diff --git "a/Embedding.mlmodelc/model.mil" "b/Embedding.mlmodelc/model.mil" --- "a/Embedding.mlmodelc/model.mil" +++ "b/Embedding.mlmodelc/model.mil" @@ -1,441 +1,524 @@ program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.8.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})] { - func main(tensor fbank, tensor weights) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"fbank", [1, 1, 80, 998]}, {"weights", [1, 589]}}), ("RangeDims", {{"fbank", [[1, 32], [1, 1], [80, 80], [998, 998]]}, {"weights", [[1, 32], [589, 589]]}})))] { - tensor var_5 = const()[name = tensor("op_5"), val = tensor(-1)]; - tensor input_1_pad_type_0 = const()[name = tensor("input_1_pad_type_0"), val = tensor("custom")]; - tensor input_1_pad_0 = const()[name = tensor("input_1_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_1_strides_0 = const()[name = tensor("input_1_strides_0"), val = tensor([1, 1])]; - tensor input_1_dilations_0 = const()[name = tensor("input_1_dilations_0"), val = tensor([1, 1])]; - tensor input_1_groups_0 = const()[name = tensor("input_1_groups_0"), val = tensor(1)]; - tensor fbank_to_fp16_dtype_0 = const()[name = tensor("fbank_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor const_2_to_fp16 = const()[name = tensor("const_2_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; - tensor const_3_to_fp16 = const()[name = tensor("const_3_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(704)))]; - tensor fbank_to_fp16 = cast(dtype = fbank_to_fp16_dtype_0, x = fbank)[name = tensor("cast_22")]; - tensor input_3_cast_fp16 = conv(bias = const_3_to_fp16, dilations = input_1_dilations_0, groups = input_1_groups_0, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = input_1_strides_0, weight = const_2_to_fp16, x = fbank_to_fp16)[name = tensor("input_3_cast_fp16")]; - tensor input_5_cast_fp16 = relu(x = input_3_cast_fp16)[name = tensor("input_5_cast_fp16")]; + func main(tensor audio_and_weights) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"audio_and_weights", [1, 1, 1, 160589]}}), ("RangeDims", {{"audio_and_weights", [[1, 32], [1, 1], [1, 1], [160589, 160589]]}})))] { + tensor _interp_right_weight = const()[name = tensor("_interp_right_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor _interp_left_weight = const()[name = tensor("_interp_left_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(640)))]; + tensor _fbank_mel_weight = const()[name = tensor("_fbank_mel_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1216)))]; + tensor _fbank_dft_imag_weight = const()[name = tensor("_fbank_dft_imag_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83520)))]; + tensor _fbank_dft_real_weight = const()[name = tensor("_fbank_dft_real_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(609920)))]; + tensor _fbank_window = const()[name = tensor("_fbank_window"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1136320)))]; + tensor _fbank_eps = const()[name = tensor("_fbank_eps"), val = tensor(0x1.b7cdfep-34)]; + tensor _fbank_frame_kernel = const()[name = tensor("_fbank_frame_kernel"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1137984)))]; + tensor resnet_seg_1_bias = const()[name = tensor("resnet_seg_1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1778048)))]; + tensor resnet_seg_1_weight = const()[name = tensor("resnet_seg_1_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1779136)))]; + tensor var_24_begin_0 = const()[name = tensor("op_24_begin_0"), val = tensor([0, 0, 0, 0])]; + tensor var_24_end_0 = const()[name = tensor("op_24_end_0"), val = tensor([0, 1, 1, 160000])]; + tensor var_24_end_mask_0 = const()[name = tensor("op_24_end_mask_0"), val = tensor([true, true, true, false])]; + tensor var_24 = slice_by_index(begin = var_24_begin_0, end = var_24_end_0, end_mask = var_24_end_mask_0, x = audio_and_weights)[name = tensor("op_24")]; + tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([-1, 1, 160000])]; + tensor waveforms_1 = reshape(shape = concat_0x, x = var_24)[name = tensor("waveforms_1")]; + tensor var_33_begin_0 = const()[name = tensor("op_33_begin_0"), val = tensor([0, 0, 0, 160000])]; + tensor var_33_end_0 = const()[name = tensor("op_33_end_0"), val = tensor([0, 1, 1, 160589])]; + tensor var_33_end_mask_0 = const()[name = tensor("op_33_end_mask_0"), val = tensor([true, true, true, true])]; + tensor var_33 = slice_by_index(begin = var_33_begin_0, end = var_33_end_0, end_mask = var_33_end_mask_0, x = audio_and_weights)[name = tensor("op_33")]; + tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([-1, 589])]; + tensor weights_1 = reshape(shape = concat_1x, x = var_33)[name = tensor("weights_1")]; + tensor var_36_promoted = const()[name = tensor("op_36_promoted"), val = tensor(0x1p+15)]; + tensor waveforms_3 = mul(x = waveforms_1, y = var_36_promoted)[name = tensor("waveforms_3")]; + tensor frames_1_pad_type_0 = const()[name = tensor("frames_1_pad_type_0"), val = tensor("valid")]; + tensor frames_1_strides_0 = const()[name = tensor("frames_1_strides_0"), val = tensor([160])]; + tensor frames_1_pad_0 = const()[name = tensor("frames_1_pad_0"), val = tensor([0, 0])]; + tensor frames_1_dilations_0 = const()[name = tensor("frames_1_dilations_0"), val = tensor([1])]; + tensor frames_1_groups_0 = const()[name = tensor("frames_1_groups_0"), val = tensor(1)]; + tensor frames_1 = conv(dilations = frames_1_dilations_0, groups = frames_1_groups_0, pad = frames_1_pad_0, pad_type = frames_1_pad_type_0, strides = frames_1_strides_0, weight = _fbank_frame_kernel, x = waveforms_3)[name = tensor("frames_1")]; + tensor frames_3_perm_0 = const()[name = tensor("frames_3_perm_0"), val = tensor([0, 2, 1])]; + tensor concat_2x = const()[name = tensor("concat_2x"), val = tensor([-1, 400])]; + tensor frames_3 = transpose(perm = frames_3_perm_0, x = frames_1)[name = tensor("transpose_1")]; + tensor frames_5 = reshape(shape = concat_2x, x = frames_3)[name = tensor("frames_5")]; + tensor var_86_axes_0 = const()[name = tensor("op_86_axes_0"), val = tensor([1])]; + tensor var_86_keep_dims_0 = const()[name = tensor("op_86_keep_dims_0"), val = tensor(true)]; + tensor var_86 = reduce_mean(axes = var_86_axes_0, keep_dims = var_86_keep_dims_0, x = frames_5)[name = tensor("op_86")]; + tensor frames_7 = sub(x = frames_5, y = var_86)[name = tensor("frames_7")]; + tensor input_1_axes_0 = const()[name = tensor("input_1_axes_0"), val = tensor([1])]; + tensor input_1 = expand_dims(axes = input_1_axes_0, x = frames_7)[name = tensor("input_1")]; + tensor const_0 = const()[name = tensor("const_0"), val = tensor(0x0p+0)]; + tensor var_90_pad_0 = const()[name = tensor("op_90_pad_0"), val = tensor([0, 0, 0, 0, 1, 0])]; + tensor var_90_mode_0 = const()[name = tensor("op_90_mode_0"), val = tensor("replicate")]; + tensor var_90 = pad(constant_val = const_0, mode = var_90_mode_0, pad = var_90_pad_0, x = input_1)[name = tensor("op_90")]; + tensor padded_axes_0 = const()[name = tensor("padded_axes_0"), val = tensor([1])]; + tensor padded = squeeze(axes = padded_axes_0, x = var_90)[name = tensor("padded")]; + tensor var_93_begin_0 = const()[name = tensor("op_93_begin_0"), val = tensor([0, 0])]; + tensor var_93_end_0 = const()[name = tensor("op_93_end_0"), val = tensor([0, 400])]; + tensor var_93_end_mask_0 = const()[name = tensor("op_93_end_mask_0"), val = tensor([true, false])]; + tensor var_93 = slice_by_index(begin = var_93_begin_0, end = var_93_end_0, end_mask = var_93_end_mask_0, x = padded)[name = tensor("op_93")]; + tensor var_94 = const()[name = tensor("op_94"), val = tensor(0x1.f0a3d8p-1)]; + tensor var_95 = mul(x = var_93, y = var_94)[name = tensor("op_95")]; + tensor frames_9 = sub(x = frames_7, y = var_95)[name = tensor("frames_9")]; + tensor frames_11 = mul(x = frames_9, y = _fbank_window)[name = tensor("frames_11")]; + tensor input_3_axes_0 = const()[name = tensor("input_3_axes_0"), val = tensor([1])]; + tensor input_3 = expand_dims(axes = input_3_axes_0, x = frames_11)[name = tensor("input_3")]; + tensor const_1 = const()[name = tensor("const_1"), val = tensor(0x0p+0)]; + tensor var_100_pad_0 = const()[name = tensor("op_100_pad_0"), val = tensor([0, 0, 0, 0, 0, 112])]; + tensor var_100_mode_0 = const()[name = tensor("op_100_mode_0"), val = tensor("constant")]; + tensor var_100 = pad(constant_val = const_1, mode = var_100_mode_0, pad = var_100_pad_0, x = input_3)[name = tensor("op_100")]; + tensor var_107_pad_type_0 = const()[name = tensor("op_107_pad_type_0"), val = tensor("valid")]; + tensor var_107_strides_0 = const()[name = tensor("op_107_strides_0"), val = tensor([1])]; + tensor var_107_pad_0 = const()[name = tensor("op_107_pad_0"), val = tensor([0, 0])]; + tensor var_107_dilations_0 = const()[name = tensor("op_107_dilations_0"), val = tensor([1])]; + tensor var_107_groups_0 = const()[name = tensor("op_107_groups_0"), val = tensor(1)]; + tensor var_107 = conv(dilations = var_107_dilations_0, groups = var_107_groups_0, pad = var_107_pad_0, pad_type = var_107_pad_type_0, strides = var_107_strides_0, weight = _fbank_dft_real_weight, x = var_100)[name = tensor("op_107")]; + tensor real_axes_0 = const()[name = tensor("real_axes_0"), val = tensor([-1])]; + tensor real = squeeze(axes = real_axes_0, x = var_107)[name = tensor("real")]; + tensor var_113_pad_type_0 = const()[name = tensor("op_113_pad_type_0"), val = tensor("valid")]; + tensor var_113_strides_0 = const()[name = tensor("op_113_strides_0"), val = tensor([1])]; + tensor var_113_pad_0 = const()[name = tensor("op_113_pad_0"), val = tensor([0, 0])]; + tensor var_113_dilations_0 = const()[name = tensor("op_113_dilations_0"), val = tensor([1])]; + tensor var_113_groups_0 = const()[name = tensor("op_113_groups_0"), val = tensor(1)]; + tensor var_113 = conv(dilations = var_113_dilations_0, groups = var_113_groups_0, pad = var_113_pad_0, pad_type = var_113_pad_type_0, strides = var_113_strides_0, weight = _fbank_dft_imag_weight, x = var_100)[name = tensor("op_113")]; + tensor imag_axes_0 = const()[name = tensor("imag_axes_0"), val = tensor([-1])]; + tensor imag = squeeze(axes = imag_axes_0, x = var_113)[name = tensor("imag")]; + tensor var_55_promoted = const()[name = tensor("op_55_promoted"), val = tensor(0x1p+1)]; + tensor var_115 = pow(x = real, y = var_55_promoted)[name = tensor("op_115")]; + tensor var_55_promoted_1 = const()[name = tensor("op_55_promoted_1"), val = tensor(0x1p+1)]; + tensor var_116 = pow(x = imag, y = var_55_promoted_1)[name = tensor("op_116")]; + tensor power = add(x = var_115, y = var_116)[name = tensor("power")]; + tensor var_118_axes_0 = const()[name = tensor("op_118_axes_0"), val = tensor([-1])]; + tensor var_118 = expand_dims(axes = var_118_axes_0, x = power)[name = tensor("op_118")]; + tensor var_123_pad_type_0 = const()[name = tensor("op_123_pad_type_0"), val = tensor("valid")]; + tensor var_123_strides_0 = const()[name = tensor("op_123_strides_0"), val = tensor([1])]; + tensor var_123_pad_0 = const()[name = tensor("op_123_pad_0"), val = tensor([0, 0])]; + tensor var_123_dilations_0 = const()[name = tensor("op_123_dilations_0"), val = tensor([1])]; + tensor var_123_groups_0 = const()[name = tensor("op_123_groups_0"), val = tensor(1)]; + tensor var_123 = conv(dilations = var_123_dilations_0, groups = var_123_groups_0, pad = var_123_pad_0, pad_type = var_123_pad_type_0, strides = var_123_strides_0, weight = _fbank_mel_weight, x = var_118)[name = tensor("op_123")]; + tensor mel_1_axes_0 = const()[name = tensor("mel_1_axes_0"), val = tensor([-1])]; + tensor mel_1 = squeeze(axes = mel_1_axes_0, x = var_123)[name = tensor("mel_1")]; + tensor const_2 = const()[name = tensor("const_2"), val = tensor(0x1.fffffep+127)]; + tensor clip_0 = clip(alpha = _fbank_eps, beta = const_2, x = mel_1)[name = tensor("clip_0")]; + tensor mel_epsilon_0 = const()[name = tensor("mel_epsilon_0"), val = tensor(0x1p-149)]; + tensor mel = log(epsilon = mel_epsilon_0, x = clip_0)[name = tensor("mel")]; + tensor concat_3x = const()[name = tensor("concat_3x"), val = tensor([-1, 998, 80])]; + tensor var_128 = reshape(shape = concat_3x, x = mel)[name = tensor("op_128")]; + tensor centered_axes_0 = const()[name = tensor("centered_axes_0"), val = tensor([1])]; + tensor centered_keep_dims_0 = const()[name = tensor("centered_keep_dims_0"), val = tensor(true)]; + tensor centered = reduce_mean(axes = centered_axes_0, keep_dims = centered_keep_dims_0, x = var_128)[name = tensor("centered")]; + tensor features_1 = sub(x = var_128, y = centered)[name = tensor("features_1")]; + tensor var_147 = const()[name = tensor("op_147"), val = tensor([0, 2, 1])]; + tensor input_5_axes_0 = const()[name = tensor("input_5_axes_0"), val = tensor([1])]; + tensor var_148 = transpose(perm = var_147, x = features_1)[name = tensor("transpose_0")]; + tensor input_5 = expand_dims(axes = input_5_axes_0, x = var_148)[name = tensor("input_5")]; + tensor left_batch_dims_0 = const()[name = tensor("left_batch_dims_0"), val = tensor(0)]; + tensor left_validate_indices_0 = const()[name = tensor("left_validate_indices_0"), val = tensor(false)]; + tensor select_3 = const()[name = tensor("select_3"), val = tensor([0, 4, 9, 14, 18, 23, 28, 33, 37, 42, 47, 52, 56, 61, 66, 71, 75, 80, 85, 90, 94, 99, 104, 109, 113, 118, 123, 128, 132, 137, 142, 147, 151, 156, 161, 165, 170, 175, 180, 184, 189, 194, 199, 203, 208, 213, 218, 222, 227, 232, 237, 241, 246, 251, 256, 260, 265, 270, 275, 279, 284, 289, 294, 298, 303, 308, 312, 317, 322, 327, 331, 336, 341, 346, 350, 355, 360, 365, 369, 374, 379, 384, 388, 393, 398, 403, 407, 412, 417, 422, 426, 431, 436, 441, 445, 450, 455, 459, 464, 469, 474, 478, 483, 488, 493, 497, 502, 507, 512, 516, 521, 526, 531, 535, 540, 545, 550, 554, 559, 564, 569, 573, 578, 583, 588])]; + tensor left_axis_1 = const()[name = tensor("left_axis_1"), val = tensor(1)]; + tensor left = gather(axis = left_axis_1, batch_dims = left_batch_dims_0, indices = select_3, validate_indices = left_validate_indices_0, x = weights_1)[name = tensor("left")]; + tensor right_batch_dims_0 = const()[name = tensor("right_batch_dims_0"), val = tensor(0)]; + tensor right_validate_indices_0 = const()[name = tensor("right_validate_indices_0"), val = tensor(false)]; + tensor select_4 = const()[name = tensor("select_4"), val = tensor([1, 5, 10, 15, 19, 24, 29, 34, 38, 43, 48, 53, 57, 62, 67, 72, 76, 81, 86, 91, 95, 100, 105, 110, 114, 119, 124, 129, 133, 138, 143, 148, 152, 157, 162, 166, 171, 176, 181, 185, 190, 195, 200, 204, 209, 214, 219, 223, 228, 233, 238, 242, 247, 252, 257, 261, 266, 271, 276, 280, 285, 290, 295, 299, 304, 309, 313, 318, 323, 328, 332, 337, 342, 347, 351, 356, 361, 366, 370, 375, 380, 385, 389, 394, 399, 404, 408, 413, 418, 423, 427, 432, 437, 442, 446, 451, 456, 460, 465, 470, 475, 479, 484, 489, 494, 498, 503, 508, 513, 517, 522, 527, 532, 536, 541, 546, 551, 555, 560, 565, 570, 574, 579, 584, 588])]; + tensor right_axis_1 = const()[name = tensor("right_axis_1"), val = tensor(1)]; + tensor right = gather(axis = right_axis_1, batch_dims = right_batch_dims_0, indices = select_4, validate_indices = right_validate_indices_0, x = weights_1)[name = tensor("right")]; + tensor var_171 = mul(x = left, y = _interp_left_weight)[name = tensor("op_171")]; + tensor var_172 = mul(x = right, y = _interp_right_weight)[name = tensor("op_172")]; + tensor weights_3 = add(x = var_171, y = var_172)[name = tensor("weights_3")]; + tensor var_176 = const()[name = tensor("op_176"), val = tensor(-1)]; + tensor var_177 = const()[name = tensor("op_177"), val = tensor(0x1.197998p-40)]; tensor input_7_pad_type_0 = const()[name = tensor("input_7_pad_type_0"), val = tensor("custom")]; tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_7_strides_0 = const()[name = tensor("input_7_strides_0"), val = tensor([1, 1])]; tensor input_7_dilations_0 = const()[name = tensor("input_7_dilations_0"), val = tensor([1, 1])]; tensor input_7_groups_0 = const()[name = tensor("input_7_groups_0"), val = tensor(1)]; - tensor const_4_to_fp16 = const()[name = tensor("const_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(832)))]; - tensor const_5_to_fp16 = const()[name = tensor("const_5_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19328)))]; - tensor input_9_cast_fp16 = conv(bias = const_5_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = const_4_to_fp16, x = input_5_cast_fp16)[name = tensor("input_9_cast_fp16")]; - tensor input_11_cast_fp16 = relu(x = input_9_cast_fp16)[name = tensor("input_11_cast_fp16")]; + tensor const_5 = const()[name = tensor("const_5"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7022080)))]; + tensor const_6 = const()[name = tensor("const_6"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7023296)))]; + tensor input_9 = conv(bias = const_6, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = const_5, x = input_5)[name = tensor("input_9")]; + tensor input_11 = relu(x = input_9)[name = tensor("input_11")]; tensor input_13_pad_type_0 = const()[name = tensor("input_13_pad_type_0"), val = tensor("custom")]; tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_13_strides_0 = const()[name = tensor("input_13_strides_0"), val = tensor([1, 1])]; tensor input_13_dilations_0 = const()[name = tensor("input_13_dilations_0"), val = tensor([1, 1])]; tensor input_13_groups_0 = const()[name = tensor("input_13_groups_0"), val = tensor(1)]; - tensor const_6_to_fp16 = const()[name = tensor("const_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19456)))]; - tensor const_7_to_fp16 = const()[name = tensor("const_7_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37952)))]; - tensor out_1_cast_fp16 = conv(bias = const_7_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = const_6_to_fp16, x = input_11_cast_fp16)[name = tensor("out_1_cast_fp16")]; - tensor input_15_cast_fp16 = add(x = out_1_cast_fp16, y = input_5_cast_fp16)[name = tensor("input_15_cast_fp16")]; - tensor input_17_cast_fp16 = relu(x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; + tensor const_7 = const()[name = tensor("const_7"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7023488)))]; + tensor const_8 = const()[name = tensor("const_8"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7060416)))]; + tensor input_15 = conv(bias = const_8, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = const_7, x = input_11)[name = tensor("input_15")]; + tensor input_17 = relu(x = input_15)[name = tensor("input_17")]; tensor input_19_pad_type_0 = const()[name = tensor("input_19_pad_type_0"), val = tensor("custom")]; tensor input_19_pad_0 = const()[name = tensor("input_19_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_19_strides_0 = const()[name = tensor("input_19_strides_0"), val = tensor([1, 1])]; tensor input_19_dilations_0 = const()[name = tensor("input_19_dilations_0"), val = tensor([1, 1])]; tensor input_19_groups_0 = const()[name = tensor("input_19_groups_0"), val = tensor(1)]; - tensor const_8_to_fp16 = const()[name = tensor("const_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38080)))]; - tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56576)))]; - tensor input_21_cast_fp16 = conv(bias = const_9_to_fp16, dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = const_8_to_fp16, x = input_17_cast_fp16)[name = tensor("input_21_cast_fp16")]; - tensor input_23_cast_fp16 = relu(x = input_21_cast_fp16)[name = tensor("input_23_cast_fp16")]; + tensor const_9 = const()[name = tensor("const_9"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7060608)))]; + tensor const_10 = const()[name = tensor("const_10"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7097536)))]; + tensor out_1 = conv(bias = const_10, dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = const_9, x = input_17)[name = tensor("out_1")]; + tensor input_21 = add(x = out_1, y = input_11)[name = tensor("input_21")]; + tensor input_23 = relu(x = input_21)[name = tensor("input_23")]; tensor input_25_pad_type_0 = const()[name = tensor("input_25_pad_type_0"), val = tensor("custom")]; tensor input_25_pad_0 = const()[name = tensor("input_25_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_25_strides_0 = const()[name = tensor("input_25_strides_0"), val = tensor([1, 1])]; tensor input_25_dilations_0 = const()[name = tensor("input_25_dilations_0"), val = tensor([1, 1])]; tensor input_25_groups_0 = const()[name = tensor("input_25_groups_0"), val = tensor(1)]; - tensor const_10_to_fp16 = const()[name = tensor("const_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56704)))]; - tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75200)))]; - tensor out_3_cast_fp16 = conv(bias = const_11_to_fp16, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = const_10_to_fp16, x = input_23_cast_fp16)[name = tensor("out_3_cast_fp16")]; - tensor input_27_cast_fp16 = add(x = out_3_cast_fp16, y = input_17_cast_fp16)[name = tensor("input_27_cast_fp16")]; - tensor input_29_cast_fp16 = relu(x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; + tensor const_11 = const()[name = tensor("const_11"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7097728)))]; + tensor const_12 = const()[name = tensor("const_12"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7134656)))]; + tensor input_27 = conv(bias = const_12, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = const_11, x = input_23)[name = tensor("input_27")]; + tensor input_29 = relu(x = input_27)[name = tensor("input_29")]; tensor input_31_pad_type_0 = const()[name = tensor("input_31_pad_type_0"), val = tensor("custom")]; tensor input_31_pad_0 = const()[name = tensor("input_31_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_31_strides_0 = const()[name = tensor("input_31_strides_0"), val = tensor([1, 1])]; tensor input_31_dilations_0 = const()[name = tensor("input_31_dilations_0"), val = tensor([1, 1])]; tensor input_31_groups_0 = const()[name = tensor("input_31_groups_0"), val = tensor(1)]; - tensor const_12_to_fp16 = const()[name = tensor("const_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75328)))]; - tensor const_13_to_fp16 = const()[name = tensor("const_13_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93824)))]; - tensor input_33_cast_fp16 = conv(bias = const_13_to_fp16, dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = const_12_to_fp16, x = input_29_cast_fp16)[name = tensor("input_33_cast_fp16")]; - tensor input_35_cast_fp16 = relu(x = input_33_cast_fp16)[name = tensor("input_35_cast_fp16")]; + tensor const_13 = const()[name = tensor("const_13"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7134848)))]; + tensor const_14 = const()[name = tensor("const_14"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7171776)))]; + tensor out_3 = conv(bias = const_14, dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = const_13, x = input_29)[name = tensor("out_3")]; + tensor input_33 = add(x = out_3, y = input_23)[name = tensor("input_33")]; + tensor input_35 = relu(x = input_33)[name = tensor("input_35")]; tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_37_strides_0 = const()[name = tensor("input_37_strides_0"), val = tensor([1, 1])]; tensor input_37_dilations_0 = const()[name = tensor("input_37_dilations_0"), val = tensor([1, 1])]; tensor input_37_groups_0 = const()[name = tensor("input_37_groups_0"), val = tensor(1)]; - tensor const_14_to_fp16 = const()[name = tensor("const_14_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93952)))]; - tensor const_15_to_fp16 = const()[name = tensor("const_15_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112448)))]; - tensor out_5_cast_fp16 = conv(bias = const_15_to_fp16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = const_14_to_fp16, x = input_35_cast_fp16)[name = tensor("out_5_cast_fp16")]; - tensor input_39_cast_fp16 = add(x = out_5_cast_fp16, y = input_29_cast_fp16)[name = tensor("input_39_cast_fp16")]; - tensor input_41_cast_fp16 = relu(x = input_39_cast_fp16)[name = tensor("input_41_cast_fp16")]; + tensor const_15 = const()[name = tensor("const_15"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7171968)))]; + tensor const_16 = const()[name = tensor("const_16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7208896)))]; + tensor input_39 = conv(bias = const_16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = const_15, x = input_35)[name = tensor("input_39")]; + tensor input_41 = relu(x = input_39)[name = tensor("input_41")]; tensor input_43_pad_type_0 = const()[name = tensor("input_43_pad_type_0"), val = tensor("custom")]; tensor input_43_pad_0 = const()[name = tensor("input_43_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_43_strides_0 = const()[name = tensor("input_43_strides_0"), val = tensor([2, 2])]; + tensor input_43_strides_0 = const()[name = tensor("input_43_strides_0"), val = tensor([1, 1])]; tensor input_43_dilations_0 = const()[name = tensor("input_43_dilations_0"), val = tensor([1, 1])]; tensor input_43_groups_0 = const()[name = tensor("input_43_groups_0"), val = tensor(1)]; - tensor const_16_to_fp16 = const()[name = tensor("const_16_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112576)))]; - tensor const_17_to_fp16 = const()[name = tensor("const_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149504)))]; - tensor input_45_cast_fp16 = conv(bias = const_17_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_16_to_fp16, x = input_41_cast_fp16)[name = tensor("input_45_cast_fp16")]; - tensor input_47_cast_fp16 = relu(x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; + tensor const_17 = const()[name = tensor("const_17"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7209088)))]; + tensor const_18 = const()[name = tensor("const_18"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7246016)))]; + tensor out_5 = conv(bias = const_18, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_17, x = input_41)[name = tensor("out_5")]; + tensor input_45 = add(x = out_5, y = input_35)[name = tensor("input_45")]; + tensor input_47 = relu(x = input_45)[name = tensor("input_47")]; tensor input_49_pad_type_0 = const()[name = tensor("input_49_pad_type_0"), val = tensor("custom")]; tensor input_49_pad_0 = const()[name = tensor("input_49_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_49_strides_0 = const()[name = tensor("input_49_strides_0"), val = tensor([1, 1])]; + tensor input_49_strides_0 = const()[name = tensor("input_49_strides_0"), val = tensor([2, 2])]; tensor input_49_dilations_0 = const()[name = tensor("input_49_dilations_0"), val = tensor([1, 1])]; tensor input_49_groups_0 = const()[name = tensor("input_49_groups_0"), val = tensor(1)]; - tensor const_18_to_fp16 = const()[name = tensor("const_18_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149696)))]; - tensor const_19_to_fp16 = const()[name = tensor("const_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223488)))]; - tensor out_7_cast_fp16 = conv(bias = const_19_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_18_to_fp16, x = input_47_cast_fp16)[name = tensor("out_7_cast_fp16")]; - tensor input_51_pad_type_0 = const()[name = tensor("input_51_pad_type_0"), val = tensor("valid")]; - tensor input_51_strides_0 = const()[name = tensor("input_51_strides_0"), val = tensor([2, 2])]; - tensor input_51_pad_0 = const()[name = tensor("input_51_pad_0"), val = tensor([0, 0, 0, 0])]; - tensor input_51_dilations_0 = const()[name = tensor("input_51_dilations_0"), val = tensor([1, 1])]; - tensor input_51_groups_0 = const()[name = tensor("input_51_groups_0"), val = tensor(1)]; - tensor const_20_to_fp16 = const()[name = tensor("const_20_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223680)))]; - tensor const_21_to_fp16 = const()[name = tensor("const_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227840)))]; - tensor var_168_cast_fp16 = conv(bias = const_21_to_fp16, dilations = input_51_dilations_0, groups = input_51_groups_0, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = input_51_strides_0, weight = const_20_to_fp16, x = input_41_cast_fp16)[name = tensor("op_168_cast_fp16")]; - tensor input_53_cast_fp16 = add(x = out_7_cast_fp16, y = var_168_cast_fp16)[name = tensor("input_53_cast_fp16")]; - tensor input_55_cast_fp16 = relu(x = input_53_cast_fp16)[name = tensor("input_55_cast_fp16")]; - tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("custom")]; - tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_57_strides_0 = const()[name = tensor("input_57_strides_0"), val = tensor([1, 1])]; + tensor const_19 = const()[name = tensor("const_19"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7246208)))]; + tensor const_20 = const()[name = tensor("const_20"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7320000)))]; + tensor input_51 = conv(bias = const_20, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_19, x = input_47)[name = tensor("input_51")]; + tensor input_53 = relu(x = input_51)[name = tensor("input_53")]; + tensor input_55_pad_type_0 = const()[name = tensor("input_55_pad_type_0"), val = tensor("custom")]; + tensor input_55_pad_0 = const()[name = tensor("input_55_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_55_strides_0 = const()[name = tensor("input_55_strides_0"), val = tensor([1, 1])]; + tensor input_55_dilations_0 = const()[name = tensor("input_55_dilations_0"), val = tensor([1, 1])]; + tensor input_55_groups_0 = const()[name = tensor("input_55_groups_0"), val = tensor(1)]; + tensor const_21 = const()[name = tensor("const_21"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7320320)))]; + tensor const_22 = const()[name = tensor("const_22"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7467840)))]; + tensor out_7 = conv(bias = const_22, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = const_21, x = input_53)[name = tensor("out_7")]; + tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("valid")]; + tensor input_57_strides_0 = const()[name = tensor("input_57_strides_0"), val = tensor([2, 2])]; + tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_57_dilations_0 = const()[name = tensor("input_57_dilations_0"), val = tensor([1, 1])]; tensor input_57_groups_0 = const()[name = tensor("input_57_groups_0"), val = tensor(1)]; - tensor const_22_to_fp16 = const()[name = tensor("const_22_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228032)))]; - tensor const_23_to_fp16 = const()[name = tensor("const_23_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301824)))]; - tensor input_59_cast_fp16 = conv(bias = const_23_to_fp16, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = const_22_to_fp16, x = input_55_cast_fp16)[name = tensor("input_59_cast_fp16")]; - tensor input_61_cast_fp16 = relu(x = input_59_cast_fp16)[name = tensor("input_61_cast_fp16")]; + tensor const_23 = const()[name = tensor("const_23"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7468160)))]; + tensor const_24 = const()[name = tensor("const_24"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7476416)))]; + tensor var_339 = conv(bias = const_24, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = const_23, x = input_47)[name = tensor("op_339")]; + tensor input_59 = add(x = out_7, y = var_339)[name = tensor("input_59")]; + tensor input_61 = relu(x = input_59)[name = tensor("input_61")]; tensor input_63_pad_type_0 = const()[name = tensor("input_63_pad_type_0"), val = tensor("custom")]; tensor input_63_pad_0 = const()[name = tensor("input_63_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_63_strides_0 = const()[name = tensor("input_63_strides_0"), val = tensor([1, 1])]; tensor input_63_dilations_0 = const()[name = tensor("input_63_dilations_0"), val = tensor([1, 1])]; tensor input_63_groups_0 = const()[name = tensor("input_63_groups_0"), val = tensor(1)]; - tensor const_24_to_fp16 = const()[name = tensor("const_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302016)))]; - tensor const_25_to_fp16 = const()[name = tensor("const_25_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375808)))]; - tensor out_9_cast_fp16 = conv(bias = const_25_to_fp16, dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = const_24_to_fp16, x = input_61_cast_fp16)[name = tensor("out_9_cast_fp16")]; - tensor input_65_cast_fp16 = add(x = out_9_cast_fp16, y = input_55_cast_fp16)[name = tensor("input_65_cast_fp16")]; - tensor input_67_cast_fp16 = relu(x = input_65_cast_fp16)[name = tensor("input_67_cast_fp16")]; + tensor const_25 = const()[name = tensor("const_25"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7476736)))]; + tensor const_26 = const()[name = tensor("const_26"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7624256)))]; + tensor input_65 = conv(bias = const_26, dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = const_25, x = input_61)[name = tensor("input_65")]; + tensor input_67 = relu(x = input_65)[name = tensor("input_67")]; tensor input_69_pad_type_0 = const()[name = tensor("input_69_pad_type_0"), val = tensor("custom")]; tensor input_69_pad_0 = const()[name = tensor("input_69_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_69_strides_0 = const()[name = tensor("input_69_strides_0"), val = tensor([1, 1])]; tensor input_69_dilations_0 = const()[name = tensor("input_69_dilations_0"), val = tensor([1, 1])]; tensor input_69_groups_0 = const()[name = tensor("input_69_groups_0"), val = tensor(1)]; - tensor const_26_to_fp16 = const()[name = tensor("const_26_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(376000)))]; - tensor const_27_to_fp16 = const()[name = tensor("const_27_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449792)))]; - tensor input_71_cast_fp16 = conv(bias = const_27_to_fp16, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = const_26_to_fp16, x = input_67_cast_fp16)[name = tensor("input_71_cast_fp16")]; - tensor input_73_cast_fp16 = relu(x = input_71_cast_fp16)[name = tensor("input_73_cast_fp16")]; + tensor const_27 = const()[name = tensor("const_27"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7624576)))]; + tensor const_28 = const()[name = tensor("const_28"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7772096)))]; + tensor out_9 = conv(bias = const_28, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = const_27, x = input_67)[name = tensor("out_9")]; + tensor input_71 = add(x = out_9, y = input_61)[name = tensor("input_71")]; + tensor input_73 = relu(x = input_71)[name = tensor("input_73")]; tensor input_75_pad_type_0 = const()[name = tensor("input_75_pad_type_0"), val = tensor("custom")]; tensor input_75_pad_0 = const()[name = tensor("input_75_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_75_strides_0 = const()[name = tensor("input_75_strides_0"), val = tensor([1, 1])]; tensor input_75_dilations_0 = const()[name = tensor("input_75_dilations_0"), val = tensor([1, 1])]; tensor input_75_groups_0 = const()[name = tensor("input_75_groups_0"), val = tensor(1)]; - tensor const_28_to_fp16 = const()[name = tensor("const_28_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449984)))]; - tensor const_29_to_fp16 = const()[name = tensor("const_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(523776)))]; - tensor out_11_cast_fp16 = conv(bias = const_29_to_fp16, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_28_to_fp16, x = input_73_cast_fp16)[name = tensor("out_11_cast_fp16")]; - tensor input_77_cast_fp16 = add(x = out_11_cast_fp16, y = input_67_cast_fp16)[name = tensor("input_77_cast_fp16")]; - tensor input_79_cast_fp16 = relu(x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; + tensor const_29 = const()[name = tensor("const_29"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7772416)))]; + tensor const_30 = const()[name = tensor("const_30"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7919936)))]; + tensor input_77 = conv(bias = const_30, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_29, x = input_73)[name = tensor("input_77")]; + tensor input_79 = relu(x = input_77)[name = tensor("input_79")]; tensor input_81_pad_type_0 = const()[name = tensor("input_81_pad_type_0"), val = tensor("custom")]; tensor input_81_pad_0 = const()[name = tensor("input_81_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_81_strides_0 = const()[name = tensor("input_81_strides_0"), val = tensor([1, 1])]; tensor input_81_dilations_0 = const()[name = tensor("input_81_dilations_0"), val = tensor([1, 1])]; tensor input_81_groups_0 = const()[name = tensor("input_81_groups_0"), val = tensor(1)]; - tensor const_30_to_fp16 = const()[name = tensor("const_30_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(523968)))]; - tensor const_31_to_fp16 = const()[name = tensor("const_31_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597760)))]; - tensor input_83_cast_fp16 = conv(bias = const_31_to_fp16, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_30_to_fp16, x = input_79_cast_fp16)[name = tensor("input_83_cast_fp16")]; - tensor input_85_cast_fp16 = relu(x = input_83_cast_fp16)[name = tensor("input_85_cast_fp16")]; + tensor const_31 = const()[name = tensor("const_31"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7920256)))]; + tensor const_32 = const()[name = tensor("const_32"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8067776)))]; + tensor out_11 = conv(bias = const_32, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_31, x = input_79)[name = tensor("out_11")]; + tensor input_83 = add(x = out_11, y = input_73)[name = tensor("input_83")]; + tensor input_85 = relu(x = input_83)[name = tensor("input_85")]; tensor input_87_pad_type_0 = const()[name = tensor("input_87_pad_type_0"), val = tensor("custom")]; tensor input_87_pad_0 = const()[name = tensor("input_87_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_87_strides_0 = const()[name = tensor("input_87_strides_0"), val = tensor([1, 1])]; tensor input_87_dilations_0 = const()[name = tensor("input_87_dilations_0"), val = tensor([1, 1])]; tensor input_87_groups_0 = const()[name = tensor("input_87_groups_0"), val = tensor(1)]; - tensor const_32_to_fp16 = const()[name = tensor("const_32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597952)))]; - tensor const_33_to_fp16 = const()[name = tensor("const_33_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(671744)))]; - tensor out_13_cast_fp16 = conv(bias = const_33_to_fp16, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_32_to_fp16, x = input_85_cast_fp16)[name = tensor("out_13_cast_fp16")]; - tensor input_89_cast_fp16 = add(x = out_13_cast_fp16, y = input_79_cast_fp16)[name = tensor("input_89_cast_fp16")]; - tensor input_91_cast_fp16 = relu(x = input_89_cast_fp16)[name = tensor("input_91_cast_fp16")]; + tensor const_33 = const()[name = tensor("const_33"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8068096)))]; + tensor const_34 = const()[name = tensor("const_34"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8215616)))]; + tensor input_89 = conv(bias = const_34, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_33, x = input_85)[name = tensor("input_89")]; + tensor input_91 = relu(x = input_89)[name = tensor("input_91")]; tensor input_93_pad_type_0 = const()[name = tensor("input_93_pad_type_0"), val = tensor("custom")]; tensor input_93_pad_0 = const()[name = tensor("input_93_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_93_strides_0 = const()[name = tensor("input_93_strides_0"), val = tensor([2, 2])]; + tensor input_93_strides_0 = const()[name = tensor("input_93_strides_0"), val = tensor([1, 1])]; tensor input_93_dilations_0 = const()[name = tensor("input_93_dilations_0"), val = tensor([1, 1])]; tensor input_93_groups_0 = const()[name = tensor("input_93_groups_0"), val = tensor(1)]; - tensor const_34_to_fp16 = const()[name = tensor("const_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(671936)))]; - tensor const_35_to_fp16 = const()[name = tensor("const_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(819456)))]; - tensor input_95_cast_fp16 = conv(bias = const_35_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_34_to_fp16, x = input_91_cast_fp16)[name = tensor("input_95_cast_fp16")]; - tensor input_97_cast_fp16 = relu(x = input_95_cast_fp16)[name = tensor("input_97_cast_fp16")]; + tensor const_35 = const()[name = tensor("const_35"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8215936)))]; + tensor const_36 = const()[name = tensor("const_36"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8363456)))]; + tensor out_13 = conv(bias = const_36, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_35, x = input_91)[name = tensor("out_13")]; + tensor input_95 = add(x = out_13, y = input_85)[name = tensor("input_95")]; + tensor input_97 = relu(x = input_95)[name = tensor("input_97")]; tensor input_99_pad_type_0 = const()[name = tensor("input_99_pad_type_0"), val = tensor("custom")]; tensor input_99_pad_0 = const()[name = tensor("input_99_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_99_strides_0 = const()[name = tensor("input_99_strides_0"), val = tensor([1, 1])]; + tensor input_99_strides_0 = const()[name = tensor("input_99_strides_0"), val = tensor([2, 2])]; tensor input_99_dilations_0 = const()[name = tensor("input_99_dilations_0"), val = tensor([1, 1])]; tensor input_99_groups_0 = const()[name = tensor("input_99_groups_0"), val = tensor(1)]; - tensor const_36_to_fp16 = const()[name = tensor("const_36_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(819776)))]; - tensor const_37_to_fp16 = const()[name = tensor("const_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1114752)))]; - tensor out_15_cast_fp16 = conv(bias = const_37_to_fp16, dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = const_36_to_fp16, x = input_97_cast_fp16)[name = tensor("out_15_cast_fp16")]; - tensor input_101_pad_type_0 = const()[name = tensor("input_101_pad_type_0"), val = tensor("valid")]; - tensor input_101_strides_0 = const()[name = tensor("input_101_strides_0"), val = tensor([2, 2])]; - tensor input_101_pad_0 = const()[name = tensor("input_101_pad_0"), val = tensor([0, 0, 0, 0])]; - tensor input_101_dilations_0 = const()[name = tensor("input_101_dilations_0"), val = tensor([1, 1])]; - tensor input_101_groups_0 = const()[name = tensor("input_101_groups_0"), val = tensor(1)]; - tensor const_38_to_fp16 = const()[name = tensor("const_38_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1115072)))]; - tensor const_39_to_fp16 = const()[name = tensor("const_39_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1131520)))]; - tensor var_304_cast_fp16 = conv(bias = const_39_to_fp16, dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = const_38_to_fp16, x = input_91_cast_fp16)[name = tensor("op_304_cast_fp16")]; - tensor input_103_cast_fp16 = add(x = out_15_cast_fp16, y = var_304_cast_fp16)[name = tensor("input_103_cast_fp16")]; - tensor input_105_cast_fp16 = relu(x = input_103_cast_fp16)[name = tensor("input_105_cast_fp16")]; - tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("custom")]; - tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_107_strides_0 = const()[name = tensor("input_107_strides_0"), val = tensor([1, 1])]; + tensor const_37 = const()[name = tensor("const_37"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8363776)))]; + tensor const_38 = const()[name = tensor("const_38"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8658752)))]; + tensor input_101 = conv(bias = const_38, dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = const_37, x = input_97)[name = tensor("input_101")]; + tensor input_103 = relu(x = input_101)[name = tensor("input_103")]; + tensor input_105_pad_type_0 = const()[name = tensor("input_105_pad_type_0"), val = tensor("custom")]; + tensor input_105_pad_0 = const()[name = tensor("input_105_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_105_strides_0 = const()[name = tensor("input_105_strides_0"), val = tensor([1, 1])]; + tensor input_105_dilations_0 = const()[name = tensor("input_105_dilations_0"), val = tensor([1, 1])]; + tensor input_105_groups_0 = const()[name = tensor("input_105_groups_0"), val = tensor(1)]; + tensor const_39 = const()[name = tensor("const_39"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8659328)))]; + tensor const_40 = const()[name = tensor("const_40"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9249216)))]; + tensor out_15 = conv(bias = const_40, dilations = input_105_dilations_0, groups = input_105_groups_0, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = input_105_strides_0, weight = const_39, x = input_103)[name = tensor("out_15")]; + tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("valid")]; + tensor input_107_strides_0 = const()[name = tensor("input_107_strides_0"), val = tensor([2, 2])]; + tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_107_dilations_0 = const()[name = tensor("input_107_dilations_0"), val = tensor([1, 1])]; tensor input_107_groups_0 = const()[name = tensor("input_107_groups_0"), val = tensor(1)]; - tensor const_40_to_fp16 = const()[name = tensor("const_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1131840)))]; - tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1426816)))]; - tensor input_109_cast_fp16 = conv(bias = const_41_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_40_to_fp16, x = input_105_cast_fp16)[name = tensor("input_109_cast_fp16")]; - tensor input_111_cast_fp16 = relu(x = input_109_cast_fp16)[name = tensor("input_111_cast_fp16")]; + tensor const_41 = const()[name = tensor("const_41"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9249792)))]; + tensor const_42 = const()[name = tensor("const_42"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9282624)))]; + tensor var_475 = conv(bias = const_42, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_41, x = input_97)[name = tensor("op_475")]; + tensor input_109 = add(x = out_15, y = var_475)[name = tensor("input_109")]; + tensor input_111 = relu(x = input_109)[name = tensor("input_111")]; tensor input_113_pad_type_0 = const()[name = tensor("input_113_pad_type_0"), val = tensor("custom")]; tensor input_113_pad_0 = const()[name = tensor("input_113_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_113_strides_0 = const()[name = tensor("input_113_strides_0"), val = tensor([1, 1])]; tensor input_113_dilations_0 = const()[name = tensor("input_113_dilations_0"), val = tensor([1, 1])]; tensor input_113_groups_0 = const()[name = tensor("input_113_groups_0"), val = tensor(1)]; - tensor const_42_to_fp16 = const()[name = tensor("const_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1427136)))]; - tensor const_43_to_fp16 = const()[name = tensor("const_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1722112)))]; - tensor out_17_cast_fp16 = conv(bias = const_43_to_fp16, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_42_to_fp16, x = input_111_cast_fp16)[name = tensor("out_17_cast_fp16")]; - tensor input_115_cast_fp16 = add(x = out_17_cast_fp16, y = input_105_cast_fp16)[name = tensor("input_115_cast_fp16")]; - tensor input_117_cast_fp16 = relu(x = input_115_cast_fp16)[name = tensor("input_117_cast_fp16")]; + tensor const_43 = const()[name = tensor("const_43"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9283200)))]; + tensor const_44 = const()[name = tensor("const_44"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9873088)))]; + tensor input_115 = conv(bias = const_44, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_43, x = input_111)[name = tensor("input_115")]; + tensor input_117 = relu(x = input_115)[name = tensor("input_117")]; tensor input_119_pad_type_0 = const()[name = tensor("input_119_pad_type_0"), val = tensor("custom")]; tensor input_119_pad_0 = const()[name = tensor("input_119_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_119_strides_0 = const()[name = tensor("input_119_strides_0"), val = tensor([1, 1])]; tensor input_119_dilations_0 = const()[name = tensor("input_119_dilations_0"), val = tensor([1, 1])]; tensor input_119_groups_0 = const()[name = tensor("input_119_groups_0"), val = tensor(1)]; - tensor const_44_to_fp16 = const()[name = tensor("const_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1722432)))]; - tensor const_45_to_fp16 = const()[name = tensor("const_45_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2017408)))]; - tensor input_121_cast_fp16 = conv(bias = const_45_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_44_to_fp16, x = input_117_cast_fp16)[name = tensor("input_121_cast_fp16")]; - tensor input_123_cast_fp16 = relu(x = input_121_cast_fp16)[name = tensor("input_123_cast_fp16")]; + tensor const_45 = const()[name = tensor("const_45"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9873664)))]; + tensor const_46 = const()[name = tensor("const_46"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10463552)))]; + tensor out_17 = conv(bias = const_46, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_45, x = input_117)[name = tensor("out_17")]; + tensor input_121 = add(x = out_17, y = input_111)[name = tensor("input_121")]; + tensor input_123 = relu(x = input_121)[name = tensor("input_123")]; tensor input_125_pad_type_0 = const()[name = tensor("input_125_pad_type_0"), val = tensor("custom")]; tensor input_125_pad_0 = const()[name = tensor("input_125_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_125_strides_0 = const()[name = tensor("input_125_strides_0"), val = tensor([1, 1])]; tensor input_125_dilations_0 = const()[name = tensor("input_125_dilations_0"), val = tensor([1, 1])]; tensor input_125_groups_0 = const()[name = tensor("input_125_groups_0"), val = tensor(1)]; - tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2017728)))]; - tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2312704)))]; - tensor out_19_cast_fp16 = conv(bias = const_47_to_fp16, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = const_46_to_fp16, x = input_123_cast_fp16)[name = tensor("out_19_cast_fp16")]; - tensor input_127_cast_fp16 = add(x = out_19_cast_fp16, y = input_117_cast_fp16)[name = tensor("input_127_cast_fp16")]; - tensor input_129_cast_fp16 = relu(x = input_127_cast_fp16)[name = tensor("input_129_cast_fp16")]; + tensor const_47 = const()[name = tensor("const_47"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10464128)))]; + tensor const_48 = const()[name = tensor("const_48"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11054016)))]; + tensor input_127 = conv(bias = const_48, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = const_47, x = input_123)[name = tensor("input_127")]; + tensor input_129 = relu(x = input_127)[name = tensor("input_129")]; tensor input_131_pad_type_0 = const()[name = tensor("input_131_pad_type_0"), val = tensor("custom")]; tensor input_131_pad_0 = const()[name = tensor("input_131_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_131_strides_0 = const()[name = tensor("input_131_strides_0"), val = tensor([1, 1])]; tensor input_131_dilations_0 = const()[name = tensor("input_131_dilations_0"), val = tensor([1, 1])]; tensor input_131_groups_0 = const()[name = tensor("input_131_groups_0"), val = tensor(1)]; - tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2313024)))]; - tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2608000)))]; - tensor input_133_cast_fp16 = conv(bias = const_49_to_fp16, dilations = input_131_dilations_0, groups = input_131_groups_0, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = input_131_strides_0, weight = const_48_to_fp16, x = input_129_cast_fp16)[name = tensor("input_133_cast_fp16")]; - tensor input_135_cast_fp16 = relu(x = input_133_cast_fp16)[name = tensor("input_135_cast_fp16")]; + tensor const_49 = const()[name = tensor("const_49"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11054592)))]; + tensor const_50 = const()[name = tensor("const_50"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11644480)))]; + tensor out_19 = conv(bias = const_50, dilations = input_131_dilations_0, groups = input_131_groups_0, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = input_131_strides_0, weight = const_49, x = input_129)[name = tensor("out_19")]; + tensor input_133 = add(x = out_19, y = input_123)[name = tensor("input_133")]; + tensor input_135 = relu(x = input_133)[name = tensor("input_135")]; tensor input_137_pad_type_0 = const()[name = tensor("input_137_pad_type_0"), val = tensor("custom")]; tensor input_137_pad_0 = const()[name = tensor("input_137_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_137_strides_0 = const()[name = tensor("input_137_strides_0"), val = tensor([1, 1])]; tensor input_137_dilations_0 = const()[name = tensor("input_137_dilations_0"), val = tensor([1, 1])]; tensor input_137_groups_0 = const()[name = tensor("input_137_groups_0"), val = tensor(1)]; - tensor const_50_to_fp16 = const()[name = tensor("const_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2608320)))]; - tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2903296)))]; - tensor out_21_cast_fp16 = conv(bias = const_51_to_fp16, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = const_50_to_fp16, x = input_135_cast_fp16)[name = tensor("out_21_cast_fp16")]; - tensor input_139_cast_fp16 = add(x = out_21_cast_fp16, y = input_129_cast_fp16)[name = tensor("input_139_cast_fp16")]; - tensor input_141_cast_fp16 = relu(x = input_139_cast_fp16)[name = tensor("input_141_cast_fp16")]; + tensor const_51 = const()[name = tensor("const_51"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11645056)))]; + tensor const_52 = const()[name = tensor("const_52"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12234944)))]; + tensor input_139 = conv(bias = const_52, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = const_51, x = input_135)[name = tensor("input_139")]; + tensor input_141 = relu(x = input_139)[name = tensor("input_141")]; tensor input_143_pad_type_0 = const()[name = tensor("input_143_pad_type_0"), val = tensor("custom")]; tensor input_143_pad_0 = const()[name = tensor("input_143_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_143_strides_0 = const()[name = tensor("input_143_strides_0"), val = tensor([1, 1])]; tensor input_143_dilations_0 = const()[name = tensor("input_143_dilations_0"), val = tensor([1, 1])]; tensor input_143_groups_0 = const()[name = tensor("input_143_groups_0"), val = tensor(1)]; - tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2903616)))]; - tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3198592)))]; - tensor input_145_cast_fp16 = conv(bias = const_53_to_fp16, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = const_52_to_fp16, x = input_141_cast_fp16)[name = tensor("input_145_cast_fp16")]; - tensor input_147_cast_fp16 = relu(x = input_145_cast_fp16)[name = tensor("input_147_cast_fp16")]; + tensor const_53 = const()[name = tensor("const_53"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12235520)))]; + tensor const_54 = const()[name = tensor("const_54"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12825408)))]; + tensor out_21 = conv(bias = const_54, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = const_53, x = input_141)[name = tensor("out_21")]; + tensor input_145 = add(x = out_21, y = input_135)[name = tensor("input_145")]; + tensor input_147 = relu(x = input_145)[name = tensor("input_147")]; tensor input_149_pad_type_0 = const()[name = tensor("input_149_pad_type_0"), val = tensor("custom")]; tensor input_149_pad_0 = const()[name = tensor("input_149_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_149_strides_0 = const()[name = tensor("input_149_strides_0"), val = tensor([1, 1])]; tensor input_149_dilations_0 = const()[name = tensor("input_149_dilations_0"), val = tensor([1, 1])]; tensor input_149_groups_0 = const()[name = tensor("input_149_groups_0"), val = tensor(1)]; - tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3198912)))]; - tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3493888)))]; - tensor out_23_cast_fp16 = conv(bias = const_55_to_fp16, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = const_54_to_fp16, x = input_147_cast_fp16)[name = tensor("out_23_cast_fp16")]; - tensor input_151_cast_fp16 = add(x = out_23_cast_fp16, y = input_141_cast_fp16)[name = tensor("input_151_cast_fp16")]; - tensor input_153_cast_fp16 = relu(x = input_151_cast_fp16)[name = tensor("input_153_cast_fp16")]; + tensor const_55 = const()[name = tensor("const_55"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12825984)))]; + tensor const_56 = const()[name = tensor("const_56"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13415872)))]; + tensor input_151 = conv(bias = const_56, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = const_55, x = input_147)[name = tensor("input_151")]; + tensor input_153 = relu(x = input_151)[name = tensor("input_153")]; tensor input_155_pad_type_0 = const()[name = tensor("input_155_pad_type_0"), val = tensor("custom")]; tensor input_155_pad_0 = const()[name = tensor("input_155_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_155_strides_0 = const()[name = tensor("input_155_strides_0"), val = tensor([1, 1])]; tensor input_155_dilations_0 = const()[name = tensor("input_155_dilations_0"), val = tensor([1, 1])]; tensor input_155_groups_0 = const()[name = tensor("input_155_groups_0"), val = tensor(1)]; - tensor const_56_to_fp16 = const()[name = tensor("const_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3494208)))]; - tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3789184)))]; - tensor input_157_cast_fp16 = conv(bias = const_57_to_fp16, dilations = input_155_dilations_0, groups = input_155_groups_0, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = input_155_strides_0, weight = const_56_to_fp16, x = input_153_cast_fp16)[name = tensor("input_157_cast_fp16")]; - tensor input_159_cast_fp16 = relu(x = input_157_cast_fp16)[name = tensor("input_159_cast_fp16")]; + tensor const_57 = const()[name = tensor("const_57"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13416448)))]; + tensor const_58 = const()[name = tensor("const_58"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14006336)))]; + tensor out_23 = conv(bias = const_58, dilations = input_155_dilations_0, groups = input_155_groups_0, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = input_155_strides_0, weight = const_57, x = input_153)[name = tensor("out_23")]; + tensor input_157 = add(x = out_23, y = input_147)[name = tensor("input_157")]; + tensor input_159 = relu(x = input_157)[name = tensor("input_159")]; tensor input_161_pad_type_0 = const()[name = tensor("input_161_pad_type_0"), val = tensor("custom")]; tensor input_161_pad_0 = const()[name = tensor("input_161_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_161_strides_0 = const()[name = tensor("input_161_strides_0"), val = tensor([1, 1])]; tensor input_161_dilations_0 = const()[name = tensor("input_161_dilations_0"), val = tensor([1, 1])]; tensor input_161_groups_0 = const()[name = tensor("input_161_groups_0"), val = tensor(1)]; - tensor const_58_to_fp16 = const()[name = tensor("const_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3789504)))]; - tensor const_59_to_fp16 = const()[name = tensor("const_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4084480)))]; - tensor out_25_cast_fp16 = conv(bias = const_59_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_58_to_fp16, x = input_159_cast_fp16)[name = tensor("out_25_cast_fp16")]; - tensor input_163_cast_fp16 = add(x = out_25_cast_fp16, y = input_153_cast_fp16)[name = tensor("input_163_cast_fp16")]; - tensor input_165_cast_fp16 = relu(x = input_163_cast_fp16)[name = tensor("input_165_cast_fp16")]; + tensor const_59 = const()[name = tensor("const_59"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14006912)))]; + tensor const_60 = const()[name = tensor("const_60"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14596800)))]; + tensor input_163 = conv(bias = const_60, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_59, x = input_159)[name = tensor("input_163")]; + tensor input_165 = relu(x = input_163)[name = tensor("input_165")]; tensor input_167_pad_type_0 = const()[name = tensor("input_167_pad_type_0"), val = tensor("custom")]; tensor input_167_pad_0 = const()[name = tensor("input_167_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_167_strides_0 = const()[name = tensor("input_167_strides_0"), val = tensor([2, 2])]; + tensor input_167_strides_0 = const()[name = tensor("input_167_strides_0"), val = tensor([1, 1])]; tensor input_167_dilations_0 = const()[name = tensor("input_167_dilations_0"), val = tensor([1, 1])]; tensor input_167_groups_0 = const()[name = tensor("input_167_groups_0"), val = tensor(1)]; - tensor const_60_to_fp16 = const()[name = tensor("const_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4084800)))]; - tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4674688)))]; - tensor input_169_cast_fp16 = conv(bias = const_61_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_60_to_fp16, x = input_165_cast_fp16)[name = tensor("input_169_cast_fp16")]; - tensor input_171_cast_fp16 = relu(x = input_169_cast_fp16)[name = tensor("input_171_cast_fp16")]; + tensor const_61 = const()[name = tensor("const_61"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14597376)))]; + tensor const_62 = const()[name = tensor("const_62"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15187264)))]; + tensor out_25 = conv(bias = const_62, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_61, x = input_165)[name = tensor("out_25")]; + tensor input_169 = add(x = out_25, y = input_159)[name = tensor("input_169")]; + tensor input_171 = relu(x = input_169)[name = tensor("input_171")]; tensor input_173_pad_type_0 = const()[name = tensor("input_173_pad_type_0"), val = tensor("custom")]; tensor input_173_pad_0 = const()[name = tensor("input_173_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_173_strides_0 = const()[name = tensor("input_173_strides_0"), val = tensor([1, 1])]; + tensor input_173_strides_0 = const()[name = tensor("input_173_strides_0"), val = tensor([2, 2])]; tensor input_173_dilations_0 = const()[name = tensor("input_173_dilations_0"), val = tensor([1, 1])]; tensor input_173_groups_0 = const()[name = tensor("input_173_groups_0"), val = tensor(1)]; - tensor const_62_to_fp16 = const()[name = tensor("const_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4675264)))]; - tensor const_63_to_fp16 = const()[name = tensor("const_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5854976)))]; - tensor out_27_cast_fp16 = conv(bias = const_63_to_fp16, dilations = input_173_dilations_0, groups = input_173_groups_0, pad = input_173_pad_0, pad_type = input_173_pad_type_0, strides = input_173_strides_0, weight = const_62_to_fp16, x = input_171_cast_fp16)[name = tensor("out_27_cast_fp16")]; - tensor input_175_pad_type_0 = const()[name = tensor("input_175_pad_type_0"), val = tensor("valid")]; - tensor input_175_strides_0 = const()[name = tensor("input_175_strides_0"), val = tensor([2, 2])]; - tensor input_175_pad_0 = const()[name = tensor("input_175_pad_0"), val = tensor([0, 0, 0, 0])]; - tensor input_175_dilations_0 = const()[name = tensor("input_175_dilations_0"), val = tensor([1, 1])]; - tensor input_175_groups_0 = const()[name = tensor("input_175_groups_0"), val = tensor(1)]; - tensor const_64_to_fp16 = const()[name = tensor("const_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5855552)))]; - tensor const_65_to_fp16 = const()[name = tensor("const_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5921152)))]; - tensor var_495_cast_fp16 = conv(bias = const_65_to_fp16, dilations = input_175_dilations_0, groups = input_175_groups_0, pad = input_175_pad_0, pad_type = input_175_pad_type_0, strides = input_175_strides_0, weight = const_64_to_fp16, x = input_165_cast_fp16)[name = tensor("op_495_cast_fp16")]; - tensor input_177_cast_fp16 = add(x = out_27_cast_fp16, y = var_495_cast_fp16)[name = tensor("input_177_cast_fp16")]; - tensor input_179_cast_fp16 = relu(x = input_177_cast_fp16)[name = tensor("input_179_cast_fp16")]; - tensor input_181_pad_type_0 = const()[name = tensor("input_181_pad_type_0"), val = tensor("custom")]; - tensor input_181_pad_0 = const()[name = tensor("input_181_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_181_strides_0 = const()[name = tensor("input_181_strides_0"), val = tensor([1, 1])]; + tensor const_63 = const()[name = tensor("const_63"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15187840)))]; + tensor const_64 = const()[name = tensor("const_64"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16367552)))]; + tensor input_175 = conv(bias = const_64, dilations = input_173_dilations_0, groups = input_173_groups_0, pad = input_173_pad_0, pad_type = input_173_pad_type_0, strides = input_173_strides_0, weight = const_63, x = input_171)[name = tensor("input_175")]; + tensor input_177 = relu(x = input_175)[name = tensor("input_177")]; + tensor input_179_pad_type_0 = const()[name = tensor("input_179_pad_type_0"), val = tensor("custom")]; + tensor input_179_pad_0 = const()[name = tensor("input_179_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_179_strides_0 = const()[name = tensor("input_179_strides_0"), val = tensor([1, 1])]; + tensor input_179_dilations_0 = const()[name = tensor("input_179_dilations_0"), val = tensor([1, 1])]; + tensor input_179_groups_0 = const()[name = tensor("input_179_groups_0"), val = tensor(1)]; + tensor const_65 = const()[name = tensor("const_65"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16368640)))]; + tensor const_66 = const()[name = tensor("const_66"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18728000)))]; + tensor out_27 = conv(bias = const_66, dilations = input_179_dilations_0, groups = input_179_groups_0, pad = input_179_pad_0, pad_type = input_179_pad_type_0, strides = input_179_strides_0, weight = const_65, x = input_177)[name = tensor("out_27")]; + tensor input_181_pad_type_0 = const()[name = tensor("input_181_pad_type_0"), val = tensor("valid")]; + tensor input_181_strides_0 = const()[name = tensor("input_181_strides_0"), val = tensor([2, 2])]; + tensor input_181_pad_0 = const()[name = tensor("input_181_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_181_dilations_0 = const()[name = tensor("input_181_dilations_0"), val = tensor([1, 1])]; tensor input_181_groups_0 = const()[name = tensor("input_181_groups_0"), val = tensor(1)]; - tensor const_66_to_fp16 = const()[name = tensor("const_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5921728)))]; - tensor const_67_to_fp16 = const()[name = tensor("const_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7101440)))]; - tensor input_183_cast_fp16 = conv(bias = const_67_to_fp16, dilations = input_181_dilations_0, groups = input_181_groups_0, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = input_181_strides_0, weight = const_66_to_fp16, x = input_179_cast_fp16)[name = tensor("input_183_cast_fp16")]; - tensor input_185_cast_fp16 = relu(x = input_183_cast_fp16)[name = tensor("input_185_cast_fp16")]; + tensor const_67 = const()[name = tensor("const_67"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18729088)))]; + tensor const_68 = const()[name = tensor("const_68"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18860224)))]; + tensor var_666 = conv(bias = const_68, dilations = input_181_dilations_0, groups = input_181_groups_0, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = input_181_strides_0, weight = const_67, x = input_171)[name = tensor("op_666")]; + tensor input_183 = add(x = out_27, y = var_666)[name = tensor("input_183")]; + tensor input_185 = relu(x = input_183)[name = tensor("input_185")]; tensor input_187_pad_type_0 = const()[name = tensor("input_187_pad_type_0"), val = tensor("custom")]; tensor input_187_pad_0 = const()[name = tensor("input_187_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_187_strides_0 = const()[name = tensor("input_187_strides_0"), val = tensor([1, 1])]; tensor input_187_dilations_0 = const()[name = tensor("input_187_dilations_0"), val = tensor([1, 1])]; tensor input_187_groups_0 = const()[name = tensor("input_187_groups_0"), val = tensor(1)]; - tensor const_68_to_fp16 = const()[name = tensor("const_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7102016)))]; - tensor const_69_to_fp16 = const()[name = tensor("const_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8281728)))]; - tensor out_29_cast_fp16 = conv(bias = const_69_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_68_to_fp16, x = input_185_cast_fp16)[name = tensor("out_29_cast_fp16")]; - tensor input_189_cast_fp16 = add(x = out_29_cast_fp16, y = input_179_cast_fp16)[name = tensor("input_189_cast_fp16")]; - tensor input_191_cast_fp16 = relu(x = input_189_cast_fp16)[name = tensor("input_191_cast_fp16")]; + tensor const_69 = const()[name = tensor("const_69"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18861312)))]; + tensor const_70 = const()[name = tensor("const_70"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21220672)))]; + tensor input_189 = conv(bias = const_70, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_69, x = input_185)[name = tensor("input_189")]; + tensor input_191 = relu(x = input_189)[name = tensor("input_191")]; tensor input_193_pad_type_0 = const()[name = tensor("input_193_pad_type_0"), val = tensor("custom")]; tensor input_193_pad_0 = const()[name = tensor("input_193_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_193_strides_0 = const()[name = tensor("input_193_strides_0"), val = tensor([1, 1])]; tensor input_193_dilations_0 = const()[name = tensor("input_193_dilations_0"), val = tensor([1, 1])]; tensor input_193_groups_0 = const()[name = tensor("input_193_groups_0"), val = tensor(1)]; - tensor const_70_to_fp16 = const()[name = tensor("const_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8282304)))]; - tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9462016)))]; - tensor input_195_cast_fp16 = conv(bias = const_71_to_fp16, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_70_to_fp16, x = input_191_cast_fp16)[name = tensor("input_195_cast_fp16")]; - tensor input_197_cast_fp16 = relu(x = input_195_cast_fp16)[name = tensor("input_197_cast_fp16")]; + tensor const_71 = const()[name = tensor("const_71"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21221760)))]; + tensor const_72 = const()[name = tensor("const_72"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23581120)))]; + tensor out_29 = conv(bias = const_72, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_71, x = input_191)[name = tensor("out_29")]; + tensor input_195 = add(x = out_29, y = input_185)[name = tensor("input_195")]; + tensor input_197 = relu(x = input_195)[name = tensor("input_197")]; tensor input_199_pad_type_0 = const()[name = tensor("input_199_pad_type_0"), val = tensor("custom")]; tensor input_199_pad_0 = const()[name = tensor("input_199_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_199_strides_0 = const()[name = tensor("input_199_strides_0"), val = tensor([1, 1])]; tensor input_199_dilations_0 = const()[name = tensor("input_199_dilations_0"), val = tensor([1, 1])]; tensor input_199_groups_0 = const()[name = tensor("input_199_groups_0"), val = tensor(1)]; - tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9462592)))]; - tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10642304)))]; - tensor out_cast_fp16 = conv(bias = const_73_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_72_to_fp16, x = input_197_cast_fp16)[name = tensor("out_cast_fp16")]; - tensor input_201_cast_fp16 = add(x = out_cast_fp16, y = input_191_cast_fp16)[name = tensor("input_201_cast_fp16")]; - tensor features_cast_fp16 = relu(x = input_201_cast_fp16)[name = tensor("features_cast_fp16")]; - tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([-1, 2560, 125])]; - tensor sequences_cast_fp16 = reshape(shape = concat_0x, x = features_cast_fp16)[name = tensor("sequences_cast_fp16")]; - tensor weights_3_axes_0 = const()[name = tensor("weights_3_axes_0"), val = tensor([1])]; - tensor weights_to_fp16_dtype_0 = const()[name = tensor("weights_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor weights_to_fp16 = cast(dtype = weights_to_fp16_dtype_0, x = weights)[name = tensor("cast_21")]; - tensor weights_3_cast_fp16 = expand_dims(axes = weights_3_axes_0, x = weights_to_fp16)[name = tensor("weights_3_cast_fp16")]; - tensor expand_dims_0_axes_0 = const()[name = tensor("expand_dims_0_axes_0"), val = tensor([3])]; - tensor expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = weights_3_cast_fp16)[name = tensor("expand_dims_0_cast_fp16")]; - tensor upsample_nearest_neighbor_0_scale_factor_height_0 = const()[name = tensor("upsample_nearest_neighbor_0_scale_factor_height_0"), val = tensor(0x1.b2a2a4p-3)]; - tensor upsample_nearest_neighbor_0_scale_factor_width_0 = const()[name = tensor("upsample_nearest_neighbor_0_scale_factor_width_0"), val = tensor(0x1p+0)]; - tensor upsample_nearest_neighbor_0_cast_fp16 = upsample_nearest_neighbor(scale_factor_height = upsample_nearest_neighbor_0_scale_factor_height_0, scale_factor_width = upsample_nearest_neighbor_0_scale_factor_width_0, x = expand_dims_0_cast_fp16)[name = tensor("upsample_nearest_neighbor_0_cast_fp16")]; - tensor weights_5_axes_0 = const()[name = tensor("weights_5_axes_0"), val = tensor([3])]; - tensor weights_5_cast_fp16 = squeeze(axes = weights_5_axes_0, x = upsample_nearest_neighbor_0_cast_fp16)[name = tensor("weights_5_cast_fp16")]; + tensor const_73 = const()[name = tensor("const_73"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23582208)))]; + tensor const_74 = const()[name = tensor("const_74"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25941568)))]; + tensor input_201 = conv(bias = const_74, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_73, x = input_197)[name = tensor("input_201")]; + tensor input_203 = relu(x = input_201)[name = tensor("input_203")]; + tensor input_205_pad_type_0 = const()[name = tensor("input_205_pad_type_0"), val = tensor("custom")]; + tensor input_205_pad_0 = const()[name = tensor("input_205_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_205_strides_0 = const()[name = tensor("input_205_strides_0"), val = tensor([1, 1])]; + tensor input_205_dilations_0 = const()[name = tensor("input_205_dilations_0"), val = tensor([1, 1])]; + tensor input_205_groups_0 = const()[name = tensor("input_205_groups_0"), val = tensor(1)]; + tensor const_75 = const()[name = tensor("const_75"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25942656)))]; + tensor const_76 = const()[name = tensor("const_76"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28302016)))]; + tensor out = conv(bias = const_76, dilations = input_205_dilations_0, groups = input_205_groups_0, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = input_205_strides_0, weight = const_75, x = input_203)[name = tensor("out")]; + tensor input_207 = add(x = out, y = input_197)[name = tensor("input_207")]; + tensor features = relu(x = input_207)[name = tensor("features")]; + tensor concat_4x = const()[name = tensor("concat_4x"), val = tensor([-1, 2560, 125])]; + tensor sequences = reshape(shape = concat_4x, x = features)[name = tensor("sequences")]; + tensor weights_5_axes_0 = const()[name = tensor("weights_5_axes_0"), val = tensor([1])]; + tensor weights_5 = expand_dims(axes = weights_5_axes_0, x = weights_3)[name = tensor("weights_5")]; tensor weights_axes_0 = const()[name = tensor("weights_axes_0"), val = tensor([2])]; - tensor weights_cast_fp16 = expand_dims(axes = weights_axes_0, x = weights_5_cast_fp16)[name = tensor("weights_cast_fp16")]; - tensor weights_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("weights_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; - tensor var_572_axes_0 = const()[name = tensor("op_572_axes_0"), val = tensor([-1])]; - tensor var_572_keep_dims_0 = const()[name = tensor("op_572_keep_dims_0"), val = tensor(false)]; - tensor weights_cast_fp16_to_fp32 = cast(dtype = weights_cast_fp16_to_fp32_dtype_0, x = weights_cast_fp16)[name = tensor("cast_20")]; - tensor var_572 = reduce_sum(axes = var_572_axes_0, keep_dims = var_572_keep_dims_0, x = weights_cast_fp16_to_fp32)[name = tensor("op_572")]; - tensor var_572_to_fp16_dtype_0 = const()[name = tensor("op_572_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor var_573_to_fp16 = const()[name = tensor("op_573_to_fp16"), val = tensor(0x1p-24)]; - tensor var_572_to_fp16 = cast(dtype = var_572_to_fp16_dtype_0, x = var_572)[name = tensor("cast_19")]; - tensor v1_cast_fp16 = add(x = var_572_to_fp16, y = var_573_to_fp16)[name = tensor("v1_cast_fp16")]; - tensor var_575_axes_0 = const()[name = tensor("op_575_axes_0"), val = tensor([1])]; - tensor var_575_cast_fp16 = expand_dims(axes = var_575_axes_0, x = sequences_cast_fp16)[name = tensor("op_575_cast_fp16")]; - tensor weighted_cast_fp16 = mul(x = var_575_cast_fp16, y = weights_cast_fp16)[name = tensor("weighted_cast_fp16")]; - tensor weighted_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("weighted_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; - tensor var_578_axes_0 = const()[name = tensor("op_578_axes_0"), val = tensor([-1])]; - tensor var_578_keep_dims_0 = const()[name = tensor("op_578_keep_dims_0"), val = tensor(false)]; - tensor weighted_cast_fp16_to_fp32 = cast(dtype = weighted_cast_fp16_to_fp32_dtype_0, x = weighted_cast_fp16)[name = tensor("cast_18")]; - tensor var_578 = reduce_sum(axes = var_578_axes_0, keep_dims = var_578_keep_dims_0, x = weighted_cast_fp16_to_fp32)[name = tensor("op_578")]; - tensor var_578_to_fp16_dtype_0 = const()[name = tensor("op_578_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor var_578_to_fp16 = cast(dtype = var_578_to_fp16_dtype_0, x = var_578)[name = tensor("cast_17")]; - tensor mean_cast_fp16 = real_div(x = var_578_to_fp16, y = v1_cast_fp16)[name = tensor("mean_cast_fp16")]; - tensor var_581_axes_0 = const()[name = tensor("op_581_axes_0"), val = tensor([-1])]; - tensor var_581_cast_fp16 = expand_dims(axes = var_581_axes_0, x = mean_cast_fp16)[name = tensor("op_581_cast_fp16")]; - tensor diff_cast_fp16 = sub(x = var_575_cast_fp16, y = var_581_cast_fp16)[name = tensor("diff_cast_fp16")]; - tensor var_583_cast_fp16 = mul(x = weights_cast_fp16, y = weights_cast_fp16)[name = tensor("op_583_cast_fp16")]; - tensor var_583_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("op_583_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor weights = expand_dims(axes = weights_axes_0, x = weights_5)[name = tensor("weights")]; + tensor var_740_axes_0 = const()[name = tensor("op_740_axes_0"), val = tensor([-1])]; + tensor var_740_keep_dims_0 = const()[name = tensor("op_740_keep_dims_0"), val = tensor(false)]; + tensor var_740 = reduce_sum(axes = var_740_axes_0, keep_dims = var_740_keep_dims_0, x = weights)[name = tensor("op_740")]; + tensor var_741 = const()[name = tensor("op_741"), val = tensor(0x1.5798eep-27)]; + tensor v1 = add(x = var_740, y = var_741)[name = tensor("v1")]; + tensor var_743_axes_0 = const()[name = tensor("op_743_axes_0"), val = tensor([1])]; + tensor var_743 = expand_dims(axes = var_743_axes_0, x = sequences)[name = tensor("op_743")]; + tensor weighted = mul(x = var_743, y = weights)[name = tensor("weighted")]; + tensor var_746_axes_0 = const()[name = tensor("op_746_axes_0"), val = tensor([-1])]; + tensor var_746_keep_dims_0 = const()[name = tensor("op_746_keep_dims_0"), val = tensor(false)]; + tensor var_746 = reduce_sum(axes = var_746_axes_0, keep_dims = var_746_keep_dims_0, x = weighted)[name = tensor("op_746")]; + tensor mean = real_div(x = var_746, y = v1)[name = tensor("mean")]; + tensor var_749_axes_0 = const()[name = tensor("op_749_axes_0"), val = tensor([-1])]; + tensor var_749 = expand_dims(axes = var_749_axes_0, x = mean)[name = tensor("op_749")]; + tensor diff = sub(x = var_743, y = var_749)[name = tensor("diff")]; + tensor var_751 = mul(x = weights, y = weights)[name = tensor("op_751")]; tensor v2_axes_0 = const()[name = tensor("v2_axes_0"), val = tensor([-1])]; tensor v2_keep_dims_0 = const()[name = tensor("v2_keep_dims_0"), val = tensor(false)]; - tensor var_583_cast_fp16_to_fp32 = cast(dtype = var_583_cast_fp16_to_fp32_dtype_0, x = var_583_cast_fp16)[name = tensor("cast_16")]; - tensor v2 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_583_cast_fp16_to_fp32)[name = tensor("v2")]; - tensor v2_to_fp16_dtype_0 = const()[name = tensor("v2_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor v2_to_fp16 = cast(dtype = v2_to_fp16_dtype_0, x = v2)[name = tensor("cast_15")]; - tensor var_586_cast_fp16 = real_div(x = v2_to_fp16, y = v1_cast_fp16)[name = tensor("op_586_cast_fp16")]; - tensor var_587_cast_fp16 = sub(x = v1_cast_fp16, y = var_586_cast_fp16)[name = tensor("op_587_cast_fp16")]; - tensor var_588_to_fp16 = const()[name = tensor("op_588_to_fp16"), val = tensor(0x1p-24)]; - tensor denom_cast_fp16 = add(x = var_587_cast_fp16, y = var_588_to_fp16)[name = tensor("denom_cast_fp16")]; - tensor var_590_cast_fp16 = mul(x = diff_cast_fp16, y = diff_cast_fp16)[name = tensor("op_590_cast_fp16")]; - tensor var_591_cast_fp16 = mul(x = var_590_cast_fp16, y = weights_cast_fp16)[name = tensor("op_591_cast_fp16")]; - tensor var_591_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("op_591_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; - tensor var_593_axes_0 = const()[name = tensor("op_593_axes_0"), val = tensor([-1])]; - tensor var_593_keep_dims_0 = const()[name = tensor("op_593_keep_dims_0"), val = tensor(false)]; - tensor var_591_cast_fp16_to_fp32 = cast(dtype = var_591_cast_fp16_to_fp32_dtype_0, x = var_591_cast_fp16)[name = tensor("cast_14")]; - tensor var_593 = reduce_sum(axes = var_593_axes_0, keep_dims = var_593_keep_dims_0, x = var_591_cast_fp16_to_fp32)[name = tensor("op_593")]; - tensor var_593_to_fp16_dtype_0 = const()[name = tensor("op_593_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor var_593_to_fp16 = cast(dtype = var_593_to_fp16_dtype_0, x = var_593)[name = tensor("cast_13")]; - tensor var_cast_fp16 = real_div(x = var_593_to_fp16, y = denom_cast_fp16)[name = tensor("var_cast_fp16")]; - tensor var_6_to_fp16 = const()[name = tensor("op_6_to_fp16"), val = tensor(0x1p-24)]; - tensor const_0_to_fp16 = const()[name = tensor("const_0_to_fp16"), val = tensor(inf)]; - tensor clip_0_cast_fp16 = clip(alpha = var_6_to_fp16, beta = const_0_to_fp16, x = var_cast_fp16)[name = tensor("clip_0_cast_fp16")]; - tensor clip_0_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("clip_0_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; - tensor clip_0_cast_fp16_to_fp32 = cast(dtype = clip_0_cast_fp16_to_fp32_dtype_0, x = clip_0_cast_fp16)[name = tensor("cast_12")]; - tensor std = sqrt(x = clip_0_cast_fp16_to_fp32)[name = tensor("std")]; + tensor v2 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_751)[name = tensor("v2")]; + tensor var_754 = real_div(x = v2, y = v1)[name = tensor("op_754")]; + tensor var_755 = sub(x = v1, y = var_754)[name = tensor("op_755")]; + tensor var_756 = const()[name = tensor("op_756"), val = tensor(0x1.5798eep-27)]; + tensor denom = add(x = var_755, y = var_756)[name = tensor("denom")]; + tensor var_758 = mul(x = diff, y = diff)[name = tensor("op_758")]; + tensor var_759 = mul(x = var_758, y = weights)[name = tensor("op_759")]; + tensor var_761_axes_0 = const()[name = tensor("op_761_axes_0"), val = tensor([-1])]; + tensor var_761_keep_dims_0 = const()[name = tensor("op_761_keep_dims_0"), val = tensor(false)]; + tensor var_761 = reduce_sum(axes = var_761_axes_0, keep_dims = var_761_keep_dims_0, x = var_759)[name = tensor("op_761")]; + tensor var = real_div(x = var_761, y = denom)[name = tensor("var")]; + tensor const_3 = const()[name = tensor("const_3"), val = tensor(0x1.fffffep+127)]; + tensor clip_1 = clip(alpha = var_177, beta = const_3, x = var)[name = tensor("clip_1")]; + tensor std = sqrt(x = clip_1)[name = tensor("std")]; tensor output_interleave_0 = const()[name = tensor("output_interleave_0"), val = tensor(false)]; - tensor std_to_fp16_dtype_0 = const()[name = tensor("std_to_fp16_dtype_0"), val = tensor("fp16")]; - tensor std_to_fp16 = cast(dtype = std_to_fp16_dtype_0, x = std)[name = tensor("cast_11")]; - tensor output_cast_fp16 = concat(axis = var_5, interleave = output_interleave_0, values = (mean_cast_fp16, std_to_fp16))[name = tensor("output_cast_fp16")]; + tensor output = concat(axis = var_176, interleave = output_interleave_0, values = (mean, std))[name = tensor("output")]; tensor stats_axes_0 = const()[name = tensor("stats_axes_0"), val = tensor([1])]; - tensor stats_cast_fp16 = squeeze(axes = stats_axes_0, x = output_cast_fp16)[name = tensor("stats_cast_fp16")]; - tensor var_600_axes_0 = const()[name = tensor("op_600_axes_0"), val = tensor([-1])]; - tensor var_600_cast_fp16 = expand_dims(axes = var_600_axes_0, x = stats_cast_fp16)[name = tensor("op_600_cast_fp16")]; - tensor input_203_axes_0 = const()[name = tensor("input_203_axes_0"), val = tensor([-1])]; - tensor input_203_cast_fp16 = expand_dims(axes = input_203_axes_0, x = var_600_cast_fp16)[name = tensor("input_203_cast_fp16")]; - tensor var_608_pad_type_0 = const()[name = tensor("op_608_pad_type_0"), val = tensor("valid")]; - tensor var_608_strides_0 = const()[name = tensor("op_608_strides_0"), val = tensor([1, 1])]; - tensor var_608_pad_0 = const()[name = tensor("op_608_pad_0"), val = tensor([0, 0, 0, 0])]; - tensor var_608_dilations_0 = const()[name = tensor("op_608_dilations_0"), val = tensor([1, 1])]; - tensor var_608_groups_0 = const()[name = tensor("op_608_groups_0"), val = tensor(1)]; - tensor resnet_seg_1_weight_to_fp16 = const()[name = tensor("resnet_seg_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10642880)))]; - tensor resnet_seg_1_bias_to_fp16 = const()[name = tensor("resnet_seg_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13264384)))]; - tensor var_608_cast_fp16 = conv(bias = resnet_seg_1_bias_to_fp16, dilations = var_608_dilations_0, groups = var_608_groups_0, pad = var_608_pad_0, pad_type = var_608_pad_type_0, strides = var_608_strides_0, weight = resnet_seg_1_weight_to_fp16, x = input_203_cast_fp16)[name = tensor("op_608_cast_fp16")]; - tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([-1, 256])]; - tensor input_cast_fp16 = reshape(shape = concat_1x, x = var_608_cast_fp16)[name = tensor("input_cast_fp16")]; - tensor var_612 = const()[name = tensor("op_612"), val = tensor([-1])]; - tensor var_613 = const()[name = tensor("op_613"), val = tensor(true)]; - tensor norms_1_cast_fp16 = reduce_l2_norm(axes = var_612, keep_dims = var_613, x = input_cast_fp16)[name = tensor("norms_1_cast_fp16")]; - tensor var_616_to_fp16 = const()[name = tensor("op_616_to_fp16"), val = tensor(0x1p-24)]; - tensor const_1_to_fp16 = const()[name = tensor("const_1_to_fp16"), val = tensor(inf)]; - tensor clip_1_cast_fp16 = clip(alpha = var_616_to_fp16, beta = const_1_to_fp16, x = norms_1_cast_fp16)[name = tensor("clip_1_cast_fp16")]; - tensor var_619_cast_fp16 = real_div(x = input_cast_fp16, y = clip_1_cast_fp16)[name = tensor("op_619_cast_fp16")]; - tensor var_619_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("op_619_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; - tensor embedding = cast(dtype = var_619_cast_fp16_to_fp32_dtype_0, x = var_619_cast_fp16)[name = tensor("cast_10")]; + tensor stats = squeeze(axes = stats_axes_0, x = output)[name = tensor("stats")]; + tensor var_768_axes_0 = const()[name = tensor("op_768_axes_0"), val = tensor([-1])]; + tensor var_768 = expand_dims(axes = var_768_axes_0, x = stats)[name = tensor("op_768")]; + tensor input_209_axes_0 = const()[name = tensor("input_209_axes_0"), val = tensor([-1])]; + tensor input_209 = expand_dims(axes = input_209_axes_0, x = var_768)[name = tensor("input_209")]; + tensor var_776_pad_type_0 = const()[name = tensor("op_776_pad_type_0"), val = tensor("valid")]; + tensor var_776_strides_0 = const()[name = tensor("op_776_strides_0"), val = tensor([1, 1])]; + tensor var_776_pad_0 = const()[name = tensor("op_776_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor var_776_dilations_0 = const()[name = tensor("op_776_dilations_0"), val = tensor([1, 1])]; + tensor var_776_groups_0 = const()[name = tensor("op_776_groups_0"), val = tensor(1)]; + tensor var_776 = conv(bias = resnet_seg_1_bias, dilations = var_776_dilations_0, groups = var_776_groups_0, pad = var_776_pad_0, pad_type = var_776_pad_type_0, strides = var_776_strides_0, weight = resnet_seg_1_weight, x = input_209)[name = tensor("op_776")]; + tensor concat_5x = const()[name = tensor("concat_5x"), val = tensor([-1, 256])]; + tensor input = reshape(shape = concat_5x, x = var_776)[name = tensor("input")]; + tensor var_780 = const()[name = tensor("op_780"), val = tensor([-1])]; + tensor var_781 = const()[name = tensor("op_781"), val = tensor(true)]; + tensor norms_1 = reduce_l2_norm(axes = var_780, keep_dims = var_781, x = input)[name = tensor("norms_1")]; + tensor var_784 = const()[name = tensor("op_784"), val = tensor(0x1.197998p-40)]; + tensor const_4 = const()[name = tensor("const_4"), val = tensor(0x1.fffffep+127)]; + tensor clip_2 = clip(alpha = var_784, beta = const_4, x = norms_1)[name = tensor("clip_2")]; + tensor embedding = real_div(x = input, y = clip_2)[name = tensor("op_787")]; } -> (embedding); } \ No newline at end of file