05, -9.0037e-06, -8.0336e-06,\n 9.0860e-05, 1.3717e-04, 1.3511e-04, -8.3453e-06, 2.1961e-05,\n -9.5769e-05, -3.6499e-05, -6.9926e-05, -1.4256e-04, 1.5087e-05,\n -1.7843e-05, -3.0983e-05, 1.3241e-04, 6.7817e-05, -1.0127e-05,\n 3.0812e-06, -1.6423e-05, 9.5053e-05, -6.1455e-05, -5.5567e-05,\n 4.1025e-05, 2.5163e-06, -7.1064e-05, -7.3315e-05, -3.8667e-05,\n -2.1695e-05, -5.1377e-05, -1.1648e-04, -5.9501e-05, -3.7869e-05,\n 8.8530e-05, 1.3731e-05, -6.1378e-05, -1.9795e-05, -2.9853e-05,\n -3.2909e-05, -5.3512e-06, 1.4833e-04, -1.1902e-04, 5.9605e-05,\n -1.3758e-04, 1.7753e-05, -4.1755e-05, 6.4359e-06, 5.7695e-05,\n 6.8486e-05, -1.6175e-05, 2.3174e-05, 8.0474e-06, 1.2974e-04,\n -3.0732e-04]), 'exp_avg_sq': tensor([7.8071e-07, 2.7677e-07, 8.5064e-07, 1.2076e-06, 2.7404e-07, 6.8992e-07,\n 7.6181e-07, 7.4950e-07, 1.0027e-06, 4.9639e-07, 5.8688e-07, 6.2197e-07,\n 4.9209e-07, 8.2195e-07, 7.5569e-07, 8.6633e-07, 7.0391e-07, 2.8690e-07,\n 1.0471e-06, 4.9341e-07, 5.1889e-07, 4.3242e-07, 7.9744e-07, 6.4900e-07,\n 7.2609e-07, 2.5394e-07, 5.5972e-07, 8.5933e-07, 6.4592e-07, 4.7925e-07,\n 2.3173e-07, 1.5857e-06, 6.3054e-07, 6.9021e-07, 9.8642e-07, 9.8575e-07,\n 6.7126e-07, 1.6020e-06, 4.7431e-07, 7.9099e-07, 1.6147e-06, 1.4221e-06,\n 1.1161e-06, 3.4255e-07, 4.5351e-07, 1.3140e-06, 1.5007e-06, 3.2903e-07,\n 1.0084e-06, 1.2967e-06, 8.3120e-07, 7.8290e-07, 4.0386e-07, 5.9821e-07,\n 1.0915e-06, 1.5858e-06, 4.7397e-07, 2.5378e-06, 5.4076e-07, 7.6597e-07,\n 5.8045e-07, 1.5102e-06, 3.5430e-07, 8.8161e-07, 2.0680e-06, 6.9752e-07,\n 8.4144e-07, 1.1922e-06, 5.1001e-07, 3.1226e-07, 1.0923e-06, 1.1282e-06,\n 5.3869e-07, 1.3022e-06, 6.5791e-07, 2.8304e-07, 6.1377e-07, 8.9040e-07,\n 9.2665e-07, 8.9871e-07, 1.0051e-06, 2.2413e-06, 1.2060e-06, 8.9293e-07,\n 5.6094e-07, 1.4442e-06, 3.0397e-07, 3.9263e-06, 6.6798e-07, 9.1397e-07,\n 8.3656e-07, 5.1907e-07, 5.9465e-07, 1.3278e-06, 4.4138e-07, 3.2077e-07,\n 8.0254e-07, 5.0846e-07, 6.9470e-07, 8.9913e-07, 6.1591e-07, 3.8313e-07,\n 2.3981e-07, 6.3507e-07, 2.3898e-06, 9.3782e-07, 1.1889e-06, 6.5225e-07,\n 9.8100e-07, 4.2498e-07, 1.4621e-06, 6.1872e-07, 1.6978e-06, 1.2201e-06,\n 7.9133e-07, 7.0240e-07, 7.2642e-07, 5.3999e-07, 1.0579e-06, 7.7825e-07,\n 5.3110e-07, 6.1467e-07, 7.8460e-07, 1.0225e-06, 7.5719e-07, 8.4990e-07,\n 7.1937e-07, 6.0493e-07, 5.9798e-07, 5.7302e-07, 6.5617e-07, 5.3768e-07,\n 9.7515e-07, 5.0908e-07, 5.9984e-07, 1.2261e-06, 3.5803e-07, 1.4174e-06,\n 5.3017e-07, 1.1584e-06, 8.1526e-07, 4.3863e-07, 6.5189e-07, 6.9398e-07,\n 1.1485e-06, 8.0963e-07, 5.1741e-07, 4.4736e-07, 1.9097e-07, 9.2697e-07,\n 1.2386e-06, 5.8035e-07, 4.5198e-07, 5.4928e-07, 7.2103e-07, 5.9615e-07,\n 6.1315e-07, 1.0617e-06, 9.1793e-07, 4.1203e-07, 1.1943e-06, 5.0751e-07,\n 5.5735e-07, 4.5915e-07, 7.1632e-07, 6.7008e-07, 8.1546e-07, 5.9588e-07,\n 8.0285e-07, 1.5238e-06, 8.6710e-07, 1.8307e-06, 5.0030e-07, 1.1062e-06,\n 6.7123e-07, 9.2205e-07, 8.6603e-07, 6.7011e-07, 8.3562e-07, 8.0385e-07,\n 3.7643e-07, 4.9636e-07, 5.4709e-07, 6.4157e-07, 6.8443e-07, 6.4017e-07,\n 9.6355e-07, 3.7060e-07, 5.7375e-07, 3.7783e-07, 7.1439e-07, 2.8524e-06,\n 7.3732e-07, 5.6670e-07, 4.2584e-07, 9.5071e-07, 1.7011e-06, 5.7931e-07,\n 9.2945e-07, 3.3600e-07, 2.7839e-07, 7.9243e-07, 2.1845e-06, 5.6554e-07,\n 3.2730e-07, 6.8409e-07, 9.4496e-07, 1.5509e-06, 3.8980e-07, 5.3325e-07,\n 9.0277e-07, 5.6945e-07, 1.0160e-06, 5.9293e-07, 5.3613e-07, 3.5669e-07,\n 4.0284e-07, 1.6817e-06, 7.6551e-07, 1.0855e-06, 9.5585e-07, 9.2064e-07,\n 5.4588e-07, 9.0437e-07, 2.1269e-06, 7.9048e-07, 1.1895e-06, 5.1186e-07,\n 4.4029e-07, 7.3791e-07, 6.4911e-07, 5.6475e-07, 1.4060e-06, 2.0837e-06,\n 3.7235e-07, 1.1758e-06, 5.7825e-07, 6.8747e-07, 7.5802e-07, 8.5788e-07,\n 5.0535e-07, 4.1849e-07, 1.9820e-06, 3.6082e-06, 8.3562e-07, 6.7658e-07,\n 9.9872e-07, 6.9459e-07, 7.8494e-07, 7.9554e-07, 5.9298e-07, 3.7506e-07,\n 2.6077e-06, 5.6208e-07, 1.3906e-06, 4.1648e-06])}, 96: {'step': 7160, 'exp_avg': tensor([[[[ 3.3544e-06, -3.6348e-06, 2.0555e-06],\n [ 7.5713e-06, -4.5477e-08, -6.9160e-07],\n [ 8.1426e-06, -2.1756e-07, -2.2973e-06]],\n\n [[-1.0781e-05, -9.6735e-06, -1.1476e-06],\n [-9.2424e-06, -8.6437e-07, 1.8943e-06],\n [-2.3510e-06, -5.1690e-07, 5.3535e-06]],\n\n [[-2.5438e-05, -1.9745e-05, -2.0244e-05],\n [-7.8005e-06, 6.9756e-06, 3.0267e-06],\n [-1.0593e-05, -2.5425e-05, -9.5857e-06]],\n\n ...,\n\n [[-8.9695e-06, -6.2657e-06, -5.3696e-06],\n [-1.1634e-05, -1.7266e-05, -1.6815e-05],\n [-1.9258e-05, 3.1715e-06, -8.8378e-06]],\n\n [[-1.0974e-05, -5.0171e-06, -1.5574e-05],\n [-4.0599e-06, -5.6855e-06, -3.6030e-06],\n [-1.0916e-05, -1.4812e-05, -2.3560e-05]],\n\n [[-2.5292e-05, -5.8550e-06, -6.8327e-06],\n [-3.6821e-05, -4.9511e-06, -2.0152e-06],\n [-3.2360e-05, -1.6336e-05, -8.8391e-06]]],\n\n\n [[[-4.0754e-07, -5.0291e-06, -1.4288e-05],\n [ 9.9941e-07, -1.5140e-06, -8.5717e-06],\n [-1.5360e-06, -4.4407e-06, -1.4666e-06]],\n\n [[ 3.6782e-06, -5.8758e-06, 1.5525e-06],\n [-3.3728e-05, 9.5180e-08, 1.9619e-06],\n [-1.1573e-05, 5.6686e-06, -2.2060e-06]],\n\n [[-9.7959e-06, 4.9211e-06, -3.7605e-06],\n [-2.7873e-06, -1.1528e-07, 7.9184e-06],\n [-5.5777e-06, -1.7820e-05, -1.0935e-05]],\n\n ...,\n\n [[-1.1228e-05, -6.4398e-06, -7.9894e-06],\n [-1.2189e-05, -7.7668e-06, -3.8924e-07],\n [-1.8692e-05, -7.3746e-06, -8.8970e-06]],\n\n [[-8.8633e-06, -3.1459e-06, -1.6442e-05],\n [-6.6781e-06, -1.0662e-05, -9.3916e-06],\n [ 4.4027e-06, -1.8613e-06, -1.7548e-05]],\n\n [[-1.9088e-05, -1.0770e-05, -2.1029e-05],\n [-1.9780e-05, -2.4335e-05, 1.2629e-06],\n [-1.4624e-05, 7.4956e-06, -7.6042e-06]]],\n\n\n [[[-6.4033e-06, -1.9143e-07, -1.1518e-06],\n [ 1.4945e-06, -3.1026e-06, 4.9556e-06],\n [-2.7694e-06, -2.7130e-06, 2.4448e-07]],\n\n [[ 5.7121e-07, 1.0595e-07, 1.7706e-06],\n [ 1.3778e-05, 2.5952e-05, -1.8750e-06],\n [-2.8172e-06, -3.9810e-06, 2.6352e-06]],\n\n [[-1.7619e-05, -9.6797e-06, -1.0747e-05],\n [ 1.1869e-06, 6.4392e-06, 1.0324e-05],\n [-3.4315e-07, 4.7719e-06, 8.5017e-06]],\n\n ...,\n\n [[ 8.7813e-06, 8.7099e-07, -2.0121e-07],\n [-3.5267e-06, -2.9359e-06, 1.5890e-06],\n [-1.1356e-05, -4.4335e-06, -8.2232e-06]],\n\n [[-6.9885e-06, 8.0470e-07, -4.5704e-06],\n [-1.0508e-05, 6.4963e-06, 1.0148e-05],\n [-3.5196e-06, -5.8962e-06, -7.0093e-06]],\n\n [[-1.6380e-05, -9.7130e-06, 1.3024e-05],\n [-2.1152e-05, 1.0272e-05, 2.2347e-05],\n [-1.3872e-05, -9.5926e-06, -7.4535e-06]]],\n\n\n ...,\n\n\n [[[ 5.1579e-06, 7.0161e-06, 7.3916e-07],\n [ 1.5428e-06, 1.0973e-05, 9.2120e-06],\n [-4.6046e-06, 3.7054e-07, 4.5410e-06]],\n\n [[ 8.0208e-06, -1.0196e-05, 2.2545e-06],\n [ 6.2849e-06, -8.8253e-06, -6.1080e-06],\n [ 3.3479e-06, -1.6730e-05, 8.0938e-07]],\n\n [[-5.5849e-06, -4.7938e-06, -4.1933e-06],\n [-4.2661e-06, -1.1625e-05, -9.2494e-06],\n [ 1.6796e-05, 3.9846e-07, -1.8028e-05]],\n\n ...,\n\n [[ 2.6981e-06, 2.9303e-06, -4.8897e-06],\n [ 7.1653e-06, 6.2831e-06, 1.0333e-06],\n [ 4.3576e-06, 1.8172e-06, -2.6794e-06]],\n\n [[-9.2875e-06, -1.1095e-06, -1.0944e-06],\n [-5.5978e-06, 6.5829e-06, 7.2878e-06],\n [-2.1202e-05, -1.8909e-05, -1.1846e-05]],\n\n [[-5.4432e-06, -7.0062e-06, -4.3341e-06],\n [ 1.6654e-05, -1.7358e-05, 2.0649e-05],\n [ 3.2802e-05, 2.6003e-06, 1.2949e-05]]],\n\n\n [[[-1.4446e-06, -3.1635e-06, -1.3747e-06],\n [-2.1044e-07, -4.2794e-06, 3.5742e-07],\n [ 2.5250e-06, -1.7431e-06, -7.9329e-08]],\n\n [[-5.9108e-06, 2.7821e-06, -2.3198e-06],\n [-5.5245e-06, -5.3263e-07, -7.0358e-06],\n [-6.0976e-06, 9.4617e-07, -1.1404e-05]],\n\n [[ 8.5330e-06, 3.7194e-06, 3.1214e-06],\n [ 1.1189e-05, 9.2021e-06, -1.2153e-05],\n [-6.6502e-06, 5.5273e-06, -6.0589e-06]],\n\n ...,\n\n [[ 7.1097e-06, -4.6868e-06, -2.5676e-06],\n [ 5.8543e-07, -2.0499e-07, 6.1491e-06],\n [ 7.0091e-06, 8.5338e-07, -6.5494e-06]],\n\n [[ 1.1918e-05, -3.7945e-06, 1.1605e-06],\n [ 4.3185e-06, 1.0828e-05, 4.7019e-07],\n [ 1.1304e-05, 8.0852e-07, -3.0013e-06]],\n\n [[ 1.0005e-05, -2.9752e-06, -1.3750e-05],\n [-2.4547e-06, 1.0089e-05, -1.2625e-05],\n [-2.5899e-06, 1.0294e-05, 1.7987e-05]]],\n\n\n [[[ 3.7724e-06, 3.5812e-06, -3.5373e-06],\n [ 3.5998e-06, 5.9539e-06, 8.2008e-06],\n [ 3.0039e-06, 3.8698e-06, 8.5243e-06]],\n\n [[ 5.5872e-06, 1.4309e-05, 6.0145e-06],\n [ 8.4437e-06, 1.2938e-05, 1.3004e-05],\n [ 2.0497e-06, 1.5997e-06, 2.6793e-06]],\n\n [[ 1.2404e-05, 6.1049e-06, -2.3413e-07],\n [ 1.5756e-05, 1.3911e-05, 7.0806e-06],\n [ 6.3409e-06, 4.8824e-06, -2.2060e-06]],\n\n ...,\n\n [[ 1.2401e-05, 1.0228e-06, -2.2479e-06],\n [ 2.0440e-05, 9.9632e-06, 5.6175e-06],\n [ 1.0881e-05, 1.0076e-05, 5.4053e-06]],\n\n [[ 5.1282e-06, 2.2612e-06, 6.9004e-07],\n [ 8.7887e-06, 4.2373e-06, 1.3145e-06],\n [ 2.0993e-05, 1.3638e-05, 7.3967e-06]],\n\n [[-6.3029e-06, -1.3953e-05, -7.0266e-06],\n [-8.8394e-06, -1.4769e-05, -1.4190e-05],\n [-7.1600e-06, -3.7576e-06, -1.2093e-05]]]]), 'exp_avg_sq': tensor([[[[2.1035e-08, 2.4891e-08, 1.5645e-08],\n [2.0103e-08, 3.0076e-08, 1.3438e-08],\n [1.5760e-08, 1.7657e-08, 1.0892e-08]],\n\n [[9.1789e-09, 7.0510e-09, 5.6906e-09],\n [1.7444e-08, 5.3800e-09, 6.8792e-09],\n [1.6261e-08, 7.2674e-09, 6.0561e-09]],\n\n [[3.6244e-08, 4.1067e-08, 4.5643e-08],\n [5.7738e-08, 4.8574e-08, 4.3784e-08],\n [8.4700e-08, 9.6730e-08, 9.4703e-08]],\n\n ...,\n\n [[4.8155e-08, 4.7950e-08, 2.7110e-08],\n [3.4815e-08, 5.7643e-08, 3.0652e-08],\n [5.1265e-08, 5.9580e-08, 5.2789e-08]],\n\n [[4.8083e-08, 5.7089e-08, 3.6871e-08],\n [7.5126e-08, 6.2418e-08, 4.7297e-08],\n [4.0366e-08, 4.1142e-08, 6.4663e-08]],\n\n [[7.8245e-08, 6.4832e-08, 2.3877e-08],\n [1.1434e-07, 7.2813e-08, 1.8883e-08],\n [5.5506e-08, 4.0327e-08, 3.1924e-08]]],\n\n\n [[[7.3358e-09, 6.1923e-09, 8.0162e-09],\n [7.8971e-09, 1.6942e-08, 9.5708e-09],\n [1.0456e-08, 7.5920e-09, 6.0803e-09]],\n\n [[3.7246e-09, 5.4665e-09, 3.9831e-09],\n [5.3861e-09, 4.0921e-09, 3.8531e-09],\n [3.8793e-09, 2.5098e-09, 2.9847e-09]],\n\n [[3.3755e-08, 2.6038e-08, 2.1988e-08],\n [2.8977e-08, 2.7792e-08, 2.6006e-08],\n [4.4968e-08, 5.0590e-08, 4.4860e-08]],\n\n ...,\n\n [[1.0858e-08, 1.1807e-08, 1.1331e-08],\n [1.2403e-08, 1.3174e-08, 1.3254e-08],\n [1.4121e-08, 1.6796e-08, 1.5002e-08]],\n\n [[2.3209e-08, 1.8166e-08, 1.7787e-08],\n [2.1812e-08, 2.3764e-08, 1.8490e-08],\n [1.9859e-08, 2.2123e-08, 1.9851e-08]],\n\n [[3.8537e-08, 1.5946e-08, 1.2720e-08],\n [2.7964e-08, 1.3784e-08, 9.3897e-09],\n [2.0272e-08, 8.5578e-09, 9.6502e-09]]],\n\n\n [[[6.1411e-09, 5.7204e-09, 9.1647e-09],\n [8.5177e-09, 6.7252e-09, 5.5821e-09],\n [5.5152e-09, 4.3753e-09, 5.5877e-09]],\n\n [[3.1931e-09, 9.3822e-09, 9.2604e-10],\n [6.9215e-09, 5.5402e-09, 1.1155e-09],\n [5.9131e-09, 4.0104e-09, 2.7378e-09]],\n\n [[1.2332e-08, 1.4447e-08, 1.7062e-08],\n [2.5169e-08, 1.6377e-08, 1.7953e-08],\n [1.3457e-08, 2.3810e-08, 1.4906e-08]],\n\n ...,\n\n [[1.5233e-08, 1.7340e-08, 8.2198e-09],\n [1.4616e-08, 1.7029e-08, 2.0166e-08],\n [1.1107e-08, 2.4168e-08, 2.0450e-08]],\n\n [[1.0576e-08, 1.5390e-08, 1.0880e-08],\n [1.1228e-08, 1.0622e-08, 1.0204e-08],\n [1.1737e-08, 1.7141e-08, 1.8740e-08]],\n\n [[1.9898e-08, 1.5762e-08, 1.1420e-08],\n [2.9695e-08, 2.1239e-08, 1.3308e-08],\n [1.6564e-08, 1.2905e-08, 9.9955e-09]]],\n\n\n ...,\n\n\n [[[1.3103e-08, 8.6309e-09, 8.2816e-09],\n [1.6030e-08, 1.1057e-08, 5.1579e-09],\n [1.9057e-08, 9.3674e-09, 7.8258e-09]],\n\n [[5.8551e-09, 1.9139e-08, 5.3496e-09],\n [9.9362e-09, 1.1537e-08, 6.0542e-09],\n [7.0221e-09, 5.8359e-09, 5.0378e-09]],\n\n [[2.6996e-08, 1.9367e-08, 2.0047e-08],\n [2.8301e-08, 2.3624e-08, 2.9435e-08],\n [3.6805e-08, 4.2652e-08, 2.7744e-08]],\n\n ...,\n\n [[2.9222e-08, 2.0294e-08, 1.1275e-08],\n [3.0866e-08, 1.6569e-08, 1.1535e-08],\n [1.9706e-08, 1.7097e-08, 1.7820e-08]],\n\n [[3.0356e-08, 2.4168e-08, 2.2513e-08],\n [2.6814e-08, 2.7530e-08, 2.5723e-08],\n [2.9280e-08, 2.4891e-08, 2.7650e-08]],\n\n [[2.2438e-08, 2.6043e-08, 3.0457e-08],\n [2.0552e-08, 2.5420e-08, 2.8461e-08],\n [2.9998e-08, 2.7109e-08, 2.1651e-08]]],\n\n\n [[[1.1294e-08, 9.8943e-09, 6.9844e-09],\n [2.4178e-08, 1.3266e-08, 1.4113e-08],\n [7.9410e-09, 6.8685e-09, 1.7391e-08]],\n\n [[1.9418e-09, 2.6370e-09, 3.3535e-09],\n [2.0614e-09, 3.7173e-09, 9.6135e-09],\n [1.7532e-09, 1.6238e-09, 3.4064e-09]],\n\n [[1.5080e-08, 1.9214e-08, 1.4330e-08],\n [2.6986e-08, 2.2628e-08, 1.7505e-08],\n [2.4280e-08, 2.3148e-08, 1.5483e-08]],\n\n ...,\n\n [[1.2362e-08, 2.0427e-08, 1.4509e-08],\n [1.4815e-08, 2.2830e-08, 1.3923e-08],\n [1.3498e-08, 1.2535e-08, 1.5756e-08]],\n\n [[1.2476e-08, 1.1549e-08, 1.0231e-08],\n [9.5076e-09, 1.2620e-08, 9.7120e-09],\n [1.0263e-08, 1.4283e-08, 1.5234e-08]],\n\n [[1.4715e-08, 1.3527e-08, 2.6565e-08],\n [1.4602e-08, 1.9063e-08, 1.3547e-08],\n [1.3308e-08, 1.2839e-08, 1.7309e-08]]],\n\n\n [[[6.8042e-09, 3.4059e-09, 5.8022e-09],\n [6.3953e-09, 5.2702e-09, 6.5602e-09],\n [7.3641e-09, 9.2339e-09, 6.3854e-09]],\n\n [[8.6453e-10, 2.0291e-09, 2.6056e-09],\n [9.0418e-10, 3.2205e-09, 3.5227e-09],\n [1.1945e-09, 1.2837e-09, 1.8294e-09]],\n\n [[1.0511e-08, 1.0283e-08, 1.0527e-08],\n [7.7789e-09, 1.0410e-08, 9.2227e-09],\n [1.2142e-08, 1.2753e-08, 8.5565e-09]],\n\n ...,\n\n [[7.2359e-09, 1.0576e-08, 4.7656e-09],\n [1.3397e-08, 1.5323e-08, 4.5623e-09],\n [7.3306e-09, 5.0915e-09, 5.4931e-09]],\n\n [[9.4289e-09, 8.5734e-09, 9.5749e-09],\n [7.5913e-09, 1.0894e-08, 7.6889e-09],\n [8.2827e-09, 9.4409e-09, 9.3917e-09]],\n\n [[1.1531e-08, 9.1095e-09, 6.3468e-09],\n [1.2735e-08, 7.0044e-09, 8.5278e-09],\n [8.9386e-09, 5.8837e-09, 6.8048e-09]]]])}, 97: {'step': 7160, 'exp_avg': tensor([-1.3203e-04, 3.6923e-05, -8.1420e-05, 1.1570e-05, -1.4190e-04,\n -1.0546e-05, -7.0329e-05, 3.3561e-05, -1.7354e-04, -5.9558e-05,\n 5.1511e-05, 1.5805e-04, -1.6352e-06, 6.4643e-05, 5.8615e-05,\n 1.3664e-04, 7.9209e-05, 6.1068e-05, 1.0823e-04, -3.7582e-05,\n -1.6638e-04, -5.9047e-07, 7.9796e-05, 5.0944e-04, 9.4245e-05,\n 9.6492e-05, -6.1410e-06, -1.3899e-04, 2.4240e-04, 1.5599e-04,\n 2.5467e-05, -4.5337e-05, 3.1357e-05, -3.0620e-05, -4.3112e-05,\n -8.8330e-05, 1.1417e-05, 2.7688e-06, 1.0115e-04, -7.5499e-05,\n 6.7818e-05, 1.5134e-05, -5.0267e-05, -2.2446e-05, -7.0505e-05,\n -6.8476e-05, 5.9311e-05, -9.3986e-05, 1.3515e-04, 1.4127e-04,\n 1.4846e-05, 6.3302e-05, -4.6869e-05, -2.4090e-05, -7.2375e-05,\n -1.5174e-05, -2.2813e-05, 6.6873e-06, -3.6508e-05, 3.7831e-05,\n 8.6952e-06, -3.3102e-05, 1.6620e-05, 2.3491e-04, -4.0086e-05,\n -2.6605e-05, 4.9624e-05, -9.4493e-05, -4.9620e-05, 3.1752e-05,\n 1.9682e-05, -4.8851e-07, 9.1990e-05, -1.8600e-04, 1.9873e-05,\n 3.1680e-05, -2.9047e-05, 5.7166e-04, 2.2606e-05, -6.4578e-06,\n 6.0551e-05, 9.5916e-06, 1.0980e-04, -6.6599e-05, 6.4538e-05,\n -2.3255e-04, 2.8839e-05, 7.3491e-05, -5.2506e-05, -2.7692e-05,\n 6.0902e-05, -1.7309e-04, -1.5186e-05, -4.1108e-05, -3.3731e-05,\n -5.1498e-05, -7.9428e-05, -5.4106e-05, 1.2934e-04, 7.6173e-06,\n 1.0175e-04, -1.2440e-04, -9.4409e-05, -2.1790e-04, 2.4080e-04,\n 2.0989e-05, 5.4759e-05, -5.4776e-05, 4.1517e-05, -5.7084e-05,\n 2.0943e-06, 6.0870e-05, 3.7966e-06, -8.4878e-05, 8.4791e-05,\n -1.4479e-04, -1.9114e-05, 3.2149e-05, -5.8059e-05, -1.5455e-05,\n -7.8895e-05, -3.4201e-05, -1.2182e-04, 1.2354e-04, 5.0354e-05,\n 1.5013e-05, -9.2480e-06, 8.8932e-05, -1.7297e-04, -2.2566e-05,\n -6.4194e-05, 1.0812e-04, 7.5560e-05, -1.4638e-05, 3.3944e-05,\n 2.2363e-05, -1.7997e-04, 1.7011e-05, 6.5224e-05, 4.5783e-05,\n -1.5147e-05, -1.2505e-04, 2.2120e-05, -9.8396e-05, -4.4449e-05,\n 1.5753e-04, 5.6212e-05, -8.5820e-06, 3.9204e-05, 7.8760e-05,\n 2.1483e-04, -1.1205e-04, 7.6821e-05, -1.2685e-04, 3.5276e-06,\n 1.2300e-05, 2.3103e-05, 1.9471e-04, -2.9417e-05, 3.3178e-05,\n 6.2241e-05, -2.5059e-04, -1.0130e-04, -1.8289e-05, -4.7022e-05,\n -1.1730e-06, -1.1544e-04, 1.4063e-06, 8.9352e-07, -1.2890e-05,\n -4.4419e-05, 4.8193e-05, 4.8200e-05, -1.7078e-04, 2.3386e-05,\n 5.4941e-05, -1.8977e-05, 2.1113e-05, -2.3506e-04, -8.2020e-06,\n 7.2025e-05, -5.6568e-05, -3.9204e-05, -1.5192e-05, 4.0054e-05,\n -1.7462e-06, -1.2991e-04, -2.2125e-05, 5.0770e-05, -7.9673e-05,\n -2.9930e-05, -2.3419e-04, -1.4573e-05, 1.2911e-05, -8.1528e-05,\n 8.5081e-05, -5.6621e-05, 1.7551e-04, 7.9447e-06, 5.7497e-05,\n 1.1508e-04, -1.5169e-04, 9.4651e-05, 6.3053e-05, -1.2274e-04,\n 1.1785e-04, -1.3755e-04, 3.0508e-05, -8.9898e-05, -1.4991e-04,\n 3.6046e-04, 7.9489e-06, -4.6180e-05, -1.8064e-04, -7.3362e-05,\n -1.0048e-04, 2.3217e-05, -5.4212e-04, -5.3578e-05, 4.4314e-05,\n -1.5710e-04, -7.6181e-05, 1.2317e-04, -7.5033e-05, 8.2184e-05,\n 1.5804e-05, -2.0500e-05, 7.4902e-05, 5.5578e-06, 8.8357e-05,\n -1.1640e-05, 3.5010e-05, -3.8570e-05, -1.2510e-05, -1.6541e-05,\n -1.4105e-05, 7.0340e-05, -3.7764e-05, 1.0865e-05, -4.1389e-05,\n 4.4725e-05, -2.5480e-06, -3.8684e-05, -2.6938e-05, -6.3169e-05,\n 1.0462e-05, 9.7550e-05, 6.2315e-05, 5.7667e-05, -5.8128e-05,\n -8.8441e-05, 2.7105e-05, 9.9509e-05, 1.5070e-04, 3.8058e-05,\n -1.2457e-04]), 'exp_avg_sq': tensor([1.0639e-05, 1.7420e-06, 1.6544e-06, 5.0283e-07, 1.4061e-06, 4.4783e-06,\n 2.0535e-06, 6.9696e-07, 9.1955e-07, 6.5093e-07, 9.0261e-07, 1.4209e-06,\n 8.5928e-07, 6.7807e-07, 1.4162e-06, 1.2005e-06, 9.7986e-07, 1.2496e-06,\n 2.1803e-06, 7.8665e-07, 1.6537e-06, 9.4448e-07, 1.4729e-06, 4.0974e-06,\n 1.1020e-06, 8.7144e-07, 1.1651e-06, 2.0204e-06, 1.9766e-06, 1.3604e-06,\n 8.1349e-07, 1.2146e-06, 1.4568e-06, 4.6766e-07, 1.1153e-06, 3.3919e-06,\n 1.4283e-06, 1.3117e-06, 1.9840e-06, 9.4314e-07, 1.4734e-06, 1.3410e-06,\n 1.2154e-06, 1.9827e-06, 8.9519e-07, 1.8154e-06, 9.6942e-07, 1.0252e-06,\n 4.1823e-06, 8.2081e-07, 1.6709e-06, 8.3663e-07, 9.6383e-07, 5.9632e-07,\n 1.3003e-06, 1.6469e-06, 6.8379e-07, 1.0703e-06, 2.2559e-06, 1.3370e-06,\n 3.2079e-06, 8.1899e-07, 1.4891e-06, 1.9241e-06, 2.7120e-06, 1.3476e-06,\n 1.3312e-06, 9.3222e-07, 1.0927e-06, 7.3852e-07, 6.8099e-07, 8.3488e-07,\n 6.7762e-07, 1.2922e-06, 9.2938e-07, 2.3189e-06, 2.0710e-06, 1.9926e-05,\n 1.6041e-06, 2.0544e-06, 2.1660e-06, 1.1003e-06, 1.6131e-06, 1.5000e-06,\n 7.4618e-07, 6.2406e-06, 5.9511e-07, 8.2628e-07, 3.9069e-06, 7.8021e-07,\n 1.3735e-06, 1.3331e-06, 3.0704e-06, 1.5259e-06, 2.0628e-06, 5.4650e-07,\n 1.3921e-06, 1.9754e-06, 1.7231e-06, 1.3838e-06, 1.2299e-06, 7.8892e-07,\n 1.1679e-06, 2.5244e-06, 3.0825e-06, 2.1586e-06, 1.2862e-06, 2.2644e-06,\n 6.9072e-07, 7.8870e-07, 1.2876e-06, 1.1809e-06, 6.7417e-07, 1.3146e-06,\n 9.3526e-06, 5.1256e-06, 1.7179e-06, 4.6161e-07, 1.1627e-06, 6.0896e-07,\n 4.4478e-07, 2.2652e-06, 3.3800e-06, 7.2808e-07, 3.9827e-07, 1.4499e-06,\n 8.1585e-07, 1.7220e-06, 3.1843e-06, 8.7213e-07, 1.0271e-06, 1.4719e-06,\n 5.1049e-07, 1.3935e-06, 1.7737e-06, 3.2079e-06, 1.3794e-06, 7.8373e-06,\n 1.1491e-06, 1.3428e-06, 6.8518e-07, 1.3196e-06, 1.0030e-06, 2.0495e-06,\n 2.5162e-06, 7.8039e-07, 9.0035e-07, 1.8746e-06, 1.3181e-06, 1.2966e-06,\n 1.8228e-06, 2.1611e-06, 6.7418e-07, 8.1567e-07, 7.2765e-07, 3.7481e-07,\n 6.4902e-07, 9.5776e-07, 1.9691e-06, 1.0292e-06, 1.8998e-06, 1.5066e-06,\n 7.4062e-07, 8.9266e-07, 9.1346e-07, 6.0358e-07, 3.3565e-06, 1.1285e-06,\n 5.7529e-07, 1.3226e-06, 8.8627e-07, 1.6990e-06, 1.2436e-06, 2.8907e-06,\n 1.3110e-06, 8.2774e-07, 1.7268e-06, 1.8974e-06, 1.8279e-06, 1.0059e-06,\n 8.1723e-07, 1.3491e-06, 1.1466e-06, 9.3979e-07, 2.1252e-06, 1.0377e-06,\n 1.1921e-06, 1.1411e-06, 4.2515e-06, 9.3478e-07, 1.5660e-06, 2.7926e-06,\n 3.7588e-07, 6.5967e-07, 8.4137e-07, 2.6103e-06, 8.5872e-07, 1.5969e-06,\n 6.9514e-07, 1.2285e-06, 1.5249e-06, 9.8828e-07, 1.2759e-06, 8.9517e-07,\n 1.9835e-06, 3.0224e-06, 1.3292e-06, 7.5005e-07, 1.0881e-06, 1.5388e-06,\n 6.3795e-06, 4.8082e-07, 1.0984e-06, 2.8552e-06, 6.5481e-07, 1.4480e-06,\n 1.1921e-06, 1.4495e-05, 1.4157e-06, 1.0404e-06, 1.0135e-06, 9.0466e-07,\n 1.6234e-06, 2.2802e-06, 1.1641e-06, 6.2552e-07, 4.2433e-06, 1.6285e-06,\n 1.5032e-06, 1.5646e-06, 1.9396e-06, 1.3647e-06, 7.1005e-07, 1.7088e-06,\n 2.0348e-06, 1.0378e-06, 2.0046e-06, 5.4358e-06, 1.2073e-06, 8.1200e-07,\n 1.2203e-06, 2.4022e-06, 1.3018e-06, 5.9149e-07, 7.5462e-07, 1.0403e-06,\n 1.5104e-06, 9.0598e-07, 2.1667e-06, 6.5761e-07, 1.2404e-06, 2.2948e-06,\n 2.5448e-06, 3.0763e-06, 9.2574e-07, 9.9867e-07])}, 98: {'step': 7160, 'exp_avg': tensor([-1.5927e-05, 6.5648e-05, -2.0621e-05, 2.1040e-05, -7.6262e-05,\n -2.9673e-05, 1.0952e-05, 1.8641e-05, -1.1396e-04, -3.9302e-05,\n 5.9471e-06, 1.2789e-04, -3.0922e-05, 6.0821e-05, 2.4162e-05,\n 1.0028e-04, 5.7496e-05, 1.3208e-05, 1.0414e-04, -3.4774e-05,\n -9.1584e-05, -1.5833e-06, -8.2405e-06, -1.7376e-05, 1.6056e-05,\n 1.0531e-04, -2.1925e-05, 1.4469e-05, 8.0347e-05, 1.1841e-04,\n -2.7118e-05, -4.4762e-05, 1.5692e-05, -4.2322e-05, -2.0981e-05,\n -9.1781e-05, -5.0009e-05, 4.1457e-05, -4.7802e-05, -3.4121e-05,\n 3.8254e-05, -1.1377e-05, -2.2815e-05, -4.1172e-05, -4.6044e-05,\n -4.7256e-05, 1.5628e-05, -4.8468e-05, 7.9064e-05, 2.1050e-05,\n -2.7989e-05, 6.1305e-05, -3.8614e-05, 1.7274e-05, -3.8208e-05,\n 9.5928e-05, -1.8860e-05, -2.1783e-05, -6.2474e-05, 5.2692e-05,\n 1.1186e-05, -1.6529e-05, -1.2649e-05, -5.2328e-06, -4.3954e-05,\n 6.8857e-05, 4.5906e-05, -5.2824e-05, -5.7164e-05, 2.6512e-05,\n 2.0762e-05, -1.0265e-05, 8.3058e-05, -6.3735e-05, 2.6184e-05,\n -4.7139e-05, -2.5585e-06, 2.7048e-04, 1.7400e-05, 3.2758e-05,\n 2.3064e-05, 1.3839e-06, 7.2780e-05, -4.5018e-05, 4.3143e-05,\n 2.0301e-05, 8.7773e-06, 5.6160e-05, -5.5320e-05, -6.4462e-06,\n 5.8888e-05, -1.1253e-04, -2.0108e-05, -3.3551e-05, 5.9818e-05,\n -2.3382e-05, -4.0598e-05, -1.3093e-05, 1.1565e-04, 3.8017e-05,\n 6.6187e-05, -4.2266e-05, -8.0746e-05, -1.6734e-04, 8.7423e-05,\n 1.3430e-05, 3.6214e-05, 1.4119e-05, 2.1117e-05, -2.9063e-05,\n -1.1301e-05, 4.8870e-05, 6.2427e-06, -6.4844e-05, 4.5552e-05,\n -9.9984e-06, -2.6693e-05, 2.4469e-05, -7.8004e-05, -2.0757e-05,\n -6.2610e-05, -3.2661e-05, -4.5064e-05, 8.6594e-05, 4.2411e-05,\n -2.4940e-05, -1.5972e-05, 4.7313e-05, -1.5699e-04, 3.2171e-07,\n -5.7399e-05, 3.8542e-05, 5.4566e-05, -6.7168e-06, -1.9169e-05,\n -4.5925e-05, -8.9134e-05, 4.2576e-06, 4.4736e-05, 2.0441e-05,\n -6.3857e-06, -4.0191e-05, 3.6597e-07, 1.1843e-05, -6.1753e-05,\n 1.0241e-04, 4.7131e-05, 5.1237e-05, 9.0589e-06, 4.2925e-05,\n 5.0119e-05, -3.5380e-05, 1.6215e-05, -6.6195e-05, 1.4216e-05,\n -7.2403e-06, -1.9550e-06, 8.4316e-05, 4.0388e-05, -1.0242e-05,\n 3.7448e-05, -1.5886e-04, -8.0086e-05, 1.1577e-05, -2.9691e-05,\n 9.9066e-06, -2.9580e-05, 4.6293e-06, -3.1356e-05, -9.8773e-06,\n -3.2438e-05, 3.3215e-06, 2.6171e-06, -7.6684e-05, 5.2993e-05,\n 3.6218e-05, -5.5614e-05, 6.7206e-05, -1.4812e-04, 6.3284e-05,\n 2.3727e-05, -8.9895e-05, -6.5834e-05, -1.2594e-05, 7.9301e-05,\n 1.4756e-05, -9.6685e-05, -2.3434e-05, 5.7018e-05, -9.5823e-05,\n 1.2826e-05, -7.2710e-05, -1.9547e-05, 6.8708e-05, -1.2428e-04,\n 1.4922e-04, -5.9606e-05, 4.5706e-05, 1.7073e-05, 1.1066e-05,\n 1.0136e-04, -1.0743e-04, 6.2893e-05, 7.9092e-05, -1.6565e-04,\n 9.0580e-05, -1.2567e-04, 5.4596e-05, -7.1144e-05, -2.5481e-05,\n 6.3750e-05, 1.0667e-05, 4.7938e-05, -1.0940e-04, -5.3927e-05,\n -4.4438e-05, 4.9966e-07, -4.0273e-04, -4.7074e-05, 2.1155e-05,\n -9.5727e-05, -3.6985e-05, 4.6958e-05, -3.2596e-06, 5.9844e-05,\n 4.4674e-05, -3.7310e-06, 6.2800e-06, -3.6865e-05, 2.2772e-05,\n 2.1071e-05, -6.5553e-05, -5.7004e-05, -1.1462e-05, -2.0671e-05,\n -1.6778e-06, 6.6723e-05, -4.6513e-05, 1.0793e-04, -5.8857e-05,\n 4.7243e-05, 1.8468e-05, -7.3214e-05, -3.4060e-05, -3.6263e-05,\n 3.8040e-06, 7.2965e-05, 8.6987e-05, 8.1420e-06, -2.1234e-05,\n -5.6081e-05, 5.9040e-05, -8.7457e-05, 9.4923e-05, 3.8854e-05,\n -1.9030e-04]), 'exp_avg_sq': tensor([4.3646e-07, 1.0147e-06, 5.8503e-07, 3.8586e-07, 7.9934e-07, 9.8914e-07,\n 7.8796e-07, 5.7804e-07, 4.9549e-07, 4.8335e-07, 5.9915e-07, 1.0270e-06,\n 4.1298e-07, 4.1611e-07, 4.5052e-07, 8.1240e-07, 4.1754e-07, 8.0478e-07,\n 8.8318e-07, 5.3445e-07, 1.0464e-06, 6.5372e-07, 4.8100e-07, 1.1011e-06,\n 9.1051e-07, 4.5265e-07, 7.1570e-07, 8.1036e-07, 7.2025e-07, 7.4771e-07,\n 4.7959e-07, 9.8265e-07, 5.1078e-07, 2.5416e-07, 7.1552e-07, 1.3537e-06,\n 7.7279e-07, 6.1922e-07, 9.6798e-07, 5.8832e-07, 9.6138e-07, 7.9408e-07,\n 4.8444e-07, 9.3225e-07, 4.0435e-07, 1.1972e-06, 5.4148e-07, 4.6938e-07,\n 1.5847e-06, 7.5131e-07, 8.7573e-07, 3.8351e-07, 6.2893e-07, 4.4096e-07,\n 1.0239e-06, 9.1943e-07, 2.7377e-07, 7.2475e-07, 9.8860e-07, 6.1579e-07,\n 1.4681e-06, 4.9649e-07, 5.7619e-07, 6.8287e-07, 5.1700e-07, 7.6437e-07,\n 8.1230e-07, 5.8621e-07, 4.9518e-07, 4.0224e-07, 3.1298e-07, 5.3409e-07,\n 3.5685e-07, 7.1707e-07, 4.9420e-07, 5.8126e-07, 1.0561e-06, 4.9306e-06,\n 1.2083e-06, 1.1017e-06, 1.0978e-06, 9.3766e-07, 5.7727e-07, 5.2823e-07,\n 3.7177e-07, 2.5082e-06, 6.5128e-07, 3.2775e-07, 9.9537e-07, 3.8897e-07,\n 5.5396e-07, 4.2326e-07, 1.0904e-06, 1.3240e-06, 1.5002e-06, 3.2421e-07,\n 1.1681e-06, 1.3923e-06, 9.6163e-07, 1.2058e-06, 7.6028e-07, 6.4150e-07,\n 9.9215e-07, 1.2128e-06, 1.3402e-06, 1.4004e-06, 5.4017e-07, 1.3531e-06,\n 2.9938e-07, 3.9689e-07, 5.0090e-07, 5.7605e-07, 3.3523e-07, 7.5089e-07,\n 2.5267e-07, 2.6941e-07, 9.5588e-07, 2.4134e-07, 4.1140e-07, 4.1996e-07,\n 3.4128e-07, 7.0844e-07, 5.9332e-07, 3.6577e-07, 2.2045e-07, 5.1942e-07,\n 6.1536e-07, 6.8463e-07, 2.5003e-06, 5.5459e-07, 6.3664e-07, 6.4932e-07,\n 3.3439e-07, 6.0896e-07, 8.7938e-07, 8.9256e-07, 9.7215e-07, 3.5644e-06,\n 9.2555e-07, 5.7350e-07, 4.3841e-07, 5.6775e-07, 8.0526e-07, 5.4751e-07,\n 1.1402e-06, 3.2901e-07, 4.6923e-07, 8.8025e-07, 4.8843e-07, 5.9510e-07,\n 1.2811e-06, 9.3964e-07, 4.3439e-07, 3.9731e-07, 4.4376e-07, 2.3571e-07,\n 3.9800e-07, 4.8028e-07, 1.1957e-06, 5.4327e-07, 8.9637e-07, 8.0264e-07,\n 4.4310e-07, 6.7440e-07, 3.9185e-07, 3.0669e-07, 9.6628e-07, 6.9109e-07,\n 3.7833e-07, 6.7197e-07, 4.5088e-07, 9.2401e-07, 4.1826e-07, 9.7470e-07,\n 8.3095e-07, 6.0353e-07, 2.0750e-06, 9.3310e-07, 1.1900e-06, 6.8147e-07,\n 4.7362e-07, 8.1395e-07, 6.1556e-07, 7.0074e-07, 1.1259e-06, 6.3331e-07,\n 6.1304e-07, 7.2228e-07, 1.1520e-06, 5.3414e-07, 7.5766e-07, 8.8687e-07,\n 2.4943e-07, 4.7477e-07, 6.5902e-07, 1.4074e-06, 3.3518e-07, 8.9824e-07,\n 3.5815e-07, 6.0003e-07, 1.2411e-06, 4.6885e-07, 4.8330e-07, 1.0527e-06,\n 7.9623e-07, 5.3262e-07, 6.8208e-07, 5.0135e-07, 5.9169e-07, 8.4102e-07,\n 2.1011e-07, 3.1094e-07, 8.9535e-07, 8.3892e-07, 4.2499e-07, 7.1098e-07,\n 6.5339e-07, 4.6172e-06, 1.0227e-06, 3.2180e-07, 7.7751e-07, 3.9151e-07,\n 6.4204e-07, 1.0603e-06, 5.9622e-07, 5.8789e-07, 1.3809e-06, 7.7409e-07,\n 7.2698e-07, 7.2964e-07, 7.1642e-07, 7.5418e-07, 6.5305e-07, 7.4167e-07,\n 7.0309e-07, 7.1017e-07, 8.6786e-07, 9.9932e-07, 1.3614e-06, 4.4233e-07,\n 5.6726e-07, 1.1453e-06, 6.5285e-07, 4.5962e-07, 5.1923e-07, 4.5677e-07,\n 9.1784e-07, 5.0045e-07, 1.0403e-06, 4.2131e-07, 1.3875e-06, 1.1158e-06,\n 8.9915e-07, 1.4286e-06, 8.6044e-07, 8.1781e-07])}, 99: {'step': 7160, 'exp_avg': tensor([[[[ 9.6811e-06]],\n\n [[ 2.4398e-05]],\n\n [[ 2.7810e-05]],\n\n ...,\n\n [[ 1.1701e-05]],\n\n [[ 1.5676e-05]],\n\n [[ 4.3635e-07]]],\n\n\n [[[-5.5689e-08]],\n\n [[ 1.0903e-05]],\n\n [[ 2.9924e-06]],\n\n ...,\n\n [[ 4.1214e-06]],\n\n [[ 4.4306e-08]],\n\n [[ 7.9146e-06]]],\n\n\n [[[ 4.1802e-06]],\n\n [[-3.4841e-07]],\n\n [[-6.3472e-06]],\n\n ...,\n\n [[ 1.2550e-05]],\n\n [[-9.8045e-06]],\n\n [[-5.3624e-06]]],\n\n\n ...,\n\n\n [[[ 2.4561e-05]],\n\n [[-7.3943e-07]],\n\n [[ 4.2649e-06]],\n\n ...,\n\n [[-5.4192e-06]],\n\n [[-1.0135e-05]],\n\n [[ 1.6518e-06]]],\n\n\n [[[ 1.0686e-05]],\n\n [[-4.3448e-06]],\n\n [[ 2.2975e-06]],\n\n ...,\n\n [[-1.7262e-06]],\n\n [[-2.6688e-06]],\n\n [[ 5.0696e-06]]],\n\n\n [[[-2.3967e-07]],\n\n [[ 1.0757e-05]],\n\n [[ 3.1329e-06]],\n\n ...,\n\n [[ 1.8998e-06]],\n\n [[-1.1267e-06]],\n\n [[-7.0215e-06]]]]), 'exp_avg_sq': tensor([[[[7.5432e-08]],\n\n [[4.2891e-08]],\n\n [[3.9942e-08]],\n\n ...,\n\n [[5.7878e-08]],\n\n [[2.7538e-08]],\n\n [[3.1079e-08]]],\n\n\n [[[1.7456e-08]],\n\n [[1.1089e-08]],\n\n [[7.1229e-09]],\n\n ...,\n\n [[1.8213e-08]],\n\n [[3.7505e-09]],\n\n [[5.8438e-09]]],\n\n\n [[[2.9958e-08]],\n\n [[8.5870e-09]],\n\n [[6.1662e-09]],\n\n ...,\n\n [[9.9864e-09]],\n\n [[9.2586e-09]],\n\n [[8.9044e-09]]],\n\n\n ...,\n\n\n [[[2.2237e-08]],\n\n [[1.5876e-08]],\n\n [[1.6016e-08]],\n\n ...,\n\n [[2.5611e-08]],\n\n [[1.2125e-08]],\n\n [[1.4461e-08]]],\n\n\n [[[1.0963e-08]],\n\n [[4.7702e-09]],\n\n [[3.3737e-09]],\n\n ...,\n\n [[1.1911e-08]],\n\n [[6.9666e-09]],\n\n [[5.9207e-09]]],\n\n\n [[[8.2121e-08]],\n\n [[1.0289e-07]],\n\n [[3.0452e-08]],\n\n ...,\n\n [[6.2227e-08]],\n\n [[1.4869e-08]],\n\n [[1.1835e-08]]]])}, 100: {'step': 7160, 'exp_avg': tensor([ 4.7256e-05, 3.0624e-05, -2.7949e-05, ..., -2.7695e-06,\n -1.9466e-05, 7.7053e-05]), 'exp_avg_sq': tensor([1.2405e-06, 2.0180e-07, 1.8338e-07, ..., 3.2652e-07, 3.8341e-07,\n 3.7262e-06])}, 101: {'step': 7160, 'exp_avg': tensor([-7.3313e-05, 3.5734e-05, 4.4815e-06, ..., -1.4444e-05,\n 3.8492e-05, 4.3602e-05]), 'exp_avg_sq': tensor([3.8929e-07, 1.0980e-07, 9.3323e-08, ..., 2.0171e-07, 3.5865e-07,\n 2.7844e-06])}, 102: {'step': 7160, 'exp_avg': tensor([[[[ 4.9157e-06]],\n\n [[-9.6778e-06]],\n\n [[-1.1213e-05]],\n\n ...,\n\n [[ 6.1804e-06]],\n\n [[ 3.2308e-06]],\n\n [[-2.4117e-07]]],\n\n\n [[[-2.4973e-05]],\n\n [[ 4.7521e-06]],\n\n [[ 1.7237e-06]],\n\n ...,\n\n [[-1.1616e-05]],\n\n [[-4.8570e-06]],\n\n [[ 2.1946e-06]]],\n\n\n [[[-6.9140e-06]],\n\n [[ 2.7806e-07]],\n\n [[-2.2556e-06]],\n\n ...,\n\n [[-2.3516e-06]],\n\n [[-4.4911e-06]],\n\n [[-4.2041e-06]]],\n\n\n ...,\n\n\n [[[-7.9326e-06]],\n\n [[-4.0895e-06]],\n\n [[ 5.0499e-06]],\n\n ...,\n\n [[-6.1417e-06]],\n\n [[ 6.3740e-06]],\n\n [[ 6.9877e-06]]],\n\n\n [[[-3.6534e-06]],\n\n [[-2.8647e-07]],\n\n [[ 1.4738e-06]],\n\n ...,\n\n [[-1.7579e-06]],\n\n [[-2.4794e-08]],\n\n [[ 3.5236e-06]]],\n\n\n [[[ 1.0015e-05]],\n\n [[ 7.0742e-06]],\n\n [[-8.4801e-08]],\n\n ...,\n\n [[-3.5545e-06]],\n\n [[ 4.0991e-06]],\n\n [[ 1.0112e-06]]]]), 'exp_avg_sq': tensor([[[[3.7031e-08]],\n\n [[5.3391e-09]],\n\n [[2.4395e-08]],\n\n ...,\n\n [[3.8009e-08]],\n\n [[1.3595e-08]],\n\n [[1.0788e-07]]],\n\n\n [[[1.0980e-08]],\n\n [[6.0015e-09]],\n\n [[1.5587e-08]],\n\n ...,\n\n [[2.2174e-08]],\n\n [[4.2640e-09]],\n\n [[2.5191e-08]]],\n\n\n [[[1.7187e-08]],\n\n [[8.2344e-09]],\n\n [[6.9876e-09]],\n\n ...,\n\n [[1.9250e-08]],\n\n [[3.7449e-09]],\n\n [[3.4933e-08]]],\n\n\n ...,\n\n\n [[[1.5672e-08]],\n\n [[6.3031e-09]],\n\n [[1.6753e-08]],\n\n ...,\n\n [[1.5880e-08]],\n\n [[5.7903e-09]],\n\n [[3.1030e-08]]],\n\n\n [[[3.0000e-09]],\n\n [[8.3993e-10]],\n\n [[2.2727e-09]],\n\n ...,\n\n [[3.9426e-09]],\n\n [[8.4774e-10]],\n\n [[4.8986e-09]]],\n\n\n [[[2.6178e-08]],\n\n [[6.5793e-09]],\n\n [[2.0589e-08]],\n\n ...,\n\n [[1.6142e-08]],\n\n [[7.7390e-09]],\n\n [[3.7592e-08]]]])}, 103: {'step': 7160, 'exp_avg': tensor([ 3.8682e-05, -1.1091e-04, -1.0314e-04, 1.1685e-04, -2.7192e-05,\n -4.2815e-05, 1.2645e-04, 7.4050e-05, -3.0868e-05, -8.8897e-05,\n -6.7697e-05, -5.4439e-05, -3.0437e-05, 3.3193e-05, 6.4232e-05,\n 1.6959e-04, -4.3192e-05, -8.8964e-05, -9.6541e-05, -1.5846e-04,\n -1.8510e-04, 1.1081e-04, 8.1650e-05, 5.5362e-05, 4.7629e-06,\n 4.0989e-05, -1.5422e-04, -5.7109e-06, -1.0914e-04, 4.2939e-06,\n -1.1199e-04, -3.7049e-05, -9.6055e-05, -1.0157e-04, 4.7382e-06,\n -1.2776e-04, -1.1186e-05, -4.7368e-05, 6.9093e-07, -1.5900e-05,\n 4.9719e-05, -2.4401e-05, -6.8291e-06, 2.7124e-05, 4.0685e-05,\n -2.7531e-05, -9.2158e-05, -1.8978e-04, 7.2871e-05, -2.2190e-05,\n -3.3661e-05, 1.7161e-05, 1.5760e-04, 4.2779e-05, 2.0640e-05,\n 5.4743e-05, 4.7471e-05, -1.4585e-04, -1.1808e-04, -2.2810e-05,\n -3.6724e-05, -6.9201e-06, 2.8827e-05, -8.8753e-05, -9.7134e-05,\n 2.4377e-05, 8.2305e-05, 1.4771e-04, -1.1283e-04, 1.7068e-04,\n -2.0298e-04, 1.2903e-04, 1.0767e-04, -8.3690e-05, 3.6773e-05,\n -3.8110e-05, -1.1404e-05, 6.1634e-05, 1.2723e-04, -1.1629e-04,\n 6.0547e-05, 2.3180e-05, 1.1223e-04, 8.4147e-05, -1.1154e-04,\n 2.0814e-04, 1.2804e-05, -1.0057e-04, 8.2616e-05, 1.4185e-04,\n -1.3286e-05, -1.9634e-05, 1.3368e-04, 8.8375e-05, 2.1973e-05,\n 1.2904e-04, -3.0928e-05, -8.6575e-06, 4.1249e-05, -1.9138e-04,\n -1.0425e-04, 2.9604e-05, 1.1254e-04, 4.3066e-05, -3.7452e-05,\n 6.0858e-05, -7.0425e-06, -1.1351e-04, 1.1946e-04, 6.1210e-06,\n 3.8785e-05, -5.2061e-06, 1.1728e-04, -4.6566e-05, 8.5392e-05,\n 4.6690e-05, -1.6580e-06, -3.3821e-05, 1.0587e-04, -7.7588e-06,\n -6.1607e-05, 4.6234e-05, -4.9885e-05, -1.5315e-04, 1.3918e-05,\n 1.0495e-04, 4.8287e-05, 6.9867e-06, 9.3471e-06, -1.1054e-04,\n -1.4380e-05, -5.3184e-05, -7.9865e-05, 3.3310e-05, -4.5902e-06,\n 9.8107e-05, 1.0007e-04, -4.2178e-05, -6.8229e-05, 4.3592e-05,\n -3.9930e-05, 9.4459e-05, 4.9147e-05, -2.3150e-05, 3.2945e-05,\n -2.1431e-05, -5.8051e-06, 1.0824e-04, -3.0515e-06, 6.6095e-05,\n 1.3426e-06, 3.1734e-05, 8.4001e-05, 1.6764e-05, 9.3103e-05,\n 3.3315e-05, 8.2267e-06, -1.3952e-05, -3.6462e-07, 6.5847e-05,\n -7.6810e-05, 7.3500e-06, 2.2997e-04, -1.0526e-04, -1.8185e-04,\n 2.9786e-05, -6.2298e-05, -2.7663e-05, -1.3660e-04, 7.6122e-05,\n 7.3025e-05, -4.7658e-06, -6.6682e-05, 1.0687e-05, 2.0192e-05,\n 6.1268e-05, 1.4388e-05, 1.1346e-05, -3.8350e-05, 7.4938e-05,\n 6.1524e-05, 3.1311e-05, -8.9359e-05, 5.8013e-05, 4.2789e-05,\n 8.1418e-05, 6.1074e-05, 3.1640e-06, 3.1486e-05, -1.3365e-04,\n 1.8786e-05, -5.9850e-06, -6.8492e-05, -1.9585e-06, 2.5250e-05,\n -2.2819e-04, 7.7826e-05, 9.1781e-05, 5.4324e-05, 5.7984e-05,\n -7.2280e-05, -2.9268e-05, 9.9172e-05, -1.0699e-05, 4.9237e-06,\n -1.3012e-04, -7.1043e-06, -6.3831e-05, 1.3364e-04, -1.0493e-04,\n -2.1116e-05, -3.0418e-05, -6.2494e-05, -8.6775e-06, -1.8151e-05,\n -9.9851e-05, 3.7533e-05, -6.5974e-05, -6.3933e-05, -4.7032e-05,\n 2.7313e-05, 4.7022e-05, 1.5481e-05, -7.0851e-05, -2.7995e-05,\n -1.0659e-04, -5.5247e-05, 2.2516e-05, -7.0573e-05, -2.6911e-05,\n 1.0066e-04, -2.1286e-06, 4.0336e-05, -1.4066e-04, -5.6337e-05,\n 1.2358e-04, 6.2046e-05, 2.4299e-04, -6.7579e-06, -1.0091e-04,\n 1.0365e-04, 7.7209e-05, -5.9096e-06, -2.5016e-05, -5.8135e-05,\n -6.3045e-05, 4.8658e-05, -8.2282e-05, -7.1519e-05, -8.3938e-05,\n 8.0937e-05, -2.5444e-05, -9.9743e-05, -1.4703e-04, -2.5321e-06,\n -1.0269e-04]), 'exp_avg_sq': tensor([1.6011e-06, 1.3077e-06, 1.6056e-06, 1.6220e-06, 4.5234e-07, 1.1228e-06,\n 1.7819e-06, 5.7277e-07, 4.5694e-07, 2.9481e-06, 9.8238e-07, 9.8964e-07,\n 1.0808e-06, 7.5114e-07, 4.9857e-07, 1.4019e-06, 1.3409e-06, 9.4608e-07,\n 2.4534e-06, 3.7468e-06, 2.5942e-06, 3.1085e-06, 8.8078e-07, 7.2568e-07,\n 4.8750e-07, 9.5837e-07, 2.6204e-06, 9.1174e-07, 1.3742e-06, 2.5228e-07,\n 1.0917e-06, 6.8254e-07, 9.9805e-07, 1.1042e-06, 5.0572e-07, 2.8133e-06,\n 8.4305e-07, 1.0376e-06, 1.5067e-06, 7.0645e-07, 9.8416e-07, 3.7548e-06,\n 2.9497e-06, 7.1591e-07, 6.0639e-06, 1.5596e-06, 1.6381e-06, 9.4925e-07,\n 2.2492e-06, 8.2199e-07, 1.1427e-06, 1.2042e-06, 1.7648e-06, 1.9662e-06,\n 9.3770e-07, 1.4268e-06, 5.1991e-07, 8.4687e-07, 1.0573e-06, 6.0433e-07,\n 1.0897e-06, 8.4358e-07, 1.0296e-06, 6.2880e-06, 1.2216e-06, 8.6137e-07,\n 2.3595e-06, 1.0335e-06, 2.8680e-06, 9.8587e-07, 1.8703e-06, 5.0068e-06,\n 1.1841e-06, 1.0154e-06, 1.7214e-06, 8.2574e-07, 6.7510e-07, 1.0945e-06,\n 1.3388e-06, 1.0186e-06, 1.6512e-06, 5.2056e-07, 9.9403e-07, 1.3158e-06,\n 1.6737e-06, 1.5665e-06, 1.2477e-06, 7.7492e-07, 1.1869e-06, 4.3407e-06,\n 9.1626e-07, 7.4924e-07, 1.6905e-06, 1.2442e-06, 2.1647e-06, 1.5210e-06,\n 1.4313e-06, 1.2772e-06, 1.1589e-06, 2.3228e-06, 2.2353e-06, 1.4136e-06,\n 8.1112e-07, 1.3134e-06, 1.3270e-06, 2.5633e-06, 6.4004e-07, 1.1013e-06,\n 1.1616e-06, 4.9760e-07, 5.7341e-07, 7.1853e-07, 1.2858e-06, 1.1453e-06,\n 1.0984e-06, 1.2849e-06, 2.4728e-06, 4.1851e-07, 3.3771e-07, 1.6249e-06,\n 1.2198e-06, 2.4185e-06, 1.2947e-06, 7.1612e-06, 7.1052e-07, 1.0627e-06,\n 1.6189e-06, 1.2148e-06, 1.6549e-06, 1.0028e-06, 4.2920e-07, 2.9966e-07,\n 7.9744e-07, 1.3182e-06, 8.2981e-07, 4.0385e-06, 1.1019e-06, 2.0903e-06,\n 2.0464e-06, 8.9159e-07, 9.5735e-07, 1.9566e-06, 1.9236e-06, 1.8249e-06,\n 1.8722e-06, 6.5476e-07, 3.1504e-07, 1.9455e-06, 2.8164e-06, 6.9590e-07,\n 1.8520e-06, 9.6893e-07, 1.0004e-06, 8.2968e-07, 2.3737e-06, 1.5976e-06,\n 3.2126e-06, 1.0510e-06, 5.9116e-07, 3.4419e-07, 1.4734e-06, 1.5547e-06,\n 2.6358e-06, 8.8484e-07, 2.4773e-06, 1.0496e-06, 8.8400e-07, 4.5428e-07,\n 4.3141e-06, 5.8663e-06, 8.3559e-07, 6.1435e-07, 9.6976e-07, 1.9990e-06,\n 1.1488e-06, 1.0606e-06, 9.0184e-07, 2.6471e-06, 8.0593e-07, 8.0181e-07,\n 1.6915e-06, 9.5856e-07, 2.6320e-06, 2.1902e-06, 1.2144e-06, 3.7885e-07,\n 2.1277e-06, 8.2828e-07, 7.5149e-07, 2.0278e-06, 8.2317e-07, 1.0765e-06,\n 9.7158e-07, 1.4986e-06, 1.5678e-06, 3.1744e-06, 9.9747e-07, 1.9836e-06,\n 1.2824e-06, 2.2806e-06, 5.4980e-07, 1.1424e-06, 2.7776e-07, 7.2227e-07,\n 8.5587e-07, 1.0326e-06, 4.6595e-07, 1.9134e-06, 1.6749e-06, 9.0817e-07,\n 5.6845e-07, 7.4441e-07, 1.6342e-06, 5.9036e-07, 1.4795e-06, 1.1229e-06,\n 8.9017e-07, 2.7837e-06, 1.0793e-06, 1.5278e-06, 1.1420e-06, 1.6870e-06,\n 1.0140e-06, 8.0060e-07, 6.0261e-07, 1.1307e-06, 4.7932e-06, 1.2232e-06,\n 1.5153e-06, 6.1686e-07, 5.7419e-07, 8.0767e-07, 9.4083e-07, 8.0879e-07,\n 2.2509e-06, 2.4171e-06, 1.1236e-06, 2.5074e-06, 8.5952e-07, 9.4065e-07,\n 1.9074e-06, 5.8410e-07, 6.4994e-07, 7.7430e-07, 1.0147e-06, 5.5592e-07,\n 8.5004e-07, 1.5104e-06, 8.5017e-07, 1.2227e-05, 8.4135e-07, 1.4172e-06,\n 1.5340e-06, 1.9543e-06, 3.2939e-07, 1.2591e-06])}, 104: {'step': 7160, 'exp_avg': tensor([ 5.3377e-05, -8.2966e-05, -7.2167e-05, 9.5478e-05, -1.1894e-06,\n -2.4716e-05, 3.4376e-05, 8.5570e-05, -4.0862e-05, -9.0235e-05,\n -5.3064e-05, -1.4991e-05, -1.3700e-05, 1.0110e-05, 5.2460e-05,\n 1.2748e-04, -1.2978e-05, -5.9907e-05, -7.3952e-05, -1.5738e-04,\n -8.6155e-05, 3.2131e-05, 1.2045e-04, 2.8602e-05, 4.6346e-06,\n 2.4595e-05, -1.2209e-04, -1.1507e-05, 3.6037e-05, 7.5449e-06,\n -1.2405e-04, -2.1618e-05, -6.3646e-05, -1.0345e-04, -2.3530e-05,\n -2.2361e-05, 1.4668e-05, -5.7129e-06, 3.0785e-05, -5.3378e-05,\n 2.7369e-06, 3.8053e-05, 4.8600e-05, 3.6067e-05, 1.8669e-05,\n -6.4478e-06, -5.6815e-05, -9.9477e-05, -2.3675e-05, 2.5488e-05,\n -2.5923e-05, -7.8233e-06, 1.2934e-04, 4.9935e-05, 3.6335e-05,\n 6.1948e-05, 2.5149e-05, -9.3405e-05, -6.2422e-05, 1.6703e-05,\n -1.7283e-05, -6.2949e-05, -1.3793e-05, 1.0304e-05, -1.5930e-04,\n 1.8607e-05, 1.1026e-04, 1.1451e-04, -1.6220e-04, 1.6219e-04,\n -1.4380e-04, 7.1626e-05, 9.5065e-05, -5.4063e-05, 2.5978e-05,\n -2.4653e-05, -8.4666e-06, 1.8112e-04, 6.3699e-05, -7.6064e-05,\n 2.1473e-05, 1.2870e-05, 9.8627e-05, 3.7955e-05, -1.0413e-04,\n 1.6821e-04, 1.2093e-05, -4.5262e-05, -1.7434e-05, 3.0108e-05,\n -1.9297e-05, 2.1047e-05, 1.4036e-04, 1.1655e-04, -1.6684e-07,\n 7.2582e-05, -2.1503e-05, 9.3656e-05, 3.8366e-05, -1.8974e-04,\n -7.4763e-05, -1.3993e-06, 8.1814e-05, 1.8021e-05, -2.9647e-05,\n 3.3129e-05, -1.0880e-05, -5.3077e-05, 8.6544e-05, 1.5182e-05,\n 2.9221e-05, 4.1375e-05, 7.2386e-05, 3.4208e-05, 5.6851e-05,\n 5.3457e-05, 9.6022e-05, -2.2102e-05, 6.5102e-05, 2.3898e-05,\n -3.6264e-05, 6.2534e-05, 8.1672e-06, -6.9785e-05, 1.4536e-07,\n 5.6576e-05, -7.1546e-06, -1.7989e-05, 1.4535e-05, -8.9055e-05,\n -2.1183e-06, -2.7451e-05, -6.4802e-05, 4.9594e-05, 3.6097e-06,\n 3.7522e-05, 8.5539e-05, -1.1997e-05, -3.5673e-05, 2.4006e-05,\n -3.5737e-05, 1.1798e-04, 7.4319e-05, 1.6035e-05, 4.8742e-05,\n -3.4859e-05, -6.6032e-06, 6.2965e-05, 4.7368e-05, 3.0736e-05,\n 2.6017e-05, 1.2270e-05, 3.5878e-05, -7.3230e-06, 9.4748e-05,\n 2.3803e-05, -4.1314e-05, -1.5282e-05, -1.1103e-06, 3.2534e-05,\n -3.3522e-05, -1.4249e-06, 1.3507e-04, -9.0490e-05, -6.7818e-05,\n 4.5881e-05, -4.9574e-05, -1.5119e-05, -1.0150e-04, 5.4154e-05,\n 7.4760e-05, -1.0058e-05, -1.7930e-05, -1.7644e-05, 1.2406e-05,\n 2.9745e-05, -3.8760e-05, 3.6051e-05, -7.2845e-06, 3.4877e-05,\n 4.2174e-05, 7.0413e-06, -4.9224e-05, 3.2635e-05, 2.0340e-05,\n 3.5607e-05, -1.7783e-05, -5.8734e-06, 4.8309e-05, -1.3887e-04,\n -2.3373e-05, 1.0669e-05, -4.8142e-05, 1.0624e-05, 1.3594e-06,\n -1.0460e-04, 6.1741e-05, 4.7299e-05, -1.0521e-05, 1.5035e-05,\n -4.0205e-05, -4.4391e-05, 6.4246e-05, -1.3598e-05, -6.4481e-05,\n -7.4997e-05, -9.2129e-06, -3.4159e-05, 1.0471e-04, -4.7133e-05,\n -2.5572e-05, -1.7904e-05, -5.7783e-05, -1.0139e-05, -2.6271e-05,\n -4.9237e-05, 1.2012e-05, -3.9689e-05, -1.2941e-06, -2.7012e-05,\n 2.1937e-05, 8.4301e-05, -5.3565e-06, -8.3838e-05, -2.2176e-05,\n -1.0054e-05, 2.3880e-05, 5.4538e-06, -2.0140e-05, -1.6616e-05,\n 3.0663e-05, 8.6775e-06, 4.8417e-05, -7.5287e-05, -1.5759e-05,\n 3.1629e-05, 5.3656e-05, 1.1529e-04, -1.8586e-05, 6.6465e-06,\n 8.2024e-05, 7.6053e-06, 1.5450e-06, -6.9172e-06, -3.8715e-05,\n -7.8225e-05, 5.4551e-05, -7.9478e-05, -4.3734e-05, 8.3427e-05,\n 1.6030e-05, -3.8085e-05, -2.5674e-05, -6.2412e-05, 3.0653e-06,\n -7.3976e-05]), 'exp_avg_sq': tensor([7.1039e-07, 6.1070e-07, 6.1391e-07, 5.2140e-07, 2.2177e-07, 3.6590e-07,\n 7.8624e-07, 3.2152e-07, 2.4239e-07, 1.5671e-06, 3.6855e-07, 1.0933e-06,\n 5.2711e-07, 2.1196e-07, 3.0289e-07, 7.7286e-07, 8.1889e-07, 4.3472e-07,\n 1.1100e-06, 1.9682e-06, 8.4884e-07, 7.6187e-07, 1.0537e-06, 3.6345e-07,\n 1.8733e-07, 3.5866e-07, 1.1947e-06, 3.4468e-07, 9.7562e-07, 3.1356e-08,\n 1.3523e-06, 2.4136e-07, 6.3975e-07, 7.2112e-07, 4.7173e-07, 1.2353e-06,\n 5.9424e-07, 5.1983e-07, 1.0617e-06, 6.3700e-07, 3.2954e-07, 8.0689e-07,\n 1.0372e-06, 4.5389e-07, 1.9103e-06, 7.3108e-07, 6.9494e-07, 6.4806e-07,\n 1.7182e-06, 6.6232e-07, 5.7850e-07, 7.2627e-07, 1.1022e-06, 5.8582e-07,\n 5.8092e-07, 7.2827e-07, 6.0044e-07, 9.4243e-07, 4.5141e-07, 3.8860e-07,\n 3.4310e-07, 7.3619e-07, 8.5558e-07, 1.2120e-06, 1.2615e-06, 6.4952e-07,\n 1.2637e-06, 5.2812e-07, 1.2026e-06, 1.0542e-06, 6.4216e-07, 1.4212e-06,\n 7.3691e-07, 4.7217e-07, 8.8370e-07, 3.4157e-07, 3.8200e-07, 1.8235e-06,\n 6.8022e-07, 4.3867e-07, 5.4767e-07, 4.6032e-07, 5.8913e-07, 6.1208e-07,\n 8.0126e-07, 1.0967e-06, 6.3551e-07, 6.0106e-07, 1.2695e-06, 1.1083e-06,\n 4.0187e-07, 7.5679e-07, 8.5720e-07, 1.2241e-06, 1.0139e-06, 5.2658e-07,\n 5.6458e-07, 7.2157e-07, 5.7824e-07, 1.2497e-06, 7.4702e-07, 6.2554e-07,\n 4.9234e-07, 7.4879e-07, 6.4377e-07, 1.2215e-06, 4.7760e-07, 7.2940e-07,\n 6.0413e-07, 2.9589e-07, 2.0620e-07, 6.7838e-07, 5.4759e-07, 6.6282e-07,\n 3.4212e-07, 9.0074e-07, 1.1394e-06, 1.8791e-07, 1.3575e-07, 1.0098e-06,\n 4.2972e-07, 1.0238e-06, 8.6137e-07, 1.8835e-06, 3.5652e-07, 1.1327e-06,\n 7.2759e-07, 4.7804e-07, 9.1543e-07, 5.2491e-07, 3.3330e-07, 1.4495e-07,\n 5.6949e-07, 9.9503e-07, 7.0709e-07, 1.1844e-06, 4.2611e-07, 7.2686e-07,\n 9.5107e-07, 3.4613e-07, 3.6209e-07, 8.8813e-07, 1.6110e-06, 1.4746e-06,\n 1.0255e-06, 3.9365e-07, 1.2048e-07, 1.2285e-06, 9.8275e-07, 4.3760e-07,\n 8.5647e-07, 4.7345e-07, 2.9840e-07, 4.9508e-07, 1.0223e-06, 7.3643e-07,\n 1.5957e-06, 8.0123e-07, 3.0481e-07, 1.0009e-07, 4.1408e-07, 9.4832e-07,\n 9.3960e-07, 5.3490e-07, 7.7664e-07, 9.7469e-07, 7.2787e-07, 1.1910e-07,\n 2.3913e-06, 1.0729e-06, 4.3738e-07, 4.1340e-07, 5.3117e-07, 7.8664e-07,\n 5.4281e-07, 4.1906e-07, 9.8978e-07, 1.9438e-06, 2.9389e-07, 3.1949e-07,\n 9.8271e-07, 3.2492e-07, 9.9933e-07, 6.0644e-07, 1.4167e-06, 3.1024e-07,\n 8.7498e-07, 5.1269e-07, 5.2779e-07, 1.0622e-06, 4.2910e-07, 4.7048e-07,\n 5.2412e-07, 1.0061e-06, 5.0900e-07, 1.0460e-06, 6.0636e-07, 1.0334e-06,\n 6.4145e-07, 8.9161e-07, 3.1887e-07, 7.4121e-07, 1.7252e-07, 4.1487e-07,\n 5.7118e-07, 5.6174e-07, 2.8277e-07, 7.4898e-07, 8.1173e-07, 4.6285e-07,\n 3.7723e-07, 2.2346e-07, 8.9005e-07, 2.5416e-07, 6.2332e-07, 7.7478e-07,\n 7.2285e-07, 8.0365e-07, 6.3788e-07, 7.4686e-07, 2.3447e-07, 1.3962e-06,\n 4.6374e-07, 7.8203e-07, 3.4585e-07, 9.4804e-07, 1.3304e-06, 5.5136e-07,\n 5.4950e-07, 2.9647e-07, 1.6957e-07, 2.8109e-07, 2.4526e-07, 6.4074e-07,\n 1.2898e-06, 1.2569e-06, 5.8452e-07, 1.0944e-06, 5.7119e-07, 9.1476e-07,\n 6.8433e-07, 1.8134e-06, 6.4224e-07, 6.0589e-07, 4.5496e-07, 5.0131e-07,\n 3.1270e-07, 8.6923e-07, 3.3343e-07, 3.7368e-06, 3.3684e-07, 6.4680e-07,\n 3.8876e-07, 1.0813e-06, 1.2310e-07, 7.0607e-07])}, 105: {'step': 7160, 'exp_avg': tensor([[[[ 2.2861e-06, 7.3578e-06, -1.2154e-06],\n [ 2.9274e-05, 1.4095e-05, -8.1404e-07],\n [-1.0941e-06, 1.0970e-05, -1.7758e-06]],\n\n [[ 1.7170e-05, -1.1163e-05, 1.5259e-05],\n [-3.4461e-06, 1.2073e-06, -6.9151e-06],\n [-5.6673e-06, -1.2797e-05, 4.0992e-07]],\n\n [[ 2.5132e-06, -2.6284e-06, -3.9198e-06],\n [-1.8130e-06, -7.3455e-06, 1.7363e-06],\n [ 1.9615e-06, -9.7306e-06, -6.8805e-07]],\n\n ...,\n\n [[-3.1773e-06, -8.1007e-06, -7.6354e-06],\n [ 8.5441e-07, 1.0433e-05, -9.4269e-06],\n [-8.7995e-06, -1.3238e-05, 1.8288e-05]],\n\n [[ 5.6603e-07, 2.6687e-07, -2.8407e-06],\n [ 3.7750e-06, -1.4822e-06, -2.1201e-06],\n [-2.6727e-07, -2.2785e-06, -1.5385e-07]],\n\n [[-6.7201e-06, 7.9404e-06, -9.7035e-06],\n [-3.8619e-06, 1.1464e-05, 9.8457e-06],\n [-6.6029e-07, 2.7235e-06, 4.1205e-06]]],\n\n\n [[[ 1.2335e-05, 7.0437e-06, 6.8227e-06],\n [ 2.0813e-05, 1.7139e-05, 1.0364e-05],\n [ 2.3946e-05, 1.8335e-05, 7.1654e-06]],\n\n [[-3.7731e-07, -5.4742e-06, -1.0944e-06],\n [ 8.3640e-06, 1.2472e-05, -8.5539e-06],\n [ 1.4211e-07, 2.9317e-06, 1.0744e-05]],\n\n [[-7.1684e-07, -2.7250e-06, 6.1752e-06],\n [-7.1048e-06, -9.2830e-06, -1.6110e-06],\n [-8.4612e-06, -1.0860e-05, 2.5957e-06]],\n\n ...,\n\n [[-3.5985e-06, -2.3481e-05, -1.9606e-05],\n [ 6.3484e-06, -1.0529e-05, -1.4954e-05],\n [-5.7742e-06, -2.2315e-05, -2.0462e-05]],\n\n [[ 1.3578e-06, -3.5459e-06, -5.1688e-07],\n [-1.3768e-06, 1.1564e-06, 4.7897e-07],\n [ 1.3960e-05, 6.6779e-07, 3.7488e-06]],\n\n [[-1.1891e-05, 3.1527e-07, -5.3409e-06],\n [ 4.4897e-06, -1.0348e-05, 6.6039e-07],\n [ 1.6483e-05, 1.7467e-05, 1.7260e-05]]],\n\n\n [[[ 1.9399e-05, -1.9855e-06, 1.4835e-05],\n [-2.7741e-06, -8.8742e-06, -6.7491e-06],\n [-1.0723e-05, -1.0894e-05, -1.0601e-05]],\n\n [[-2.5959e-06, 7.9989e-06, 2.2976e-05],\n [-7.6322e-06, -2.4171e-05, 1.7182e-05],\n [-5.7582e-06, -1.1576e-05, 4.3654e-07]],\n\n [[-1.5419e-07, -6.0105e-06, -2.9605e-07],\n [ 1.3362e-06, -2.9017e-06, -1.1330e-06],\n [-1.8705e-06, -1.9413e-09, 1.9709e-06]],\n\n ...,\n\n [[ 7.7244e-07, -7.5137e-06, 1.5594e-06],\n [ 8.2387e-07, 9.8288e-06, -1.3905e-05],\n [ 4.2985e-06, 1.7503e-06, -8.2762e-06]],\n\n [[ 6.2893e-07, -1.1931e-06, -2.0779e-06],\n [ 1.2591e-06, 2.3977e-06, 1.0248e-06],\n [-2.0633e-06, -3.0026e-07, -6.1684e-07]],\n\n [[ 3.5514e-06, -1.6124e-06, -4.0041e-06],\n [-3.5343e-06, 8.3592e-06, -2.0804e-06],\n [-1.0258e-05, -1.8853e-06, -2.4954e-06]]],\n\n\n ...,\n\n\n [[[-6.7869e-07, -5.9477e-06, 1.0638e-05],\n [ 1.2080e-05, 8.5653e-06, 6.2801e-06],\n [-3.5440e-06, -5.5677e-06, -2.8438e-06]],\n\n [[-1.9047e-06, 1.8023e-05, 7.3689e-06],\n [-6.0925e-06, 1.0752e-05, 6.0966e-06],\n [-6.2971e-06, -9.1243e-06, -2.2959e-06]],\n\n [[ 9.5718e-06, 2.3392e-06, -4.7825e-06],\n [ 9.2852e-06, 2.3092e-06, -4.6724e-06],\n [ 2.4642e-06, 4.1605e-06, -1.6376e-06]],\n\n ...,\n\n [[-9.2378e-06, -1.1462e-05, 1.4203e-05],\n [ 4.2916e-06, -2.1774e-06, 1.4395e-05],\n [ 3.3025e-07, -1.2706e-05, 1.7594e-05]],\n\n [[-6.0988e-06, -2.0586e-06, -2.3829e-06],\n [-5.9428e-06, 1.6844e-06, -3.5044e-07],\n [-3.3177e-06, 2.2781e-06, -1.5200e-07]],\n\n [[ 1.5573e-05, 8.8089e-06, 1.2106e-05],\n [ 8.0018e-06, 1.1246e-06, 6.1821e-06],\n [-5.7266e-06, -3.7191e-06, -3.5078e-06]]],\n\n\n [[[ 1.8640e-06, 2.0879e-07, 1.7169e-06],\n [-1.3058e-06, -1.8378e-06, -5.8526e-07],\n [-9.0767e-07, 1.1978e-06, -2.5401e-06]],\n\n [[-4.6589e-06, -2.5244e-06, 2.7401e-06],\n [-1.6022e-06, -2.4620e-06, 3.2448e-06],\n [ 3.3278e-06, 5.2422e-06, 1.0410e-05]],\n\n [[ 1.6813e-07, -1.0876e-07, 1.8704e-06],\n [ 3.9023e-07, 1.9558e-06, 1.5124e-06],\n [-2.1341e-06, 3.3474e-08, 1.9645e-06]],\n\n ...,\n\n [[-9.7401e-06, -8.1046e-06, -1.1060e-05],\n [-5.7561e-07, -6.5968e-06, -6.4771e-06],\n [-7.8191e-07, -5.6930e-06, -3.0627e-06]],\n\n [[ 3.5030e-07, 1.9053e-07, 7.9547e-07],\n [-5.5973e-07, 1.4481e-07, 4.0268e-07],\n [ 4.8191e-06, 1.5505e-06, 2.1246e-06]],\n\n [[ 9.1887e-07, 4.9859e-07, 1.6828e-06],\n [ 8.9717e-07, -3.2514e-06, -1.3596e-06],\n [ 4.8660e-06, 4.2520e-06, 1.1875e-06]]],\n\n\n [[[ 2.2215e-06, -4.3112e-06, -7.8865e-06],\n [-8.8552e-08, 1.0261e-05, -6.2340e-06],\n [ 2.3022e-06, -1.0078e-05, -7.7026e-06]],\n\n [[-3.4946e-06, 1.4303e-06, -4.3431e-07],\n [ 2.5159e-06, -5.3434e-06, 5.7616e-06],\n [ 5.9795e-06, 1.4192e-06, -3.9406e-07]],\n\n [[ 4.9473e-06, -4.3515e-07, 2.1937e-06],\n [ 3.6227e-06, 3.8794e-07, -4.6410e-08],\n [ 4.1250e-06, 2.4420e-06, 1.8713e-06]],\n\n ...,\n\n [[ 8.6550e-07, 1.1825e-06, -4.4295e-06],\n [-7.6910e-06, 1.5414e-06, 6.6791e-07],\n [-1.3071e-06, -1.0458e-06, -1.5299e-07]],\n\n [[-2.5740e-06, 2.9574e-07, -4.1031e-06],\n [-2.9403e-06, -4.1888e-06, -1.5143e-06],\n [ 1.4505e-06, -4.1482e-07, -4.2566e-07]],\n\n [[ 4.3817e-06, 1.8908e-06, 1.8623e-06],\n [ 1.5935e-06, 4.0125e-06, -5.6227e-06],\n [ 5.3267e-07, -5.8659e-06, -2.6944e-06]]]]), 'exp_avg_sq': tensor([[[[5.4042e-09, 1.6656e-08, 4.0228e-09],\n [8.0706e-09, 1.4901e-08, 1.9365e-08],\n [3.7828e-09, 1.0057e-08, 4.6684e-09]],\n\n [[1.2452e-08, 1.0144e-08, 8.8035e-09],\n [8.5339e-09, 7.8911e-09, 7.5173e-09],\n [4.3431e-09, 5.8931e-09, 3.9857e-09]],\n\n [[5.2501e-09, 4.4643e-09, 5.5920e-09],\n [3.7931e-09, 5.0855e-09, 9.8720e-09],\n [5.6452e-09, 5.7155e-09, 8.1939e-09]],\n\n ...,\n\n [[7.1642e-09, 8.8672e-09, 7.7826e-09],\n [8.1609e-09, 9.6705e-09, 6.4825e-09],\n [5.3798e-09, 9.2518e-09, 7.5959e-09]],\n\n [[9.0842e-10, 1.0724e-09, 1.2041e-09],\n [1.1838e-09, 1.3668e-09, 8.7385e-10],\n [8.0569e-10, 8.6545e-10, 7.5525e-10]],\n\n [[6.0119e-09, 8.0264e-09, 7.7765e-09],\n [9.0810e-09, 6.8378e-09, 6.1314e-09],\n [6.7206e-09, 7.1191e-09, 1.1379e-08]]],\n\n\n [[[1.9871e-08, 1.4684e-08, 2.6503e-08],\n [1.7573e-08, 1.9846e-08, 2.3934e-08],\n [1.8397e-08, 1.8637e-08, 1.2454e-08]],\n\n [[2.2771e-08, 2.3384e-08, 2.1473e-08],\n [2.0040e-08, 2.0593e-08, 1.6741e-08],\n [1.8998e-08, 1.7571e-08, 1.4714e-08]],\n\n [[1.8177e-08, 1.8120e-08, 2.0255e-08],\n [1.2731e-08, 1.1045e-08, 1.7004e-08],\n [1.2117e-08, 1.1470e-08, 1.8795e-08]],\n\n ...,\n\n [[1.6755e-08, 3.5584e-08, 2.6466e-08],\n [1.1563e-08, 1.9762e-08, 2.9791e-08],\n [1.2216e-08, 1.9254e-08, 1.5352e-08]],\n\n [[1.8022e-09, 1.9487e-09, 1.9398e-09],\n [1.7956e-09, 1.6569e-09, 1.5919e-09],\n [3.0037e-09, 2.7013e-09, 1.2228e-09]],\n\n [[9.3018e-09, 9.6725e-09, 1.1788e-08],\n [1.5471e-08, 1.1138e-08, 1.1421e-08],\n [1.4946e-08, 1.9150e-08, 2.6937e-08]]],\n\n\n [[[1.0377e-08, 8.9458e-09, 1.1763e-08],\n [1.0890e-08, 1.3093e-08, 1.4717e-08],\n [8.4639e-09, 8.8723e-09, 1.0866e-08]],\n\n [[8.9754e-09, 1.1647e-08, 1.1390e-08],\n [1.1983e-08, 1.3494e-08, 1.0050e-08],\n [1.0920e-08, 9.0454e-09, 1.1512e-08]],\n\n [[6.6463e-09, 5.6861e-09, 5.2230e-09],\n [1.0315e-08, 6.9595e-09, 8.3395e-09],\n [1.5346e-08, 1.7570e-08, 6.9207e-09]],\n\n ...,\n\n [[8.8473e-09, 1.3518e-08, 2.6669e-08],\n [1.2436e-08, 2.1029e-08, 1.6635e-08],\n [8.0502e-09, 8.1312e-09, 1.7697e-08]],\n\n [[1.6946e-09, 1.9457e-09, 1.4550e-09],\n [2.7431e-09, 1.8366e-09, 1.6549e-09],\n [1.7112e-09, 1.1375e-09, 9.5294e-10]],\n\n [[1.1671e-08, 9.6146e-09, 1.0057e-08],\n [1.1346e-08, 1.2794e-08, 1.0462e-08],\n [1.0837e-08, 1.2427e-08, 6.5355e-09]]],\n\n\n ...,\n\n\n [[[1.3095e-08, 2.1386e-08, 3.6721e-08],\n [1.5228e-08, 2.8279e-08, 1.4145e-08],\n [1.2161e-08, 2.0762e-08, 6.7901e-09]],\n\n [[9.3102e-09, 1.8812e-08, 1.7246e-08],\n [1.7293e-08, 1.2698e-08, 1.0684e-08],\n [3.0173e-08, 1.5662e-08, 1.3351e-08]],\n\n [[5.2517e-09, 1.0045e-08, 9.9914e-09],\n [1.4651e-08, 6.0240e-09, 6.8078e-09],\n [1.7449e-08, 1.4404e-08, 7.4464e-09]],\n\n ...,\n\n [[2.1567e-08, 3.7148e-08, 7.3393e-09],\n [2.7604e-08, 4.9608e-08, 2.5461e-08],\n [1.0408e-08, 4.1836e-08, 1.6119e-08]],\n\n [[2.1249e-09, 2.2621e-09, 3.3476e-09],\n [3.1520e-09, 2.5538e-09, 2.6981e-09],\n [2.4422e-09, 1.4681e-09, 9.8239e-10]],\n\n [[2.2194e-08, 2.1712e-08, 2.1328e-08],\n [1.1226e-08, 1.6149e-08, 3.1690e-08],\n [7.5357e-09, 8.3422e-09, 1.4689e-08]]],\n\n\n [[[1.3613e-09, 2.0819e-09, 1.8745e-09],\n [2.8494e-09, 2.7674e-09, 3.5083e-09],\n [4.0967e-09, 4.5456e-09, 9.4692e-09]],\n\n [[2.0537e-09, 2.2059e-09, 2.5570e-09],\n [5.7256e-09, 5.9252e-09, 4.3601e-09],\n [4.8693e-09, 5.1839e-09, 2.9098e-09]],\n\n [[1.5393e-09, 1.3136e-09, 2.2533e-09],\n [2.0042e-09, 1.6890e-09, 1.3448e-09],\n [7.8944e-10, 6.1887e-10, 9.0990e-10]],\n\n ...,\n\n [[4.8739e-09, 1.0143e-08, 6.3039e-09],\n [6.1592e-09, 1.3697e-08, 9.8432e-09],\n [1.6503e-09, 4.4884e-09, 4.1092e-09]],\n\n [[3.8426e-10, 1.4289e-10, 1.9791e-10],\n [2.7714e-10, 1.6415e-10, 2.9168e-10],\n [5.8800e-10, 6.6634e-10, 7.0897e-10]],\n\n [[1.5536e-09, 3.1432e-09, 2.0864e-09],\n [1.1060e-09, 8.9289e-10, 8.7343e-10],\n [3.1850e-09, 4.4217e-09, 2.1576e-09]]],\n\n\n [[[6.3843e-09, 6.2495e-09, 1.0098e-08],\n [2.9472e-09, 3.7610e-09, 7.6028e-09],\n [4.5077e-09, 7.0350e-09, 7.1814e-09]],\n\n [[3.4431e-09, 1.8283e-09, 2.3716e-09],\n [6.3653e-09, 6.6435e-09, 2.8592e-09],\n [6.4074e-09, 3.4092e-09, 4.7007e-09]],\n\n [[2.7593e-09, 1.6781e-09, 4.0367e-09],\n [1.9771e-08, 1.7175e-09, 4.8935e-09],\n [1.6575e-08, 4.2601e-09, 2.4222e-09]],\n\n ...,\n\n [[3.3840e-09, 7.9732e-09, 6.3103e-09],\n [8.1570e-09, 2.2016e-08, 4.0378e-09],\n [5.6887e-09, 1.1509e-08, 5.9259e-09]],\n\n [[6.2198e-10, 6.3697e-10, 1.0543e-09],\n [1.8037e-09, 1.1836e-09, 7.3819e-10],\n [1.0083e-09, 6.8339e-10, 9.2176e-10]],\n\n [[5.7974e-09, 6.4831e-09, 9.9077e-09],\n [4.3979e-09, 4.2258e-09, 4.4728e-09],\n [4.9384e-09, 2.9684e-09, 2.1756e-09]]]])}, 106: {'step': 7160, 'exp_avg': tensor([-2.4207e-05, 2.2447e-05, 1.7207e-04, 1.9610e-05, 7.0767e-07,\n 1.2000e-04, -7.7164e-05, -1.1505e-04, -2.0258e-05, 4.6820e-05,\n -3.4850e-05, -4.0580e-05, 2.1467e-05, 1.1975e-05, 4.8958e-05,\n 9.2259e-05, 8.5023e-05, -1.1653e-04, 1.0637e-05, 4.3944e-05,\n -1.1204e-04, -1.6074e-04, 8.3641e-06, -1.0869e-04, 3.9629e-05,\n -2.2312e-05, -1.3605e-04, -1.3916e-05, 3.1944e-05, 2.8910e-05,\n -1.6926e-04, -2.7523e-05, -2.0786e-05, -1.8623e-05, 9.2795e-05,\n -2.3971e-04, 2.6040e-06, 9.1655e-05, 1.2952e-05, -4.3274e-06,\n -9.8462e-05, -1.8061e-04, -1.0078e-04, -6.9077e-05, -4.4752e-06,\n 7.7764e-05, 2.6640e-05, 1.4060e-04, -5.9814e-05, 3.2898e-05,\n 1.2118e-04, 2.7107e-04, -9.6105e-05, -6.6163e-05, -9.5243e-05,\n -1.1529e-04, 1.1019e-05, 3.0657e-05, 3.3407e-05, -2.6770e-05,\n 3.6156e-05, -2.3279e-05, 7.4335e-05, -9.0320e-05, 3.7987e-05,\n 1.4978e-04, 7.4696e-05, -3.3677e-05, 1.0540e-04, -1.4705e-05,\n 5.4207e-05, -2.1561e-06, -2.8176e-05, -1.1191e-04, 8.9159e-05,\n -5.5472e-06, 6.9461e-05, 1.3234e-04, -1.0599e-04, 2.2250e-04,\n -2.3239e-05, -2.1889e-05, -3.9563e-05, -5.8748e-05, -2.1137e-05,\n 2.1465e-04, 3.8371e-05, -2.9809e-05, -3.8488e-05, 3.9800e-05,\n 1.3409e-06, 4.2114e-05, 1.7937e-04, -4.0721e-05, -1.0071e-04,\n 3.5464e-04, 2.2475e-04, -3.0815e-05, 7.3322e-06, -5.1853e-05,\n 1.0016e-04, 6.6615e-05, 6.3836e-05, 7.9912e-06, -2.8558e-05,\n -1.3247e-04, -8.2461e-05, -2.5739e-05, -2.4463e-05, 1.5909e-04,\n -3.3258e-05, -2.5827e-05, 3.9106e-05, 2.6865e-08, -6.5780e-06,\n -1.0681e-04, -9.0042e-05, 3.5563e-05, -2.5527e-06, 2.3597e-05,\n -1.1772e-04, 1.6020e-05, -2.9617e-05, -4.6980e-05, 4.4749e-05,\n -1.0685e-04, -7.8463e-05, -2.7619e-04, 1.3921e-05, -8.7444e-05,\n -1.7591e-05, 2.6560e-05, 3.0347e-05, -2.3854e-05, -2.0971e-05,\n 1.7008e-04, 1.4561e-04, 1.5118e-04, 5.7419e-06, -1.0412e-04,\n -3.4524e-05, -3.4468e-05, 5.7026e-05, 6.1772e-05, 1.2460e-04,\n 3.5249e-05, -1.6431e-04, -6.8455e-05, 2.0543e-05, -7.2337e-05,\n -1.9379e-05, 4.3034e-05, 3.3148e-05, -4.9639e-06, 1.3793e-05,\n 2.6530e-05, 2.0029e-05, -1.0974e-04, 2.9310e-05, -1.5947e-05,\n 2.3703e-05, -4.0712e-05, 9.6087e-06, 1.4998e-05, -7.7736e-05,\n -1.8676e-04, 9.0890e-06, 3.9797e-05, 6.8482e-05, -1.6133e-05,\n 1.4996e-04, -1.2724e-05, -3.5705e-05, -1.0843e-04, -9.3961e-05,\n -4.9312e-05, -1.0630e-04, 3.7695e-06, -5.4068e-05, -7.8410e-05,\n 2.8573e-05, 1.1418e-04, 1.2203e-05, -1.4091e-05, 1.9162e-04,\n 1.7387e-04, 1.3000e-04, -1.4142e-04, -4.1054e-06, 7.7992e-05,\n -5.4325e-05, 1.3288e-05, -6.6859e-06, -7.8054e-05, 6.5771e-05,\n -3.5864e-05, 4.3145e-05, -8.4080e-05, -4.8792e-05, -1.7271e-04,\n -1.1382e-04, 7.6008e-05, -5.3488e-05, -1.6196e-04, -2.3495e-05,\n 6.0547e-05, 1.9176e-05, 1.2981e-04, -1.9189e-05, -1.1378e-04,\n -3.9743e-05, 1.9473e-05, 5.1339e-06, 7.4133e-05, -2.6823e-05,\n 2.8275e-05, -2.6046e-05, 6.9049e-05, -8.1181e-06, 2.1017e-05,\n 1.8461e-05, -7.3204e-05, 3.7880e-05, -1.0140e-04, 3.9652e-05,\n -8.1427e-06, 5.0263e-05, -9.4895e-05, -9.8381e-05, 1.4851e-07,\n -4.6836e-05, 2.0027e-05, -1.1456e-05, -7.9760e-05, -1.1047e-05,\n 1.5502e-04, 4.6538e-05, 2.9413e-04, 5.4011e-05, -1.4038e-05,\n 5.0050e-05, 6.5839e-05, -8.1902e-05, -6.4645e-05, -5.5604e-05,\n 8.3187e-05, -3.9442e-05, 4.1877e-07, 4.2050e-05, -4.9263e-05,\n 3.8683e-05, 2.0334e-05, 1.4420e-05, 2.1042e-04, -4.2875e-05,\n 2.1675e-05]), 'exp_avg_sq': tensor([8.9601e-07, 2.3524e-06, 1.2215e-06, 9.2973e-07, 3.7340e-07, 4.7107e-07,\n 8.1496e-07, 6.1993e-07, 1.0103e-06, 1.3966e-06, 6.7312e-07, 2.0034e-06,\n 1.0830e-06, 6.8490e-07, 1.8275e-06, 1.0056e-06, 8.6369e-07, 1.7865e-06,\n 7.2079e-07, 8.2544e-07, 2.0100e-06, 1.1165e-06, 8.4971e-07, 2.3043e-06,\n 3.9693e-07, 4.6573e-07, 1.4064e-06, 1.7101e-06, 8.1996e-07, 7.4631e-07,\n 8.2194e-07, 1.0513e-06, 8.1606e-07, 4.5649e-07, 6.9492e-07, 2.0216e-06,\n 7.5864e-07, 4.1870e-07, 9.5590e-07, 1.5420e-06, 2.3322e-06, 3.3664e-06,\n 2.5492e-06, 1.6055e-06, 4.9034e-07, 8.7542e-07, 6.1996e-07, 2.3522e-06,\n 7.6179e-07, 5.0625e-07, 4.1767e-06, 3.1294e-06, 6.7733e-07, 6.5630e-07,\n 1.4070e-06, 4.0973e-07, 2.4593e-06, 6.1103e-07, 8.2483e-07, 5.4322e-07,\n 1.3482e-06, 3.0629e-06, 5.1240e-07, 4.8417e-07, 4.3603e-07, 1.7874e-06,\n 1.0108e-06, 7.1072e-07, 1.4289e-06, 8.7550e-07, 9.4588e-07, 7.8971e-06,\n 9.9002e-07, 1.1544e-06, 4.2624e-07, 3.6953e-07, 6.2337e-07, 1.2769e-06,\n 5.7077e-07, 4.9497e-06, 1.0272e-06, 7.7489e-07, 1.3705e-06, 1.5424e-06,\n 9.1227e-07, 7.8077e-07, 3.6863e-07, 1.9134e-06, 1.4839e-06, 5.0749e-07,\n 1.4311e-06, 1.6296e-06, 1.3082e-06, 7.8278e-07, 1.0859e-06, 1.3267e-05,\n 2.5479e-06, 4.3176e-07, 1.5334e-06, 1.5917e-06, 8.8116e-07, 9.9585e-07,\n 5.3902e-07, 3.6765e-07, 3.5282e-07, 1.2450e-06, 1.6634e-06, 1.5017e-06,\n 6.8579e-07, 9.4465e-07, 8.0242e-07, 4.2078e-07, 1.1969e-06, 8.6353e-07,\n 1.1640e-06, 6.0845e-07, 5.7396e-07, 2.9333e-07, 5.8157e-07, 1.2800e-06,\n 5.1732e-07, 1.2120e-06, 4.7391e-07, 6.0798e-07, 7.4481e-07, 2.4967e-07,\n 1.3481e-06, 2.5225e-06, 3.4085e-07, 7.4769e-07, 4.6298e-07, 1.0045e-06,\n 6.9140e-07, 7.9357e-07, 6.5128e-07, 1.5152e-06, 2.5558e-06, 1.3541e-06,\n 7.9130e-07, 1.1042e-06, 4.8746e-07, 5.3834e-07, 4.1374e-07, 5.2442e-07,\n 5.8946e-07, 1.2072e-06, 1.1756e-06, 7.8968e-07, 1.6258e-06, 6.3847e-07,\n 1.2843e-06, 8.5747e-07, 4.3444e-07, 5.8452e-07, 8.7748e-07, 6.2969e-07,\n 4.6033e-07, 1.9884e-06, 6.9698e-07, 4.3598e-07, 8.1100e-06, 4.0312e-07,\n 3.0543e-07, 8.3403e-07, 1.7489e-06, 1.6454e-06, 8.2119e-07, 9.0589e-07,\n 1.7425e-06, 1.2378e-06, 8.6598e-07, 6.1386e-07, 4.4695e-07, 6.6204e-06,\n 1.0622e-06, 3.7193e-07, 2.6882e-06, 9.4732e-07, 1.2976e-06, 3.6252e-07,\n 3.2081e-07, 1.0134e-06, 1.0451e-06, 2.0972e-06, 2.8373e-06, 3.3754e-06,\n 9.9337e-07, 3.0365e-06, 7.8569e-07, 9.5301e-07, 2.5195e-06, 1.3862e-06,\n 6.7494e-07, 2.1014e-06, 7.5771e-07, 3.5240e-07, 9.3219e-07, 5.9613e-07,\n 6.0460e-07, 1.4808e-06, 1.8743e-06, 3.0477e-06, 1.4516e-06, 7.9623e-07,\n 1.8311e-06, 9.4299e-07, 6.3217e-07, 7.6861e-07, 3.8755e-07, 1.2228e-06,\n 1.2265e-06, 3.7932e-07, 7.6947e-07, 1.0818e-06, 4.7251e-07, 9.1721e-07,\n 4.9065e-07, 1.1252e-06, 2.5310e-06, 6.7643e-07, 8.0757e-07, 1.1029e-06,\n 1.0313e-06, 7.0572e-07, 7.1025e-07, 9.7349e-07, 1.3481e-06, 1.5213e-06,\n 1.1962e-06, 4.7198e-06, 1.9403e-07, 7.0398e-07, 6.0014e-07, 4.7427e-07,\n 6.8318e-07, 2.8097e-06, 1.3952e-06, 3.0866e-06, 9.1858e-07, 4.7058e-07,\n 3.2494e-07, 1.5094e-06, 1.7645e-06, 1.0796e-06, 1.5042e-06, 3.0452e-06,\n 7.6514e-07, 1.7884e-06, 1.4873e-06, 4.0075e-07, 6.7790e-07, 6.9909e-07,\n 4.9245e-07, 1.5508e-06, 3.1771e-07, 4.4016e-07])}, 107: {'step': 7160, 'exp_avg': tensor([ 8.7093e-06, 1.5183e-05, 1.0352e-04, 4.2984e-05, -7.6422e-05,\n 9.8039e-05, -6.7327e-05, -4.4593e-05, -5.3220e-05, 2.2885e-05,\n -6.4312e-06, 4.3709e-05, 1.5470e-05, 3.0122e-05, 3.4103e-05,\n 5.3693e-05, 2.2400e-05, -8.7853e-05, 9.3783e-06, 5.0818e-05,\n -5.2116e-05, -9.3758e-05, 9.8230e-06, -6.3359e-05, 3.4938e-05,\n -1.8319e-05, -2.6136e-05, -1.4476e-05, -2.4526e-05, 2.5595e-05,\n -1.4511e-04, -6.3462e-06, -2.5038e-05, -2.6991e-06, 7.8734e-05,\n -1.3719e-04, -5.3040e-05, 6.4762e-05, -3.9589e-05, -2.4737e-05,\n 1.4707e-05, -1.1204e-04, 7.9350e-05, -4.6797e-05, -1.3651e-05,\n -1.8275e-06, 3.0889e-05, -1.1952e-05, -1.3180e-05, 2.7754e-05,\n 6.0587e-05, 7.5368e-05, -6.9063e-05, -2.2486e-05, -5.6390e-05,\n -8.3520e-05, -1.3860e-05, 2.1390e-05, 6.3143e-05, -2.4756e-05,\n 2.3795e-05, -8.7972e-06, 5.2410e-05, -6.7330e-05, 4.4704e-05,\n -3.4203e-05, 6.3985e-05, 8.8669e-06, 5.5451e-05, -1.2658e-05,\n 4.1766e-05, -1.2677e-05, -6.6282e-06, -4.6144e-05, 5.1053e-05,\n 6.3957e-06, 5.1342e-05, 7.5165e-05, -1.0039e-04, 3.2403e-05,\n -1.1679e-05, 1.3770e-05, -1.3389e-05, 1.7377e-05, -7.7386e-05,\n 9.2576e-05, 7.5949e-06, -1.6733e-05, 4.7539e-05, 1.0201e-05,\n -9.6288e-06, -4.6611e-05, 6.3568e-05, -1.2360e-05, -5.1235e-05,\n 5.5753e-05, -1.2538e-05, -3.4154e-05, 1.1667e-05, -6.6425e-06,\n -3.0213e-05, 1.7146e-05, 3.7759e-05, 1.3026e-05, -2.5489e-05,\n -8.7475e-05, -6.3410e-05, -6.3600e-05, -6.4327e-06, 1.4779e-04,\n -2.1703e-05, -3.7292e-05, 2.7935e-06, 1.8637e-05, -1.6900e-05,\n -2.3154e-05, -3.9333e-05, 5.1294e-06, -4.4084e-06, 6.5987e-05,\n -4.8058e-05, 3.0743e-05, -9.6108e-06, -3.1965e-05, 1.9993e-05,\n -6.3102e-05, -3.2002e-05, -1.4555e-04, 9.4833e-06, -3.3871e-05,\n -1.5640e-05, 6.2999e-05, -5.0751e-06, -5.6153e-06, -3.2998e-05,\n 1.1738e-04, -6.4924e-05, 1.0485e-04, 1.9173e-06, -4.0002e-05,\n -1.6790e-07, -4.0609e-05, 9.1665e-05, 2.9061e-05, 1.1611e-04,\n 6.8468e-05, -4.7468e-05, -1.3169e-04, 4.5103e-05, -1.6867e-06,\n -5.0099e-05, 8.1125e-06, 1.7380e-05, -1.4710e-05, 5.2092e-05,\n 2.3610e-05, 2.9876e-05, -1.6280e-05, 2.5881e-05, 3.5541e-06,\n -9.2055e-05, -5.8674e-05, 8.2264e-06, 4.2916e-05, -2.1666e-05,\n -9.9012e-05, 2.8141e-05, 1.0774e-05, 2.0648e-05, -4.1485e-05,\n 1.0901e-04, -2.2696e-05, -4.2180e-05, -1.0545e-04, -4.9667e-05,\n -3.5570e-05, -2.9550e-05, 5.8812e-05, -4.1578e-05, -7.6664e-05,\n 4.2314e-05, 8.9707e-05, 1.6441e-06, -2.1505e-05, 1.4698e-05,\n 3.5038e-05, 6.1684e-05, -7.1031e-05, -5.7328e-05, 6.4912e-05,\n -3.7562e-05, 5.2397e-06, 2.2461e-05, -5.3488e-05, 5.0446e-05,\n -4.3238e-06, 8.7295e-05, -6.9881e-05, -4.3788e-05, -1.2497e-04,\n -7.6618e-05, 4.8711e-05, -3.4274e-05, -1.2952e-04, -4.8623e-05,\n 5.0610e-05, 7.9166e-06, 8.1885e-05, -1.0025e-04, -1.0245e-04,\n 1.5532e-05, 2.0936e-05, 2.4689e-05, 6.1053e-05, -2.0866e-05,\n 3.0142e-05, -1.8469e-05, 8.8318e-05, -4.3875e-05, 3.9153e-05,\n 4.8478e-05, -4.4198e-05, 7.2930e-05, -6.1176e-05, 4.8532e-05,\n -2.5350e-05, 7.8857e-05, 6.0635e-05, -6.7133e-05, 1.4868e-05,\n -3.9015e-05, 1.0226e-06, 3.0263e-05, -8.0088e-05, -2.7696e-05,\n 2.1999e-05, 3.7470e-05, -2.6890e-06, 3.5388e-05, 1.8152e-05,\n 3.8138e-06, 4.2368e-05, -6.8987e-05, -8.4902e-05, -6.1373e-05,\n -1.7963e-04, -7.2734e-05, 1.8605e-05, 1.3749e-05, -5.2041e-05,\n 6.3494e-05, 3.8956e-05, -3.3613e-05, 1.3862e-04, 1.3408e-05,\n 1.6510e-05]), 'exp_avg_sq': tensor([4.2406e-07, 1.5032e-06, 7.2692e-07, 4.9941e-07, 3.6140e-07, 4.8284e-07,\n 5.1101e-07, 5.5016e-07, 3.5571e-07, 9.2645e-07, 5.3772e-07, 9.5557e-07,\n 6.9585e-07, 4.8229e-07, 9.4651e-07, 4.3003e-07, 4.1307e-07, 7.3555e-07,\n 8.2137e-07, 4.3374e-07, 3.9485e-07, 6.9764e-07, 6.6992e-07, 6.3204e-07,\n 3.1125e-07, 2.5482e-07, 7.5205e-07, 1.2198e-06, 5.4851e-07, 6.4394e-07,\n 6.8188e-07, 5.1261e-07, 3.0243e-07, 2.3750e-07, 3.3595e-07, 6.6288e-07,\n 4.8258e-07, 2.8745e-07, 5.5339e-07, 6.5694e-07, 7.6656e-07, 1.9584e-06,\n 1.7603e-06, 1.1558e-06, 2.5709e-07, 5.0134e-07, 3.8234e-07, 1.1693e-06,\n 3.4514e-07, 2.4209e-07, 1.4304e-06, 8.1209e-07, 2.8479e-07, 4.9009e-07,\n 5.5365e-07, 2.7002e-07, 1.9380e-06, 3.4091e-07, 4.8344e-07, 2.9696e-07,\n 8.5275e-07, 8.0453e-07, 2.7192e-07, 2.9385e-07, 4.3256e-07, 1.0674e-06,\n 4.3854e-07, 4.3763e-07, 6.3791e-07, 5.9980e-07, 3.9789e-07, 7.0199e-07,\n 4.3100e-07, 6.6372e-07, 2.6025e-07, 3.2365e-07, 2.8089e-07, 5.1379e-07,\n 3.2851e-07, 5.2759e-07, 4.3376e-07, 5.4242e-07, 7.1726e-07, 3.8731e-07,\n 8.6907e-07, 4.9218e-07, 2.3862e-07, 5.7132e-07, 8.2442e-07, 6.1069e-07,\n 5.1622e-07, 8.1077e-07, 7.2247e-07, 9.6174e-07, 8.7277e-07, 2.0128e-07,\n 8.6878e-07, 5.3099e-07, 5.0705e-07, 1.2779e-06, 5.1392e-07, 4.5836e-07,\n 2.1540e-07, 3.6137e-07, 2.8480e-07, 7.5551e-07, 8.1873e-07, 1.4571e-06,\n 2.8183e-07, 1.2648e-06, 3.6066e-07, 2.3107e-07, 5.0278e-07, 4.5204e-07,\n 9.7394e-07, 1.0761e-07, 3.5943e-07, 1.8375e-07, 5.7938e-07, 6.7296e-07,\n 3.8231e-07, 7.3264e-07, 3.4094e-07, 4.1912e-07, 4.9751e-07, 1.5892e-07,\n 5.8400e-07, 1.1705e-06, 1.7462e-07, 4.5288e-07, 3.0495e-07, 6.6806e-07,\n 4.7045e-07, 5.1980e-07, 4.9806e-07, 1.0040e-06, 7.9781e-07, 5.1951e-07,\n 3.1009e-07, 5.2356e-07, 4.7590e-07, 3.4431e-07, 6.0338e-07, 2.0727e-07,\n 7.6101e-07, 1.0923e-06, 9.2906e-07, 6.3885e-07, 5.6595e-07, 4.9458e-07,\n 7.4890e-07, 4.7598e-07, 2.0043e-07, 3.0196e-07, 8.3625e-07, 3.8925e-07,\n 3.3921e-07, 6.7857e-07, 3.8766e-07, 3.2445e-07, 6.0929e-07, 2.3958e-07,\n 2.6023e-07, 4.6698e-07, 6.6945e-07, 1.0098e-06, 4.9599e-07, 4.4215e-07,\n 3.2982e-07, 1.2209e-06, 7.0366e-07, 2.8407e-07, 4.3208e-07, 2.7606e-06,\n 7.5395e-07, 2.1946e-07, 4.6251e-07, 5.1863e-07, 4.9703e-07, 2.6806e-07,\n 2.3207e-07, 3.4455e-07, 4.9684e-07, 1.0172e-06, 4.3259e-07, 9.8271e-07,\n 6.0795e-07, 7.1300e-07, 4.7560e-07, 4.9547e-07, 7.4076e-07, 5.4910e-07,\n 3.6482e-07, 9.8149e-07, 3.1416e-07, 5.4731e-07, 5.1548e-07, 4.2553e-07,\n 2.3232e-07, 9.8665e-07, 6.7149e-07, 1.3901e-06, 6.8799e-07, 4.7742e-07,\n 7.6414e-07, 9.3302e-07, 2.4998e-07, 3.4701e-07, 2.9961e-07, 8.1758e-07,\n 4.3723e-07, 4.1429e-07, 5.0098e-07, 4.0200e-07, 3.3149e-07, 5.0624e-07,\n 4.2437e-07, 6.1001e-07, 6.3445e-07, 4.6766e-07, 3.9464e-07, 6.2639e-07,\n 7.2341e-07, 2.9507e-07, 3.5187e-07, 5.0900e-07, 8.8550e-07, 8.3295e-07,\n 4.9380e-07, 4.9921e-07, 9.3715e-08, 2.8877e-07, 4.4201e-07, 3.4115e-07,\n 4.7233e-07, 7.5690e-08, 7.1806e-07, 3.7553e-07, 4.3841e-07, 5.1310e-07,\n 2.9813e-07, 7.6609e-07, 1.0597e-06, 5.6841e-07, 7.9239e-07, 1.5357e-06,\n 1.1747e-06, 8.8678e-07, 6.1011e-07, 2.1689e-07, 3.3617e-07, 5.1623e-07,\n 5.8887e-07, 7.4381e-07, 1.9538e-07, 2.0608e-07])}, 108: {'step': 7160, 'exp_avg': tensor([[[[-1.7601e-06]],\n\n [[ 2.1186e-05]],\n\n [[ 2.0679e-05]],\n\n ...,\n\n [[-4.5263e-06]],\n\n [[ 4.4099e-06]],\n\n [[-5.4208e-06]]],\n\n\n [[[ 6.7072e-06]],\n\n [[-3.3286e-06]],\n\n [[ 1.4537e-05]],\n\n ...,\n\n [[-3.2932e-06]],\n\n [[ 6.9866e-07]],\n\n [[ 4.1470e-06]]],\n\n\n [[[-1.0088e-06]],\n\n [[-2.0360e-06]],\n\n [[ 8.1871e-06]],\n\n ...,\n\n [[-2.4698e-06]],\n\n [[-5.0839e-07]],\n\n [[ 1.9602e-06]]],\n\n\n ...,\n\n\n [[[ 5.4746e-06]],\n\n [[ 1.9698e-06]],\n\n [[-1.0669e-05]],\n\n ...,\n\n [[ 1.3108e-05]],\n\n [[-2.0681e-06]],\n\n [[ 2.9563e-06]]],\n\n\n [[[-1.6268e-06]],\n\n [[-1.4763e-05]],\n\n [[-8.0800e-06]],\n\n ...,\n\n [[-2.9573e-06]],\n\n [[-4.4326e-06]],\n\n [[ 1.5695e-06]]],\n\n\n [[[ 4.1976e-07]],\n\n [[ 2.1443e-06]],\n\n [[ 1.0444e-05]],\n\n ...,\n\n [[-2.2522e-06]],\n\n [[ 1.8099e-06]],\n\n [[-3.2990e-07]]]]), 'exp_avg_sq': tensor([[[[8.3298e-09]],\n\n [[1.8303e-08]],\n\n [[2.0823e-08]],\n\n ...,\n\n [[7.5049e-09]],\n\n [[7.7119e-09]],\n\n [[5.1694e-09]]],\n\n\n [[[6.0938e-09]],\n\n [[1.7385e-08]],\n\n [[1.7426e-08]],\n\n ...,\n\n [[8.1853e-09]],\n\n [[5.4738e-09]],\n\n [[6.7588e-09]]],\n\n\n [[[5.1882e-09]],\n\n [[6.2457e-09]],\n\n [[4.8879e-09]],\n\n ...,\n\n [[1.0918e-08]],\n\n [[6.3889e-09]],\n\n [[9.8214e-09]]],\n\n\n ...,\n\n\n [[[1.3785e-08]],\n\n [[1.2563e-08]],\n\n [[1.7127e-08]],\n\n ...,\n\n [[2.0456e-08]],\n\n [[4.1463e-09]],\n\n [[1.0677e-08]]],\n\n\n [[[8.1723e-09]],\n\n [[1.2612e-08]],\n\n [[7.1064e-09]],\n\n ...,\n\n [[2.7050e-09]],\n\n [[4.8040e-09]],\n\n [[2.8411e-09]]],\n\n\n [[[3.1295e-09]],\n\n [[4.3415e-09]],\n\n [[6.3118e-09]],\n\n ...,\n\n [[2.5230e-09]],\n\n [[1.6974e-09]],\n\n [[1.4145e-09]]]])}, 109: {'step': 7160, 'exp_avg': tensor([-3.2433e-06, 2.9832e-05, 2.9741e-05, ..., -2.9348e-05,\n -1.8719e-05, 1.0192e-04]), 'exp_avg_sq': tensor([1.3446e-06, 1.3604e-07, 8.3177e-08, ..., 4.3262e-07, 4.9099e-07,\n 2.1670e-06])}, 110: {'step': 7160, 'exp_avg': tensor([-5.8273e-05, 3.6743e-05, 1.3736e-05, ..., -2.9899e-05,\n 3.1666e-05, 8.6436e-05]), 'exp_avg_sq': tensor([3.5160e-07, 8.3314e-08, 6.6949e-08, ..., 2.4697e-07, 3.9817e-07,\n 2.6199e-06])}, 111: {'step': 7160, 'exp_avg': tensor([[[[ 8.3838e-06]],\n\n [[-1.0881e-07]],\n\n [[-3.4289e-06]],\n\n ...,\n\n [[-1.8404e-05]],\n\n [[-2.7684e-07]],\n\n [[-7.0000e-07]]],\n\n\n [[[-3.0275e-05]],\n\n [[-3.8914e-07]],\n\n [[-9.3595e-06]],\n\n ...,\n\n [[-2.3418e-06]],\n\n [[ 2.5546e-06]],\n\n [[-8.2901e-06]]],\n\n\n [[[ 1.2203e-05]],\n\n [[-1.4625e-05]],\n\n [[-4.1614e-07]],\n\n ...,\n\n [[ 3.2330e-07]],\n\n [[ 1.0722e-05]],\n\n [[ 1.1657e-05]]],\n\n\n ...,\n\n\n [[[-2.4841e-06]],\n\n [[ 8.2127e-06]],\n\n [[-9.0002e-06]],\n\n ...,\n\n [[ 1.6559e-06]],\n\n [[-6.2795e-06]],\n\n [[-2.2904e-06]]],\n\n\n [[[-1.4244e-05]],\n\n [[ 4.7696e-06]],\n\n [[ 4.7066e-06]],\n\n ...,\n\n [[-4.4370e-06]],\n\n [[ 7.8795e-07]],\n\n [[-1.1387e-05]]],\n\n\n [[[-4.4736e-06]],\n\n [[-1.2009e-05]],\n\n [[-3.9854e-06]],\n\n ...,\n\n [[-1.1426e-05]],\n\n [[-2.2746e-06]],\n\n [[ 6.0591e-06]]]]), 'exp_avg_sq': tensor([[[[2.7421e-08]],\n\n [[1.4584e-08]],\n\n [[4.3605e-09]],\n\n ...,\n\n [[1.2210e-08]],\n\n [[4.6453e-09]],\n\n [[3.5149e-08]]],\n\n\n [[[5.0527e-08]],\n\n [[3.1133e-08]],\n\n [[1.2573e-08]],\n\n ...,\n\n [[3.9771e-08]],\n\n [[1.4998e-08]],\n\n [[7.6493e-08]]],\n\n\n [[[2.1112e-08]],\n\n [[2.1581e-08]],\n\n [[6.5711e-09]],\n\n ...,\n\n [[2.8326e-08]],\n\n [[6.5899e-09]],\n\n [[8.5156e-08]]],\n\n\n ...,\n\n\n [[[1.4241e-08]],\n\n [[2.3776e-08]],\n\n [[8.6663e-09]],\n\n ...,\n\n [[7.9382e-09]],\n\n [[4.8743e-09]],\n\n [[2.5298e-08]]],\n\n\n [[[1.3090e-08]],\n\n [[8.9297e-09]],\n\n [[1.0114e-08]],\n\n ...,\n\n [[2.8701e-08]],\n\n [[3.8160e-09]],\n\n [[1.9168e-07]]],\n\n\n [[[1.0604e-08]],\n\n [[1.2115e-08]],\n\n [[6.7958e-09]],\n\n ...,\n\n [[1.0982e-08]],\n\n [[6.8929e-09]],\n\n [[1.0273e-07]]]])}, 112: {'step': 7160, 'exp_avg': tensor([-9.1862e-05, -7.0039e-05, 2.8246e-05, 4.7080e-05, -1.3291e-05,\n -3.2284e-05, -1.0027e-04, -1.3148e-04, 5.0495e-05, 3.8080e-05,\n 5.1582e-06, -1.1086e-04, 8.1274e-05, -1.3309e-04, 4.0152e-05,\n -3.6721e-05, 1.0517e-04, 5.5461e-05, 6.1122e-05, -3.4476e-06,\n 4.1632e-05, 7.7984e-05, -4.9094e-05, -8.5842e-05, 2.0564e-09,\n -9.4581e-05, 1.4907e-04, -6.9991e-05, -1.0691e-06, 1.9327e-04,\n -2.3504e-05, 6.8545e-05, -9.8022e-05, -4.4582e-06, 5.4528e-05,\n 8.9520e-05, 5.7946e-05, -7.8373e-05, 2.7585e-05, 2.2830e-04,\n 1.1467e-04, 4.7158e-05, 1.1150e-04, 1.2188e-04, -8.7092e-06,\n 2.7082e-05, -1.0291e-05, 1.2703e-05, 3.8417e-05, -5.9894e-05,\n 5.6753e-05, -4.0889e-05, -7.8577e-05, 4.4061e-05, -2.6885e-05,\n -8.4275e-06, 1.2395e-04, -1.9772e-05, 3.8268e-05, -2.0870e-05,\n -4.3591e-05, -1.0476e-05, 1.4561e-04, -1.0683e-05, 2.4026e-04,\n -2.7815e-05, 1.1802e-04, 9.1986e-05, -6.8671e-05, 8.7191e-05,\n -9.3268e-05, -1.0754e-04, 3.2707e-05, 8.1770e-06, 4.3904e-05,\n -4.4278e-05, -1.0919e-05, -3.8831e-05, -1.0842e-04, 7.0965e-05,\n 1.0744e-04, 3.7712e-05, -1.1798e-05, -5.0945e-05, 6.1758e-07,\n -4.3744e-05, -1.0198e-04, -3.9166e-05, 1.1688e-04, -5.1132e-05,\n -1.2161e-04, 1.0174e-05, 8.6240e-05, 7.2929e-05, -5.0115e-05,\n 6.5527e-05, 3.4687e-04, -2.8983e-05, 1.2718e-04, 5.7383e-05,\n -7.3937e-05, 7.4224e-06, -8.9128e-05, 1.6873e-04, 2.6950e-05,\n 6.5393e-05, 1.4333e-04, -1.4262e-05, 8.9653e-05, -8.4555e-05,\n 9.6657e-05, 5.7092e-05, -1.7698e-04, -1.0593e-04, -2.2411e-06,\n -1.2627e-04, 1.1211e-05, -1.2181e-04, -7.7476e-05, 6.3524e-05,\n -2.9844e-05, 1.3509e-04, -3.4738e-05, 1.6884e-05, -9.4715e-06,\n -5.5189e-05, -2.3633e-05, 4.6084e-05, 8.3700e-05, -5.7562e-05,\n 3.3886e-05, -6.1321e-05, -7.7973e-05, -3.1720e-05, 4.4419e-05,\n 8.3395e-05, -6.5590e-06, 2.9120e-06, 1.6212e-05, -5.8275e-05,\n -1.2716e-05, -2.0396e-05, 1.3249e-05, 3.6325e-05, -1.5693e-04,\n -6.6403e-05, -1.0389e-04, -7.4109e-05, 2.1711e-05, 9.5628e-05,\n 4.7003e-06, -4.8481e-05, 5.1856e-05, 2.0363e-04, -4.5421e-05,\n 4.8325e-05, 3.4727e-05, -3.2031e-05, 2.5182e-05, -4.1503e-05,\n 5.1640e-05, 6.6428e-05, -6.9083e-06, -5.7079e-06, 1.9469e-05,\n 9.1166e-05, -6.5067e-05, 2.4276e-05, -6.5787e-06, 1.1303e-04,\n -2.8003e-05, 1.0787e-05, 6.6372e-05, 7.8451e-05, -8.1028e-05,\n -4.2079e-05, -2.4212e-05, 5.7609e-05, 4.5882e-05, -1.0482e-04,\n -6.5431e-06, -8.1604e-05, -1.6320e-04, -8.4725e-05, 1.1362e-04,\n -8.9273e-05, -1.3068e-04, 9.6503e-05, -4.0618e-05, 8.6083e-05,\n -6.4521e-05, -2.1470e-05, -6.1662e-05, -8.2765e-05, -8.4725e-05,\n -4.6264e-05, 7.0766e-06, 9.8685e-05, 2.0741e-05, -2.4666e-05,\n -4.8871e-05, 3.2449e-06, -5.6372e-05, -8.1283e-05, -9.1836e-05,\n -2.5968e-06, -3.1450e-05, 2.1677e-06, -5.8431e-05, 7.7325e-05,\n -1.3134e-04, -6.4325e-05, 8.8102e-05, 2.4032e-04, -2.1136e-04,\n -5.6015e-05, -7.3381e-06, -1.8524e-06, 8.0369e-05, 1.7798e-05,\n -5.3242e-05, 4.3122e-05, -4.9976e-05, -6.9799e-05, 5.8105e-05,\n 6.6274e-05, -6.0693e-07, 1.8538e-05, -7.3324e-05, 4.7929e-06,\n -2.2129e-05, 2.3715e-05, -5.5769e-05, -4.0919e-05, -2.5142e-04,\n 6.4623e-05, 4.1524e-05, -5.8495e-05, 6.5067e-05, -1.4418e-05,\n 1.1318e-04, -6.0221e-05, 4.4271e-05, -2.4338e-05, -3.1359e-06,\n 1.6569e-05, -8.6131e-05, 1.7121e-04, 2.5160e-05, -1.1040e-04,\n -1.0130e-04, 3.4481e-05, -6.2738e-06, 1.3552e-05, -1.0638e-05,\n 4.0317e-05]), 'exp_avg_sq': tensor([5.1196e-07, 2.0087e-06, 1.9832e-06, 1.1045e-06, 6.5945e-07, 1.3127e-06,\n 2.0854e-06, 3.0965e-06, 1.3063e-06, 1.0453e-06, 5.3954e-07, 3.0345e-06,\n 1.2476e-06, 1.5968e-06, 1.1698e-06, 5.7230e-07, 1.7267e-06, 1.4296e-06,\n 2.3906e-06, 2.9350e-06, 8.6498e-07, 1.5528e-06, 1.6599e-06, 9.8287e-07,\n 1.3438e-06, 2.4172e-06, 1.8817e-06, 2.8329e-07, 8.9264e-07, 4.0087e-06,\n 3.0213e-07, 1.3584e-06, 9.2543e-07, 2.2822e-07, 1.9595e-06, 5.9433e-07,\n 6.1247e-07, 9.5808e-07, 1.0146e-06, 1.0369e-06, 1.1643e-06, 2.6589e-06,\n 9.9975e-07, 1.3440e-06, 4.0884e-07, 4.3333e-07, 5.3911e-07, 4.0336e-07,\n 8.4943e-07, 2.4943e-07, 7.9737e-07, 1.0623e-06, 2.1365e-06, 5.6532e-07,\n 2.1114e-06, 9.2292e-07, 8.3436e-07, 5.3713e-07, 5.1740e-07, 5.3364e-07,\n 5.9875e-07, 1.3020e-06, 1.5368e-06, 2.5541e-06, 9.3685e-07, 6.3576e-07,\n 1.0840e-06, 2.2109e-06, 6.7840e-07, 1.0222e-06, 1.1175e-06, 1.4062e-06,\n 7.6277e-07, 8.1309e-07, 5.4404e-07, 1.0149e-06, 3.1557e-07, 6.1580e-07,\n 1.4910e-06, 1.9509e-06, 1.1528e-06, 7.1631e-07, 2.9501e-07, 1.1667e-06,\n 3.5912e-07, 6.4206e-07, 3.5589e-07, 1.1147e-06, 3.0619e-06, 5.9412e-07,\n 8.0858e-07, 5.1327e-06, 2.2382e-06, 1.0601e-05, 6.0425e-07, 3.9513e-07,\n 2.3374e-06, 1.7678e-06, 3.1921e-06, 2.7621e-07, 1.3368e-06, 1.2404e-06,\n 8.4494e-07, 2.0454e-06, 5.8332e-07, 6.6910e-07, 1.4488e-06, 1.8708e-07,\n 2.6407e-06, 9.1952e-07, 1.2610e-06, 9.1295e-07, 1.5370e-06, 4.6752e-07,\n 5.7585e-07, 1.3839e-06, 9.1815e-07, 7.5450e-07, 3.7536e-06, 2.1532e-06,\n 9.5144e-07, 1.3928e-06, 2.5237e-07, 1.0793e-06, 7.3334e-07, 2.3423e-06,\n 4.1337e-07, 5.7324e-07, 1.0067e-06, 5.3829e-07, 4.3266e-07, 3.5058e-07,\n 1.7661e-06, 2.7032e-06, 3.9049e-06, 9.9673e-07, 2.1027e-06, 1.9016e-06,\n 1.3321e-06, 4.4999e-07, 1.0718e-06, 1.0715e-06, 1.0232e-06, 4.5883e-07,\n 1.6360e-06, 1.7278e-06, 7.0032e-07, 3.3333e-06, 1.2176e-06, 4.7011e-07,\n 2.0583e-06, 5.0830e-07, 1.8364e-06, 4.3535e-06, 6.8400e-07, 4.9108e-07,\n 1.3774e-06, 1.0401e-06, 9.3389e-07, 1.5317e-06, 8.4403e-07, 5.5078e-07,\n 7.6079e-07, 6.9107e-07, 3.1067e-07, 2.8713e-06, 4.0903e-07, 5.6589e-07,\n 4.7131e-07, 8.6598e-07, 1.4326e-06, 1.2100e-06, 1.8726e-06, 3.4119e-06,\n 4.4272e-07, 1.2974e-06, 9.1695e-07, 8.9140e-07, 2.5844e-07, 2.1903e-06,\n 1.2210e-06, 5.9860e-06, 1.5090e-06, 2.2643e-06, 1.9561e-06, 4.9137e-07,\n 6.7459e-07, 5.2399e-07, 6.7642e-07, 1.5705e-06, 1.4247e-06, 4.2261e-07,\n 5.5261e-07, 6.5089e-07, 5.1535e-07, 1.0712e-06, 1.4872e-06, 1.1489e-06,\n 8.2850e-07, 2.9956e-07, 6.9054e-07, 1.1568e-06, 2.1216e-06, 1.2105e-06,\n 1.2259e-06, 2.1974e-06, 9.2459e-07, 5.7828e-07, 1.2489e-06, 6.4006e-07,\n 1.9928e-06, 1.2228e-06, 1.6273e-06, 7.9736e-07, 3.0215e-06, 1.8190e-06,\n 5.4003e-07, 9.8406e-07, 1.7008e-06, 2.9558e-06, 5.9224e-07, 5.6815e-07,\n 7.6569e-07, 1.6445e-06, 2.0108e-06, 1.7029e-06, 1.1599e-06, 6.4563e-07,\n 7.2551e-07, 2.9495e-06, 1.2165e-06, 3.4898e-07, 4.7919e-07, 3.6266e-06,\n 2.7381e-06, 3.7057e-07, 5.4779e-07, 9.6202e-07, 2.0047e-06, 2.8756e-07,\n 1.0090e-06, 1.0198e-06, 6.3959e-07, 4.1300e-07, 6.4577e-07, 1.1200e-06,\n 5.1642e-07, 9.5360e-07, 1.1242e-06, 1.3824e-06, 1.7037e-06, 1.9142e-06,\n 4.1442e-07, 8.5968e-07, 8.6918e-07, 1.7905e-06])}, 113: {'step': 7160, 'exp_avg': tensor([-4.8413e-05, -1.1280e-05, -1.7109e-05, -5.4527e-06, -3.2084e-05,\n -3.3364e-05, -1.2742e-05, -8.3419e-05, 7.1789e-05, -1.1144e-05,\n 5.7711e-06, -6.2136e-05, -1.1163e-05, -2.4208e-05, 2.8003e-05,\n -2.4430e-05, 6.1690e-05, 3.2223e-05, 1.7003e-04, 2.3669e-05,\n 6.6713e-06, 5.1669e-05, -2.0929e-06, -5.1818e-05, -3.7863e-05,\n -7.6367e-05, 9.4839e-05, -3.0574e-05, 5.0314e-05, 1.6472e-04,\n -2.8402e-05, 7.9079e-05, -3.8625e-05, 4.2378e-06, 1.5310e-05,\n 6.3510e-05, 2.3598e-05, 2.1712e-05, 6.9220e-06, 8.3799e-05,\n 8.8293e-05, 7.6678e-05, 1.4215e-04, 1.1519e-04, 1.8438e-05,\n 2.6668e-05, -2.7511e-05, 2.0285e-05, 2.2566e-05, -5.6256e-05,\n 8.1365e-05, -3.0514e-05, -4.2340e-05, 3.0647e-05, -8.0933e-06,\n -2.0323e-06, 8.8042e-05, -3.2660e-05, 6.1979e-06, -6.7374e-05,\n -2.2428e-05, -5.7451e-05, 5.4380e-05, -4.9381e-06, 1.6083e-04,\n -1.9223e-05, 4.9006e-05, 1.1173e-04, -4.4895e-05, 8.5131e-06,\n -4.6522e-05, -1.6978e-05, 8.1426e-06, 2.0389e-05, 2.5362e-05,\n -5.0600e-05, 3.7476e-06, -1.8305e-05, -2.4667e-05, 1.4856e-04,\n 3.6424e-05, 1.4012e-05, -7.3502e-06, -1.9880e-05, 7.5727e-06,\n 2.2324e-06, -5.5873e-05, -3.0598e-05, 1.5155e-04, -6.7236e-06,\n -7.3469e-05, -3.9606e-05, 6.6033e-05, 4.2239e-05, 1.7417e-05,\n 4.9482e-05, -8.6477e-06, -4.5905e-05, 5.6411e-05, 4.0556e-05,\n -3.7737e-05, 4.6474e-05, -4.5239e-05, 8.2104e-05, 9.1068e-06,\n 7.2103e-05, 8.7026e-05, -7.1510e-06, 7.2293e-05, -6.1829e-05,\n 6.5096e-05, 3.4842e-05, -1.3258e-04, -6.8047e-05, 9.1387e-06,\n -1.1958e-04, 4.5144e-05, -6.1614e-05, -7.1471e-05, 3.8320e-05,\n -3.4525e-05, 6.0154e-05, -3.0322e-05, 1.3443e-05, -1.7541e-05,\n -3.8960e-05, -8.9976e-06, 9.1178e-05, 4.0088e-05, -4.5275e-05,\n 4.4098e-05, -6.2322e-05, -9.4343e-05, 6.4476e-05, 2.2566e-05,\n 5.7111e-05, -3.3189e-05, -5.4992e-05, 7.4427e-05, -3.4930e-06,\n -7.7448e-06, -5.5345e-05, -2.0719e-05, 1.7966e-05, -1.4544e-04,\n 2.7504e-05, -4.9994e-05, -1.3438e-05, -1.5501e-05, 9.1371e-05,\n 1.2836e-04, -1.6667e-05, 1.9355e-05, 1.0171e-04, -5.9379e-05,\n 7.7346e-06, -2.3551e-08, 8.5089e-07, -2.3867e-06, 1.0259e-04,\n 1.2594e-05, 6.0445e-05, -5.4897e-05, 1.3365e-05, 4.6159e-05,\n 5.9777e-05, -7.8360e-05, 1.7601e-05, 6.9951e-06, 1.3455e-04,\n 3.0911e-05, 2.5586e-06, 2.9045e-07, -1.0472e-04, -9.3360e-05,\n -7.2710e-06, 1.7313e-06, 8.9488e-07, 4.0446e-05, -6.5176e-05,\n 4.0738e-05, 1.5481e-04, -8.4837e-05, -5.1193e-05, 5.7922e-05,\n -8.2226e-05, -6.6946e-05, 4.1009e-05, 7.8289e-06, 2.4377e-05,\n -2.1357e-05, -1.3761e-05, -4.4403e-05, -5.8358e-05, -5.8459e-05,\n -2.6042e-05, -2.5392e-06, 2.4433e-05, 3.0085e-05, -2.1545e-05,\n -3.1167e-05, 2.3898e-06, -1.7491e-05, -5.6199e-05, -4.2231e-05,\n 4.2122e-06, -3.4299e-05, 1.6894e-06, -3.3632e-05, 5.8261e-05,\n -1.3400e-04, -8.2907e-05, 6.2199e-05, 1.4412e-04, -2.0516e-04,\n 6.8489e-05, -4.9726e-06, -6.1636e-05, 4.2961e-05, 3.9542e-05,\n -2.2212e-05, 1.5224e-05, -8.1840e-05, -4.1216e-05, 7.7431e-05,\n -1.7516e-05, 4.5142e-05, 2.3059e-05, -1.4547e-05, -5.4945e-05,\n 8.2606e-05, 2.7938e-05, -5.5043e-05, -3.6711e-06, -6.0229e-05,\n 1.8764e-05, 3.9867e-05, -8.8385e-05, 4.7780e-05, -5.7193e-07,\n 3.9100e-05, -4.5824e-05, 4.3266e-05, -1.6188e-05, -2.2764e-05,\n 3.2279e-05, -4.7893e-05, 1.2848e-04, 6.6517e-06, -6.8489e-05,\n -6.1281e-05, 1.2108e-05, -1.1279e-05, 3.7112e-07, -3.3995e-05,\n 3.5802e-05]), 'exp_avg_sq': tensor([6.4846e-07, 8.8490e-07, 2.2677e-06, 6.3334e-07, 3.3363e-07, 3.4026e-07,\n 5.1416e-07, 1.1010e-06, 9.7881e-07, 4.6902e-07, 2.5559e-07, 7.3803e-07,\n 9.5409e-07, 1.0840e-06, 4.5002e-07, 2.6060e-07, 5.8814e-07, 1.1221e-06,\n 1.7141e-06, 1.6204e-06, 3.9300e-07, 6.7682e-07, 1.0021e-06, 6.9493e-07,\n 6.3909e-07, 1.6592e-06, 7.4942e-07, 9.8907e-08, 7.1109e-07, 1.4823e-06,\n 1.6988e-07, 8.0233e-07, 3.3013e-07, 7.6301e-08, 6.2388e-07, 3.4976e-07,\n 7.1367e-07, 1.1476e-06, 8.4690e-07, 4.7743e-07, 4.1353e-07, 1.7161e-06,\n 7.6264e-07, 7.0553e-07, 1.5921e-07, 2.0354e-07, 5.1546e-07, 2.7640e-07,\n 5.5187e-07, 1.9993e-07, 7.0577e-07, 5.9871e-07, 1.1249e-06, 1.7190e-07,\n 9.1058e-07, 5.4468e-07, 1.2026e-06, 5.6024e-07, 4.4395e-07, 5.4999e-07,\n 2.3161e-07, 1.1554e-06, 1.2214e-06, 7.8373e-07, 5.1577e-07, 4.6909e-07,\n 2.1427e-06, 1.2104e-06, 1.8169e-07, 5.8674e-07, 5.7496e-07, 7.0253e-07,\n 3.2890e-07, 6.3471e-07, 1.9730e-07, 7.7404e-07, 1.2922e-07, 5.2347e-07,\n 1.1820e-06, 8.2614e-07, 1.2339e-06, 5.0673e-07, 1.2742e-07, 3.6926e-07,\n 2.3068e-07, 2.9916e-07, 2.0057e-07, 6.2982e-07, 1.0022e-06, 2.4932e-07,\n 4.3931e-07, 1.1413e-06, 6.3301e-07, 1.6432e-06, 5.1984e-07, 1.6009e-07,\n 2.8871e-06, 1.0016e-06, 1.3661e-06, 1.2154e-07, 2.2577e-07, 9.7996e-07,\n 2.4449e-07, 7.4594e-07, 3.4393e-07, 5.0312e-07, 4.8629e-07, 1.2774e-07,\n 1.1686e-06, 5.9862e-07, 5.2811e-07, 4.7635e-07, 1.9041e-06, 4.4623e-07,\n 1.5104e-07, 1.2121e-06, 5.5410e-07, 3.5600e-07, 1.8375e-06, 1.8188e-06,\n 4.2736e-07, 6.0241e-07, 1.4779e-07, 3.8603e-07, 4.1166e-07, 1.8161e-06,\n 1.7547e-07, 3.0066e-07, 8.6419e-08, 9.2921e-08, 2.5258e-07, 2.5782e-07,\n 1.0376e-06, 1.4041e-06, 9.7360e-07, 3.5689e-07, 1.5191e-06, 1.5906e-06,\n 8.0775e-07, 3.0930e-07, 4.4319e-07, 6.4165e-07, 1.5277e-06, 1.9123e-07,\n 9.6945e-07, 1.5918e-06, 1.7943e-07, 1.1673e-06, 7.6289e-07, 5.5340e-07,\n 1.6220e-06, 3.9419e-07, 9.3432e-07, 7.0468e-07, 6.2906e-07, 2.2619e-07,\n 4.0594e-07, 2.4617e-07, 4.2130e-07, 1.7718e-06, 5.0841e-07, 3.7232e-07,\n 6.7865e-07, 3.6216e-07, 2.2640e-07, 1.2745e-06, 5.4780e-07, 4.3823e-07,\n 1.6518e-07, 5.2938e-07, 6.4195e-07, 5.3313e-07, 1.4276e-06, 1.2753e-06,\n 4.4693e-07, 1.1093e-06, 5.9331e-07, 3.9397e-07, 1.1470e-07, 6.3020e-07,\n 1.2995e-06, 2.2836e-06, 7.4259e-07, 9.5869e-07, 6.6135e-07, 4.4634e-07,\n 2.7062e-07, 3.0398e-07, 7.5028e-07, 9.6287e-07, 8.0746e-07, 2.2619e-07,\n 3.2409e-07, 5.8874e-07, 2.8792e-07, 6.6248e-07, 5.7145e-07, 1.1091e-06,\n 5.4892e-07, 2.0548e-07, 2.5220e-07, 4.8660e-07, 5.2766e-07, 2.5902e-07,\n 5.5114e-07, 2.3027e-06, 4.8421e-07, 4.4801e-07, 3.9401e-07, 7.1511e-07,\n 8.6132e-07, 5.4633e-07, 5.8822e-07, 5.0871e-07, 1.3876e-06, 9.1409e-07,\n 1.9771e-07, 8.9479e-07, 4.8652e-07, 8.6122e-07, 2.2252e-07, 2.5088e-07,\n 5.4153e-07, 1.6287e-06, 1.4659e-06, 1.6473e-06, 1.1491e-06, 2.8611e-07,\n 5.7842e-07, 1.1482e-06, 1.2270e-06, 1.7953e-07, 1.9878e-07, 5.2371e-07,\n 1.1393e-06, 2.9517e-07, 5.5590e-07, 6.8565e-07, 1.6754e-06, 1.5762e-07,\n 3.6556e-07, 7.4459e-07, 3.7850e-07, 5.5763e-07, 6.2211e-07, 4.3093e-07,\n 2.6455e-07, 4.2377e-07, 9.3022e-07, 8.3350e-07, 6.0566e-06, 8.2739e-07,\n 4.2187e-07, 4.6620e-07, 5.6991e-07, 7.8362e-07])}, 114: {'step': 7160, 'exp_avg': tensor([[[[ 1.8951e-06, -3.8701e-07, -4.6399e-06],\n [-1.5180e-06, 4.4196e-06, 4.3987e-06],\n [-1.1273e-07, 2.4614e-06, 3.9189e-06]],\n\n [[-5.2527e-06, 3.1771e-07, -1.1588e-06],\n [-4.9254e-07, -1.6079e-06, -1.9897e-06],\n [ 5.7766e-06, 3.0265e-07, 7.4041e-07]],\n\n [[-2.6724e-06, 4.0956e-06, 3.2327e-06],\n [ 2.5911e-07, -1.4205e-06, -3.8404e-07],\n [ 1.8195e-06, 5.9311e-07, -5.4584e-07]],\n\n ...,\n\n [[-1.1534e-07, -1.8306e-08, -3.4858e-07],\n [ 1.2945e-06, -2.6318e-06, -7.8669e-07],\n [-1.6078e-06, 6.7774e-08, 1.7793e-06]],\n\n [[ 1.9762e-06, 3.3937e-07, -1.2036e-07],\n [ 1.5903e-06, 1.9780e-06, 8.1915e-07],\n [-7.4545e-07, 5.0834e-07, 7.4857e-08]],\n\n [[ 2.9009e-06, 2.4473e-06, 3.6157e-06],\n [ 4.7850e-06, 4.2045e-06, 2.3615e-06],\n [ 1.4912e-06, 1.7047e-06, 1.6510e-06]]],\n\n\n [[[-1.4213e-05, 1.1025e-05, 3.9982e-06],\n [-1.9126e-05, 2.0039e-05, 4.5437e-06],\n [-1.4954e-06, -2.1092e-05, -9.3701e-06]],\n\n [[ 2.1486e-05, 2.5584e-05, 1.9382e-05],\n [ 2.6699e-06, 2.6632e-05, 5.8275e-06],\n [ 1.1365e-05, 1.3270e-05, -3.0075e-06]],\n\n [[ 2.3201e-05, -2.0061e-07, -9.1932e-07],\n [ 5.7565e-06, 8.8640e-06, 1.0841e-05],\n [ 2.3826e-06, -8.1674e-06, -2.4840e-08]],\n\n ...,\n\n [[-5.8169e-07, -2.9277e-06, 1.7296e-06],\n [-6.2982e-06, -1.1269e-05, -3.6207e-06],\n [-8.5162e-07, 3.6069e-06, -1.0807e-07]],\n\n [[ 2.9981e-06, -2.9124e-06, 7.5761e-07],\n [-2.1315e-06, -7.2298e-06, 3.0454e-06],\n [ 1.2715e-05, 6.1500e-06, 8.7646e-06]],\n\n [[-9.8992e-07, 3.3034e-06, 2.6076e-06],\n [-3.2578e-06, -1.7804e-06, -1.1145e-07],\n [ 1.4288e-07, -2.0392e-06, 5.3204e-07]]],\n\n\n [[[-1.8229e-05, -9.5011e-06, -1.0135e-06],\n [-2.1315e-05, -2.5770e-06, 2.3188e-06],\n [-2.6205e-05, -5.3875e-06, -1.2308e-05]],\n\n [[ 5.9102e-06, 1.6836e-05, 1.5739e-05],\n [-1.0801e-05, 7.8441e-07, 1.0040e-05],\n [-2.3487e-05, -5.9752e-06, 1.2130e-05]],\n\n [[ 5.5399e-06, -3.6299e-06, -5.4931e-06],\n [ 1.3371e-05, 1.2341e-05, 2.2567e-06],\n [ 5.3987e-06, 3.8627e-06, -9.0499e-07]],\n\n ...,\n\n [[ 4.0629e-06, -2.3399e-06, -7.2473e-06],\n [ 4.5515e-06, 1.1721e-06, 6.9497e-07],\n [-8.4197e-07, -1.5251e-06, 7.0491e-06]],\n\n [[ 1.6007e-06, 1.8942e-06, 2.9206e-06],\n [ 1.2894e-06, 7.2185e-07, -4.3265e-06],\n [ 6.6216e-06, 1.0447e-06, 4.8748e-06]],\n\n [[ 8.3674e-06, 4.2559e-06, 7.6667e-06],\n [ 9.6659e-06, 6.1485e-06, 7.4777e-06],\n [ 1.1603e-05, 7.7802e-06, 6.9273e-06]]],\n\n\n ...,\n\n\n [[[ 3.2209e-07, -6.0578e-06, -1.6266e-05],\n [ 4.0591e-06, -7.3788e-06, -8.5517e-06],\n [-1.0355e-05, -9.4771e-06, -5.1192e-06]],\n\n [[ 2.3765e-06, 2.0765e-06, -8.4861e-06],\n [ 9.1295e-07, 1.5281e-06, -1.4558e-05],\n [ 4.5199e-06, -2.3631e-06, -1.3026e-05]],\n\n [[-1.3724e-06, 4.9495e-06, 1.4704e-06],\n [ 4.9287e-07, -5.3780e-06, -3.1855e-06],\n [-2.3012e-06, -2.4851e-06, -4.3103e-07]],\n\n ...,\n\n [[ 9.9128e-08, 2.6293e-06, -3.4632e-07],\n [ 8.5502e-07, -5.0728e-06, -1.4120e-06],\n [ 3.5581e-06, 2.0666e-06, 2.9308e-08]],\n\n [[ 3.3085e-07, 3.1973e-06, 8.6703e-07],\n [ 3.3854e-06, 2.3198e-08, -1.5004e-06],\n [ 5.2157e-06, 4.6727e-06, 3.3438e-06]],\n\n [[ 4.6146e-06, -6.3872e-07, 2.8819e-06],\n [-4.4609e-07, 1.4044e-06, 2.3752e-06],\n [-2.1639e-07, -3.7773e-06, -4.3018e-09]]],\n\n\n [[[ 2.5831e-06, 1.5524e-06, 1.1884e-05],\n [ 2.2792e-06, 1.7901e-06, 4.8888e-06],\n [-4.3591e-06, -1.2766e-06, -3.8276e-06]],\n\n [[-6.9593e-07, -3.5238e-06, -8.6273e-07],\n [-3.5621e-06, -5.3758e-06, 3.9306e-07],\n [-7.2636e-06, -7.8461e-06, -2.5285e-06]],\n\n [[ 5.8949e-06, 3.2736e-06, -3.2461e-06],\n [ 1.8965e-06, 1.4226e-06, 8.7397e-07],\n [ 2.9539e-06, 8.5435e-07, 5.5427e-07]],\n\n ...,\n\n [[-1.6252e-06, 7.6055e-07, 3.2261e-08],\n [-3.4247e-06, 8.1696e-07, -1.0355e-06],\n [ 2.5836e-06, 1.9410e-06, -1.2735e-06]],\n\n [[-2.5083e-06, -1.7533e-06, 7.4266e-07],\n [ 4.2235e-06, 1.7450e-06, -4.3782e-06],\n [ 2.3693e-06, -3.0273e-06, -2.0982e-06]],\n\n [[-7.0425e-06, -5.8410e-06, -2.7562e-06],\n [-5.8837e-06, -5.9295e-06, -2.0210e-06],\n [-1.9283e-06, -3.0280e-06, 5.8528e-07]]],\n\n\n [[[ 3.1856e-07, -8.5686e-08, 1.0268e-05],\n [-5.4546e-08, -2.0015e-06, 1.1302e-05],\n [-8.2782e-06, -1.2434e-05, -1.4780e-05]],\n\n [[ 6.8176e-06, -5.7518e-06, 8.9751e-06],\n [ 1.7442e-05, -1.5540e-05, 1.3525e-05],\n [-5.4372e-06, -1.2121e-06, 2.3184e-06]],\n\n [[ 1.0874e-05, -9.0670e-06, -5.8537e-06],\n [ 5.7439e-06, -1.2230e-05, -4.5945e-06],\n [-4.2846e-06, -6.1926e-06, -4.7200e-06]],\n\n ...,\n\n [[ 2.3388e-07, -5.9848e-07, 1.5653e-06],\n [-1.0121e-06, 1.6800e-06, 1.8502e-06],\n [-4.0686e-06, -2.4743e-07, 3.1229e-06]],\n\n [[ 2.1803e-06, -4.8361e-06, -1.0078e-06],\n [-4.0078e-06, -8.7679e-06, -8.1082e-06],\n [ 6.1160e-07, 2.2013e-06, 2.6366e-06]],\n\n [[ 9.5266e-07, 1.8388e-06, 3.2858e-07],\n [ 3.4417e-06, 6.3660e-06, 1.0546e-06],\n [ 9.5954e-07, 1.2189e-06, -4.5680e-07]]]]), 'exp_avg_sq': tensor([[[[1.1315e-09, 1.8942e-09, 1.3909e-09],\n [1.0401e-09, 2.2688e-09, 1.4489e-09],\n [1.1982e-09, 1.6701e-09, 1.2808e-09]],\n\n [[3.7839e-09, 4.7292e-09, 4.6059e-09],\n [1.3669e-09, 2.0472e-09, 2.8752e-09],\n [9.6079e-10, 1.6183e-09, 3.3628e-09]],\n\n [[2.0160e-09, 1.6887e-09, 2.4366e-09],\n [1.5762e-09, 1.4890e-09, 1.7701e-09],\n [1.4175e-09, 1.6771e-09, 1.7091e-09]],\n\n ...,\n\n [[7.7142e-10, 5.0975e-10, 4.4243e-10],\n [8.2373e-10, 1.4548e-09, 1.2140e-09],\n [2.4625e-09, 2.6809e-09, 3.3839e-09]],\n\n [[7.4464e-10, 6.1437e-10, 7.4005e-10],\n [1.1942e-09, 1.0769e-09, 7.5935e-10],\n [1.4673e-09, 2.7979e-09, 2.6529e-09]],\n\n [[1.7478e-09, 2.6123e-09, 1.3097e-09],\n [8.9694e-10, 1.2042e-09, 7.7708e-10],\n [1.1563e-09, 1.2171e-09, 1.1059e-09]]],\n\n\n [[[1.5675e-08, 1.6339e-08, 1.5591e-08],\n [1.9589e-08, 2.4935e-08, 1.6687e-08],\n [1.5515e-08, 2.1781e-08, 1.9870e-08]],\n\n [[1.9870e-08, 1.5911e-08, 2.8612e-08],\n [2.2029e-08, 2.3809e-08, 1.9575e-08],\n [2.5731e-08, 2.3203e-08, 1.9912e-08]],\n\n [[1.3475e-08, 1.0356e-08, 1.2937e-08],\n [1.2611e-08, 1.1898e-08, 1.3070e-08],\n [1.5326e-08, 1.3827e-08, 1.2588e-08]],\n\n ...,\n\n [[8.0850e-09, 9.3178e-09, 7.5628e-09],\n [8.0521e-09, 1.2076e-08, 4.9704e-09],\n [9.9142e-09, 6.9016e-09, 8.8674e-09]],\n\n [[7.0855e-09, 1.0074e-08, 8.9959e-09],\n [7.2115e-09, 9.2340e-09, 6.5619e-09],\n [8.0767e-09, 1.4815e-08, 1.0002e-08]],\n\n [[1.3143e-08, 8.4547e-09, 1.1553e-08],\n [7.7122e-09, 7.5112e-09, 1.0431e-08],\n [8.7479e-09, 7.3213e-09, 6.3828e-09]]],\n\n\n [[[1.7634e-08, 1.6719e-08, 1.8619e-08],\n [1.8114e-08, 1.6898e-08, 1.8641e-08],\n [1.9773e-08, 2.3530e-08, 2.3404e-08]],\n\n [[2.2325e-08, 2.0603e-08, 4.7432e-08],\n [3.8114e-08, 3.2172e-08, 4.0833e-08],\n [3.0166e-08, 4.0521e-08, 5.4655e-08]],\n\n [[2.8528e-08, 2.0868e-08, 2.0405e-08],\n [2.5486e-08, 2.2231e-08, 1.4477e-08],\n [1.7704e-08, 2.2228e-08, 1.5908e-08]],\n\n ...,\n\n [[1.6454e-08, 6.6830e-09, 1.0162e-08],\n [1.0817e-08, 8.7666e-09, 8.1343e-09],\n [1.1838e-08, 1.0158e-08, 6.3755e-09]],\n\n [[6.6636e-09, 6.9903e-09, 6.4077e-09],\n [4.3951e-09, 5.3229e-09, 5.8872e-09],\n [5.6611e-09, 7.9526e-09, 6.6041e-09]],\n\n [[1.1654e-08, 9.3633e-09, 2.6974e-08],\n [1.0544e-08, 9.7163e-09, 1.1752e-08],\n [1.1323e-08, 1.2224e-08, 1.4633e-08]]],\n\n\n ...,\n\n\n [[[9.1597e-09, 1.1677e-08, 7.4518e-09],\n [1.0321e-08, 1.2512e-08, 9.0676e-09],\n [7.4025e-09, 1.1410e-08, 9.0508e-09]],\n\n [[8.6807e-09, 9.1367e-09, 7.7295e-09],\n [1.2743e-08, 1.2196e-08, 7.0128e-09],\n [1.8702e-08, 1.2650e-08, 9.0114e-09]],\n\n [[6.7823e-09, 4.9154e-09, 3.8006e-09],\n [8.6946e-09, 5.4129e-09, 4.3507e-09],\n [8.7064e-09, 6.3775e-09, 4.5092e-09]],\n\n ...,\n\n [[3.9807e-09, 4.4225e-09, 4.5778e-09],\n [1.1291e-08, 7.5201e-09, 5.9069e-09],\n [4.5788e-09, 7.6356e-09, 4.4783e-09]],\n\n [[6.4473e-09, 1.4740e-08, 6.8632e-09],\n [5.7512e-09, 1.3901e-08, 1.1386e-08],\n [7.5275e-09, 9.1606e-09, 6.8380e-09]],\n\n [[8.1672e-09, 3.8557e-09, 5.9001e-09],\n [1.3958e-08, 6.1998e-09, 4.0519e-09],\n [8.0461e-09, 4.6814e-09, 6.5139e-09]]],\n\n\n [[[8.3144e-09, 5.9474e-09, 5.4918e-09],\n [1.1658e-08, 1.0388e-08, 8.4790e-09],\n [1.4081e-08, 1.2588e-08, 1.0649e-08]],\n\n [[9.0976e-09, 7.0257e-09, 5.0010e-09],\n [1.2184e-08, 6.3960e-09, 5.0923e-09],\n [9.2745e-09, 5.9109e-09, 7.6284e-09]],\n\n [[5.6799e-09, 5.1895e-09, 5.0622e-09],\n [7.5896e-09, 6.9117e-09, 5.4737e-09],\n [7.5471e-09, 8.4481e-09, 6.6331e-09]],\n\n ...,\n\n [[4.7700e-09, 6.2189e-09, 6.2543e-09],\n [2.8876e-09, 3.5151e-09, 3.1980e-09],\n [2.8250e-09, 3.5761e-09, 2.9850e-09]],\n\n [[6.8380e-09, 4.8670e-09, 4.3216e-09],\n [4.3599e-09, 3.3979e-09, 5.2084e-09],\n [6.1637e-09, 5.7158e-09, 6.4880e-09]],\n\n [[5.2040e-09, 4.4925e-09, 6.1732e-09],\n [3.0470e-09, 3.6746e-09, 3.2343e-09],\n [3.2905e-09, 2.7870e-09, 4.2533e-09]]],\n\n\n [[[3.6410e-09, 3.6922e-09, 4.7422e-09],\n [4.3108e-09, 4.7998e-09, 5.6076e-09],\n [6.5729e-09, 8.3426e-09, 9.7339e-09]],\n\n [[5.5562e-09, 1.1818e-08, 1.5892e-08],\n [8.2194e-09, 1.3814e-08, 1.4099e-08],\n [9.5348e-09, 1.1362e-08, 1.7126e-08]],\n\n [[4.2414e-09, 3.8883e-09, 7.3185e-09],\n [4.6423e-09, 6.2822e-09, 4.5848e-09],\n [5.4929e-09, 6.0939e-09, 4.1100e-09]],\n\n ...,\n\n [[4.4015e-09, 2.2556e-09, 1.8552e-09],\n [5.4042e-09, 4.9877e-09, 2.1379e-09],\n [7.5381e-09, 5.7549e-09, 7.2030e-09]],\n\n [[4.1384e-09, 3.4600e-09, 2.0075e-09],\n [3.8527e-09, 3.7234e-09, 3.2594e-09],\n [4.1668e-09, 6.4372e-09, 5.8338e-09]],\n\n [[4.2274e-09, 3.9070e-09, 4.4562e-09],\n [5.5999e-09, 5.3740e-09, 3.1039e-09],\n [6.7748e-09, 4.6486e-09, 4.6915e-09]]]])}, 115: {'step': 7160, 'exp_avg': tensor([ 5.6552e-05, -6.7167e-06, 5.2326e-05, 4.9300e-05, 8.6749e-05,\n -3.1217e-05, -1.3083e-05, -3.8098e-06, -5.4073e-05, -1.4553e-05,\n 3.3276e-05, 2.2789e-05, 5.5767e-05, -4.4742e-06, -6.2015e-05,\n 4.4854e-04, -1.1453e-04, -3.7599e-05, 1.5064e-04, -3.5774e-05,\n -1.3392e-05, -5.9796e-05, -2.5716e-05, 6.0380e-05, 5.0204e-05,\n 5.8880e-05, -1.1916e-04, -2.0476e-06, -6.2773e-05, 4.4114e-05,\n -3.3587e-05, -5.0373e-05, -1.0778e-05, -6.1628e-05, 1.1277e-04,\n 5.9488e-05, -2.2233e-05, -1.4089e-07, 2.0995e-05, 3.2849e-05,\n -8.0356e-05, -5.1420e-05, -3.0647e-05, -1.1950e-05, 8.2841e-05,\n 6.1873e-05, 2.9223e-05, 1.4572e-05, 4.1376e-05, 9.6666e-06,\n 8.9486e-05, 2.6116e-05, -1.1429e-04, -2.4548e-04, -8.6856e-06,\n 9.3838e-05, 2.9063e-05, -2.2074e-05, -6.1928e-05, 6.7049e-05,\n 2.6544e-05, 3.0959e-04, -2.5487e-05, -3.4164e-05, 5.9037e-05,\n 8.2437e-06, -1.0419e-04, -1.3688e-04, 3.5025e-05, -1.0039e-05,\n 9.2493e-05, 1.6039e-04, 5.6359e-05, 3.9873e-05, 1.9919e-04,\n 6.3894e-04, 1.8425e-04, 2.0082e-05, -4.6790e-05, -1.5842e-04,\n -2.7470e-05, -8.4099e-06, 8.6994e-05, 8.3139e-05, -1.5040e-04,\n -2.0511e-05, -9.4220e-05, 3.8893e-05, -1.0681e-04, 2.9917e-05,\n 8.7531e-05, -8.1870e-05, -9.6225e-05, 5.0551e-05, 1.4351e-04,\n 1.4316e-04, 4.2339e-05, 8.7714e-05, -3.0119e-04, 6.6835e-05,\n -1.2353e-05, 1.3524e-04, -2.9829e-05, -1.5942e-05, 2.6082e-05,\n -6.6525e-05, -5.0480e-05, -7.6494e-07, 3.3400e-05, 1.0933e-05,\n 3.0212e-05, 5.1784e-05, -1.5222e-04, 1.6027e-05, -2.5026e-05,\n 4.3991e-05, 1.6680e-04, 3.1936e-05, -1.4481e-04, -2.6299e-05,\n 3.2498e-05, 4.3345e-05, 4.1928e-05, -1.7633e-05, 2.7489e-05,\n 1.0483e-04, -2.1194e-05, 3.9343e-06, -8.9948e-05, 1.9117e-05,\n -4.2870e-05, -3.4733e-05, -5.3212e-05, -2.1079e-04, 8.9934e-07,\n 1.7710e-04, -2.7316e-05, -1.7946e-05, -8.6194e-05, -6.6895e-05,\n 2.2463e-05, -1.0218e-04, 3.9648e-05, 4.1275e-05, 7.3580e-05,\n 7.6412e-05, 3.0590e-05, -1.7627e-05, -1.7188e-04, -6.8057e-05,\n -4.0114e-06, 1.0374e-04, -2.8837e-05, -1.1774e-06, -4.1880e-05,\n 1.2213e-05, -1.4204e-04, -1.8431e-05, -1.4793e-04, -1.3356e-04,\n 6.1889e-06, 1.9885e-05, -8.7579e-05, 3.9649e-05, 6.0634e-05,\n -5.3228e-05, -5.4983e-05, -1.6225e-04, -7.2909e-06, 9.5546e-05,\n -8.4077e-07, -8.6353e-05, 1.5302e-04, -8.8030e-05, -2.3359e-05,\n 1.1403e-05, 4.9819e-05, -1.8347e-05, 2.6444e-05, -8.4843e-08,\n 2.8625e-05, 1.0277e-04, 3.6414e-05, -3.4856e-05, -6.6069e-07,\n 3.6072e-05, -1.3776e-05, 5.2001e-06, -3.0739e-05, -5.3490e-05,\n 3.6297e-05, -4.2261e-06, 7.9397e-05, 4.1414e-05, 3.4204e-05,\n -1.4831e-04, -8.1920e-05, -6.9653e-05, -4.3670e-05, -3.8505e-05,\n 1.0748e-04, 9.4088e-05, -1.7175e-05, -2.2406e-04, -3.8886e-05,\n 2.8988e-05, 6.7206e-05, -3.2824e-05, 6.7263e-06, -3.0867e-05,\n -6.4531e-06, -7.3877e-06, 9.9317e-05, 5.6833e-05, 8.3643e-05,\n 8.7979e-05, -2.1312e-05, -2.2791e-05, -1.1318e-04, -8.2248e-06,\n -1.8878e-05, -1.0961e-05, -7.3995e-05, 6.0941e-05, 4.7791e-05,\n -7.5285e-05, 1.0679e-04, -2.1636e-05, -1.1115e-04, 3.2029e-05,\n 1.1482e-04, -6.5730e-05, 2.3249e-06, 8.0409e-05, 4.9903e-05,\n 1.9637e-05, 1.3938e-05, -1.0978e-05, 2.0246e-06, -1.2466e-05,\n -9.5527e-05, 5.0821e-05, -2.2756e-04, -5.5730e-05, 1.4751e-04,\n -1.1804e-04, -5.1198e-05, -1.9550e-05, -2.3237e-05, 2.5829e-05,\n -2.9411e-05, -2.3907e-05, 1.2635e-05, 3.5336e-05, 2.2546e-04,\n 4.8546e-05]), 'exp_avg_sq': tensor([2.2777e-07, 1.2057e-06, 1.5477e-06, 7.3048e-07, 1.7043e-06, 2.8913e-06,\n 2.0160e-06, 5.6348e-07, 1.3024e-06, 8.1176e-07, 1.1855e-06, 1.1465e-06,\n 3.0923e-07, 3.3113e-07, 3.4265e-07, 8.5279e-06, 7.8715e-07, 4.4413e-07,\n 8.0246e-07, 2.1533e-07, 5.3304e-06, 8.6978e-07, 1.4368e-06, 3.2727e-07,\n 3.1373e-07, 2.7886e-07, 2.5986e-06, 2.8357e-07, 6.1710e-07, 1.2976e-06,\n 4.2944e-07, 6.3397e-07, 3.7409e-07, 2.7029e-06, 1.0510e-06, 3.1779e-07,\n 5.6078e-07, 4.7233e-07, 1.1693e-07, 2.2638e-07, 1.3663e-06, 6.4224e-07,\n 8.7833e-07, 6.9670e-08, 1.3815e-06, 4.1574e-07, 2.1962e-07, 2.8131e-07,\n 2.4604e-06, 1.1248e-07, 4.2074e-07, 7.2033e-07, 5.1791e-07, 3.8274e-06,\n 3.3998e-07, 3.4792e-07, 1.8962e-07, 4.8453e-07, 1.4097e-06, 5.9328e-07,\n 1.6590e-06, 2.4729e-05, 6.6797e-07, 2.3738e-07, 3.2893e-07, 9.4825e-07,\n 6.9615e-07, 7.0342e-07, 1.6930e-07, 6.4633e-07, 1.6199e-06, 9.4514e-07,\n 1.5200e-07, 8.1821e-07, 7.3158e-07, 2.9113e-05, 2.2798e-06, 4.8736e-06,\n 1.8916e-06, 2.7753e-06, 7.4311e-07, 4.0594e-07, 6.1614e-07, 6.1553e-07,\n 8.2172e-07, 2.3812e-06, 3.6726e-06, 2.3517e-07, 2.5075e-06, 1.6275e-06,\n 8.6636e-07, 6.1413e-07, 1.0422e-06, 4.5788e-07, 9.3475e-07, 1.0045e-06,\n 7.3969e-07, 8.3418e-07, 5.0087e-06, 7.0041e-07, 7.6844e-07, 4.3870e-06,\n 6.8686e-07, 1.0714e-06, 2.1226e-07, 2.1153e-07, 6.5034e-07, 3.6560e-07,\n 1.8777e-06, 9.8335e-07, 4.7557e-07, 7.7070e-07, 1.1132e-06, 2.8041e-07,\n 2.6062e-07, 5.6038e-07, 3.8246e-07, 3.1240e-07, 1.0662e-06, 7.1195e-07,\n 7.1074e-07, 3.0094e-06, 4.9347e-07, 2.7779e-07, 1.0791e-06, 6.8974e-07,\n 2.8904e-06, 5.9352e-07, 1.4039e-06, 4.9924e-07, 5.9526e-07, 3.4051e-07,\n 7.5376e-07, 3.3415e-06, 4.5936e-07, 1.5913e-06, 6.8708e-07, 3.2659e-07,\n 6.0680e-07, 8.1968e-07, 4.7155e-07, 1.6245e-06, 6.0881e-07, 9.7542e-07,\n 1.1651e-06, 7.6568e-07, 2.5732e-07, 4.2002e-07, 1.7030e-06, 1.2772e-06,\n 5.2620e-07, 8.1762e-07, 3.6973e-07, 3.7595e-07, 3.1885e-07, 4.3953e-07,\n 8.5821e-07, 3.9633e-08, 2.5146e-06, 1.1771e-06, 1.9407e-07, 2.1479e-07,\n 2.9315e-06, 4.5929e-07, 7.1753e-07, 1.1326e-05, 2.3126e-07, 6.9996e-06,\n 3.7864e-07, 6.5998e-07, 1.9044e-07, 8.2905e-07, 1.9949e-06, 9.9641e-07,\n 4.0538e-07, 5.9702e-07, 1.1197e-06, 7.2969e-07, 3.4988e-07, 1.2720e-07,\n 4.8907e-07, 7.9030e-07, 1.2840e-06, 4.9082e-07, 1.2723e-07, 4.8435e-07,\n 4.2162e-07, 2.8338e-07, 1.3703e-06, 3.2845e-06, 3.6790e-07, 9.7801e-07,\n 5.8764e-07, 1.4260e-06, 6.5145e-07, 9.9850e-07, 7.0163e-07, 1.8803e-06,\n 6.4221e-07, 4.1762e-06, 6.0712e-07, 1.5126e-06, 1.3145e-07, 1.7237e-06,\n 4.8117e-07, 2.2455e-07, 5.1746e-07, 4.3940e-07, 6.1913e-07, 1.3018e-06,\n 1.0092e-06, 1.1282e-07, 1.2690e-06, 4.5639e-07, 8.1169e-07, 1.1027e-06,\n 2.5840e-06, 4.3229e-07, 1.5699e-06, 9.1140e-07, 2.0341e-07, 2.3481e-07,\n 1.1573e-06, 3.6198e-07, 1.7460e-06, 1.1002e-06, 2.0167e-06, 2.8500e-07,\n 1.0540e-06, 3.1457e-07, 8.1914e-07, 1.5604e-06, 7.7926e-07, 5.0041e-07,\n 7.1528e-07, 2.2359e-06, 2.6404e-07, 4.8174e-07, 3.3566e-07, 9.6734e-07,\n 5.7043e-06, 2.9556e-07, 1.6678e-06, 9.1670e-07, 8.5249e-07, 9.1540e-07,\n 1.9585e-06, 7.8080e-07, 3.6586e-07, 1.5245e-06, 8.7297e-07, 4.3343e-07,\n 8.5024e-07, 1.2027e-06, 1.5794e-06, 6.0058e-07])}, 116: {'step': 7160, 'exp_avg': tensor([ 4.4484e-05, 6.0363e-05, 7.4172e-05, 3.8220e-05, 5.1544e-05,\n -9.3974e-05, 8.7509e-05, 1.0160e-07, 3.2903e-05, -1.0507e-06,\n 1.3098e-05, -3.0451e-06, 5.7656e-05, 1.0981e-05, -3.1831e-05,\n 2.0284e-04, -4.8208e-05, -7.3174e-05, 7.4819e-05, -7.0271e-06,\n 6.4890e-06, -6.4088e-05, 3.6855e-05, 4.0779e-05, 4.2363e-05,\n 2.7631e-05, -5.6812e-05, -1.4743e-05, -4.3164e-05, 4.8951e-05,\n 2.2723e-05, -5.2931e-05, -2.9058e-05, -1.6004e-05, 8.0429e-05,\n 1.7471e-05, -2.8190e-05, -5.0118e-06, 2.6962e-05, 4.3559e-05,\n -3.0675e-05, 6.4291e-06, -2.9498e-06, -2.5249e-05, 7.7326e-05,\n 4.8272e-05, 1.8466e-05, -7.4187e-06, -3.6001e-05, 5.1643e-06,\n 8.1799e-05, -2.6776e-06, -9.1915e-05, -1.2308e-04, 1.3901e-05,\n 1.0331e-04, 4.6399e-06, -2.7251e-06, -7.9784e-05, 4.1696e-05,\n 3.5939e-05, -1.2169e-04, -9.9560e-06, -1.6494e-05, 3.4379e-05,\n 6.3633e-05, -8.6822e-05, -6.5170e-05, 1.0856e-05, -1.5895e-05,\n 8.9981e-06, 1.2270e-04, 1.6943e-05, 3.4097e-05, 1.5891e-04,\n -1.4752e-04, 1.0199e-04, -1.8709e-04, -7.8518e-05, -7.5858e-05,\n -4.1170e-05, -2.9580e-06, 6.4618e-05, -2.0949e-05, -3.9058e-05,\n -2.9205e-05, -6.7814e-05, 1.4784e-05, -2.7851e-05, 6.1045e-06,\n 8.5799e-05, -6.6163e-05, -2.8551e-05, 5.0952e-05, 1.0740e-04,\n 1.2337e-04, 5.7978e-05, 5.6606e-05, -1.5528e-04, 6.0173e-05,\n -8.8183e-06, 7.2414e-05, -1.2977e-05, 3.5412e-05, 1.5595e-05,\n -4.8403e-05, 6.0002e-05, -7.3684e-05, 1.4671e-05, 2.9130e-05,\n -1.2691e-06, 3.7657e-05, -9.3695e-05, 3.1107e-05, -2.8572e-05,\n 7.3332e-06, 9.8620e-05, 7.8379e-06, -1.4775e-04, -2.1062e-05,\n 2.8994e-05, 4.2907e-05, -1.0183e-05, 7.3136e-07, -4.2743e-05,\n 8.2798e-05, 4.9897e-05, -1.5244e-05, -8.7968e-05, 5.1114e-05,\n -2.1056e-05, -1.3110e-05, -2.0211e-05, -1.5901e-04, 8.5815e-06,\n 9.5290e-05, -7.0208e-05, -7.1072e-06, -7.2429e-05, -3.3768e-05,\n 1.0320e-05, -1.0445e-05, 3.1678e-05, 9.6109e-06, 4.2023e-05,\n 5.6667e-05, 4.0274e-05, -3.8826e-05, -3.4990e-05, -7.6063e-06,\n 1.5044e-05, 9.8385e-05, -4.3404e-05, -1.3401e-05, -3.6539e-05,\n -2.1411e-06, -7.5101e-05, -1.6301e-05, -2.7540e-04, -1.0771e-04,\n 9.8814e-06, 2.3052e-05, -1.3051e-05, 7.0732e-06, 9.6499e-05,\n -4.9460e-06, -3.8167e-05, 4.0996e-05, -1.9278e-05, 8.2783e-05,\n 1.0107e-06, -4.6620e-05, 8.1089e-05, -5.7536e-05, -1.8974e-05,\n 3.4438e-06, 2.4209e-05, -2.7618e-05, 4.9427e-05, -2.4205e-06,\n 2.0943e-05, 9.0074e-05, 1.8905e-05, -3.4379e-05, 1.4290e-05,\n 5.0597e-05, -2.2941e-05, 1.5390e-05, -4.6220e-05, -5.6240e-05,\n 7.2039e-06, 1.2475e-05, 1.4970e-05, 3.3098e-05, 3.6382e-05,\n -1.3888e-04, -6.9143e-05, -3.3444e-05, -6.6811e-05, -9.5371e-06,\n 7.7338e-05, -1.2273e-05, -2.1125e-05, -1.7543e-04, -8.9793e-05,\n 2.4096e-05, 9.9940e-05, -9.0158e-06, 1.3812e-05, -5.8170e-05,\n 4.9717e-06, 1.8629e-06, 7.3581e-05, 4.0000e-05, 1.3296e-04,\n 4.0146e-05, -2.1275e-05, -2.7877e-06, -7.0382e-05, -1.2090e-06,\n -4.3950e-05, -5.5184e-07, -2.8905e-05, 5.8822e-05, -1.3447e-04,\n -6.2501e-05, 2.7018e-05, 1.4247e-07, -3.8148e-06, 2.6947e-05,\n 7.7991e-05, 3.7873e-05, 6.9303e-05, 7.1207e-05, 5.1300e-05,\n 7.1979e-06, -1.3610e-05, -1.5993e-05, -6.6693e-06, -7.0342e-06,\n -4.0522e-05, 8.4318e-05, -1.1611e-04, -4.7162e-05, 1.0169e-04,\n -8.0172e-05, -1.5865e-05, -3.1893e-05, -1.4575e-05, -1.9038e-05,\n -3.4290e-05, 2.7285e-06, -5.1968e-05, 9.4793e-05, 1.6104e-04,\n 3.3971e-05]), 'exp_avg_sq': tensor([1.1641e-07, 1.0541e-06, 1.3662e-06, 6.2679e-07, 4.1255e-07, 1.7120e-06,\n 5.7840e-07, 2.0776e-07, 4.2503e-07, 8.9988e-07, 4.7810e-07, 3.2462e-07,\n 1.6310e-07, 6.1246e-07, 1.1279e-07, 1.8847e-06, 4.2196e-07, 3.5901e-07,\n 3.9892e-07, 3.2685e-08, 1.1480e-06, 4.5027e-07, 6.0374e-07, 3.0540e-07,\n 3.3353e-07, 1.4816e-07, 1.3881e-06, 9.5269e-08, 3.1376e-07, 1.0077e-06,\n 3.0141e-07, 3.5489e-07, 1.8567e-07, 1.0817e-06, 4.0581e-07, 1.9549e-07,\n 5.7256e-07, 5.9635e-07, 1.6885e-07, 1.2396e-07, 6.9157e-07, 3.2920e-07,\n 4.6963e-07, 2.8157e-08, 9.4314e-07, 2.4327e-07, 1.1991e-07, 1.8608e-07,\n 1.2613e-06, 1.1059e-07, 2.4879e-07, 4.4904e-07, 4.4344e-07, 7.3708e-07,\n 1.7959e-07, 3.3885e-07, 2.1639e-07, 2.1614e-07, 6.2132e-07, 1.0106e-06,\n 6.2180e-07, 3.4598e-07, 7.5425e-07, 1.2817e-07, 1.9701e-07, 3.8190e-07,\n 4.7542e-07, 2.7655e-07, 2.2985e-08, 3.0220e-07, 5.3974e-07, 4.8875e-07,\n 3.7171e-08, 4.7401e-07, 7.0700e-07, 4.0414e-07, 8.7346e-07, 2.7472e-06,\n 7.8132e-07, 7.1890e-07, 4.7872e-07, 3.1034e-07, 2.1866e-07, 7.2780e-07,\n 6.9477e-07, 5.2300e-07, 9.4939e-07, 1.4794e-07, 8.6559e-07, 4.7484e-07,\n 5.1778e-07, 3.7971e-07, 3.5657e-07, 3.8772e-07, 5.0291e-07, 5.7396e-07,\n 4.2094e-07, 5.0818e-07, 3.3917e-06, 1.0722e-06, 5.5667e-07, 8.7578e-07,\n 3.3283e-07, 4.2441e-07, 1.0909e-07, 1.3058e-07, 3.4621e-07, 2.7553e-07,\n 6.4099e-07, 9.6795e-07, 2.4046e-07, 5.1861e-07, 3.6611e-07, 2.9354e-07,\n 1.3349e-07, 2.3618e-07, 2.3111e-07, 1.4305e-07, 4.9397e-07, 5.8041e-07,\n 4.5241e-07, 1.7256e-06, 4.9472e-07, 1.7212e-07, 4.9663e-07, 3.0605e-07,\n 1.3400e-06, 2.2231e-07, 6.1140e-07, 4.6642e-07, 2.4057e-07, 1.2251e-07,\n 4.0240e-07, 3.3381e-06, 1.8502e-07, 6.7536e-07, 5.0867e-07, 2.4511e-07,\n 3.9799e-07, 8.7550e-07, 3.7743e-07, 6.4517e-07, 4.9173e-07, 1.8538e-07,\n 5.5465e-07, 3.4560e-07, 2.2186e-07, 2.9883e-07, 7.4381e-07, 1.0812e-06,\n 2.4528e-07, 5.4964e-07, 3.0454e-07, 2.0944e-07, 1.5226e-07, 2.7564e-07,\n 3.2336e-07, 2.3709e-08, 1.5339e-06, 7.3580e-07, 1.3143e-07, 1.2930e-07,\n 1.1709e-06, 1.5279e-06, 5.9180e-07, 1.4121e-06, 1.7376e-07, 2.4516e-06,\n 1.6908e-07, 3.2301e-07, 1.8207e-07, 4.7548e-07, 9.2766e-07, 5.3485e-07,\n 2.1698e-07, 2.3636e-07, 6.9659e-07, 2.9634e-07, 2.1639e-07, 4.7468e-08,\n 2.5245e-07, 4.1041e-07, 3.1595e-07, 5.6378e-07, 9.0855e-08, 3.1257e-07,\n 3.1915e-07, 2.0388e-07, 7.1370e-07, 2.0848e-06, 3.1914e-07, 6.9694e-07,\n 3.0532e-07, 5.7097e-07, 3.8511e-07, 5.1413e-07, 2.8225e-07, 5.6032e-07,\n 2.3905e-07, 1.2568e-06, 3.3637e-07, 9.5933e-07, 9.7437e-08, 9.4481e-07,\n 3.3330e-07, 1.2869e-07, 2.7813e-07, 1.4514e-07, 2.3027e-07, 4.5052e-07,\n 2.9187e-07, 9.7179e-08, 8.4386e-07, 2.0595e-07, 5.4954e-07, 5.4605e-07,\n 7.8298e-07, 2.0916e-07, 1.2939e-06, 4.9169e-07, 2.0816e-07, 1.1667e-07,\n 5.3103e-07, 3.3056e-07, 1.9348e-06, 5.5147e-07, 1.0237e-06, 2.1435e-07,\n 9.5222e-07, 1.7212e-07, 5.4399e-07, 8.1450e-07, 5.3559e-07, 4.8563e-07,\n 4.3863e-07, 1.0278e-06, 1.1503e-07, 2.8970e-07, 2.4877e-07, 3.3535e-07,\n 6.9594e-07, 1.9242e-07, 5.3459e-07, 5.4847e-07, 3.1568e-07, 4.3218e-07,\n 4.8997e-07, 5.3105e-07, 3.3004e-07, 7.0663e-07, 2.9426e-07, 1.9543e-07,\n 5.5421e-07, 1.0233e-06, 5.0428e-07, 2.5518e-07])}, 117: {'step': 7160, 'exp_avg': tensor([[[[-1.2413e-08]],\n\n [[ 1.3536e-07]],\n\n [[ 1.7053e-07]],\n\n ...,\n\n [[ 3.6075e-08]],\n\n [[-1.4805e-08]],\n\n [[-7.1571e-08]]],\n\n\n [[[-1.8928e-06]],\n\n [[ 3.0714e-06]],\n\n [[ 1.2591e-05]],\n\n ...,\n\n [[ 1.8621e-05]],\n\n [[ 4.6556e-07]],\n\n [[-1.1917e-05]]],\n\n\n [[[-3.5067e-06]],\n\n [[ 4.1871e-06]],\n\n [[ 9.7801e-07]],\n\n ...,\n\n [[ 6.3146e-06]],\n\n [[-2.9491e-06]],\n\n [[ 1.9411e-06]]],\n\n\n ...,\n\n\n [[[-6.3906e-07]],\n\n [[ 1.7636e-06]],\n\n [[-1.1704e-05]],\n\n ...,\n\n [[ 4.9515e-06]],\n\n [[ 3.5590e-06]],\n\n [[ 4.4123e-06]]],\n\n\n [[[ 4.2834e-06]],\n\n [[ 2.8585e-06]],\n\n [[ 8.7734e-06]],\n\n ...,\n\n [[-7.1207e-06]],\n\n [[ 6.0659e-06]],\n\n [[-2.5335e-06]]],\n\n\n [[[-1.0901e-06]],\n\n [[ 2.3637e-06]],\n\n [[-5.4879e-06]],\n\n ...,\n\n [[ 1.2262e-05]],\n\n [[-3.5428e-06]],\n\n [[ 1.1638e-06]]]]), 'exp_avg_sq': tensor([[[[9.4177e-12]],\n\n [[7.4617e-11]],\n\n [[4.7186e-11]],\n\n ...,\n\n [[3.3695e-11]],\n\n [[3.6113e-11]],\n\n [[2.7052e-11]]],\n\n\n [[[1.3888e-09]],\n\n [[9.6134e-09]],\n\n [[7.1352e-09]],\n\n ...,\n\n [[1.0700e-08]],\n\n [[2.4028e-09]],\n\n [[1.3051e-08]]],\n\n\n [[[7.4404e-10]],\n\n [[8.4218e-09]],\n\n [[3.9263e-09]],\n\n ...,\n\n [[7.8879e-09]],\n\n [[2.8857e-09]],\n\n [[2.6921e-09]]],\n\n\n ...,\n\n\n [[[9.3526e-10]],\n\n [[1.7548e-08]],\n\n [[1.4042e-08]],\n\n ...,\n\n [[1.1978e-08]],\n\n [[7.8183e-09]],\n\n [[5.1804e-09]]],\n\n\n [[[1.1155e-09]],\n\n [[8.2702e-09]],\n\n [[5.3594e-09]],\n\n ...,\n\n [[3.3289e-09]],\n\n [[2.7278e-09]],\n\n [[2.2058e-09]]],\n\n\n [[[1.6885e-09]],\n\n [[1.9776e-08]],\n\n [[1.7178e-08]],\n\n ...,\n\n [[1.7620e-08]],\n\n [[1.1281e-08]],\n\n [[1.8708e-08]]]])}, 118: {'step': 7160, 'exp_avg': tensor([ 5.9315e-05, 1.8432e-05, 3.4242e-05, ..., -3.5260e-05,\n 5.0100e-05, 6.2623e-05]), 'exp_avg_sq': tensor([1.0371e-06, 1.8789e-07, 7.4035e-08, ..., 2.1682e-07, 1.9948e-07,\n 4.3765e-07])}, 119: {'step': 7160, 'exp_avg': tensor([-4.9266e-05, 3.3346e-05, 9.8082e-06, ..., -2.5597e-05,\n 4.1008e-05, 7.2498e-05]), 'exp_avg_sq': tensor([2.9927e-07, 8.1102e-08, 4.6969e-08, ..., 1.9026e-07, 3.8542e-07,\n 2.5940e-06])}, 120: {'step': 7160, 'exp_avg': tensor([[[[ 1.5367e-05]],\n\n [[ 1.1042e-06]],\n\n [[ 2.1137e-06]],\n\n ...,\n\n [[ 1.9732e-06]],\n\n [[-6.6158e-06]],\n\n [[ 9.6629e-06]]],\n\n\n [[[ 1.3544e-05]],\n\n [[-7.7006e-07]],\n\n [[-5.3488e-07]],\n\n ...,\n\n [[ 2.8857e-06]],\n\n [[ 1.2333e-06]],\n\n [[ 9.1645e-06]]],\n\n\n [[[ 1.1138e-06]],\n\n [[-2.6899e-05]],\n\n [[ 9.5800e-07]],\n\n ...,\n\n [[-5.0593e-06]],\n\n [[-1.5484e-06]],\n\n [[ 3.6695e-05]]],\n\n\n ...,\n\n\n [[[ 2.3823e-05]],\n\n [[-1.8316e-05]],\n\n [[ 7.3546e-06]],\n\n ...,\n\n [[ 1.4449e-05]],\n\n [[-1.7284e-05]],\n\n [[ 2.2821e-05]]],\n\n\n [[[-1.4261e-06]],\n\n [[-2.5243e-06]],\n\n [[ 7.1415e-07]],\n\n ...,\n\n [[-1.5518e-06]],\n\n [[ 1.1243e-08]],\n\n [[-2.1525e-06]]],\n\n\n [[[ 1.2108e-06]],\n\n [[ 6.1920e-07]],\n\n [[ 1.7654e-06]],\n\n ...,\n\n [[ 7.3783e-07]],\n\n [[ 9.7878e-07]],\n\n [[ 1.7584e-06]]]]), 'exp_avg_sq': tensor([[[[1.7298e-08]],\n\n [[4.8361e-09]],\n\n [[5.9809e-09]],\n\n ...,\n\n [[1.0957e-08]],\n\n [[2.3121e-09]],\n\n [[1.8439e-08]]],\n\n\n [[[1.0711e-08]],\n\n [[4.2547e-09]],\n\n [[2.0239e-09]],\n\n ...,\n\n [[7.0413e-09]],\n\n [[2.4139e-09]],\n\n [[7.1898e-09]]],\n\n\n [[[7.5595e-08]],\n\n [[1.5754e-08]],\n\n [[9.7450e-09]],\n\n ...,\n\n [[3.4753e-08]],\n\n [[2.0645e-08]],\n\n [[1.0821e-07]]],\n\n\n ...,\n\n\n [[[9.9271e-08]],\n\n [[3.3670e-08]],\n\n [[1.0287e-08]],\n\n ...,\n\n [[5.0288e-08]],\n\n [[2.8374e-08]],\n\n [[4.2321e-07]]],\n\n\n [[[7.5232e-09]],\n\n [[1.5345e-09]],\n\n [[3.7548e-09]],\n\n ...,\n\n [[4.7884e-09]],\n\n [[4.5379e-09]],\n\n [[5.5090e-09]]],\n\n\n [[[2.1634e-09]],\n\n [[4.1786e-10]],\n\n [[1.6515e-10]],\n\n ...,\n\n [[3.0205e-10]],\n\n [[1.1585e-10]],\n\n [[1.4950e-09]]]])}, 121: {'step': 7160, 'exp_avg': tensor([ 1.0016e-04, -5.4778e-05, 1.3665e-04, 5.9593e-06, -7.9540e-05,\n -7.3765e-06, -1.2895e-06, -1.1180e-04, 2.7081e-05, -2.4268e-05,\n -4.9502e-05, -4.7317e-06, 8.7949e-05, -1.3235e-04, 1.1488e-04,\n 5.7931e-06, 5.0394e-05, -8.6492e-05, -4.3038e-06, -4.2209e-05,\n 2.3624e-05, 4.5246e-04, -4.1236e-05, 3.3745e-05, -3.7186e-05,\n -1.6415e-04, -2.9702e-05, 4.2332e-05, -1.6190e-05, 9.1952e-05,\n 4.4926e-05, 5.4602e-05, 2.1781e-04, 8.1962e-05, -4.9952e-05,\n -2.0806e-05, -1.2375e-05, 1.0019e-04, 2.1668e-05, 2.9266e-05,\n -7.0855e-05, 1.9377e-04, -1.1674e-04, 1.6425e-05, -2.1203e-05,\n -2.9369e-05, -1.1573e-05, 4.3186e-05, -9.4403e-06, -1.6377e-04,\n 1.1701e-04, 1.7294e-05, -3.8511e-06, -2.1345e-04, 5.9083e-05,\n -5.1848e-05, -1.4526e-04, -4.7468e-06, 6.0592e-06, -5.6163e-05,\n -2.5590e-04, -4.5919e-06, 7.3181e-06, -5.2522e-05, 9.3247e-06,\n 2.5119e-06, -1.9205e-06, -8.0725e-06, -3.5166e-05, 6.0039e-06,\n -1.9073e-05, -4.0438e-05, 1.1698e-04, -3.7970e-05, -2.2132e-06,\n 4.3150e-05, 1.9215e-05, 1.9389e-05, -1.5871e-05, -6.7057e-06,\n 2.1886e-05, 4.5741e-05, 9.9841e-05, 1.8135e-05, 1.7404e-04,\n -2.8919e-05, 6.3297e-05, -3.6973e-05, 2.0718e-05, -4.3334e-05,\n -4.0940e-05, 1.9864e-05, -5.0349e-06, -1.8220e-04, -1.2691e-04,\n -7.4066e-06, -2.0413e-04, -2.0663e-04, 1.4598e-04, -1.3655e-05,\n 7.9379e-06, -5.9677e-05, 3.1991e-05, 1.5441e-04, -4.1561e-06,\n 4.1647e-06, -1.2729e-04, -9.8529e-06, -1.0642e-04, -3.0642e-05,\n 3.5161e-05, 3.2108e-06, -2.7593e-07, 1.5029e-04, -5.0369e-05,\n 5.9671e-06, 8.7794e-05, 9.5252e-07, 1.4932e-04, -7.5847e-05,\n 1.8665e-05, 1.7516e-04, -1.6577e-05, 3.0056e-05, -1.4862e-04,\n -3.9960e-05, 3.1079e-05, -6.6725e-05, -2.7088e-05, 1.5112e-04,\n -1.2548e-04, 7.7702e-05, 3.1252e-05, 2.4758e-05, -9.4145e-05,\n -1.5608e-04, -1.6424e-05, 7.1348e-06, -6.1899e-04, 2.5475e-05,\n 1.1593e-05, -2.4652e-05, 6.5380e-07, -1.7824e-05, -3.2447e-05,\n 1.7293e-05, -5.7624e-05, 9.1759e-05, -7.2141e-05, -1.4103e-05,\n -8.4995e-05, 1.7878e-05, 8.0645e-05, -1.4138e-04, 3.3862e-05,\n 1.7247e-05, 4.6996e-05, 2.8602e-05, 2.4080e-05, -6.7739e-05,\n -1.7264e-04, -4.4844e-06, 4.7950e-05, -4.8677e-06, -1.5813e-04,\n 1.8726e-04, -7.1546e-05, -1.9817e-05, -3.5682e-05, -2.0463e-05,\n 6.4466e-05, -2.6625e-05, 1.0114e-04, -7.4827e-05, 6.3926e-05,\n -1.5035e-05, 4.4462e-05, 1.6577e-04, 7.1320e-05, -1.5982e-04,\n 2.5617e-05, -5.3051e-05, 5.1591e-07, -2.8550e-05, 9.9385e-06,\n 1.8007e-05, -4.7125e-05, 2.1521e-04, -3.9175e-05, 3.2479e-05,\n 1.4121e-04, -1.0642e-04, -5.3468e-05, -4.8578e-05, 8.3402e-05,\n -4.6420e-05, -2.5429e-05, 7.5176e-05, -5.2512e-05, 6.9233e-05,\n -1.7393e-05, 2.7242e-05, 3.6211e-06, 1.6387e-05, -2.7068e-05,\n -1.7911e-05, 8.3707e-05, -2.3464e-05, 4.3555e-05, 6.2740e-05,\n 3.3189e-05, -1.1972e-04, 9.6322e-06, -6.8164e-06, 1.1662e-05,\n 1.7776e-04, 1.5445e-04, 6.6017e-05, 6.6120e-06, -7.7267e-05,\n -3.8089e-05, 3.1613e-05, -4.5315e-05, 2.1501e-05, -9.9684e-05,\n 1.9535e-04, 1.8789e-05, 7.9380e-05, -2.2481e-06, 9.4189e-05,\n -5.6436e-05, -6.0659e-05, 7.7849e-05, -1.1143e-04, -4.3049e-05,\n -1.4073e-05, -1.8846e-06, -1.5290e-04, 6.2953e-05, 2.2647e-04,\n -1.3005e-04, 4.2395e-05, -1.5928e-04, 2.5671e-04, -1.1023e-04,\n 9.2020e-05, -7.9645e-05, 3.2453e-05, 3.8950e-05, -6.0684e-05,\n -6.2180e-05, -7.1444e-05, -1.3120e-04, -6.4068e-05, -4.4708e-06,\n 2.3482e-07]), 'exp_avg_sq': tensor([9.6422e-07, 3.7102e-07, 3.7571e-06, 1.4042e-06, 8.2358e-07, 4.9399e-08,\n 1.9637e-07, 1.1707e-06, 4.6758e-07, 3.5430e-07, 9.5823e-07, 2.1558e-07,\n 1.3860e-06, 1.0302e-06, 7.7095e-07, 1.4142e-06, 7.3810e-07, 2.3277e-07,\n 7.6366e-08, 1.9392e-07, 4.2542e-07, 3.6924e-06, 5.2850e-07, 2.0802e-07,\n 7.0104e-07, 4.4180e-07, 1.7893e-06, 1.2041e-06, 1.1541e-07, 7.3456e-07,\n 9.4931e-07, 1.8118e-06, 1.3744e-06, 1.1465e-06, 1.4715e-06, 2.4719e-06,\n 5.1204e-07, 4.2576e-07, 4.0021e-07, 6.4187e-07, 1.5043e-06, 3.6524e-06,\n 1.1560e-06, 7.1564e-07, 1.6278e-06, 5.3567e-07, 3.3826e-07, 3.7918e-07,\n 6.1317e-07, 1.2035e-06, 1.6352e-06, 5.7593e-07, 1.8402e-07, 2.5158e-06,\n 8.7219e-07, 3.9281e-07, 3.6382e-06, 3.8920e-07, 1.2914e-06, 8.5969e-07,\n 1.6985e-06, 3.0977e-07, 9.9875e-07, 1.3833e-06, 9.5531e-08, 1.6153e-07,\n 8.2882e-07, 3.5482e-07, 1.3864e-06, 2.7450e-06, 9.1295e-07, 4.4553e-07,\n 2.0005e-06, 6.5110e-07, 3.7047e-07, 5.0059e-07, 3.0175e-07, 6.1953e-07,\n 2.7666e-07, 1.0503e-06, 5.8791e-07, 2.2857e-07, 4.3896e-07, 3.7441e-07,\n 9.0788e-07, 2.6701e-06, 3.4415e-07, 4.7228e-07, 5.5801e-07, 5.2502e-07,\n 3.0767e-07, 3.7532e-07, 6.9684e-07, 1.1344e-06, 9.8178e-07, 9.7431e-07,\n 3.1047e-06, 2.6145e-06, 9.8626e-07, 6.7214e-07, 4.2077e-07, 3.0809e-06,\n 6.5050e-07, 7.8831e-07, 8.4836e-07, 3.4217e-07, 8.3684e-07, 7.1561e-07,\n 1.0234e-06, 9.6646e-07, 6.5401e-06, 4.2567e-07, 1.7529e-06, 6.6313e-07,\n 7.7596e-07, 2.1011e-07, 8.0342e-07, 1.0490e-06, 6.7070e-07, 1.0742e-06,\n 2.6280e-07, 1.0085e-06, 4.6743e-07, 2.2392e-06, 6.4507e-07, 2.3848e-07,\n 4.3558e-07, 3.0937e-07, 1.3779e-06, 2.4638e-06, 6.5666e-07, 1.3127e-06,\n 1.0635e-06, 7.8556e-07, 1.1160e-06, 2.6459e-06, 9.6524e-07, 5.7012e-07,\n 1.4428e-05, 3.9359e-06, 9.0479e-07, 1.8988e-07, 2.7986e-07, 9.8354e-07,\n 2.7091e-07, 4.3509e-07, 8.2819e-07, 1.0475e-06, 1.0633e-06, 4.4324e-07,\n 5.5661e-07, 4.3098e-07, 1.6758e-06, 2.0371e-06, 1.7923e-06, 3.8211e-07,\n 2.0677e-06, 1.5033e-06, 4.6352e-06, 1.2837e-06, 1.3245e-05, 2.6716e-07,\n 6.6112e-07, 8.5426e-07, 1.9683e-06, 5.4183e-06, 5.5236e-07, 2.8410e-07,\n 2.9835e-07, 1.7727e-06, 7.7723e-07, 1.2436e-06, 1.6897e-06, 7.9790e-07,\n 5.7356e-07, 1.7245e-07, 4.4141e-07, 1.2776e-06, 5.5266e-07, 1.0659e-06,\n 7.3067e-07, 5.2208e-07, 7.3403e-07, 7.2379e-07, 3.5156e-07, 4.5446e-07,\n 3.0185e-06, 2.7812e-06, 2.4807e-06, 5.3042e-07, 1.9381e-06, 2.8306e-06,\n 3.9474e-07, 3.2194e-07, 7.0003e-07, 4.7721e-07, 4.3441e-07, 3.6657e-07,\n 1.3223e-06, 5.2435e-07, 3.5802e-07, 2.4542e-06, 8.3305e-07, 1.1188e-06,\n 9.8594e-07, 2.3636e-06, 7.4052e-07, 2.5806e-06, 6.8266e-07, 3.6926e-06,\n 1.4927e-06, 4.3845e-07, 2.9120e-07, 2.5734e-07, 9.1560e-07, 7.8513e-07,\n 4.2968e-06, 6.7484e-07, 1.5351e-06, 3.6639e-06, 3.1238e-06, 2.1177e-06,\n 1.0722e-06, 4.7476e-07, 4.0533e-06, 7.6531e-07, 1.1081e-06, 2.3584e-06,\n 3.7747e-07, 5.8632e-07, 4.2437e-07, 1.9065e-06, 9.0470e-07, 8.3546e-07,\n 5.4425e-07, 1.2812e-06, 6.1438e-07, 6.3657e-07, 3.1701e-07, 1.6589e-06,\n 9.9010e-07, 1.4449e-06, 1.6866e-06, 5.7337e-06, 1.3390e-06, 8.3130e-07,\n 7.0879e-07, 2.0730e-06, 9.2507e-07, 4.9611e-07, 4.1301e-07, 9.4889e-07,\n 5.0652e-07, 6.7929e-06, 4.3726e-07, 1.3723e-07])}, 122: {'step': 7160, 'exp_avg': tensor([ 5.8426e-05, -3.1894e-05, -1.3155e-04, -1.6461e-05, -5.5858e-05,\n -6.0866e-06, -9.4553e-07, -1.0301e-04, 1.6936e-05, -1.4992e-05,\n -2.2054e-05, 2.8301e-06, 9.0733e-05, -8.7661e-05, 9.1401e-05,\n 5.8219e-06, 2.8262e-05, -4.5109e-05, -2.9747e-06, -2.8530e-05,\n 2.0221e-05, 4.8060e-04, -2.3579e-05, 2.5911e-05, -2.4289e-05,\n -1.3175e-04, 7.4127e-06, 4.8844e-05, -1.0014e-05, 7.9060e-05,\n 1.4166e-05, -5.3571e-07, 1.9306e-04, 1.1874e-04, -1.6696e-05,\n -4.0950e-05, -1.3423e-05, 6.2655e-05, 2.4133e-05, 2.2702e-05,\n -4.1853e-05, 1.2749e-04, -9.9777e-05, 1.4649e-05, 1.2711e-05,\n -1.5845e-05, -1.1257e-05, 4.4395e-05, -1.2405e-05, -2.3381e-04,\n -8.0784e-06, 1.1869e-05, 2.5275e-06, -4.3174e-05, 4.2612e-05,\n -2.9847e-05, 7.7312e-05, -1.3504e-05, -3.5681e-05, -7.7188e-05,\n -2.5363e-04, 7.5211e-06, -2.4863e-05, -9.7865e-05, 7.4367e-07,\n -1.0140e-05, -1.9641e-05, -2.9199e-05, -4.6606e-06, 2.9856e-06,\n -1.0493e-05, -1.5324e-05, 1.4695e-04, -3.5582e-05, -2.9625e-06,\n 4.4050e-05, 4.0637e-05, 2.8502e-05, -4.2316e-05, -1.3582e-06,\n -5.3336e-07, 1.6309e-05, 5.3678e-05, 1.9086e-05, 9.1138e-05,\n 8.8002e-05, 4.4568e-05, -1.8748e-05, 2.9849e-06, -3.4228e-05,\n -3.1163e-05, 1.8057e-05, 3.4426e-06, -1.0497e-04, -1.2479e-04,\n 1.4602e-05, -7.8030e-05, -1.9450e-04, 1.4105e-04, -3.5111e-06,\n 9.1920e-06, -7.9808e-05, 3.9321e-05, 6.9617e-05, -1.9414e-05,\n 2.6103e-05, -8.3016e-05, -2.1920e-05, -9.7231e-05, -3.4316e-05,\n 2.0999e-06, -6.2985e-06, -1.2945e-05, 8.1278e-05, -4.3193e-05,\n 4.1352e-06, 1.1425e-04, -4.0332e-06, 1.2288e-04, -5.6372e-05,\n 6.6917e-06, 7.8505e-05, -2.0657e-05, 2.4945e-05, -1.0532e-04,\n -1.9039e-05, 3.7124e-05, -7.2248e-05, -6.5958e-05, -4.3119e-05,\n -7.6001e-05, 7.1276e-05, 1.6515e-05, 5.9684e-06, -1.6179e-04,\n -3.4870e-05, -9.9433e-06, 4.4935e-07, 7.3724e-05, 1.8748e-05,\n -1.4853e-05, -1.6508e-05, -2.1807e-05, 5.7732e-06, -5.7753e-05,\n 1.1284e-05, -6.6210e-05, 7.4332e-05, 6.7726e-05, -2.6172e-05,\n -7.3968e-05, 1.6624e-05, 1.3409e-04, -5.2338e-05, 8.0363e-05,\n 2.9374e-05, 6.2908e-05, 1.6073e-05, 2.8786e-05, -3.0962e-05,\n -1.6652e-05, -3.4316e-06, 2.8045e-05, -1.1950e-05, -8.9356e-05,\n 7.8032e-05, -3.6572e-05, -3.6693e-05, -5.1922e-06, -1.2285e-04,\n 4.0916e-05, -4.2185e-06, 1.4662e-04, -6.3247e-05, 7.7571e-05,\n -1.8442e-05, 1.5599e-05, 1.5993e-04, 2.0382e-04, -1.5963e-04,\n 3.9790e-05, -4.6004e-05, -9.4551e-06, -2.1302e-05, 1.1660e-05,\n -4.6635e-06, 1.3916e-04, 5.4289e-05, -5.1604e-05, 1.3584e-05,\n 8.8591e-05, -1.4886e-04, -3.0740e-05, -4.5791e-05, 3.1207e-05,\n -4.5840e-05, -2.4162e-05, 3.6318e-05, -5.9810e-05, 1.5579e-05,\n -2.5422e-05, -6.5819e-05, -3.9610e-07, 7.9339e-06, 1.8875e-05,\n -2.0890e-05, 6.4748e-05, -3.2194e-06, 3.8973e-05, -6.7251e-06,\n 1.0288e-05, -9.0693e-05, 5.6862e-06, -6.7479e-06, 2.0913e-05,\n 5.3047e-05, 4.7055e-05, 6.8513e-05, 5.5188e-05, -1.4851e-04,\n -7.9608e-06, 5.0702e-05, -5.2861e-05, 2.5026e-05, -1.1683e-04,\n 1.4769e-04, 1.6693e-05, 5.6361e-05, 1.0421e-05, 8.1703e-05,\n -4.4595e-05, 1.9044e-06, 7.9465e-05, -1.0924e-04, -2.3025e-05,\n 8.5349e-07, -2.1046e-05, -7.2987e-05, 3.8114e-06, 5.3804e-05,\n -1.1706e-04, 2.8138e-05, -2.4091e-05, 1.5479e-04, -4.7336e-05,\n 4.3085e-05, -6.1291e-05, 1.5376e-05, -2.0420e-05, -3.1517e-05,\n -5.2361e-05, -2.1281e-05, -7.6550e-05, -2.7156e-04, 1.9507e-06,\n -4.9146e-06]), 'exp_avg_sq': tensor([3.2487e-07, 1.7383e-07, 2.0189e-06, 8.5012e-07, 2.5309e-07, 2.6584e-08,\n 1.0847e-07, 5.9422e-07, 2.1576e-07, 2.4792e-07, 3.8465e-07, 2.9578e-08,\n 9.4662e-07, 6.8293e-07, 3.9188e-07, 8.2388e-07, 2.6758e-07, 8.9369e-08,\n 3.7707e-08, 1.0906e-07, 2.2131e-07, 5.1184e-06, 2.2256e-07, 9.2189e-08,\n 4.0318e-07, 2.8188e-07, 9.5142e-07, 6.2034e-07, 7.5296e-08, 4.0938e-07,\n 4.0958e-07, 6.5525e-07, 1.2601e-06, 9.0692e-07, 5.4091e-07, 1.5007e-06,\n 5.9113e-07, 2.8577e-07, 3.3312e-07, 3.1310e-07, 5.4014e-07, 1.2791e-06,\n 7.0846e-07, 3.5490e-07, 7.5145e-07, 3.0566e-07, 1.1727e-07, 3.4026e-07,\n 3.4151e-07, 1.3448e-06, 1.3145e-06, 2.4692e-07, 1.4082e-07, 1.1887e-06,\n 4.1565e-07, 1.6366e-07, 2.5700e-06, 1.4985e-07, 6.2889e-07, 5.2715e-07,\n 1.3577e-06, 3.1731e-07, 3.7990e-07, 1.4097e-06, 1.6640e-08, 1.2720e-07,\n 4.2260e-07, 2.9936e-07, 4.9471e-07, 4.7728e-07, 1.7040e-07, 9.6631e-08,\n 1.1963e-06, 5.9794e-07, 2.7959e-07, 2.6333e-07, 1.6466e-07, 3.9418e-07,\n 4.8545e-07, 8.1611e-07, 3.3106e-07, 4.2198e-08, 1.1513e-07, 2.1078e-07,\n 3.5298e-07, 1.9447e-06, 1.9483e-07, 2.7192e-07, 2.2333e-07, 1.7793e-07,\n 1.4524e-07, 2.0756e-07, 1.7778e-07, 7.1271e-07, 6.4392e-07, 3.4280e-07,\n 6.4125e-07, 1.4417e-06, 7.8765e-07, 3.4039e-07, 2.1819e-07, 1.3577e-06,\n 2.5204e-07, 5.0589e-07, 2.8728e-07, 4.0906e-07, 6.3921e-07, 2.3006e-07,\n 8.5433e-07, 6.0809e-07, 3.8647e-06, 2.2564e-07, 8.7958e-07, 2.7515e-07,\n 3.3647e-07, 8.9269e-08, 5.3234e-07, 7.5758e-07, 5.1805e-07, 5.0996e-07,\n 1.6384e-07, 1.3547e-06, 2.6806e-07, 7.2909e-07, 3.8779e-07, 9.8653e-08,\n 3.6143e-07, 1.8744e-07, 5.7799e-07, 1.2407e-06, 5.4902e-07, 1.0411e-06,\n 3.3413e-07, 4.1063e-07, 1.3735e-06, 1.2534e-06, 5.1449e-07, 3.4951e-07,\n 3.4851e-06, 1.8444e-06, 1.1002e-06, 8.3830e-08, 1.2041e-07, 4.6576e-07,\n 4.5487e-07, 1.8843e-07, 8.2279e-07, 5.0405e-07, 6.3374e-07, 4.0540e-07,\n 3.3386e-07, 2.6479e-07, 2.2114e-06, 4.4608e-07, 6.9848e-07, 3.5891e-07,\n 6.4595e-07, 2.9029e-07, 1.0129e-06, 4.4607e-07, 2.5014e-06, 1.3330e-07,\n 2.8550e-07, 2.0567e-07, 6.0755e-07, 4.6490e-06, 1.9531e-07, 1.9970e-07,\n 3.9734e-08, 1.5694e-06, 3.1611e-07, 5.9695e-07, 1.1257e-06, 3.6024e-07,\n 5.2607e-07, 1.4869e-07, 2.0418e-07, 7.7665e-07, 7.8870e-07, 5.0710e-07,\n 4.1218e-07, 6.1833e-07, 2.8363e-07, 2.2169e-07, 1.7387e-07, 2.6981e-07,\n 1.7735e-06, 1.4648e-06, 4.8277e-07, 4.0272e-07, 1.0050e-06, 1.5763e-06,\n 1.9091e-07, 1.4881e-07, 2.5122e-07, 3.3843e-07, 4.6596e-07, 3.0839e-07,\n 1.2811e-06, 3.4441e-07, 1.6593e-07, 1.3368e-06, 4.6943e-07, 4.4045e-07,\n 4.4848e-07, 8.9470e-07, 3.2236e-07, 4.3365e-07, 7.1889e-07, 9.0117e-07,\n 9.6867e-07, 1.5100e-07, 1.4192e-07, 3.1328e-07, 5.0521e-07, 4.8688e-07,\n 1.3967e-06, 5.1144e-07, 1.6119e-06, 1.4136e-06, 1.0306e-06, 1.5853e-06,\n 9.0003e-07, 3.8415e-07, 1.6783e-06, 3.7872e-07, 5.4409e-07, 6.8546e-07,\n 9.1688e-08, 3.4330e-07, 3.3691e-07, 8.3475e-07, 8.8114e-07, 1.0201e-06,\n 1.5333e-07, 4.9442e-07, 2.7492e-07, 6.0025e-07, 3.1002e-08, 5.5553e-07,\n 4.3097e-07, 9.0469e-07, 1.4528e-06, 2.4046e-06, 6.7316e-07, 4.5484e-07,\n 3.1073e-07, 6.3102e-07, 1.9806e-07, 4.4457e-07, 2.3341e-07, 3.6436e-07,\n 3.3335e-07, 5.7410e-06, 2.5606e-07, 2.7319e-08])}, 123: {'step': 7160, 'exp_avg': tensor([[[[ 2.9234e-07, -6.0468e-07, 1.8360e-06],\n [-1.6342e-06, -9.7311e-06, 2.0292e-06],\n [-4.0527e-06, 1.2627e-05, -2.0929e-06]],\n\n [[ 2.3175e-06, 9.3283e-08, 3.0993e-06],\n [-1.3301e-06, 3.1052e-06, -1.4717e-07],\n [ 6.1640e-07, -1.6430e-07, -6.9363e-08]],\n\n [[-1.6171e-05, -2.8798e-06, -2.4669e-06],\n [ 7.1029e-06, 1.6476e-06, 9.1263e-06],\n [ 2.0363e-05, 1.8719e-05, 1.2222e-05]],\n\n ...,\n\n [[ 1.3596e-06, 1.9630e-06, 7.8857e-06],\n [-4.2313e-06, -2.9812e-06, 3.0156e-06],\n [-6.7273e-06, -3.5182e-06, -9.7009e-07]],\n\n [[-3.1922e-06, -4.8888e-06, -4.6859e-06],\n [-1.3797e-06, -3.4894e-06, -1.3187e-07],\n [-1.0073e-06, -2.6174e-06, 1.2875e-06]],\n\n [[-8.1228e-06, -1.3303e-05, -9.4670e-06],\n [ 3.2885e-06, -2.5136e-07, -2.8254e-06],\n [ 1.0479e-07, -6.4854e-07, -4.3214e-07]]],\n\n\n [[[-6.1214e-06, -4.3671e-06, -3.2170e-06],\n [-3.0335e-06, -2.9499e-06, -1.9465e-06],\n [-3.1580e-06, -2.0698e-06, 9.1082e-06]],\n\n [[ 1.2284e-06, 5.9799e-07, 6.1108e-07],\n [ 2.2475e-07, 1.0681e-06, -5.6183e-07],\n [ 1.1789e-06, -2.0656e-06, -1.9038e-06]],\n\n [[ 5.0645e-06, -2.0617e-06, 1.2201e-05],\n [ 1.2807e-05, 1.6722e-05, 2.3596e-05],\n [ 1.8379e-05, 2.2692e-05, 2.8943e-05]],\n\n ...,\n\n [[ 1.6527e-06, -1.6016e-06, -1.1307e-05],\n [-6.9500e-07, -9.3684e-06, -2.0020e-05],\n [ 6.5879e-06, -6.1659e-06, -1.8088e-05]],\n\n [[ 7.4731e-07, 2.1363e-06, 9.1021e-07],\n [ 1.1179e-06, -1.3795e-07, -3.4434e-07],\n [-1.5390e-06, -1.4910e-06, -1.3141e-06]],\n\n [[ 6.6436e-06, 7.5075e-06, 5.2276e-06],\n [ 2.3217e-06, 2.1904e-06, 7.8051e-07],\n [-3.9943e-07, -3.2479e-07, -2.4418e-07]]],\n\n\n [[[ 9.9846e-09, -1.1369e-07, 6.2390e-07],\n [-6.2601e-08, -1.5109e-07, 1.7190e-07],\n [-1.0023e-06, 2.1107e-07, 2.1699e-08]],\n\n [[-5.0053e-08, -3.4457e-08, -5.6084e-07],\n [-3.8806e-07, -4.2063e-08, -8.7644e-07],\n [-1.6169e-06, 1.9000e-08, -9.8555e-08]],\n\n [[ 9.2565e-07, 1.4676e-06, -1.1253e-06],\n [ 8.8321e-07, 5.5346e-06, 9.3902e-07],\n [ 1.0001e-06, 2.8761e-06, 8.0079e-07]],\n\n ...,\n\n [[ 3.3468e-06, 1.6732e-06, 3.2006e-06],\n [ 1.2974e-06, -1.5550e-06, -9.1606e-07],\n [-4.1725e-07, -3.3859e-06, -1.9183e-06]],\n\n [[-3.4803e-07, -4.1833e-07, 2.0377e-07],\n [ 7.6177e-09, -5.5130e-07, 1.5278e-06],\n [ 1.1662e-07, -1.2002e-07, 9.5831e-08]],\n\n [[ 2.6816e-07, 2.8214e-07, -8.9449e-08],\n [-1.5922e-07, -2.1859e-07, -1.1952e-07],\n [-1.3006e-08, -2.0824e-07, 4.5906e-08]]],\n\n\n ...,\n\n\n [[[ 3.8728e-06, -5.4587e-07, -4.5976e-06],\n [ 3.3121e-06, 3.3008e-06, 1.3776e-05],\n [ 5.7671e-06, 2.8448e-06, 6.1981e-06]],\n\n [[ 1.1082e-06, 2.8871e-06, 8.5863e-07],\n [ 1.7617e-06, 9.6843e-07, 1.9942e-06],\n [ 9.7400e-07, 1.2909e-06, 1.2729e-06]],\n\n [[-1.0102e-05, -5.0737e-06, -2.2182e-05],\n [-1.3994e-06, -1.3463e-05, -2.0027e-05],\n [ 6.6562e-06, 1.8078e-06, -1.4921e-05]],\n\n ...,\n\n [[ 3.6834e-06, 9.4391e-06, 1.9299e-05],\n [-5.1819e-06, 1.2205e-05, 1.2967e-05],\n [-1.4940e-05, -4.1965e-06, 4.4227e-06]],\n\n [[ 3.8972e-06, 4.3188e-06, 2.2760e-06],\n [ 1.2020e-06, -1.0217e-06, 1.2385e-06],\n [-9.2257e-07, -2.6025e-06, -2.4208e-06]],\n\n [[ 5.8694e-06, 3.6948e-06, 2.2531e-06],\n [ 1.7328e-06, -5.6403e-07, -1.0281e-06],\n [ 1.6643e-06, -1.0807e-06, 1.6449e-07]]],\n\n\n [[[-2.8757e-06, 7.9678e-07, -2.1756e-06],\n [ 1.5674e-06, 1.3699e-06, 9.1312e-07],\n [ 7.0025e-07, 4.3943e-07, 2.0734e-06]],\n\n [[ 4.4270e-07, 7.5590e-07, 7.0446e-07],\n [ 3.2679e-07, -6.4874e-08, 1.0778e-06],\n [-4.2001e-07, -2.3120e-07, -2.4704e-07]],\n\n [[-2.9912e-07, -3.7610e-07, 4.1224e-08],\n [-2.2164e-06, -1.9549e-06, -1.6936e-06],\n [-5.6569e-07, -1.2051e-07, 8.4415e-08]],\n\n ...,\n\n [[ 2.4073e-06, 1.7475e-06, 8.0290e-07],\n [ 1.2138e-06, -8.1287e-08, -2.5718e-07],\n [ 8.6513e-07, 2.3212e-07, 1.2719e-06]],\n\n [[ 1.3452e-07, 1.7601e-06, 1.4015e-06],\n [ 1.0193e-06, 8.2776e-07, 1.1300e-06],\n [ 1.1211e-06, 1.7804e-06, 8.8172e-07]],\n\n [[-1.8692e-06, 4.5691e-08, -1.1071e-07],\n [ 3.3179e-06, 1.3012e-06, 2.3839e-06],\n [ 4.2522e-08, -1.1525e-08, 1.0222e-07]]],\n\n\n [[[-4.4955e-06, 3.7896e-07, 7.8484e-07],\n [-3.3407e-06, -2.0620e-06, -3.9513e-06],\n [-1.4248e-06, -1.8210e-07, 2.2268e-06]],\n\n [[ 6.1702e-07, 5.4494e-07, 2.7055e-08],\n [ 8.1275e-07, 9.6622e-07, 1.0016e-06],\n [ 4.5788e-07, 7.0646e-07, 9.5433e-07]],\n\n [[-4.7170e-06, 1.6842e-06, -1.2823e-05],\n [ 5.9026e-06, -9.7550e-06, -1.7782e-05],\n [-1.1679e-05, -1.7823e-05, -2.3267e-05]],\n\n ...,\n\n [[ 7.6666e-06, 1.2372e-05, 1.4198e-05],\n [ 1.4076e-05, 2.2486e-05, 1.4811e-05],\n [ 4.1707e-06, 3.7319e-06, 7.9523e-06]],\n\n [[ 2.8398e-06, -1.8305e-07, 2.1912e-06],\n [ 3.3563e-06, -4.7051e-06, 5.2394e-07],\n [ 3.8132e-06, -5.6209e-08, 3.3377e-06]],\n\n [[ 6.1180e-06, 4.9922e-06, 5.8335e-06],\n [ 5.8322e-06, 5.0499e-06, 4.9403e-06],\n [ 6.2754e-07, -4.3122e-07, 4.0932e-07]]]]), 'exp_avg_sq': tensor([[[[7.1066e-10, 2.9820e-09, 2.2395e-09],\n [1.4385e-09, 5.2399e-09, 2.1672e-09],\n [1.4453e-09, 3.0186e-09, 2.5232e-09]],\n\n [[4.6222e-10, 4.0513e-10, 5.5148e-10],\n [3.8479e-10, 7.2699e-10, 4.4507e-10],\n [5.9449e-10, 3.7817e-10, 4.1532e-10]],\n\n [[5.3257e-09, 7.1322e-09, 5.5611e-09],\n [6.4112e-09, 8.4677e-09, 9.7604e-09],\n [1.0707e-08, 9.8308e-09, 9.5537e-09]],\n\n ...,\n\n [[6.9837e-09, 8.0406e-09, 1.2004e-08],\n [4.8815e-09, 6.4956e-09, 9.8450e-09],\n [4.4434e-09, 6.6160e-09, 8.7196e-09]],\n\n [[8.1823e-10, 1.4025e-09, 1.7707e-09],\n [5.7468e-10, 7.8253e-10, 3.1809e-09],\n [5.5874e-10, 7.8066e-10, 2.4249e-09]],\n\n [[2.3681e-09, 5.1517e-09, 2.3184e-09],\n [6.7666e-10, 8.3045e-10, 5.1892e-10],\n [9.6817e-11, 2.1700e-10, 6.0103e-11]]],\n\n\n [[[1.6288e-09, 9.3056e-10, 2.1171e-09],\n [1.2675e-09, 6.4912e-10, 2.0324e-09],\n [1.5722e-09, 1.5784e-09, 1.8328e-09]],\n\n [[3.3137e-10, 3.9788e-10, 3.4905e-10],\n [3.5364e-10, 4.1615e-10, 4.9440e-10],\n [4.8790e-10, 4.7232e-10, 3.8698e-10]],\n\n [[6.2082e-09, 4.4900e-09, 5.3694e-09],\n [6.0420e-09, 5.9591e-09, 6.7295e-09],\n [7.4822e-09, 7.3226e-09, 8.0581e-09]],\n\n ...,\n\n [[6.8608e-09, 6.1041e-09, 6.0715e-09],\n [1.0670e-08, 9.1708e-09, 7.1356e-09],\n [7.6685e-09, 6.6280e-09, 6.1671e-09]],\n\n [[3.3308e-10, 4.6084e-10, 2.8268e-10],\n [9.4649e-10, 1.1290e-09, 7.6732e-10],\n [3.3679e-10, 6.3760e-10, 3.6619e-10]],\n\n [[6.1838e-10, 8.2503e-10, 4.4546e-10],\n [1.8423e-10, 3.2994e-10, 1.1009e-10],\n [1.8584e-11, 3.1098e-11, 1.9901e-11]]],\n\n\n [[[6.0463e-10, 1.4153e-09, 8.1342e-10],\n [5.4612e-10, 6.6743e-10, 6.5003e-10],\n [1.9019e-09, 4.5601e-10, 6.8389e-10]],\n\n [[2.7136e-10, 3.3372e-10, 2.7182e-10],\n [2.3715e-10, 1.3258e-10, 1.5028e-10],\n [2.7999e-10, 1.8965e-10, 3.2782e-10]],\n\n [[3.9431e-09, 3.1387e-09, 3.7832e-09],\n [2.8581e-09, 3.3805e-09, 3.3977e-09],\n [4.0608e-09, 4.6454e-09, 3.7860e-09]],\n\n ...,\n\n [[3.5296e-09, 5.1985e-09, 8.0851e-09],\n [2.9159e-09, 4.9238e-09, 7.1755e-09],\n [3.3067e-09, 3.6955e-09, 5.4465e-09]],\n\n [[5.0808e-10, 5.8982e-10, 7.2132e-10],\n [8.5283e-10, 8.8905e-10, 6.9355e-10],\n [6.8903e-10, 6.0122e-10, 3.2557e-10]],\n\n [[1.0845e-10, 9.1326e-11, 5.1812e-11],\n [5.4786e-10, 6.4201e-10, 2.0686e-10],\n [1.0059e-11, 3.8003e-11, 1.3910e-11]]],\n\n\n ...,\n\n\n [[[7.2366e-09, 3.1096e-09, 1.2863e-08],\n [1.7997e-08, 7.7911e-09, 7.1751e-09],\n [4.7243e-09, 4.5067e-09, 5.2257e-09]],\n\n [[3.4105e-09, 4.0941e-09, 3.0866e-09],\n [2.2919e-09, 4.2115e-09, 5.3208e-09],\n [2.7015e-09, 2.4947e-09, 3.5263e-09]],\n\n [[2.4936e-08, 1.8654e-08, 1.7130e-08],\n [2.4417e-08, 2.0469e-08, 2.3197e-08],\n [2.1703e-08, 1.9458e-08, 2.2176e-08]],\n\n ...,\n\n [[6.4686e-08, 6.4346e-08, 7.6280e-08],\n [5.8978e-08, 4.6904e-08, 7.1321e-08],\n [3.9238e-08, 4.3589e-08, 5.6610e-08]],\n\n [[3.4041e-09, 4.4528e-09, 2.8724e-09],\n [6.0529e-09, 6.4697e-09, 3.0536e-09],\n [3.9802e-09, 6.0742e-09, 3.2271e-09]],\n\n [[3.0506e-09, 1.3935e-09, 6.0009e-10],\n [4.8541e-09, 1.6018e-09, 4.2955e-10],\n [5.8106e-10, 4.3014e-10, 5.5708e-11]]],\n\n\n [[[7.3425e-10, 3.2320e-10, 3.2463e-10],\n [4.5969e-10, 1.9817e-10, 1.8035e-10],\n [2.1709e-10, 6.7171e-10, 3.8306e-10]],\n\n [[7.1832e-11, 7.8825e-11, 1.0505e-10],\n [1.5186e-10, 2.7588e-10, 1.2022e-10],\n [1.0573e-10, 1.5171e-10, 8.6152e-11]],\n\n [[2.7864e-09, 1.2957e-09, 1.1089e-09],\n [1.3507e-09, 1.6051e-09, 2.1632e-09],\n [1.5052e-09, 3.6833e-09, 3.3359e-09]],\n\n ...,\n\n [[1.0575e-09, 8.1372e-10, 7.2529e-10],\n [1.4849e-09, 8.9781e-10, 9.1372e-10],\n [9.1538e-10, 7.4507e-10, 8.2475e-10]],\n\n [[4.8880e-10, 6.7354e-10, 8.2818e-10],\n [9.4001e-10, 2.3414e-09, 1.4144e-09],\n [1.0458e-10, 3.1077e-10, 3.8901e-10]],\n\n [[1.7697e-09, 1.4561e-09, 3.8801e-10],\n [1.3719e-09, 6.0181e-10, 3.1296e-10],\n [1.3900e-10, 3.8079e-11, 1.1941e-11]]],\n\n\n [[[1.3604e-09, 1.7302e-09, 8.5851e-10],\n [3.7707e-09, 2.7300e-09, 5.7984e-10],\n [3.8868e-09, 6.2504e-09, 5.4664e-10]],\n\n [[3.1955e-10, 4.6359e-10, 4.6297e-10],\n [4.0773e-10, 4.7301e-10, 2.9794e-10],\n [3.2004e-10, 2.0481e-10, 1.3023e-10]],\n\n [[7.1064e-09, 5.7183e-09, 4.9284e-09],\n [5.7477e-09, 5.1652e-09, 1.1359e-08],\n [6.2876e-09, 6.0684e-09, 6.2358e-09]],\n\n ...,\n\n [[6.2854e-09, 7.7713e-09, 5.0858e-09],\n [1.1130e-08, 1.0438e-08, 7.6136e-09],\n [9.0915e-09, 1.0636e-08, 8.1681e-09]],\n\n [[9.6490e-10, 3.1233e-09, 4.8108e-09],\n [4.9966e-09, 5.6447e-09, 8.7546e-09],\n [1.4222e-09, 4.0324e-09, 1.8044e-09]],\n\n [[5.7021e-09, 4.6376e-09, 1.8590e-09],\n [5.9952e-09, 1.2440e-08, 3.4147e-09],\n [4.2085e-10, 3.4675e-10, 4.1095e-11]]]])}, 124: {'step': 7160, 'exp_avg': tensor([ 5.6689e-05, 1.1041e-04, -2.6165e-06, -2.1583e-05, -1.3648e-04,\n 1.4687e-04, 4.2480e-05, 5.1888e-05, 7.8807e-06, 7.5615e-06,\n -2.5380e-05, -1.3134e-05, 1.8255e-04, 8.2758e-06, 5.2152e-05,\n -8.9965e-05, 5.3274e-05, 1.7940e-04, -1.8418e-05, 6.5793e-07,\n -3.2619e-05, 1.8885e-05, -2.2045e-05, 9.6801e-05, -4.3760e-05,\n -6.3653e-05, 5.5989e-05, 9.1687e-05, 5.9658e-06, 8.2671e-06,\n -3.4736e-05, 3.8196e-05, -7.4138e-05, 1.1372e-05, 3.0841e-05,\n -7.7211e-05, -6.4256e-05, 1.2756e-05, 6.2068e-05, -3.5399e-05,\n -1.2302e-04, -2.1795e-05, -7.3998e-05, -1.8206e-05, 7.2130e-05,\n -1.3913e-04, -6.6289e-05, 7.4498e-06, -5.5274e-05, -1.0421e-04,\n 2.0998e-04, 2.9177e-05, -7.0888e-06, 6.9524e-05, 3.9899e-07,\n -2.6172e-05, -1.8689e-04, -2.1665e-05, -3.6856e-05, 1.9928e-04,\n -5.9282e-05, -6.7871e-05, 7.1143e-06, 3.4772e-06, -1.9507e-05,\n -7.2530e-06, 4.3517e-05, -8.5069e-06, -5.3218e-05, -6.9878e-06,\n 1.9056e-04, 2.6796e-05, 4.7142e-05, -3.3359e-06, 2.8083e-05,\n -1.0018e-06, -2.6879e-05, 3.7681e-05, -4.8304e-05, -6.9008e-05,\n -4.4965e-05, -6.2484e-05, -2.8757e-05, -2.5714e-05, 3.7622e-05,\n 3.8099e-05, 2.0533e-04, -1.5812e-06, 1.4911e-04, 2.1117e-06,\n 6.7882e-05, 1.4419e-05, 5.1683e-05, 1.0495e-05, 5.4433e-05,\n -3.4043e-05, -1.8245e-05, 1.3534e-04, 6.3198e-05, -3.4826e-05,\n -9.2369e-06, 4.1100e-06, -8.9575e-06, 2.2553e-05, 3.1705e-06,\n 1.8050e-05, -2.3191e-05, -2.3100e-05, 2.5418e-06, -4.9545e-05,\n -8.4236e-06, -1.1005e-04, 7.3377e-05, 4.5417e-05, -4.9796e-04,\n -3.0197e-05, -4.4883e-05, 9.4853e-07, -7.6924e-05, -3.2056e-05,\n -3.2453e-05, 4.8974e-06, 4.4622e-05, -2.1145e-05, -1.6105e-05,\n -5.2507e-05, 2.6966e-05, 5.8035e-05, 1.7488e-05, 1.0751e-05,\n 5.3597e-07, 4.6045e-06, -2.7371e-05, 8.4063e-06, -4.6328e-05,\n 5.0946e-05, 3.0722e-05, -5.6873e-05, -1.2174e-06, 1.9126e-05,\n 1.3334e-06, -8.5307e-06, 2.5373e-04, -2.9841e-05, 2.8316e-08,\n -2.3763e-05, -5.2429e-06, -3.7573e-05, 3.4158e-05, -5.2029e-05,\n -1.1445e-05, 3.7353e-05, 6.9677e-05, 3.2511e-05, -4.8475e-05,\n -1.1794e-04, -9.6087e-05, 7.0557e-05, 4.1095e-05, 8.9492e-05,\n 4.4671e-05, -3.4886e-05, -2.1797e-05, -2.1286e-05, -5.5496e-05,\n -6.4918e-07, 2.0957e-05, 5.7618e-06, 2.9816e-05, 1.6060e-06,\n 1.0101e-04, 5.6695e-05, 1.2985e-04, -2.2203e-05, 4.4880e-06,\n 4.8809e-05, -6.2312e-06, 2.5396e-05, 5.2272e-05, -1.2118e-06,\n -1.6926e-04, -3.5929e-05, 1.1054e-05, 2.1373e-05, -5.0810e-05,\n 1.9897e-05, 3.6797e-05, -7.8234e-05, 1.0094e-05, 1.8090e-05,\n 1.2625e-05, -1.8022e-06, 1.8597e-06, 5.6884e-06, 4.3581e-05,\n 1.1981e-05, -2.0400e-05, -1.9381e-06, 2.8333e-05, 1.8206e-04,\n 4.0432e-07, -5.6196e-05, -1.9119e-04, 1.9172e-04, 2.3376e-05,\n -7.2086e-06, 8.1811e-05, 5.1815e-05, -5.0684e-05, -3.1394e-05,\n 8.3728e-05, 2.0012e-06, -1.8404e-05, 5.6256e-06, 2.0718e-05,\n -2.9882e-05, 1.5012e-04, -3.3614e-04, 1.5374e-05, -6.2169e-05,\n 7.6997e-05, -3.8017e-05, -9.6460e-06, -2.2773e-05, 3.4747e-05,\n 8.4503e-05, -7.8018e-06, 4.3552e-05, -1.1428e-04, -1.9010e-04,\n -4.3976e-05, 5.1692e-05, -1.0305e-04, -1.4831e-04, -5.5019e-05,\n 1.1182e-04, -4.5143e-06, 2.3301e-04, -1.1409e-05, 8.1844e-05,\n -5.4209e-05, -1.4693e-05, 3.4627e-05, -1.0152e-04, 4.2915e-06,\n -4.3039e-05, 1.9288e-05, 2.6216e-05, -2.5460e-05, -2.1004e-06,\n 2.9821e-05, 9.6564e-05, -4.1906e-05, -1.0370e-05, -3.0784e-06,\n 2.9910e-05]), 'exp_avg_sq': tensor([2.3465e-07, 2.1078e-07, 9.5404e-08, 1.2770e-06, 3.6902e-06, 8.8447e-07,\n 3.0473e-07, 2.1481e-07, 1.6291e-07, 2.8585e-07, 5.5781e-07, 6.4394e-07,\n 1.5333e-06, 1.3859e-07, 2.2961e-07, 4.9086e-06, 9.9045e-07, 1.9592e-06,\n 1.9455e-07, 2.1296e-07, 2.7009e-07, 1.9821e-07, 2.9880e-07, 9.4763e-07,\n 2.7477e-07, 1.5716e-06, 2.4720e-06, 1.0290e-06, 3.1958e-07, 3.8050e-07,\n 3.6303e-07, 4.1303e-07, 2.4150e-06, 8.2373e-08, 5.5152e-07, 4.7857e-07,\n 1.0606e-06, 2.3025e-07, 3.6903e-07, 1.8481e-07, 9.4569e-07, 2.0990e-07,\n 5.6344e-06, 2.3861e-07, 7.7684e-07, 8.1406e-07, 2.3880e-07, 3.2247e-07,\n 3.0908e-07, 3.7069e-06, 2.1314e-05, 1.1882e-07, 3.1721e-07, 1.0712e-06,\n 1.1726e-07, 5.2804e-07, 6.6004e-06, 5.6645e-08, 3.9305e-07, 6.4356e-07,\n 1.3768e-06, 2.7473e-06, 1.7287e-07, 9.3404e-07, 1.4120e-07, 2.8572e-07,\n 2.0838e-07, 3.5446e-07, 4.6809e-07, 3.2703e-07, 1.2804e-06, 3.6294e-07,\n 3.2888e-07, 2.4505e-07, 2.2316e-07, 2.6782e-07, 1.2188e-07, 3.7829e-07,\n 1.7296e-07, 9.3670e-07, 1.6619e-07, 3.8230e-07, 2.4410e-07, 5.1156e-07,\n 1.1048e-07, 5.4479e-07, 2.6951e-06, 1.3441e-06, 4.5766e-06, 1.2365e-07,\n 3.7059e-07, 3.6497e-07, 2.8385e-07, 1.6342e-08, 7.1719e-07, 3.3602e-07,\n 1.3831e-07, 4.1447e-07, 1.3368e-07, 5.1200e-07, 4.1476e-07, 2.7581e-07,\n 5.1447e-08, 1.1895e-06, 2.8357e-07, 2.4878e-07, 5.0386e-07, 2.3636e-07,\n 1.3390e-07, 2.8829e-07, 9.9386e-07, 5.7100e-07, 9.0665e-07, 1.5467e-07,\n 2.9674e-05, 6.2242e-07, 4.7813e-06, 3.0541e-07, 2.4748e-06, 4.1998e-07,\n 7.1569e-07, 4.0072e-08, 2.4376e-07, 4.6819e-07, 1.9985e-07, 1.1695e-06,\n 1.4485e-07, 9.8039e-07, 5.6010e-07, 2.6410e-07, 3.5374e-07, 6.7831e-07,\n 1.4376e-07, 2.1176e-07, 6.8102e-08, 1.7673e-07, 2.0018e-07, 4.3618e-07,\n 1.7850e-07, 4.0388e-07, 5.0309e-07, 1.1652e-06, 1.3469e-06, 3.4618e-06,\n 1.0560e-07, 8.1985e-07, 1.0227e-06, 2.0335e-06, 4.9733e-07, 1.9635e-07,\n 2.0801e-07, 1.0619e-06, 2.2761e-07, 2.0868e-06, 1.0933e-06, 4.5767e-07,\n 1.1894e-06, 8.0302e-07, 4.8565e-07, 3.9327e-07, 3.1845e-07, 6.2131e-07,\n 5.6862e-08, 8.9401e-08, 1.8716e-06, 8.9167e-08, 1.7577e-07, 7.2992e-07,\n 2.8466e-07, 2.5959e-07, 2.0195e-07, 1.4382e-06, 2.6226e-07, 2.1660e-07,\n 2.0933e-07, 2.3212e-06, 1.5441e-07, 3.8907e-07, 4.5752e-07, 3.0575e-07,\n 5.1880e-06, 5.7725e-07, 4.3323e-07, 1.7426e-07, 2.3318e-06, 1.6332e-07,\n 3.4204e-07, 1.4728e-06, 1.6166e-07, 9.9796e-07, 5.0237e-07, 3.6299e-07,\n 7.2925e-07, 4.0683e-07, 3.3183e-07, 4.1202e-07, 6.7107e-07, 2.4898e-08,\n 1.6789e-07, 2.6166e-06, 1.4066e-06, 4.1120e-07, 2.7765e-05, 1.9175e-06,\n 1.5499e-07, 5.8126e-08, 2.8746e-07, 3.3379e-07, 2.2276e-07, 1.1768e-07,\n 6.8519e-07, 5.2489e-07, 5.8207e-07, 1.1659e-07, 4.7707e-07, 6.3840e-07,\n 7.6312e-07, 2.2367e-06, 1.3127e-07, 6.5374e-07, 3.1358e-07, 3.4764e-07,\n 1.2774e-07, 2.7485e-06, 7.7042e-07, 1.3495e-06, 8.6371e-08, 4.9884e-07,\n 6.9207e-07, 2.5333e-06, 1.4118e-07, 8.9735e-07, 6.5489e-07, 1.6703e-06,\n 3.9114e-07, 1.2595e-06, 7.2765e-07, 4.6912e-06, 2.5741e-07, 6.7065e-07,\n 7.0619e-07, 6.9434e-07, 4.6766e-07, 1.9001e-06, 7.6971e-08, 2.7478e-07,\n 1.3342e-07, 1.9691e-07, 2.9353e-06, 1.3326e-08, 2.4773e-07, 3.0612e-06,\n 1.6812e-07, 5.1408e-07, 8.3696e-08, 3.8357e-07])}, 125: {'step': 7160, 'exp_avg': tensor([ 5.2916e-05, 1.3878e-04, -9.1136e-06, 3.0519e-05, -9.9121e-05,\n 8.0256e-05, 4.4287e-05, 8.7410e-05, 1.3155e-05, 1.0080e-05,\n -1.5315e-05, -6.4231e-05, 1.0408e-04, -1.1974e-05, 5.0308e-05,\n 1.2432e-04, 1.5335e-05, 1.8149e-04, 9.3449e-06, 2.6104e-06,\n -2.6983e-05, 3.4439e-05, -5.6600e-05, 6.1229e-05, -3.8447e-05,\n -9.2136e-05, 2.8093e-05, 9.0276e-05, 1.6967e-05, 4.5994e-05,\n -3.9000e-05, 3.2126e-05, -3.7670e-05, 2.5439e-05, 4.6996e-05,\n -9.4129e-05, -7.8485e-05, -6.2146e-06, 6.2926e-05, -4.5929e-05,\n -8.6659e-05, 5.9808e-06, -1.8016e-04, -2.1537e-05, 8.1868e-05,\n -1.9936e-05, -4.5094e-05, -1.2141e-06, -6.2485e-05, -1.0158e-04,\n -1.9383e-05, 2.1999e-05, 5.7098e-06, 4.7531e-05, 1.0096e-06,\n -3.2366e-05, -2.1708e-05, -3.5558e-05, -3.2493e-05, 1.8724e-04,\n -1.5488e-04, -2.3223e-05, 1.3264e-05, -8.7325e-06, -1.7797e-05,\n -1.1354e-05, 4.3648e-05, -1.5845e-05, 5.2437e-05, -2.6061e-05,\n 6.7337e-05, -2.2188e-05, 3.6296e-05, 1.0252e-05, 4.6145e-05,\n -1.1339e-05, -1.4458e-05, 5.9440e-05, -4.3431e-05, -7.7443e-05,\n -8.3300e-05, -5.2113e-05, -2.6254e-05, -5.3072e-05, 3.1031e-05,\n 2.9697e-06, 1.0767e-04, -2.4762e-05, -1.0983e-05, -1.0255e-05,\n 5.6170e-05, 2.4798e-05, 5.4469e-05, 1.1933e-05, 2.4546e-05,\n -4.3751e-07, -1.1371e-05, 8.0114e-05, 2.0069e-05, -2.6258e-05,\n 1.2159e-05, 1.3361e-05, -8.3574e-06, 2.4335e-05, -3.2422e-05,\n 1.5420e-05, -3.7843e-05, 1.1048e-05, -1.7358e-05, 9.9063e-06,\n 4.5723e-05, -4.7082e-05, 4.1461e-05, -1.6289e-06, -1.3093e-04,\n -3.1135e-05, 1.9249e-04, -1.7044e-05, -3.9890e-05, -6.3785e-05,\n -3.6470e-06, -1.0962e-06, 1.6838e-06, -1.0993e-05, 1.6260e-05,\n -1.4048e-04, 2.1575e-05, 3.5187e-05, 1.3911e-05, -2.7092e-06,\n 1.7439e-05, -1.1039e-06, -3.9115e-05, -2.1794e-05, -4.2385e-05,\n 2.4545e-05, 2.1168e-05, -4.1780e-05, -2.5764e-06, 3.8429e-05,\n -9.6925e-07, -1.1462e-06, 1.5840e-04, 5.6115e-05, -5.8373e-06,\n -2.9798e-05, 2.7806e-06, -1.2554e-04, 3.7575e-05, -5.2738e-05,\n -5.0381e-06, -3.4070e-06, 4.7689e-05, 7.4481e-06, -6.7813e-05,\n -8.4709e-05, -9.8262e-05, 3.1970e-05, 3.0218e-05, 7.5015e-05,\n 5.4163e-05, -4.2364e-05, -1.5038e-05, -2.4156e-05, -5.1585e-05,\n 7.6599e-06, 2.4117e-05, -3.5185e-05, 1.8957e-05, 2.2651e-05,\n 1.4688e-04, -2.4462e-05, 1.2037e-04, -2.2372e-05, -5.4730e-06,\n 2.2062e-05, -4.2931e-06, 2.5694e-05, 7.6412e-05, -1.3356e-05,\n -6.9673e-05, -1.9400e-05, -4.2118e-06, 3.2819e-06, -7.2860e-06,\n 1.0052e-05, 6.4672e-05, -7.3593e-05, 8.9244e-06, 3.8433e-05,\n 5.8091e-06, -8.6708e-06, 1.6972e-05, -2.3878e-05, 4.2735e-06,\n -1.0872e-05, -4.5850e-05, -2.9650e-06, 2.1695e-06, 9.4969e-05,\n -4.4069e-06, -2.6772e-05, -9.2833e-05, 7.7513e-05, 1.4672e-05,\n 1.6682e-06, 8.8936e-05, 5.3216e-05, -4.4378e-05, -8.5445e-06,\n 1.6188e-05, -1.0475e-05, -5.5944e-09, 1.2901e-06, 2.2098e-05,\n -4.7036e-06, 1.1941e-04, -7.8127e-05, 2.7466e-06, -4.9136e-05,\n 6.2330e-05, -6.5884e-06, -7.9145e-06, -4.2480e-06, 1.4642e-05,\n 9.2385e-05, -1.3200e-05, 3.7148e-05, -3.6603e-05, -3.4775e-05,\n -5.0673e-05, 2.8913e-05, -7.5716e-05, -4.3853e-06, -1.7013e-05,\n 5.8127e-05, -2.3064e-05, -4.7938e-05, -2.1738e-05, 7.0229e-05,\n -2.8824e-05, -8.2149e-05, 3.2675e-05, -1.6610e-04, -5.3172e-07,\n -1.0690e-05, 1.2924e-05, 1.6728e-05, -4.2951e-05, -2.1325e-06,\n 4.0961e-05, 7.7655e-06, -1.7483e-05, 7.6894e-06, -1.2601e-05,\n -5.9165e-05]), 'exp_avg_sq': tensor([1.9684e-07, 2.9304e-07, 1.4400e-07, 5.7179e-07, 5.1123e-07, 4.3583e-07,\n 1.7359e-07, 3.1433e-07, 7.8169e-08, 1.9076e-07, 3.0608e-07, 3.8093e-07,\n 4.9883e-07, 6.7217e-08, 1.8905e-07, 2.5066e-06, 5.1846e-07, 1.5630e-06,\n 2.3308e-07, 8.7454e-08, 1.7027e-07, 2.4429e-07, 1.4784e-07, 6.0445e-07,\n 1.7213e-07, 7.9957e-07, 1.3366e-06, 6.0481e-07, 2.8430e-07, 4.7547e-07,\n 3.4714e-07, 3.1513e-07, 1.5557e-06, 2.6382e-07, 2.5863e-07, 9.8980e-07,\n 1.0136e-06, 1.9256e-07, 3.1798e-07, 1.7095e-07, 6.2596e-07, 1.6158e-07,\n 2.6458e-06, 1.5434e-07, 6.9418e-07, 9.4847e-07, 1.3977e-07, 2.6512e-07,\n 1.4290e-07, 3.4239e-06, 1.3294e-06, 3.1626e-08, 3.8569e-07, 4.9572e-07,\n 4.8394e-08, 2.8442e-07, 2.2017e-06, 7.7212e-08, 2.2803e-07, 4.8851e-07,\n 6.5884e-07, 9.3717e-07, 2.1880e-07, 2.5975e-07, 8.8250e-08, 1.9672e-07,\n 2.3239e-07, 5.1830e-07, 4.2595e-07, 3.3620e-07, 3.5982e-07, 2.3638e-07,\n 3.0284e-07, 2.6921e-07, 6.3155e-07, 3.0968e-07, 1.2326e-07, 3.9331e-07,\n 1.1489e-07, 9.4418e-07, 1.7355e-07, 1.8069e-07, 1.9901e-07, 3.6065e-07,\n 8.7472e-08, 3.2238e-07, 6.9264e-07, 7.8083e-07, 1.5630e-06, 1.6344e-07,\n 2.8211e-07, 1.7173e-07, 2.7440e-07, 1.5502e-08, 3.4964e-07, 3.8269e-07,\n 6.0848e-08, 2.4203e-07, 4.1946e-08, 2.9617e-07, 4.8552e-07, 1.6039e-07,\n 7.7332e-08, 6.7424e-07, 3.4183e-07, 4.1217e-08, 4.2648e-07, 2.9449e-07,\n 7.2497e-08, 2.0741e-07, 5.5662e-07, 4.1412e-07, 1.6529e-07, 1.1144e-07,\n 1.3421e-05, 4.6547e-07, 2.0545e-06, 1.1994e-07, 1.2680e-06, 4.8098e-07,\n 2.8530e-07, 5.7544e-08, 7.3815e-08, 4.6679e-07, 3.8223e-07, 8.4670e-07,\n 9.4909e-08, 2.2868e-07, 3.5841e-07, 3.2145e-07, 3.2843e-07, 5.7074e-07,\n 2.1171e-07, 1.5763e-07, 5.0537e-08, 5.2521e-08, 1.1615e-07, 1.8747e-07,\n 1.3899e-07, 2.9061e-07, 4.6517e-07, 3.3753e-07, 5.0523e-07, 1.3591e-06,\n 2.9516e-07, 9.0682e-07, 1.6583e-06, 1.7801e-06, 2.8547e-07, 2.8881e-07,\n 3.4975e-07, 4.2753e-07, 1.5725e-07, 2.1462e-06, 6.7908e-07, 3.7004e-07,\n 6.8258e-07, 3.5103e-07, 4.0875e-07, 2.8802e-07, 6.1261e-07, 4.5186e-07,\n 4.8421e-08, 8.3384e-08, 5.9540e-07, 1.0190e-07, 1.6197e-07, 3.7229e-07,\n 2.0703e-07, 3.3289e-07, 3.7398e-07, 1.4944e-06, 2.3351e-07, 2.4014e-07,\n 3.2255e-07, 8.1635e-07, 2.5464e-08, 3.0281e-07, 4.3243e-07, 2.7740e-07,\n 7.2858e-07, 2.6339e-07, 5.7530e-07, 5.4911e-08, 2.1948e-06, 2.1092e-07,\n 2.4961e-07, 1.0272e-06, 2.6249e-07, 4.7644e-07, 4.3106e-07, 1.1085e-07,\n 6.2471e-07, 6.3627e-07, 1.8894e-07, 4.8046e-07, 5.8899e-07, 2.6587e-08,\n 1.7941e-08, 1.2376e-06, 9.3517e-07, 1.7441e-07, 1.6617e-05, 6.6560e-07,\n 7.2806e-08, 6.2684e-08, 2.6280e-07, 2.3957e-07, 2.2237e-07, 3.0629e-08,\n 4.0759e-07, 3.8514e-07, 4.2638e-07, 9.7305e-09, 4.7423e-07, 3.5323e-07,\n 4.6362e-07, 7.1511e-07, 1.4667e-07, 3.0642e-07, 2.4541e-07, 1.0351e-07,\n 3.4476e-08, 7.3575e-07, 2.6938e-07, 5.1490e-07, 3.8598e-08, 7.2783e-07,\n 4.9209e-07, 1.5705e-06, 3.0850e-07, 3.1252e-07, 4.6025e-07, 6.0897e-07,\n 4.5183e-07, 4.4733e-07, 6.2298e-07, 1.0657e-06, 2.6935e-07, 3.2481e-07,\n 4.9087e-07, 8.5730e-07, 3.2631e-07, 6.5482e-07, 3.3786e-08, 2.3061e-07,\n 6.7362e-08, 1.7267e-07, 5.3306e-07, 1.2607e-08, 1.9000e-07, 1.9250e-06,\n 5.0662e-08, 5.7377e-07, 4.0125e-08, 4.4476e-07])}, 126: {'step': 7160, 'exp_avg': tensor([[[[-8.5425e-09]],\n\n [[ 1.4633e-08]],\n\n [[ 1.1409e-08]],\n\n ...,\n\n [[ 1.4859e-08]],\n\n [[-2.2747e-09]],\n\n [[ 2.3241e-09]]],\n\n\n [[[-9.1149e-07]],\n\n [[-8.0135e-08]],\n\n [[ 1.7982e-07]],\n\n ...,\n\n [[-1.0263e-07]],\n\n [[-7.6481e-07]],\n\n [[-2.0219e-06]]],\n\n\n [[[ 5.6707e-06]],\n\n [[-2.6925e-06]],\n\n [[-5.2670e-07]],\n\n ...,\n\n [[-7.1385e-06]],\n\n [[ 3.2250e-06]],\n\n [[ 4.2998e-06]]],\n\n\n ...,\n\n\n [[[-8.7930e-07]],\n\n [[ 8.0445e-07]],\n\n [[-1.0920e-06]],\n\n ...,\n\n [[ 9.7305e-07]],\n\n [[-7.8031e-07]],\n\n [[-4.5996e-07]]],\n\n\n [[[-3.2407e-06]],\n\n [[ 4.7158e-08]],\n\n [[ 1.0562e-06]],\n\n ...,\n\n [[ 5.7924e-07]],\n\n [[ 2.3270e-06]],\n\n [[ 4.0528e-06]]],\n\n\n [[[ 5.9147e-06]],\n\n [[-4.0530e-06]],\n\n [[-1.3192e-06]],\n\n ...,\n\n [[-3.4103e-06]],\n\n [[ 7.2921e-06]],\n\n [[ 7.0394e-06]]]]), 'exp_avg_sq': tensor([[[[2.9704e-12]],\n\n [[5.2682e-12]],\n\n [[2.7831e-12]],\n\n ...,\n\n [[9.4140e-12]],\n\n [[2.8611e-12]],\n\n [[9.9153e-12]]],\n\n\n [[[1.3342e-10]],\n\n [[2.1144e-10]],\n\n [[4.4836e-11]],\n\n ...,\n\n [[2.6257e-10]],\n\n [[8.8154e-11]],\n\n [[4.6512e-10]]],\n\n\n [[[8.8874e-10]],\n\n [[2.7463e-10]],\n\n [[1.7166e-10]],\n\n ...,\n\n [[1.8685e-09]],\n\n [[1.0094e-09]],\n\n [[2.1126e-09]]],\n\n\n ...,\n\n\n [[[2.2300e-09]],\n\n [[6.0290e-10]],\n\n [[4.6893e-10]],\n\n ...,\n\n [[4.2462e-09]],\n\n [[6.4483e-09]],\n\n [[1.2519e-08]]],\n\n\n [[[7.1419e-10]],\n\n [[2.1429e-09]],\n\n [[4.0546e-10]],\n\n ...,\n\n [[3.3870e-09]],\n\n [[7.6201e-10]],\n\n [[2.8764e-09]]],\n\n\n [[[2.5639e-09]],\n\n [[1.2340e-08]],\n\n [[2.2578e-09]],\n\n ...,\n\n [[6.1052e-09]],\n\n [[4.4488e-09]],\n\n [[5.2427e-09]]]])}, 127: {'step': 7160, 'exp_avg': tensor([-9.9151e-06, -2.4188e-06, 1.2933e-05, ..., 4.1933e-06,\n 2.3081e-05, 8.6780e-05]), 'exp_avg_sq': tensor([1.8775e-07, 1.8807e-09, 2.5111e-08, ..., 2.4912e-07, 4.1632e-08,\n 1.2135e-06])}, 128: {'step': 7160, 'exp_avg': tensor([-2.9711e-05, 1.1645e-05, 2.0276e-06, ..., -8.5804e-06,\n 6.2705e-05, 6.4618e-05]), 'exp_avg_sq': tensor([2.9288e-07, 2.3113e-08, 3.5265e-08, ..., 1.5807e-07, 3.0310e-07,\n 2.3437e-06])}, 129: {'step': 7160, 'exp_avg': tensor([[[[-7.0930e-06]],\n\n [[-2.4864e-06]],\n\n [[-6.9520e-07]],\n\n ...,\n\n [[-5.3671e-07]],\n\n [[ 9.7496e-06]],\n\n [[-1.9756e-05]]],\n\n\n [[[ 5.3868e-07]],\n\n [[ 3.4886e-06]],\n\n [[-5.7296e-06]],\n\n ...,\n\n [[ 7.5969e-06]],\n\n [[ 1.4680e-06]],\n\n [[ 3.4830e-06]]],\n\n\n [[[-6.0705e-06]],\n\n [[ 1.7256e-06]],\n\n [[-2.2620e-07]],\n\n ...,\n\n [[-4.3336e-06]],\n\n [[ 1.0415e-05]],\n\n [[-8.8724e-06]]],\n\n\n ...,\n\n\n [[[ 4.4860e-06]],\n\n [[ 1.1268e-05]],\n\n [[ 4.5624e-06]],\n\n ...,\n\n [[ 6.8959e-06]],\n\n [[ 2.7691e-06]],\n\n [[-1.6531e-05]]],\n\n\n [[[-6.6691e-07]],\n\n [[-5.6212e-08]],\n\n [[-1.3597e-06]],\n\n ...,\n\n [[ 1.8527e-06]],\n\n [[ 1.7247e-06]],\n\n [[-3.4641e-07]]],\n\n\n [[[-1.3594e-07]],\n\n [[-1.2960e-05]],\n\n [[ 5.9077e-07]],\n\n ...,\n\n [[ 1.7388e-06]],\n\n [[ 1.3953e-06]],\n\n [[ 7.8768e-07]]]]), 'exp_avg_sq': tensor([[[[8.3494e-08]],\n\n [[2.1128e-09]],\n\n [[2.1156e-09]],\n\n ...,\n\n [[1.5385e-08]],\n\n [[1.3538e-08]],\n\n [[1.1218e-07]]],\n\n\n [[[3.5723e-08]],\n\n [[1.6572e-09]],\n\n [[3.1552e-09]],\n\n ...,\n\n [[5.4581e-09]],\n\n [[3.9264e-09]],\n\n [[2.7064e-08]]],\n\n\n [[[5.5798e-08]],\n\n [[1.7636e-09]],\n\n [[1.7742e-09]],\n\n ...,\n\n [[3.7765e-09]],\n\n [[1.1112e-08]],\n\n [[6.5079e-08]]],\n\n\n ...,\n\n\n [[[5.7560e-08]],\n\n [[8.3200e-10]],\n\n [[2.4278e-09]],\n\n ...,\n\n [[3.7723e-09]],\n\n [[3.7072e-09]],\n\n [[4.6913e-07]]],\n\n\n [[[9.6885e-09]],\n\n [[2.5465e-10]],\n\n [[8.3376e-10]],\n\n ...,\n\n [[1.9252e-09]],\n\n [[2.3567e-09]],\n\n [[5.2022e-09]]],\n\n\n [[[6.2559e-08]],\n\n [[4.7139e-09]],\n\n [[1.7995e-09]],\n\n ...,\n\n [[2.1827e-08]],\n\n [[1.5262e-08]],\n\n [[1.3595e-08]]]])}, 130: {'step': 7160, 'exp_avg': tensor([ 8.9218e-05, -4.3421e-06, -1.4423e-05, 1.4683e-04, -3.5275e-05,\n 4.4133e-05, 1.4300e-04, -2.5617e-05, -5.5157e-05, 3.2456e-05,\n -2.1102e-04, -1.7331e-04, -1.9552e-05, -5.5718e-05, -1.8277e-05,\n 1.1004e-04, -1.7303e-04, -2.7446e-04, 4.1199e-05, -1.7228e-04,\n -5.0256e-05, -1.9140e-05, -3.3745e-05, -5.3876e-05, 2.8540e-05,\n -1.0095e-04, -5.7548e-05, -2.4988e-05, 5.3116e-06, 2.7666e-04,\n 9.5893e-05, 6.2543e-06, 2.6169e-05, 7.7521e-05, -2.4071e-05,\n -7.0448e-05, -2.3972e-05, -3.6287e-05, 1.3686e-04, 8.0818e-06,\n 2.5416e-04, 4.7070e-06, -9.2788e-05, 2.5276e-04, -3.7082e-05,\n 1.0806e-04, -6.5537e-05, -8.2561e-06, -9.7010e-05, -1.6766e-04,\n -1.7402e-04, -2.0355e-05, 6.5915e-05, -7.3971e-05, -9.8813e-06,\n 2.6859e-04, -4.2020e-05, 2.0485e-05, -1.4639e-05, 2.0926e-05,\n -5.4082e-05, 3.3986e-05, -6.7246e-05, 8.0989e-05, -1.8153e-04,\n -4.5750e-06, -8.3646e-06, 1.9100e-04, -2.2601e-05, 1.4118e-04,\n 1.7610e-06, 9.4353e-05, -6.7107e-05, -8.6943e-05, -6.9177e-05,\n 2.2585e-04, -3.0397e-05, -6.1892e-05, -3.4606e-04, 2.0862e-05,\n -8.7681e-05, 4.9747e-05, -8.2913e-06, 8.6527e-05, 7.9618e-05,\n -1.7920e-05, -2.0070e-05, 2.8989e-05, -3.3870e-05, 7.9380e-05,\n 3.7755e-05, -3.4797e-05, -1.7091e-04, -7.0002e-05, 6.6468e-05,\n 1.1831e-05, 4.1701e-05, -1.3292e-04, 2.3871e-05, 7.4317e-05,\n 5.8896e-06, 9.3499e-05, 4.9288e-05, 6.2663e-05, 4.8348e-05,\n -5.0132e-05, 2.6278e-05, -2.6744e-04, -6.4279e-06, -1.7396e-05,\n 6.5010e-05, 1.2586e-04, 1.7407e-05, -4.9215e-06, -1.6454e-06,\n -4.1052e-05, 9.3757e-05, 8.3884e-05, -3.8401e-05, -1.0383e-05,\n 8.2642e-05, 8.0082e-05, -6.4272e-05, -2.7118e-04, -2.7526e-05,\n -1.0232e-04, 1.0397e-05, -2.0751e-04, 7.5627e-05, -1.3670e-04,\n -1.3504e-04, 1.1157e-04, 1.8648e-05, -9.8986e-05, -1.1627e-04,\n 9.8479e-05, -2.3929e-06, -1.0259e-04, -1.1846e-04, 2.3643e-05,\n -4.6336e-04, -7.8764e-06, 6.3437e-05, -7.4579e-05, -2.5667e-05,\n -2.4031e-05, 1.0408e-05, -1.3758e-04, -8.6355e-05, -5.6143e-05,\n 1.0366e-04, -2.7573e-05, -8.8718e-05, 5.5451e-05, 8.5558e-05,\n -3.4715e-05, -1.4710e-06, -7.2030e-05, -7.0653e-05, -6.5461e-05,\n -3.1322e-04, -4.3445e-06, 5.0255e-05, -2.9944e-05, 7.8079e-06,\n -2.2175e-04, 1.5881e-04, -1.1745e-04, -2.4722e-07, -3.0388e-05,\n 2.9678e-05, -2.8155e-05, 2.2937e-05, 5.6106e-05, 6.4851e-05,\n 4.0588e-05, 1.1602e-04, -1.0654e-04, 1.8425e-05, -3.9211e-04,\n -2.7949e-05, 7.9278e-06, -7.0232e-05, -1.3041e-04, -1.1131e-05,\n -6.1572e-06, -1.6369e-05, -2.3019e-05, 8.2238e-05, -1.0858e-06,\n -8.7893e-05, 2.9974e-06, 2.8145e-05, -6.4803e-06, 5.3182e-05,\n 2.6828e-05, -1.1970e-05, -3.8098e-05, -1.2256e-05, -1.4654e-04,\n 5.0397e-05, 2.6781e-05, 2.8352e-05, -2.4546e-04, 1.0114e-04,\n -5.2617e-05, -5.6678e-05, 1.2694e-04, 9.5542e-05, 1.7959e-04,\n 1.3803e-04, -3.5628e-05, -1.1291e-05, -2.2680e-04, 8.6662e-06,\n 8.4127e-06, 6.7078e-05, -5.1753e-05, 2.7499e-05, 4.0664e-05,\n -7.6199e-06, -2.3445e-04, -4.9080e-04, 5.2047e-06, -7.6362e-05,\n 1.5314e-05, -8.4309e-05, 2.9813e-05, 2.1092e-06, 1.3156e-04,\n 4.4947e-06, 2.9017e-05, -2.4319e-05, 4.8947e-04, -1.3121e-05,\n -7.2387e-05, 8.8475e-05, -7.0006e-05, 3.5435e-05, 3.3679e-05,\n -5.4904e-05, 1.2799e-04, -5.0636e-05, 6.0380e-05, 4.4017e-05,\n 6.0784e-05, -4.2964e-05, -5.3712e-05, 1.2103e-05, -2.0900e-05,\n 1.0907e-04, -1.7713e-04, 3.5735e-05, 9.0064e-05, 1.8195e-05,\n -2.3544e-04, 5.3477e-05, 1.3765e-04, 7.4506e-05, -5.3512e-05,\n -8.5430e-05, -7.7150e-05, -1.8399e-05, -1.3844e-04, 8.3496e-06,\n -9.9942e-06, 1.8378e-05, 1.2202e-04, 1.6222e-04, -8.8590e-05,\n -3.3486e-05, 6.4361e-05, 2.6850e-05, -7.4901e-07, 1.5762e-04,\n 9.9100e-05, -7.6180e-08, -9.7506e-05, 3.3532e-05, 8.4085e-05,\n 5.2695e-05, -6.5890e-05, -1.3716e-04, -2.3411e-05, -3.4238e-05,\n -3.1474e-05, 8.3427e-05, 3.6611e-05, 6.8978e-05, -6.7471e-05,\n -3.0648e-06, -8.9324e-05, -2.7067e-05, 1.0366e-04, -4.5461e-06,\n 1.9892e-05, -1.8011e-05, -3.8672e-06, 1.1332e-04, -1.1240e-04,\n -4.4498e-05, 3.1967e-05, 1.4372e-04, -1.0385e-04, 1.3431e-04,\n 7.7199e-05, -6.4045e-05, 1.1261e-04, -1.2199e-05, -7.3569e-05,\n 6.3096e-05, -1.5869e-05, -2.9395e-05, -6.2364e-05, 2.7658e-05,\n -8.5298e-05, 1.7848e-05, 1.3534e-05, 1.1375e-04, -9.4395e-06,\n -4.5510e-05, -4.0223e-05, 7.7849e-05, -4.5858e-05, 2.6319e-05,\n 8.6138e-05, -3.6506e-05, 4.4188e-05, -1.0177e-04, 2.5371e-05,\n -7.1626e-05, -2.1745e-05, -8.1262e-05, -5.5467e-05, 8.8560e-05,\n -8.3736e-05, -1.3352e-06, -1.0160e-04, 7.8805e-05, -8.7791e-06,\n -1.9706e-05, -7.4125e-05, 1.1662e-04, 5.6755e-05, -1.9322e-05,\n -1.7602e-04, -3.2210e-06, -5.5916e-05, -5.9563e-06, 1.1657e-04,\n 1.1712e-04, -3.0070e-05, -5.4986e-05, -2.9724e-05, 1.2100e-04,\n 5.0651e-05, 1.0975e-04, -1.3575e-05, 1.2705e-05, 4.4573e-05,\n 4.6891e-05, -2.5364e-05, 2.2328e-05, 4.7534e-05, -4.7693e-06,\n 4.9672e-06, 7.2407e-05, 3.9086e-05, 3.5376e-05, 2.9283e-05,\n -3.8043e-05, 6.1145e-05, -1.0065e-04, -6.2632e-05, -2.7329e-06,\n 9.9430e-05, 1.3255e-04, 2.1091e-05, 5.8139e-05, -7.5164e-05,\n 4.2762e-05, -3.5416e-05, -3.4953e-07, -2.3010e-04, 5.6427e-06,\n 3.5933e-05, -1.8168e-05, -4.2214e-05, -1.0234e-05, -1.1560e-05,\n -1.4258e-04, -6.7047e-05, 1.3568e-05, -9.0853e-05, 3.1246e-05,\n 1.3244e-04, -1.4346e-04, -1.5873e-05, -1.9819e-05, 2.8648e-05,\n 1.6608e-05, 3.4098e-05, 2.3243e-05, 6.4100e-05, -6.9640e-05,\n 1.8328e-05, 1.8170e-05, 2.6090e-05, 1.9095e-04, 4.2249e-05,\n 8.1091e-05, 8.7391e-05, -2.3452e-05, -6.1032e-05, 5.3856e-05,\n 6.4798e-05, -7.1798e-05, 1.0194e-05, 1.7133e-05, -9.4194e-05,\n 2.4280e-05, -1.9878e-04, 9.2077e-05, -5.8714e-04, -5.3370e-05,\n -2.6942e-05, -2.0585e-05, -7.4576e-05, -3.4586e-04, 1.4634e-05,\n -3.4149e-05, -2.3888e-06, 1.0318e-04, -2.3239e-05, 8.8226e-05,\n -1.9736e-06, -4.0821e-05, -8.3564e-04, 2.4744e-04, -1.6570e-04,\n -3.3015e-05, 1.8574e-04, -3.1334e-05, -9.4602e-06, -1.0565e-06,\n -1.4578e-04, 2.3214e-04, -1.1919e-04, -7.9462e-05, -7.1985e-05,\n 6.0604e-05, -7.9321e-05, -4.5330e-05, 3.2304e-05, 5.0470e-05,\n 1.3701e-04, 1.8859e-05, -6.8587e-05, 2.4260e-05, 1.2617e-05,\n 7.1835e-05, 4.2646e-05, -1.7265e-05, 6.1236e-05, 3.6988e-05,\n -4.6912e-05, 6.4976e-05, 9.1916e-05, -4.7202e-05, 6.8479e-06,\n 1.9011e-05, -5.2862e-05, -7.5250e-05, -3.7138e-05, 7.9102e-06,\n -5.2851e-06, -2.7196e-05, -8.6850e-05, -6.9079e-05, -5.0382e-05,\n 9.8777e-05, 7.0091e-05, -1.1111e-04, -9.7346e-06, -1.1283e-04,\n 5.8809e-05, 2.9104e-05, 5.8559e-05, -4.2261e-05, 1.0276e-04,\n -2.7349e-04, -5.5779e-06, 5.4826e-06, 7.3183e-05, -2.8821e-05,\n -4.8189e-05, -6.6756e-05, 7.4073e-06, 9.3542e-05, -9.4076e-05,\n 8.9778e-05, -3.6717e-05, -1.2366e-05, -9.7022e-05, -1.9234e-04,\n 7.9929e-05, -1.7940e-06, -2.7940e-05, -1.8694e-04, 1.1501e-05,\n 3.7890e-05, 4.4821e-06]), 'exp_avg_sq': tensor([3.2529e-06, 5.9950e-07, 6.4385e-07, 6.4926e-06, 8.3684e-07, 7.7317e-07,\n 1.8100e-06, 3.4501e-07, 1.0099e-06, 2.5264e-06, 4.7927e-06, 6.6761e-06,\n 5.4105e-07, 1.1512e-06, 1.5300e-07, 3.5242e-06, 6.6423e-06, 1.1860e-05,\n 7.3490e-07, 3.1553e-06, 3.0882e-06, 1.1025e-06, 3.5836e-07, 8.2537e-07,\n 8.1131e-07, 6.1240e-07, 9.5534e-08, 5.5302e-07, 2.2995e-07, 8.2202e-06,\n 6.4430e-07, 2.4170e-06, 2.7291e-07, 1.5708e-06, 9.3494e-07, 6.1593e-07,\n 1.7059e-06, 7.8122e-06, 2.4481e-06, 6.1532e-08, 2.5962e-06, 5.4388e-05,\n 1.2307e-06, 1.4034e-06, 2.4029e-06, 3.9767e-06, 8.2466e-07, 6.3729e-08,\n 1.2026e-06, 4.6077e-06, 4.6487e-06, 1.0016e-06, 2.1043e-07, 6.5140e-07,\n 4.9435e-07, 4.0000e-06, 1.1506e-06, 1.1767e-06, 7.2316e-07, 2.2190e-07,\n 4.3546e-07, 6.9785e-07, 1.1072e-06, 7.0434e-07, 1.9786e-06, 1.7521e-06,\n 5.1005e-07, 1.6760e-06, 3.0132e-07, 6.5501e-07, 1.8867e-07, 3.5612e-07,\n 2.5412e-06, 5.1581e-06, 3.9441e-07, 4.2103e-06, 3.3541e-07, 3.6390e-07,\n 2.9325e-06, 3.9645e-07, 1.6766e-06, 1.0886e-06, 1.4453e-06, 1.6646e-06,\n 3.1377e-07, 4.3183e-07, 4.4599e-07, 9.0042e-07, 5.7389e-06, 7.5330e-07,\n 9.2340e-07, 3.5350e-07, 8.0867e-07, 6.4668e-07, 7.6811e-07, 1.0309e-07,\n 2.0718e-06, 6.5104e-07, 1.2385e-06, 7.3970e-07, 4.8773e-07, 5.1185e-07,\n 3.1285e-07, 1.1855e-06, 1.8524e-06, 4.2988e-07, 6.2683e-07, 2.1132e-06,\n 7.2407e-08, 6.7407e-07, 7.9028e-07, 1.1245e-06, 1.5501e-06, 2.3876e-06,\n 4.5707e-07, 8.9936e-07, 6.5451e-07, 8.0096e-06, 1.3331e-07, 4.0537e-07,\n 2.5753e-06, 5.3654e-07, 1.6972e-06, 1.6946e-06, 2.9865e-07, 7.5216e-06,\n 6.3023e-06, 2.5357e-05, 4.4450e-07, 1.2024e-06, 1.9386e-06, 4.5781e-06,\n 2.3207e-07, 5.6396e-07, 3.4401e-06, 1.2112e-06, 3.1294e-06, 1.7987e-05,\n 2.4915e-06, 3.2347e-06, 1.4414e-05, 4.8438e-07, 8.5925e-07, 4.8490e-07,\n 2.0897e-06, 5.5802e-07, 9.2136e-08, 1.0456e-06, 3.6625e-07, 2.0948e-06,\n 1.5582e-06, 4.2312e-07, 8.3246e-07, 2.0829e-06, 1.0685e-06, 1.4314e-07,\n 6.6788e-07, 3.7945e-06, 1.6857e-06, 1.1470e-06, 2.5813e-06, 1.5796e-07,\n 5.4035e-06, 2.5528e-07, 1.4680e-06, 1.6551e-05, 1.7791e-06, 2.0202e-06,\n 5.3686e-07, 1.2525e-06, 5.6718e-07, 5.6279e-07, 3.9634e-07, 1.9139e-06,\n 7.9501e-07, 2.2682e-07, 1.6734e-06, 5.2719e-06, 2.1564e-06, 1.6993e-05,\n 1.1958e-06, 4.1575e-07, 1.4983e-06, 4.2147e-06, 3.7510e-07, 1.2244e-06,\n 6.9679e-07, 3.5936e-07, 3.3025e-07, 8.9553e-07, 2.4549e-06, 2.2299e-06,\n 6.1646e-07, 3.8100e-07, 3.8508e-07, 1.2034e-07, 6.1472e-07, 1.3256e-07,\n 6.8870e-07, 2.2182e-06, 5.7168e-07, 5.8514e-07, 2.4425e-07, 5.2238e-06,\n 5.2557e-07, 4.0539e-07, 4.8999e-07, 2.0276e-06, 4.6142e-07, 5.2360e-06,\n 2.3811e-06, 4.2744e-07, 3.8114e-07, 1.5677e-05, 3.1915e-07, 3.7733e-07,\n 8.2175e-07, 1.8555e-07, 3.9987e-06, 5.5156e-07, 5.2842e-07, 4.1421e-06,\n 1.2297e-05, 2.3059e-06, 1.0844e-06, 5.4855e-07, 3.0204e-06, 2.5321e-06,\n 2.9265e-07, 2.9323e-06, 5.8676e-06, 1.0024e-06, 1.0275e-06, 1.8059e-05,\n 4.5157e-07, 3.5587e-06, 8.6364e-07, 3.2966e-06, 7.8582e-07, 2.2354e-06,\n 9.3508e-07, 1.5831e-06, 6.4766e-07, 3.8402e-07, 5.0728e-06, 2.1255e-06,\n 2.4211e-07, 1.9252e-06, 1.7398e-07, 1.4459e-06, 4.0026e-06, 1.5444e-06,\n 5.2143e-07, 9.7512e-07, 9.8805e-07, 3.9949e-06, 2.1236e-06, 1.2686e-06,\n 9.0293e-07, 4.4480e-07, 8.2447e-07, 7.2899e-07, 3.5695e-07, 1.9364e-06,\n 3.1186e-07, 1.1831e-06, 3.5906e-07, 2.1285e-06, 2.1587e-06, 8.8166e-07,\n 3.0118e-07, 6.8533e-07, 1.4516e-05, 5.2358e-07, 5.0903e-07, 2.5216e-06,\n 7.0679e-06, 2.7929e-06, 2.9084e-07, 8.8318e-07, 2.0360e-07, 3.8375e-06,\n 4.8260e-06, 7.5325e-07, 3.4973e-07, 4.2698e-06, 6.3510e-07, 2.1287e-06,\n 9.5692e-07, 3.4130e-06, 4.1159e-07, 1.8422e-06, 7.0126e-07, 7.1777e-07,\n 7.6351e-07, 5.8826e-07, 1.1515e-06, 4.5462e-06, 1.8147e-06, 1.1290e-06,\n 2.8565e-07, 1.7973e-06, 5.8503e-07, 1.8290e-06, 4.9750e-07, 8.4643e-07,\n 3.0138e-07, 5.2527e-06, 4.0103e-07, 2.1267e-06, 5.6600e-07, 4.4962e-07,\n 6.7196e-07, 2.7100e-07, 3.7269e-07, 1.6105e-06, 3.5052e-07, 5.5260e-07,\n 7.7023e-07, 6.4763e-07, 1.0097e-06, 4.7591e-06, 1.5240e-06, 2.5362e-06,\n 6.5367e-07, 2.4832e-06, 9.4992e-07, 2.2875e-07, 1.2520e-05, 8.5712e-07,\n 1.5142e-06, 1.0313e-06, 1.8622e-06, 3.1538e-07, 2.8001e-07, 1.6066e-06,\n 1.0219e-06, 1.6786e-06, 2.8420e-06, 5.7630e-07, 1.3301e-06, 3.0701e-07,\n 1.4959e-06, 1.0078e-06, 4.7386e-07, 3.0283e-06, 8.5580e-07, 7.4663e-07,\n 2.5895e-07, 5.7453e-07, 5.2020e-06, 6.8069e-07, 7.7583e-07, 4.4151e-07,\n 1.4977e-06, 9.1817e-07, 1.6653e-06, 1.4386e-06, 3.2932e-07, 4.0774e-07,\n 3.1915e-06, 1.9250e-06, 7.8491e-07, 8.9735e-07, 8.8426e-07, 1.8531e-07,\n 1.0603e-06, 4.6517e-07, 2.3150e-06, 5.4471e-07, 2.2078e-06, 3.4824e-07,\n 3.3432e-06, 2.3010e-07, 1.4439e-06, 3.8264e-06, 6.8001e-07, 1.5871e-07,\n 8.8258e-07, 1.3659e-06, 2.4039e-06, 6.2602e-07, 3.7738e-07, 4.8435e-06,\n 8.4195e-07, 9.2917e-07, 1.0008e-06, 9.4360e-07, 8.1930e-07, 4.8024e-07,\n 2.7240e-06, 7.0811e-07, 1.8811e-07, 1.1379e-06, 5.5753e-06, 1.1777e-06,\n 3.3146e-06, 1.2682e-07, 1.6475e-06, 2.6808e-06, 5.2015e-07, 2.8565e-07,\n 2.2664e-07, 4.3952e-07, 3.0672e-06, 1.4720e-06, 2.6456e-07, 1.5411e-06,\n 4.2012e-06, 4.6102e-07, 1.4250e-06, 6.0208e-07, 2.7288e-07, 1.1825e-06,\n 1.2822e-05, 7.0427e-07, 1.3386e-06, 3.2740e-07, 1.9770e-06, 7.8353e-07,\n 6.3103e-07, 4.0398e-06, 1.9162e-06, 1.2315e-05, 4.6845e-06, 8.7961e-07,\n 1.5565e-06, 3.5127e-07, 2.9662e-06, 2.8444e-07, 3.3536e-07, 1.8425e-06,\n 2.1818e-06, 4.4840e-07, 3.0396e-06, 3.5857e-08, 1.4312e-06, 3.4512e-05,\n 1.5643e-05, 1.5163e-06, 4.4393e-07, 1.6229e-06, 2.5596e-06, 6.0195e-07,\n 7.1752e-07, 4.1015e-06, 7.1618e-06, 8.6300e-07, 7.7545e-07, 1.9282e-05,\n 9.7123e-07, 4.4731e-07, 2.8567e-06, 1.8668e-06, 6.5876e-07, 2.4052e-06,\n 8.4421e-07, 1.0656e-06, 4.3588e-07, 3.7517e-06, 4.1240e-05, 2.3036e-06,\n 8.7315e-07, 1.9278e-07, 2.5610e-07, 1.1247e-06, 1.6511e-06, 2.1989e-06,\n 2.3523e-06, 1.0795e-06, 1.4537e-06, 3.4529e-06, 9.5203e-07, 2.6135e-07,\n 1.0825e-07, 5.7586e-07, 5.8169e-06, 3.4986e-06, 1.7143e-06, 3.9438e-07,\n 1.6241e-06, 5.1027e-07, 2.4083e-06, 1.5274e-06, 1.6289e-06, 1.7689e-06,\n 2.3863e-07, 8.9084e-06, 9.9834e-07, 4.1405e-06, 2.7122e-06, 3.0059e-07,\n 8.9692e-07, 2.9218e-06, 5.5086e-07, 6.5976e-07, 6.8928e-07, 8.9973e-07,\n 4.1128e-05, 6.9448e-07, 7.1187e-07, 2.2639e-07, 3.6115e-07, 4.0576e-06,\n 1.1979e-06, 2.7908e-06, 7.4842e-07, 6.3072e-07, 2.3796e-06, 9.5920e-07,\n 4.0079e-07, 2.9611e-06])}, 131: {'step': 7160, 'exp_avg': tensor([ 2.2891e-05, -1.4303e-05, 2.2769e-05, 6.9653e-05, -1.8053e-05,\n 7.3955e-05, 1.0680e-04, -1.8716e-05, -2.4305e-05, 7.7264e-05,\n -1.5304e-04, -1.1391e-04, -1.4106e-05, -7.5278e-05, -1.4289e-05,\n 7.0806e-05, -1.1902e-04, -2.6198e-04, 1.5893e-05, -1.2920e-04,\n -7.5188e-05, -2.0856e-05, -1.8507e-05, -2.9387e-06, 2.7306e-05,\n -6.8423e-05, -4.1404e-05, -1.5045e-05, -2.3840e-05, 9.6608e-05,\n 7.0709e-05, 2.4680e-05, 2.5661e-05, 3.9489e-05, -1.7880e-05,\n -5.6348e-05, -1.7950e-05, -2.1137e-05, 9.7706e-05, 3.4271e-06,\n 1.4612e-04, 9.1325e-05, -1.2067e-04, 1.5839e-04, -3.6687e-05,\n 7.3755e-05, -7.4846e-05, -5.6488e-06, -5.8406e-05, 3.2372e-05,\n -1.3170e-04, -4.7464e-05, 2.6685e-05, -4.1072e-05, 9.0298e-07,\n 1.7040e-04, -2.2766e-05, 7.3763e-06, -2.0524e-05, 2.0300e-05,\n -4.3732e-05, 3.0215e-05, -5.2296e-05, 7.4501e-05, -1.5627e-04,\n -3.2776e-05, -2.8267e-05, 1.9119e-04, -2.1507e-05, 1.2974e-04,\n 2.9742e-06, 6.8935e-05, -1.9193e-05, -3.8059e-05, -5.1923e-05,\n 1.8760e-04, -4.7814e-05, -4.4884e-05, -1.4051e-04, -6.7396e-06,\n -5.6027e-05, 3.0325e-05, 5.9012e-06, 1.0280e-04, 9.9150e-05,\n -1.4016e-05, -1.3526e-05, 4.0613e-06, 1.7516e-05, 4.7874e-05,\n 6.9303e-07, -3.4871e-05, -1.1592e-04, -4.8137e-05, 4.5282e-05,\n 4.8881e-06, -1.1530e-05, -6.7445e-05, -5.0050e-06, 1.1455e-06,\n 1.3218e-05, 6.4662e-05, 3.3659e-05, 1.1392e-04, 4.3012e-05,\n -3.9187e-05, 8.3821e-06, -1.1365e-04, -5.8675e-06, -6.1799e-06,\n 5.4923e-05, 1.0997e-04, -1.8006e-05, -1.2071e-05, 1.1930e-05,\n -1.9135e-05, 7.0195e-05, -2.7051e-05, -1.8932e-05, -2.7012e-06,\n 1.0143e-04, 6.5705e-05, -3.5055e-05, -1.9603e-04, -2.5894e-05,\n -6.0806e-05, 4.5014e-07, -1.1369e-04, 3.7410e-05, -1.1466e-04,\n -1.1848e-04, -6.8042e-06, 1.3159e-05, -6.6342e-05, -9.5383e-05,\n 7.2486e-05, -2.2525e-05, -1.0032e-04, -6.3878e-05, -1.9625e-05,\n -1.8747e-04, -2.3426e-05, 4.0191e-05, -4.5432e-05, -5.5456e-07,\n 2.3978e-05, 7.3154e-06, -9.8164e-05, -6.4564e-05, -3.0367e-05,\n 4.8874e-05, 1.8229e-05, -6.4971e-05, 3.2722e-05, 1.9009e-06,\n -3.4643e-05, 4.0123e-06, -5.7782e-05, -3.2514e-05, -4.2492e-05,\n -1.7957e-04, -2.3923e-06, 6.2395e-05, -1.2679e-05, 1.4691e-06,\n -1.7345e-04, 9.7210e-05, -7.7367e-05, -9.7871e-07, -5.6695e-05,\n 1.4024e-05, -1.6191e-05, 2.2270e-05, 3.2882e-05, 4.6540e-05,\n 2.4888e-05, 9.5558e-05, -1.0054e-04, -2.0443e-05, -3.4388e-04,\n -2.0908e-05, 1.4691e-05, -6.8146e-05, -7.8590e-05, -7.2282e-06,\n -3.7447e-06, -8.4562e-06, -8.2799e-06, 6.4852e-05, -1.7238e-05,\n -1.0989e-05, 1.1585e-05, 2.7595e-05, -1.6482e-05, 3.6819e-05,\n 2.9579e-05, -2.2557e-05, -2.2318e-05, 8.8496e-07, -4.6892e-05,\n 3.9544e-05, 2.6307e-05, 4.1862e-06, -1.2581e-04, 3.1251e-05,\n -4.2305e-05, -3.1067e-05, 7.4495e-05, 8.6880e-05, 1.0244e-04,\n 5.5560e-05, -1.0264e-05, -4.6618e-06, -1.6775e-04, 1.8441e-06,\n 1.0459e-05, 4.4530e-05, -2.6629e-05, 1.6243e-05, 4.0638e-05,\n -1.4937e-05, -1.4355e-04, -4.1624e-04, 3.2254e-06, -5.4197e-05,\n -5.0389e-06, -2.2238e-05, -1.4276e-05, -6.5318e-06, 1.3312e-04,\n -3.9410e-05, 3.9390e-05, -2.0359e-05, 3.4931e-04, -5.5152e-06,\n -5.2268e-05, 1.0775e-05, -8.1135e-05, 8.9101e-06, 2.9583e-05,\n -1.1328e-04, 7.2927e-05, -1.9000e-05, 3.0585e-05, -1.9724e-05,\n 5.8538e-05, -4.4746e-05, -5.6143e-05, 5.0374e-06, -6.4367e-05,\n 6.3915e-05, -9.9883e-05, 1.1670e-05, 7.1975e-05, 4.8813e-05,\n -2.0769e-04, -3.9899e-05, 1.0592e-04, 5.0119e-05, -4.2922e-05,\n -6.2147e-05, -5.4186e-05, -2.6521e-06, -1.5491e-04, 5.7776e-06,\n -7.8511e-06, 2.4662e-05, 1.0862e-04, 6.9373e-05, -4.5434e-05,\n -2.2047e-05, 6.8881e-05, -6.7890e-05, -1.2386e-05, 9.4935e-05,\n 9.5396e-05, -1.0896e-05, -2.2059e-04, 1.3287e-05, 3.8310e-05,\n 5.4547e-05, -8.9153e-05, -1.0892e-04, -3.6402e-05, -2.4630e-05,\n -3.0733e-05, 4.9977e-05, 2.9449e-06, 4.5099e-05, 1.5506e-06,\n 2.5734e-05, -5.0882e-05, -2.7252e-05, 6.1721e-05, -1.4240e-06,\n 3.1719e-06, -3.0598e-06, 1.5933e-05, 1.2317e-04, -1.0152e-04,\n -4.2413e-05, -3.7521e-05, 8.4930e-05, -5.0136e-05, 1.0323e-04,\n 5.7354e-05, -2.4450e-05, 1.1532e-04, -2.3685e-05, -6.6492e-05,\n 4.9172e-05, -7.4765e-06, -1.5277e-05, -4.2210e-05, 2.1219e-05,\n -7.4542e-05, 1.4594e-05, 7.2377e-06, 7.3113e-05, 7.1045e-06,\n -1.6621e-05, -1.7618e-05, 2.9777e-05, -4.6732e-05, 2.7254e-05,\n -1.9081e-05, -2.4529e-05, 3.8031e-05, -7.6232e-05, 3.3954e-05,\n -4.7653e-05, -5.0774e-05, -6.5582e-05, -4.1205e-05, 6.5063e-05,\n -5.2015e-05, -5.5339e-05, -8.3762e-05, 4.0462e-05, -2.1108e-05,\n -3.0435e-07, -2.7754e-05, 5.0407e-05, 5.2927e-05, -1.6594e-05,\n -1.3440e-04, -2.0316e-06, -3.4880e-05, 9.9840e-08, 7.8428e-05,\n 1.0283e-04, -2.0000e-05, -4.2721e-05, -2.9781e-05, 5.0272e-05,\n 1.2926e-05, 6.9063e-05, -1.6491e-05, 1.0845e-05, 3.3396e-05,\n 1.6172e-05, 5.6159e-05, 2.2362e-05, 3.7048e-05, -6.2987e-06,\n 1.1479e-05, 3.8581e-05, 2.2546e-05, -9.0743e-06, 2.1519e-05,\n -2.0230e-05, 4.3260e-05, -6.1701e-05, -6.2116e-05, -2.7768e-06,\n 5.8042e-05, 9.8013e-05, 1.2604e-05, 6.9209e-06, -4.6708e-05,\n 2.3644e-05, -1.4209e-05, -3.6442e-06, -1.9547e-04, -4.9832e-06,\n 1.0386e-05, -7.0599e-05, -4.5633e-05, -2.1662e-05, -5.9000e-06,\n -1.0706e-04, -3.4666e-05, 5.4716e-06, -5.5743e-05, -2.8540e-05,\n 6.3230e-05, -1.0526e-04, -1.0590e-05, -5.9517e-06, 5.1797e-05,\n 3.0725e-06, 2.3592e-05, 1.4793e-05, 2.7883e-05, -5.6911e-05,\n 1.8996e-05, 1.1133e-05, 1.4726e-05, 9.1347e-05, 4.8016e-05,\n 4.2891e-05, 4.5844e-05, -2.8634e-05, -3.8050e-05, -4.4030e-05,\n 4.2809e-05, -5.8417e-05, 2.5068e-06, 9.1210e-07, -9.0082e-05,\n 3.2850e-05, -1.3153e-04, 1.3416e-04, -1.2333e-04, -4.6202e-05,\n -1.0211e-05, -1.6875e-05, -7.7058e-05, -3.6343e-04, 1.0166e-05,\n -1.9228e-05, -1.8700e-05, 3.0451e-05, -3.2115e-05, 3.4954e-05,\n -1.5252e-06, -7.0173e-05, -5.4167e-04, -4.0353e-05, -1.4510e-04,\n -1.8439e-05, 5.5599e-05, -3.0072e-05, 2.0008e-06, -8.1310e-07,\n -8.2211e-05, 1.3509e-04, -5.2467e-05, -4.8109e-05, -5.8457e-05,\n 1.1663e-05, -5.5816e-05, 1.7452e-05, -1.8519e-06, -1.1964e-06,\n 1.0729e-04, 5.0463e-05, -5.8187e-05, 5.6412e-06, 1.5511e-05,\n -1.0236e-04, 6.4728e-06, -2.6452e-05, 4.1445e-05, 3.0462e-05,\n -2.8511e-05, 3.8186e-05, 5.7917e-05, -2.6689e-05, -3.5830e-05,\n 1.8614e-05, -7.8378e-05, -7.6257e-05, -3.0998e-05, 5.4519e-06,\n -4.3502e-06, -5.2201e-05, -7.7370e-05, -3.7970e-05, -5.1953e-05,\n 6.9094e-05, 5.3247e-05, -8.1782e-05, -1.1115e-06, -9.9064e-05,\n 1.5912e-05, 2.4901e-05, -1.4256e-05, -5.1880e-05, 3.7250e-05,\n -1.3819e-04, -2.7932e-07, -3.1771e-09, 3.7652e-05, -4.2038e-05,\n -5.9042e-05, -6.2991e-05, 1.9646e-06, -2.8211e-05, -1.1869e-04,\n 6.6032e-05, -2.0897e-05, -1.5816e-05, -9.5538e-05, -1.1106e-04,\n 1.2648e-04, -9.6110e-06, -3.3435e-05, -1.3562e-04, 2.4218e-06,\n 2.4924e-05, -2.1732e-05]), 'exp_avg_sq': tensor([1.3770e-06, 1.5526e-07, 6.9288e-07, 2.2691e-06, 3.1925e-07, 1.5307e-06,\n 1.0254e-06, 1.4820e-07, 3.2483e-07, 1.3908e-06, 1.9200e-06, 2.3793e-06,\n 2.4838e-07, 5.6566e-07, 7.6631e-08, 2.1804e-06, 1.8341e-06, 4.7541e-06,\n 3.4696e-07, 1.7115e-06, 1.0841e-06, 5.7347e-07, 3.6603e-07, 4.3927e-07,\n 4.8464e-07, 4.2700e-07, 5.3202e-08, 2.3994e-07, 1.2058e-07, 2.3914e-06,\n 4.9699e-07, 1.1692e-06, 9.7146e-08, 3.4835e-07, 5.6875e-07, 3.4994e-07,\n 1.0382e-06, 3.9938e-06, 1.2679e-06, 3.2090e-08, 1.2773e-06, 1.0207e-05,\n 5.5495e-07, 8.4302e-07, 1.0321e-06, 2.3875e-06, 4.6263e-07, 3.4403e-08,\n 3.9016e-07, 3.0785e-06, 1.4520e-06, 6.3692e-07, 8.0675e-08, 1.9153e-07,\n 1.9111e-07, 1.5968e-06, 7.7594e-07, 1.0129e-06, 5.8145e-07, 8.0696e-08,\n 2.7470e-07, 2.4257e-07, 4.4514e-07, 4.1626e-07, 1.1118e-06, 8.3246e-07,\n 3.4828e-07, 1.7264e-06, 1.7416e-07, 6.2637e-07, 6.4430e-08, 2.3038e-07,\n 5.5713e-07, 1.2451e-06, 2.4568e-07, 3.1456e-06, 1.7778e-07, 1.9272e-07,\n 7.9888e-07, 1.6953e-07, 6.3462e-07, 4.4792e-07, 1.2616e-06, 7.6767e-07,\n 2.9078e-07, 1.6862e-07, 4.1315e-07, 4.8083e-07, 3.5309e-06, 2.9057e-07,\n 3.2194e-07, 1.8507e-07, 3.7447e-07, 2.9108e-07, 3.5723e-07, 5.2388e-08,\n 1.0455e-06, 2.0881e-07, 6.7477e-07, 4.2587e-07, 1.2078e-07, 1.9058e-07,\n 1.2839e-07, 1.2609e-06, 8.1972e-07, 2.7251e-07, 3.9524e-07, 1.1298e-06,\n 3.0235e-08, 2.6963e-07, 4.2560e-07, 5.9197e-07, 7.6623e-07, 8.9272e-07,\n 1.8377e-07, 5.1228e-07, 3.4928e-07, 3.3456e-06, 5.3383e-08, 2.1303e-07,\n 9.1382e-07, 4.2212e-07, 8.8943e-07, 1.3336e-06, 1.2977e-07, 1.3911e-06,\n 1.5516e-06, 7.6939e-06, 1.9757e-07, 5.5119e-07, 5.3831e-07, 2.0079e-06,\n 1.4130e-07, 2.0813e-07, 8.8190e-07, 7.4078e-07, 1.7183e-06, 6.4869e-06,\n 6.7378e-07, 1.4105e-06, 5.7057e-06, 3.0127e-07, 3.8251e-07, 1.8101e-07,\n 1.4273e-06, 2.3813e-07, 7.1452e-08, 3.9990e-07, 1.7892e-07, 1.0130e-06,\n 7.0095e-07, 2.4853e-07, 3.9150e-07, 1.6639e-06, 1.4867e-06, 1.3223e-07,\n 4.0680e-07, 1.6248e-06, 8.7614e-07, 3.7093e-07, 9.9268e-07, 6.5607e-08,\n 1.9514e-06, 8.9664e-08, 1.1206e-06, 1.3038e-05, 1.2757e-06, 1.0078e-06,\n 2.1505e-07, 8.3380e-07, 2.5264e-07, 2.0185e-07, 2.1325e-07, 1.0971e-06,\n 2.9618e-07, 1.0764e-07, 9.9047e-07, 2.9380e-06, 8.7357e-07, 9.2552e-06,\n 5.4540e-07, 2.1367e-07, 6.8395e-07, 1.7223e-06, 1.9525e-07, 3.0874e-07,\n 2.3349e-07, 2.6949e-07, 1.8282e-07, 3.3803e-07, 6.2282e-07, 6.4529e-07,\n 3.2276e-07, 1.6982e-07, 1.3552e-07, 8.1345e-08, 2.6960e-07, 6.4064e-08,\n 3.0655e-07, 9.4334e-07, 2.8024e-07, 2.2808e-07, 1.9416e-07, 2.0902e-06,\n 3.1514e-07, 1.6574e-07, 3.0093e-07, 2.5460e-06, 4.0302e-07, 1.9623e-06,\n 6.0224e-07, 2.1412e-07, 4.2885e-07, 8.0520e-06, 1.9322e-07, 2.4974e-07,\n 4.8048e-07, 6.3612e-08, 1.2331e-06, 2.6323e-07, 2.6159e-07, 1.5339e-06,\n 7.7049e-06, 5.5831e-07, 4.3718e-07, 3.0321e-07, 1.2590e-06, 1.0512e-06,\n 2.1466e-07, 8.2011e-07, 1.7183e-06, 4.8457e-07, 4.2129e-07, 8.4176e-06,\n 2.0444e-07, 1.4217e-06, 6.2878e-07, 1.0115e-06, 2.9968e-07, 1.3948e-06,\n 7.5813e-07, 5.3670e-07, 2.4486e-07, 1.9349e-07, 2.3706e-06, 1.9233e-06,\n 2.0416e-07, 1.2873e-06, 8.7882e-08, 7.8949e-07, 2.8947e-06, 6.0334e-07,\n 1.8706e-07, 3.6010e-07, 7.0611e-07, 2.2839e-06, 9.5413e-07, 5.8988e-07,\n 5.0642e-07, 2.5148e-07, 4.7759e-07, 2.3774e-07, 3.8998e-07, 1.7259e-06,\n 1.7996e-07, 9.6324e-07, 1.8303e-07, 1.0633e-06, 5.5128e-07, 5.2631e-07,\n 1.1381e-07, 4.3554e-07, 7.5451e-06, 2.2162e-07, 1.9602e-07, 1.4939e-06,\n 2.3644e-06, 1.8646e-06, 1.6390e-07, 4.0113e-07, 1.2837e-07, 1.0008e-06,\n 1.6374e-06, 4.8774e-07, 1.1286e-07, 3.8078e-06, 1.9171e-07, 6.1242e-07,\n 6.7904e-07, 1.2987e-06, 6.0541e-07, 7.4957e-07, 2.7449e-07, 2.3450e-07,\n 3.0434e-07, 3.6127e-07, 5.0481e-07, 1.3973e-06, 1.4230e-06, 4.1875e-07,\n 2.7049e-07, 6.4601e-07, 2.3378e-07, 7.2065e-07, 2.4944e-07, 4.5097e-07,\n 1.2415e-07, 4.1122e-06, 3.3960e-07, 1.4574e-06, 2.5653e-07, 2.3415e-07,\n 2.8353e-07, 1.1288e-07, 2.1889e-07, 9.8154e-07, 1.9563e-07, 2.4662e-07,\n 3.3261e-07, 2.3241e-07, 2.6012e-07, 1.4470e-06, 1.0970e-06, 2.0659e-06,\n 3.3746e-07, 5.8395e-07, 2.9077e-07, 1.6088e-07, 5.0421e-06, 3.7616e-07,\n 7.8111e-07, 6.1065e-07, 1.8043e-06, 2.3576e-07, 1.5467e-07, 6.1134e-07,\n 3.6171e-07, 9.9360e-07, 1.9642e-06, 4.7654e-07, 2.9750e-07, 1.0385e-07,\n 4.5190e-07, 6.6563e-07, 3.5277e-07, 1.7851e-06, 5.3917e-07, 5.1365e-07,\n 1.4807e-07, 2.7076e-07, 3.5010e-06, 2.4200e-07, 2.0191e-07, 1.3374e-07,\n 4.9950e-07, 1.8359e-07, 4.5319e-07, 8.5978e-07, 1.6615e-07, 1.8746e-07,\n 1.0451e-06, 1.0451e-06, 3.5331e-07, 5.9749e-07, 5.2010e-07, 1.4904e-07,\n 4.3314e-07, 1.4200e-07, 5.2952e-07, 1.9391e-07, 4.6526e-07, 1.6332e-07,\n 1.0761e-06, 1.5798e-07, 7.3148e-07, 1.7203e-06, 3.6663e-07, 1.0014e-07,\n 7.0630e-07, 5.5607e-07, 1.1317e-06, 4.5686e-07, 2.2226e-07, 2.6432e-06,\n 3.2786e-07, 3.1060e-07, 5.5108e-07, 4.1325e-07, 5.7387e-07, 2.3508e-07,\n 1.1480e-06, 2.8319e-07, 9.1061e-08, 3.8520e-07, 1.6090e-06, 7.0539e-07,\n 1.6630e-06, 4.1925e-08, 9.5235e-07, 7.5186e-07, 3.8792e-07, 8.7740e-08,\n 9.3625e-08, 1.3530e-07, 1.0791e-06, 2.8413e-07, 1.2134e-07, 6.9944e-07,\n 1.3607e-06, 3.3614e-07, 5.0562e-07, 2.5404e-07, 1.9954e-07, 5.8120e-07,\n 3.6520e-06, 5.4256e-07, 5.0449e-07, 1.0156e-07, 1.1582e-06, 4.4679e-07,\n 2.6211e-07, 1.3808e-06, 1.0065e-06, 3.1220e-06, 1.2086e-06, 2.8375e-07,\n 6.5385e-07, 1.7180e-07, 2.9896e-06, 6.7833e-08, 1.3452e-07, 5.4340e-07,\n 9.9748e-07, 2.0051e-07, 1.6615e-06, 1.5885e-08, 7.8229e-07, 1.5415e-05,\n 1.5463e-06, 9.7667e-07, 1.4395e-07, 8.0867e-07, 1.3405e-06, 2.5887e-07,\n 3.2315e-07, 1.2770e-06, 2.7216e-06, 3.1423e-07, 2.5222e-07, 6.9468e-06,\n 3.6622e-07, 2.3971e-07, 9.3627e-07, 4.6829e-07, 2.6121e-07, 1.0814e-06,\n 6.4139e-07, 4.5646e-07, 2.4762e-07, 2.6202e-06, 1.5029e-05, 1.0178e-06,\n 2.7540e-07, 1.3711e-07, 1.2748e-07, 1.1010e-06, 6.0961e-07, 8.5630e-07,\n 8.8159e-07, 3.6869e-07, 7.3911e-07, 1.8532e-06, 6.1226e-07, 1.6102e-07,\n 5.8184e-08, 2.0366e-07, 1.7037e-06, 1.3705e-06, 3.5979e-07, 2.5400e-07,\n 4.7797e-07, 2.4177e-07, 1.0980e-06, 6.0019e-07, 1.0211e-06, 8.8913e-07,\n 1.4400e-07, 3.2916e-06, 3.5849e-07, 1.3412e-06, 1.1875e-06, 2.1635e-07,\n 6.3176e-07, 1.7465e-06, 2.4211e-07, 7.2731e-07, 2.9660e-07, 3.6416e-07,\n 1.6998e-05, 7.1690e-07, 5.1209e-07, 7.5234e-08, 2.1853e-07, 2.1798e-06,\n 4.1742e-07, 2.3713e-06, 3.1953e-07, 5.6509e-07, 1.1284e-06, 5.8766e-07,\n 1.1220e-07, 1.1767e-06])}, 132: {'step': 7160, 'exp_avg': tensor([[[[ 1.3987e-06, -5.5943e-06, 4.6961e-06],\n [ 2.2716e-06, 1.8467e-06, 5.0596e-06],\n [ 7.3758e-07, 2.7631e-06, 1.5943e-06]],\n\n [[ 4.1942e-07, -1.6293e-08, -2.8979e-07],\n [ 1.9560e-06, 2.8678e-06, 2.6317e-06],\n [ 3.1153e-06, 2.6854e-06, 4.8653e-06]],\n\n [[-1.0657e-05, -3.3172e-06, 9.2642e-06],\n [-4.5886e-06, 6.3728e-07, 7.8662e-06],\n [ 1.2696e-06, 6.5941e-06, 7.2177e-06]],\n\n ...,\n\n [[ 1.0428e-06, 2.2731e-07, -2.1860e-06],\n [ 2.1972e-07, 3.6883e-06, -8.1303e-07],\n [ 4.4109e-06, 7.2764e-06, 5.3747e-06]],\n\n [[ 4.2078e-07, -7.3571e-07, 2.1453e-06],\n [ 4.1512e-07, -1.0681e-07, 2.6825e-06],\n [ 3.5472e-06, 1.7855e-06, 2.8681e-06]],\n\n [[-4.7921e-06, -5.7166e-06, -2.1692e-06],\n [ 1.0388e-06, 1.7835e-06, -3.8906e-07],\n [ 2.7553e-06, -5.1072e-06, 2.0573e-06]]],\n\n\n [[[ 5.2755e-07, 4.3087e-07, 2.5335e-06],\n [ 1.0680e-06, 1.3816e-06, 3.1294e-06],\n [ 2.3977e-06, 1.8301e-06, 2.5153e-06]],\n\n [[-4.9860e-06, -1.5650e-06, -1.8229e-06],\n [ 1.5989e-06, 4.3053e-08, 2.4193e-06],\n [ 2.4353e-06, 2.6877e-06, 1.2300e-06]],\n\n [[-3.4212e-06, 2.3604e-07, 4.2762e-06],\n [-3.4518e-07, 1.6340e-06, 4.1979e-06],\n [-9.2356e-06, 4.4158e-06, 1.0075e-05]],\n\n ...,\n\n [[-1.2817e-06, -5.5928e-07, -1.4840e-05],\n [ 1.0837e-06, 1.8769e-06, -2.9993e-06],\n [ 1.1947e-06, 2.2932e-06, 3.6459e-06]],\n\n [[ 2.6115e-07, 6.3842e-07, 1.2207e-06],\n [ 1.0709e-07, 3.3473e-07, 5.2965e-07],\n [ 3.6552e-07, 1.3585e-06, 6.8488e-07]],\n\n [[-2.9570e-06, -1.1366e-07, -4.9729e-06],\n [ 1.5905e-06, 4.5146e-06, -5.0166e-06],\n [ 4.5421e-06, -1.3836e-06, -8.4002e-06]]],\n\n\n [[[ 3.8836e-06, 3.5555e-06, 5.4220e-06],\n [ 2.2203e-06, 3.3860e-08, 5.3745e-06],\n [ 3.6436e-06, 2.5527e-06, -5.1980e-07]],\n\n [[-2.4217e-06, -7.8557e-07, -3.0717e-06],\n [-4.5792e-06, 8.7885e-07, -2.7631e-06],\n [ 1.8789e-06, -1.3542e-06, -1.7953e-06]],\n\n [[-6.4787e-08, 2.0144e-07, -4.7322e-06],\n [ 4.3592e-06, -4.7112e-06, -2.5705e-06],\n [-5.6685e-06, -1.3723e-05, -1.0355e-05]],\n\n ...,\n\n [[ 1.3062e-06, -1.2860e-06, 5.4940e-07],\n [-3.8920e-07, 1.8579e-06, -1.6753e-06],\n [-7.1520e-06, -1.9187e-05, -8.8294e-06]],\n\n [[ 6.9297e-07, 1.4460e-07, 8.0409e-07],\n [ 4.5029e-07, 8.4119e-07, -2.8062e-06],\n [-2.6903e-06, -6.3477e-07, -2.1219e-06]],\n\n [[ 1.0687e-06, 2.8103e-06, 7.5686e-07],\n [ 2.1393e-06, 9.1546e-06, 2.6313e-06],\n [ 4.1800e-06, 3.0466e-07, -1.4161e-06]]],\n\n\n ...,\n\n\n [[[ 1.2827e-06, 1.1254e-07, 2.0771e-06],\n [ 1.5320e-06, 1.0031e-06, 1.5498e-06],\n [ 2.3494e-06, 1.7449e-06, 2.1373e-06]],\n\n [[ 6.2597e-07, -1.0015e-06, -2.0935e-06],\n [ 7.1411e-08, 3.0570e-06, 1.6596e-06],\n [ 2.9805e-06, 1.3108e-06, 3.9302e-06]],\n\n [[ 8.7214e-07, 6.5519e-07, -4.0925e-06],\n [ 4.4440e-06, 1.2187e-06, 1.3405e-06],\n [-1.3013e-06, 1.4264e-06, 6.9278e-08]],\n\n ...,\n\n [[-8.2475e-07, -7.3816e-06, -3.4344e-06],\n [ 2.6450e-06, 1.9248e-06, -2.6403e-07],\n [-1.7959e-06, -3.8512e-06, -3.4335e-06]],\n\n [[-5.3182e-07, 2.6412e-07, -1.8181e-07],\n [ 3.4087e-06, 1.3112e-06, 2.5647e-06],\n [ 6.6543e-07, 1.0499e-06, 1.5389e-06]],\n\n [[ 9.4485e-07, 2.9150e-06, 1.7331e-07],\n [ 1.9672e-06, -1.2409e-07, -2.2276e-06],\n [ 2.4658e-06, -2.5776e-06, -3.7042e-06]]],\n\n\n [[[-1.6989e-07, -9.8692e-09, 3.1428e-06],\n [ 8.7582e-07, 1.8758e-07, 3.9930e-06],\n [-1.9717e-07, 6.1946e-07, 2.1658e-06]],\n\n [[ 4.0793e-07, 2.8500e-06, -1.2358e-06],\n [ 1.4582e-06, 6.3427e-06, 3.9869e-06],\n [ 2.3723e-06, 3.0577e-06, 7.4442e-06]],\n\n [[-1.0324e-06, -1.2955e-06, 7.9117e-06],\n [-2.6269e-06, -5.1992e-07, 8.6302e-06],\n [-1.8911e-06, 2.6366e-06, 2.8245e-06]],\n\n ...,\n\n [[ 1.7590e-06, 1.6266e-06, 9.0064e-07],\n [ 6.3550e-08, 6.2210e-06, 2.0458e-07],\n [ 2.8052e-06, 7.8676e-06, 6.0233e-06]],\n\n [[ 1.3093e-07, -1.9410e-06, 1.7617e-06],\n [-1.8030e-06, -1.2384e-08, 3.8343e-06],\n [ 1.7649e-06, -6.0281e-07, 2.5581e-06]],\n\n [[-4.3188e-06, 6.5367e-08, 5.2407e-06],\n [ 4.3486e-06, 3.1553e-06, 7.5081e-06],\n [ 3.1282e-06, -2.1450e-06, 9.5921e-06]]],\n\n\n [[[ 5.1677e-07, 3.0996e-07, 5.0187e-07],\n [ 1.8760e-07, -8.9720e-07, 4.4104e-07],\n [ 8.9147e-09, 3.8996e-07, 1.0421e-06]],\n\n [[ 3.8310e-07, 7.3525e-07, 3.4762e-07],\n [ 5.0084e-08, 3.8264e-07, 7.7638e-07],\n [ 5.2895e-08, 2.1057e-07, -1.2863e-06]],\n\n [[ 2.3124e-07, -6.6059e-07, -5.0681e-09],\n [ 6.7015e-07, -2.8641e-06, -5.5219e-07],\n [ 1.2842e-06, 5.2397e-07, 4.0964e-07]],\n\n ...,\n\n [[-1.7879e-06, -6.1816e-07, 2.3629e-07],\n [-2.6801e-06, 7.3906e-07, -4.7169e-08],\n [ 4.1698e-07, -1.1162e-07, 4.7432e-07]],\n\n [[ 1.0237e-07, 1.9273e-07, -4.0300e-07],\n [ 1.8192e-08, 2.6324e-07, 1.6448e-06],\n [ 7.2327e-08, 3.3271e-07, 2.2049e-07]],\n\n [[-2.2671e-07, 1.4040e-07, 1.2175e-06],\n [ 2.8338e-07, 1.2058e-06, 1.4722e-06],\n [-2.2677e-06, -1.2986e-06, 6.5173e-07]]]]), 'exp_avg_sq': tensor([[[[1.3485e-09, 1.5570e-09, 2.1717e-09],\n [2.7351e-09, 1.5260e-09, 1.5121e-09],\n [3.3546e-09, 2.1978e-09, 2.8533e-09]],\n\n [[8.0766e-10, 1.2761e-09, 1.4180e-09],\n [1.1945e-09, 1.4756e-09, 1.5389e-09],\n [1.0698e-09, 1.6270e-09, 2.1781e-09]],\n\n [[1.8340e-09, 1.1076e-09, 4.1242e-09],\n [1.3932e-09, 1.5924e-09, 3.8028e-09],\n [3.9080e-09, 4.9603e-09, 1.0744e-08]],\n\n ...,\n\n [[5.6977e-10, 1.1832e-09, 1.7770e-09],\n [3.0287e-10, 7.5682e-10, 1.2011e-09],\n [1.0470e-09, 2.0609e-09, 3.6591e-09]],\n\n [[1.6274e-10, 1.5777e-10, 7.5599e-10],\n [1.2804e-10, 1.7538e-10, 1.4903e-09],\n [5.2618e-10, 1.0762e-09, 1.6576e-09]],\n\n [[5.0051e-09, 2.8230e-09, 5.9945e-09],\n [4.1818e-09, 4.5430e-09, 4.9369e-09],\n [1.1199e-08, 7.3843e-09, 1.1710e-08]]],\n\n\n [[[8.9133e-10, 1.5001e-09, 1.0318e-09],\n [1.6955e-09, 1.3792e-09, 2.6796e-09],\n [1.7295e-09, 1.6338e-09, 1.3842e-09]],\n\n [[8.5045e-10, 2.2509e-09, 1.2895e-09],\n [1.1460e-09, 2.2760e-09, 1.7053e-09],\n [1.3877e-09, 1.7559e-09, 1.4297e-09]],\n\n [[7.9732e-10, 3.2285e-09, 2.6696e-09],\n [1.0693e-09, 1.6618e-09, 3.7370e-09],\n [1.5869e-09, 2.2348e-09, 5.9596e-09]],\n\n ...,\n\n [[8.5264e-10, 4.3855e-10, 1.5428e-09],\n [4.0282e-10, 8.4896e-10, 1.6877e-09],\n [8.1443e-10, 1.4670e-09, 4.3016e-09]],\n\n [[5.0299e-10, 4.1816e-10, 4.5164e-10],\n [2.9028e-09, 2.8356e-10, 5.7522e-10],\n [1.3422e-09, 2.8649e-10, 1.3101e-09]],\n\n [[3.5820e-09, 3.2326e-09, 6.7347e-09],\n [5.7691e-09, 6.2485e-09, 1.0364e-08],\n [7.4855e-09, 3.1540e-09, 3.4562e-09]]],\n\n\n [[[4.7006e-09, 7.4373e-09, 6.5962e-09],\n [5.1637e-09, 8.3594e-09, 1.2356e-08],\n [7.2456e-09, 1.0007e-08, 1.1704e-08]],\n\n [[1.7022e-09, 1.9825e-09, 2.0749e-09],\n [5.7859e-09, 5.6481e-09, 5.5746e-09],\n [1.0905e-08, 1.1492e-08, 8.9317e-09]],\n\n [[9.8030e-09, 5.1417e-09, 1.0016e-08],\n [4.1371e-09, 5.6410e-09, 8.5729e-09],\n [1.9786e-08, 2.5940e-08, 2.9994e-08]],\n\n ...,\n\n [[2.6964e-09, 2.9324e-09, 3.2226e-09],\n [2.1514e-09, 3.2431e-09, 4.9913e-09],\n [7.9331e-09, 1.3144e-08, 1.0907e-08]],\n\n [[7.4605e-09, 7.8837e-10, 4.2529e-08],\n [1.8980e-09, 9.7607e-10, 1.5312e-09],\n [3.3062e-09, 3.6599e-09, 5.6503e-09]],\n\n [[8.2089e-09, 7.1324e-09, 8.9129e-09],\n [6.0254e-09, 5.9012e-09, 8.6060e-09],\n [1.3023e-08, 8.9980e-09, 1.1779e-08]]],\n\n\n ...,\n\n\n [[[9.1060e-10, 9.2357e-10, 7.4343e-10],\n [1.7514e-09, 1.8139e-09, 5.4125e-10],\n [7.3644e-10, 7.0817e-10, 7.9204e-10]],\n\n [[1.9027e-10, 5.4303e-10, 6.8771e-10],\n [3.0325e-10, 5.5129e-10, 8.0341e-10],\n [8.5950e-10, 1.1658e-09, 8.3998e-10]],\n\n [[6.9336e-10, 6.8051e-10, 9.5917e-10],\n [1.3163e-09, 7.1436e-10, 1.6102e-09],\n [1.2596e-09, 2.0953e-09, 1.8680e-09]],\n\n ...,\n\n [[4.1308e-10, 5.7654e-10, 5.9282e-10],\n [3.4855e-10, 5.8142e-10, 7.4575e-10],\n [6.5229e-10, 1.0239e-09, 9.8332e-10]],\n\n [[6.7061e-11, 1.3358e-10, 1.7665e-10],\n [1.3774e-10, 1.4828e-10, 1.9050e-10],\n [2.6877e-10, 1.9879e-10, 5.5288e-10]],\n\n [[7.9518e-10, 1.6487e-09, 1.7500e-09],\n [1.1730e-09, 6.6828e-10, 2.4029e-09],\n [1.0870e-09, 6.5379e-10, 1.9181e-09]]],\n\n\n [[[2.1967e-09, 4.0213e-09, 3.0858e-09],\n [1.4762e-09, 4.2039e-09, 1.9504e-09],\n [1.2107e-09, 5.2731e-09, 2.5332e-09]],\n\n [[1.0286e-09, 1.8409e-09, 1.9899e-09],\n [2.9553e-09, 3.0671e-09, 3.7746e-09],\n [2.7931e-09, 4.9104e-09, 6.9305e-09]],\n\n [[1.5684e-09, 1.8655e-09, 5.9706e-09],\n [1.1363e-09, 1.7939e-09, 4.8279e-09],\n [2.4100e-09, 2.8236e-09, 1.1144e-08]],\n\n ...,\n\n [[1.5379e-09, 8.6307e-10, 2.5380e-09],\n [6.7662e-10, 8.7985e-10, 1.7943e-09],\n [3.0271e-09, 5.7741e-09, 1.0907e-08]],\n\n [[3.4272e-10, 1.1043e-09, 4.7811e-10],\n [4.6640e-10, 2.3400e-09, 2.4152e-09],\n [9.6320e-10, 1.2920e-09, 2.1797e-09]],\n\n [[4.8945e-09, 1.6153e-08, 6.9552e-09],\n [5.6330e-09, 9.8300e-09, 8.1848e-09],\n [1.0382e-08, 1.1746e-08, 1.2840e-08]]],\n\n\n [[[1.7041e-10, 2.7548e-10, 1.8798e-10],\n [3.5083e-10, 2.8511e-10, 4.6232e-10],\n [1.1499e-10, 1.9262e-10, 2.5256e-10]],\n\n [[7.3095e-11, 1.3338e-10, 1.1693e-10],\n [1.5254e-10, 1.7724e-10, 2.8291e-10],\n [8.6449e-11, 1.9533e-10, 1.2655e-10]],\n\n [[1.4738e-10, 1.1653e-10, 2.8914e-10],\n [2.8244e-10, 2.5840e-10, 4.8080e-10],\n [2.3110e-10, 1.9715e-10, 4.2873e-10]],\n\n ...,\n\n [[1.2808e-10, 1.4104e-10, 2.1537e-10],\n [1.1480e-10, 2.7101e-10, 4.3260e-10],\n [5.1488e-11, 1.4621e-10, 2.7389e-10]],\n\n [[1.7794e-11, 2.6557e-11, 6.7857e-11],\n [2.0799e-11, 4.8459e-11, 9.6892e-11],\n [2.2886e-11, 2.3410e-11, 6.5148e-11]],\n\n [[3.7511e-11, 2.3813e-10, 2.4797e-10],\n [2.4132e-10, 3.0549e-10, 4.0302e-10],\n [3.5152e-10, 1.1048e-10, 1.9036e-10]]]])}, 133: {'step': 7160, 'exp_avg': tensor([ 7.6897e-07, -3.1235e-06, 9.3213e-05, 5.1064e-05, 1.0667e-05,\n 4.5070e-05, 1.3850e-05, 8.9837e-06, -9.3183e-06, -3.0372e-05,\n -9.2764e-06, 1.5787e-06, -4.2547e-05, -2.4233e-05, 4.3903e-05,\n 3.4442e-05, -1.2402e-05, -1.0881e-05, -3.2590e-05, -3.4669e-05,\n -1.0432e-05, 5.6412e-05, -4.9781e-05, -5.1675e-05, -9.9767e-06,\n 2.1040e-06, -4.5305e-05, 2.9827e-06, -5.3414e-06, -4.7167e-06,\n -8.2237e-06, 2.6727e-06, -1.0689e-05, 3.8422e-05, 2.5937e-05,\n 1.5124e-05, -3.6223e-05, -3.3077e-05, -6.8953e-06, -1.8013e-05,\n -2.1047e-05, -3.9991e-05, 1.9330e-05, -3.3509e-05, -6.4803e-06,\n 2.8861e-05, -2.0144e-05, -8.8282e-06, -6.9720e-05, -7.1267e-06,\n 9.2507e-06, 2.1989e-05, -9.4441e-06, 4.1416e-05, 6.5177e-07,\n -2.0171e-05, -4.2049e-05, 1.5074e-05, 7.5324e-06, -1.1311e-06,\n 4.1812e-05, -2.9883e-05, 1.5360e-04, -7.8386e-06, -4.6976e-07,\n -1.3212e-06, -1.5051e-05, 6.2275e-07, -1.0479e-04, -1.0919e-05,\n -1.6330e-05, 2.7393e-05, -1.4259e-05, 1.0788e-05, -1.4486e-05,\n 3.8904e-06, 1.6611e-05, 4.2008e-05, -5.1961e-05, -4.0136e-05,\n 6.4336e-05, 2.8429e-05, -3.6683e-05, 2.0613e-05, -8.9907e-06,\n -6.6031e-05, 7.1074e-06, -6.4907e-05, -2.0198e-05, 1.2886e-05,\n 9.6389e-06, 5.8041e-06, 1.8307e-05, 2.1106e-05, 2.6974e-04,\n -2.6172e-05, 1.0346e-05, -1.4603e-04, -1.7580e-05, 2.8406e-06,\n -3.4672e-05, -3.0104e-05, -2.2501e-05, -1.1344e-05, 5.8775e-05,\n 1.1103e-05, 3.6610e-05, -5.4329e-05, -7.5847e-06, 2.6591e-05,\n 1.4634e-05, 1.8890e-05, -1.1512e-05, 1.4370e-05, -7.9995e-06,\n -2.2576e-06, -1.2793e-04, -6.5294e-06, -5.9064e-05, -6.3414e-05,\n 6.6491e-05, -4.2747e-05, -6.3838e-05, -3.7275e-05, -2.6846e-06,\n -2.9852e-05, 6.1125e-06, -3.4193e-06, 6.2212e-05, -8.0587e-05,\n 1.7515e-05, -4.7196e-05, -1.2820e-04, 2.6984e-05, -6.2432e-07,\n 1.1221e-05, -1.9350e-05, -8.2414e-06, -9.9202e-06, -1.1895e-06,\n -1.8200e-05, -1.0348e-05, 1.2081e-05, -9.0345e-06, -3.4017e-05,\n -6.8293e-07, -1.0183e-04, -3.8332e-05, -1.3719e-05, 6.3288e-06,\n -1.1622e-05, -2.5956e-05, 1.1702e-04, -1.0188e-06, 2.1097e-05,\n -1.2252e-05, -2.7198e-05, -3.7600e-06, -9.7581e-05, -3.4705e-05,\n 6.5231e-05, 1.2533e-05, -4.8518e-05, 1.2095e-05, 9.6474e-06,\n -3.3382e-05, 4.6673e-05, 2.2064e-06, 2.5018e-05, 2.5855e-05,\n -9.1631e-06, -1.8591e-05, -2.9486e-05, 2.5173e-05, -3.2339e-05,\n -1.3298e-05, -4.5794e-05, 2.8844e-05, 9.7585e-06, -3.4863e-05,\n 2.2060e-05, -3.8510e-06, -7.5795e-06, 5.7837e-05, 1.0730e-05,\n 2.6473e-05, -1.1396e-04, -1.1160e-04, -2.0228e-05, 4.8396e-05,\n -2.4945e-05, 2.4380e-05, 4.0454e-05, -2.0891e-05, 5.6704e-05,\n 1.3294e-05, -5.4867e-05, 7.3868e-06, 6.7351e-05, -2.8134e-05,\n -6.5597e-05, -7.4442e-05, -1.7470e-05, 4.3544e-05, 7.9581e-05,\n 2.7565e-05, 1.0858e-05, -6.8669e-05, -7.1015e-05, -3.4864e-05,\n 2.1397e-05, -8.6627e-06, 3.2371e-05, -3.6348e-05, -4.2209e-05,\n 3.4047e-05, -1.2379e-05, 2.1739e-05, -2.0351e-06, 1.5058e-06,\n 4.1957e-05, 2.0282e-04, 1.1588e-05, 4.7439e-06, -2.8877e-06,\n 1.6503e-05, -3.4855e-05, -3.1735e-05, 1.2459e-05, -1.0685e-04,\n 1.4417e-05, 1.6212e-05, 1.5764e-05, 2.1188e-05, 1.1451e-05,\n -7.3984e-05, 1.4778e-05, -7.0008e-06, -2.7580e-05, -2.3115e-05,\n 1.2410e-05, -2.7398e-05, -2.1079e-07, -2.1024e-05, 5.4641e-05,\n 5.6983e-05, -1.4309e-05, -2.6539e-05, 1.0219e-05, 1.6864e-05,\n 4.3578e-05, 2.4969e-05, -3.3907e-05, 2.0854e-05, 3.5196e-05,\n -3.5424e-05, 3.9469e-05, -6.9213e-06, -8.5438e-06, 4.7072e-06,\n -5.4489e-05, 1.9438e-05, -1.2114e-05, 3.0658e-05, -3.5422e-05,\n 7.2248e-07, -1.7379e-05, -1.4518e-05, -1.7419e-05, 4.6693e-06,\n -8.3213e-06, 1.1043e-05, 7.0125e-07, -4.6677e-05, -1.0088e-05,\n 6.7411e-06, -1.3366e-05, -1.6918e-05, 2.8275e-06, -7.2038e-07,\n 8.5887e-07, 1.9732e-06, 1.5521e-05, -1.8795e-05, 2.0068e-05,\n -2.3544e-06, -3.1041e-05, -6.6477e-06, -3.6176e-05, 7.4673e-07,\n -9.1217e-06, 5.0701e-05, -7.0066e-06, -1.0199e-05, -1.8741e-05,\n -4.0552e-05, 2.9893e-05, -1.4918e-05, 1.2231e-05, 2.0730e-05,\n 2.5305e-05, 5.6954e-06, -3.3055e-05, 4.0245e-05, 2.9177e-05,\n 1.4877e-05, -2.5920e-05, 7.4483e-05, -2.7796e-05, 3.3917e-05,\n 2.0117e-05, -4.4803e-06, -1.8856e-05, 6.3191e-07, 4.5151e-05,\n -1.1057e-05, 2.5469e-05, -2.8906e-05, -5.0352e-05, 2.9471e-05,\n -1.4191e-05, 3.2738e-06, -5.5231e-06, 2.5513e-05, -7.3583e-06,\n -9.0113e-06, 9.7575e-05, -3.9103e-05, 4.0896e-05, -2.6887e-06,\n -8.1494e-05, -3.4269e-05, -4.7551e-05, 7.7521e-06, 9.0633e-05,\n -1.4344e-05, 4.2962e-05, -8.5113e-05, -6.6750e-05, -2.6884e-05,\n -2.1127e-05, -8.4022e-05, 3.1028e-05, -4.1452e-05, -3.1604e-05,\n -4.8230e-05, -2.8244e-05, -6.7140e-06, -1.7050e-04, -5.4116e-05,\n 1.0600e-05, 8.6223e-06, 6.6788e-06, 8.8517e-05, 2.7210e-07,\n -2.6548e-05, 5.3922e-06, 5.9075e-06, -5.1976e-05, 2.3084e-05,\n -1.4851e-04, 6.4604e-06, 1.7820e-06, 1.6652e-05, -2.4685e-05,\n -1.2560e-05, -1.9808e-05, -1.6410e-07, -1.0484e-04, -6.2320e-06,\n -7.0352e-06, -1.1175e-05, 3.3477e-05, -1.7738e-05, 2.0021e-05,\n 2.2689e-05, -6.9618e-06, -1.1767e-05, 2.3991e-05, -3.8693e-05,\n 2.4780e-05, 2.9759e-05, -6.4249e-05, -5.0029e-05, 2.0450e-05,\n 6.4224e-05, -8.4687e-07, 1.3542e-05, 7.7686e-05, 2.2104e-05,\n 3.5490e-05, -2.8663e-05, -1.4304e-05, -2.1187e-05, 3.2605e-05,\n -1.1082e-05, -1.9716e-05, 1.9613e-05, 1.1402e-04, -6.7761e-05,\n -1.2196e-05, 2.6721e-05, -4.1321e-05, 3.2945e-05, 5.6574e-06,\n -1.3758e-05, 3.7727e-05, -3.0518e-05, -2.4924e-05, -4.1300e-06,\n -6.3145e-05, -5.0813e-05, -2.2374e-05, -2.5117e-05, 3.2004e-05,\n 8.8645e-06, -1.2268e-05, -4.9360e-05, 2.4474e-05, 1.3061e-05,\n -4.0758e-05, -9.1317e-05, 3.0144e-05, 1.9216e-05, 7.6723e-06,\n 5.5590e-05, 1.7484e-05, 6.4314e-05, 1.7156e-05, -9.1334e-06,\n -2.7043e-05, 3.9524e-05, 3.0799e-05, -1.0252e-05, -4.0105e-06,\n 6.3407e-06, -7.0896e-05, -2.2538e-05, 1.6972e-05, 4.1362e-05,\n -4.7913e-05, 2.6087e-05, -1.2334e-05, 1.5867e-04, 2.1579e-06,\n -2.2744e-06, -1.3752e-05, 5.7895e-05, -6.2751e-05, -4.6320e-05,\n 1.0217e-05, -2.4298e-05, -2.9217e-05, 4.3866e-05, 6.7469e-06,\n 1.0205e-05, 2.9397e-05, -1.2951e-04, -1.2259e-05, 1.1086e-05,\n -1.6955e-05, 1.1495e-05, -3.5343e-05, -6.9957e-05, 3.2893e-06,\n 8.0618e-06, 2.5862e-05, -1.2240e-05, -8.4885e-06, 5.5374e-05,\n 3.6439e-05, 2.6731e-05, 8.1460e-05, -7.2911e-07, -8.2414e-08,\n -1.4069e-05, -4.3183e-05, -2.1375e-05, 1.8080e-05, -2.4300e-05,\n 3.0532e-06, -1.2072e-05, -9.1732e-05, -5.8517e-06, -3.5594e-05,\n -6.3304e-05, 3.0816e-05, 1.2220e-05, -1.0612e-04, 1.4813e-05,\n -1.1631e-05, -8.5415e-06, 4.0841e-06, 1.1566e-05, 1.0994e-04,\n -1.3253e-04, -2.0218e-05, 4.1290e-06, -1.4775e-05, 9.3666e-06,\n -2.4102e-05, -8.1957e-05, -1.0902e-05, -7.9608e-06, -4.4836e-06,\n -1.1238e-05, 5.1503e-06, 3.9105e-05, 9.0611e-06, -4.1872e-05,\n 3.9980e-05, -1.7546e-05]), 'exp_avg_sq': tensor([1.6595e-07, 2.4186e-07, 8.3273e-07, 3.7137e-07, 1.7045e-07, 6.2079e-07,\n 6.9672e-08, 7.3536e-07, 9.2750e-08, 1.3113e-07, 5.2816e-08, 2.7503e-07,\n 2.2126e-07, 3.1390e-08, 3.4543e-07, 5.5957e-07, 2.2681e-07, 3.0764e-07,\n 7.7938e-08, 2.7610e-07, 1.0571e-07, 1.7968e-07, 3.4448e-07, 2.1866e-06,\n 1.2009e-07, 3.9010e-07, 6.1032e-07, 4.4625e-08, 2.3367e-07, 5.2897e-08,\n 4.4807e-08, 3.0389e-07, 1.4181e-07, 1.4072e-06, 1.9694e-06, 6.1810e-08,\n 3.9434e-07, 4.0533e-07, 2.0958e-08, 3.1753e-07, 5.7078e-07, 3.9245e-07,\n 2.0184e-07, 2.1299e-07, 3.3637e-07, 1.1064e-07, 2.4386e-08, 4.8724e-07,\n 6.8093e-07, 2.3231e-07, 1.3159e-07, 1.5290e-07, 1.3732e-07, 7.8457e-08,\n 3.6404e-07, 1.6541e-07, 7.5620e-07, 1.5679e-07, 1.0275e-07, 6.0424e-08,\n 5.8488e-07, 2.4554e-07, 6.8903e-07, 2.1749e-07, 4.1633e-08, 5.6746e-08,\n 3.0274e-08, 5.4148e-08, 8.3025e-07, 5.8500e-08, 1.2389e-07, 2.9016e-07,\n 1.2779e-07, 1.5821e-07, 6.1132e-07, 9.2686e-08, 1.2039e-07, 1.0156e-06,\n 1.3359e-07, 5.3140e-07, 1.6537e-07, 4.7380e-07, 2.2859e-06, 1.2142e-07,\n 2.0231e-07, 2.5607e-07, 2.1427e-07, 5.5873e-07, 1.0741e-07, 7.9343e-08,\n 1.3800e-06, 4.6101e-07, 3.9881e-08, 1.3925e-06, 1.9626e-06, 2.1940e-07,\n 3.9694e-07, 9.9691e-07, 4.8449e-07, 4.8656e-08, 7.9126e-08, 1.8225e-07,\n 3.0225e-07, 1.1572e-07, 3.8624e-07, 1.6132e-07, 3.9515e-07, 2.0412e-06,\n 2.2475e-07, 3.6440e-08, 1.8166e-07, 1.3061e-07, 1.6283e-07, 3.9118e-07,\n 5.6346e-08, 5.3261e-08, 2.0665e-06, 3.5702e-08, 5.7551e-07, 1.1347e-07,\n 1.5910e-07, 2.8556e-07, 5.1386e-07, 3.5251e-07, 9.5952e-07, 1.8644e-07,\n 6.8479e-08, 1.7764e-08, 3.3970e-07, 4.3685e-07, 2.8357e-07, 4.7268e-07,\n 3.3314e-06, 7.4568e-07, 3.2150e-07, 8.1145e-08, 9.6171e-08, 2.9626e-08,\n 1.8507e-07, 1.8213e-07, 1.6564e-07, 5.6011e-08, 2.0904e-07, 1.1850e-07,\n 3.0720e-07, 1.1178e-07, 6.1712e-07, 3.9022e-07, 1.0651e-07, 3.7140e-07,\n 1.3062e-07, 8.1802e-07, 4.6113e-07, 2.2556e-07, 3.4625e-07, 1.3240e-08,\n 4.1967e-08, 2.5885e-07, 5.3235e-07, 2.4353e-07, 5.2625e-07, 1.6996e-07,\n 2.7252e-07, 8.7415e-08, 1.1446e-07, 9.4806e-07, 3.5299e-07, 4.3687e-07,\n 2.1948e-07, 5.1141e-07, 2.9005e-08, 3.5382e-08, 2.7114e-07, 6.1677e-07,\n 3.3077e-07, 1.9381e-07, 3.9897e-07, 1.0317e-07, 1.2489e-07, 8.9557e-08,\n 6.9518e-08, 1.0854e-07, 9.2707e-08, 2.0647e-07, 3.2886e-07, 8.9488e-08,\n 4.2054e-07, 8.2542e-07, 1.5627e-07, 1.2416e-07, 1.7218e-07, 1.7198e-06,\n 2.1236e-07, 1.8591e-07, 4.8637e-07, 3.3572e-08, 1.5471e-07, 2.3693e-07,\n 9.9209e-07, 1.8866e-07, 2.8647e-06, 3.5568e-07, 1.1266e-07, 7.5384e-08,\n 3.0159e-07, 1.9823e-07, 4.8950e-07, 4.2626e-07, 2.1999e-07, 1.1863e-07,\n 4.4569e-07, 7.7627e-08, 3.7760e-07, 1.6032e-07, 9.1388e-08, 8.7825e-08,\n 5.9096e-08, 9.0917e-08, 5.6370e-08, 1.3531e-07, 1.3570e-07, 8.6778e-07,\n 3.4979e-08, 7.1324e-08, 1.0545e-07, 2.1099e-07, 5.5366e-07, 6.2164e-08,\n 1.8179e-07, 6.2387e-07, 5.1541e-08, 3.4631e-07, 2.6238e-07, 2.7004e-07,\n 1.4653e-07, 1.2231e-06, 4.1896e-08, 1.4492e-07, 4.6219e-08, 1.4307e-07,\n 1.4334e-07, 1.8088e-07, 2.6753e-07, 2.5538e-07, 8.6932e-07, 1.6261e-06,\n 8.8029e-08, 3.3373e-08, 2.3306e-07, 1.8885e-07, 1.2903e-06, 4.2147e-07,\n 2.5920e-07, 1.5436e-07, 2.6560e-07, 1.6525e-07, 4.0033e-07, 6.2512e-08,\n 2.1332e-07, 2.8038e-07, 1.2971e-07, 1.5990e-07, 1.0839e-07, 3.8417e-08,\n 1.2501e-06, 6.8605e-08, 1.1845e-07, 7.6226e-08, 1.6756e-07, 2.9631e-07,\n 1.8552e-07, 6.1488e-07, 1.1886e-07, 1.5075e-07, 2.9956e-07, 5.4058e-07,\n 6.4556e-08, 5.7063e-08, 1.2745e-07, 7.6731e-08, 1.6541e-07, 6.0375e-08,\n 9.0108e-08, 8.6699e-08, 2.8425e-07, 9.1213e-08, 2.2171e-07, 1.2470e-07,\n 2.1386e-07, 2.5798e-07, 1.8482e-07, 2.6949e-07, 5.7027e-08, 1.0760e-06,\n 1.1977e-07, 2.8018e-07, 2.9784e-07, 1.8178e-06, 1.2844e-07, 5.8040e-07,\n 8.4836e-08, 1.4705e-07, 4.1431e-07, 2.8365e-07, 9.0540e-08, 6.9083e-08,\n 9.6495e-08, 4.5909e-07, 3.2748e-07, 2.7195e-07, 9.4984e-08, 1.6818e-07,\n 7.0504e-07, 9.0665e-08, 1.5271e-07, 1.4430e-07, 1.3040e-07, 9.2154e-08,\n 4.0685e-07, 1.2824e-07, 2.3616e-07, 1.7651e-07, 2.2443e-07, 1.6193e-07,\n 2.6248e-08, 2.6681e-07, 6.0251e-07, 3.8305e-07, 6.4236e-07, 8.4201e-08,\n 5.0604e-07, 1.5908e-06, 1.0234e-06, 5.0697e-08, 4.8066e-07, 2.2015e-07,\n 1.2132e-07, 4.0458e-07, 1.0322e-06, 1.6455e-07, 2.9250e-07, 9.8137e-07,\n 1.0546e-07, 4.3429e-07, 3.3918e-08, 1.8652e-07, 1.1254e-07, 2.3658e-07,\n 2.4533e-06, 3.0462e-07, 6.0725e-08, 1.3499e-08, 3.9911e-07, 3.7530e-07,\n 2.7859e-07, 4.4010e-08, 2.1201e-07, 1.0946e-07, 1.9114e-07, 1.2174e-07,\n 6.0385e-07, 3.6181e-08, 8.3112e-08, 1.3292e-07, 1.9987e-06, 3.6782e-08,\n 2.7130e-07, 1.0169e-07, 1.1334e-06, 1.2270e-07, 3.8250e-08, 2.0909e-07,\n 4.3150e-08, 6.7594e-08, 4.0640e-07, 3.1890e-07, 3.6690e-07, 1.7625e-07,\n 4.7018e-07, 2.5068e-07, 2.5954e-07, 1.1486e-07, 1.7534e-07, 4.9433e-07,\n 4.8524e-08, 1.3133e-06, 8.7204e-07, 1.2655e-07, 8.8316e-07, 3.5698e-07,\n 1.5672e-07, 1.6976e-07, 1.0814e-06, 3.0170e-08, 1.7246e-07, 2.2549e-08,\n 7.9313e-08, 1.1525e-07, 6.0408e-07, 2.8750e-07, 2.8880e-07, 8.6476e-08,\n 1.6881e-07, 9.0131e-08, 1.3458e-07, 8.0818e-07, 4.7145e-08, 2.1281e-07,\n 3.6750e-07, 5.4193e-07, 7.5351e-08, 2.3094e-06, 9.2319e-08, 6.1894e-07,\n 1.1914e-07, 1.3036e-06, 3.6611e-07, 4.1125e-07, 1.6417e-07, 8.1433e-08,\n 1.2867e-07, 2.9793e-07, 5.5817e-08, 4.4867e-07, 1.0557e-06, 2.9824e-07,\n 1.3171e-07, 2.8467e-07, 9.5689e-08, 1.5993e-07, 6.8451e-08, 2.4944e-07,\n 1.8066e-07, 3.5547e-07, 5.5035e-08, 3.7268e-08, 1.2823e-06, 6.2676e-07,\n 5.0711e-08, 2.1387e-07, 4.8681e-07, 1.0772e-07, 1.1171e-06, 1.0647e-06,\n 9.6005e-08, 7.5793e-08, 8.7725e-08, 3.0335e-07, 1.4420e-07, 2.0036e-07,\n 1.0515e-07, 5.1406e-08, 3.1268e-07, 1.4760e-07, 2.9901e-08, 1.0576e-07,\n 3.6911e-07, 3.0664e-07, 1.1021e-07, 8.5533e-08, 3.1805e-07, 9.5152e-08,\n 1.1648e-06, 3.9843e-07, 2.1310e-07, 8.6584e-08, 2.9198e-07, 7.8293e-08,\n 4.8744e-07, 8.4466e-07, 9.6774e-08, 9.4964e-08, 8.4372e-07, 5.1112e-08,\n 3.7773e-07, 1.6013e-07, 5.2238e-07, 1.9732e-07, 5.6321e-08, 2.4402e-07,\n 1.0907e-07, 2.9809e-08, 8.6738e-07, 5.2009e-08, 7.9621e-08, 3.6569e-07,\n 7.4912e-08, 2.1139e-08, 4.5682e-07, 3.2271e-08, 2.7363e-07, 7.7735e-08,\n 6.0649e-07, 1.4155e-06, 1.0802e-06, 3.9521e-07, 2.8526e-07, 4.2956e-08,\n 1.3971e-07, 3.3065e-07, 9.0112e-08, 4.4755e-07, 9.2609e-08, 8.1536e-08,\n 1.0246e-07, 3.3280e-08, 1.3653e-07, 4.4590e-07, 4.9590e-07, 7.4624e-08,\n 3.1412e-07, 4.2242e-08])}, 134: {'step': 7160, 'exp_avg': tensor([-3.2723e-05, -9.0482e-06, 1.0212e-04, 3.8450e-05, 2.1159e-05,\n 3.6501e-05, -2.1144e-06, 1.3412e-05, -1.5954e-05, -2.7890e-05,\n -1.4340e-06, -1.2689e-05, -2.3594e-05, -2.5703e-05, 5.0230e-06,\n 2.0585e-05, 2.7890e-05, -7.6652e-06, -2.4029e-05, -5.6828e-05,\n -2.4883e-05, 4.7074e-05, -6.6982e-05, -3.2348e-05, -2.1514e-05,\n -3.2700e-05, 3.4647e-06, 8.2000e-07, 1.3864e-05, 7.6761e-06,\n -2.3892e-06, 4.5025e-05, -1.8739e-05, -1.9278e-05, -1.9585e-05,\n 1.3275e-05, -1.1460e-05, -2.8887e-05, -7.7827e-06, -4.8966e-05,\n -2.0834e-05, 1.2949e-05, -1.3386e-05, -2.2196e-05, -2.5093e-05,\n 3.5849e-05, -1.5041e-05, -7.0769e-06, -4.4308e-05, -5.5166e-06,\n -3.7814e-07, 6.0810e-07, -5.2777e-05, 3.1320e-05, -3.3550e-06,\n -3.6647e-05, -1.8762e-05, 8.5513e-06, -9.9943e-06, -9.7481e-06,\n 4.7536e-07, -2.1380e-05, 1.0828e-04, -1.5034e-06, -7.4708e-07,\n -2.2692e-06, -6.0628e-06, -5.4258e-07, -7.1190e-05, -6.7984e-06,\n -2.8518e-05, 3.9547e-05, -1.0469e-05, 6.8322e-06, -6.9060e-05,\n -7.3440e-05, -1.9831e-05, -1.6941e-05, -5.8649e-05, -4.4667e-05,\n 2.9504e-05, 1.9559e-05, 3.4565e-05, 7.4787e-06, -9.3486e-06,\n -1.9299e-05, 1.3717e-05, -5.9874e-05, 6.8791e-06, -9.0012e-07,\n 2.8362e-05, 4.6896e-06, 1.3113e-05, 2.7206e-06, 7.7570e-05,\n -4.1720e-05, -3.8686e-05, -1.4686e-04, -5.5006e-05, -3.0859e-06,\n -2.5801e-05, -4.3755e-05, 4.6299e-05, 1.7882e-06, 2.0185e-05,\n 3.3189e-05, 4.3358e-05, -1.1214e-04, -2.2027e-05, 1.2442e-05,\n 1.1481e-06, 5.8788e-06, -8.8027e-06, -6.5717e-07, -1.9469e-05,\n -8.9397e-06, -1.0235e-04, -1.1687e-06, -5.5962e-05, -3.4726e-05,\n 6.5040e-05, -3.3870e-05, -2.1471e-05, -4.6430e-05, -9.8192e-06,\n -1.4111e-05, -1.9168e-07, -9.2020e-06, 5.3921e-05, -7.4096e-05,\n 9.4947e-06, -4.7590e-05, -5.5508e-05, 2.6323e-05, -5.9450e-05,\n 3.9425e-07, -2.5283e-05, -2.9617e-06, -1.2292e-05, -5.1090e-06,\n -1.1755e-05, -2.3780e-05, -1.8393e-05, -1.4864e-05, 6.1666e-05,\n -1.1192e-05, -3.0649e-05, -2.2773e-05, -6.3563e-05, 2.0584e-05,\n -1.1925e-06, -7.2386e-05, 2.1832e-05, -2.0646e-05, 1.7880e-05,\n -8.9208e-06, -2.9932e-05, -4.4188e-05, 9.0794e-06, -2.9554e-05,\n 3.9519e-05, 2.4088e-05, -3.3468e-05, -7.7143e-06, 1.7418e-06,\n -3.5680e-05, 2.0240e-05, 1.1231e-05, 1.0507e-05, 1.6640e-06,\n -5.9967e-06, -1.2334e-05, -4.0036e-05, 9.2968e-06, -2.0060e-05,\n -1.5592e-05, -9.6892e-05, 5.2141e-06, 1.9830e-05, -3.3393e-05,\n 2.0071e-05, -4.3041e-06, -1.5206e-05, 6.8531e-05, 3.1662e-05,\n 1.2514e-05, -1.2653e-04, -8.3890e-05, 1.5103e-05, 6.3017e-06,\n -5.2377e-05, 2.0435e-05, -1.3953e-05, 1.6013e-05, -8.2590e-06,\n 2.1795e-05, -2.1204e-05, -1.5974e-05, 5.9550e-06, -3.7802e-05,\n -1.2338e-04, -1.4359e-05, -9.3367e-06, 3.4173e-05, 7.9319e-05,\n 8.6563e-06, -2.6066e-06, -5.0209e-05, -8.3172e-05, -4.9416e-05,\n 3.2186e-05, -6.9039e-06, 1.7666e-05, -3.2692e-05, -4.2840e-05,\n 9.0442e-06, -9.5758e-06, -1.1919e-05, -8.9924e-06, -4.6596e-05,\n 3.4882e-05, 8.0993e-05, -4.0555e-06, -5.0332e-06, -1.0584e-05,\n 3.2171e-05, -1.8769e-05, -3.8400e-05, -8.7132e-06, 1.0368e-05,\n 1.5331e-05, 3.1522e-05, 4.5483e-05, 2.1902e-05, -2.5385e-06,\n -9.5470e-05, 3.1586e-05, -4.0185e-06, -4.4574e-05, -1.9574e-05,\n -3.8297e-06, -2.9779e-05, 1.2552e-05, -1.8334e-05, 1.4200e-05,\n -2.1623e-05, 3.1482e-06, -9.9603e-06, -1.1096e-05, 1.0113e-05,\n 7.5636e-05, 6.3157e-06, 3.9551e-05, 5.8639e-06, 3.6490e-05,\n -3.2189e-05, 3.9301e-05, -1.2706e-05, -3.3599e-05, 1.8776e-05,\n -5.8198e-05, -8.2876e-06, -1.1029e-05, 3.1810e-05, -2.2263e-05,\n -3.4779e-06, 3.0297e-06, -1.1995e-05, -4.0211e-05, 1.5047e-05,\n -2.8719e-05, 2.8400e-05, 1.3509e-05, -3.1947e-05, -2.4045e-06,\n 1.3221e-05, -2.8004e-05, -1.7429e-05, -1.4028e-06, 1.5545e-05,\n 3.5032e-06, 2.0732e-06, 2.3462e-05, -1.4888e-05, 1.2395e-05,\n -2.6279e-06, -8.6072e-06, -4.2274e-06, -5.0502e-05, 1.5008e-05,\n -1.7202e-05, -1.4816e-06, -2.5200e-05, 1.6101e-05, 4.4996e-06,\n -2.2335e-05, 1.7118e-05, -4.4305e-05, 5.0535e-06, -3.6464e-05,\n 1.8723e-05, -6.2832e-06, -3.5753e-05, -1.5130e-05, 2.0890e-05,\n 1.4060e-05, -3.4442e-05, -2.2912e-05, -1.8729e-05, 8.5281e-06,\n -1.0390e-05, 5.1962e-07, -4.6210e-05, -6.2198e-06, -8.8571e-07,\n 3.3446e-06, 3.3731e-05, -5.7160e-05, -3.2527e-05, 3.0288e-05,\n -2.0360e-05, 1.0710e-05, -6.3031e-05, 1.2312e-05, -1.0283e-05,\n -1.9483e-05, 9.0547e-05, -9.6809e-05, 9.8884e-06, 6.3529e-06,\n -6.2203e-05, -1.7497e-05, -7.9489e-05, 1.1628e-05, 4.0145e-05,\n -5.4503e-05, 4.1284e-05, -9.2826e-05, -5.0266e-05, -4.5174e-06,\n -1.2689e-05, -6.0846e-05, 3.3146e-05, -6.0879e-06, -3.1928e-05,\n -8.9078e-05, -3.5734e-05, -1.8869e-05, -1.0028e-04, -7.1818e-05,\n 1.0102e-05, 1.2699e-05, -1.7265e-05, 8.2165e-05, -3.1161e-05,\n -1.7914e-05, 8.8606e-06, 1.2736e-05, -7.2560e-05, 2.7914e-05,\n -2.1413e-05, 1.3375e-06, 3.6819e-06, 2.1699e-05, -3.7865e-05,\n -6.7859e-06, -2.1968e-05, 1.7251e-05, -4.0037e-05, 1.0915e-05,\n -4.0017e-06, -1.8270e-05, 3.1269e-05, -1.8655e-06, -7.1809e-07,\n -8.7914e-06, -2.0931e-06, 1.7292e-06, 7.0953e-06, -6.6909e-05,\n 1.9661e-05, 1.1679e-05, -4.6238e-05, -1.2514e-04, 2.3001e-05,\n 4.9902e-05, 1.1072e-05, 1.4193e-05, 4.7801e-05, 5.5491e-05,\n 2.2598e-05, -1.0960e-05, 2.9442e-05, -2.1988e-05, 4.1471e-05,\n -7.9725e-06, -2.6260e-05, 1.0484e-05, 4.5889e-05, -5.9495e-05,\n 3.5313e-06, 2.4095e-05, -4.1918e-05, 1.9402e-05, 3.1707e-05,\n -6.2321e-06, 3.6718e-05, -3.1493e-05, -5.8971e-05, -1.1885e-05,\n -5.6655e-05, -2.7733e-05, -4.1067e-05, -2.6587e-05, 2.0599e-05,\n -3.5555e-06, -3.1841e-05, -5.3295e-05, 1.1527e-06, -1.1753e-05,\n -5.3037e-05, -8.0975e-05, 2.3802e-05, 9.2154e-06, -1.3858e-05,\n -1.9011e-05, 1.2350e-05, 4.4003e-05, 1.3124e-05, -2.5681e-05,\n -1.5613e-05, 1.3028e-05, 2.0207e-05, -1.8212e-05, -1.6537e-05,\n 2.7635e-05, -7.5481e-05, -1.8260e-05, 2.8208e-06, 2.1649e-05,\n -7.1359e-05, 1.1183e-05, -4.2884e-05, 8.3215e-05, 5.4305e-08,\n -7.1401e-06, -1.9691e-05, -4.8296e-06, -5.4630e-05, -4.2735e-05,\n 2.0079e-06, -2.7379e-05, -2.2433e-05, 1.3196e-05, -5.9966e-06,\n 2.1060e-05, -1.8509e-05, -2.5702e-05, -3.2228e-06, -1.5973e-06,\n -9.9878e-06, 1.6723e-06, 1.8293e-06, -6.7246e-05, 6.8297e-06,\n 5.0974e-06, 2.5629e-06, -1.6373e-05, 4.8361e-06, -3.3317e-05,\n 2.2441e-05, 1.0201e-05, 5.6645e-05, 8.0965e-07, -1.2115e-05,\n -4.5524e-06, -3.7627e-05, -5.4403e-06, 1.3878e-05, -1.8492e-07,\n 5.5107e-06, -1.2735e-05, -7.2066e-05, -1.0204e-05, -3.4598e-05,\n -7.4061e-05, 1.6679e-05, 7.1311e-06, -7.5912e-05, 5.1357e-06,\n -1.6330e-05, -1.7684e-05, 5.9958e-06, -1.0753e-04, 2.7023e-05,\n -9.9354e-05, -4.1844e-05, 5.6991e-06, -2.7237e-05, -1.4418e-05,\n -2.2575e-05, -1.1481e-04, 5.7368e-06, -2.7339e-05, -1.2474e-06,\n -2.8561e-05, -1.4912e-05, 3.9401e-05, -1.5517e-05, -3.8078e-05,\n -2.8461e-05, -1.6854e-05]), 'exp_avg_sq': tensor([1.1109e-07, 1.8732e-07, 7.3068e-07, 3.2124e-07, 2.1334e-07, 5.1407e-07,\n 4.5224e-08, 3.3307e-07, 2.6638e-08, 6.7355e-08, 3.6975e-08, 1.5454e-07,\n 1.9297e-07, 3.7199e-08, 4.0977e-07, 2.8409e-07, 9.7236e-08, 1.9345e-07,\n 8.8316e-08, 2.5570e-07, 1.8266e-07, 1.8724e-07, 1.6066e-07, 8.2570e-07,\n 1.0576e-07, 1.9845e-07, 2.0131e-07, 4.5381e-08, 3.1964e-07, 8.2530e-08,\n 3.0874e-08, 5.8697e-07, 9.2305e-08, 3.3127e-07, 1.4074e-06, 3.9878e-08,\n 2.1790e-07, 2.5925e-07, 1.8452e-08, 3.1404e-07, 3.3872e-07, 1.9317e-07,\n 9.7496e-08, 1.2237e-07, 2.3864e-07, 1.3336e-07, 1.6509e-08, 1.9688e-07,\n 2.2465e-07, 2.2263e-07, 6.6899e-08, 7.5382e-08, 1.4255e-07, 6.5959e-08,\n 1.6300e-07, 1.8089e-07, 7.2201e-07, 1.0463e-07, 4.4169e-08, 5.7562e-08,\n 1.8068e-07, 1.5468e-07, 2.6395e-07, 1.2844e-07, 4.3903e-08, 5.6719e-08,\n 2.1487e-08, 3.7604e-08, 5.1705e-07, 3.7681e-08, 1.0099e-07, 1.5607e-07,\n 6.0899e-08, 3.4039e-08, 4.5603e-07, 1.9183e-07, 1.8166e-07, 4.3953e-07,\n 1.6768e-07, 3.3969e-07, 1.4715e-07, 9.4303e-07, 1.3446e-06, 9.2670e-08,\n 7.9481e-08, 1.8001e-07, 1.1767e-07, 1.9766e-07, 1.1035e-07, 7.7156e-08,\n 7.9712e-07, 2.0395e-07, 3.8867e-08, 5.0614e-07, 3.4052e-06, 1.6504e-07,\n 4.1545e-07, 7.3509e-07, 5.1854e-07, 2.5665e-08, 4.3949e-08, 1.8131e-07,\n 3.0124e-07, 6.3244e-08, 9.6523e-08, 1.1427e-07, 2.7905e-07, 1.7975e-06,\n 1.4557e-07, 6.3920e-08, 1.0575e-07, 6.7330e-08, 3.8050e-08, 2.3669e-07,\n 3.0521e-08, 8.1577e-08, 1.1069e-06, 2.2460e-08, 3.7154e-07, 6.5002e-08,\n 1.9683e-07, 1.8766e-07, 2.8311e-07, 3.0787e-07, 7.2651e-07, 8.3433e-08,\n 5.5700e-08, 8.3252e-09, 3.4861e-07, 5.7524e-07, 2.2267e-07, 4.7330e-07,\n 1.2499e-06, 4.3423e-07, 2.8147e-07, 1.1216e-07, 8.6841e-08, 2.1396e-08,\n 1.5190e-07, 1.3005e-07, 2.5165e-07, 4.8875e-08, 1.7954e-07, 2.8962e-08,\n 3.1440e-07, 1.4288e-07, 3.9127e-07, 6.4556e-07, 8.4743e-08, 4.3086e-07,\n 1.2403e-07, 9.2311e-07, 1.6154e-07, 2.2798e-07, 2.7134e-07, 3.4222e-09,\n 1.9334e-08, 1.7227e-07, 4.3963e-07, 1.9520e-07, 2.9859e-07, 2.4471e-07,\n 2.6925e-07, 3.8054e-08, 6.5241e-08, 3.4147e-07, 1.6933e-07, 4.6707e-07,\n 1.4048e-07, 1.1638e-07, 2.1133e-08, 4.0872e-08, 1.5358e-07, 1.9214e-07,\n 2.5668e-07, 1.2525e-07, 4.4299e-07, 1.6679e-07, 1.4165e-07, 5.5434e-08,\n 5.6328e-08, 1.1332e-07, 5.3375e-08, 1.6243e-07, 3.3307e-07, 3.8508e-08,\n 5.5206e-07, 5.6972e-07, 1.4474e-07, 9.2084e-08, 1.6761e-07, 1.3087e-06,\n 4.1431e-07, 2.9858e-07, 7.8286e-07, 3.1814e-08, 1.7806e-07, 1.3558e-07,\n 1.0184e-06, 1.4086e-07, 1.4373e-06, 1.6774e-07, 9.6879e-08, 5.8476e-08,\n 2.1358e-07, 1.4954e-07, 1.6885e-07, 2.4705e-07, 3.3220e-07, 9.8851e-08,\n 5.3991e-07, 5.8224e-08, 5.1160e-07, 1.3174e-07, 9.2280e-08, 2.1065e-08,\n 1.8332e-08, 3.4766e-08, 5.9018e-08, 1.4394e-07, 1.0660e-07, 4.1509e-07,\n 5.6376e-08, 9.8419e-08, 7.4975e-08, 2.6907e-07, 4.9596e-07, 4.4828e-08,\n 1.8651e-07, 6.2662e-07, 3.4095e-08, 2.5070e-07, 4.5108e-07, 1.5934e-07,\n 1.2621e-07, 7.7005e-07, 4.2156e-08, 1.4007e-07, 5.4433e-08, 7.7843e-08,\n 8.2975e-08, 9.2266e-08, 1.8551e-07, 2.1413e-07, 7.1358e-07, 6.9474e-07,\n 6.2216e-08, 4.7231e-08, 9.9856e-08, 9.2900e-08, 5.5097e-07, 6.0247e-07,\n 4.1807e-07, 6.1011e-08, 2.0831e-07, 1.2947e-07, 2.5215e-07, 7.0225e-08,\n 1.1841e-07, 1.9178e-07, 1.4599e-07, 9.6057e-08, 5.8620e-08, 3.7399e-08,\n 4.6263e-07, 6.8643e-08, 1.0618e-07, 7.0862e-08, 1.1283e-07, 1.6557e-07,\n 2.0696e-07, 3.4016e-07, 1.2807e-07, 8.4430e-08, 2.0632e-07, 2.7490e-07,\n 1.2155e-07, 3.9002e-08, 6.3528e-08, 6.6046e-08, 8.0658e-08, 6.3884e-08,\n 8.5335e-08, 1.1354e-07, 2.8208e-07, 5.2458e-08, 1.6328e-07, 3.4654e-08,\n 3.0436e-07, 2.0735e-07, 1.9017e-07, 2.2031e-07, 4.3529e-08, 4.4913e-07,\n 4.8244e-08, 3.0024e-07, 1.7899e-07, 9.9796e-07, 2.0985e-07, 3.9383e-07,\n 7.0967e-08, 6.1923e-08, 2.1743e-07, 3.3310e-07, 5.1087e-08, 5.6323e-08,\n 5.1951e-08, 3.3502e-07, 2.2106e-07, 3.4351e-07, 5.0188e-08, 1.3826e-07,\n 3.8903e-07, 1.2571e-07, 8.2224e-08, 1.2312e-07, 1.1774e-07, 8.6639e-08,\n 2.5281e-07, 9.2121e-08, 1.3372e-07, 1.8365e-07, 4.3720e-07, 1.0528e-07,\n 1.3997e-08, 2.0660e-07, 4.5627e-07, 5.7047e-07, 3.7098e-07, 4.9443e-08,\n 3.0268e-07, 1.2372e-06, 9.3374e-07, 4.3350e-08, 1.7603e-07, 1.6241e-07,\n 1.0866e-07, 4.0659e-07, 4.4915e-07, 9.6680e-08, 1.4074e-07, 6.5008e-07,\n 1.0676e-07, 3.5262e-07, 3.1460e-08, 1.3276e-07, 1.0941e-07, 1.5178e-07,\n 5.6841e-07, 2.0132e-07, 3.1471e-08, 6.7373e-09, 1.3418e-07, 4.1766e-07,\n 1.6890e-07, 3.8998e-08, 4.5792e-08, 1.0397e-07, 1.8731e-07, 1.2847e-07,\n 4.5109e-07, 9.9688e-09, 9.5605e-08, 1.6299e-07, 5.0083e-07, 8.2640e-09,\n 2.5976e-07, 1.0453e-07, 9.1206e-07, 4.6248e-08, 2.7931e-08, 9.8479e-08,\n 3.2820e-08, 5.0934e-08, 3.4199e-07, 2.9635e-07, 3.1928e-07, 4.1645e-08,\n 2.3026e-07, 2.2369e-07, 3.8542e-07, 5.2582e-08, 1.1030e-07, 4.9159e-07,\n 5.7632e-08, 9.7280e-07, 4.1868e-07, 7.2274e-08, 4.9349e-07, 3.4478e-07,\n 9.9842e-08, 1.4245e-07, 4.3465e-07, 1.3550e-08, 2.1587e-07, 2.6994e-08,\n 1.0363e-07, 1.0752e-07, 2.1022e-07, 1.7976e-07, 1.6850e-07, 6.7365e-08,\n 2.0938e-07, 1.4434e-07, 1.2089e-07, 3.6554e-07, 5.5174e-08, 5.6206e-07,\n 2.3999e-07, 2.9776e-07, 6.2300e-08, 1.0648e-06, 6.8600e-08, 1.0110e-06,\n 1.1400e-07, 4.2681e-07, 3.8600e-07, 3.5930e-07, 2.5881e-07, 3.2887e-08,\n 2.0215e-07, 1.7885e-07, 3.5812e-08, 2.8087e-07, 3.7508e-07, 1.4425e-07,\n 1.9956e-07, 2.7487e-07, 7.5115e-08, 8.9271e-08, 4.5618e-08, 1.8773e-07,\n 8.8172e-08, 3.1589e-07, 5.9713e-08, 7.5405e-08, 8.4411e-07, 3.0743e-07,\n 4.0241e-08, 8.9277e-08, 1.1015e-06, 4.3295e-08, 8.6540e-07, 6.0237e-07,\n 5.1318e-08, 4.3498e-08, 9.5812e-08, 2.1646e-07, 1.2987e-07, 3.4754e-07,\n 6.4528e-08, 7.2135e-08, 1.7922e-07, 6.9214e-08, 2.3466e-08, 1.3938e-07,\n 1.3038e-07, 4.4800e-07, 8.5917e-08, 8.1760e-08, 1.4992e-07, 5.7555e-08,\n 4.4117e-07, 2.8368e-07, 2.2222e-07, 5.0084e-08, 3.4204e-07, 9.9557e-08,\n 5.0961e-07, 8.0485e-07, 2.9919e-08, 4.9230e-08, 4.4911e-07, 2.3232e-08,\n 4.0817e-07, 2.7154e-07, 2.4086e-07, 1.4878e-07, 4.7718e-08, 1.2497e-07,\n 1.3687e-07, 1.3344e-08, 6.9145e-07, 4.8130e-08, 8.6754e-08, 2.5439e-07,\n 5.2352e-08, 2.0454e-08, 2.7382e-07, 2.8560e-08, 1.0505e-07, 1.1619e-07,\n 6.8517e-07, 8.1028e-07, 2.7576e-07, 4.3789e-07, 2.8669e-07, 2.4311e-08,\n 1.7106e-07, 2.3491e-07, 1.1023e-07, 6.9013e-07, 9.0807e-08, 1.0959e-07,\n 8.0192e-08, 3.6597e-08, 5.7355e-08, 4.3306e-07, 1.2530e-07, 9.8730e-08,\n 1.4334e-07, 1.6682e-08])}, 135: {'step': 7160, 'exp_avg': tensor([[[[ 1.2715e-06]],\n\n [[ 2.5590e-07]],\n\n [[-1.0240e-07]],\n\n ...,\n\n [[ 1.8555e-06]],\n\n [[ 2.0035e-06]],\n\n [[-4.4032e-07]]],\n\n\n [[[ 3.5410e-07]],\n\n [[-1.7326e-07]],\n\n [[-3.1929e-07]],\n\n ...,\n\n [[ 7.7125e-07]],\n\n [[ 1.2901e-06]],\n\n [[ 6.5742e-07]]],\n\n\n [[[-4.3719e-07]],\n\n [[ 1.5020e-06]],\n\n [[-2.9663e-06]],\n\n ...,\n\n [[ 2.7367e-06]],\n\n [[ 4.6426e-06]],\n\n [[-8.0224e-07]]],\n\n\n ...,\n\n\n [[[-5.3254e-06]],\n\n [[-2.4427e-06]],\n\n [[-2.3885e-06]],\n\n ...,\n\n [[ 5.2734e-06]],\n\n [[-2.1346e-06]],\n\n [[ 3.3810e-06]]],\n\n\n [[[ 1.2163e-06]],\n\n [[-7.7506e-07]],\n\n [[-1.8715e-07]],\n\n ...,\n\n [[-5.5337e-07]],\n\n [[-1.0556e-06]],\n\n [[-3.7256e-08]]],\n\n\n [[[ 4.2528e-07]],\n\n [[ 1.0988e-06]],\n\n [[-3.4823e-06]],\n\n ...,\n\n [[-8.9923e-07]],\n\n [[ 5.8322e-07]],\n\n [[ 1.2256e-06]]]]), 'exp_avg_sq': tensor([[[[8.6920e-10]],\n\n [[9.9695e-10]],\n\n [[8.5287e-10]],\n\n ...,\n\n [[2.1963e-10]],\n\n [[9.2361e-10]],\n\n [[1.1675e-10]]],\n\n\n [[[5.9340e-10]],\n\n [[7.2086e-10]],\n\n [[7.2126e-10]],\n\n ...,\n\n [[1.9677e-10]],\n\n [[9.9388e-10]],\n\n [[1.1457e-10]]],\n\n\n [[[1.4072e-09]],\n\n [[4.2441e-10]],\n\n [[6.5082e-10]],\n\n ...,\n\n [[2.8437e-10]],\n\n [[1.2140e-09]],\n\n [[3.3720e-10]]],\n\n\n ...,\n\n\n [[[2.5927e-09]],\n\n [[1.8013e-09]],\n\n [[4.3924e-09]],\n\n ...,\n\n [[1.7914e-09]],\n\n [[1.8270e-09]],\n\n [[6.8742e-10]]],\n\n\n [[[2.4102e-10]],\n\n [[4.0792e-10]],\n\n [[5.0901e-10]],\n\n ...,\n\n [[1.0255e-09]],\n\n [[4.4386e-10]],\n\n [[1.5687e-10]]],\n\n\n [[[1.5138e-10]],\n\n [[2.2296e-10]],\n\n [[4.1493e-10]],\n\n ...,\n\n [[1.8389e-10]],\n\n [[2.2091e-10]],\n\n [[5.1551e-11]]]])}, 136: {'step': 7160, 'exp_avg': tensor([ 5.9004e-06, -1.9939e-06, 8.2711e-07, ..., -1.2231e-05,\n 5.0323e-07, -1.9663e-08]), 'exp_avg_sq': tensor([1.8960e-09, 2.0576e-09, 1.4002e-09, ..., 1.8684e-08, 1.5528e-09,\n 9.0396e-10])}, 137: {'step': 7160, 'exp_avg': tensor([ 1.7445e-06, -3.0621e-06, -2.9219e-06, ..., 9.2219e-08,\n -1.1666e-06, -3.7559e-07]), 'exp_avg_sq': tensor([6.5624e-10, 2.8271e-09, 2.1118e-09, ..., 6.8816e-09, 1.1707e-09,\n 9.6055e-10])}, 138: {'step': 7160, 'exp_avg': tensor([[[[ 1.3029e-06]],\n\n [[ 1.4959e-07]],\n\n [[-2.1794e-07]],\n\n ...,\n\n [[ 4.8075e-07]],\n\n [[ 1.1746e-07]],\n\n [[-6.7604e-07]]],\n\n\n [[[ 1.3155e-06]],\n\n [[-2.4544e-08]],\n\n [[ 4.6504e-07]],\n\n ...,\n\n [[-1.1041e-08]],\n\n [[-2.8985e-07]],\n\n [[-2.6307e-06]]],\n\n\n [[[ 1.6460e-06]],\n\n [[ 4.0533e-07]],\n\n [[ 2.2324e-07]],\n\n ...,\n\n [[ 1.9971e-06]],\n\n [[ 8.0831e-07]],\n\n [[ 1.8664e-06]]],\n\n\n ...,\n\n\n [[[ 1.6145e-06]],\n\n [[ 6.3754e-07]],\n\n [[-2.8191e-07]],\n\n ...,\n\n [[-1.1772e-07]],\n\n [[-7.9570e-07]],\n\n [[-4.0230e-06]]],\n\n\n [[[ 2.8226e-06]],\n\n [[-2.3062e-07]],\n\n [[ 2.4916e-07]],\n\n ...,\n\n [[-1.6972e-06]],\n\n [[ 2.6787e-07]],\n\n [[-7.3847e-07]]],\n\n\n [[[-2.2774e-06]],\n\n [[-4.3318e-07]],\n\n [[-6.6226e-07]],\n\n ...,\n\n [[ 1.2045e-06]],\n\n [[-4.6954e-07]],\n\n [[-4.1778e-07]]]]), 'exp_avg_sq': tensor([[[[5.8605e-10]],\n\n [[5.1982e-11]],\n\n [[1.9489e-11]],\n\n ...,\n\n [[1.7351e-10]],\n\n [[9.3779e-11]],\n\n [[5.2587e-10]]],\n\n\n [[[1.5312e-09]],\n\n [[3.2635e-11]],\n\n [[2.6993e-11]],\n\n ...,\n\n [[7.3880e-10]],\n\n [[1.0187e-10]],\n\n [[9.4698e-10]]],\n\n\n [[[8.1289e-10]],\n\n [[1.8584e-10]],\n\n [[4.4093e-11]],\n\n ...,\n\n [[1.5704e-10]],\n\n [[1.3229e-10]],\n\n [[6.7124e-10]]],\n\n\n ...,\n\n\n [[[1.9891e-09]],\n\n [[1.2617e-10]],\n\n [[5.9623e-11]],\n\n ...,\n\n [[3.1735e-10]],\n\n [[2.5379e-10]],\n\n [[3.3723e-09]]],\n\n\n [[[1.1825e-09]],\n\n [[2.2631e-11]],\n\n [[4.0002e-11]],\n\n ...,\n\n [[1.7474e-10]],\n\n [[2.5733e-10]],\n\n [[1.6429e-09]]],\n\n\n [[[1.4347e-09]],\n\n [[2.9255e-11]],\n\n [[7.6479e-11]],\n\n ...,\n\n [[2.0605e-10]],\n\n [[2.1681e-10]],\n\n [[2.8586e-09]]]])}, 139: {'step': 7160, 'exp_avg': tensor([ 1.8052e-06, 1.8224e-07, -6.1481e-06, ..., 1.6665e-06,\n 6.3920e-07, 3.0814e-06]), 'exp_avg_sq': tensor([1.4992e-09, 2.9672e-09, 3.7278e-09, ..., 1.4438e-08, 1.4904e-09,\n 2.6664e-09])}, 140: {'step': 7160, 'exp_avg': tensor([ 1.7445e-06, -3.0621e-06, -2.9219e-06, ..., 9.2219e-08,\n -1.1666e-06, -3.7559e-07]), 'exp_avg_sq': tensor([6.5624e-10, 2.8271e-09, 2.1118e-09, ..., 6.8816e-09, 1.1707e-09,\n 9.6055e-10])}, 141: {'step': 7160, 'exp_avg': tensor([[[[-1.5579e-06]],\n\n [[ 5.5070e-07]],\n\n [[ 1.8307e-06]],\n\n ...,\n\n [[ 3.3062e-07]],\n\n [[ 1.9278e-07]],\n\n [[-1.9249e-07]]],\n\n\n [[[ 4.6324e-06]],\n\n [[-1.1846e-05]],\n\n [[-2.4454e-06]],\n\n ...,\n\n [[-2.2882e-06]],\n\n [[-6.6027e-06]],\n\n [[-7.8460e-06]]],\n\n\n [[[ 1.3990e-07]],\n\n [[ 3.4794e-06]],\n\n [[ 1.6518e-06]],\n\n ...,\n\n [[-4.5382e-06]],\n\n [[-1.6525e-07]],\n\n [[-6.2628e-06]]],\n\n\n ...,\n\n\n [[[ 1.2583e-06]],\n\n [[ 6.3547e-06]],\n\n [[ 1.1069e-06]],\n\n ...,\n\n [[-3.2940e-06]],\n\n [[ 1.7016e-06]],\n\n [[-1.7194e-06]]],\n\n\n [[[ 3.0046e-06]],\n\n [[ 1.2387e-06]],\n\n [[ 1.4340e-06]],\n\n ...,\n\n [[-3.6823e-06]],\n\n [[ 1.0708e-06]],\n\n [[-2.1254e-06]]],\n\n\n [[[-2.7355e-07]],\n\n [[ 3.6895e-07]],\n\n [[-9.5108e-07]],\n\n ...,\n\n [[ 6.8009e-07]],\n\n [[ 5.5262e-08]],\n\n [[ 3.9748e-07]]]]), 'exp_avg_sq': tensor([[[[3.8437e-10]],\n\n [[2.4418e-10]],\n\n [[1.7614e-10]],\n\n ...,\n\n [[1.1319e-10]],\n\n [[7.9836e-11]],\n\n [[8.5714e-11]]],\n\n\n [[[5.8378e-09]],\n\n [[6.5873e-09]],\n\n [[2.4320e-09]],\n\n ...,\n\n [[1.7207e-09]],\n\n [[1.4400e-09]],\n\n [[1.1509e-09]]],\n\n\n [[[2.1176e-10]],\n\n [[1.5544e-09]],\n\n [[1.6243e-09]],\n\n ...,\n\n [[8.5903e-09]],\n\n [[4.8789e-09]],\n\n [[1.5518e-09]]],\n\n\n ...,\n\n\n [[[2.9948e-10]],\n\n [[1.7676e-09]],\n\n [[3.4415e-10]],\n\n ...,\n\n [[3.0551e-09]],\n\n [[2.0314e-09]],\n\n [[2.3420e-09]]],\n\n\n [[[3.0954e-10]],\n\n [[2.0101e-09]],\n\n [[9.6574e-10]],\n\n ...,\n\n [[5.7243e-09]],\n\n [[3.0661e-09]],\n\n [[3.1523e-09]]],\n\n\n [[[1.6032e-10]],\n\n [[8.8377e-11]],\n\n [[1.5562e-10]],\n\n ...,\n\n [[1.8456e-10]],\n\n [[2.4937e-10]],\n\n [[1.0145e-10]]]])}, 142: {'step': 7160, 'exp_avg': tensor([ 9.8710e-06, -6.5622e-05, -1.4028e-04, -7.2247e-06, 2.6756e-05,\n 4.1910e-05, -8.6404e-05, 3.2906e-05, 3.8891e-05, 1.2056e-05,\n 3.2340e-05, 3.1948e-05, 2.0364e-06, 4.6058e-06, -1.6685e-05,\n 1.2224e-05, 3.0483e-05, 6.1990e-05, -9.7971e-05, 8.2803e-07,\n 6.3401e-06, -1.5685e-05, 1.3877e-05, 6.2005e-05, -2.0101e-05,\n 5.4953e-05, 1.1228e-06, 8.2703e-06, 1.8889e-04, -1.2506e-05,\n 1.5098e-05, 2.6787e-05, -4.6386e-05, -1.5084e-04, -3.2104e-06,\n 8.8748e-05, -7.8252e-05, -6.2087e-06, 6.1844e-06, -5.1456e-07,\n -1.2093e-05, -9.0279e-05, -1.3803e-05, -3.1721e-05, 7.1934e-05,\n -5.2859e-05, -1.6198e-05, 2.5840e-05, 1.4890e-05, 2.6253e-05,\n 3.4454e-05, -2.2166e-05, -1.2102e-05, -7.3985e-05, 3.7044e-06,\n -2.7509e-05, 1.0144e-04, 1.2807e-05, 2.0493e-05, 6.7359e-06,\n 1.9857e-05, -7.6490e-05, -6.3825e-06, 1.9648e-05, 1.0312e-06,\n -2.6508e-05, -1.2512e-05, -1.3118e-04, 6.8584e-06, -1.4002e-06,\n -8.8390e-05, -5.8121e-05, 1.6843e-04, -6.9087e-05, 6.8158e-05,\n 4.0958e-05, 9.8007e-05, -1.5986e-05, -2.0719e-06, -8.4847e-05,\n 6.0973e-05, -3.5945e-05, 1.4227e-04, -4.9806e-05, -4.7912e-05,\n 3.7626e-06, 7.4842e-05, 4.8702e-05, -1.1049e-04, -6.4666e-05,\n -8.7417e-05, -5.0156e-06, -5.6484e-06, -2.7342e-06, 6.4644e-05,\n -2.0543e-05, 3.1219e-05, 4.0605e-05, 2.5828e-05, -1.2859e-04,\n 5.4730e-06, -6.5432e-06, -2.4593e-06, -1.3824e-05, 8.5425e-06,\n 1.4240e-05, 7.2579e-05, 6.3221e-05, 7.6888e-05, -4.2874e-04,\n -6.5095e-05, 1.1452e-06, -7.5143e-05, -3.0042e-05, 5.0462e-05,\n -6.5953e-05, 1.1313e-05, 7.9381e-06, 1.9250e-05, -3.9784e-05,\n 4.7634e-05, -6.7292e-05, -5.1135e-05, -3.0834e-05, -1.0778e-05,\n 2.2642e-05, 2.2803e-05, 5.4119e-06, 3.8820e-05, 6.5681e-05,\n 1.8961e-05, -7.0666e-05, -5.2929e-07, -4.1048e-05, 4.3356e-05,\n -1.4753e-05, 5.3117e-05, -3.7818e-05, 6.7976e-05, 7.8037e-06,\n -7.2935e-06, -5.4966e-06, -9.3909e-05, 5.3705e-06, 2.2394e-05,\n -1.3949e-05, 3.3987e-08, 7.8681e-06, 7.4356e-05, 5.1291e-07,\n 1.1493e-04, -1.8926e-04, 1.7336e-05, 6.9644e-06, 2.0651e-05,\n -8.3586e-08, 1.8976e-05, 4.5138e-05, -2.7797e-06, -1.4108e-05,\n -9.1593e-05, -8.3930e-05, 4.2227e-05, -1.0870e-04, -4.8417e-06,\n -1.6754e-05, -1.5340e-04, -5.8091e-05, 2.4391e-05, 5.1792e-05,\n -3.0853e-05, 5.5873e-05, 1.9238e-05, -6.0326e-05, 2.8825e-05,\n 4.7553e-06, -1.2390e-07, -1.4922e-04, 3.6924e-05, 1.6250e-05,\n 7.4596e-05, 5.0450e-05, -2.8896e-04, -6.3891e-05, 1.6579e-05,\n 4.5755e-05, -5.5754e-05, 5.2268e-05, -2.8469e-05, -1.8921e-06,\n 7.9752e-05, 3.7218e-05, -1.5243e-05, -4.2998e-05, -1.7787e-05,\n 6.6582e-06, -1.0500e-06, 1.0508e-04, 2.5162e-06, -1.3391e-05,\n -4.2316e-05, -1.1592e-04, 6.4177e-06, -3.6049e-05, -4.3899e-05,\n 1.3332e-05, 1.0037e-05, -6.6264e-05, 8.1187e-05, -2.4804e-05,\n -6.6628e-05, -1.1339e-04, -1.1733e-04, -1.8600e-05, 7.4127e-06,\n -3.7197e-04, 1.6722e-05, -3.3103e-06, -5.0342e-05, 4.2039e-05,\n 6.3514e-05, -1.1634e-04, -1.8528e-05, -7.9849e-06, 6.2930e-05,\n 1.5756e-05, 5.4994e-06, -8.2341e-06, 3.4947e-06, -1.9927e-05,\n -1.0410e-04, 9.9611e-06, 1.3044e-05, 8.4156e-05, -5.6372e-06,\n 1.2483e-06, -2.3471e-05, -6.9157e-05, -2.5736e-05, 6.7474e-06,\n 5.3049e-06, -8.2784e-06, -5.6121e-05, -1.9415e-04, -9.3054e-07,\n 8.4379e-06, 6.8576e-05, 1.2031e-06, 1.1011e-06, -2.5247e-04,\n 5.4604e-05, 9.4612e-05, -2.7059e-04, -5.5582e-05, -1.8638e-05,\n -2.7147e-05, 2.1050e-05, 4.6091e-05, -1.7832e-05, -8.1802e-05,\n 3.0201e-05, 1.3166e-04, 1.8892e-05, -1.9065e-05, 1.4012e-05,\n 2.3383e-05, -2.3713e-05, 3.4391e-05, 2.5888e-05, 3.4844e-05,\n -2.8803e-06, 3.7889e-06, 1.8413e-04, -9.1666e-05, -1.7264e-05,\n 3.6496e-05, -2.0251e-05, 1.6081e-05, -5.0521e-05, -4.4748e-06,\n 4.0579e-05, -3.3210e-05, -2.7900e-05, -4.2072e-05, 7.4146e-05,\n -5.9387e-05, 1.3225e-05, 2.8185e-05, 2.5908e-05, -6.2118e-05,\n 2.5444e-05, 1.0042e-04, 5.8258e-05, -1.0146e-04, -4.7630e-05,\n 2.8498e-05, 2.5516e-06, -6.4342e-06, 1.2406e-05, 9.9757e-05,\n 7.4654e-07, -3.6032e-05, -7.1597e-05, -7.4456e-06, -3.5485e-05,\n -5.3802e-06, 5.5826e-05, 1.1401e-05, 7.8697e-05, -1.8322e-05,\n 5.5152e-06, 8.3904e-06, 5.7179e-05, -2.3938e-05, 2.0355e-05,\n 3.4709e-06, 1.2033e-05, -4.9130e-05, 1.3070e-05, -1.0830e-06,\n -9.9133e-05, -8.6942e-05, 1.0342e-05, 1.2875e-06, 1.8104e-05,\n 1.1689e-05, -3.2188e-06, 5.1314e-05, 1.6276e-05, 1.0584e-04,\n -4.2339e-06, 7.5304e-05, 1.5925e-05, 3.4653e-05, 4.8589e-06,\n -6.8935e-05, 5.0381e-05, 1.9806e-05, -1.0767e-05, 1.0402e-05,\n 6.1216e-08, -2.4824e-04, -6.3757e-06, -4.1807e-05, -1.5894e-05,\n 1.6250e-06, -2.1106e-06, -4.9884e-05, -3.5826e-04, 1.4171e-05,\n -6.6826e-05, 8.7631e-06, 3.3196e-05, 5.0171e-05, 1.4896e-05,\n 1.7661e-05, -5.3824e-06, -2.3715e-06, -2.4434e-05, 6.7107e-06,\n 9.8900e-05, 1.2964e-05, 3.2143e-05, 1.8921e-05, -1.1606e-05,\n 6.0340e-05, 5.8093e-05, 5.5383e-06, 4.3708e-05, -2.3401e-05,\n -7.4314e-05, 2.2468e-05, 2.2421e-06, 3.2964e-06, -8.6409e-05,\n 1.5706e-05, 7.2629e-06, 2.2607e-05, 3.1422e-06, 1.4884e-05,\n 3.7716e-05, -4.6190e-06, -1.3054e-04, 5.3812e-06, -4.2091e-05,\n -2.5265e-05, 2.5796e-05, -2.9268e-04, 8.2498e-06, 3.2293e-06,\n 2.6126e-05, 4.2512e-05, -1.9365e-05, 1.0946e-06, 9.2059e-05,\n 3.0199e-05, -1.6175e-07, 3.5705e-05, 5.3251e-05, -5.5820e-05,\n -8.0870e-05, -2.2500e-04, 3.7198e-06, -1.0092e-04, -3.2659e-05,\n -3.0826e-05, -7.5579e-07, -2.0473e-05, 3.8702e-05, -5.4798e-05,\n -3.3325e-05, 5.1916e-05, 2.1274e-05, -1.4943e-05, 4.2559e-06,\n -3.7188e-05, 3.5364e-05, -4.2560e-06, 2.2961e-05, 2.8479e-05,\n 2.6386e-05, -1.2305e-05, -6.7070e-05, -2.7652e-04, 6.2412e-07,\n -6.1342e-05, -9.1540e-06, 5.4936e-05, 1.1765e-05, -2.1273e-05,\n 3.5807e-05, 4.6670e-05, 2.2198e-05, 2.3739e-06, -1.8466e-05,\n -1.7256e-04, -3.4392e-07, -1.7017e-04, 5.1590e-05, -4.0814e-05,\n -7.5504e-05, -2.6342e-05, 7.3078e-05, -2.8472e-05, 7.0923e-05,\n 5.3659e-05, 5.0297e-05, -1.6579e-05, 1.4494e-06, -3.0799e-05,\n -1.0513e-04, 4.7366e-05, 1.1773e-05, 6.3387e-05, -7.3914e-05,\n 2.3219e-05, 4.5113e-06, -3.0894e-05, 5.1848e-06, 9.5118e-06,\n 1.1949e-05, 2.9933e-05, 1.2393e-05, -3.3520e-05, -9.8994e-05,\n -7.1180e-06, -7.2122e-05, 3.3783e-05, 6.8679e-05, 2.2050e-04,\n 3.1274e-05, -2.4357e-05, -2.6980e-05, -6.4302e-06, -2.2429e-07,\n 1.5988e-05, -3.4208e-05, 2.7219e-05, 7.1822e-06, 4.0082e-05,\n 1.0731e-05, -5.6637e-06, 4.3969e-05, 1.4876e-05, -3.3972e-05,\n 9.2824e-05, -1.8379e-04, -5.0558e-05, -5.7265e-06, 2.2615e-07,\n -7.8155e-05, -5.2494e-05, -4.6302e-05, 2.9108e-05, -3.0155e-06,\n -7.4392e-07, -8.9417e-05, -1.1339e-05, 3.3954e-05, 3.3728e-06,\n -6.6549e-06, 8.3550e-05, 2.2893e-05, 8.0150e-05, -7.5316e-05,\n 5.6249e-05, -5.3564e-05, 1.3751e-05, -2.3877e-05, 8.0259e-05,\n -6.2309e-05, 2.1201e-05]), 'exp_avg_sq': tensor([9.1058e-08, 1.9527e-06, 2.0451e-06, 9.5739e-08, 6.6548e-08, 3.0255e-07,\n 1.5026e-07, 2.3478e-07, 3.3451e-07, 6.4092e-07, 8.4876e-08, 1.8256e-07,\n 5.1477e-08, 2.0996e-07, 1.4305e-07, 2.8712e-08, 5.0134e-07, 1.1444e-06,\n 4.6037e-07, 3.9183e-08, 4.6218e-07, 1.1808e-07, 2.1455e-07, 2.1850e-07,\n 4.9051e-07, 2.8785e-07, 4.0902e-07, 7.7727e-08, 5.0434e-06, 6.4343e-08,\n 6.6078e-08, 9.4257e-08, 1.0506e-06, 6.9320e-07, 2.2314e-07, 1.0336e-06,\n 2.2209e-07, 5.3023e-08, 1.2285e-07, 1.5936e-06, 6.8617e-07, 7.4688e-07,\n 4.7881e-07, 1.3236e-07, 6.8292e-07, 1.5636e-06, 1.9833e-07, 9.4823e-08,\n 2.9474e-07, 1.4921e-07, 3.3941e-07, 4.7628e-09, 1.9617e-08, 5.9337e-07,\n 1.0746e-06, 1.9353e-08, 1.0884e-06, 4.5313e-08, 1.9881e-07, 2.7549e-07,\n 4.8161e-07, 6.9973e-07, 4.5388e-07, 4.1402e-08, 9.3788e-08, 5.6273e-07,\n 1.4917e-06, 1.8088e-06, 1.4256e-07, 1.6164e-08, 5.4378e-07, 3.9267e-06,\n 1.6656e-06, 4.3046e-07, 3.3496e-07, 2.7152e-07, 3.3368e-07, 8.2096e-07,\n 1.0074e-08, 2.7704e-06, 8.6245e-07, 9.5068e-07, 2.4607e-06, 8.3584e-07,\n 3.9458e-07, 2.4442e-07, 2.7874e-07, 5.7117e-08, 3.6468e-07, 4.8635e-07,\n 7.2494e-07, 2.2329e-07, 2.1088e-08, 3.9683e-07, 1.8351e-07, 6.8413e-08,\n 3.8303e-07, 9.8959e-08, 1.9740e-07, 5.3577e-07, 2.3691e-07, 5.0893e-08,\n 4.3009e-08, 2.8228e-06, 9.1475e-07, 1.4825e-07, 2.0823e-07, 1.3122e-07,\n 1.7953e-06, 4.2925e-06, 1.8824e-06, 3.7168e-07, 2.5384e-07, 2.9498e-07,\n 7.4944e-07, 3.8858e-07, 3.9780e-08, 1.8645e-08, 3.5214e-08, 8.4113e-08,\n 2.4231e-07, 9.8823e-07, 1.1917e-06, 2.2319e-07, 5.5311e-07, 5.9419e-08,\n 3.0385e-07, 2.4928e-08, 7.4930e-08, 2.8457e-07, 9.3056e-08, 8.2241e-07,\n 6.9161e-08, 1.7290e-06, 2.2704e-07, 6.5691e-07, 1.3590e-07, 2.2936e-07,\n 1.0668e-06, 1.5567e-06, 2.6501e-07, 2.3981e-08, 1.5682e-07, 1.9115e-07,\n 3.0651e-07, 1.0082e-07, 1.9069e-06, 1.0577e-07, 7.0421e-07, 3.7782e-08,\n 5.5904e-07, 1.0665e-06, 2.2372e-07, 7.0368e-08, 2.5854e-07, 1.3401e-07,\n 5.6765e-08, 4.7101e-07, 4.0602e-07, 1.3394e-07, 1.5342e-06, 3.4614e-07,\n 4.2436e-07, 9.6321e-07, 1.2008e-08, 4.8263e-07, 7.8375e-07, 1.6429e-07,\n 1.6895e-07, 2.0244e-07, 2.9610e-07, 6.6582e-07, 1.9685e-07, 1.1706e-06,\n 1.3959e-07, 8.3697e-07, 2.3597e-08, 2.6801e-06, 1.3223e-07, 7.1223e-08,\n 3.2832e-07, 2.2344e-06, 2.2477e-06, 3.1838e-07, 4.4712e-07, 3.9229e-07,\n 2.8227e-07, 2.1931e-07, 1.9355e-07, 1.0371e-08, 1.1764e-06, 1.7517e-07,\n 6.0566e-07, 5.8400e-07, 1.2156e-07, 7.5341e-08, 2.0658e-06, 6.5409e-07,\n 2.7818e-08, 1.2140e-07, 2.0908e-07, 1.1497e-06, 5.2687e-08, 2.6260e-07,\n 8.4402e-08, 5.9174e-08, 5.0692e-08, 2.9455e-07, 5.9722e-07, 1.7452e-07,\n 4.6192e-07, 1.0034e-06, 7.1202e-07, 1.3039e-07, 2.5272e-08, 3.5524e-06,\n 2.1631e-07, 6.1969e-08, 1.6608e-07, 3.0187e-07, 2.3652e-07, 7.8631e-07,\n 2.4777e-07, 9.1500e-09, 3.2326e-07, 1.9449e-07, 1.8531e-08, 2.8046e-07,\n 7.5733e-08, 2.9613e-08, 4.2657e-07, 7.6308e-08, 1.1202e-06, 8.9746e-07,\n 2.6848e-07, 2.2397e-07, 5.7613e-08, 7.1462e-07, 6.6065e-07, 1.3137e-08,\n 1.1225e-06, 3.0180e-07, 4.6492e-07, 2.2024e-06, 1.1344e-06, 2.1635e-08,\n 3.4034e-07, 2.5957e-06, 8.6246e-09, 7.1877e-06, 1.5602e-07, 1.4110e-06,\n 3.4340e-06, 1.8046e-06, 8.5057e-08, 6.1833e-07, 4.4205e-07, 1.3836e-07,\n 3.8408e-06, 7.1857e-07, 1.7080e-07, 9.2270e-07, 6.6995e-07, 6.2254e-08,\n 1.1750e-07, 2.4648e-07, 6.4984e-08, 2.3354e-08, 9.5066e-08, 6.4692e-08,\n 2.8347e-07, 3.3530e-08, 1.4328e-06, 1.9336e-06, 4.3624e-07, 3.6160e-07,\n 3.4005e-07, 6.2617e-08, 8.5863e-07, 3.5896e-07, 5.3337e-07, 9.2947e-08,\n 6.3775e-07, 1.4978e-07, 1.6735e-07, 1.4536e-06, 3.4990e-07, 1.6555e-07,\n 2.2173e-07, 5.5957e-07, 4.0320e-07, 2.4896e-07, 1.1416e-07, 7.9682e-07,\n 3.3909e-07, 1.6291e-08, 6.0667e-09, 4.1982e-08, 8.8776e-07, 4.4614e-07,\n 1.0794e-07, 2.5894e-07, 2.7117e-07, 1.4041e-07, 1.0274e-07, 4.2050e-07,\n 1.7415e-07, 7.1393e-08, 4.7078e-07, 4.0545e-08, 3.2235e-08, 1.8555e-08,\n 5.5316e-07, 1.1292e-07, 3.1829e-07, 3.3335e-08, 5.6025e-08, 3.9065e-07,\n 3.9428e-07, 1.7314e-08, 1.9660e-06, 6.3083e-07, 1.9315e-07, 3.3323e-09,\n 1.6044e-07, 3.2292e-08, 4.5896e-07, 1.9905e-07, 2.6575e-07, 6.4501e-07,\n 4.9463e-08, 6.1822e-07, 3.5041e-08, 2.6678e-07, 1.3628e-07, 2.5236e-07,\n 6.7704e-07, 5.3258e-07, 1.3524e-07, 5.8442e-09, 9.9055e-10, 1.6689e-06,\n 4.7306e-08, 7.3333e-07, 3.1349e-07, 8.2231e-08, 4.5187e-07, 3.8007e-07,\n 1.9825e-06, 1.1375e-07, 3.4488e-07, 2.6573e-07, 4.3090e-07, 3.5928e-07,\n 9.0159e-08, 4.1445e-07, 2.6478e-08, 1.9194e-08, 2.1663e-07, 4.9971e-08,\n 1.0885e-06, 3.9781e-07, 9.0750e-08, 2.0986e-08, 9.4227e-08, 2.1218e-07,\n 4.2672e-07, 7.1904e-08, 2.1985e-07, 8.4194e-08, 3.8464e-07, 1.0332e-07,\n 6.8837e-08, 7.6113e-09, 1.4896e-06, 1.5352e-07, 4.0215e-08, 2.1629e-07,\n 2.3633e-08, 2.5383e-07, 2.3370e-07, 9.4133e-09, 9.1018e-07, 2.2075e-07,\n 8.6646e-07, 2.7881e-07, 1.1232e-07, 8.5815e-06, 2.5043e-08, 2.4351e-08,\n 1.8163e-07, 6.3250e-07, 8.3902e-08, 3.5267e-07, 5.8195e-07, 8.5609e-08,\n 7.7820e-07, 4.8993e-07, 5.1086e-07, 4.4265e-07, 4.4496e-07, 1.9880e-06,\n 3.1948e-07, 1.9871e-06, 1.6188e-07, 1.9511e-07, 1.1994e-07, 2.5347e-07,\n 5.6301e-07, 5.4434e-07, 8.5767e-07, 7.2317e-07, 8.9245e-08, 2.5671e-06,\n 2.3128e-08, 2.3814e-07, 2.6404e-07, 2.6021e-07, 4.7110e-07, 3.6068e-07,\n 2.8728e-07, 1.6084e-07, 1.3425e-06, 1.1998e-06, 1.4803e-07, 6.3047e-07,\n 1.0469e-07, 1.3435e-07, 7.5800e-08, 9.8316e-07, 3.1769e-07, 1.8173e-07,\n 1.8706e-07, 1.4424e-07, 3.4701e-07, 1.3710e-06, 1.0638e-06, 1.1773e-06,\n 2.8477e-07, 1.8955e-07, 1.7112e-06, 2.9251e-07, 5.7815e-07, 5.9519e-08,\n 3.2499e-07, 2.8178e-07, 3.3009e-07, 2.3805e-07, 1.2450e-07, 1.6456e-07,\n 2.9165e-07, 2.8442e-07, 1.3049e-06, 1.7491e-07, 5.6183e-07, 7.0240e-08,\n 4.9162e-08, 1.2589e-07, 3.7102e-08, 5.1014e-07, 6.6890e-08, 1.4640e-07,\n 1.4743e-08, 2.8203e-07, 7.0155e-07, 2.2817e-07, 1.1381e-06, 3.5167e-07,\n 4.2613e-07, 2.5719e-06, 1.4217e-07, 8.0373e-07, 2.6491e-07, 3.9174e-07,\n 1.6887e-09, 7.0331e-08, 1.0512e-07, 3.3177e-07, 8.4230e-08, 9.1955e-07,\n 2.4179e-06, 3.4442e-07, 2.4891e-07, 7.2678e-08, 5.1290e-08, 3.3105e-07,\n 1.9438e-06, 2.3148e-07, 2.7303e-07, 1.8168e-07, 3.0181e-06, 4.2100e-07,\n 1.1947e-07, 7.5995e-07, 3.6018e-07, 1.2228e-07, 8.9600e-07, 3.7335e-08,\n 3.7880e-07, 2.3798e-08, 8.2066e-08, 1.3279e-06, 1.3895e-07, 3.9678e-07,\n 6.6421e-07, 3.1087e-07, 1.4954e-07, 2.0199e-07, 7.5181e-08, 4.4489e-07,\n 8.7465e-07, 4.6388e-08])}, 143: {'step': 7160, 'exp_avg': tensor([ 1.0010e-05, -5.1613e-05, -1.3595e-04, -8.5073e-06, 1.4823e-05,\n -2.6670e-05, -7.7604e-05, 1.8307e-05, 1.9706e-05, -1.3615e-05,\n 1.0015e-05, 1.7894e-05, -2.3415e-06, 1.4175e-05, -1.6733e-05,\n 2.4802e-06, 1.2924e-05, 4.3824e-05, -3.9994e-05, 6.0406e-07,\n 8.6997e-06, -1.5980e-05, 5.4081e-06, 2.6952e-05, -1.6347e-05,\n 1.9334e-05, -5.6260e-06, 6.8696e-06, -3.6247e-05, -2.2381e-05,\n 8.5276e-06, 1.6940e-05, -3.6650e-05, -8.4782e-05, 2.6836e-06,\n 5.8185e-05, -7.8880e-05, -8.4644e-06, 8.7399e-06, -2.7148e-05,\n -7.3757e-05, -6.7519e-05, -2.6077e-05, -2.6943e-05, 4.9578e-05,\n -1.1348e-05, -1.3656e-05, 1.9541e-05, 5.5258e-06, 2.7382e-05,\n 3.0987e-05, -2.0632e-05, -1.3608e-05, -6.4463e-05, 4.9261e-06,\n -2.5149e-05, 4.1579e-05, 6.6120e-06, 7.7340e-06, -4.3637e-06,\n -2.9915e-05, -6.5713e-05, -1.0993e-06, 1.6338e-05, -3.6838e-06,\n -2.7656e-05, -3.1438e-05, 3.0920e-05, 6.5327e-06, -5.1152e-06,\n -1.2299e-05, -8.7059e-05, 5.0983e-05, -7.2745e-05, 5.2283e-05,\n 2.8835e-05, 6.3899e-05, -3.7486e-05, -3.0159e-06, 1.4275e-04,\n -8.7079e-06, -2.1897e-05, 6.8823e-05, -3.9703e-05, -5.0548e-05,\n -1.1789e-05, 5.7171e-05, 3.9612e-05, -8.0862e-05, -3.7603e-05,\n -6.3186e-05, 1.7357e-05, -5.5967e-06, -2.0354e-05, 4.5881e-05,\n -2.2660e-05, 6.0813e-07, 1.8486e-05, -4.0518e-06, -1.0608e-04,\n -1.6251e-05, -7.0129e-06, -4.6024e-06, -1.4768e-04, 6.8336e-06,\n 6.6355e-06, 4.3300e-05, 6.7955e-05, 4.3856e-05, -2.8451e-04,\n -7.1261e-05, 5.9038e-06, -7.0625e-05, -3.1544e-05, 4.9147e-05,\n -4.1394e-05, 4.8837e-06, 5.2582e-06, 1.7712e-05, -3.9043e-05,\n 2.9264e-05, -6.0585e-05, -7.0386e-05, -5.3036e-05, -2.7379e-06,\n 1.6313e-05, 1.4929e-05, 4.8959e-06, 1.7664e-05, 2.9524e-05,\n 2.3595e-05, 1.1763e-05, -9.9973e-06, 1.6583e-05, 2.7478e-05,\n -1.6081e-05, 2.9393e-05, -6.5457e-05, 3.0653e-05, -1.1904e-05,\n -2.2923e-05, -5.2715e-06, -8.6216e-05, -6.4105e-06, 1.8690e-05,\n -1.2310e-05, 1.6002e-04, 2.8306e-06, 2.7086e-05, -3.8296e-06,\n 8.8582e-05, -3.5876e-05, 1.0896e-05, 6.6324e-06, 6.2222e-06,\n -1.1737e-05, 4.7014e-06, 2.0839e-05, 3.5628e-05, -1.4716e-05,\n -7.5897e-05, -6.5900e-05, 2.5495e-05, -9.4762e-05, -3.3407e-06,\n -1.4269e-05, -1.1678e-04, -6.0746e-05, -1.4257e-06, 5.1192e-05,\n -2.0942e-05, -4.6165e-05, 2.0158e-05, -4.4911e-05, 2.2600e-05,\n 6.3969e-06, -1.8646e-07, -7.7261e-05, 1.1296e-05, 3.3625e-06,\n 4.7206e-05, 1.8795e-05, -3.0879e-04, -3.9136e-05, 7.4693e-06,\n 3.6096e-05, -4.1508e-05, 3.5261e-05, -5.3843e-05, -2.0040e-06,\n 4.0718e-05, 2.4592e-05, -3.6113e-05, -3.4653e-05, 4.4794e-06,\n 8.8155e-06, -3.2762e-05, 8.1113e-05, 2.6342e-06, -4.5541e-06,\n -5.5017e-05, -1.6818e-04, 3.3505e-06, -3.4260e-05, -4.8504e-05,\n 6.6116e-06, 1.6114e-06, -7.4966e-05, 6.3558e-05, -4.0188e-05,\n -7.0294e-05, -1.1042e-04, -9.0549e-05, -1.2243e-05, 9.5524e-06,\n -3.0002e-04, 8.2123e-06, -5.3905e-07, -5.4772e-05, 3.0375e-05,\n 2.6750e-05, -1.0681e-04, -2.2843e-05, -8.9305e-06, 2.4642e-05,\n 3.8895e-05, 5.8597e-06, -1.1266e-05, 2.8721e-06, -1.2432e-05,\n -8.8985e-05, 6.5523e-06, 2.8640e-05, 3.5258e-05, -2.8971e-05,\n -1.5359e-05, -2.1044e-05, 4.3591e-06, -3.2756e-05, 6.5587e-06,\n -9.0981e-06, 5.9405e-06, -5.7635e-05, -1.3439e-04, 8.7574e-06,\n 8.3325e-06, 5.9791e-05, 9.6667e-06, 1.2975e-06, -1.8987e-04,\n 3.7582e-05, 3.4511e-05, 2.1974e-04, -6.6714e-05, -1.3175e-05,\n -2.4940e-05, 1.4577e-05, 3.7623e-05, -4.4263e-06, -5.9532e-05,\n 1.5036e-05, 1.4030e-04, 1.9954e-05, -1.6291e-05, 7.8453e-06,\n 1.1941e-05, -1.8478e-05, 3.2621e-05, 1.6500e-05, 1.3733e-05,\n -9.9169e-06, 5.7745e-06, 8.4320e-05, -1.0364e-04, -1.6308e-05,\n 1.1506e-05, -1.7260e-05, 9.0047e-06, -7.6080e-05, 2.7390e-05,\n 3.1401e-05, -3.3141e-05, -1.9587e-05, 1.4201e-05, 5.8458e-05,\n -7.4347e-05, 7.5571e-06, 2.3232e-05, 2.0923e-05, -4.9907e-05,\n -8.4431e-06, 5.9615e-05, 3.7398e-05, -7.7504e-05, -5.6528e-05,\n 3.4907e-05, 2.7079e-06, -5.1841e-06, -4.1649e-05, 5.8728e-05,\n -1.0386e-05, -3.0927e-05, -6.8094e-05, -5.6259e-06, -5.0443e-05,\n -1.2349e-05, 2.4279e-05, 1.7488e-05, 2.3822e-05, -1.1969e-05,\n -4.7554e-08, 2.0704e-07, 2.9728e-05, -1.7512e-05, 2.6620e-05,\n 2.0184e-06, 6.8773e-06, -3.2070e-05, 6.6093e-06, -1.4333e-06,\n -6.4532e-05, -8.2229e-05, 2.8349e-06, 1.3221e-06, 9.5400e-06,\n 3.6558e-06, -1.2460e-05, 4.1699e-05, -4.0515e-06, 7.7413e-05,\n -4.9218e-06, 3.9382e-05, 6.7025e-06, 1.6600e-05, 5.7855e-06,\n -5.5223e-05, 3.5972e-05, 5.7000e-06, -4.7039e-06, 5.1461e-06,\n 1.5508e-07, -2.0220e-04, -6.9136e-06, -5.6491e-05, 3.2439e-06,\n 4.3579e-06, 6.1022e-06, -6.6564e-05, -2.9048e-04, 3.4234e-07,\n -7.0119e-05, 1.1875e-05, 6.3606e-06, 5.3370e-05, 5.1959e-06,\n -3.7357e-06, -9.6821e-06, -2.3434e-06, -2.7682e-05, -1.6082e-06,\n 4.6090e-05, 1.9467e-05, 1.5812e-05, 1.9674e-05, -1.6175e-05,\n 4.7010e-05, 1.5023e-05, 5.4856e-06, -1.1466e-05, -2.8335e-05,\n -6.7523e-05, 2.1538e-05, -5.4252e-06, 3.5460e-06, -6.8559e-05,\n 1.9188e-05, 1.5527e-06, 6.2657e-05, 6.6230e-07, -1.1438e-05,\n 1.8469e-05, -4.7282e-06, -1.3439e-04, 6.5845e-06, -9.4602e-06,\n -2.4623e-05, 3.8936e-05, -3.0654e-04, 6.7570e-06, 3.3500e-06,\n 2.7601e-05, -4.5266e-07, -5.7127e-05, 1.2192e-06, 3.9121e-05,\n 3.0830e-05, -2.3899e-06, 1.0755e-05, 2.0127e-05, 1.3665e-05,\n -7.8782e-05, 2.2499e-04, 5.0841e-06, -5.2001e-05, -3.5860e-05,\n -3.5029e-05, -9.9608e-07, -1.5515e-05, 6.6485e-05, -5.6667e-05,\n -1.5847e-05, 6.9862e-05, 1.3843e-05, -1.4164e-05, 3.2849e-06,\n -3.0244e-05, 1.9963e-05, -1.8593e-05, -2.0005e-06, 2.0318e-05,\n 5.6019e-06, -5.3903e-06, -7.3465e-05, -2.1990e-04, -9.5312e-06,\n -7.0212e-05, -8.3116e-06, 3.4795e-05, 2.9904e-06, -2.8653e-05,\n 3.2968e-05, 2.8067e-05, 2.6361e-05, -1.7894e-05, -1.6852e-05,\n -1.6017e-04, -1.6326e-05, -1.0633e-04, 3.5003e-05, -3.0168e-05,\n 6.4157e-05, -1.3292e-05, 3.2022e-05, -3.0638e-05, 3.9221e-05,\n 2.9299e-05, 2.9856e-05, -1.6750e-05, 8.5661e-06, -3.6745e-05,\n -9.6320e-05, 8.8916e-06, 9.3051e-06, 9.5631e-05, -9.1191e-05,\n 1.9305e-05, 4.0382e-06, -1.4157e-05, 2.9402e-06, -2.7336e-06,\n 5.8702e-06, 2.5373e-05, 1.3643e-05, -2.8646e-05, -8.4790e-05,\n -1.6790e-05, -4.9703e-05, 1.1678e-05, 1.5262e-05, -3.6546e-05,\n 1.4739e-05, -3.7675e-06, -1.3866e-05, 5.8613e-06, -2.3252e-07,\n 9.9603e-06, -3.6821e-05, 1.5014e-05, -3.7514e-07, 3.1786e-07,\n -2.1745e-05, -2.4007e-05, 2.0028e-05, 3.6624e-06, -2.6824e-05,\n 3.1181e-05, -1.3501e-04, -8.0777e-05, 4.4414e-05, -2.2757e-06,\n -1.0152e-04, -5.4127e-05, -6.9838e-05, 5.9144e-07, -1.4178e-05,\n -1.8298e-06, -4.5497e-05, -1.0173e-05, 3.0408e-05, 2.0351e-07,\n 1.3318e-05, 7.9715e-05, 1.3565e-05, 4.6995e-05, -7.1853e-05,\n 3.8881e-05, -4.6772e-05, 1.6985e-05, -1.8642e-05, 1.2681e-05,\n -7.1275e-05, 1.4572e-05]), 'exp_avg_sq': tensor([5.6288e-08, 1.2242e-06, 2.2753e-06, 5.6863e-08, 3.3947e-08, 2.7193e-07,\n 2.0001e-07, 1.9985e-07, 1.6205e-07, 1.1903e-07, 2.3532e-08, 1.6765e-07,\n 2.6133e-08, 1.3836e-07, 8.1167e-08, 1.3246e-08, 4.7248e-07, 5.3709e-07,\n 2.7109e-07, 2.4254e-08, 3.4961e-07, 5.6354e-08, 1.3392e-07, 9.6342e-08,\n 1.5778e-07, 6.5614e-08, 1.0664e-07, 9.8150e-08, 1.8933e-06, 5.8311e-08,\n 2.5402e-08, 6.2074e-08, 4.8482e-07, 4.3956e-07, 1.2646e-07, 3.9410e-07,\n 2.2485e-07, 7.2507e-08, 1.0529e-07, 4.8499e-07, 8.0232e-07, 4.4053e-07,\n 1.7914e-07, 1.9331e-07, 2.4147e-07, 3.2899e-07, 2.0119e-07, 3.8079e-08,\n 8.6070e-08, 6.5456e-08, 1.6599e-07, 4.2295e-09, 2.1197e-08, 9.5884e-07,\n 2.6986e-07, 1.9657e-08, 3.9531e-07, 9.5979e-09, 6.1526e-08, 7.0833e-08,\n 3.7263e-07, 4.8354e-07, 9.8312e-08, 3.2147e-08, 1.2510e-08, 5.5808e-07,\n 6.5039e-07, 9.3453e-07, 8.3333e-08, 5.9693e-09, 2.9396e-07, 8.4158e-07,\n 3.9700e-07, 3.7255e-07, 2.0937e-07, 1.4177e-07, 1.9557e-07, 4.4422e-07,\n 9.5741e-09, 1.2484e-06, 5.0118e-07, 2.5110e-07, 8.4901e-07, 7.5222e-07,\n 1.5156e-07, 1.3445e-07, 1.7279e-07, 4.3543e-08, 2.7155e-07, 2.9077e-07,\n 4.1569e-07, 1.1697e-07, 1.8427e-08, 9.2664e-08, 7.8792e-08, 4.9058e-08,\n 1.8199e-07, 3.8261e-08, 1.5408e-07, 3.3866e-07, 1.6324e-07, 3.8875e-08,\n 4.1627e-08, 9.2246e-07, 2.4921e-07, 6.2418e-08, 1.3385e-07, 1.5980e-07,\n 8.7975e-07, 1.7969e-06, 1.3857e-06, 2.4128e-07, 1.6203e-07, 1.1477e-07,\n 7.8567e-07, 2.6987e-07, 8.3036e-09, 7.5012e-09, 2.9951e-08, 6.7808e-08,\n 1.1705e-07, 5.4408e-07, 4.6317e-07, 1.2641e-07, 2.4933e-07, 4.3133e-08,\n 1.2793e-07, 1.5465e-08, 2.8559e-08, 1.0684e-07, 7.3735e-08, 5.2732e-07,\n 5.8741e-08, 7.1250e-07, 2.0663e-07, 3.0228e-07, 1.0465e-07, 2.7091e-07,\n 4.0537e-07, 8.3343e-07, 1.2367e-07, 2.2132e-08, 1.7608e-07, 1.2365e-07,\n 2.9123e-07, 1.0289e-07, 1.2306e-06, 3.8398e-08, 1.5598e-07, 1.3693e-08,\n 3.9566e-07, 6.3475e-07, 1.1349e-07, 5.0011e-08, 1.3948e-07, 5.9689e-08,\n 3.5856e-08, 1.7452e-07, 2.8967e-07, 5.6108e-08, 6.1620e-07, 2.8204e-07,\n 5.4112e-07, 6.7189e-07, 2.1168e-09, 1.7324e-07, 5.4612e-07, 1.2525e-07,\n 4.8074e-08, 2.4233e-07, 2.2797e-07, 3.4851e-07, 2.1023e-07, 4.2127e-07,\n 8.7461e-08, 4.0007e-07, 2.4089e-08, 1.1739e-06, 5.4021e-08, 3.2981e-08,\n 2.0863e-07, 6.1048e-07, 1.5251e-06, 3.1151e-07, 3.0913e-07, 3.3678e-07,\n 7.0548e-08, 1.3203e-07, 9.6412e-08, 9.3072e-09, 7.0988e-07, 9.0370e-08,\n 1.6801e-07, 3.3011e-07, 7.7925e-08, 4.0446e-08, 7.6521e-07, 5.5768e-07,\n 8.1037e-09, 1.6761e-07, 1.8576e-07, 1.2416e-06, 2.4500e-08, 2.0598e-07,\n 1.1824e-07, 1.7953e-08, 2.1107e-08, 2.3070e-07, 3.7668e-07, 1.5280e-07,\n 3.6690e-07, 4.5802e-07, 3.5894e-07, 6.0653e-08, 1.2000e-08, 2.6140e-06,\n 1.9364e-07, 2.8332e-08, 9.7799e-08, 2.5632e-07, 7.9358e-08, 4.2801e-07,\n 1.1114e-07, 1.0327e-08, 1.5137e-07, 2.3448e-07, 3.6787e-08, 1.3501e-07,\n 1.0385e-08, 1.7655e-08, 2.9875e-07, 4.6606e-08, 2.6170e-07, 2.7826e-07,\n 1.8541e-07, 1.2064e-07, 4.7618e-08, 5.0509e-07, 2.2215e-07, 1.5621e-08,\n 2.7565e-07, 2.2462e-07, 2.4898e-07, 1.0953e-06, 3.1372e-07, 1.4314e-08,\n 2.3174e-07, 1.1744e-06, 9.1151e-09, 2.4451e-06, 1.1292e-07, 5.7499e-07,\n 2.3784e-06, 3.3205e-07, 6.9372e-08, 2.4521e-07, 2.6051e-07, 8.2761e-08,\n 1.0341e-06, 3.9453e-07, 5.2990e-08, 1.0595e-06, 3.5004e-07, 2.6680e-08,\n 6.3068e-08, 2.7291e-07, 3.4033e-08, 1.7120e-08, 2.7733e-08, 2.3695e-08,\n 1.3824e-07, 2.8668e-08, 4.7840e-07, 5.9759e-07, 1.6390e-07, 7.6995e-08,\n 3.3950e-07, 2.7855e-08, 6.5722e-07, 6.1893e-07, 2.7522e-07, 7.7141e-08,\n 1.9955e-07, 1.7231e-07, 9.6975e-08, 5.9375e-07, 1.4749e-07, 2.5973e-07,\n 3.1579e-07, 2.1963e-07, 1.8612e-07, 9.6367e-08, 6.3622e-08, 3.5218e-07,\n 2.3427e-07, 1.9068e-08, 5.6902e-09, 3.2985e-08, 7.8079e-07, 1.4084e-07,\n 1.8985e-08, 1.9899e-07, 2.0026e-07, 1.1775e-07, 8.1890e-08, 1.3383e-07,\n 6.0871e-08, 7.8849e-08, 2.2968e-07, 1.2446e-08, 3.1042e-08, 5.7507e-09,\n 4.6624e-07, 5.2590e-08, 2.1800e-07, 1.1654e-08, 3.0865e-08, 9.6767e-08,\n 1.4034e-07, 7.4486e-09, 9.2152e-07, 3.1858e-07, 1.2004e-07, 2.8655e-09,\n 1.1255e-07, 6.6894e-09, 2.1658e-07, 8.3503e-08, 2.1755e-07, 3.3551e-07,\n 3.5890e-08, 2.6619e-07, 7.8972e-09, 6.5392e-08, 1.4541e-07, 2.1684e-07,\n 3.1918e-07, 2.1684e-07, 8.9437e-08, 2.7904e-09, 7.2593e-10, 8.4019e-07,\n 5.2225e-08, 4.9961e-07, 1.6412e-07, 5.2124e-08, 2.0955e-07, 4.0603e-07,\n 1.2396e-06, 9.4270e-08, 3.5173e-07, 9.6631e-08, 1.4802e-07, 2.4166e-07,\n 1.5749e-08, 3.4026e-07, 1.4223e-08, 1.3943e-08, 9.5816e-08, 1.0810e-08,\n 5.5841e-07, 1.2656e-07, 2.8238e-08, 1.7126e-08, 9.0320e-08, 1.2930e-07,\n 1.9145e-07, 5.5733e-08, 1.4782e-07, 6.8594e-08, 3.0892e-07, 7.3329e-08,\n 7.2034e-08, 7.4255e-09, 5.2535e-07, 1.5035e-07, 1.9542e-08, 2.4103e-07,\n 3.9251e-08, 1.8220e-07, 2.0710e-07, 7.9858e-09, 5.1769e-07, 1.7496e-07,\n 2.6166e-07, 1.5817e-07, 2.2143e-07, 9.6535e-06, 1.7861e-08, 1.7779e-08,\n 6.9037e-08, 2.2938e-07, 1.4991e-07, 1.0740e-07, 2.6965e-07, 1.0300e-07,\n 2.1946e-07, 2.8475e-07, 2.5812e-07, 3.7959e-07, 3.9495e-07, 1.2101e-06,\n 4.2056e-07, 4.7980e-07, 1.2912e-07, 1.7189e-07, 3.3658e-08, 1.1578e-07,\n 2.5700e-07, 3.1204e-07, 3.0336e-07, 6.3445e-07, 4.2171e-08, 1.1280e-06,\n 1.8347e-08, 1.1021e-07, 1.1692e-07, 1.1922e-07, 2.1654e-07, 1.1079e-07,\n 1.2717e-07, 1.3140e-07, 5.2055e-07, 9.3496e-07, 8.8539e-08, 4.3727e-07,\n 4.0396e-08, 5.5601e-08, 1.0023e-08, 7.8132e-07, 6.3368e-07, 1.2880e-07,\n 9.7242e-08, 1.4762e-07, 1.7848e-07, 6.5303e-07, 3.2847e-07, 5.2314e-07,\n 1.6705e-07, 8.6719e-08, 8.3058e-07, 1.7921e-07, 3.1456e-07, 2.2587e-08,\n 1.4255e-07, 1.0899e-07, 9.5962e-08, 1.9971e-07, 8.6018e-08, 1.7956e-07,\n 2.3216e-07, 9.2364e-08, 1.0512e-06, 2.5423e-07, 5.4274e-07, 4.6040e-08,\n 5.5681e-08, 1.1462e-07, 1.3396e-08, 3.0627e-07, 1.5049e-08, 1.2901e-07,\n 1.6911e-08, 1.5184e-07, 4.3684e-07, 1.5027e-07, 6.0652e-07, 3.9935e-07,\n 1.1104e-07, 1.6293e-06, 5.8999e-08, 2.9765e-07, 7.7031e-08, 2.3557e-07,\n 1.3055e-09, 3.9169e-08, 1.4566e-07, 1.2917e-07, 2.6712e-08, 5.1666e-07,\n 4.9689e-07, 1.3168e-07, 1.2368e-07, 4.3965e-08, 3.2226e-08, 1.1846e-07,\n 1.2302e-06, 2.4315e-07, 2.5226e-07, 9.1797e-08, 1.3081e-06, 1.4327e-07,\n 2.0887e-07, 6.6746e-07, 1.6258e-07, 7.9794e-08, 4.1445e-07, 3.8604e-08,\n 3.1658e-07, 7.7344e-09, 2.1812e-07, 1.1014e-06, 9.5495e-08, 3.7162e-07,\n 6.4422e-07, 1.6227e-07, 1.2951e-07, 1.9349e-07, 2.4059e-08, 1.8726e-07,\n 2.1742e-07, 1.8269e-08])}, 144: {'step': 7160, 'exp_avg': tensor([[[[ 1.0053e-06, 1.6433e-06, -1.0392e-06],\n [ 1.6128e-06, 7.2706e-07, 1.5457e-06],\n [-2.2814e-07, 8.0563e-07, 2.6925e-06]],\n\n [[-2.5571e-06, -3.9255e-06, -2.8077e-05],\n [ 3.9942e-06, -1.8907e-06, -1.4814e-05],\n [-2.1509e-07, -2.7932e-06, 2.3708e-08]],\n\n [[ 2.7420e-06, 4.7693e-06, 1.6992e-06],\n [ 2.1034e-06, 5.5152e-06, 1.7517e-06],\n [ 1.1961e-06, 5.2984e-06, 1.8853e-06]],\n\n ...,\n\n [[ 3.4007e-06, -1.0914e-05, -4.2053e-06],\n [ 8.3462e-07, -3.6704e-06, -2.1095e-06],\n [ 2.6773e-06, 4.3917e-06, 2.3488e-06]],\n\n [[ 4.7076e-06, -5.5098e-06, 6.0680e-07],\n [ 3.3926e-06, -1.1411e-06, 1.5331e-07],\n [-2.0637e-07, -1.1102e-06, 1.6852e-06]],\n\n [[ 1.2014e-06, 1.8845e-06, 2.0419e-06],\n [ 2.9432e-06, 1.8635e-06, 4.3757e-06],\n [ 1.7381e-07, 6.6383e-07, 1.6324e-06]]],\n\n\n [[[-1.4493e-07, -6.5517e-07, 1.7925e-08],\n [-5.7504e-07, -8.6535e-07, -4.9777e-07],\n [-4.2268e-07, -1.2596e-06, 8.2638e-07]],\n\n [[ 4.7564e-06, -1.5673e-07, -6.0692e-07],\n [ 4.9040e-06, -7.2531e-07, -7.4885e-08],\n [-7.4719e-07, -1.1282e-06, 3.4331e-07]],\n\n [[-2.3733e-06, -3.2718e-06, -2.0132e-06],\n [-2.3469e-06, -3.8724e-06, -3.0421e-06],\n [-9.1863e-07, -2.6009e-06, -2.8976e-06]],\n\n ...,\n\n [[-3.1487e-06, -2.5788e-06, 1.6328e-07],\n [-2.3590e-06, -1.0632e-06, 2.7319e-06],\n [-5.5889e-07, -2.1851e-06, 2.9933e-06]],\n\n [[-3.6630e-06, -3.4727e-06, -2.1340e-06],\n [-4.8881e-06, -3.1925e-06, -3.2171e-06],\n [-5.0678e-06, -3.7317e-06, -1.9735e-06]],\n\n [[-5.0658e-07, -7.5818e-07, -6.5157e-07],\n [-2.5758e-07, -6.0278e-07, -4.2855e-07],\n [-1.8827e-07, -3.3660e-07, -2.6936e-07]]],\n\n\n [[[-2.5987e-07, -6.2723e-07, -4.6439e-07],\n [-6.5289e-07, -7.0591e-07, -1.3322e-07],\n [-4.5657e-07, -5.1471e-07, -4.5474e-07]],\n\n [[ 9.4513e-07, -1.1854e-07, -3.3319e-07],\n [-4.4370e-07, -3.5933e-07, -3.2627e-07],\n [-1.8856e-07, -3.0045e-07, 3.6158e-07]],\n\n [[-2.0035e-06, -2.9556e-06, -2.2469e-06],\n [-2.6137e-06, -3.9849e-06, -3.0806e-06],\n [-4.2930e-07, -2.3868e-06, -2.6710e-06]],\n\n ...,\n\n [[-2.1291e-06, -2.4156e-06, -1.8978e-06],\n [-3.0864e-06, -2.2302e-06, 3.3936e-06],\n [ 1.4977e-07, -5.4819e-07, 4.5973e-06]],\n\n [[-2.1987e-06, -2.0958e-06, -2.7994e-06],\n [-3.7202e-06, -4.5422e-06, -1.8605e-06],\n [-4.6162e-06, -2.3795e-06, 6.8741e-07]],\n\n [[-4.1044e-07, -4.2251e-07, -6.4642e-07],\n [-4.5753e-07, -4.3203e-07, -1.5872e-07],\n [-2.0290e-07, 3.2586e-08, -2.9620e-08]]],\n\n\n ...,\n\n\n [[[ 6.6982e-09, 1.8890e-08, -7.4500e-08],\n [ 9.1321e-07, 9.2545e-07, 5.0111e-07],\n [ 2.3623e-07, -3.2420e-07, 4.8728e-07]],\n\n [[-9.2874e-07, -1.6153e-06, 4.1033e-07],\n [-2.2777e-06, -1.4106e-06, -8.2671e-07],\n [ 2.5996e-07, 4.5181e-08, 2.6083e-07]],\n\n [[ 6.7932e-07, 2.9885e-07, 5.7712e-07],\n [ 1.8772e-07, 4.7646e-07, 4.0578e-07],\n [ 5.5353e-07, -6.8608e-08, 1.1977e-07]],\n\n ...,\n\n [[ 6.1855e-07, 4.2649e-07, -4.9516e-07],\n [ 8.8418e-08, -3.0848e-06, -1.8945e-07],\n [ 4.7997e-08, -6.3294e-07, -1.7634e-06]],\n\n [[ 9.6148e-07, 6.0843e-07, 4.0328e-07],\n [-2.4368e-07, -7.2454e-06, -1.0564e-06],\n [ 4.7278e-07, 7.4315e-08, -4.4201e-06]],\n\n [[ 3.8626e-07, 4.6240e-07, 6.3621e-07],\n [ 3.0041e-07, -8.6929e-07, 1.2119e-07],\n [ 5.6713e-07, -1.5619e-07, -6.2089e-07]]],\n\n\n [[[ 5.0840e-08, 1.3827e-06, 6.5335e-07],\n [-8.1632e-07, -6.1811e-07, -1.1075e-06],\n [-1.1566e-07, -1.0759e-10, -5.2322e-08]],\n\n [[-2.3032e-07, 5.6048e-07, 7.4617e-07],\n [-1.5139e-06, -9.2952e-07, -1.5140e-06],\n [ 1.7111e-07, 6.0512e-08, -9.9904e-07]],\n\n [[-3.8130e-07, -1.6626e-07, -7.4606e-08],\n [-6.3087e-08, -5.7090e-08, -1.0536e-08],\n [-1.9339e-07, -9.4413e-08, -4.9981e-09]],\n\n ...,\n\n [[ 1.2314e-06, 2.6583e-07, -1.2372e-07],\n [ 4.8031e-07, 9.6195e-08, 4.7679e-08],\n [ 1.1156e-08, 9.3617e-07, 7.9212e-07]],\n\n [[ 2.2884e-06, 3.8827e-08, 4.7812e-08],\n [ 3.6338e-06, 2.3215e-06, -9.7944e-08],\n [ 7.3514e-07, 1.6739e-06, 1.0783e-06]],\n\n [[-6.7044e-07, -8.1285e-07, -3.5650e-07],\n [-2.9979e-07, -3.1360e-08, 2.7774e-07],\n [-2.1127e-07, -1.2568e-07, 1.0503e-07]]],\n\n\n [[[-3.0334e-07, -2.4984e-07, 1.2330e-07],\n [-2.7047e-07, 1.5045e-07, 4.6662e-07],\n [-1.5401e-07, -2.5735e-08, -1.1239e-08]],\n\n [[ 3.2178e-06, 9.6680e-07, 1.2735e-07],\n [ 2.6254e-06, 7.4470e-07, 2.1540e-06],\n [ 9.3357e-07, 1.2533e-08, 3.2838e-06]],\n\n [[-1.1532e-06, -9.4184e-07, -4.8505e-07],\n [-1.0328e-06, -9.4450e-07, -8.4129e-07],\n [-1.1480e-06, -1.1421e-06, -9.5889e-07]],\n\n ...,\n\n [[-4.7514e-07, -1.7114e-06, 1.7972e-07],\n [-1.4712e-06, -1.4687e-06, 3.7781e-06],\n [ 4.0782e-08, 1.9886e-06, 1.3882e-06]],\n\n [[-1.3449e-07, -1.6924e-06, -5.3797e-07],\n [-1.7144e-06, -2.4340e-06, 9.9182e-07],\n [-6.7529e-07, 1.3005e-06, -4.2815e-07]],\n\n [[-3.4303e-07, 3.9341e-07, 2.0027e-06],\n [-3.5584e-07, -5.3615e-07, 4.4399e-08],\n [ 4.2063e-09, -3.1054e-08, -8.3106e-08]]]]), 'exp_avg_sq': tensor([[[[1.7145e-10, 2.4946e-10, 8.6630e-10],\n [3.3906e-10, 5.0606e-10, 1.9044e-09],\n [6.4876e-10, 7.8414e-10, 8.8425e-10]],\n\n [[7.2120e-09, 2.0546e-08, 3.9746e-08],\n [7.4853e-09, 1.9546e-08, 6.1700e-08],\n [7.4172e-09, 1.3524e-08, 3.0691e-08]],\n\n [[1.1609e-09, 1.1837e-09, 4.7522e-10],\n [1.2486e-09, 1.6194e-09, 3.3592e-10],\n [1.1791e-09, 1.7019e-09, 3.1051e-10]],\n\n ...,\n\n [[1.2168e-09, 1.4903e-09, 5.8446e-10],\n [1.5156e-09, 2.7159e-09, 4.1711e-10],\n [2.6006e-09, 2.1884e-09, 4.9516e-10]],\n\n [[1.8194e-09, 2.4433e-09, 8.2092e-10],\n [1.8424e-09, 4.7871e-09, 1.3672e-09],\n [3.3845e-09, 3.0942e-09, 1.1331e-09]],\n\n [[2.7098e-10, 1.9723e-10, 4.3416e-10],\n [4.8648e-10, 2.5827e-10, 3.4052e-09],\n [6.1831e-11, 7.2195e-11, 3.8443e-10]]],\n\n\n [[[2.5430e-10, 1.9769e-10, 2.0585e-10],\n [1.6807e-10, 1.7928e-10, 1.4030e-10],\n [2.2918e-10, 2.3292e-10, 2.0031e-10]],\n\n [[3.0358e-09, 1.3788e-09, 1.6227e-09],\n [1.7578e-09, 3.3213e-10, 6.0088e-10],\n [1.9440e-09, 1.3133e-09, 1.0472e-09]],\n\n [[4.2424e-10, 6.0256e-10, 4.3785e-10],\n [7.3757e-10, 4.3699e-10, 3.3580e-10],\n [4.0350e-10, 4.3826e-10, 2.8560e-10]],\n\n ...,\n\n [[5.9854e-10, 8.5526e-10, 8.6965e-10],\n [1.0060e-09, 1.7391e-09, 1.8902e-09],\n [1.0754e-09, 1.2623e-09, 1.3493e-09]],\n\n [[7.7775e-10, 1.2542e-09, 1.4544e-09],\n [1.6041e-09, 2.6058e-09, 3.2078e-09],\n [1.5325e-09, 1.9791e-09, 2.5223e-09]],\n\n [[3.6601e-11, 5.4398e-11, 8.1112e-11],\n [2.7905e-11, 5.2649e-11, 4.4579e-11],\n [1.0252e-11, 1.5208e-11, 2.4394e-11]]],\n\n\n [[[1.1856e-10, 4.0941e-11, 1.3170e-10],\n [4.9797e-11, 2.6412e-11, 3.6393e-11],\n [1.4856e-10, 7.6230e-11, 4.3917e-11]],\n\n [[1.3400e-09, 7.2593e-10, 8.2280e-10],\n [5.1229e-10, 1.2596e-10, 2.5694e-10],\n [1.2256e-09, 1.2596e-09, 3.1915e-10]],\n\n [[3.1877e-10, 6.6477e-10, 5.6688e-10],\n [8.8625e-10, 4.8407e-10, 3.5619e-10],\n [2.9735e-10, 5.2620e-10, 3.6473e-10]],\n\n ...,\n\n [[3.2391e-10, 4.9949e-10, 4.5486e-10],\n [8.4781e-10, 1.1502e-09, 1.4951e-09],\n [1.0429e-09, 1.6524e-09, 1.6123e-09]],\n\n [[4.5391e-10, 5.9156e-10, 6.3218e-10],\n [1.2976e-09, 2.0643e-09, 2.7401e-09],\n [1.6473e-09, 2.8834e-09, 2.5302e-09]],\n\n [[3.1671e-11, 6.7075e-11, 6.8409e-11],\n [2.7292e-11, 3.2964e-11, 2.5286e-11],\n [7.1869e-12, 1.1260e-11, 1.8325e-11]]],\n\n\n ...,\n\n\n [[[2.4260e-11, 2.9399e-11, 1.6431e-11],\n [1.9612e-10, 3.4345e-10, 1.4126e-10],\n [3.7362e-11, 3.8306e-11, 3.9108e-11]],\n\n [[5.4521e-10, 7.9258e-10, 7.5799e-10],\n [8.9593e-10, 9.8692e-10, 1.9284e-09],\n [2.6053e-10, 3.2234e-10, 8.8647e-10]],\n\n [[6.2245e-11, 5.8148e-11, 5.6519e-11],\n [7.4696e-11, 6.1499e-11, 3.8717e-11],\n [3.5224e-11, 3.9971e-11, 2.7346e-11]],\n\n ...,\n\n [[1.0787e-10, 1.7195e-10, 2.0136e-10],\n [1.2622e-10, 1.2896e-09, 3.9696e-10],\n [9.6857e-11, 4.1774e-10, 9.7606e-10]],\n\n [[1.2277e-10, 6.5440e-10, 4.5890e-10],\n [3.5775e-10, 3.8597e-09, 1.5952e-09],\n [2.1416e-10, 7.8450e-10, 1.7102e-09]],\n\n [[2.0160e-10, 1.9129e-10, 2.1767e-10],\n [5.9332e-11, 1.0335e-10, 4.3422e-11],\n [2.2507e-11, 5.0754e-12, 8.1045e-12]]],\n\n\n [[[1.1819e-11, 2.7449e-11, 1.9989e-11],\n [2.3436e-10, 3.9357e-10, 2.4744e-10],\n [3.5813e-11, 2.8283e-11, 1.9487e-11]],\n\n [[1.4263e-09, 9.2872e-10, 1.2108e-09],\n [1.4827e-09, 1.2481e-09, 1.6364e-09],\n [5.4776e-10, 4.1214e-10, 6.7669e-10]],\n\n [[1.7276e-10, 1.3870e-10, 1.0288e-10],\n [6.5320e-11, 4.7314e-11, 3.6047e-11],\n [4.8663e-11, 3.8140e-11, 2.8857e-11]],\n\n ...,\n\n [[2.6369e-10, 2.9289e-10, 2.8749e-10],\n [1.7773e-10, 2.6165e-10, 1.8068e-10],\n [1.8514e-10, 2.4077e-10, 3.4684e-10]],\n\n [[4.5417e-10, 5.2327e-10, 5.2400e-10],\n [6.3468e-10, 1.1278e-09, 8.9404e-10],\n [4.6917e-10, 7.4358e-10, 8.6421e-10]],\n\n [[4.1001e-11, 6.0130e-11, 4.5201e-11],\n [5.1366e-11, 6.0448e-11, 3.3307e-11],\n [7.8188e-12, 1.4270e-11, 1.9777e-11]]],\n\n\n [[[7.3812e-11, 3.2786e-11, 3.2458e-11],\n [5.0481e-11, 4.0477e-11, 2.7444e-11],\n [3.8510e-11, 3.0656e-11, 3.2200e-11]],\n\n [[6.3137e-09, 4.1407e-09, 3.9573e-09],\n [4.9764e-09, 2.2477e-09, 2.5624e-09],\n [2.3433e-09, 1.5571e-09, 2.2671e-09]],\n\n [[1.6635e-10, 1.5084e-10, 1.5315e-10],\n [1.6317e-10, 1.4953e-10, 1.3982e-10],\n [1.6255e-10, 1.4147e-10, 1.4525e-10]],\n\n ...,\n\n [[2.5926e-10, 3.8113e-10, 4.0663e-10],\n [4.1565e-10, 6.8892e-10, 5.2740e-10],\n [4.9636e-10, 6.8419e-10, 5.6535e-10]],\n\n [[3.4061e-10, 5.8558e-10, 6.0136e-10],\n [7.8696e-10, 1.1890e-09, 1.0850e-09],\n [8.8642e-10, 1.1147e-09, 1.0257e-09]],\n\n [[5.7174e-11, 8.6929e-11, 6.0547e-11],\n [8.4782e-11, 1.4090e-10, 6.8345e-11],\n [7.9365e-12, 1.1068e-11, 1.1117e-11]]]])}, 145: {'step': 7160, 'exp_avg': tensor([-5.0775e-05, 2.4947e-05, 3.3028e-06, 1.5396e-05, -2.0856e-05,\n -1.1642e-05, -1.9458e-05, 2.6016e-05, -1.0670e-05, -1.6836e-06,\n 4.7947e-06, -3.8540e-06, 4.5254e-05, -6.7312e-06, -1.2728e-05,\n -3.3386e-05, 1.1063e-05, -2.7051e-06, -8.7464e-06, 9.9705e-06,\n -3.1914e-05, -3.8085e-06, 5.9826e-07, 2.7535e-06, -3.7587e-06,\n -2.9030e-05, 6.8018e-05, -1.0068e-06, 3.1630e-06, 1.1411e-05,\n -5.6145e-06, 3.6233e-05, -4.0641e-08, -5.4373e-06, -7.4293e-06,\n 5.5787e-06, 3.9612e-06, -3.4528e-05, -5.0498e-05, 8.8414e-06,\n -2.5243e-05, 4.3577e-06, 5.8614e-05, -4.2890e-06, -4.1022e-06,\n 5.0234e-06, 4.4107e-06, 3.1976e-06, 1.1575e-05, 1.6159e-05,\n 2.2584e-05, -1.1915e-05, 2.5877e-05, 8.5992e-06, -6.8843e-06,\n -5.8551e-05, 1.8842e-05, 1.1184e-05, -7.3891e-06, 2.1936e-05,\n -8.8309e-06, 3.5720e-05, -7.4849e-06, 7.3157e-05, -1.9458e-05,\n 2.3375e-05, 1.2760e-05, -1.4833e-05, -1.3375e-05, 1.7889e-05,\n 1.8304e-05, 9.6214e-06, -3.1416e-05, 8.2008e-06, -4.3892e-06,\n 5.9943e-06, 8.7010e-06, 3.5229e-05, -9.2837e-06, -2.0462e-05,\n 1.4878e-05, -2.1695e-05, 8.7992e-06, -3.3737e-06, 2.1421e-06,\n -2.3253e-05, 2.7907e-06, -3.2317e-05, 2.4380e-06, 3.0686e-05,\n -1.4115e-05, 1.0978e-05, 9.9408e-06, -7.3334e-05, 3.5576e-05,\n -6.2597e-06, 6.4680e-06, -6.8842e-06, -3.7038e-05, -1.5173e-05,\n 5.5785e-06, 2.5230e-05, 2.3785e-05, 4.7030e-05, 5.3664e-06,\n 1.3408e-05, -1.4511e-05, -2.2865e-06, 1.2689e-06, -7.0295e-07,\n 1.1775e-05, -2.4575e-05, 2.7736e-05, -2.4882e-05, 1.9133e-05,\n 6.5771e-06, 1.2443e-05, 1.5087e-05, 6.9530e-06, 1.4035e-05,\n -1.2400e-05, -1.0098e-05, 4.5388e-06, 1.9369e-05, 1.5025e-05,\n 1.8100e-05, 1.9276e-05, 3.0443e-06, 1.1755e-05, -1.8681e-05,\n 2.4968e-06, 3.2688e-05, -2.8243e-05, -2.5744e-06, 4.6347e-06,\n 6.7154e-05, 2.1375e-05, 7.1652e-06, -1.6485e-05, -1.7505e-05,\n -4.9528e-06, -4.4816e-07, 1.8658e-05, -3.6297e-05, 8.1176e-06,\n 1.9008e-06, 3.3995e-05, -2.2237e-05, -5.3832e-06, 2.6251e-05,\n 1.8868e-06, -1.8400e-04, 7.4516e-06, 1.0448e-06, 2.0156e-05,\n -2.3927e-06, -8.4600e-06, 7.5888e-06, -6.7874e-06, 1.9142e-05,\n 2.3980e-05, -5.7238e-06, 1.0796e-05, 3.4532e-06, 1.1272e-05,\n 1.6156e-06, 1.0283e-05, 3.9947e-05, 1.0903e-05, 1.7807e-05,\n 1.8985e-05, 1.3068e-05, 4.7877e-05, -1.0083e-05, 1.7801e-06,\n 1.3313e-05, -2.3524e-05, 1.2790e-05, -8.7775e-06, 6.4762e-06,\n 2.3612e-06, 8.7713e-07, 2.7283e-06, -1.0425e-05, 6.6174e-06,\n 1.2353e-05, -3.1048e-05, -3.3296e-06, 1.3687e-05, -8.9928e-06,\n -4.6200e-05, -9.0330e-06, -6.9943e-06, 3.1232e-06, -5.3802e-06,\n -6.7309e-06, 4.3673e-05, -3.1215e-06, 1.1719e-05, -3.2242e-05,\n -2.3821e-05, -5.9723e-06, -4.4958e-05, 1.7423e-05, 7.8973e-05,\n 1.2771e-05, 1.4667e-05, 1.6170e-05, 5.9959e-06, 6.4760e-05,\n 3.4152e-06, 5.1349e-05, -4.1930e-05, -1.2464e-05, 2.4819e-06,\n 6.4823e-07, 2.0111e-06, 5.4114e-06, 1.0324e-05, 6.2451e-05,\n 1.6977e-05, 4.9161e-06, 1.1597e-05, -9.4418e-06, 3.8009e-05,\n 1.6713e-05, 2.5730e-05, 3.7756e-05, -8.8122e-06, -9.0191e-07,\n 6.7724e-05, 7.1103e-07, 5.3283e-06, -2.5081e-06, -4.4537e-06,\n -5.7184e-06, -8.1658e-06, 5.2435e-05, 1.2399e-05, -6.6351e-06,\n -2.5056e-06, 2.1755e-05, -3.5151e-06, 7.3222e-06, 6.4440e-07,\n 9.0004e-06, 1.6812e-05, -2.4748e-05, 1.7989e-05, 3.0041e-05,\n -1.6822e-05, 7.0478e-05, 3.7635e-05, 2.0962e-05, -1.7175e-05,\n -2.5116e-06, -9.3189e-06, -1.9212e-06, -9.8356e-06, 1.3277e-05,\n -8.4827e-06, 2.4189e-05, -4.0887e-08, 2.2903e-06, -6.8854e-08,\n 4.1346e-05, -1.9766e-07, -3.5144e-07, 3.6037e-06, -5.9288e-06,\n 1.4316e-06, 3.7199e-05, 5.7440e-06, 3.8643e-06, 2.9360e-05,\n 2.3308e-06, 1.2114e-05, 6.3780e-06, 2.3341e-05, 1.0692e-06,\n -2.6949e-05, 2.6094e-05, 1.2756e-05, 2.1539e-05, -5.8039e-06,\n -5.9018e-05, 5.9736e-06, -1.9060e-06, -1.1855e-05, -7.9529e-06,\n 2.4808e-06, -3.9286e-06, 1.1735e-05, -2.9857e-06, 1.9761e-05,\n 3.3812e-05, 3.6594e-05, -1.6606e-07, -3.6347e-05, 1.5767e-05,\n -1.6426e-06, 8.3108e-06, -5.3924e-06, 1.7406e-05, 1.3966e-05,\n 6.6040e-06, -4.3660e-05, -1.5181e-05, 1.3845e-05, -4.8750e-06,\n -7.9631e-06, 2.4700e-05, 3.6667e-06, 9.6250e-06, 2.1985e-05,\n -1.1476e-04, -6.8554e-05, -1.7407e-06, -1.1149e-04, 1.6235e-05,\n 1.4360e-05, 2.7555e-05, 8.9877e-06, -2.3146e-05, 1.5278e-05,\n -4.7860e-06, 4.0484e-05, 1.4602e-05, 8.7949e-06, 3.5793e-06,\n -5.0334e-06, 5.8075e-07, -1.6830e-05, 4.5974e-05, 9.1463e-06,\n 1.1354e-05, -8.1609e-06, 3.6056e-06, 5.0259e-06, -2.6757e-06,\n 3.0475e-05, -6.5764e-05, 3.6317e-05, 3.6782e-05, -1.8030e-05,\n 2.2152e-05, 1.1341e-05, 5.7735e-06, -5.3673e-05, -2.4439e-05,\n -2.4135e-05, 1.5972e-06, 1.5099e-05, -5.2450e-06, -1.3488e-05,\n 3.1978e-06, 2.3057e-05, 4.0017e-06, 1.5253e-05, 3.3573e-05,\n 5.4705e-05, 2.8350e-06, -3.1398e-06, 2.4308e-05, -1.4931e-06,\n -1.2424e-04, 2.6986e-05, -3.9509e-06, -9.0153e-06, -9.7122e-06,\n 2.1623e-05, -2.6094e-06, -3.1701e-05, 2.6134e-05, -4.3459e-08,\n 1.1808e-05, -1.3184e-05, 4.0848e-05, -6.2417e-06, 7.5366e-05,\n -8.8944e-06, 1.3229e-05, 2.1224e-05, 3.4367e-06, -1.9271e-06,\n -4.5374e-05, 3.1139e-05, -1.1482e-05, 3.3394e-06, -3.5248e-05,\n 3.2933e-05, 2.1802e-05, -1.6406e-05, 7.8643e-06, -1.8904e-06,\n -2.3172e-05, 2.1301e-07, 2.2522e-05, 4.1595e-06, 2.2357e-05,\n 1.5490e-05, -3.3089e-06, 7.5293e-06, -3.6687e-06, 2.5512e-05,\n 7.2488e-06, 1.0905e-05, 2.3544e-05, -1.1290e-05, 1.2334e-05,\n 6.0194e-05, 9.6136e-06, -1.5755e-06, 1.8948e-04, 2.8664e-05,\n -5.9064e-06, 2.7010e-06, -3.1386e-06, -1.1231e-05, 1.1615e-05,\n -2.5108e-05, -1.3654e-06, -2.9611e-06, -7.0581e-06, 6.3668e-06,\n 2.0175e-05, -1.3271e-05, 1.2162e-05, 1.6324e-05, -1.1362e-05,\n -2.9117e-05, -3.3579e-08, 2.2494e-05, 5.0758e-06, 2.8144e-05,\n -1.7802e-05, -3.2827e-06, -1.8123e-06, 4.6433e-06, 7.6535e-06,\n -1.8515e-06, 8.4803e-06, -1.8473e-05, -1.7242e-05, 2.0911e-06,\n -5.6964e-05, 9.5823e-06, 9.0699e-06, -5.6503e-05, 3.1374e-06,\n 6.7904e-06, -7.0513e-06, -7.2851e-06, 2.4694e-06, 2.3747e-07,\n -9.6701e-06, -6.1981e-06, -4.5440e-05, -1.4099e-05, 5.1845e-06,\n -8.4885e-06, 1.7255e-05, -1.5485e-06, 1.3889e-06, 4.1507e-06,\n -6.6470e-06, -1.2578e-06, 5.3702e-06, -3.4355e-06, -5.9274e-05,\n -3.4886e-06, -1.3874e-06, 7.2523e-06, 1.1497e-05, -7.8538e-06,\n 3.3364e-05, -8.5921e-05, -7.4276e-10, 8.8399e-06, 2.9059e-06,\n 1.5060e-05, -2.5358e-06, -2.0607e-05, 1.6326e-05, 4.0399e-05,\n 5.8299e-06, 1.3475e-05, -6.4332e-06, -2.0863e-05, -1.0098e-05,\n 3.7214e-06, -2.6811e-05, 2.0561e-05, 1.0807e-05, 1.6031e-05,\n 2.2192e-06, -9.8507e-06, 2.1072e-06, 3.1908e-05, 7.0388e-06,\n 2.0345e-05, -2.3218e-06, -6.5499e-06, -4.3921e-06, -1.4981e-05,\n 2.3255e-05, 1.3436e-05, 3.3672e-07, 5.7874e-06, 2.3108e-05,\n -2.6592e-05, -2.0312e-06]), 'exp_avg_sq': tensor([1.1924e-06, 1.1637e-07, 5.4897e-08, 1.7930e-08, 1.0573e-06, 2.3286e-07,\n 1.2544e-07, 1.4779e-07, 1.5932e-08, 8.8364e-09, 2.4678e-08, 1.9921e-08,\n 2.8647e-07, 7.7846e-08, 2.5309e-08, 2.8163e-07, 3.2106e-08, 2.0222e-08,\n 1.2690e-08, 5.2273e-08, 3.0410e-07, 5.0822e-08, 2.8407e-07, 1.1783e-07,\n 1.0786e-08, 1.2963e-07, 2.8648e-07, 3.3161e-08, 5.8876e-08, 2.0814e-08,\n 8.4210e-09, 1.3690e-07, 5.8532e-09, 5.8576e-08, 3.6449e-09, 2.0258e-07,\n 6.2431e-08, 3.9425e-07, 6.7616e-07, 1.2837e-07, 2.2233e-07, 2.1297e-08,\n 3.0134e-07, 6.4101e-08, 5.4748e-07, 1.3424e-08, 4.7849e-07, 3.1337e-08,\n 3.0990e-07, 4.9074e-08, 6.9014e-08, 2.1396e-08, 1.7739e-07, 2.6309e-08,\n 1.5043e-08, 1.0589e-06, 9.0654e-08, 5.9231e-07, 2.5233e-08, 1.1827e-07,\n 9.9683e-08, 3.6564e-07, 7.5428e-08, 5.2974e-07, 2.3740e-07, 8.8518e-08,\n 1.8160e-07, 3.1075e-08, 1.0708e-07, 6.3397e-08, 2.9999e-08, 2.9231e-08,\n 3.4689e-08, 9.3853e-09, 1.8522e-08, 8.0239e-09, 8.4802e-08, 9.1514e-08,\n 4.0831e-08, 1.6068e-08, 5.2466e-08, 8.4288e-08, 5.4942e-08, 1.6745e-07,\n 3.5548e-07, 3.3244e-08, 2.2378e-08, 5.8515e-08, 9.6430e-09, 5.4489e-07,\n 1.4532e-07, 2.4340e-08, 1.9600e-08, 8.2496e-07, 2.5208e-07, 1.9374e-08,\n 1.1305e-08, 2.4604e-08, 3.5950e-07, 1.6013e-06, 1.1955e-06, 9.0988e-08,\n 4.1242e-07, 1.3344e-07, 1.0034e-07, 3.7981e-08, 3.5757e-08, 1.8421e-08,\n 2.1498e-07, 2.0528e-08, 6.8053e-08, 2.4862e-07, 5.1265e-08, 2.0492e-07,\n 9.6354e-09, 5.0149e-08, 4.6987e-08, 2.7665e-07, 4.2843e-08, 4.1530e-08,\n 5.5247e-08, 3.6066e-08, 1.7698e-08, 6.5284e-08, 8.6162e-08, 1.0191e-08,\n 3.3981e-08, 4.0917e-08, 6.3002e-08, 7.8134e-08, 9.9144e-09, 1.7792e-07,\n 6.5431e-07, 6.1701e-08, 5.4870e-08, 1.6942e-07, 1.3778e-07, 1.9139e-08,\n 8.7760e-08, 1.9405e-08, 5.5329e-08, 1.2242e-09, 5.1337e-08, 3.1985e-08,\n 1.8772e-09, 1.2362e-08, 3.1716e-08, 8.9755e-08, 6.7611e-09, 1.3750e-07,\n 9.5100e-09, 1.7763e-06, 7.3195e-09, 7.3712e-08, 1.3891e-07, 2.8730e-08,\n 1.9457e-08, 4.2522e-08, 3.6819e-08, 2.2779e-08, 3.1348e-07, 3.0810e-09,\n 5.4682e-08, 4.1907e-08, 3.9578e-08, 7.0021e-08, 3.2321e-08, 2.0067e-07,\n 1.5681e-08, 6.2477e-07, 1.8843e-07, 6.5854e-08, 1.9314e-07, 1.1195e-07,\n 3.0574e-08, 5.6648e-08, 5.2634e-08, 3.0572e-07, 5.3214e-08, 3.1455e-08,\n 3.2619e-07, 1.9628e-08, 4.2349e-08, 5.3945e-07, 3.5562e-09, 1.8743e-08,\n 1.2196e-07, 2.6332e-08, 4.6831e-08, 5.5448e-07, 3.8018e-07, 1.5456e-07,\n 5.8050e-08, 1.1009e-08, 3.5972e-08, 2.6894e-08, 1.6512e-07, 3.9533e-08,\n 2.4282e-08, 7.2800e-08, 1.0244e-07, 1.0439e-08, 4.1443e-07, 1.1149e-07,\n 2.9096e-07, 4.7537e-08, 1.3370e-08, 6.7873e-08, 1.3352e-07, 4.4911e-07,\n 3.7276e-09, 2.7645e-07, 5.7522e-07, 2.1094e-07, 2.0744e-07, 1.1241e-08,\n 1.1727e-07, 3.3054e-07, 1.0358e-07, 1.2920e-07, 3.0854e-08, 1.9094e-08,\n 4.1262e-08, 7.4880e-08, 3.0518e-07, 2.7277e-08, 1.1333e-06, 1.0565e-06,\n 2.5620e-08, 1.7855e-08, 6.8449e-07, 5.4288e-09, 2.9809e-08, 2.9353e-07,\n 1.3525e-07, 2.3823e-07, 7.2603e-07, 1.2057e-07, 1.2728e-07, 1.3612e-08,\n 2.5018e-08, 2.4375e-08, 3.2237e-08, 8.2286e-08, 4.3373e-08, 2.0213e-08,\n 1.0698e-07, 1.7025e-07, 6.6067e-09, 3.7916e-08, 5.7095e-08, 5.3512e-07,\n 1.5480e-07, 5.4461e-08, 3.4968e-08, 1.1039e-08, 3.2894e-08, 1.5022e-08,\n 5.2119e-08, 1.5706e-08, 6.2287e-09, 2.1008e-07, 5.5991e-08, 1.3931e-07,\n 2.3184e-08, 4.1514e-08, 3.3183e-08, 1.3723e-07, 4.2040e-07, 3.9280e-08,\n 3.1262e-09, 3.0779e-06, 9.6369e-09, 1.0710e-07, 2.0952e-07, 5.4985e-07,\n 3.0598e-08, 2.4002e-08, 4.1742e-08, 2.8026e-07, 2.6273e-07, 9.3187e-08,\n 1.2317e-07, 8.5208e-08, 1.5908e-08, 1.8177e-07, 1.4811e-07, 3.2893e-08,\n 3.0381e-07, 5.1134e-08, 9.4118e-08, 4.1650e-07, 1.8674e-08, 2.0698e-08,\n 4.8880e-08, 1.4098e-07, 9.9945e-08, 1.1409e-08, 2.1888e-07, 3.4706e-08,\n 6.8138e-08, 2.9092e-08, 1.2781e-08, 1.3241e-07, 1.6370e-08, 5.0233e-08,\n 3.6101e-07, 3.1505e-07, 2.1048e-08, 5.4377e-08, 5.0078e-08, 2.2980e-07,\n 2.2063e-08, 1.4546e-07, 5.5002e-08, 6.9575e-07, 6.3143e-07, 1.5599e-09,\n 6.7899e-07, 2.3459e-07, 3.2550e-08, 1.3797e-08, 1.9635e-07, 1.3738e-07,\n 8.0771e-08, 2.0111e-08, 7.8448e-07, 2.0482e-08, 6.3208e-08, 3.4465e-08,\n 4.7081e-08, 6.0907e-09, 1.2885e-07, 1.1486e-06, 3.1561e-08, 2.0536e-08,\n 2.6109e-07, 3.1305e-08, 4.2668e-08, 2.3684e-08, 7.7014e-08, 1.2128e-06,\n 8.3106e-08, 7.6608e-08, 8.1171e-08, 2.2333e-08, 1.2843e-08, 1.8260e-08,\n 9.1716e-07, 1.3978e-07, 1.7577e-07, 7.0558e-08, 2.8012e-08, 5.2873e-08,\n 1.6856e-07, 4.6323e-08, 1.6551e-07, 3.0922e-08, 1.9195e-08, 5.4410e-08,\n 1.9511e-07, 2.1164e-07, 2.6524e-08, 1.0108e-06, 2.5668e-08, 2.4796e-06,\n 4.2931e-08, 3.1863e-08, 9.1158e-09, 1.4178e-07, 3.8461e-08, 2.1182e-08,\n 5.0504e-08, 9.7542e-08, 6.4123e-09, 1.4099e-08, 1.1699e-07, 1.2616e-07,\n 4.6574e-08, 2.3157e-07, 2.3994e-07, 1.1497e-08, 9.6115e-08, 1.4870e-08,\n 2.7796e-08, 7.8543e-08, 2.3912e-07, 1.3049e-07, 4.7947e-08, 7.6483e-08,\n 1.6855e-07, 4.5324e-08, 1.1699e-07, 1.5219e-08, 3.0944e-09, 2.1364e-08,\n 5.5357e-09, 4.0234e-08, 4.9472e-07, 1.5198e-07, 1.4371e-07, 7.7616e-09,\n 1.8031e-07, 1.0118e-08, 1.2196e-07, 4.7351e-09, 3.9064e-08, 4.1433e-07,\n 1.6931e-07, 4.9224e-09, 2.4767e-07, 2.6684e-07, 8.1176e-08, 2.8928e-06,\n 7.0858e-08, 1.7805e-08, 1.6949e-08, 1.2253e-07, 9.5248e-09, 2.7387e-07,\n 1.1783e-07, 2.0590e-08, 1.0249e-09, 8.2950e-08, 1.6236e-08, 5.7894e-08,\n 9.7719e-08, 1.5494e-08, 6.1793e-08, 5.1277e-08, 8.5464e-08, 5.4109e-08,\n 2.1217e-08, 2.1785e-07, 1.6481e-07, 1.2951e-07, 4.2345e-08, 6.0027e-07,\n 4.4696e-08, 5.5890e-08, 4.2869e-09, 2.7861e-08, 5.1040e-07, 5.6168e-08,\n 7.6150e-09, 5.4753e-08, 8.9560e-08, 2.9250e-08, 3.0249e-07, 3.1175e-08,\n 5.4882e-08, 1.4311e-07, 1.1866e-08, 1.9373e-09, 2.3226e-08, 6.7949e-09,\n 2.8171e-09, 3.6574e-07, 6.2560e-08, 1.5317e-08, 2.1958e-08, 1.1218e-07,\n 4.8801e-08, 6.3666e-08, 2.1924e-07, 1.6802e-07, 1.8664e-08, 1.9655e-07,\n 8.9620e-09, 9.0290e-07, 3.2971e-09, 8.3109e-09, 8.7876e-08, 1.4655e-07,\n 9.2130e-08, 2.2131e-07, 3.2782e-07, 3.2083e-09, 6.5992e-08, 4.5722e-08,\n 3.4066e-08, 4.2266e-08, 1.4821e-08, 1.4955e-07, 3.2687e-08, 5.1917e-08,\n 4.0607e-08, 8.4781e-09, 1.5688e-06, 5.1767e-07, 5.8603e-09, 1.1166e-07,\n 1.3113e-08, 3.6262e-08, 8.1496e-08, 3.4566e-08, 1.8103e-08, 2.1046e-08,\n 4.9434e-08, 6.8876e-08, 8.8644e-07, 8.6060e-08, 9.2637e-09, 7.9671e-08,\n 1.2907e-08, 1.6187e-07, 1.8637e-08, 1.3417e-07, 2.1970e-07, 6.6690e-08,\n 1.2032e-07, 1.2392e-07])}, 146: {'step': 7160, 'exp_avg': tensor([-7.9016e-05, 4.5539e-05, 1.7577e-05, 1.6997e-05, 1.5004e-05,\n -4.2423e-05, -1.4879e-06, 3.7478e-05, -8.6654e-06, 6.1869e-07,\n 6.0552e-06, -2.6529e-06, 1.2402e-05, 2.0266e-06, -1.0644e-05,\n -2.9668e-05, 2.1523e-06, -1.7558e-06, -8.0180e-06, 1.3970e-05,\n -3.7564e-05, -1.8405e-06, 6.4920e-06, 9.2059e-07, -4.7535e-06,\n -3.9931e-05, 6.7851e-05, -7.0807e-06, 1.3297e-05, 8.6143e-06,\n -1.5743e-05, 5.8128e-05, -2.5990e-06, -6.0361e-06, -4.8360e-06,\n -2.3163e-05, 1.8544e-05, 1.2491e-06, -2.4599e-06, -8.0140e-07,\n -1.6207e-05, 6.8853e-06, 5.8901e-05, 1.2164e-05, 9.8174e-05,\n 6.9717e-06, 1.4401e-04, 5.0865e-06, 8.3554e-05, 9.2932e-06,\n 3.1528e-05, 1.5904e-06, 2.6526e-05, 5.3448e-06, -5.0442e-06,\n -6.3596e-05, 2.6010e-05, 6.8480e-05, -2.4422e-06, 1.6139e-05,\n -3.0425e-06, 1.6359e-05, -6.7577e-06, 4.1845e-05, 4.9710e-05,\n 1.2199e-05, 1.6243e-06, -9.5570e-06, -4.3883e-06, 4.7122e-05,\n 1.4237e-05, 1.0422e-05, -1.4703e-05, 6.5195e-06, 8.5766e-06,\n 2.5105e-06, 1.6493e-05, 4.8040e-05, -4.0887e-06, -1.6698e-05,\n 1.3756e-05, 4.0294e-06, 1.3037e-06, 4.2783e-05, -8.0896e-06,\n -1.7595e-05, 3.5368e-07, -2.0686e-05, 3.0586e-06, -9.2533e-06,\n -7.1025e-06, 7.9966e-06, 9.8843e-06, -9.4208e-05, 7.5804e-06,\n -4.6689e-06, 4.9595e-06, -2.9530e-07, -2.8711e-05, -3.7977e-05,\n -7.4011e-06, 2.6251e-05, 1.0964e-04, 5.9529e-05, 4.7733e-05,\n 7.5808e-06, 3.0035e-05, -4.0242e-06, -9.0793e-06, 1.0608e-05,\n 1.7807e-05, -3.9784e-05, 2.0895e-05, 3.4589e-05, 1.5233e-05,\n 2.0624e-05, 7.5272e-06, -3.8450e-05, 7.3207e-06, 5.5226e-06,\n -9.4400e-06, -7.4240e-06, 6.0343e-06, 7.8843e-06, 1.7846e-06,\n 1.2109e-05, 1.3499e-05, -9.1249e-06, 9.7126e-06, -1.3310e-05,\n 3.5304e-06, 2.5121e-05, -2.1733e-05, -4.3562e-07, -1.8360e-06,\n 2.9725e-05, 2.8984e-05, 1.5506e-06, -1.4946e-05, -2.1446e-05,\n -6.4741e-06, -5.7627e-07, 1.8765e-05, -3.2457e-05, 7.1753e-06,\n 8.2780e-06, 2.9487e-05, -1.4317e-05, -5.4963e-06, 4.8476e-05,\n 1.0010e-06, -1.3353e-04, 7.6622e-06, -8.3435e-06, 2.9809e-05,\n 9.4978e-07, -8.9473e-06, 4.8922e-06, -6.9286e-06, 1.4978e-05,\n 1.2445e-04, -4.5853e-06, 4.2016e-06, 1.4322e-06, 2.2847e-05,\n 4.3437e-06, -2.3729e-06, 6.3910e-05, 1.1704e-05, 3.3835e-05,\n 2.7052e-05, 9.8026e-06, -2.2796e-05, 2.6876e-05, 8.6693e-06,\n 7.1547e-06, -2.1291e-05, 4.0064e-05, -5.3681e-06, 2.0015e-06,\n -6.0159e-06, 1.5611e-06, 2.1864e-06, 1.6193e-05, 8.0686e-06,\n 1.3230e-05, -3.2416e-05, 1.9513e-06, 9.2471e-06, 1.3437e-05,\n -3.1405e-05, 6.1381e-05, 1.3242e-05, 3.8660e-06, -5.9455e-06,\n -5.0110e-06, 6.0659e-05, -2.1254e-06, 1.6897e-05, -2.3934e-05,\n -3.5724e-05, -5.9058e-06, -1.8093e-05, 5.0341e-05, 9.4378e-05,\n 9.7740e-07, 9.1984e-06, 5.5184e-05, 4.4242e-06, 7.2312e-05,\n 2.5422e-06, 2.5505e-05, -2.0843e-05, -5.0434e-06, 2.5356e-05,\n -1.8259e-07, 3.2637e-05, 6.0465e-05, 3.8312e-05, 3.5143e-05,\n 4.5592e-06, 2.1628e-05, 2.6529e-06, -3.1495e-06, 5.9271e-05,\n 1.0822e-05, 1.9026e-05, 7.5289e-05, -6.1082e-06, -2.0166e-06,\n 9.5486e-05, 3.1365e-06, 2.3418e-06, -2.4137e-05, 1.3857e-05,\n -5.7597e-06, 3.2612e-05, 6.8245e-05, 3.3840e-05, -4.3084e-06,\n 3.1263e-06, 1.9673e-05, -3.8277e-08, 1.0812e-05, 1.8524e-06,\n 9.4765e-06, 1.0999e-05, -2.0166e-05, 1.4258e-05, 2.7934e-05,\n -3.0093e-07, 3.4167e-05, 4.2118e-05, 2.0596e-05, 2.5487e-05,\n 6.5012e-07, -2.3609e-05, -3.5094e-06, -1.0024e-05, 9.6322e-06,\n -8.8533e-06, 6.6676e-05, 1.4560e-05, 2.0445e-05, 1.0548e-05,\n 3.6841e-05, -6.8506e-06, -1.0879e-05, -4.9633e-05, 7.9751e-06,\n 5.8935e-07, -1.6613e-06, 5.4774e-06, 6.0730e-06, 4.0644e-05,\n -2.7331e-05, 6.9129e-06, 1.0971e-05, 4.2897e-05, -1.0082e-05,\n -5.1235e-05, 9.6146e-06, 3.3487e-06, 3.5684e-05, -6.5926e-06,\n -4.4049e-05, 2.5323e-05, 6.5029e-07, -5.5216e-07, -9.6072e-07,\n 4.8541e-06, -5.3956e-06, 7.0274e-06, -5.5659e-07, 1.2593e-05,\n 2.6408e-05, 8.0513e-05, 2.7494e-07, -2.0261e-05, 1.7237e-05,\n -1.5344e-06, 1.9986e-06, 3.4063e-06, 5.7000e-05, 1.7959e-05,\n 1.0197e-05, 2.5676e-05, 7.8270e-06, 1.5523e-05, -1.9732e-06,\n -6.3137e-06, 1.8705e-05, -3.9921e-06, 1.6667e-05, 1.8203e-05,\n -2.1477e-05, -4.3951e-05, -2.6167e-06, -5.1173e-05, 1.7989e-05,\n 1.1127e-05, 1.9882e-05, 2.5829e-05, 1.6088e-05, 1.6068e-05,\n 1.2481e-06, 2.9779e-05, 1.0562e-05, 9.2451e-06, 9.4506e-06,\n -7.8094e-06, 7.7662e-07, -1.5931e-05, 1.9461e-04, 1.4679e-05,\n 7.5239e-06, -8.1399e-06, 5.5741e-06, 7.6431e-06, -2.5345e-05,\n 3.7799e-05, -1.2873e-04, 6.6207e-05, 5.9326e-05, -1.8242e-05,\n 2.1651e-05, 9.0244e-06, 1.4107e-05, -2.4675e-05, -3.6385e-05,\n -3.0248e-06, 8.9959e-08, 8.1913e-06, -4.4528e-07, 5.5562e-05,\n 1.2448e-05, -2.9831e-06, 5.3016e-07, 8.1643e-06, 2.5291e-05,\n 8.0630e-05, -3.6126e-05, -5.6741e-06, -5.5427e-05, -5.0799e-06,\n -8.7498e-05, 1.6577e-05, -5.4667e-06, -4.4241e-06, -4.7343e-05,\n 2.3558e-05, 1.7656e-06, -1.9697e-05, 2.3578e-05, 5.4703e-07,\n 9.8889e-06, 1.8509e-05, 2.9101e-05, -4.8030e-06, 4.6157e-05,\n -2.0571e-06, 4.3874e-06, 2.2855e-05, 2.6937e-06, -6.8486e-06,\n -6.0353e-05, 4.0970e-05, 1.8577e-06, 5.0801e-05, -3.1649e-05,\n 1.4867e-05, 2.0167e-05, -2.2512e-05, 9.5526e-06, -1.3450e-06,\n -2.4406e-05, 2.6432e-06, 1.4631e-05, 2.8792e-05, 4.4878e-05,\n 4.8068e-05, -6.4116e-06, 1.3437e-05, -2.3345e-06, 3.1865e-05,\n 5.1127e-06, 1.7767e-05, 6.1682e-06, 8.3166e-06, 9.9375e-06,\n 7.1483e-05, 7.8832e-05, 7.3976e-06, 3.6441e-06, 1.9355e-05,\n -6.4889e-06, 3.8522e-06, 1.1051e-05, -7.4197e-06, 2.0830e-05,\n -3.1810e-05, 4.3175e-06, -3.3285e-06, -4.3849e-06, 3.2032e-06,\n 2.7594e-05, -2.5492e-05, 7.2664e-06, 2.5228e-05, 7.6127e-07,\n -7.0047e-05, 5.3920e-06, 2.4123e-05, 1.0008e-05, 2.4530e-06,\n -1.1420e-05, -8.3162e-06, 1.5881e-05, 1.2181e-05, 9.9816e-06,\n -1.1248e-06, 8.1841e-06, -4.5550e-06, -2.4858e-05, 9.4704e-07,\n -4.7897e-05, -1.0663e-05, -1.5198e-05, -5.6703e-05, 3.4704e-06,\n 3.3735e-05, 9.2678e-06, -8.2291e-06, 3.0419e-06, 3.9828e-07,\n -9.8786e-06, -7.6113e-06, -2.8882e-05, -1.7308e-05, 2.8386e-06,\n -1.6494e-05, 6.5422e-05, 7.0542e-06, 9.8749e-07, 2.0509e-05,\n -4.6927e-06, -1.0360e-06, 3.2289e-05, -1.0820e-05, -2.0895e-05,\n -1.6146e-06, -1.0670e-06, 1.2517e-05, -3.3464e-06, -1.5344e-06,\n 3.9568e-05, -3.9436e-05, -8.5325e-07, 1.1112e-05, 8.3733e-07,\n 1.9833e-06, -2.4991e-06, -1.6017e-05, 1.3593e-05, 3.1986e-05,\n 1.7036e-05, 4.6416e-06, -5.3551e-06, 5.3074e-05, -3.3381e-06,\n 5.0458e-06, 3.3982e-05, 9.7705e-06, 1.7172e-05, 1.2105e-05,\n 8.5110e-06, -9.2812e-06, 9.6883e-07, 3.1407e-05, 3.9796e-06,\n -4.3622e-05, -3.1656e-07, -1.2903e-05, 1.5158e-06, -1.2858e-05,\n 3.8111e-06, 1.2301e-05, 1.4070e-05, 3.3804e-06, 3.3700e-05,\n -1.0926e-05, -1.0340e-05]), 'exp_avg_sq': tensor([3.9886e-07, 1.3770e-07, 1.3391e-07, 2.6431e-08, 5.2795e-07, 2.3757e-07,\n 8.8070e-08, 8.1533e-08, 1.8538e-08, 6.6042e-09, 1.7482e-08, 8.4955e-09,\n 8.8033e-08, 9.3068e-08, 1.1805e-08, 1.8115e-07, 5.4693e-09, 2.2876e-08,\n 1.0379e-08, 1.7714e-08, 1.6709e-07, 3.2549e-08, 3.1163e-07, 6.6496e-08,\n 7.4784e-09, 1.4035e-07, 3.9635e-07, 2.0606e-08, 1.0924e-07, 1.1281e-08,\n 1.0069e-08, 1.7864e-07, 4.5755e-09, 4.4407e-08, 2.0431e-09, 1.5602e-07,\n 7.3052e-08, 2.1408e-07, 4.5300e-07, 5.9690e-08, 1.0056e-07, 1.7246e-08,\n 3.6295e-07, 1.5461e-07, 9.9003e-07, 2.6416e-08, 1.4957e-06, 1.9838e-08,\n 6.5408e-07, 2.7415e-08, 1.4593e-07, 2.7086e-08, 1.8077e-07, 1.0952e-08,\n 1.4945e-08, 7.1682e-07, 7.3807e-08, 5.9443e-07, 1.4059e-08, 7.2385e-08,\n 4.4410e-08, 2.0748e-07, 1.1950e-08, 2.7839e-07, 4.0166e-07, 9.6109e-09,\n 8.9812e-08, 2.0409e-08, 1.0606e-07, 1.2024e-07, 2.0445e-08, 1.5319e-08,\n 1.5533e-08, 3.4711e-09, 1.8655e-08, 1.5269e-09, 7.1370e-08, 1.1671e-07,\n 4.5838e-08, 1.6711e-08, 4.0623e-08, 8.4557e-08, 7.7845e-09, 3.9178e-07,\n 1.2823e-07, 2.3822e-08, 3.7251e-09, 4.0661e-08, 7.7444e-09, 2.4135e-07,\n 1.5279e-07, 1.6592e-08, 1.9196e-08, 3.9430e-07, 2.6327e-08, 1.4296e-08,\n 9.4472e-09, 3.7635e-08, 1.4573e-07, 7.1300e-07, 4.1745e-07, 1.4613e-07,\n 9.2879e-07, 5.1079e-07, 2.7048e-07, 5.3554e-08, 7.4875e-08, 1.0074e-08,\n 9.1320e-08, 4.6622e-08, 4.2179e-08, 2.0191e-07, 4.1305e-08, 2.8152e-07,\n 7.3896e-09, 6.6345e-08, 3.7838e-08, 1.5163e-07, 3.1793e-08, 2.1989e-08,\n 2.8298e-08, 4.8654e-08, 1.0513e-08, 3.7750e-08, 2.7966e-08, 1.2006e-08,\n 1.7098e-08, 2.6413e-08, 3.4141e-08, 3.3767e-08, 9.5699e-09, 1.2293e-07,\n 4.6312e-07, 1.4943e-07, 2.2912e-08, 4.0540e-08, 8.2806e-08, 7.4608e-09,\n 1.4132e-07, 2.4383e-08, 2.1028e-08, 8.7235e-10, 2.9030e-08, 2.1864e-08,\n 1.0648e-09, 1.5344e-08, 3.5980e-08, 7.6752e-08, 7.4507e-09, 2.4343e-07,\n 1.7548e-09, 1.0421e-06, 7.2962e-09, 4.1181e-08, 2.0118e-07, 1.5680e-08,\n 9.2917e-09, 4.7133e-08, 3.8694e-08, 1.1821e-08, 6.9060e-07, 1.0263e-09,\n 4.4318e-08, 5.6810e-09, 5.0510e-08, 5.9754e-08, 2.7711e-08, 2.2181e-07,\n 1.6770e-08, 8.7791e-07, 1.6906e-07, 1.2175e-07, 6.6595e-08, 2.3742e-07,\n 5.3797e-08, 5.6216e-08, 5.1069e-08, 3.6602e-07, 5.6477e-08, 2.8737e-08,\n 1.5406e-07, 2.2222e-08, 2.0338e-08, 4.7260e-07, 3.9533e-09, 1.7246e-08,\n 9.4660e-08, 2.3232e-08, 4.7308e-08, 3.5145e-07, 2.3298e-07, 1.7184e-07,\n 8.1847e-08, 1.1754e-08, 1.4200e-08, 1.7001e-08, 1.3008e-07, 1.4592e-08,\n 2.5267e-08, 5.7453e-08, 9.6764e-08, 1.1117e-08, 2.3129e-07, 2.0408e-07,\n 2.8126e-07, 9.3204e-09, 1.0884e-08, 1.2011e-07, 7.6569e-08, 2.9149e-07,\n 1.6726e-09, 1.0547e-07, 3.0490e-07, 7.8865e-08, 3.1421e-07, 5.9741e-09,\n 2.5047e-07, 4.7473e-07, 2.6898e-07, 8.4907e-08, 2.6328e-08, 3.2013e-08,\n 1.1570e-08, 3.7968e-08, 2.4920e-07, 8.5597e-09, 7.0693e-07, 7.3770e-07,\n 9.0046e-09, 1.3589e-08, 5.5785e-07, 3.3958e-09, 3.2419e-08, 1.4621e-07,\n 1.7016e-07, 1.3655e-07, 8.5002e-07, 3.1804e-07, 1.7690e-07, 1.4518e-08,\n 2.3358e-08, 3.1003e-08, 1.9083e-08, 5.2136e-08, 8.0011e-08, 1.4257e-08,\n 8.4467e-08, 7.3179e-08, 6.1630e-09, 3.6078e-08, 7.1707e-08, 1.8668e-07,\n 8.9101e-08, 6.6237e-08, 5.3047e-08, 6.7060e-09, 3.2276e-08, 1.3133e-08,\n 3.8508e-08, 3.0914e-08, 6.2332e-09, 4.6109e-07, 1.4316e-07, 1.3105e-07,\n 4.2388e-08, 4.1599e-08, 4.4483e-08, 5.6657e-08, 2.2307e-07, 4.6852e-08,\n 3.0459e-09, 1.1188e-06, 6.2889e-09, 6.5160e-08, 1.6522e-07, 2.3887e-07,\n 2.0303e-08, 5.5078e-08, 7.7406e-08, 1.4040e-07, 1.9553e-07, 3.8605e-08,\n 5.6569e-08, 1.0875e-07, 1.4941e-08, 7.8230e-08, 1.4272e-07, 1.8608e-08,\n 8.2747e-08, 2.5988e-08, 4.5524e-08, 1.3563e-07, 6.6167e-09, 1.3209e-08,\n 3.0689e-08, 1.2821e-07, 1.7470e-07, 6.1377e-09, 2.0527e-07, 3.3072e-08,\n 2.0323e-08, 3.7174e-09, 2.1020e-08, 2.3725e-07, 2.4701e-08, 5.1395e-08,\n 7.0227e-07, 3.1355e-07, 1.9965e-08, 5.6853e-08, 3.1431e-08, 1.8031e-07,\n 1.1318e-08, 1.6474e-07, 6.6813e-08, 2.0612e-07, 3.4833e-07, 2.0347e-09,\n 4.7723e-07, 1.7847e-07, 2.4912e-08, 1.0173e-08, 2.3582e-07, 3.3078e-07,\n 1.3954e-07, 2.9917e-08, 3.2757e-07, 1.0252e-08, 1.8426e-08, 7.2140e-08,\n 4.4206e-08, 4.8344e-09, 9.7630e-08, 1.3518e-06, 3.8482e-08, 1.5033e-08,\n 1.0437e-07, 3.0527e-08, 2.8102e-08, 3.9600e-08, 1.2930e-07, 1.5682e-06,\n 1.9017e-07, 1.5274e-07, 8.9093e-08, 2.5657e-08, 9.4712e-09, 1.7792e-08,\n 3.0784e-07, 1.4886e-07, 2.0010e-07, 1.9832e-08, 1.3296e-08, 4.3025e-08,\n 4.0020e-07, 4.7364e-08, 5.2887e-08, 1.9887e-08, 1.2806e-08, 7.9132e-08,\n 4.2223e-07, 1.7910e-07, 3.7320e-08, 2.7262e-07, 3.5116e-08, 7.8078e-07,\n 6.5388e-08, 1.1591e-08, 5.4800e-09, 1.6644e-07, 5.2234e-08, 2.5177e-08,\n 2.4672e-08, 5.4221e-08, 7.1152e-09, 7.2582e-09, 1.1155e-07, 1.2016e-07,\n 3.6611e-08, 1.2666e-07, 9.3669e-08, 5.5092e-09, 1.0878e-07, 7.2179e-09,\n 1.3025e-08, 1.0247e-07, 2.6927e-07, 7.6734e-08, 1.2844e-07, 9.0431e-08,\n 2.1835e-07, 2.1604e-08, 7.6099e-08, 2.2286e-08, 2.8639e-09, 1.9770e-08,\n 3.8193e-09, 3.3507e-08, 1.1890e-07, 2.0381e-07, 2.6010e-07, 4.2903e-09,\n 2.0668e-07, 1.0679e-08, 1.3419e-07, 2.8192e-09, 7.4934e-08, 1.9323e-07,\n 3.9255e-08, 3.3420e-09, 3.1362e-07, 7.6358e-07, 9.2881e-08, 5.6044e-07,\n 4.6696e-08, 1.1757e-08, 1.1351e-08, 1.4589e-07, 1.1256e-08, 1.4378e-07,\n 6.4486e-08, 3.6290e-08, 1.0133e-09, 4.7954e-08, 2.1877e-08, 5.0599e-08,\n 9.4501e-08, 1.0711e-08, 1.2591e-07, 5.9697e-08, 7.5270e-08, 8.6730e-08,\n 2.6570e-08, 9.5646e-08, 6.4084e-08, 2.3691e-08, 5.1888e-08, 4.7867e-07,\n 5.5746e-08, 5.4057e-08, 2.6392e-09, 2.6835e-08, 3.7478e-07, 2.5743e-08,\n 7.0361e-09, 4.9997e-08, 7.6366e-08, 3.3787e-08, 2.1125e-07, 3.9605e-08,\n 8.8350e-08, 2.3782e-07, 1.3092e-08, 1.5573e-09, 2.8787e-08, 5.9651e-09,\n 2.6978e-09, 2.3686e-07, 5.5020e-08, 7.9736e-09, 1.3314e-08, 3.9155e-07,\n 4.1887e-08, 4.1774e-08, 2.9781e-07, 1.1099e-07, 2.1869e-08, 2.2567e-07,\n 6.9649e-09, 1.4765e-07, 3.0854e-09, 9.3026e-09, 6.3291e-08, 1.2177e-07,\n 1.0668e-07, 1.2008e-07, 1.7116e-07, 1.6952e-09, 6.4871e-08, 6.9392e-09,\n 1.2045e-08, 2.9269e-08, 1.3180e-08, 2.2437e-08, 3.1565e-08, 7.5125e-08,\n 5.2991e-09, 6.9293e-09, 9.9548e-07, 2.7747e-07, 5.5705e-09, 4.0104e-07,\n 4.0504e-09, 4.7666e-08, 4.1220e-08, 6.6642e-08, 1.7280e-08, 9.7230e-09,\n 3.7741e-08, 3.5609e-08, 5.1736e-07, 1.2100e-07, 9.3164e-09, 7.1360e-08,\n 1.4208e-08, 1.8999e-08, 1.4972e-08, 1.5396e-07, 1.0500e-07, 1.0973e-07,\n 4.5292e-08, 1.0194e-07])}, 147: {'step': 7160, 'exp_avg': tensor([[[[-1.4168e-07]],\n\n [[ 4.4336e-09]],\n\n [[-2.5305e-07]],\n\n ...,\n\n [[ 8.8254e-07]],\n\n [[-3.1649e-08]],\n\n [[ 9.3973e-07]]],\n\n\n [[[-2.9279e-06]],\n\n [[-8.0247e-07]],\n\n [[-2.4643e-07]],\n\n ...,\n\n [[ 1.7886e-06]],\n\n [[ 8.6347e-08]],\n\n [[-4.7676e-07]]],\n\n\n [[[-2.7569e-07]],\n\n [[ 3.4088e-07]],\n\n [[ 2.5685e-07]],\n\n ...,\n\n [[-6.0250e-09]],\n\n [[-8.8897e-07]],\n\n [[ 2.3473e-07]]],\n\n\n ...,\n\n\n [[[ 1.8653e-06]],\n\n [[-4.1195e-07]],\n\n [[-3.7798e-07]],\n\n ...,\n\n [[-1.7032e-06]],\n\n [[-2.9122e-06]],\n\n [[ 1.0511e-06]]],\n\n\n [[[ 7.1815e-07]],\n\n [[-2.5752e-09]],\n\n [[-5.8145e-08]],\n\n ...,\n\n [[-4.4037e-07]],\n\n [[-3.7789e-07]],\n\n [[ 3.6859e-07]]],\n\n\n [[[ 1.7455e-06]],\n\n [[ 1.6912e-07]],\n\n [[-2.8787e-07]],\n\n ...,\n\n [[ 7.3962e-07]],\n\n [[ 4.6201e-07]],\n\n [[ 6.5469e-07]]]]), 'exp_avg_sq': tensor([[[[3.4276e-11]],\n\n [[6.3393e-11]],\n\n [[2.2972e-11]],\n\n ...,\n\n [[5.3977e-11]],\n\n [[3.7165e-11]],\n\n [[5.3517e-11]]],\n\n\n [[[3.9311e-10]],\n\n [[1.3322e-10]],\n\n [[5.9441e-11]],\n\n ...,\n\n [[3.5021e-10]],\n\n [[2.9550e-10]],\n\n [[4.8399e-10]]],\n\n\n [[[2.6576e-11]],\n\n [[2.9941e-11]],\n\n [[1.0608e-11]],\n\n ...,\n\n [[3.0483e-11]],\n\n [[1.3872e-10]],\n\n [[6.2393e-11]]],\n\n\n ...,\n\n\n [[[1.2446e-10]],\n\n [[5.2853e-10]],\n\n [[1.2323e-10]],\n\n ...,\n\n [[1.1816e-10]],\n\n [[6.0858e-10]],\n\n [[9.9406e-10]]],\n\n\n [[[2.4854e-11]],\n\n [[2.7316e-10]],\n\n [[6.3827e-11]],\n\n ...,\n\n [[1.9902e-11]],\n\n [[9.7451e-11]],\n\n [[3.1341e-10]]],\n\n\n [[[4.4463e-10]],\n\n [[1.0004e-10]],\n\n [[3.9535e-11]],\n\n ...,\n\n [[8.7434e-11]],\n\n [[5.4213e-11]],\n\n [[1.5843e-10]]]])}, 148: {'step': 7160, 'exp_avg': tensor([ 1.7584e-06, -3.0838e-07, 7.4208e-07, ..., -3.0743e-06,\n -8.2183e-07, 2.8554e-06]), 'exp_avg_sq': tensor([5.2123e-10, 2.2926e-10, 1.5086e-10, ..., 1.5193e-09, 3.0092e-10,\n 5.9476e-10])}, 149: {'step': 7160, 'exp_avg': tensor([ 1.3374e-06, -1.9467e-06, -5.0880e-08, ..., 7.0950e-06,\n 7.2246e-07, -1.3674e-06]), 'exp_avg_sq': tensor([3.1066e-10, 7.5724e-10, 9.2760e-11, ..., 1.4941e-09, 1.0383e-10,\n 3.4771e-10])}, 150: {'step': 7160, 'exp_avg': tensor([[[[-7.3455e-07]],\n\n [[-6.1575e-08]],\n\n [[-8.3441e-07]],\n\n ...,\n\n [[-1.2405e-06]],\n\n [[ 1.5342e-07]],\n\n [[-3.4155e-07]]],\n\n\n [[[-1.7472e-08]],\n\n [[-1.4719e-08]],\n\n [[ 3.6876e-08]],\n\n ...,\n\n [[ 1.1773e-10]],\n\n [[-1.1951e-08]],\n\n [[-2.8532e-08]]],\n\n\n [[[-5.2754e-07]],\n\n [[-2.6780e-06]],\n\n [[-1.1884e-06]],\n\n ...,\n\n [[-2.5237e-07]],\n\n [[-1.8299e-07]],\n\n [[-8.4194e-07]]],\n\n\n ...,\n\n\n [[[-9.1434e-07]],\n\n [[-1.6541e-07]],\n\n [[-8.7870e-07]],\n\n ...,\n\n [[-1.0032e-06]],\n\n [[-1.9990e-07]],\n\n [[-2.8437e-07]]],\n\n\n [[[-3.7970e-07]],\n\n [[ 1.3135e-07]],\n\n [[-1.5843e-07]],\n\n ...,\n\n [[-4.1793e-07]],\n\n [[ 3.4246e-08]],\n\n [[-1.8426e-08]]],\n\n\n [[[-1.2349e-07]],\n\n [[ 2.3630e-07]],\n\n [[-9.2761e-08]],\n\n ...,\n\n [[-1.6665e-07]],\n\n [[-4.8866e-08]],\n\n [[ 2.2065e-07]]]]), 'exp_avg_sq': tensor([[[[7.9685e-11]],\n\n [[1.3013e-10]],\n\n [[4.2822e-11]],\n\n ...,\n\n [[2.0107e-10]],\n\n [[3.8268e-10]],\n\n [[2.4022e-10]]],\n\n\n [[[5.2465e-12]],\n\n [[3.7735e-11]],\n\n [[1.1295e-11]],\n\n ...,\n\n [[1.7174e-12]],\n\n [[2.4816e-11]],\n\n [[4.6573e-11]]],\n\n\n [[[8.7285e-10]],\n\n [[2.1666e-09]],\n\n [[4.4526e-10]],\n\n ...,\n\n [[1.3138e-10]],\n\n [[8.5149e-11]],\n\n [[1.0217e-09]]],\n\n\n ...,\n\n\n [[[6.7360e-11]],\n\n [[4.8647e-11]],\n\n [[4.4548e-11]],\n\n ...,\n\n [[1.1375e-10]],\n\n [[7.6677e-11]],\n\n [[1.1585e-10]]],\n\n\n [[[1.3499e-11]],\n\n [[6.4757e-12]],\n\n [[1.4336e-11]],\n\n ...,\n\n [[5.8821e-11]],\n\n [[3.7259e-11]],\n\n [[4.9016e-11]]],\n\n\n [[[1.0560e-11]],\n\n [[4.4519e-12]],\n\n [[3.9503e-12]],\n\n ...,\n\n [[1.1929e-11]],\n\n [[1.2189e-11]],\n\n [[1.0218e-11]]]])}, 151: {'step': 7160, 'exp_avg': tensor([ 1.8164e-05, -4.6315e-07, -1.0042e-05, 3.4480e-07, 1.0724e-05,\n -2.4702e-07, 1.5614e-05, 2.4016e-06, -2.4970e-06, -2.0356e-05,\n 1.0767e-05, 3.2482e-06, -6.6914e-06, -2.3569e-05, -1.4178e-05,\n -1.2313e-05, 1.7779e-04, -3.1015e-06, -6.4718e-06, -1.6589e-06,\n 6.1027e-05, 1.7645e-06, -1.1644e-06, -2.6705e-06, 5.2466e-06,\n 6.4666e-06, 1.3173e-06, 1.4039e-06, -7.1054e-06, -3.9620e-05,\n -8.5631e-06, -7.9587e-07, -3.3599e-06, -2.1468e-08, 6.6037e-06,\n -6.1933e-06, 4.9655e-05, -1.5425e-06, 2.3509e-06, 8.9088e-06,\n 7.2162e-06, -4.9951e-06, 5.6105e-06, -2.0090e-05, 4.0658e-06,\n -2.2056e-05, -1.1193e-06, 5.6796e-05, 5.0450e-07, -2.9264e-05,\n 1.0894e-05, 2.6475e-05, -3.3121e-06, 6.3171e-07, 1.3014e-05,\n 7.9794e-06, -4.1832e-06, -8.5156e-07, -2.4248e-06, 4.4284e-05,\n 1.5492e-05, -4.5204e-06, 1.6983e-05, 5.2459e-05, 4.4495e-05,\n -1.4724e-06, 1.5690e-04, -3.2273e-05, 4.1404e-05, 5.8157e-06,\n -6.9127e-07, -2.2158e-05, 8.6396e-05, -1.0675e-05, -6.1167e-06,\n -2.5635e-06, 2.0078e-05, 1.8817e-05, -5.4359e-07, 9.7958e-06,\n -4.8450e-06, 1.3565e-05, 3.9545e-05, 4.5355e-05, 3.5496e-06,\n -1.6425e-05, -6.2893e-05, -4.0046e-05, 2.6987e-05, 4.0755e-06,\n -1.1947e-05, -1.4819e-05, -6.5671e-06, 2.8673e-06, 1.5514e-05,\n -1.5264e-06, -2.3867e-06, -4.0235e-06, -1.7302e-06, -1.9737e-05,\n -2.1605e-05, 1.4333e-05, 2.1806e-07, -7.9823e-06, 4.0407e-06,\n 1.5382e-05, 1.1836e-05, -1.2032e-05, -4.5054e-06, -2.6015e-05,\n -5.6380e-06, -8.5513e-06, 2.6158e-06, 1.2034e-05, 2.3225e-06,\n 1.5518e-05, 7.1854e-06, -1.5900e-05, -2.1511e-05, 1.4150e-06,\n 5.2429e-06, 2.6281e-05, -3.6685e-06, -2.9828e-05, -2.0477e-05,\n 3.5680e-05, -1.3003e-05, 2.1271e-05, -1.5245e-06, -5.6367e-06,\n 2.4596e-05, 6.9575e-06, -2.4029e-05, -4.9372e-07, -3.0109e-05,\n -1.0349e-05, -2.5737e-05, -1.9916e-06, 3.9728e-07, 2.9600e-05,\n 7.7106e-06, 1.6397e-05, -3.8166e-07, 1.6570e-05, -2.9528e-06,\n -1.5858e-05, -4.3200e-06, 3.3689e-06, -1.6300e-05, 2.3984e-06,\n 3.0740e-06, -2.0792e-05, 3.0428e-05, -1.8487e-05, -8.8340e-07,\n -1.9966e-05, -3.9913e-06, -9.9667e-06, -1.8830e-06, -1.7716e-05,\n -1.2870e-06, 9.5396e-05, -3.5166e-05, 3.8226e-06, -1.0923e-05,\n 1.6561e-07, 3.1365e-05, 2.3552e-08, 5.2727e-06, 3.0772e-06,\n 1.1996e-06, 1.3898e-05, 1.0677e-05, 4.8696e-06, -2.7220e-07,\n 2.2535e-05, -3.1438e-05, -1.3845e-05, -1.1087e-05, 1.3382e-05,\n -7.7569e-06, 1.4039e-05, -6.6474e-06, -1.8555e-05, -2.7214e-06,\n -1.5874e-05, -7.3923e-06, 6.1361e-06, -5.4595e-06, 7.3157e-06,\n 3.7851e-06, 2.6881e-05, 1.9714e-05, 3.8819e-06, -6.9805e-07,\n 1.8357e-05, 8.5554e-07, -1.4349e-05, -1.0506e-05, 1.7396e-05,\n -1.7896e-05, 1.5805e-05, -4.4466e-06, -5.3952e-06, 4.9709e-05,\n -2.5146e-06, -8.4306e-06, -1.6425e-06, -1.8622e-05, 2.1031e-06,\n 2.8609e-05, 1.2005e-05, -1.9125e-06, -7.6484e-06, 3.6795e-06,\n -3.2600e-06, 1.4101e-05, 6.5802e-06, -2.5095e-05, 1.1202e-06,\n 3.5120e-07, 2.9872e-05, 2.0298e-05, 5.4304e-05, 5.4052e-06,\n 1.7757e-06, -1.3936e-05, 1.7126e-06, -1.1600e-05, 1.3842e-05,\n 2.3266e-05, -1.9672e-06, -6.2704e-06, -1.3626e-06, 1.9096e-05,\n -5.9517e-08, -5.6747e-06, -7.3267e-06, -3.2848e-05, 1.7360e-05,\n -1.2700e-05, 4.5093e-06, 9.4904e-06, 4.3573e-06, -2.5553e-06,\n 1.5145e-05, -1.6082e-06, -2.3785e-06, 1.0850e-05, -4.2492e-06,\n 2.1868e-05, -3.7608e-08, 4.9905e-05, -1.1473e-05, -2.4441e-06,\n -1.1259e-05, -3.0373e-05, 3.8865e-08, 1.9609e-08, -5.6934e-07,\n -1.4180e-06, 4.3000e-06, -6.0958e-07, 1.8962e-05, 5.7575e-06,\n 7.2667e-06, 1.5585e-05, -3.8427e-06, 7.2903e-05, 1.2648e-05,\n 1.1886e-06, -1.0340e-04, -3.3225e-05, -8.6465e-06, 1.2987e-05,\n 8.9464e-06, 5.6461e-05, 3.4440e-05, 6.2728e-06, -4.9599e-06,\n -1.7946e-05, -3.3600e-06, -1.2726e-05, 2.0919e-05, -2.5108e-05,\n -8.9108e-06, -1.5004e-05, -4.5188e-06, -6.0702e-06, 1.1379e-05,\n -4.8756e-06, -1.7272e-05, -7.6734e-06, 7.9560e-06, 9.9482e-06,\n -4.9175e-06, 3.1739e-06, 5.2021e-06, -2.6247e-05, -1.6850e-05,\n 1.0950e-05, -1.8698e-05, 8.1299e-05, 3.4058e-06, 1.8229e-07,\n -3.3856e-05, 1.1332e-06, -2.8179e-05, -5.2470e-06, 2.1319e-05,\n 1.1386e-04, -1.2188e-05, 9.7639e-06, -2.0809e-05, 2.3902e-05,\n 5.0695e-06, 8.1389e-06, 2.6187e-06, -6.4819e-05, 2.8709e-07,\n 7.7403e-07, 3.2405e-08, 1.0381e-05, 5.3382e-05, 7.4735e-06,\n -2.5901e-05, 4.0507e-05, -8.7659e-07, 3.6166e-06, -3.8416e-05,\n -1.2951e-05, 3.6100e-06, 1.3782e-05, -2.2861e-06, 9.5160e-07,\n -2.5037e-05, 2.4599e-06, 2.2295e-05, -7.9969e-06, 4.5267e-05,\n -5.7924e-06, 9.5348e-07, -2.3492e-05, -3.0863e-05, 3.1061e-06,\n -5.8183e-06, 1.3151e-04, 2.2704e-06, 1.4532e-05, 4.2279e-06,\n 3.8854e-05, 7.7942e-06, 2.4816e-05, 1.9185e-06, 1.6283e-05,\n -3.7256e-06, -6.3892e-06, 1.3226e-05, 3.8002e-07, 3.5224e-06,\n 1.5498e-05, 2.5730e-05, 1.0837e-05, 4.7268e-06, -6.5646e-07,\n 2.4646e-05, -5.9960e-06, -6.6401e-06, 2.6404e-06, -8.9645e-06,\n 5.3258e-05, -9.0343e-06, 1.0140e-04, 2.7428e-05, 1.3557e-05,\n -6.2697e-05, 1.0440e-06, -6.3261e-07, -5.2767e-05, 1.0950e-05,\n 6.9285e-09, 1.4518e-06, -6.8408e-07, 9.5738e-06, 8.8125e-06,\n 1.4724e-04, 8.1135e-06, -3.2895e-05, 1.0215e-05, -3.2641e-05,\n -6.5776e-06, 2.0318e-06, -3.4978e-06, -3.1063e-05, 2.5155e-05,\n 5.6762e-05, -3.4526e-06, 7.5670e-06, -4.4401e-06, -2.4205e-06,\n 5.7851e-07, 1.0168e-05, 2.3162e-05, -1.0390e-05, 3.3747e-06,\n -5.1666e-06, -9.2337e-07, -1.2893e-05, 1.1246e-05, -7.6708e-07,\n -1.1217e-05, -4.8184e-06, -1.2342e-05, 3.3700e-05, 3.3035e-05,\n 9.9321e-06, -2.4744e-05, -5.8721e-07, -3.3991e-06, -2.2263e-06,\n 1.3809e-04, 8.2333e-06, 2.2074e-06, -1.8353e-05, 1.0326e-05,\n -2.8741e-05, 1.1613e-05, 1.7872e-05, -1.5462e-06, 1.4158e-04,\n 2.7396e-05, 7.0892e-06, -7.1128e-06, -1.3704e-06, -4.0891e-06,\n 1.4079e-05, 1.0931e-06, 4.1791e-05, 1.3348e-05, -3.1526e-05,\n -1.3677e-06, 4.0667e-05, 9.1589e-06, -4.7837e-06, 1.4480e-05,\n -1.4579e-05, -1.4780e-06, -1.7060e-06, -1.3870e-06, 2.5113e-05,\n -2.8940e-07, -1.3893e-05, 4.6139e-05, 1.9520e-05, 1.0311e-05,\n -3.5407e-06, 7.5182e-06, -5.6770e-06, -2.9436e-06, -5.1892e-06,\n -1.8320e-05, -8.2305e-07, -6.8465e-06, -4.9301e-06, -8.7026e-06,\n 1.3871e-05, -7.9751e-05, -1.7082e-05, -3.8634e-07, -1.0422e-05,\n -2.2373e-06, 8.4856e-08, 3.4115e-05, -2.4301e-05, -3.9810e-06,\n 2.5883e-05, 1.5178e-05, 1.0063e-05, 1.1114e-05, 6.6293e-07,\n 5.2040e-07, -7.4249e-06, 1.7715e-05, -3.0553e-06, -5.2040e-06,\n 7.2660e-08, -1.1593e-05, 7.9734e-05, -2.3163e-06, 1.4735e-06,\n -1.7396e-05, -8.4962e-06, -2.5556e-05, -8.1809e-07, -1.2453e-05,\n -3.8617e-05, -8.8133e-07, -3.9904e-07, -1.8788e-06, -1.8550e-05,\n -9.8708e-06, 2.8132e-06, -4.0419e-05, -1.8119e-05, -9.5099e-06,\n -5.0211e-06, 2.4009e-05, 1.4402e-05, 4.2768e-07, 1.5629e-05,\n -1.2388e-05, -3.2380e-06]), 'exp_avg_sq': tensor([1.0189e-07, 2.7992e-08, 1.9270e-07, 2.1279e-09, 6.5586e-08, 1.7488e-09,\n 1.0990e-08, 3.1780e-09, 1.5633e-08, 2.5080e-07, 8.2706e-08, 7.9478e-09,\n 9.9447e-09, 1.7131e-07, 5.5715e-08, 7.7213e-09, 1.5489e-06, 1.0048e-08,\n 1.1802e-07, 2.0002e-09, 5.2958e-07, 1.5522e-08, 3.0083e-08, 1.0149e-08,\n 6.4271e-08, 2.4070e-08, 1.5145e-07, 1.0471e-08, 1.7077e-08, 3.8411e-08,\n 1.1046e-07, 5.8684e-09, 1.7982e-08, 1.8610e-07, 2.6635e-08, 1.2245e-08,\n 1.1614e-07, 1.2298e-08, 9.4787e-09, 6.0831e-08, 1.1710e-08, 2.2084e-08,\n 5.0052e-08, 2.6410e-07, 1.5493e-09, 2.7270e-07, 1.0780e-07, 3.3631e-07,\n 4.3362e-10, 7.8824e-08, 1.7585e-08, 2.8894e-08, 1.5138e-08, 9.5657e-10,\n 7.4425e-08, 6.7325e-08, 9.5286e-08, 6.5435e-09, 8.3940e-08, 9.5804e-07,\n 2.7276e-07, 1.4900e-08, 7.4265e-08, 9.9629e-08, 3.1229e-07, 3.3920e-08,\n 8.2861e-07, 1.0447e-06, 3.3664e-07, 1.7316e-07, 7.5510e-09, 1.0679e-07,\n 2.4029e-07, 8.1438e-09, 7.5290e-08, 6.4148e-09, 1.0336e-07, 3.4082e-08,\n 3.8940e-08, 2.2034e-08, 5.8367e-08, 2.0766e-07, 5.2899e-08, 1.8084e-07,\n 3.8389e-08, 1.0325e-07, 1.7325e-06, 2.9553e-07, 3.5485e-07, 1.8392e-09,\n 2.6228e-07, 3.4462e-08, 1.1332e-08, 2.7649e-09, 1.8223e-08, 1.1057e-08,\n 1.4122e-08, 7.5427e-09, 5.0913e-09, 3.6052e-08, 5.5592e-08, 1.0003e-07,\n 5.3710e-10, 3.0622e-08, 2.5468e-07, 2.3147e-08, 6.2555e-08, 1.1827e-07,\n 3.6741e-08, 1.0589e-07, 3.9265e-08, 3.9436e-08, 2.8989e-09, 3.1287e-08,\n 4.4922e-09, 6.1750e-08, 2.2324e-08, 3.5992e-08, 1.3423e-07, 1.4484e-07,\n 3.7632e-09, 1.6950e-07, 1.4848e-08, 3.1969e-08, 3.6480e-08, 2.8812e-07,\n 6.8596e-08, 3.7528e-08, 1.5150e-08, 6.4744e-08, 2.9638e-08, 2.9098e-08,\n 4.6002e-07, 5.9950e-08, 2.2277e-07, 8.7890e-08, 6.3810e-08, 5.8677e-09,\n 6.1763e-10, 1.3049e-07, 4.4603e-08, 8.2342e-08, 2.6215e-08, 7.4610e-08,\n 9.4825e-09, 6.7882e-08, 2.3994e-08, 9.9243e-08, 5.4188e-08, 1.4370e-09,\n 6.8854e-09, 5.8555e-07, 1.6787e-07, 3.3098e-07, 9.0691e-08, 4.3098e-07,\n 1.0185e-08, 2.2114e-08, 2.0020e-08, 2.7540e-07, 1.5011e-09, 4.1088e-07,\n 1.3060e-07, 1.3977e-08, 6.1659e-09, 6.3877e-09, 7.3753e-08, 1.8333e-08,\n 1.8244e-07, 2.8575e-09, 2.3163e-07, 1.2492e-08, 3.3893e-08, 6.0590e-08,\n 4.2010e-10, 1.0719e-07, 2.1188e-07, 2.0735e-07, 1.7508e-08, 5.2025e-08,\n 2.1334e-07, 9.3603e-09, 3.8921e-08, 2.8805e-07, 8.5601e-09, 1.2313e-07,\n 5.8792e-09, 7.2162e-09, 1.4490e-08, 1.2382e-08, 4.1699e-07, 3.4333e-07,\n 7.3419e-08, 5.0750e-08, 1.6973e-08, 8.0495e-08, 7.6341e-09, 3.6009e-08,\n 5.3743e-09, 6.2050e-07, 1.4029e-08, 8.0908e-09, 7.7348e-08, 2.3108e-08,\n 1.2169e-07, 3.0419e-10, 9.2276e-09, 1.8922e-08, 4.7232e-08, 1.3176e-09,\n 7.5291e-08, 3.6981e-08, 2.0474e-09, 3.6892e-08, 1.2138e-08, 4.3019e-08,\n 2.6151e-08, 4.4122e-09, 2.7490e-08, 4.3105e-08, 2.1521e-08, 3.9702e-07,\n 7.5449e-08, 1.6537e-07, 6.1593e-08, 1.8911e-08, 2.3708e-08, 8.8952e-09,\n 1.9526e-07, 8.2652e-09, 3.5840e-07, 6.5478e-10, 1.1440e-08, 1.7093e-08,\n 5.3049e-08, 1.3537e-09, 1.9103e-08, 6.4301e-09, 3.5528e-08, 6.7415e-07,\n 4.6934e-08, 7.3022e-09, 8.4209e-08, 1.3529e-09, 1.6373e-08, 8.3751e-09,\n 8.6222e-09, 1.1496e-07, 3.7537e-08, 1.6005e-08, 7.3978e-08, 5.6911e-11,\n 1.5822e-07, 2.0676e-08, 2.7316e-08, 7.8524e-09, 1.6608e-06, 1.8961e-10,\n 5.0787e-09, 4.5650e-09, 1.3885e-08, 4.7866e-08, 1.1556e-09, 3.5051e-08,\n 1.0170e-08, 1.5600e-08, 1.8568e-07, 3.0479e-09, 2.4750e-07, 1.5694e-08,\n 1.1163e-08, 7.5344e-07, 3.0417e-08, 2.7984e-08, 4.3042e-08, 6.5367e-09,\n 5.9646e-07, 1.6571e-07, 6.5831e-08, 1.7532e-08, 1.6612e-07, 4.9252e-08,\n 3.3078e-08, 2.3399e-08, 4.4071e-08, 2.2866e-08, 3.7746e-07, 1.5654e-08,\n 2.9152e-09, 5.0991e-08, 2.7609e-08, 2.4781e-08, 4.6135e-09, 4.0584e-09,\n 2.0160e-08, 5.2656e-08, 2.1259e-08, 3.2443e-08, 2.0315e-07, 1.0494e-07,\n 2.0292e-07, 6.1732e-08, 5.2956e-07, 1.1695e-07, 1.5549e-08, 1.0828e-06,\n 7.9698e-08, 9.9877e-08, 1.4019e-08, 4.3532e-08, 4.9470e-07, 3.8171e-08,\n 3.1243e-07, 3.0138e-08, 8.0505e-07, 1.0034e-08, 1.7971e-07, 4.5693e-09,\n 2.3723e-06, 1.0147e-08, 4.0867e-10, 1.9910e-08, 1.0314e-07, 2.1295e-07,\n 2.9586e-07, 2.9483e-08, 9.3678e-08, 1.2335e-09, 2.8780e-09, 4.9827e-08,\n 1.3824e-08, 3.0912e-08, 3.4686e-08, 3.8069e-09, 5.3158e-10, 5.1434e-07,\n 4.2799e-07, 3.0830e-08, 2.3917e-07, 7.2237e-07, 1.1711e-08, 3.1379e-08,\n 1.8708e-07, 4.0082e-08, 5.0564e-09, 1.5031e-07, 9.7777e-07, 2.6921e-08,\n 6.6671e-08, 1.8902e-07, 1.2873e-07, 3.4927e-07, 4.3977e-08, 1.5161e-08,\n 1.2334e-07, 1.1023e-07, 3.1768e-08, 1.5539e-08, 5.7437e-10, 3.3855e-08,\n 1.1329e-07, 1.5255e-07, 1.3578e-08, 1.2258e-07, 1.8858e-09, 7.4062e-07,\n 5.0952e-09, 9.3670e-08, 7.4680e-07, 9.0336e-09, 1.8313e-06, 1.4520e-08,\n 3.8240e-07, 1.0815e-07, 5.8243e-08, 1.3493e-07, 1.2741e-09, 4.1987e-09,\n 6.7077e-07, 1.9065e-07, 3.1474e-10, 9.6120e-09, 2.6368e-08, 2.6095e-08,\n 2.2879e-08, 1.4988e-06, 4.5630e-08, 6.7191e-08, 1.9691e-07, 3.6392e-08,\n 6.5977e-09, 3.9978e-09, 1.3295e-07, 2.8446e-07, 1.1133e-07, 3.3189e-07,\n 3.7406e-08, 4.4698e-08, 8.0769e-09, 3.2977e-08, 6.1010e-08, 8.4327e-08,\n 9.7696e-08, 9.8636e-09, 4.3689e-09, 7.5301e-08, 1.3875e-08, 4.4486e-08,\n 6.1581e-08, 5.1178e-10, 2.7053e-07, 5.5110e-09, 2.3392e-08, 2.1308e-07,\n 9.3857e-08, 1.4191e-07, 7.1992e-07, 3.5176e-09, 8.9964e-09, 1.6983e-08,\n 1.0824e-06, 9.2051e-08, 1.0329e-07, 5.0557e-08, 1.0962e-08, 1.8163e-07,\n 1.3012e-07, 3.7454e-08, 6.4831e-10, 1.6823e-06, 1.1111e-07, 6.1143e-07,\n 1.3650e-08, 4.8673e-09, 1.0707e-08, 1.0600e-07, 1.9307e-07, 1.0407e-07,\n 4.4564e-09, 2.7453e-08, 4.7057e-10, 7.9501e-08, 3.1554e-08, 9.1292e-08,\n 2.0373e-07, 8.5966e-08, 4.3332e-09, 5.7667e-09, 4.8503e-08, 2.5535e-07,\n 4.1057e-08, 4.6088e-08, 4.1372e-07, 1.3499e-07, 2.6748e-08, 2.0680e-08,\n 8.0582e-09, 5.4972e-08, 4.0216e-09, 8.0360e-09, 3.1777e-08, 2.8267e-08,\n 5.0003e-08, 7.0333e-09, 7.4230e-09, 3.0225e-08, 1.8745e-07, 5.9409e-08,\n 1.1348e-09, 6.6020e-08, 3.5980e-08, 7.7320e-09, 3.5243e-08, 3.6148e-08,\n 1.8509e-09, 4.9913e-08, 9.9200e-08, 7.5401e-09, 1.0679e-07, 9.7685e-09,\n 2.2843e-07, 1.1145e-08, 5.0834e-08, 4.7591e-09, 5.1939e-09, 9.7423e-10,\n 1.4258e-07, 6.6612e-06, 4.1135e-08, 5.7094e-08, 1.9434e-07, 1.7772e-08,\n 3.2306e-07, 6.6233e-10, 1.5541e-08, 5.5640e-07, 3.8823e-10, 9.5116e-10,\n 2.0203e-09, 6.0241e-08, 2.8362e-08, 1.3598e-08, 8.0524e-08, 4.8916e-08,\n 5.7695e-08, 9.4705e-09, 1.0051e-07, 6.4208e-08, 2.4251e-07, 1.8352e-08,\n 2.3048e-08, 4.2786e-09])}, 152: {'step': 7160, 'exp_avg': tensor([ 3.2456e-05, -4.1184e-07, -2.5621e-07, 3.5282e-07, 2.9231e-06,\n -5.7742e-07, 1.1513e-05, 4.7235e-07, 9.4230e-06, -1.0901e-05,\n -4.1331e-09, 2.2100e-06, -3.2036e-06, -1.4494e-05, -1.4114e-05,\n -8.1315e-06, 3.5551e-04, 2.1818e-07, -1.0189e-05, -1.2452e-06,\n 1.4470e-04, 1.7840e-06, -1.9102e-06, 1.9284e-06, -7.0585e-06,\n 1.2937e-05, -1.5113e-06, 4.5264e-06, -5.5034e-06, -3.8304e-05,\n -1.0499e-05, -6.3598e-07, -4.5510e-06, 2.2187e-05, 1.0705e-05,\n -6.3610e-06, 6.9614e-05, 1.4650e-06, 2.4695e-06, -8.5312e-06,\n 6.8414e-06, 3.4735e-06, 2.3484e-05, -1.6298e-05, 4.4618e-06,\n -1.0171e-05, 2.5751e-06, 8.7565e-05, 4.7661e-07, -1.7334e-05,\n 8.8723e-06, 2.9262e-05, -7.5740e-06, 5.8246e-07, 2.3873e-05,\n 7.7019e-06, -7.7078e-06, -1.1647e-06, -6.3407e-07, 8.8487e-05,\n -4.6765e-07, -3.3534e-06, 3.3090e-05, 3.5655e-05, 5.5744e-05,\n -8.2079e-07, 2.7405e-04, -6.3057e-06, 7.8694e-05, 4.4854e-06,\n -4.7740e-07, -1.1781e-05, 1.7464e-04, -8.8162e-06, -4.0833e-06,\n -4.0754e-06, 4.2569e-05, 1.1727e-05, 7.0795e-07, 1.6355e-05,\n 1.7702e-05, 3.8554e-05, 4.8314e-05, 5.9090e-05, 1.9222e-05,\n -1.5318e-05, -3.4757e-05, -2.3748e-05, 4.8119e-05, 3.2214e-06,\n 4.7801e-06, -9.5747e-06, -2.8796e-06, 2.5467e-06, 1.4355e-05,\n 2.2629e-07, -2.8093e-06, -2.7290e-06, -1.3736e-06, -2.2068e-05,\n -2.2339e-05, -1.3502e-05, 1.9145e-07, -3.2521e-06, -2.2400e-05,\n 2.3525e-05, 2.0664e-05, -1.1122e-06, -8.0510e-06, -1.8205e-05,\n -2.8169e-06, -6.2965e-06, 2.8390e-06, 2.8799e-05, 3.4545e-06,\n 2.9558e-05, 1.8229e-06, -1.1788e-05, -1.0823e-05, 1.0379e-06,\n 4.7744e-06, 5.0293e-05, -1.0550e-07, -4.6680e-05, -2.1851e-05,\n 6.5530e-05, -1.6765e-05, 2.4484e-05, 1.7693e-06, -4.7261e-06,\n 2.3434e-05, 1.4875e-05, -1.6374e-05, 8.0910e-06, -3.7473e-05,\n -1.1590e-05, -1.7912e-05, -3.5049e-06, 3.0953e-07, 8.3261e-05,\n 2.4698e-05, 2.5636e-05, 5.4231e-06, 3.9530e-05, -2.3405e-06,\n -1.8778e-05, -2.8351e-06, 7.0092e-06, -1.0698e-05, 1.6888e-06,\n 4.1734e-06, -2.2499e-05, 2.6341e-05, -1.5710e-05, -7.7776e-06,\n -2.8179e-05, -7.5306e-07, -5.5196e-06, -1.3751e-06, -2.2875e-06,\n -1.4185e-06, 1.5739e-04, -2.1870e-05, 3.1264e-06, -7.8897e-06,\n 7.4429e-08, 6.0893e-05, -7.6490e-07, -8.5512e-07, 2.9267e-06,\n -2.8075e-07, 1.1152e-05, 1.3031e-05, 1.4288e-05, -2.9876e-07,\n 3.8928e-05, -5.0325e-05, -3.4472e-06, -5.3792e-06, 2.6147e-05,\n -9.2130e-07, 1.0284e-05, -6.5640e-06, -1.5027e-05, -2.0277e-06,\n -2.1055e-05, -4.2172e-06, 1.0092e-05, -5.2390e-06, 8.9344e-06,\n -2.3386e-05, 3.3992e-05, -1.6094e-05, 1.3009e-05, -1.0623e-06,\n 3.0353e-05, 1.9232e-06, -1.1166e-05, -9.9649e-06, 5.1745e-05,\n -1.5232e-05, 1.7480e-05, -3.3835e-06, -4.7161e-06, 1.1308e-04,\n -2.0518e-06, -6.0101e-06, -1.4303e-06, -2.4453e-05, 1.3389e-06,\n 3.2489e-05, 1.3042e-05, -1.5906e-06, -9.1117e-06, -9.8459e-07,\n -6.1340e-06, 1.5659e-05, 5.7926e-06, -1.6950e-05, 3.9248e-06,\n 2.7925e-06, 3.9211e-05, 2.3940e-05, 9.3020e-05, 1.5729e-05,\n -1.2110e-06, -1.4182e-05, 5.3693e-06, 7.7608e-06, 1.4749e-05,\n 8.1665e-05, -1.8781e-06, -7.1492e-06, -2.5688e-06, 3.3981e-05,\n 1.0112e-07, -6.5678e-07, -9.2900e-06, -2.8812e-05, -1.4261e-05,\n -1.9153e-05, 3.9295e-06, 3.1922e-05, 5.1073e-06, -3.2084e-06,\n 1.4328e-05, -1.1509e-06, -2.0699e-06, 2.3482e-05, -3.0977e-07,\n 5.4790e-05, -2.1847e-08, 8.5567e-05, -9.5191e-06, -3.2379e-06,\n -7.1495e-06, -5.1202e-05, 3.9800e-08, 5.0280e-07, 1.4063e-06,\n -9.1004e-07, -1.8919e-06, -4.4119e-07, 1.7258e-05, 1.7793e-05,\n 4.8033e-06, 3.9166e-06, -3.4635e-06, 1.3283e-04, 1.5439e-05,\n 5.5230e-08, -7.3542e-05, -2.8442e-05, -2.2781e-06, 1.7677e-05,\n 1.0440e-05, 1.0936e-04, 1.1053e-04, 2.0519e-05, -4.6722e-06,\n -7.8474e-06, 4.4538e-06, -1.7509e-05, 6.8631e-05, -2.7195e-05,\n -7.5964e-06, -1.1060e-05, -3.0332e-06, -5.1088e-06, -1.4935e-06,\n -9.9586e-07, -1.5282e-05, -4.6798e-06, 5.7045e-06, 5.7747e-06,\n -1.7148e-05, 3.3516e-06, 2.3848e-06, -1.2234e-05, -1.3334e-05,\n 4.1684e-05, -1.9361e-05, 1.9255e-04, 1.9440e-05, 2.3540e-07,\n -1.5776e-05, 2.0200e-05, -3.9834e-05, 1.2288e-06, 2.0442e-05,\n 4.7013e-05, -1.1279e-05, -5.0074e-05, -1.2551e-05, 1.4767e-05,\n 4.6652e-06, 1.3184e-05, 2.8574e-06, -3.8845e-05, 6.5301e-06,\n 6.7436e-07, 3.1407e-07, 3.2805e-06, 9.1129e-05, 2.9132e-06,\n -2.0048e-05, 6.8517e-05, -8.1088e-07, 2.8354e-06, -2.9563e-05,\n -1.0553e-05, 9.7463e-06, 3.0569e-06, -1.5233e-06, 9.7429e-07,\n -3.1900e-05, 2.9988e-05, 2.9409e-05, 2.6574e-06, 2.8120e-04,\n -9.0356e-06, -1.5596e-06, -2.2869e-05, -2.7772e-05, 6.9046e-07,\n 5.6099e-06, 1.5402e-04, 8.2375e-06, 2.4339e-05, 2.4196e-05,\n 2.6802e-05, -1.2475e-05, 1.3567e-05, 2.8229e-06, 2.5274e-05,\n 1.8617e-05, -6.0865e-07, 2.5005e-05, 3.3102e-07, 2.1172e-06,\n 4.8454e-06, 5.4648e-05, 9.2523e-06, 3.2357e-05, -6.2937e-07,\n 4.8578e-05, -6.2689e-06, -1.5133e-06, -3.3595e-05, -7.6145e-06,\n 1.4343e-04, -3.5294e-06, 1.3703e-04, 3.4039e-05, 1.7271e-05,\n -4.9111e-05, 7.6006e-07, 2.7312e-06, -3.8501e-05, 4.4831e-05,\n 8.7566e-09, 1.1900e-06, 5.4684e-06, -5.4468e-07, 1.1934e-05,\n 2.1804e-04, 1.7557e-06, -3.4501e-05, 2.6909e-05, -2.6952e-05,\n -4.1144e-06, 1.7400e-06, 7.7390e-06, 1.2613e-05, 1.5428e-05,\n 1.1806e-04, -1.4765e-06, -9.5399e-06, -3.7145e-06, -2.1865e-06,\n 1.2908e-05, 1.0463e-05, 3.5499e-05, -6.9334e-06, 2.8912e-06,\n 3.8095e-06, 3.1226e-06, -1.2655e-05, -9.9135e-07, -7.6584e-07,\n -4.7562e-06, -3.6812e-06, -3.5236e-06, 5.7479e-05, 4.8948e-05,\n 1.9242e-05, -5.6499e-05, -1.0192e-06, -3.7688e-06, 1.3521e-06,\n 2.3386e-04, 1.9019e-05, -2.1617e-07, -1.3554e-05, 1.0393e-05,\n -4.1247e-05, 7.5575e-06, 3.6270e-05, -1.3755e-06, 2.5916e-04,\n 5.3517e-05, 4.9800e-05, -2.5830e-06, -9.3012e-07, -2.1065e-06,\n 4.2076e-06, 4.9239e-06, 7.0770e-05, 1.4937e-05, -2.5980e-05,\n -1.1830e-06, 5.4411e-05, 8.2851e-06, -2.4463e-06, 6.3429e-06,\n -9.4914e-06, -1.4602e-06, -1.7263e-06, -6.9416e-06, 2.8573e-05,\n 1.0280e-05, -9.9007e-06, -8.1282e-06, 8.6743e-06, 2.0469e-05,\n -2.4790e-06, 6.7245e-06, -1.2094e-05, -3.3276e-06, -3.8650e-06,\n -1.0835e-05, -6.6685e-07, 6.9307e-06, -3.8945e-06, -5.3316e-06,\n 1.2730e-05, -4.9331e-05, -3.6041e-05, -3.8493e-07, -4.6961e-06,\n 8.5960e-06, 7.2582e-06, 3.0673e-05, -1.8023e-05, -4.4342e-06,\n 4.4992e-05, 3.4752e-05, 1.0757e-05, 8.0710e-06, 4.2062e-07,\n -1.3852e-05, -3.9245e-06, 1.6585e-05, -2.7964e-06, -3.6403e-06,\n 5.7058e-08, -2.5637e-05, -2.5282e-05, -7.2847e-06, 2.0182e-05,\n -1.4296e-05, -6.6437e-06, -1.3935e-05, -9.4242e-07, -7.1898e-06,\n -5.4581e-06, -7.8939e-07, -2.6888e-07, -7.7940e-07, -1.5924e-05,\n -7.0178e-06, 2.1296e-06, -2.3368e-05, -1.8714e-05, -6.4164e-06,\n -2.2346e-06, 5.8966e-05, 5.1906e-06, 9.1358e-06, 3.4461e-05,\n -3.6352e-06, -8.9807e-07]), 'exp_avg_sq': tensor([6.5189e-08, 2.4655e-08, 6.4031e-08, 1.4329e-09, 1.7109e-08, 1.0619e-09,\n 7.1050e-09, 2.2552e-09, 1.1764e-08, 1.2176e-07, 6.0295e-08, 8.1183e-09,\n 4.4464e-09, 5.9099e-08, 3.4335e-08, 6.2177e-09, 4.5662e-06, 5.5650e-09,\n 7.7541e-08, 1.1095e-09, 1.0639e-06, 6.4908e-09, 2.9488e-08, 4.3098e-09,\n 4.4014e-08, 2.3548e-08, 3.5454e-08, 1.0984e-08, 1.4440e-08, 3.1282e-08,\n 6.9553e-08, 1.4914e-09, 1.4368e-08, 1.1898e-07, 2.0265e-08, 9.0949e-09,\n 1.0419e-07, 1.0039e-08, 7.8651e-09, 4.6582e-08, 9.5984e-09, 1.5578e-08,\n 3.7686e-08, 1.5436e-07, 1.6930e-09, 6.5394e-08, 7.8364e-08, 3.0392e-07,\n 2.5788e-10, 3.4052e-08, 1.0613e-08, 2.8252e-08, 2.4895e-08, 6.4790e-10,\n 4.4321e-08, 5.6899e-08, 6.0471e-08, 4.3287e-09, 2.3182e-08, 8.2214e-07,\n 8.7203e-08, 7.5159e-09, 6.8097e-08, 7.4775e-08, 1.8629e-07, 8.7184e-09,\n 2.4114e-06, 5.2086e-07, 3.0362e-07, 7.9689e-08, 3.6176e-09, 2.3648e-08,\n 1.4079e-06, 4.7768e-09, 1.4303e-07, 4.8245e-09, 9.7702e-08, 2.2759e-08,\n 1.4003e-08, 1.5317e-08, 7.4042e-08, 1.9529e-07, 7.5839e-08, 2.0324e-07,\n 4.4492e-08, 3.4358e-08, 6.3050e-07, 1.1745e-07, 1.5709e-07, 1.1402e-09,\n 1.2586e-07, 1.3706e-08, 4.9752e-09, 2.1231e-09, 1.3741e-08, 5.1264e-09,\n 4.0845e-09, 3.2282e-09, 2.9275e-09, 1.8891e-08, 3.9770e-08, 4.8348e-08,\n 5.2781e-10, 1.4589e-08, 1.1233e-07, 2.1845e-08, 3.6808e-08, 7.6921e-08,\n 2.4926e-08, 5.0149e-08, 2.3408e-08, 2.4073e-08, 3.1379e-09, 3.0474e-08,\n 5.2046e-09, 4.6696e-08, 9.1372e-09, 1.8921e-08, 5.9010e-08, 6.3701e-08,\n 3.0206e-09, 1.1129e-07, 8.5213e-09, 3.4250e-08, 3.7485e-08, 2.5970e-07,\n 2.1890e-08, 5.7230e-08, 8.1682e-09, 3.3290e-08, 2.7069e-08, 1.9635e-08,\n 1.0450e-07, 4.9350e-08, 1.8031e-07, 4.7314e-08, 4.1259e-08, 4.4845e-09,\n 3.2114e-10, 2.8017e-07, 2.7352e-08, 8.1564e-08, 1.8082e-08, 7.8134e-08,\n 2.2849e-09, 5.6143e-08, 1.4883e-08, 4.3287e-08, 1.5239e-08, 4.1426e-10,\n 9.3509e-09, 1.0485e-07, 7.4065e-08, 9.2320e-08, 7.0800e-08, 2.0183e-07,\n 6.2008e-09, 9.9955e-09, 1.3435e-08, 9.6669e-08, 1.2679e-09, 3.8301e-06,\n 6.8070e-08, 9.4073e-09, 2.9888e-09, 6.5680e-09, 1.5972e-07, 7.1999e-09,\n 6.6842e-08, 2.0534e-09, 4.9534e-08, 6.9457e-09, 4.1580e-08, 6.0810e-08,\n 2.9970e-10, 7.6131e-08, 1.4200e-07, 6.0897e-08, 5.2087e-09, 3.9463e-08,\n 8.0503e-08, 7.7046e-09, 1.4570e-08, 5.2247e-08, 3.4867e-09, 5.2994e-08,\n 2.9626e-09, 5.0175e-09, 7.8134e-09, 1.2905e-08, 1.1058e-07, 1.3247e-07,\n 6.7312e-07, 2.4393e-08, 9.0030e-09, 6.5120e-08, 7.6472e-09, 1.8138e-08,\n 4.3953e-09, 4.5999e-07, 8.9525e-09, 8.7351e-09, 1.6950e-08, 1.1711e-08,\n 3.4932e-07, 1.8025e-10, 6.8291e-09, 1.6843e-08, 3.6319e-08, 3.2486e-10,\n 7.0618e-08, 3.4567e-08, 1.5769e-09, 1.0042e-08, 9.5231e-09, 1.6023e-08,\n 2.3628e-08, 3.4064e-09, 1.6076e-08, 3.8403e-08, 8.9015e-09, 1.8003e-07,\n 6.2219e-08, 1.3273e-06, 3.9798e-08, 4.5625e-09, 1.9345e-08, 7.6219e-09,\n 1.3374e-07, 8.9315e-09, 3.5434e-07, 4.3845e-10, 7.8825e-09, 1.5178e-08,\n 4.8398e-08, 5.0022e-10, 1.0727e-08, 5.8689e-09, 2.5999e-08, 1.0197e-07,\n 2.2249e-08, 8.2730e-09, 7.7937e-08, 1.4889e-09, 4.8129e-09, 7.4142e-09,\n 7.1373e-09, 1.7523e-08, 4.4186e-08, 8.1459e-09, 1.2232e-07, 1.9475e-11,\n 2.1679e-07, 1.2294e-08, 1.9818e-08, 3.5931e-09, 3.6017e-07, 1.1476e-10,\n 1.3638e-09, 3.3492e-09, 6.7550e-09, 2.9345e-08, 5.9696e-10, 4.7643e-08,\n 1.3305e-08, 7.8230e-09, 2.7957e-08, 1.8318e-09, 3.3111e-07, 1.0572e-08,\n 6.3404e-09, 4.8732e-07, 1.9226e-08, 2.3560e-08, 2.1170e-08, 8.7295e-09,\n 4.5609e-07, 7.8295e-07, 5.2133e-08, 1.3073e-08, 6.4760e-08, 3.8037e-08,\n 2.3816e-08, 1.2041e-07, 3.1048e-08, 1.0277e-08, 1.6786e-07, 7.1273e-09,\n 1.6035e-09, 4.3119e-08, 1.2245e-08, 1.6340e-08, 3.0773e-09, 2.0716e-09,\n 8.3774e-09, 3.7338e-08, 8.1640e-09, 3.1278e-08, 8.3203e-08, 2.9186e-08,\n 2.2601e-07, 4.8566e-08, 5.1154e-06, 9.2353e-08, 1.1789e-08, 7.4420e-07,\n 7.1206e-08, 3.9799e-08, 3.3041e-08, 3.4882e-08, 3.9743e-06, 2.1600e-08,\n 1.3202e-06, 1.6906e-08, 1.7476e-07, 8.8410e-09, 6.7478e-08, 2.5574e-09,\n 9.5486e-07, 8.9571e-09, 2.4557e-10, 1.2432e-08, 6.4912e-08, 2.7303e-07,\n 1.0802e-07, 1.7214e-08, 1.3973e-07, 8.5326e-10, 1.6565e-09, 4.5274e-08,\n 7.1867e-09, 1.9568e-08, 1.6635e-08, 3.0088e-09, 4.2972e-10, 8.5906e-08,\n 2.0268e-07, 2.6189e-08, 8.3379e-08, 7.6317e-06, 8.0150e-09, 9.6606e-09,\n 1.3012e-07, 2.3593e-08, 1.9199e-09, 5.4264e-08, 3.3502e-06, 1.1436e-08,\n 4.1971e-08, 1.4336e-07, 5.0066e-08, 1.1083e-07, 1.6731e-08, 5.7942e-09,\n 8.0691e-08, 1.4924e-07, 2.6106e-08, 1.4465e-08, 3.9739e-10, 1.4102e-08,\n 4.2505e-08, 1.3833e-07, 1.0781e-08, 2.0678e-07, 1.1673e-09, 3.6115e-07,\n 2.8652e-09, 3.1787e-08, 1.4508e-07, 4.9861e-09, 1.3872e-06, 8.7256e-09,\n 4.4925e-07, 1.3625e-07, 3.5052e-08, 1.3899e-07, 7.2603e-10, 3.2496e-09,\n 3.7110e-07, 2.0318e-07, 1.7760e-10, 8.1663e-09, 1.5541e-08, 1.4803e-08,\n 1.5403e-08, 4.9536e-06, 2.2074e-08, 4.6517e-08, 1.4789e-07, 2.3406e-08,\n 1.9497e-09, 1.9985e-09, 1.1394e-07, 1.8665e-07, 5.6426e-08, 4.2690e-07,\n 1.9749e-08, 4.7095e-08, 4.6403e-09, 1.4093e-08, 4.3777e-08, 3.3361e-08,\n 7.3901e-08, 4.5543e-09, 2.8756e-09, 4.3268e-08, 8.5803e-09, 1.9361e-08,\n 4.7511e-08, 4.1046e-10, 1.3598e-07, 3.8352e-09, 2.1621e-08, 2.8165e-07,\n 8.6316e-08, 1.0252e-07, 2.4014e-07, 3.1770e-09, 1.0666e-08, 1.0139e-08,\n 2.1526e-06, 7.6968e-08, 3.8417e-08, 2.2672e-08, 1.0274e-08, 3.2401e-07,\n 7.9914e-08, 3.5953e-08, 4.3695e-10, 2.8363e-06, 1.2107e-07, 4.7230e-07,\n 7.5428e-09, 2.5884e-09, 5.8001e-09, 2.0606e-08, 6.9361e-08, 1.6384e-07,\n 3.5881e-09, 1.5985e-08, 2.7427e-10, 8.6962e-08, 2.2552e-08, 1.1480e-08,\n 4.8987e-08, 4.6523e-08, 3.9647e-09, 3.5529e-09, 4.2323e-08, 1.0247e-07,\n 3.5210e-08, 3.1606e-08, 1.7353e-06, 5.9438e-08, 1.8329e-08, 7.2442e-09,\n 6.0227e-09, 5.9302e-08, 4.0061e-09, 4.9191e-09, 1.5591e-08, 1.7162e-08,\n 3.9953e-08, 3.7484e-09, 2.6654e-09, 1.9033e-08, 4.8181e-08, 4.5433e-08,\n 6.9272e-10, 3.5012e-08, 3.8780e-08, 6.5343e-09, 3.1860e-08, 1.5898e-08,\n 1.5813e-09, 6.2998e-08, 9.5459e-08, 9.2879e-09, 2.4532e-08, 4.8788e-09,\n 8.4975e-08, 5.8877e-09, 3.4515e-08, 3.0825e-09, 2.8732e-09, 4.2006e-10,\n 1.2008e-07, 3.9234e-06, 4.2846e-08, 4.2801e-08, 1.1866e-07, 8.1574e-09,\n 7.7812e-08, 3.3667e-10, 5.7394e-09, 4.7080e-07, 2.9767e-10, 6.5532e-10,\n 1.6963e-09, 5.5292e-08, 1.7093e-08, 7.3094e-09, 1.2702e-07, 3.8619e-08,\n 2.0382e-08, 3.7893e-09, 1.3378e-07, 4.2131e-08, 1.8778e-07, 2.4779e-08,\n 1.5350e-08, 1.6576e-09])}, 153: {'step': 7160, 'exp_avg': tensor([[[[ 4.7023e-09, 3.1533e-08, 9.3016e-09],\n [ 4.9130e-08, 7.5983e-08, 5.3444e-08],\n [ 5.8414e-08, 6.1350e-08, 4.4219e-08]],\n\n [[ 2.2455e-08, 1.9407e-08, 1.6596e-08],\n [ 2.4698e-08, 1.6249e-08, 2.0457e-08],\n [ 2.1958e-08, 2.4240e-08, 2.5894e-08]],\n\n [[ 1.6237e-07, -3.7919e-08, -2.0065e-07],\n [ 1.6795e-07, -1.0103e-08, -4.2820e-08],\n [-5.7736e-09, -8.3974e-08, -5.8501e-08]],\n\n ...,\n\n [[-1.2127e-08, 2.9661e-09, -2.6953e-09],\n [ 5.2052e-08, 7.2128e-08, 4.6654e-08],\n [ 5.7859e-08, 6.3401e-08, 4.2068e-08]],\n\n [[ 2.5722e-08, 4.5706e-08, 2.0448e-08],\n [ 5.0031e-08, 5.8633e-08, 3.7700e-08],\n [ 5.8588e-08, 5.4961e-08, 4.3153e-08]],\n\n [[ 1.7616e-08, 1.3519e-08, -1.6294e-08],\n [ 3.8255e-08, 5.0848e-08, 3.7022e-08],\n [ 3.7221e-08, 4.7765e-08, 3.6293e-08]]],\n\n\n [[[ 5.5130e-07, -5.3782e-07, 5.8665e-07],\n [-3.1885e-07, -8.9020e-07, -5.2882e-07],\n [ 6.5460e-07, -3.0850e-08, 3.6096e-09]],\n\n [[ 5.0902e-08, 9.1350e-08, 5.7178e-08],\n [ 6.6235e-08, 6.8689e-08, 5.6305e-08],\n [ 6.1936e-08, 1.2826e-07, 1.1999e-07]],\n\n [[-1.6311e-07, 6.1677e-07, 5.5260e-07],\n [ 2.4992e-07, 3.2854e-07, -7.0980e-07],\n [ 6.8833e-08, -1.6744e-06, -1.6892e-06]],\n\n ...,\n\n [[ 5.4254e-07, -3.0073e-07, 6.8888e-07],\n [-2.1530e-07, -6.3879e-07, -6.5078e-08],\n [ 3.2380e-07, -6.2904e-08, 1.0496e-07]],\n\n [[ 5.3966e-07, 2.2390e-07, 8.6775e-07],\n [ 1.5845e-07, 4.2610e-08, 3.2634e-07],\n [ 7.1347e-07, 5.0091e-07, 8.3296e-07]],\n\n [[ 4.7929e-07, -1.8040e-08, 6.2709e-07],\n [ 1.0488e-07, -9.9973e-08, 1.0363e-07],\n [ 3.6454e-07, 1.5089e-07, 1.7492e-07]]],\n\n\n [[[ 2.1066e-07, -9.5835e-09, -6.0344e-08],\n [ 2.1797e-07, 3.1889e-08, -1.3894e-07],\n [ 3.3920e-07, 9.8273e-08, -6.2426e-08]],\n\n [[ 6.6953e-08, 1.1686e-07, 5.8859e-08],\n [ 7.6522e-08, 1.1731e-07, 5.4882e-08],\n [ 6.7707e-08, 1.0495e-07, 7.4569e-08]],\n\n [[ 3.2999e-08, 2.9512e-08, -4.7067e-07],\n [ 2.5903e-07, 1.6095e-07, -2.9014e-07],\n [-2.5740e-08, 1.3870e-07, -1.8545e-07]],\n\n ...,\n\n [[ 1.9809e-07, 8.6238e-10, 2.2865e-08],\n [ 2.2316e-07, 7.9329e-08, -1.3952e-08],\n [ 3.4235e-07, 1.3399e-07, 3.7787e-08]],\n\n [[ 2.4253e-07, 9.9019e-08, 1.1611e-07],\n [ 1.9254e-07, 7.9885e-08, 2.9575e-08],\n [ 2.8268e-07, 1.3941e-07, 1.0205e-07]],\n\n [[ 2.0281e-07, 2.5767e-08, 5.8936e-08],\n [ 1.5295e-07, 3.9513e-08, 6.5607e-09],\n [ 1.9465e-07, 6.9484e-08, 2.3616e-08]]],\n\n\n ...,\n\n\n [[[ 1.6892e-08, 1.9126e-08, 6.7130e-08],\n [ 7.0801e-08, 7.4473e-08, 9.4343e-08],\n [ 1.2517e-07, 6.7254e-08, 1.0241e-07]],\n\n [[ 4.7931e-08, 4.2031e-08, 2.2882e-08],\n [ 5.3643e-08, 3.3578e-08, 2.8537e-08],\n [ 4.8734e-08, 5.3753e-08, 2.6398e-08]],\n\n [[ 2.7862e-07, 7.0338e-08, -2.4427e-07],\n [ 3.3251e-07, -2.7690e-09, -4.7192e-07],\n [ 1.8573e-08, -2.0867e-07, -1.1863e-07]],\n\n ...,\n\n [[ 1.9775e-08, -6.5155e-10, 9.3897e-09],\n [ 3.5791e-08, 9.5411e-08, 1.1268e-07],\n [ 1.3452e-07, 8.7096e-08, 1.1058e-07]],\n\n [[ 9.2698e-08, 9.3388e-08, 7.8109e-08],\n [ 7.8844e-08, 7.8388e-08, 9.2780e-08],\n [ 1.1749e-07, 7.9140e-08, 1.1104e-07]],\n\n [[ 5.1878e-08, 3.0191e-08, 1.7611e-08],\n [ 6.6371e-08, 4.6557e-08, 7.6900e-08],\n [ 7.5460e-08, 5.8302e-08, 7.1931e-08]]],\n\n\n [[[ 4.3725e-07, -4.1116e-07, 3.4754e-07],\n [ 3.2996e-07, -7.8951e-07, -1.6764e-07],\n [ 5.3934e-07, 1.3711e-07, 3.0215e-08]],\n\n [[ 6.4937e-08, 9.3190e-08, 5.6444e-08],\n [ 7.5259e-08, 6.9568e-08, 6.4503e-08],\n [ 7.1044e-08, 1.3008e-07, 1.2100e-07]],\n\n [[-6.5613e-08, 4.1527e-07, 7.4533e-08],\n [ 2.6897e-07, 2.5548e-07, -7.1809e-07],\n [ 1.1102e-08, -1.5164e-06, -1.5637e-06]],\n\n ...,\n\n [[ 4.2610e-07, -1.8887e-07, 4.9202e-07],\n [ 2.8481e-07, -4.9838e-07, 2.4002e-07],\n [ 4.4496e-07, -1.1493e-08, 1.8747e-07]],\n\n [[ 4.4927e-07, 2.3171e-07, 6.5005e-07],\n [ 3.5813e-07, 3.9372e-08, 2.8484e-07],\n [ 5.8306e-07, 3.9728e-07, 3.4954e-07]],\n\n [[ 3.8959e-07, 4.4894e-08, 4.9654e-07],\n [ 4.0702e-07, -1.0892e-07, 2.7887e-07],\n [ 3.8399e-07, 1.3412e-07, 1.5937e-07]]],\n\n\n [[[ 3.9886e-08, 3.1721e-08, -2.7823e-08],\n [ 9.6199e-09, -4.1683e-08, -1.1153e-07],\n [ 9.5454e-08, -2.0407e-08, -1.0405e-07]],\n\n [[ 6.2414e-08, 2.4265e-08, 3.0339e-08],\n [ 7.0430e-08, 3.0351e-08, 4.1724e-08],\n [ 5.9697e-08, 3.3168e-08, 4.0550e-08]],\n\n [[-4.6940e-09, -3.2164e-07, -3.2548e-07],\n [ 2.7358e-07, 2.6969e-07, 2.0013e-07],\n [ 2.2440e-07, 4.9778e-07, 4.8522e-07]],\n\n ...,\n\n [[ 3.6050e-08, 4.7725e-08, 2.5135e-08],\n [ 5.0971e-08, 3.5840e-09, 3.8520e-09],\n [ 1.0327e-07, 1.0433e-08, -7.5604e-09]],\n\n [[ 6.8376e-08, 5.7400e-08, 6.8078e-08],\n [ 4.0190e-08, -3.2143e-09, 1.5392e-08],\n [ 7.9243e-08, 1.8594e-08, 2.7273e-08]],\n\n [[ 3.9869e-08, 3.4283e-08, 3.6013e-08],\n [ 2.5088e-08, -1.4362e-08, -3.6733e-09],\n [ 3.3238e-08, -2.3830e-08, -2.3170e-08]]]]), 'exp_avg_sq': tensor([[[[6.5837e-13, 5.3266e-13, 1.1684e-12],\n [6.4292e-13, 6.0692e-13, 5.7222e-13],\n [1.4408e-12, 6.5549e-13, 6.7186e-13]],\n\n [[2.8413e-13, 5.9781e-13, 3.9377e-13],\n [3.3281e-13, 5.9806e-13, 4.2929e-13],\n [6.1676e-13, 6.9323e-13, 4.5124e-13]],\n\n [[1.4079e-11, 1.5318e-11, 1.3819e-11],\n [2.1124e-11, 2.7883e-11, 1.9024e-11],\n [1.3539e-11, 2.8379e-11, 2.5895e-11]],\n\n ...,\n\n [[6.6055e-13, 5.4641e-13, 1.1675e-12],\n [4.8787e-13, 5.5204e-13, 5.4076e-13],\n [5.7384e-13, 5.2146e-13, 5.1993e-13]],\n\n [[5.3288e-13, 4.8674e-13, 2.6396e-12],\n [4.0823e-13, 4.0604e-13, 3.2979e-13],\n [5.0894e-13, 4.0826e-13, 4.1888e-13]],\n\n [[3.1531e-13, 2.4773e-13, 3.6959e-13],\n [2.3903e-13, 3.0093e-13, 2.4862e-13],\n [2.3051e-13, 2.4907e-13, 2.1415e-13]]],\n\n\n [[[5.5731e-11, 4.4381e-11, 4.8447e-11],\n [5.2054e-11, 4.7240e-11, 4.9195e-11],\n [6.8890e-11, 5.0694e-11, 7.1527e-11]],\n\n [[2.4128e-12, 7.4545e-12, 3.8832e-12],\n [2.7739e-12, 2.7218e-11, 9.3784e-12],\n [1.5887e-11, 3.6404e-11, 1.6627e-11]],\n\n [[1.9020e-10, 1.7494e-10, 2.1026e-10],\n [2.1529e-10, 1.4039e-10, 1.6752e-10],\n [5.6674e-10, 5.2797e-10, 2.8494e-10]],\n\n ...,\n\n [[4.8581e-11, 2.9603e-11, 3.4791e-11],\n [3.4383e-11, 2.8175e-11, 2.7412e-11],\n [4.3763e-11, 2.6428e-11, 3.9416e-11]],\n\n [[2.2065e-11, 3.4068e-11, 3.9618e-11],\n [2.0130e-11, 3.0629e-11, 5.4053e-11],\n [2.8680e-11, 2.6410e-11, 4.9299e-11]],\n\n [[3.7294e-11, 2.1450e-11, 3.2087e-11],\n [1.9127e-11, 1.4306e-11, 1.7567e-11],\n [2.3299e-11, 1.5559e-11, 2.5263e-11]]],\n\n\n [[[6.6309e-12, 2.7274e-12, 4.4176e-12],\n [4.5562e-12, 3.7552e-12, 3.8445e-12],\n [1.0290e-11, 4.8884e-12, 5.3729e-12]],\n\n [[1.4751e-12, 4.3759e-12, 2.1876e-12],\n [1.5453e-12, 3.8651e-12, 3.2583e-12],\n [1.6942e-12, 2.8947e-12, 3.1661e-12]],\n\n [[8.1088e-11, 8.7737e-11, 9.1364e-11],\n [9.5850e-11, 1.0870e-10, 1.0977e-10],\n [7.6128e-11, 9.6232e-11, 9.7667e-11]],\n\n ...,\n\n [[5.6216e-12, 2.5353e-12, 3.5514e-12],\n [2.6973e-12, 2.4923e-12, 2.0755e-12],\n [5.1528e-12, 2.9911e-12, 2.9448e-12]],\n\n [[3.4877e-12, 2.6402e-12, 8.4328e-12],\n [2.2015e-12, 2.8491e-12, 1.3111e-12],\n [4.4750e-12, 3.0126e-12, 2.6568e-12]],\n\n [[3.6975e-12, 1.3517e-12, 2.1936e-12],\n [1.1487e-12, 6.8264e-13, 7.2628e-13],\n [1.9901e-12, 9.8160e-13, 9.4593e-13]]],\n\n\n ...,\n\n\n [[[3.8473e-12, 1.8364e-12, 2.2080e-12],\n [1.5042e-12, 1.3504e-12, 1.5504e-12],\n [1.7938e-12, 9.3246e-13, 1.4579e-12]],\n\n [[6.0824e-13, 8.5532e-13, 6.2617e-13],\n [6.9006e-13, 9.5351e-13, 1.2478e-12],\n [1.1978e-12, 8.8557e-13, 1.3092e-12]],\n\n [[2.5991e-11, 2.4622e-11, 2.3232e-11],\n [3.0872e-11, 3.7549e-11, 2.9892e-11],\n [3.3960e-11, 5.3737e-11, 3.6396e-11]],\n\n ...,\n\n [[1.7553e-12, 1.0770e-12, 1.8655e-12],\n [7.6288e-13, 7.5802e-13, 9.6776e-13],\n [8.1232e-13, 7.5234e-13, 1.1519e-12]],\n\n [[1.1982e-12, 1.2678e-12, 4.2934e-12],\n [5.2089e-13, 1.1203e-12, 1.1529e-12],\n [6.4582e-13, 8.3604e-13, 2.5673e-12]],\n\n [[1.1914e-12, 6.2174e-13, 8.2543e-13],\n [4.0048e-13, 3.0136e-13, 3.7485e-13],\n [4.0015e-13, 3.4873e-13, 3.9834e-13]]],\n\n\n [[[4.4409e-11, 3.9265e-11, 3.3981e-11],\n [3.0609e-11, 3.3902e-11, 2.6969e-11],\n [3.5657e-11, 2.2409e-11, 2.3368e-11]],\n\n [[1.6451e-12, 6.7834e-12, 2.5636e-12],\n [1.3963e-12, 1.9331e-11, 8.1942e-12],\n [1.2046e-11, 1.6151e-11, 1.6295e-11]],\n\n [[1.7070e-10, 1.5359e-10, 1.6009e-10],\n [1.3887e-10, 1.1362e-10, 1.3007e-10],\n [4.3634e-10, 3.9080e-10, 2.1400e-10]],\n\n ...,\n\n [[3.0371e-11, 2.4614e-11, 2.1487e-11],\n [1.9052e-11, 2.4590e-11, 2.1082e-11],\n [1.7987e-11, 1.3922e-11, 1.4857e-11]],\n\n [[1.5164e-11, 3.3860e-11, 3.8876e-11],\n [1.6188e-11, 1.7771e-11, 4.4398e-11],\n [1.7094e-11, 1.4325e-11, 1.3085e-11]],\n\n [[2.3008e-11, 1.3170e-11, 1.5656e-11],\n [1.0102e-11, 1.0265e-11, 8.7790e-12],\n [9.0556e-12, 6.6759e-12, 7.4567e-12]]],\n\n\n [[[2.4550e-12, 1.4899e-12, 3.1241e-12],\n [1.4196e-12, 2.1415e-12, 1.7203e-12],\n [2.0212e-12, 1.3756e-12, 1.5126e-12]],\n\n [[1.1710e-12, 1.3419e-12, 8.2694e-13],\n [1.2661e-12, 9.3969e-13, 8.6437e-13],\n [1.2287e-12, 9.1634e-13, 8.9764e-13]],\n\n [[4.3201e-11, 4.4322e-11, 3.5866e-11],\n [4.7247e-11, 5.0425e-11, 4.4051e-11],\n [3.8915e-11, 5.3723e-11, 4.9514e-11]],\n\n ...,\n\n [[2.9698e-12, 1.5570e-12, 2.5976e-12],\n [1.5508e-12, 2.0648e-12, 1.2871e-12],\n [1.4980e-12, 1.1966e-12, 1.0203e-12]],\n\n [[1.7100e-12, 1.0234e-12, 4.7797e-12],\n [9.1516e-13, 1.4285e-12, 6.6314e-13],\n [1.0001e-12, 6.1944e-13, 7.0105e-13]],\n\n [[1.3114e-12, 7.4837e-13, 1.2347e-12],\n [5.0968e-13, 5.9119e-13, 5.1206e-13],\n [5.1022e-13, 6.6312e-13, 4.7463e-13]]]])}, 154: {'step': 7160, 'exp_avg': tensor([ 2.4033e-06, -2.0830e-05, -1.0101e-05, 9.2190e-06, -7.7700e-06,\n -1.4489e-05, -2.3104e-06, -1.6908e-05, 1.4392e-05, -1.5695e-05,\n -3.5454e-05, 1.1336e-05, -7.6144e-06, -6.7813e-06, 8.0960e-06,\n 4.1724e-05, 1.3072e-05, -1.4298e-05, -1.2609e-05, -2.2127e-06,\n -1.4853e-05, -1.7297e-05, -1.5783e-05, 1.8281e-06, -1.1556e-06,\n 1.5861e-05, -3.0153e-06, -5.1782e-06, -1.2056e-05, -5.7191e-06,\n -1.0022e-05, -1.2034e-05, 2.8532e-05, 2.5855e-06, -1.9164e-06,\n -1.4772e-05, -9.2850e-06, -4.1210e-06, 3.3129e-05, -1.2440e-05,\n -1.4471e-06, -6.7799e-06, 7.4206e-06, 1.4582e-05, -3.8174e-06,\n -1.1227e-07, -6.8525e-06, -3.6142e-06, -6.8204e-06, -2.1209e-05,\n -9.0684e-06, -1.4770e-05, -2.3796e-06, -1.0888e-06, -6.0844e-06,\n -7.2003e-06, -4.6628e-06, -7.3282e-06, -1.5998e-05, 1.0521e-05,\n -2.1287e-05, 1.2923e-06, -7.3659e-06, -3.9191e-07, -9.2554e-06,\n -2.4345e-05, -2.3981e-05, -8.4117e-05, -1.1607e-05, 2.1590e-05,\n 1.3506e-05, -1.1014e-05, 5.2547e-06, -2.2549e-06, -1.6732e-05,\n -7.5301e-06, 8.3132e-06, -1.5264e-05, -4.3402e-06, -3.8404e-05,\n -2.8015e-06, 6.8759e-07, -1.7153e-05, -3.3590e-05, 2.7079e-06,\n -6.8301e-06, -7.1809e-06, -7.4425e-06, -1.1145e-05, 1.1103e-05,\n -9.9617e-06, 2.1166e-05, 1.2031e-05, -8.8141e-06, -1.4549e-05,\n -1.2308e-05, -1.7878e-06, -6.3931e-06, -6.7425e-06, 1.5588e-05,\n -1.5605e-05, 2.8556e-05, 1.0562e-06, -7.4615e-06, -2.6517e-06,\n -1.8287e-07, -2.3145e-05, -2.9440e-05, -1.2423e-05, -1.3813e-05,\n 1.3877e-05, -1.5202e-05, -4.6374e-06, -1.9882e-05, -7.0916e-06,\n 5.0566e-06, -2.8179e-05, 4.8367e-06, -1.7984e-06, 2.4167e-05,\n -2.4260e-05, -6.5339e-06, 1.1326e-06, -1.5004e-05, -1.6581e-06,\n 1.9837e-05, 8.0624e-06, -3.1673e-06, -8.0644e-06, -1.2253e-05,\n -8.8387e-06, -7.8424e-06, 2.5639e-07, -7.8658e-06, -1.1984e-05,\n -1.0238e-05, -8.3593e-06, -1.7069e-05, -5.9536e-05, -1.0065e-05,\n 1.0879e-06, 4.0916e-05, -3.6374e-07, -1.4056e-05, -6.1220e-06,\n -3.8604e-06, -3.9827e-06, -1.4671e-05, 1.0190e-07, -2.1356e-05,\n -6.2375e-06, -1.3059e-05, -1.0412e-05, 4.3587e-06, 9.5936e-07,\n -1.1693e-05, -8.6933e-06, 1.3644e-05, -3.0132e-06, 9.6986e-07,\n -3.7982e-05, -4.6071e-06, -1.1488e-05, -6.7578e-06, 9.2734e-06,\n -5.6501e-06, 1.5412e-05, -3.2608e-06, -7.0292e-06, 3.4464e-06,\n 2.1877e-05, 2.3004e-05, 1.2748e-05, -2.3674e-07, 3.5802e-05,\n 5.8235e-06, -4.4141e-06, -2.1072e-06, 1.5485e-06, -1.6646e-05,\n -1.3876e-05, -1.6271e-05, -9.5032e-07, 5.1446e-06, -8.6468e-07,\n -1.2459e-05, -3.5493e-06, 1.8468e-05, -5.7276e-06, 1.2722e-05,\n -2.1606e-05, -6.7734e-06, -2.7591e-07, -1.3354e-05, -7.8078e-06,\n -1.8527e-05, -5.6319e-06, 3.3440e-06, -4.5023e-06, 2.7156e-06,\n -7.1328e-06, 5.4001e-06, -1.4677e-05, -1.7012e-05, -1.7887e-06,\n -2.5201e-06, -1.4040e-05, -1.1096e-05, -1.6030e-05, -1.8036e-05,\n -1.0954e-05, -5.7642e-05, -2.0435e-05, -2.5930e-05, 1.2185e-05,\n 2.2416e-05, 1.4982e-05, -1.0961e-05, 1.5865e-05, -2.0589e-05,\n -2.9103e-05, -2.4329e-05, -1.6084e-05, 1.9095e-06, -2.0010e-05,\n 4.3907e-06, -5.3914e-07, -1.6584e-06, 1.9748e-05, -1.8384e-05,\n -1.0231e-05, -1.6745e-05, -9.0488e-06, -1.7479e-05, -1.3069e-05,\n 8.4953e-06, -1.1209e-05, -1.3146e-05, -2.8968e-05, -4.8552e-06,\n -1.4215e-05, -1.0582e-05, 1.1163e-05, -4.8314e-06, -2.0659e-05,\n -6.6082e-06, -1.2884e-05, 2.0924e-06, 1.2752e-07, -1.0520e-05,\n -1.9197e-05, -7.1763e-06, -4.8959e-06, -7.8664e-06, -6.0106e-08,\n -9.8565e-08, 2.6887e-05, 1.9726e-05, 9.8250e-08, -7.0663e-06,\n -8.1020e-06, -2.1157e-05, 2.6790e-06, -1.8374e-06, -5.2159e-06,\n -2.7785e-05, -1.7325e-05, -1.1310e-05, -1.1098e-05, -7.3981e-06,\n -2.0203e-06, -2.5219e-05, -4.8783e-06, -6.8087e-06, -1.1074e-05,\n -7.6632e-07, -3.0381e-05, 7.4819e-06, -1.1604e-05, -1.0842e-05,\n -1.9315e-06, -5.1578e-07, -1.6620e-05, 1.1625e-05, -1.6077e-06,\n 6.9778e-06, -6.2382e-06, -9.8159e-06, 1.8222e-05, -4.6452e-06,\n -1.8563e-05, -1.0252e-05, -1.5122e-05, 1.7146e-05, 3.5177e-06,\n -8.8050e-06, -2.1756e-06, -8.4543e-06, -8.9171e-06, -9.0634e-06,\n -1.3315e-05, -8.7240e-06, -1.0301e-05, -5.7689e-06, -8.0005e-06,\n -9.1244e-06, -1.3915e-05, -7.6161e-06, -1.7789e-06, -7.4621e-06,\n -4.1907e-06, -1.3198e-05, -2.4464e-06, 8.8145e-06, -7.0244e-06,\n -3.8931e-06, 8.0552e-06, -1.0386e-05, -1.5874e-05, -7.1675e-06,\n 9.1100e-06, 1.7335e-06, -8.1386e-06, -4.0353e-06, 3.6372e-06,\n -1.0052e-05, 3.0512e-06, -2.3317e-05, 3.1813e-05, 1.7536e-05,\n -6.1022e-06, -9.1235e-06, 1.4568e-05, 1.5225e-05, -1.0488e-05,\n -1.2527e-05, -9.5517e-06, -2.5989e-06, -1.8248e-05, -7.2932e-06,\n -1.7706e-05, 1.9156e-05, -7.0722e-06, -3.6858e-06, 5.1244e-06,\n -1.1132e-05, -1.3251e-05, -1.5189e-05, 7.9928e-06, -2.7760e-06,\n 5.6593e-06, 1.1433e-05, -1.6461e-05, 6.9881e-06, 3.3988e-06,\n 1.8245e-07, 4.6272e-06, 8.4701e-07, -1.7742e-05, 5.1673e-06,\n -1.2165e-05, -9.8225e-06, -2.1353e-05, 1.3888e-07, -2.2496e-06,\n -1.6364e-05, 1.1820e-06, 1.1115e-05, 2.7815e-05, 1.8003e-06,\n -3.4724e-06, 1.7084e-05, -3.3411e-05, -1.3847e-07, -1.9918e-05,\n 1.0430e-05, -1.9215e-06, -9.2891e-07, -1.7680e-05, 1.0059e-06,\n 3.7276e-05, -1.7104e-05, -1.4908e-05, -3.4516e-05, -4.7942e-06,\n 1.2182e-05, -6.7925e-06, -7.4222e-06, -2.7493e-06, -1.3923e-05,\n -3.4223e-05, -5.5678e-06, -1.6682e-05, 1.8414e-05, 3.5747e-06,\n -1.2980e-05, 1.2639e-05, -6.2424e-07, 2.6340e-06, -1.4760e-05,\n -4.2822e-06, -1.1493e-05, 1.8261e-05, 1.3948e-05, -2.1206e-05,\n -1.4377e-05, -1.3266e-05, -1.1837e-05, -6.7271e-06, -1.4492e-05,\n 1.1639e-06, 1.4214e-05, -1.3074e-05, -1.6533e-05, -1.3349e-05,\n -2.1136e-05, 2.6482e-06, -1.6458e-05, -7.5520e-06, 2.1151e-05,\n -8.7220e-06, -7.5212e-06, -1.1699e-05, -1.2788e-06, 3.8710e-07,\n -1.2109e-05, 3.0971e-05, -9.4031e-06, -1.3787e-05, -3.5817e-06,\n -3.7560e-05, 1.2415e-05, -9.2345e-06, -1.1926e-05, 1.3821e-05,\n 1.3959e-05, 5.7312e-06, -9.7412e-06, -7.4959e-06, -1.6259e-05,\n -1.9143e-05, 1.9438e-06, -3.7013e-06, -2.5744e-06, -8.8029e-06,\n -1.0941e-05, 2.8831e-06, -1.0230e-05, 7.7393e-06, -1.1777e-06,\n -6.9187e-06, -7.2295e-06, -5.0108e-06, 3.0110e-05, -7.0008e-06,\n -2.7513e-05, -2.6107e-05, -4.7689e-06, -3.9885e-06, 1.9221e-06,\n -1.0893e-05, -1.1972e-05, -6.0822e-06, -6.3233e-06, 2.4927e-06,\n 3.6222e-06, -1.3369e-05, 2.4510e-05, -1.1501e-05, 6.9230e-06,\n -6.1736e-06, -1.0368e-06, -8.6238e-06, -7.9386e-06, 2.9860e-05,\n -9.2073e-06, -1.6533e-05, -4.3092e-06, -1.0684e-05, -7.7251e-06,\n -1.4573e-05, -1.7541e-05, -3.8420e-06, -1.3960e-05, -1.4445e-06,\n -1.3299e-05, 1.4229e-05, -4.4243e-06, -6.6707e-06, -8.0370e-06,\n 2.6478e-06, -8.0215e-06, -2.0108e-05, -2.5316e-05, 1.5405e-05,\n -8.6797e-06, 3.2097e-07, -1.1788e-05, -1.1177e-05, 4.9802e-06,\n -7.6558e-06, -1.5215e-05, 2.5371e-06, 1.4352e-05, -8.0372e-06,\n -5.3617e-06, -1.0689e-05, -5.5461e-06, -3.2409e-06, -4.8211e-06,\n -2.2427e-05, -9.1288e-06]), 'exp_avg_sq': tensor([2.2790e-09, 3.4680e-08, 2.2697e-08, 2.8309e-08, 5.9250e-09, 3.4775e-08,\n 3.1132e-09, 4.2910e-08, 7.9593e-09, 1.7030e-08, 6.4896e-08, 1.1348e-08,\n 7.2359e-09, 8.5980e-09, 2.8369e-08, 3.7569e-08, 1.7225e-08, 4.6379e-08,\n 2.2311e-08, 6.7432e-09, 4.2310e-08, 2.2322e-08, 2.3672e-08, 1.4719e-08,\n 1.8708e-08, 2.1022e-08, 6.6789e-09, 7.3668e-09, 3.4099e-08, 4.7561e-09,\n 1.2116e-08, 2.8766e-08, 1.9473e-08, 8.4498e-08, 2.4995e-09, 1.4245e-08,\n 1.1373e-08, 8.7179e-09, 7.1901e-08, 2.0619e-08, 3.6632e-08, 1.1613e-08,\n 8.1317e-09, 8.9087e-09, 6.2771e-09, 1.5846e-08, 1.0795e-08, 1.9480e-09,\n 7.5436e-09, 2.6594e-08, 1.2894e-08, 4.9160e-08, 1.2905e-08, 1.3485e-08,\n 2.4295e-08, 8.1794e-09, 2.3599e-08, 1.1540e-08, 2.7930e-08, 7.3067e-09,\n 4.6352e-08, 9.3462e-09, 2.1531e-08, 1.1290e-08, 1.1572e-08, 5.5800e-08,\n 8.0239e-08, 9.9448e-07, 3.3077e-08, 8.4086e-09, 2.9682e-08, 1.3448e-08,\n 1.2695e-08, 2.2494e-08, 3.9721e-08, 3.8158e-08, 2.1844e-08, 4.1527e-08,\n 2.6539e-08, 4.2248e-08, 1.6988e-09, 6.8396e-09, 1.5412e-08, 4.2205e-08,\n 4.6133e-09, 5.8299e-09, 4.1503e-08, 8.3992e-09, 2.7258e-08, 4.3389e-09,\n 2.4656e-08, 1.1288e-08, 4.3988e-09, 7.3088e-09, 3.1190e-08, 2.0746e-08,\n 2.4702e-08, 6.1214e-09, 8.1194e-09, 1.6221e-08, 2.9356e-08, 3.1237e-08,\n 1.8688e-08, 6.9282e-09, 6.3102e-09, 1.1341e-08, 4.3835e-08, 4.3972e-08,\n 2.4907e-08, 2.3588e-08, 8.9893e-09, 4.8749e-08, 2.4746e-08, 5.0680e-08,\n 8.8506e-09, 3.4634e-09, 5.8452e-08, 7.6220e-08, 1.7672e-09, 1.6993e-08,\n 1.2962e-07, 1.5452e-08, 2.6796e-09, 3.2176e-08, 9.7261e-09, 3.5461e-08,\n 3.6260e-08, 5.1446e-09, 3.4102e-08, 2.5946e-08, 6.1064e-09, 1.6008e-08,\n 1.8756e-08, 1.2949e-08, 1.3754e-08, 1.1414e-08, 1.1984e-08, 3.3049e-08,\n 4.6056e-07, 1.3579e-08, 3.5819e-09, 5.3687e-08, 3.8742e-09, 3.1554e-08,\n 3.0331e-08, 6.7470e-09, 6.7333e-09, 4.1618e-08, 8.7945e-09, 4.2516e-08,\n 1.1372e-08, 1.5974e-08, 2.7669e-08, 1.0632e-08, 1.5670e-09, 2.5216e-08,\n 7.9849e-09, 1.4343e-08, 4.8942e-09, 1.8380e-09, 5.3561e-08, 5.7493e-09,\n 1.0725e-08, 1.2547e-08, 9.1827e-09, 1.7615e-08, 3.6711e-08, 1.0954e-08,\n 1.0726e-08, 2.5379e-08, 8.0270e-09, 1.5579e-08, 8.5695e-09, 5.9479e-10,\n 3.5674e-08, 4.5251e-09, 8.6978e-09, 6.1583e-09, 6.3239e-09, 1.4026e-08,\n 2.5761e-08, 2.5001e-08, 1.8427e-09, 2.0591e-08, 3.3340e-09, 1.0398e-08,\n 7.0689e-09, 9.8234e-08, 8.7060e-09, 1.1591e-08, 2.9866e-08, 1.0624e-08,\n 1.3004e-08, 2.1101e-08, 5.4771e-09, 3.7435e-08, 1.4390e-08, 2.8135e-08,\n 4.6364e-09, 5.1137e-09, 5.4688e-09, 4.6046e-09, 2.8409e-08, 1.9793e-08,\n 1.3714e-08, 7.0291e-09, 4.6852e-08, 1.0947e-08, 2.1610e-08, 2.0765e-08,\n 5.1455e-09, 2.0358e-07, 1.6347e-08, 5.1998e-08, 4.2048e-08, 2.3901e-08,\n 1.0853e-08, 1.4516e-08, 3.2717e-08, 2.6568e-08, 4.1154e-08, 4.7937e-08,\n 3.8591e-08, 4.4879e-09, 4.7670e-08, 2.7635e-09, 4.7638e-09, 1.8543e-09,\n 1.3921e-08, 8.4842e-08, 9.4598e-09, 3.5160e-08, 1.8357e-08, 1.1677e-08,\n 3.6581e-08, 4.8193e-09, 2.1304e-08, 5.5723e-08, 1.3624e-08, 1.1678e-08,\n 1.6015e-08, 8.7074e-09, 1.0762e-08, 1.1085e-08, 2.3499e-07, 2.2857e-08,\n 2.5427e-08, 1.1418e-08, 2.6167e-08, 7.6933e-09, 3.3515e-08, 1.5470e-08,\n 5.4867e-09, 4.0801e-08, 2.4631e-09, 9.9464e-09, 2.5674e-08, 1.4700e-08,\n 2.8652e-09, 1.4006e-08, 1.4726e-08, 6.8927e-08, 1.5336e-08, 1.2679e-08,\n 2.2339e-08, 4.7388e-08, 1.2552e-08, 2.1809e-08, 5.0124e-08, 1.1246e-08,\n 7.2655e-10, 3.9254e-08, 2.9050e-09, 3.4255e-08, 2.1583e-08, 6.0523e-09,\n 3.1706e-08, 8.7957e-09, 1.9572e-08, 5.2891e-09, 6.5030e-09, 3.1845e-08,\n 1.0935e-08, 2.3049e-08, 1.9101e-08, 2.2949e-09, 2.7785e-09, 1.2171e-08,\n 8.8506e-09, 3.4019e-08, 3.9786e-08, 4.3364e-08, 3.5284e-08, 2.8901e-08,\n 7.9302e-09, 2.8752e-08, 1.0635e-08, 2.7747e-08, 7.2188e-09, 5.7110e-09,\n 1.2611e-08, 1.9801e-08, 3.0721e-08, 2.1888e-09, 2.2213e-08, 1.8642e-08,\n 2.0208e-08, 2.1111e-08, 1.3888e-08, 8.9778e-09, 6.1987e-09, 2.3317e-08,\n 8.9551e-09, 6.8547e-09, 1.2800e-08, 1.8165e-08, 6.2017e-09, 1.8058e-08,\n 2.2756e-08, 1.8600e-08, 2.2400e-08, 4.0436e-09, 7.2296e-09, 7.3574e-09,\n 5.3494e-09, 3.0138e-08, 6.8160e-09, 3.3350e-08, 3.5001e-08, 5.8890e-08,\n 1.4397e-08, 1.7374e-08, 2.0747e-08, 5.4882e-09, 1.0194e-08, 2.1877e-08,\n 1.7741e-08, 1.3779e-08, 4.5652e-08, 1.8496e-08, 1.6933e-08, 1.7439e-08,\n 1.0640e-08, 1.5245e-08, 5.0681e-09, 3.2059e-08, 2.1784e-08, 2.2775e-08,\n 1.4543e-08, 5.1361e-09, 2.0341e-08, 4.8902e-09, 1.6477e-08, 5.1540e-09,\n 6.3277e-09, 3.6318e-09, 6.5548e-09, 8.6237e-09, 7.4534e-08, 9.8977e-09,\n 1.9811e-08, 2.7221e-08, 7.4044e-08, 2.6122e-08, 4.6589e-09, 3.0900e-08,\n 1.3647e-08, 2.6875e-08, 1.6916e-08, 1.5432e-09, 3.4253e-09, 1.4017e-08,\n 5.2965e-07, 1.5664e-09, 3.8436e-08, 3.3225e-09, 5.2447e-09, 3.9791e-09,\n 2.4046e-07, 2.8879e-09, 7.0276e-08, 2.6650e-08, 1.2404e-08, 1.4804e-07,\n 3.3125e-09, 3.8159e-09, 1.6822e-08, 2.5618e-08, 7.1090e-09, 2.7405e-08,\n 2.4160e-08, 9.5348e-09, 3.2367e-08, 1.6346e-08, 1.5683e-08, 1.1230e-08,\n 6.0982e-09, 8.1182e-09, 9.5732e-10, 1.6737e-08, 5.2261e-09, 1.2004e-08,\n 5.4693e-09, 5.7461e-09, 4.4604e-08, 1.7252e-08, 2.1100e-08, 1.2066e-08,\n 4.9652e-09, 5.1345e-09, 5.7337e-09, 1.8315e-08, 4.2837e-08, 4.1243e-08,\n 1.5123e-08, 7.9793e-08, 1.6890e-08, 1.8340e-08, 1.6479e-08, 3.1367e-08,\n 7.4354e-09, 1.0818e-08, 2.0029e-08, 1.7812e-08, 2.2602e-09, 2.9345e-08,\n 2.1023e-08, 1.7865e-08, 3.0308e-08, 3.4116e-09, 2.2451e-08, 1.3678e-08,\n 9.9458e-09, 3.2744e-08, 5.0439e-09, 1.7482e-08, 1.2915e-08, 1.2357e-08,\n 8.5409e-09, 2.4233e-08, 3.0044e-08, 2.1763e-08, 1.1768e-08, 8.1663e-09,\n 5.2550e-09, 1.8912e-08, 2.4380e-09, 1.7662e-08, 8.1744e-09, 1.2011e-08,\n 1.1725e-08, 1.7037e-08, 1.2569e-08, 2.6136e-08, 1.2297e-08, 4.2913e-08,\n 2.5938e-08, 5.1859e-08, 8.1203e-09, 8.9946e-09, 1.8538e-08, 1.0069e-08,\n 3.0770e-09, 2.0361e-09, 3.3098e-08, 2.7780e-08, 2.3792e-08, 1.8824e-08,\n 3.5363e-08, 2.4546e-09, 6.5514e-09, 6.5948e-09, 1.0698e-08, 1.6878e-08,\n 1.6306e-08, 2.2284e-08, 1.9428e-08, 3.3531e-08, 2.1955e-08, 1.0017e-08,\n 2.4896e-08, 5.3676e-08, 1.3354e-08, 2.7934e-08, 9.4499e-09, 2.2071e-08,\n 3.8391e-09, 1.2372e-08, 3.0465e-08, 2.1931e-08, 1.9345e-09, 7.1514e-09,\n 1.1224e-07, 3.7829e-07, 9.6036e-09, 1.1027e-08, 2.1488e-11, 9.1937e-09,\n 3.2293e-08, 3.2494e-09, 1.3691e-08, 1.7811e-08, 1.9587e-09, 1.8837e-08,\n 9.4425e-09, 1.7257e-08, 3.4441e-08, 9.2077e-09, 4.0520e-09, 6.2909e-09,\n 5.9082e-08, 1.0294e-08])}, 155: {'step': 7160, 'exp_avg': tensor([-2.2654e-07, -1.0851e-04, -2.9618e-05, 1.0662e-05, -1.4832e-05,\n -5.8593e-05, -5.6510e-06, -2.0267e-05, 1.9864e-05, -2.8369e-05,\n -1.7103e-04, 1.5940e-05, -1.5129e-05, -2.2447e-05, -4.2117e-06,\n 5.4136e-05, 1.5989e-05, -8.8575e-06, -3.3615e-05, -7.1858e-06,\n -4.2364e-05, -6.3943e-05, -7.0659e-05, 2.7814e-06, -8.8158e-06,\n 2.0594e-05, -4.8546e-06, -1.6661e-05, -4.4488e-05, -1.6814e-05,\n -3.7962e-05, -1.2727e-04, 3.6380e-05, 5.9793e-07, -3.9207e-06,\n -5.5906e-05, -2.1408e-05, -1.6776e-05, 4.3774e-05, -3.4551e-05,\n -3.6533e-05, -3.0764e-05, 1.1175e-05, 1.8862e-05, -5.9749e-06,\n -2.0376e-05, -2.8288e-05, -7.7179e-06, -1.6671e-05, -4.0943e-05,\n -2.7834e-05, -1.6645e-05, -2.3618e-06, -6.7148e-06, -4.6255e-06,\n -2.0445e-05, -1.6247e-05, -1.9731e-05, -4.4100e-05, 1.3372e-05,\n -5.2829e-05, 3.8476e-07, -2.6449e-05, -2.8178e-06, -1.9514e-05,\n -1.6130e-04, -9.5993e-05, -3.8557e-06, -3.7658e-05, 3.0539e-05,\n 5.1927e-06, -4.2895e-05, 7.3540e-06, -7.1941e-06, -6.3173e-05,\n -2.5240e-05, 8.4068e-06, -4.5958e-05, -2.1296e-05, -1.1581e-04,\n -1.0347e-05, -6.3327e-06, -7.5041e-05, -4.3437e-05, 1.5512e-06,\n -1.4856e-05, -1.0476e-04, -2.0461e-05, -4.4747e-05, 1.6366e-05,\n -1.1963e-05, 2.7990e-05, 1.8426e-05, -2.3324e-05, -3.9933e-05,\n -2.2794e-05, -1.6416e-05, -1.3101e-05, -1.1775e-05, 1.6074e-05,\n -5.6461e-05, 3.8437e-05, -8.1400e-06, -2.6560e-05, -9.1231e-06,\n -4.4246e-07, -9.3026e-05, -9.6242e-05, -3.0232e-05, -3.9196e-05,\n 1.8181e-05, -1.0871e-04, -4.6561e-06, -6.2482e-05, -1.6834e-05,\n 2.9637e-06, -1.2234e-04, -4.1028e-06, -1.5658e-05, 3.1968e-05,\n -2.4756e-05, -1.7481e-05, -2.7648e-06, -4.6137e-05, -1.1469e-05,\n 2.5172e-05, 3.9415e-06, -1.0407e-05, -4.1473e-05, -3.1333e-05,\n -5.9250e-05, -1.6813e-05, -1.2354e-05, -2.3721e-05, -5.9268e-05,\n -3.7987e-05, -2.5733e-05, -5.8492e-05, -7.9743e-05, -2.4318e-05,\n -2.3420e-05, 5.3288e-05, -2.3455e-06, -5.1415e-05, -2.9171e-05,\n -1.4056e-05, -9.3311e-06, -4.6385e-05, -2.0525e-06, -6.0003e-05,\n -2.3491e-05, -2.6407e-05, -3.2795e-05, 5.0909e-06, -1.3472e-05,\n -7.2863e-05, -1.9858e-05, 1.6156e-05, -1.1266e-05, 1.1473e-06,\n -1.1060e-04, -1.5163e-05, -3.4526e-05, -7.6480e-06, 9.0514e-06,\n -1.2725e-05, 1.9520e-05, -2.6351e-05, -2.7425e-05, -1.2958e-05,\n 3.3150e-05, 3.1532e-05, 1.4979e-05, -1.8505e-07, 4.3636e-05,\n 5.3994e-06, -1.1706e-05, -7.0507e-06, 1.9222e-07, -5.0554e-05,\n -3.8162e-05, -3.6058e-05, -3.0060e-06, -5.6821e-06, -6.3326e-06,\n -2.0717e-05, -1.3675e-05, 1.8858e-05, -1.1712e-05, 1.3599e-05,\n -7.2415e-05, -5.6629e-05, -1.8945e-06, -1.7959e-05, -3.6157e-05,\n -9.6474e-05, -2.2398e-05, -4.2908e-05, -1.3495e-05, -1.4878e-06,\n -5.9187e-05, 8.0416e-06, -4.3127e-05, -9.0038e-05, 1.7143e-07,\n -1.8782e-05, -5.4463e-05, -8.0277e-05, -7.7323e-05, -5.2752e-05,\n -2.5896e-05, -2.0978e-04, -3.3793e-05, -3.6742e-05, 9.6660e-06,\n 2.5970e-05, 1.7471e-05, -5.5154e-05, 1.4890e-05, -3.6948e-05,\n -1.1756e-04, -9.6227e-05, -6.6599e-05, 1.2560e-06, -3.2764e-05,\n 4.0458e-06, -8.9107e-06, -3.8189e-06, 2.6793e-05, -9.0975e-05,\n -2.2217e-05, -5.4691e-05, -2.9733e-05, -9.1624e-05, -3.7836e-05,\n 7.2554e-06, -3.1209e-05, -5.3353e-05, -1.1170e-04, -5.2027e-06,\n -1.2484e-05, -4.6711e-05, 1.0892e-05, -2.3376e-05, -1.0700e-04,\n -2.0318e-05, -3.5817e-05, 2.8419e-06, 5.6803e-06, -5.2764e-05,\n -3.9280e-05, -3.2118e-05, -1.3116e-05, -6.5674e-06, -2.3402e-06,\n -9.5110e-06, 3.1578e-05, 2.7951e-05, -4.0923e-06, -2.4730e-05,\n -3.4210e-05, -8.9949e-05, -3.6245e-06, -1.4619e-05, 1.2409e-06,\n -1.0410e-04, -5.5415e-05, -3.0348e-05, -3.8867e-05, -1.6654e-05,\n -3.6932e-06, -1.4312e-04, -3.3593e-05, -5.0807e-05, -4.0016e-05,\n -6.5659e-06, -1.3258e-04, -2.8276e-06, -3.1968e-05, -1.0171e-05,\n -1.1277e-05, 2.2446e-06, -2.3586e-05, 1.9944e-06, -2.1583e-05,\n 9.9946e-06, -1.2899e-05, -2.1205e-05, 2.5920e-05, -3.6752e-05,\n -7.9027e-05, -4.0721e-05, -5.7385e-05, 2.2012e-05, 2.2846e-06,\n -2.7582e-05, -1.8824e-05, -2.8502e-05, -2.4376e-05, -3.0569e-05,\n -5.4901e-05, -2.7541e-05, -3.5206e-05, -1.0621e-05, -2.8514e-05,\n -2.7848e-05, -3.4504e-05, -2.1914e-05, -1.7388e-05, -1.4949e-05,\n -1.4998e-05, -6.9282e-05, -1.0923e-05, 1.6525e-06, -1.4496e-05,\n -2.5172e-05, 5.6588e-06, -2.7116e-05, -6.4084e-05, -2.5958e-05,\n -1.7112e-06, -1.8306e-06, -1.8597e-05, -1.3235e-05, 4.4432e-06,\n -3.2490e-05, -1.0223e-06, -4.5039e-05, 3.9775e-05, 2.3200e-05,\n -2.5583e-05, -3.0395e-05, 1.2330e-05, 1.9564e-05, -4.8225e-05,\n -3.7989e-05, -2.3777e-05, -3.5452e-06, -1.9206e-05, -2.5124e-05,\n -9.7831e-05, 2.1792e-05, -1.8808e-05, -2.1862e-05, 5.4553e-06,\n -4.1423e-05, -3.9965e-05, -3.6846e-05, 1.0273e-05, -1.2354e-05,\n -5.3270e-06, 1.3978e-05, -5.4717e-05, 1.0626e-05, 4.9464e-07,\n -3.3587e-06, -1.1656e-05, 2.0638e-06, -8.1557e-05, 2.5808e-06,\n -3.3713e-05, -3.9493e-05, -6.3734e-05, -2.3457e-06, -9.2212e-06,\n -7.7288e-05, -7.5941e-06, 1.5242e-05, 3.9439e-05, 2.7634e-06,\n -7.3686e-06, 2.0407e-05, -4.0521e-05, -1.9669e-06, -7.5466e-05,\n 1.3598e-05, -9.8927e-06, -5.2160e-06, -2.4658e-05, -4.0757e-06,\n 4.4552e-05, -2.6749e-05, -2.2270e-05, -3.1805e-05, -1.0712e-05,\n 1.6433e-05, -1.8040e-05, -3.5095e-05, -1.1186e-05, -3.6318e-05,\n -1.7602e-04, -2.5803e-05, -4.3011e-05, 2.0252e-05, -8.6196e-07,\n -4.7698e-05, 1.6713e-05, -2.2837e-05, 3.3369e-06, -5.9335e-05,\n -8.0605e-06, -1.7121e-05, 2.7405e-05, 1.9617e-05, -1.2151e-04,\n -2.8968e-05, -2.7040e-05, -2.3168e-05, -9.3032e-06, -5.2730e-05,\n -1.3832e-06, 7.8281e-06, -5.0352e-05, -4.2433e-05, -2.8030e-05,\n -8.7452e-05, -1.0784e-05, -3.2287e-05, -4.2189e-05, 1.1530e-05,\n -2.4430e-05, -3.0654e-05, -3.5034e-05, -4.6826e-06, -7.5372e-06,\n -5.7807e-05, 4.1649e-05, -2.2617e-05, -3.9433e-05, -1.0633e-05,\n -1.0871e-04, 1.0786e-05, -2.1020e-05, -3.3364e-05, 1.9217e-05,\n 1.3884e-05, -1.7569e-06, -3.6538e-05, -3.2153e-05, -1.0072e-04,\n -4.0901e-05, -9.1280e-06, -2.3362e-05, -1.6721e-05, -2.0493e-05,\n -3.1195e-05, -1.1132e-06, -2.4999e-05, 1.0741e-05, -1.3197e-05,\n -2.2390e-05, -4.2912e-05, -1.5454e-05, 4.1816e-05, -3.7787e-05,\n -3.3431e-05, -1.3867e-04, -1.8860e-05, -1.7100e-05, 4.0395e-06,\n -1.6632e-05, -4.7904e-05, -1.5087e-05, -1.1940e-05, -7.1852e-06,\n -2.0677e-05, -2.9028e-05, 3.7293e-05, -6.4095e-05, 7.9695e-06,\n -1.6030e-05, -1.8087e-05, -1.2560e-05, -2.3751e-05, 3.9389e-05,\n -1.1112e-05, -1.0841e-04, -3.4941e-05, -3.1649e-05, -1.6281e-05,\n -5.4390e-05, -6.3118e-05, -3.8409e-05, -4.1147e-05, -5.9649e-06,\n -3.1646e-05, 1.9542e-05, -2.1232e-05, -2.2674e-05, -2.5338e-05,\n 1.8096e-06, -1.6181e-05, -1.1496e-04, -2.4643e-05, 1.8393e-05,\n -2.8662e-05, 3.4307e-07, -2.2433e-05, -3.8953e-05, 7.3488e-06,\n -2.3404e-05, -2.8540e-05, -1.1607e-06, 1.1953e-05, -1.6386e-05,\n -1.7975e-05, -3.0675e-05, -1.9250e-05, -2.4491e-05, -1.7926e-05,\n -9.4159e-05, -1.8988e-05]), 'exp_avg_sq': tensor([9.0145e-09, 9.2372e-07, 1.1199e-07, 4.9085e-08, 7.7941e-09, 3.3554e-07,\n 8.3955e-09, 6.9804e-08, 1.4425e-08, 7.1573e-08, 3.6283e-06, 2.1332e-08,\n 2.4892e-08, 4.8549e-08, 1.0472e-07, 5.8346e-08, 3.8917e-08, 9.3508e-08,\n 1.0861e-07, 1.3128e-08, 2.3670e-07, 1.8682e-07, 1.6342e-07, 2.6788e-08,\n 6.8134e-08, 3.6879e-08, 9.0212e-09, 3.7658e-08, 1.9249e-07, 1.4557e-08,\n 7.9651e-08, 1.5377e-06, 2.9466e-08, 1.5984e-07, 3.3845e-09, 9.9510e-08,\n 4.2595e-08, 4.3220e-08, 1.2713e-07, 1.1236e-07, 2.6715e-07, 9.8482e-08,\n 1.9866e-08, 1.5908e-08, 1.8886e-08, 8.7227e-08, 7.3723e-08, 6.4812e-09,\n 3.1945e-08, 1.2253e-07, 7.5728e-08, 9.1379e-08, 2.6376e-08, 3.2043e-08,\n 5.6680e-08, 4.1273e-08, 5.1131e-08, 5.3220e-08, 1.7015e-07, 2.0550e-08,\n 1.0767e-07, 1.7905e-08, 1.0017e-07, 2.6460e-08, 5.3098e-08, 1.9893e-06,\n 6.3843e-07, 3.8500e-07, 1.4674e-07, 1.5991e-08, 8.0146e-08, 1.1432e-07,\n 3.3814e-08, 8.3484e-08, 3.2847e-07, 1.7559e-07, 3.6644e-08, 2.1640e-07,\n 1.1406e-07, 3.9928e-07, 6.6869e-09, 1.3065e-08, 2.7416e-07, 6.1043e-08,\n 1.1366e-08, 1.7998e-08, 1.9978e-06, 4.1964e-08, 2.1238e-07, 9.1131e-09,\n 6.3577e-08, 2.3765e-08, 9.3532e-09, 3.5495e-08, 1.3149e-07, 6.9896e-08,\n 5.5412e-08, 1.8886e-08, 2.2528e-08, 3.0092e-08, 2.8331e-07, 6.6749e-08,\n 3.8772e-08, 5.5761e-08, 2.4055e-08, 2.6751e-08, 6.3847e-07, 3.6489e-07,\n 8.3740e-08, 1.2602e-07, 1.9991e-08, 1.5036e-06, 4.6659e-08, 4.0329e-07,\n 3.0688e-08, 7.0997e-09, 1.6158e-06, 1.2052e-07, 2.6962e-08, 3.2461e-08,\n 2.9578e-07, 6.7219e-08, 1.1462e-08, 1.9083e-07, 4.4830e-08, 5.9923e-08,\n 8.5163e-08, 2.0524e-08, 1.5899e-07, 1.2633e-07, 2.6327e-07, 3.0378e-08,\n 7.4638e-08, 9.5974e-08, 1.9973e-07, 8.5417e-08, 5.8488e-08, 3.0812e-07,\n 8.6275e-07, 5.7706e-08, 8.3737e-08, 8.7226e-08, 1.0376e-08, 2.2069e-07,\n 8.0093e-08, 2.8734e-08, 2.1540e-08, 2.5642e-07, 1.6907e-08, 2.4018e-07,\n 3.8797e-08, 6.1040e-08, 1.5276e-07, 2.1280e-08, 2.9952e-08, 1.8668e-07,\n 3.4534e-08, 3.2181e-08, 2.2223e-08, 2.2428e-09, 4.3553e-07, 2.1496e-08,\n 5.0017e-08, 2.9244e-08, 3.3207e-08, 4.0047e-08, 7.9413e-08, 1.2995e-07,\n 5.8928e-08, 8.2580e-08, 2.0694e-08, 2.7760e-08, 2.0835e-08, 3.1419e-10,\n 5.0505e-08, 2.0138e-08, 3.5458e-08, 1.9005e-08, 9.2969e-09, 6.7452e-08,\n 1.5797e-07, 1.0606e-07, 4.8754e-09, 5.4186e-08, 1.4572e-08, 3.5692e-08,\n 3.7174e-08, 1.5805e-07, 2.8556e-08, 2.5284e-08, 3.7446e-07, 1.9476e-07,\n 2.7103e-08, 2.7845e-08, 7.6578e-08, 4.2635e-07, 6.6596e-08, 2.1340e-07,\n 1.9300e-08, 1.0991e-08, 2.1538e-07, 1.6197e-08, 1.6114e-07, 5.1086e-07,\n 2.6481e-08, 2.2784e-08, 3.2060e-07, 3.6655e-07, 5.1054e-07, 1.5909e-07,\n 1.2861e-08, 6.3998e-06, 5.6522e-08, 7.0314e-08, 9.4738e-08, 3.5265e-08,\n 1.6989e-08, 2.6630e-07, 7.0757e-08, 1.2147e-07, 7.9473e-07, 1.0626e-06,\n 5.6246e-07, 6.9514e-09, 7.0973e-08, 7.4650e-09, 1.2563e-08, 4.9847e-09,\n 2.4331e-08, 1.1188e-06, 4.3928e-08, 9.2866e-08, 1.0962e-07, 5.6019e-07,\n 1.9565e-07, 1.3688e-08, 1.0659e-07, 4.3151e-07, 5.3743e-07, 3.2106e-08,\n 4.0462e-08, 1.3915e-07, 2.1775e-08, 7.2388e-08, 2.2274e-06, 7.9064e-08,\n 1.3129e-07, 2.0727e-08, 3.9059e-08, 9.4977e-08, 1.3313e-07, 1.0824e-07,\n 2.6644e-08, 7.5708e-08, 9.8391e-09, 2.4677e-08, 3.6953e-08, 2.6191e-08,\n 9.8592e-09, 7.2445e-08, 1.3029e-07, 1.0700e-06, 3.0924e-08, 4.9284e-08,\n 5.6415e-08, 5.3594e-07, 9.3039e-08, 1.2270e-07, 2.2020e-07, 3.3836e-08,\n 1.4338e-09, 1.7991e-06, 5.6355e-08, 2.5490e-07, 1.1658e-07, 2.2787e-08,\n 1.5579e-06, 4.6063e-08, 9.1742e-08, 4.9854e-09, 2.9457e-08, 7.6897e-08,\n 2.0481e-08, 1.3748e-07, 9.2199e-08, 6.4183e-09, 1.0328e-08, 4.9151e-08,\n 1.6834e-08, 1.7606e-07, 3.4170e-07, 3.6454e-07, 2.8468e-07, 5.7557e-08,\n 3.0988e-08, 1.3464e-07, 6.3850e-08, 1.2455e-07, 4.6513e-08, 6.0102e-08,\n 2.0354e-07, 3.6188e-08, 1.7559e-07, 6.6851e-09, 1.1498e-07, 8.1900e-08,\n 1.0483e-07, 1.0201e-07, 6.4956e-08, 3.7567e-08, 2.4693e-08, 3.1080e-07,\n 3.5430e-08, 3.7615e-08, 2.7725e-08, 1.3190e-07, 1.3554e-08, 9.4840e-08,\n 2.0189e-07, 9.2632e-08, 5.6293e-08, 1.2488e-08, 1.6005e-08, 1.7991e-08,\n 1.0135e-08, 1.2336e-07, 3.1506e-08, 1.2337e-07, 5.6445e-08, 1.0274e-07,\n 6.5359e-08, 1.0479e-07, 7.6335e-08, 9.3817e-09, 3.0762e-07, 1.3237e-07,\n 7.6285e-08, 3.0424e-08, 7.9933e-08, 9.8310e-08, 2.4747e-07, 4.7281e-08,\n 4.8434e-08, 1.0188e-07, 1.0765e-08, 1.9205e-07, 1.1546e-07, 1.0772e-07,\n 2.7946e-08, 4.1237e-08, 8.7788e-08, 1.3485e-08, 1.5214e-07, 1.1920e-08,\n 1.3851e-08, 6.0884e-09, 5.7998e-08, 2.0993e-08, 9.3345e-07, 1.0304e-08,\n 1.0355e-07, 1.5521e-07, 5.6761e-07, 4.7940e-08, 1.4895e-08, 6.9981e-07,\n 6.7372e-08, 5.7543e-08, 3.1397e-08, 3.3694e-09, 6.3703e-09, 2.9252e-08,\n 4.2646e-07, 2.9761e-09, 5.9870e-07, 1.4385e-08, 2.3373e-08, 1.8235e-08,\n 1.7878e-07, 1.1107e-08, 1.2928e-07, 8.5855e-08, 3.2214e-08, 2.8425e-07,\n 9.4619e-09, 6.2754e-09, 7.6315e-08, 1.6580e-07, 3.4736e-08, 1.8457e-07,\n 2.9955e-06, 4.2022e-08, 1.5513e-07, 3.0677e-08, 3.1831e-08, 1.2226e-07,\n 1.4114e-08, 9.4966e-08, 1.5941e-09, 1.6112e-07, 1.5056e-08, 2.5737e-08,\n 1.0495e-08, 1.0614e-08, 9.5324e-07, 8.2422e-08, 7.2167e-08, 3.7974e-08,\n 9.0369e-09, 6.4026e-08, 1.0592e-08, 7.6299e-08, 2.4466e-07, 2.1987e-07,\n 7.2994e-08, 1.0944e-06, 5.5325e-08, 7.9975e-08, 1.9444e-07, 5.9570e-08,\n 2.6503e-08, 7.6080e-08, 9.4392e-08, 3.8013e-08, 9.5712e-09, 2.6020e-07,\n 3.5405e-08, 3.8745e-08, 1.4788e-07, 1.0777e-08, 4.8080e-07, 9.6817e-09,\n 4.4093e-08, 1.5605e-07, 8.8381e-09, 3.2506e-08, 2.7112e-08, 1.0318e-07,\n 1.1859e-07, 5.0994e-07, 1.4441e-07, 4.5618e-08, 6.3629e-08, 4.2437e-08,\n 2.1709e-08, 4.6847e-08, 8.5891e-09, 7.3219e-08, 1.7116e-08, 4.8730e-08,\n 2.8868e-08, 3.4640e-07, 4.0631e-08, 4.7488e-08, 8.0800e-08, 6.7699e-08,\n 9.5235e-07, 1.2056e-07, 2.4202e-08, 1.9936e-08, 3.7317e-08, 1.4464e-07,\n 1.5341e-08, 6.0975e-09, 5.7148e-08, 7.6745e-08, 8.2753e-08, 3.8826e-08,\n 3.7562e-07, 5.8893e-09, 2.9638e-08, 3.8152e-08, 2.8500e-08, 7.4960e-08,\n 2.7826e-08, 3.4993e-08, 9.5760e-07, 1.8061e-07, 1.0838e-07, 3.7377e-08,\n 2.6476e-07, 3.3269e-07, 1.4276e-07, 1.4828e-07, 1.9259e-08, 1.1539e-07,\n 7.3356e-09, 5.5713e-08, 6.9167e-08, 1.1347e-07, 5.9729e-09, 2.1853e-08,\n 1.5983e-06, 1.8528e-07, 1.7304e-08, 4.6275e-08, 1.7054e-11, 3.4017e-08,\n 1.6383e-07, 1.2082e-08, 6.5467e-08, 6.8593e-08, 1.4304e-08, 6.4014e-08,\n 3.4647e-08, 6.5422e-08, 1.5345e-07, 2.2260e-08, 5.5310e-08, 2.8766e-08,\n 6.1438e-07, 3.4672e-08])}, 156: {'step': 7160, 'exp_avg': tensor([[[[-4.1301e-07]],\n\n [[ 4.9083e-07]],\n\n [[-4.3765e-07]],\n\n ...,\n\n [[-4.6796e-07]],\n\n [[ 4.0509e-07]],\n\n [[-2.6740e-07]]],\n\n\n [[[-1.2915e-07]],\n\n [[-8.0551e-07]],\n\n [[-2.9249e-07]],\n\n ...,\n\n [[-1.6251e-07]],\n\n [[-6.0179e-07]],\n\n [[-3.5225e-09]]],\n\n\n [[[-5.7408e-08]],\n\n [[-2.2088e-07]],\n\n [[-1.0065e-07]],\n\n ...,\n\n [[-6.4225e-08]],\n\n [[-1.9478e-07]],\n\n [[-2.1227e-08]]],\n\n\n ...,\n\n\n [[[-1.3530e-07]],\n\n [[ 1.4933e-07]],\n\n [[-1.6596e-07]],\n\n ...,\n\n [[-1.3967e-07]],\n\n [[-8.8059e-09]],\n\n [[-5.1303e-08]]],\n\n\n [[[-3.3292e-08]],\n\n [[-3.1497e-07]],\n\n [[-8.7057e-08]],\n\n ...,\n\n [[-5.3159e-08]],\n\n [[-2.2081e-07]],\n\n [[ 2.8981e-08]]],\n\n\n [[[ 5.4105e-08]],\n\n [[-6.4987e-07]],\n\n [[-5.3566e-08]],\n\n ...,\n\n [[ 3.7233e-08]],\n\n [[-3.8866e-07]],\n\n [[ 2.1878e-07]]]]), 'exp_avg_sq': tensor([[[[1.0302e-11]],\n\n [[1.5788e-11]],\n\n [[1.1486e-11]],\n\n ...,\n\n [[7.7553e-12]],\n\n [[6.7434e-11]],\n\n [[7.5468e-12]]],\n\n\n [[[6.7646e-12]],\n\n [[8.2139e-11]],\n\n [[1.9387e-11]],\n\n ...,\n\n [[1.1573e-11]],\n\n [[5.3264e-11]],\n\n [[2.7373e-12]]],\n\n\n [[[3.7167e-13]],\n\n [[2.9695e-12]],\n\n [[9.0064e-13]],\n\n ...,\n\n [[5.1761e-13]],\n\n [[3.1453e-12]],\n\n [[1.4927e-13]]],\n\n\n ...,\n\n\n [[[1.3079e-12]],\n\n [[2.2809e-12]],\n\n [[1.8412e-12]],\n\n ...,\n\n [[1.4048e-12]],\n\n [[1.3607e-12]],\n\n [[8.5499e-13]]],\n\n\n [[[3.5052e-13]],\n\n [[5.2002e-12]],\n\n [[1.0050e-12]],\n\n ...,\n\n [[6.5819e-13]],\n\n [[3.0012e-12]],\n\n [[5.6976e-13]]],\n\n\n [[[5.0688e-12]],\n\n [[6.4465e-11]],\n\n [[8.0257e-12]],\n\n ...,\n\n [[6.4337e-12]],\n\n [[2.7646e-11]],\n\n [[1.0770e-11]]]])}, 157: {'step': 7160, 'exp_avg': tensor([-3.8741e-07, -1.1775e-06, -2.1223e-07, ..., -3.7851e-07,\n -6.0872e-07, -2.1959e-06]), 'exp_avg_sq': tensor([8.0001e-11, 2.6435e-10, 6.7606e-12, ..., 5.1570e-11, 5.3213e-11,\n 6.7949e-10])}, 158: {'step': 7160, 'exp_avg': tensor([ 1.3273e-06, -1.2728e-06, -2.9862e-07, ..., 6.1790e-07,\n -6.2399e-07, -2.0458e-06]), 'exp_avg_sq': tensor([5.0450e-10, 2.9731e-10, 7.9486e-12, ..., 1.8564e-10, 4.1279e-11,\n 6.2198e-10])}, 159: {'step': 7160, 'exp_avg': tensor([[ 1.2290e-05, 8.4663e-05, 5.9159e-05, ..., -3.7607e-06,\n 5.2114e-05, 5.8358e-05],\n [-1.2112e-05, -8.4325e-05, -5.8714e-05, ..., 4.0415e-06,\n -5.1705e-05, -5.8195e-05]]), 'exp_avg_sq': tensor([[1.2432e-07, 1.1153e-06, 5.5024e-07, ..., 5.6599e-08, 6.2604e-07,\n 5.3612e-07],\n [1.2401e-07, 1.1184e-06, 5.5141e-07, ..., 5.6733e-08, 6.2798e-07,\n 5.3749e-07]])}, 160: {'step': 7160, 'exp_avg': tensor([ 0.0001, -0.0001]), 'exp_avg_sq': tensor([2.4855e-06, 2.4743e-06])}}, 'param_groups': [{'lr': 5e-05, 'betas': (0.9, 0.999), 'eps': 1e-08, 'weight_decay': 0, 'amsgrad': False, 'params': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160]}]}]", + "lr_schedulers": [ + { + "factor": 0.5, + "min_lrs": [ + 0 + ], + "patience": 10, + "verbose": true, + "cooldown": 0, + "cooldown_counter": 0, + "mode": "min", + "threshold": 0.0001, + "threshold_mode": "rel", + "best": 0.34857404232025146, + "num_bad_epochs": 10, + "mode_worse": Infinity, + "eps": 1e-08, + "last_epoch": 40, + "_last_lr": [ + 5e-05 + ] + } + ] +} \ No newline at end of file