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aten.max_pool2d_with_indices_backward.default
TorchBench/squeezenet1_1
((T([32, 256, 13, 13], f16), T([32, 256, 27, 27], f16), [3, 3], [2, 2], [0, 0], [1, 1], True, T([32, 256, 13, 13], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/timm_vovnet
((T([32, 256, 28, 28], f16), T([32, 256, 56, 56], f16), [3, 3], [2, 2], [0, 0], [1, 1], True, T([32, 256, 28, 28], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/timm_vovnet
((T([32, 512, 14, 14], f16), T([32, 512, 28, 28], f16), [3, 3], [2, 2], [0, 0], [1, 1], True, T([32, 512, 14, 14], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/squeezenet1_1
((T([32, 64, 55, 55], f16), T([32, 64, 111, 111], f16), [3, 3], [2, 2], [0, 0], [1, 1], True, T([32, 64, 55, 55], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/swsl_resnext101_32x16d
((T([32, 64, 56, 56], f16), T([32, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([32, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/resnet50
((T([32, 64, 56, 56], f16), T([32, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([32, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/timm_resnest
((T([32, 64, 56, 56], f16), T([32, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([32, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/timm_vovnet
((T([32, 768, 7, 7], f16), T([32, 768, 14, 14], f16), [3, 3], [2, 2], [0, 0], [1, 1], True, T([32, 768, 7, 7], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/densenet121
((T([4, 64, 56, 56], f16), T([4, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([4, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/maml_omniglot
((T([5, 64, 1, 1], f16), T([5, 64, 3, 3], f16, stride=(576, 1, 192, 64)), [2, 2], [2, 2], [0, 0], [1, 1], False, T([5, 64, 1, 1], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/maml_omniglot
((T([5, 64, 13, 13], f16, stride=(10816, 1, 832, 64)), T([5, 64, 26, 26], f16, stride=(43264, 1, 1664, 64)), [2, 2], [2, 2], [0, 0], [1, 1], False, T([5, 64, 13, 13], i64, stride=(10816, 1, 832, 64))), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/maml_omniglot
((T([5, 64, 5, 5], f16, stride=(1600, 1, 320, 64)), T([5, 64, 11, 11], f16, stride=(7744, 1, 704, 64)), [2, 2], [2, 2], [0, 0], [1, 1], False, T([5, 64, 5, 5], i64, stride=(1600, 1, 320, 64))), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/Super_SloMo
((T([6, 128, 88, 88], f16), T([6, 128, 176, 176], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([6, 128, 88, 88], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/Super_SloMo
((T([6, 256, 44, 44], f16), T([6, 256, 88, 88], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([6, 256, 44, 44], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/Super_SloMo
((T([6, 64, 176, 176], f16), T([6, 64, 352, 352], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([6, 64, 176, 176], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/dla102
((T([64, 128, 28, 28], f16), T([64, 128, 56, 56], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 128, 28, 28], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/dla102
((T([64, 128, 28, 28], f16, stride=(903168, 784, 28, 1)), T([64, 128, 56, 56], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 128, 28, 28], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/vgg16
((T([64, 128, 56, 56], f16), T([64, 128, 112, 112], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 128, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/dla102
((T([64, 256, 14, 14], f16), T([64, 256, 28, 28], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 256, 14, 14], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/dla102
((T([64, 256, 14, 14], f16, stride=(551936, 196, 14, 1)), T([64, 256, 28, 28], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 256, 14, 14], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/vgg16
((T([64, 256, 28, 28], f16), T([64, 256, 56, 56], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 256, 28, 28], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/jx_nest_base
((T([64, 256, 28, 28], f16, stride=(200704, 1, 7168, 256)), T([64, 256, 57, 57], f16, stride=(831744, 1, 14592, 256)), [3, 3], [2, 2], [0, 0], [1, 1], False, T([64, 256, 28, 28], i64, stride=(200704, 1, 7168, 256))), {})
aten.max_pool2d_with_indices_backward.default
TIMM/dla102
((T([64, 32, 56, 56], f16), T([64, 32, 112, 112], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 32, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/vgg16
((T([64, 512, 14, 14], f16), T([64, 512, 28, 28], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 512, 14, 14], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/jx_nest_base
((T([64, 512, 14, 14], f16), T([64, 512, 29, 29], f16, stride=(430592, 1, 14848, 512)), [3, 3], [2, 2], [0, 0], [1, 1], False, T([64, 512, 14, 14], i64, stride=(100352, 1, 7168, 512))), {})
aten.max_pool2d_with_indices_backward.default
TIMM/dla102
((T([64, 512, 7, 7], f16), T([64, 512, 14, 14], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 512, 7, 7], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/vgg16
((T([64, 512, 7, 7], f16), T([64, 512, 14, 14], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 512, 7, 7], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/vgg16
((T([64, 64, 112, 112], f16), T([64, 64, 224, 224], f16), [2, 2], [2, 2], [0, 0], [1, 1], False, T([64, 64, 112, 112], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/densenet121
((T([64, 64, 56, 56], f16), T([64, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([64, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/ecaresnet101d
((T([64, 64, 56, 56], f16), T([64, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([64, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TIMM/res2net101_26w_4s
((T([64, 64, 56, 56], f16), T([64, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([64, 64, 56, 56], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/yolov3
((T([8, 512, 12, 16], f16, stride=(393216, 192, 16, 1)), T([8, 512, 12, 16], f16), [13, 13], [1, 1], [6, 6], [1, 1], False, T([8, 512, 12, 16], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/yolov3
((T([8, 512, 12, 16], f16, stride=(393216, 192, 16, 1)), T([8, 512, 12, 16], f16), [5, 5], [1, 1], [2, 2], [1, 1], False, T([8, 512, 12, 16], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/yolov3
((T([8, 512, 12, 16], f16, stride=(393216, 192, 16, 1)), T([8, 512, 12, 16], f16), [9, 9], [1, 1], [4, 4], [1, 1], False, T([8, 512, 12, 16], i64)), {})
aten.max_pool2d_with_indices_backward.default
TorchBench/resnext50_32x4d
((T([8, 64, 56, 56], f16), T([8, 64, 112, 112], f16), [3, 3], [2, 2], [1, 1], [1, 1], False, T([8, 64, 56, 56], i64)), {})
aten.maximum.default
HuggingFace/OPTForCausalLM
((T([4, 12, 128, 128], f16), T([], f32)), {})
aten.mean.default
TorchBench/Super_SloMo
((T([6, 2, 351, 352], f16),), {})
aten.mean.default
TorchBench/Super_SloMo
((T([6, 2, 352, 351], f16),), {})
aten.mean.default
TorchBench/Super_SloMo
((T([6, 3, 352, 352], f16),), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 1152, 20, 20], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 144, 160, 160], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 144, 80, 80], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 16, 320, 320], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 1920, 20, 20], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 240, 40, 40], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 240, 80, 80], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 32, 320, 320], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 480, 40, 40], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 672, 20, 20], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 672, 40, 40], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientdet
((T([1, 96, 160, 160], f16), [2, 3], True), {})
aten.mean.dim
TIMM/selecsls42b
((T([128, 1024, 4, 4], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/ese_vovnet19b_dw
((T([128, 1024, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/shufflenet_v2_x1_0
((T([128, 1024, 7, 7], f16), [2, 3]), {})
aten.mean.dim
TIMM/ese_vovnet19b_dw
((T([128, 1024, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 1044, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/fbnetv3_b
((T([128, 1104, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 1152, 6, 6], f16), [2, 3], True), {})
aten.mean.dim
TIMM/hardcorenas_a
((T([128, 1152, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 1152, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/fbnetv3_b
((T([128, 120, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ghostnet_100
((T([128, 120, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilenetv3_large_100
((T([128, 120, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/eca_botnext26ts_256
((T([128, 128, 32, 32], f16), [2, 3]), {})
aten.mean.dim
TIMM/eca_halonext26ts
((T([128, 128, 32, 32], f16), [2, 3]), {})
aten.mean.dim
TIMM/lcnet_050
((T([128, 128, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 1280, 6, 6], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/mnasnet_100
((T([128, 1280, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/mobilenetv2_100
((T([128, 1280, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 1280, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/spnasnet_100
((T([128, 1280, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 1280, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/fbnetv3_b
((T([128, 1344, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/repvgg_a2
((T([128, 1408, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 144, 24, 24], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 144, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tinynet_a
((T([128, 144, 48, 48], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_efficientnet_b0
((T([128, 144, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/regnety_002
((T([128, 152, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/dm_nfnet_f0
((T([128, 1536, 12, 12], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_nfnet
((T([128, 1536, 12, 12], f16), [2, 3], True), {})
aten.mean.dim
TIMM/nfnet_l0
((T([128, 1536, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/dm_nfnet_f0
((T([128, 1536, 6, 6], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_nfnet
((T([128, 1536, 6, 6], f16), [2, 3], True), {})
aten.mean.dim
TIMM/nfnet_l0
((T([128, 1536, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/levit_128
((T([128, 16, 384], f16), [1]), {})
aten.mean.dim
TIMM/resmlp_12_224
((T([128, 196, 384], f16, stride=(75264, 1, 196)), [1]), {})
aten.mean.dim
TIMM/fbnetc_100
((T([128, 1984, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/hrnet_w18
((T([128, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/res2net50_14w_8s
((T([128, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/res2next50
((T([128, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/adv_inception_v3
((T([128, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/botnet26t_256
((T([128, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/eca_botnext26ts_256
((T([128, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/eca_halonext26ts
((T([128, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/gluon_inception_v3
((T([128, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/inception_v3
((T([128, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/rexnet_100
((T([128, 228, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/nfnet_l0
((T([128, 2304, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/regnety_002
((T([128, 24, 56, 56], f16), [2, 3], True), {})