| program(1.0) |
| [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"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<ios17>(tensor<fp32, [1, 1, 160000]> audio, tensor<fp32, [1, 589]> weights) { |
| tensor<fp32, [1, 125]> _interp_right_weight = const()[name = tensor<string, []>("_interp_right_weight"), val = tensor<fp32, [1, 125]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))]; |
| tensor<fp32, [1, 125]> _interp_left_weight = const()[name = tensor<string, []>("_interp_left_weight"), val = tensor<fp32, [1, 125]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(640)))]; |
| tensor<int32, [1, 125]> _interp_right_idx = const()[name = tensor<string, []>("_interp_right_idx"), val = tensor<int32, [1, 125]>([[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<int32, [1, 125]> _interp_left_idx = const()[name = tensor<string, []>("_interp_left_idx"), val = tensor<int32, [1, 125]>([[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<fp32, [1, 400]> _fbank_window = const()[name = tensor<string, []>("_fbank_window"), val = tensor<fp32, [1, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1216)))]; |
| tensor<fp32, []> _fbank_eps = const()[name = tensor<string, []>("_fbank_eps"), val = tensor<fp32, []>(0x1.b7cdfep-34)]; |
| tensor<fp32, [400, 1, 400]> _fbank_frame_kernel = const()[name = tensor<string, []>("_fbank_frame_kernel"), val = tensor<fp32, [400, 1, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2880)))]; |
| tensor<fp32, [256]> resnet_seg_1_bias = const()[name = tensor<string, []>("resnet_seg_1_bias"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(642944)))]; |
| tensor<fp32, [256, 5120]> resnet_seg_1_weight = const()[name = tensor<string, []>("resnet_seg_1_weight"), val = tensor<fp32, [256, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(644032)))]; |
| tensor<fp32, []> var_9_promoted = const()[name = tensor<string, []>("op_9_promoted"), val = tensor<fp32, []>(0x1p+15)]; |
| tensor<fp32, [1, 1, 160000]> waveforms_3 = mul(x = audio, y = var_9_promoted)[name = tensor<string, []>("waveforms_3")]; |
| tensor<string, []> frames_1_pad_type_0 = const()[name = tensor<string, []>("frames_1_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [1]> frames_1_strides_0 = const()[name = tensor<string, []>("frames_1_strides_0"), val = tensor<int32, [1]>([160])]; |
| tensor<int32, [2]> frames_1_pad_0 = const()[name = tensor<string, []>("frames_1_pad_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [1]> frames_1_dilations_0 = const()[name = tensor<string, []>("frames_1_dilations_0"), val = tensor<int32, [1]>([1])]; |
| tensor<int32, []> frames_1_groups_0 = const()[name = tensor<string, []>("frames_1_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [1, 400, 998]> 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<string, []>("frames_1")]; |
| tensor<int32, [1]> var_49_axes_0 = const()[name = tensor<string, []>("op_49_axes_0"), val = tensor<int32, [1]>([0])]; |
| tensor<fp32, [400, 998]> var_49 = squeeze(axes = var_49_axes_0, x = frames_1)[name = tensor<string, []>("op_49")]; |
| tensor<int32, [2]> frames_3_perm_0 = const()[name = tensor<string, []>("frames_3_perm_0"), val = tensor<int32, [2]>([1, 0])]; |
| tensor<int32, [1]> var_52_axes_0 = const()[name = tensor<string, []>("op_52_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<bool, []> var_52_keep_dims_0 = const()[name = tensor<string, []>("op_52_keep_dims_0"), val = tensor<bool, []>(true)]; |
| tensor<fp32, [998, 400]> frames_3 = transpose(perm = frames_3_perm_0, x = var_49)[name = tensor<string, []>("transpose_4")]; |
| tensor<fp32, [998, 1]> var_52 = reduce_mean(axes = var_52_axes_0, keep_dims = var_52_keep_dims_0, x = frames_3)[name = tensor<string, []>("op_52")]; |
| tensor<fp32, [998, 400]> frames_5 = sub(x = frames_3, y = var_52)[name = tensor<string, []>("frames_5")]; |
| tensor<int32, [1]> input_1_axes_0 = const()[name = tensor<string, []>("input_1_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [998, 1, 400]> input_1 = expand_dims(axes = input_1_axes_0, x = frames_5)[name = tensor<string, []>("input_1")]; |
| tensor<fp32, []> const_0 = const()[name = tensor<string, []>("const_0"), val = tensor<fp32, []>(0x0p+0)]; |
| tensor<int32, [6]> var_56_pad_0 = const()[name = tensor<string, []>("op_56_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 1, 0])]; |
| tensor<string, []> var_56_mode_0 = const()[name = tensor<string, []>("op_56_mode_0"), val = tensor<string, []>("replicate")]; |
| tensor<fp32, [998, 1, 401]> var_56 = pad(constant_val = const_0, mode = var_56_mode_0, pad = var_56_pad_0, x = input_1)[name = tensor<string, []>("op_56")]; |
| tensor<int32, [1]> padded_axes_0 = const()[name = tensor<string, []>("padded_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [998, 401]> padded = squeeze(axes = padded_axes_0, x = var_56)[name = tensor<string, []>("padded")]; |
| tensor<int32, [2]> var_59_begin_0 = const()[name = tensor<string, []>("op_59_begin_0"), val = tensor<int32, [2]>([0, 0])]; |
| tensor<int32, [2]> var_59_end_0 = const()[name = tensor<string, []>("op_59_end_0"), val = tensor<int32, [2]>([998, 400])]; |
| tensor<bool, [2]> var_59_end_mask_0 = const()[name = tensor<string, []>("op_59_end_mask_0"), val = tensor<bool, [2]>([true, false])]; |
| tensor<fp32, [998, 400]> var_59 = slice_by_index(begin = var_59_begin_0, end = var_59_end_0, end_mask = var_59_end_mask_0, x = padded)[name = tensor<string, []>("op_59")]; |
| tensor<fp32, []> var_60 = const()[name = tensor<string, []>("op_60"), val = tensor<fp32, []>(0x1.f0a3d8p-1)]; |
| tensor<fp32, [998, 400]> var_61 = mul(x = var_59, y = var_60)[name = tensor<string, []>("op_61")]; |
| tensor<fp32, [998, 400]> frames_7 = sub(x = frames_5, y = var_61)[name = tensor<string, []>("frames_7")]; |
| tensor<fp32, [998, 400]> frames_9 = mul(x = frames_7, y = _fbank_window)[name = tensor<string, []>("frames_9")]; |
| tensor<int32, [1]> input_3_axes_0 = const()[name = tensor<string, []>("input_3_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [998, 1, 400]> input_3 = expand_dims(axes = input_3_axes_0, x = frames_9)[name = tensor<string, []>("input_3")]; |
| tensor<fp32, []> const_1 = const()[name = tensor<string, []>("const_1"), val = tensor<fp32, []>(0x0p+0)]; |
| tensor<int32, [6]> var_66_pad_0 = const()[name = tensor<string, []>("op_66_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 112])]; |
| tensor<string, []> var_66_mode_0 = const()[name = tensor<string, []>("op_66_mode_0"), val = tensor<string, []>("constant")]; |
| tensor<fp32, [998, 1, 512]> var_66 = pad(constant_val = const_1, mode = var_66_mode_0, pad = var_66_pad_0, x = input_3)[name = tensor<string, []>("op_66")]; |
| tensor<int32, [1]> frames_11_axes_0 = const()[name = tensor<string, []>("frames_11_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [998, 512]> frames_11 = squeeze(axes = frames_11_axes_0, x = var_66)[name = tensor<string, []>("frames_11")]; |
| tensor<fp32, [257, 512]> transpose_0 = const()[name = tensor<string, []>("transpose_0"), val = tensor<fp32, [257, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5886976)))]; |
| tensor<fp32, [257]> real_bias_0 = const()[name = tensor<string, []>("real_bias_0"), val = tensor<fp32, [257]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6413376)))]; |
| tensor<fp32, [998, 257]> real = linear(bias = real_bias_0, weight = transpose_0, x = frames_11)[name = tensor<string, []>("real")]; |
| tensor<fp32, [257, 512]> transpose_1 = const()[name = tensor<string, []>("transpose_1"), val = tensor<fp32, [257, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6414528)))]; |
| tensor<fp32, [998, 257]> imag = linear(bias = real_bias_0, weight = transpose_1, x = frames_11)[name = tensor<string, []>("imag")]; |
| tensor<fp32, []> var_22_promoted = const()[name = tensor<string, []>("op_22_promoted"), val = tensor<fp32, []>(0x1p+1)]; |
| tensor<fp32, [998, 257]> var_70 = pow(x = real, y = var_22_promoted)[name = tensor<string, []>("op_70")]; |
| tensor<fp32, []> var_22_promoted_1 = const()[name = tensor<string, []>("op_22_promoted_1"), val = tensor<fp32, []>(0x1p+1)]; |
| tensor<fp32, [998, 257]> var_71 = pow(x = imag, y = var_22_promoted_1)[name = tensor<string, []>("op_71")]; |
| tensor<fp32, [998, 257]> power = add(x = var_70, y = var_71)[name = tensor<string, []>("power")]; |
| tensor<fp32, [80, 257]> transpose_2 = const()[name = tensor<string, []>("transpose_2"), val = tensor<fp32, [80, 257]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6940928)))]; |
| tensor<fp32, [80]> mel_bias_0 = const()[name = tensor<string, []>("mel_bias_0"), val = tensor<fp32, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7023232)))]; |
| tensor<fp32, [998, 80]> mel = linear(bias = mel_bias_0, weight = transpose_2, x = power)[name = tensor<string, []>("mel")]; |
| tensor<fp32, []> const_2 = const()[name = tensor<string, []>("const_2"), val = tensor<fp32, []>(0x1.fffffep+127)]; |
| tensor<fp32, [998, 80]> clip_0 = clip(alpha = _fbank_eps, beta = const_2, x = mel)[name = tensor<string, []>("clip_0")]; |
| tensor<fp32, []> var_75_epsilon_0 = const()[name = tensor<string, []>("op_75_epsilon_0"), val = tensor<fp32, []>(0x1p-149)]; |
| tensor<fp32, [998, 80]> var_75 = log(epsilon = var_75_epsilon_0, x = clip_0)[name = tensor<string, []>("op_75")]; |
| tensor<int32, [1]> var_78_axes_0 = const()[name = tensor<string, []>("op_78_axes_0"), val = tensor<int32, [1]>([0])]; |
| tensor<fp32, [1, 998, 80]> var_78 = expand_dims(axes = var_78_axes_0, x = var_75)[name = tensor<string, []>("op_78")]; |
| tensor<int32, [1]> centered_axes_0 = const()[name = tensor<string, []>("centered_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<bool, []> centered_keep_dims_0 = const()[name = tensor<string, []>("centered_keep_dims_0"), val = tensor<bool, []>(true)]; |
| tensor<fp32, [1, 1, 80]> centered = reduce_mean(axes = centered_axes_0, keep_dims = centered_keep_dims_0, x = var_78)[name = tensor<string, []>("centered")]; |
| tensor<fp32, [1, 998, 80]> fbank_1 = sub(x = var_78, y = centered)[name = tensor<string, []>("fbank_1")]; |
| tensor<int32, []> var_107 = const()[name = tensor<string, []>("op_107"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> left_validate_indices_0 = const()[name = tensor<string, []>("left_validate_indices_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 125]> left = gather_along_axis(axis = var_107, indices = _interp_left_idx, validate_indices = left_validate_indices_0, x = weights)[name = tensor<string, []>("left")]; |
| tensor<int32, []> var_110 = const()[name = tensor<string, []>("op_110"), val = tensor<int32, []>(1)]; |
| tensor<bool, []> right_validate_indices_0 = const()[name = tensor<string, []>("right_validate_indices_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 125]> right = gather_along_axis(axis = var_110, indices = _interp_right_idx, validate_indices = right_validate_indices_0, x = weights)[name = tensor<string, []>("right")]; |
| tensor<fp32, [1, 125]> var_113 = mul(x = left, y = _interp_left_weight)[name = tensor<string, []>("op_113")]; |
| tensor<fp32, [1, 125]> var_114 = mul(x = right, y = _interp_right_weight)[name = tensor<string, []>("op_114")]; |
| tensor<fp32, [1, 125]> weights_3 = add(x = var_113, y = var_114)[name = tensor<string, []>("weights_3")]; |
| tensor<int32, []> var_118 = const()[name = tensor<string, []>("op_118"), val = tensor<int32, []>(-1)]; |
| tensor<fp32, []> var_119 = const()[name = tensor<string, []>("op_119"), val = tensor<fp32, []>(0x1.197998p-40)]; |
| tensor<int32, [3]> var_135 = const()[name = tensor<string, []>("op_135"), val = tensor<int32, [3]>([0, 2, 1])]; |
| tensor<int32, [1]> input_5_axes_0 = const()[name = tensor<string, []>("input_5_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [1, 80, 998]> fbank = transpose(perm = var_135, x = fbank_1)[name = tensor<string, []>("transpose_3")]; |
| tensor<fp32, [1, 1, 80, 998]> input_5 = expand_dims(axes = input_5_axes_0, x = fbank)[name = tensor<string, []>("input_5")]; |
| tensor<string, []> input_7_pad_type_0 = const()[name = tensor<string, []>("input_7_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_7_pad_0 = const()[name = tensor<string, []>("input_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_7_strides_0 = const()[name = tensor<string, []>("input_7_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_7_dilations_0 = const()[name = tensor<string, []>("input_7_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_7_groups_0 = const()[name = tensor<string, []>("input_7_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 1, 3, 3]> const_10 = const()[name = tensor<string, []>("const_10"), val = tensor<fp32, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7023616)))]; |
| tensor<fp32, [32]> const_11 = const()[name = tensor<string, []>("const_11"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7024832)))]; |
| tensor<fp32, [1, 32, 80, 998]> input_9 = conv(bias = const_11, 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_10, x = input_5)[name = tensor<string, []>("input_9")]; |
| tensor<fp32, [1, 32, 80, 998]> input_11 = relu(x = input_9)[name = tensor<string, []>("input_11")]; |
| tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_13_strides_0 = const()[name = tensor<string, []>("input_13_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_13_dilations_0 = const()[name = tensor<string, []>("input_13_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_13_groups_0 = const()[name = tensor<string, []>("input_13_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 32, 3, 3]> const_12 = const()[name = tensor<string, []>("const_12"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7025024)))]; |
| tensor<fp32, [32]> const_13 = const()[name = tensor<string, []>("const_13"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7061952)))]; |
| tensor<fp32, [1, 32, 80, 998]> input_15 = conv(bias = const_13, 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_12, x = input_11)[name = tensor<string, []>("input_15")]; |
| tensor<fp32, [1, 32, 80, 998]> input_17 = relu(x = input_15)[name = tensor<string, []>("input_17")]; |
| tensor<string, []> input_19_pad_type_0 = const()[name = tensor<string, []>("input_19_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_19_pad_0 = const()[name = tensor<string, []>("input_19_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_19_strides_0 = const()[name = tensor<string, []>("input_19_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_19_dilations_0 = const()[name = tensor<string, []>("input_19_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_19_groups_0 = const()[name = tensor<string, []>("input_19_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 32, 3, 3]> const_14 = const()[name = tensor<string, []>("const_14"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7062144)))]; |
| tensor<fp32, [32]> const_15 = const()[name = tensor<string, []>("const_15"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7099072)))]; |
| tensor<fp32, [1, 32, 80, 998]> out_1 = conv(bias = const_15, 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_14, x = input_17)[name = tensor<string, []>("out_1")]; |
| tensor<fp32, [1, 32, 80, 998]> input_21 = add(x = out_1, y = input_11)[name = tensor<string, []>("input_21")]; |
| tensor<fp32, [1, 32, 80, 998]> input_23 = relu(x = input_21)[name = tensor<string, []>("input_23")]; |
| tensor<string, []> input_25_pad_type_0 = const()[name = tensor<string, []>("input_25_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_25_pad_0 = const()[name = tensor<string, []>("input_25_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_25_strides_0 = const()[name = tensor<string, []>("input_25_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_25_dilations_0 = const()[name = tensor<string, []>("input_25_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_25_groups_0 = const()[name = tensor<string, []>("input_25_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 32, 3, 3]> const_16 = const()[name = tensor<string, []>("const_16"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7099264)))]; |
| tensor<fp32, [32]> const_17 = const()[name = tensor<string, []>("const_17"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7136192)))]; |
| tensor<fp32, [1, 32, 80, 998]> input_27 = conv(bias = const_17, 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_16, x = input_23)[name = tensor<string, []>("input_27")]; |
| tensor<fp32, [1, 32, 80, 998]> input_29 = relu(x = input_27)[name = tensor<string, []>("input_29")]; |
| tensor<string, []> input_31_pad_type_0 = const()[name = tensor<string, []>("input_31_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_31_pad_0 = const()[name = tensor<string, []>("input_31_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_31_strides_0 = const()[name = tensor<string, []>("input_31_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_31_dilations_0 = const()[name = tensor<string, []>("input_31_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_31_groups_0 = const()[name = tensor<string, []>("input_31_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 32, 3, 3]> const_18 = const()[name = tensor<string, []>("const_18"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7136384)))]; |
| tensor<fp32, [32]> const_19 = const()[name = tensor<string, []>("const_19"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7173312)))]; |
| tensor<fp32, [1, 32, 80, 998]> out_3 = conv(bias = const_19, 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_18, x = input_29)[name = tensor<string, []>("out_3")]; |
| tensor<fp32, [1, 32, 80, 998]> input_33 = add(x = out_3, y = input_23)[name = tensor<string, []>("input_33")]; |
| tensor<fp32, [1, 32, 80, 998]> input_35 = relu(x = input_33)[name = tensor<string, []>("input_35")]; |
| tensor<string, []> input_37_pad_type_0 = const()[name = tensor<string, []>("input_37_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_37_pad_0 = const()[name = tensor<string, []>("input_37_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_37_strides_0 = const()[name = tensor<string, []>("input_37_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_37_dilations_0 = const()[name = tensor<string, []>("input_37_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_37_groups_0 = const()[name = tensor<string, []>("input_37_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 32, 3, 3]> const_20 = const()[name = tensor<string, []>("const_20"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7173504)))]; |
| tensor<fp32, [32]> const_21 = const()[name = tensor<string, []>("const_21"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7210432)))]; |
| tensor<fp32, [1, 32, 80, 998]> input_39 = conv(bias = const_21, 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_20, x = input_35)[name = tensor<string, []>("input_39")]; |
| tensor<fp32, [1, 32, 80, 998]> input_41 = relu(x = input_39)[name = tensor<string, []>("input_41")]; |
| tensor<string, []> input_43_pad_type_0 = const()[name = tensor<string, []>("input_43_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_43_pad_0 = const()[name = tensor<string, []>("input_43_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_43_strides_0 = const()[name = tensor<string, []>("input_43_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_43_dilations_0 = const()[name = tensor<string, []>("input_43_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_43_groups_0 = const()[name = tensor<string, []>("input_43_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [32, 32, 3, 3]> const_22 = const()[name = tensor<string, []>("const_22"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7210624)))]; |
| tensor<fp32, [32]> const_23 = const()[name = tensor<string, []>("const_23"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7247552)))]; |
| tensor<fp32, [1, 32, 80, 998]> out_5 = conv(bias = const_23, 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_22, x = input_41)[name = tensor<string, []>("out_5")]; |
| tensor<fp32, [1, 32, 80, 998]> input_45 = add(x = out_5, y = input_35)[name = tensor<string, []>("input_45")]; |
| tensor<fp32, [1, 32, 80, 998]> input_47 = relu(x = input_45)[name = tensor<string, []>("input_47")]; |
| tensor<string, []> input_49_pad_type_0 = const()[name = tensor<string, []>("input_49_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_49_pad_0 = const()[name = tensor<string, []>("input_49_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_49_strides_0 = const()[name = tensor<string, []>("input_49_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> input_49_dilations_0 = const()[name = tensor<string, []>("input_49_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_49_groups_0 = const()[name = tensor<string, []>("input_49_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 32, 3, 3]> const_24 = const()[name = tensor<string, []>("const_24"), val = tensor<fp32, [64, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7247744)))]; |
| tensor<fp32, [64]> const_25 = const()[name = tensor<string, []>("const_25"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7321536)))]; |
| tensor<fp32, [1, 64, 40, 499]> input_51 = conv(bias = const_25, 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_24, x = input_47)[name = tensor<string, []>("input_51")]; |
| tensor<fp32, [1, 64, 40, 499]> input_53 = relu(x = input_51)[name = tensor<string, []>("input_53")]; |
| tensor<string, []> input_55_pad_type_0 = const()[name = tensor<string, []>("input_55_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_55_pad_0 = const()[name = tensor<string, []>("input_55_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_55_strides_0 = const()[name = tensor<string, []>("input_55_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_55_dilations_0 = const()[name = tensor<string, []>("input_55_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_55_groups_0 = const()[name = tensor<string, []>("input_55_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_26 = const()[name = tensor<string, []>("const_26"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7321856)))]; |
| tensor<fp32, [64]> const_27 = const()[name = tensor<string, []>("const_27"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7469376)))]; |
| tensor<fp32, [1, 64, 40, 499]> out_7 = conv(bias = const_27, 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_26, x = input_53)[name = tensor<string, []>("out_7")]; |
| tensor<string, []> input_57_pad_type_0 = const()[name = tensor<string, []>("input_57_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> input_57_strides_0 = const()[name = tensor<string, []>("input_57_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [4]> input_57_pad_0 = const()[name = tensor<string, []>("input_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<int32, [2]> input_57_dilations_0 = const()[name = tensor<string, []>("input_57_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_57_groups_0 = const()[name = tensor<string, []>("input_57_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 32, 1, 1]> const_28 = const()[name = tensor<string, []>("const_28"), val = tensor<fp32, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7469696)))]; |
| tensor<fp32, [64]> const_29 = const()[name = tensor<string, []>("const_29"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7477952)))]; |
| tensor<fp32, [1, 64, 40, 499]> var_284 = conv(bias = const_29, 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_28, x = input_47)[name = tensor<string, []>("op_284")]; |
| tensor<fp32, [1, 64, 40, 499]> input_59 = add(x = out_7, y = var_284)[name = tensor<string, []>("input_59")]; |
| tensor<fp32, [1, 64, 40, 499]> input_61 = relu(x = input_59)[name = tensor<string, []>("input_61")]; |
| tensor<string, []> input_63_pad_type_0 = const()[name = tensor<string, []>("input_63_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_63_pad_0 = const()[name = tensor<string, []>("input_63_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_63_strides_0 = const()[name = tensor<string, []>("input_63_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_63_dilations_0 = const()[name = tensor<string, []>("input_63_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_63_groups_0 = const()[name = tensor<string, []>("input_63_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_30 = const()[name = tensor<string, []>("const_30"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7478272)))]; |
| tensor<fp32, [64]> const_31 = const()[name = tensor<string, []>("const_31"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7625792)))]; |
| tensor<fp32, [1, 64, 40, 499]> input_65 = conv(bias = const_31, 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_30, x = input_61)[name = tensor<string, []>("input_65")]; |
| tensor<fp32, [1, 64, 40, 499]> input_67 = relu(x = input_65)[name = tensor<string, []>("input_67")]; |
| tensor<string, []> input_69_pad_type_0 = const()[name = tensor<string, []>("input_69_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_69_pad_0 = const()[name = tensor<string, []>("input_69_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_69_strides_0 = const()[name = tensor<string, []>("input_69_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_69_dilations_0 = const()[name = tensor<string, []>("input_69_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_69_groups_0 = const()[name = tensor<string, []>("input_69_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_32 = const()[name = tensor<string, []>("const_32"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7626112)))]; |
| tensor<fp32, [64]> const_33 = const()[name = tensor<string, []>("const_33"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7773632)))]; |
| tensor<fp32, [1, 64, 40, 499]> out_9 = conv(bias = const_33, 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_32, x = input_67)[name = tensor<string, []>("out_9")]; |
| tensor<fp32, [1, 64, 40, 499]> input_71 = add(x = out_9, y = input_61)[name = tensor<string, []>("input_71")]; |
| tensor<fp32, [1, 64, 40, 499]> input_73 = relu(x = input_71)[name = tensor<string, []>("input_73")]; |
| tensor<string, []> input_75_pad_type_0 = const()[name = tensor<string, []>("input_75_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_75_pad_0 = const()[name = tensor<string, []>("input_75_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_75_strides_0 = const()[name = tensor<string, []>("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_75_dilations_0 = const()[name = tensor<string, []>("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_75_groups_0 = const()[name = tensor<string, []>("input_75_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_34 = const()[name = tensor<string, []>("const_34"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7773952)))]; |
| tensor<fp32, [64]> const_35 = const()[name = tensor<string, []>("const_35"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7921472)))]; |
| tensor<fp32, [1, 64, 40, 499]> input_77 = conv(bias = const_35, 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_34, x = input_73)[name = tensor<string, []>("input_77")]; |
| tensor<fp32, [1, 64, 40, 499]> input_79 = relu(x = input_77)[name = tensor<string, []>("input_79")]; |
| tensor<string, []> input_81_pad_type_0 = const()[name = tensor<string, []>("input_81_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_81_pad_0 = const()[name = tensor<string, []>("input_81_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_81_strides_0 = const()[name = tensor<string, []>("input_81_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_81_dilations_0 = const()[name = tensor<string, []>("input_81_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_81_groups_0 = const()[name = tensor<string, []>("input_81_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_36 = const()[name = tensor<string, []>("const_36"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7921792)))]; |
| tensor<fp32, [64]> const_37 = const()[name = tensor<string, []>("const_37"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8069312)))]; |
| tensor<fp32, [1, 64, 40, 499]> out_11 = conv(bias = const_37, 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_36, x = input_79)[name = tensor<string, []>("out_11")]; |
| tensor<fp32, [1, 64, 40, 499]> input_83 = add(x = out_11, y = input_73)[name = tensor<string, []>("input_83")]; |
| tensor<fp32, [1, 64, 40, 499]> input_85 = relu(x = input_83)[name = tensor<string, []>("input_85")]; |
| tensor<string, []> input_87_pad_type_0 = const()[name = tensor<string, []>("input_87_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_87_pad_0 = const()[name = tensor<string, []>("input_87_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_87_strides_0 = const()[name = tensor<string, []>("input_87_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_87_dilations_0 = const()[name = tensor<string, []>("input_87_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_87_groups_0 = const()[name = tensor<string, []>("input_87_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_38 = const()[name = tensor<string, []>("const_38"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8069632)))]; |
| tensor<fp32, [64]> const_39 = const()[name = tensor<string, []>("const_39"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8217152)))]; |
| tensor<fp32, [1, 64, 40, 499]> input_89 = conv(bias = const_39, 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_38, x = input_85)[name = tensor<string, []>("input_89")]; |
| tensor<fp32, [1, 64, 40, 499]> input_91 = relu(x = input_89)[name = tensor<string, []>("input_91")]; |
| tensor<string, []> input_93_pad_type_0 = const()[name = tensor<string, []>("input_93_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_93_pad_0 = const()[name = tensor<string, []>("input_93_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_93_strides_0 = const()[name = tensor<string, []>("input_93_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_93_dilations_0 = const()[name = tensor<string, []>("input_93_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_93_groups_0 = const()[name = tensor<string, []>("input_93_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [64, 64, 3, 3]> const_40 = const()[name = tensor<string, []>("const_40"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8217472)))]; |
| tensor<fp32, [64]> const_41 = const()[name = tensor<string, []>("const_41"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8364992)))]; |
| tensor<fp32, [1, 64, 40, 499]> out_13 = conv(bias = const_41, 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_40, x = input_91)[name = tensor<string, []>("out_13")]; |
| tensor<fp32, [1, 64, 40, 499]> input_95 = add(x = out_13, y = input_85)[name = tensor<string, []>("input_95")]; |
| tensor<fp32, [1, 64, 40, 499]> input_97 = relu(x = input_95)[name = tensor<string, []>("input_97")]; |
| tensor<string, []> input_99_pad_type_0 = const()[name = tensor<string, []>("input_99_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_99_pad_0 = const()[name = tensor<string, []>("input_99_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_99_strides_0 = const()[name = tensor<string, []>("input_99_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> input_99_dilations_0 = const()[name = tensor<string, []>("input_99_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_99_groups_0 = const()[name = tensor<string, []>("input_99_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 64, 3, 3]> const_42 = const()[name = tensor<string, []>("const_42"), val = tensor<fp32, [128, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8365312)))]; |
| tensor<fp32, [128]> const_43 = const()[name = tensor<string, []>("const_43"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8660288)))]; |
| tensor<fp32, [1, 128, 20, 250]> input_101 = conv(bias = const_43, 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_42, x = input_97)[name = tensor<string, []>("input_101")]; |
| tensor<fp32, [1, 128, 20, 250]> input_103 = relu(x = input_101)[name = tensor<string, []>("input_103")]; |
| tensor<string, []> input_105_pad_type_0 = const()[name = tensor<string, []>("input_105_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_105_pad_0 = const()[name = tensor<string, []>("input_105_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_105_strides_0 = const()[name = tensor<string, []>("input_105_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_105_dilations_0 = const()[name = tensor<string, []>("input_105_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_105_groups_0 = const()[name = tensor<string, []>("input_105_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_44 = const()[name = tensor<string, []>("const_44"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8660864)))]; |
| tensor<fp32, [128]> const_45 = const()[name = tensor<string, []>("const_45"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9250752)))]; |
| tensor<fp32, [1, 128, 20, 250]> out_15 = conv(bias = const_45, 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_44, x = input_103)[name = tensor<string, []>("out_15")]; |
| tensor<string, []> input_107_pad_type_0 = const()[name = tensor<string, []>("input_107_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> input_107_strides_0 = const()[name = tensor<string, []>("input_107_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [4]> input_107_pad_0 = const()[name = tensor<string, []>("input_107_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<int32, [2]> input_107_dilations_0 = const()[name = tensor<string, []>("input_107_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_107_groups_0 = const()[name = tensor<string, []>("input_107_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 64, 1, 1]> const_46 = const()[name = tensor<string, []>("const_46"), val = tensor<fp32, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9251328)))]; |
| tensor<fp32, [128]> const_47 = const()[name = tensor<string, []>("const_47"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9284160)))]; |
| tensor<fp32, [1, 128, 20, 250]> var_420 = conv(bias = const_47, 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_46, x = input_97)[name = tensor<string, []>("op_420")]; |
| tensor<fp32, [1, 128, 20, 250]> input_109 = add(x = out_15, y = var_420)[name = tensor<string, []>("input_109")]; |
| tensor<fp32, [1, 128, 20, 250]> input_111 = relu(x = input_109)[name = tensor<string, []>("input_111")]; |
| tensor<string, []> input_113_pad_type_0 = const()[name = tensor<string, []>("input_113_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_113_pad_0 = const()[name = tensor<string, []>("input_113_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_113_strides_0 = const()[name = tensor<string, []>("input_113_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_113_dilations_0 = const()[name = tensor<string, []>("input_113_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_113_groups_0 = const()[name = tensor<string, []>("input_113_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_48 = const()[name = tensor<string, []>("const_48"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9284736)))]; |
| tensor<fp32, [128]> const_49 = const()[name = tensor<string, []>("const_49"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9874624)))]; |
| tensor<fp32, [1, 128, 20, 250]> input_115 = conv(bias = const_49, 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_48, x = input_111)[name = tensor<string, []>("input_115")]; |
| tensor<fp32, [1, 128, 20, 250]> input_117 = relu(x = input_115)[name = tensor<string, []>("input_117")]; |
| tensor<string, []> input_119_pad_type_0 = const()[name = tensor<string, []>("input_119_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_119_pad_0 = const()[name = tensor<string, []>("input_119_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_119_strides_0 = const()[name = tensor<string, []>("input_119_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_119_dilations_0 = const()[name = tensor<string, []>("input_119_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_119_groups_0 = const()[name = tensor<string, []>("input_119_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_50 = const()[name = tensor<string, []>("const_50"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9875200)))]; |
| tensor<fp32, [128]> const_51 = const()[name = tensor<string, []>("const_51"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10465088)))]; |
| tensor<fp32, [1, 128, 20, 250]> out_17 = conv(bias = const_51, 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_50, x = input_117)[name = tensor<string, []>("out_17")]; |
| tensor<fp32, [1, 128, 20, 250]> input_121 = add(x = out_17, y = input_111)[name = tensor<string, []>("input_121")]; |
| tensor<fp32, [1, 128, 20, 250]> input_123 = relu(x = input_121)[name = tensor<string, []>("input_123")]; |
| tensor<string, []> input_125_pad_type_0 = const()[name = tensor<string, []>("input_125_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_125_pad_0 = const()[name = tensor<string, []>("input_125_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_125_strides_0 = const()[name = tensor<string, []>("input_125_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_125_dilations_0 = const()[name = tensor<string, []>("input_125_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_125_groups_0 = const()[name = tensor<string, []>("input_125_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_52 = const()[name = tensor<string, []>("const_52"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10465664)))]; |
| tensor<fp32, [128]> const_53 = const()[name = tensor<string, []>("const_53"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11055552)))]; |
| tensor<fp32, [1, 128, 20, 250]> input_127 = conv(bias = const_53, 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_52, x = input_123)[name = tensor<string, []>("input_127")]; |
| tensor<fp32, [1, 128, 20, 250]> input_129 = relu(x = input_127)[name = tensor<string, []>("input_129")]; |
| tensor<string, []> input_131_pad_type_0 = const()[name = tensor<string, []>("input_131_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_131_pad_0 = const()[name = tensor<string, []>("input_131_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_131_strides_0 = const()[name = tensor<string, []>("input_131_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_131_dilations_0 = const()[name = tensor<string, []>("input_131_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_131_groups_0 = const()[name = tensor<string, []>("input_131_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_54 = const()[name = tensor<string, []>("const_54"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11056128)))]; |
| tensor<fp32, [128]> const_55 = const()[name = tensor<string, []>("const_55"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11646016)))]; |
| tensor<fp32, [1, 128, 20, 250]> out_19 = conv(bias = const_55, 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_54, x = input_129)[name = tensor<string, []>("out_19")]; |
| tensor<fp32, [1, 128, 20, 250]> input_133 = add(x = out_19, y = input_123)[name = tensor<string, []>("input_133")]; |
| tensor<fp32, [1, 128, 20, 250]> input_135 = relu(x = input_133)[name = tensor<string, []>("input_135")]; |
| tensor<string, []> input_137_pad_type_0 = const()[name = tensor<string, []>("input_137_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_137_pad_0 = const()[name = tensor<string, []>("input_137_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_137_strides_0 = const()[name = tensor<string, []>("input_137_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_137_dilations_0 = const()[name = tensor<string, []>("input_137_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_137_groups_0 = const()[name = tensor<string, []>("input_137_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_56 = const()[name = tensor<string, []>("const_56"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11646592)))]; |
| tensor<fp32, [128]> const_57 = const()[name = tensor<string, []>("const_57"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12236480)))]; |
| tensor<fp32, [1, 128, 20, 250]> input_139 = conv(bias = const_57, 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_56, x = input_135)[name = tensor<string, []>("input_139")]; |
| tensor<fp32, [1, 128, 20, 250]> input_141 = relu(x = input_139)[name = tensor<string, []>("input_141")]; |
| tensor<string, []> input_143_pad_type_0 = const()[name = tensor<string, []>("input_143_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_143_pad_0 = const()[name = tensor<string, []>("input_143_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_143_strides_0 = const()[name = tensor<string, []>("input_143_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_143_dilations_0 = const()[name = tensor<string, []>("input_143_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_143_groups_0 = const()[name = tensor<string, []>("input_143_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_58 = const()[name = tensor<string, []>("const_58"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12237056)))]; |
| tensor<fp32, [128]> const_59 = const()[name = tensor<string, []>("const_59"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12826944)))]; |
| tensor<fp32, [1, 128, 20, 250]> out_21 = conv(bias = const_59, 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_58, x = input_141)[name = tensor<string, []>("out_21")]; |
| tensor<fp32, [1, 128, 20, 250]> input_145 = add(x = out_21, y = input_135)[name = tensor<string, []>("input_145")]; |
| tensor<fp32, [1, 128, 20, 250]> input_147 = relu(x = input_145)[name = tensor<string, []>("input_147")]; |
| tensor<string, []> input_149_pad_type_0 = const()[name = tensor<string, []>("input_149_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_149_pad_0 = const()[name = tensor<string, []>("input_149_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_149_strides_0 = const()[name = tensor<string, []>("input_149_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_149_dilations_0 = const()[name = tensor<string, []>("input_149_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_149_groups_0 = const()[name = tensor<string, []>("input_149_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_60 = const()[name = tensor<string, []>("const_60"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12827520)))]; |
| tensor<fp32, [128]> const_61 = const()[name = tensor<string, []>("const_61"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13417408)))]; |
| tensor<fp32, [1, 128, 20, 250]> input_151 = conv(bias = const_61, 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_60, x = input_147)[name = tensor<string, []>("input_151")]; |
| tensor<fp32, [1, 128, 20, 250]> input_153 = relu(x = input_151)[name = tensor<string, []>("input_153")]; |
| tensor<string, []> input_155_pad_type_0 = const()[name = tensor<string, []>("input_155_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_155_pad_0 = const()[name = tensor<string, []>("input_155_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_155_strides_0 = const()[name = tensor<string, []>("input_155_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_155_dilations_0 = const()[name = tensor<string, []>("input_155_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_155_groups_0 = const()[name = tensor<string, []>("input_155_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_62 = const()[name = tensor<string, []>("const_62"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13417984)))]; |
| tensor<fp32, [128]> const_63 = const()[name = tensor<string, []>("const_63"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14007872)))]; |
| tensor<fp32, [1, 128, 20, 250]> out_23 = conv(bias = const_63, 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_62, x = input_153)[name = tensor<string, []>("out_23")]; |
| tensor<fp32, [1, 128, 20, 250]> input_157 = add(x = out_23, y = input_147)[name = tensor<string, []>("input_157")]; |
| tensor<fp32, [1, 128, 20, 250]> input_159 = relu(x = input_157)[name = tensor<string, []>("input_159")]; |
| tensor<string, []> input_161_pad_type_0 = const()[name = tensor<string, []>("input_161_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_161_pad_0 = const()[name = tensor<string, []>("input_161_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_161_strides_0 = const()[name = tensor<string, []>("input_161_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_161_dilations_0 = const()[name = tensor<string, []>("input_161_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_161_groups_0 = const()[name = tensor<string, []>("input_161_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_64 = const()[name = tensor<string, []>("const_64"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14008448)))]; |
| tensor<fp32, [128]> const_65 = const()[name = tensor<string, []>("const_65"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14598336)))]; |
| tensor<fp32, [1, 128, 20, 250]> input_163 = conv(bias = const_65, 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_64, x = input_159)[name = tensor<string, []>("input_163")]; |
| tensor<fp32, [1, 128, 20, 250]> input_165 = relu(x = input_163)[name = tensor<string, []>("input_165")]; |
| tensor<string, []> input_167_pad_type_0 = const()[name = tensor<string, []>("input_167_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_167_pad_0 = const()[name = tensor<string, []>("input_167_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_167_strides_0 = const()[name = tensor<string, []>("input_167_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_167_dilations_0 = const()[name = tensor<string, []>("input_167_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_167_groups_0 = const()[name = tensor<string, []>("input_167_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [128, 128, 3, 3]> const_66 = const()[name = tensor<string, []>("const_66"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14598912)))]; |
| tensor<fp32, [128]> const_67 = const()[name = tensor<string, []>("const_67"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15188800)))]; |
| tensor<fp32, [1, 128, 20, 250]> out_25 = conv(bias = const_67, 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_66, x = input_165)[name = tensor<string, []>("out_25")]; |
| tensor<fp32, [1, 128, 20, 250]> input_169 = add(x = out_25, y = input_159)[name = tensor<string, []>("input_169")]; |
| tensor<fp32, [1, 128, 20, 250]> input_171 = relu(x = input_169)[name = tensor<string, []>("input_171")]; |
| tensor<string, []> input_173_pad_type_0 = const()[name = tensor<string, []>("input_173_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_173_pad_0 = const()[name = tensor<string, []>("input_173_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_173_strides_0 = const()[name = tensor<string, []>("input_173_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [2]> input_173_dilations_0 = const()[name = tensor<string, []>("input_173_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_173_groups_0 = const()[name = tensor<string, []>("input_173_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 128, 3, 3]> const_68 = const()[name = tensor<string, []>("const_68"), val = tensor<fp32, [256, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15189376)))]; |
| tensor<fp32, [256]> const_69 = const()[name = tensor<string, []>("const_69"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16369088)))]; |
| tensor<fp32, [1, 256, 10, 125]> input_175 = conv(bias = const_69, 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_68, x = input_171)[name = tensor<string, []>("input_175")]; |
| tensor<fp32, [1, 256, 10, 125]> input_177 = relu(x = input_175)[name = tensor<string, []>("input_177")]; |
| tensor<string, []> input_179_pad_type_0 = const()[name = tensor<string, []>("input_179_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_179_pad_0 = const()[name = tensor<string, []>("input_179_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_179_strides_0 = const()[name = tensor<string, []>("input_179_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_179_dilations_0 = const()[name = tensor<string, []>("input_179_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_179_groups_0 = const()[name = tensor<string, []>("input_179_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 256, 3, 3]> const_70 = const()[name = tensor<string, []>("const_70"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16370176)))]; |
| tensor<fp32, [256]> const_71 = const()[name = tensor<string, []>("const_71"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18729536)))]; |
| tensor<fp32, [1, 256, 10, 125]> out_27 = conv(bias = const_71, 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_70, x = input_177)[name = tensor<string, []>("out_27")]; |
| tensor<string, []> input_181_pad_type_0 = const()[name = tensor<string, []>("input_181_pad_type_0"), val = tensor<string, []>("valid")]; |
| tensor<int32, [2]> input_181_strides_0 = const()[name = tensor<string, []>("input_181_strides_0"), val = tensor<int32, [2]>([2, 2])]; |
| tensor<int32, [4]> input_181_pad_0 = const()[name = tensor<string, []>("input_181_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; |
| tensor<int32, [2]> input_181_dilations_0 = const()[name = tensor<string, []>("input_181_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_181_groups_0 = const()[name = tensor<string, []>("input_181_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 128, 1, 1]> const_72 = const()[name = tensor<string, []>("const_72"), val = tensor<fp32, [256, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18730624)))]; |
| tensor<fp32, [256]> const_73 = const()[name = tensor<string, []>("const_73"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18861760)))]; |
| tensor<fp32, [1, 256, 10, 125]> var_611 = conv(bias = const_73, 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_72, x = input_171)[name = tensor<string, []>("op_611")]; |
| tensor<fp32, [1, 256, 10, 125]> input_183 = add(x = out_27, y = var_611)[name = tensor<string, []>("input_183")]; |
| tensor<fp32, [1, 256, 10, 125]> input_185 = relu(x = input_183)[name = tensor<string, []>("input_185")]; |
| tensor<string, []> input_187_pad_type_0 = const()[name = tensor<string, []>("input_187_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_187_pad_0 = const()[name = tensor<string, []>("input_187_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_187_strides_0 = const()[name = tensor<string, []>("input_187_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_187_dilations_0 = const()[name = tensor<string, []>("input_187_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_187_groups_0 = const()[name = tensor<string, []>("input_187_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 256, 3, 3]> const_74 = const()[name = tensor<string, []>("const_74"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18862848)))]; |
| tensor<fp32, [256]> const_75 = const()[name = tensor<string, []>("const_75"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21222208)))]; |
| tensor<fp32, [1, 256, 10, 125]> input_189 = conv(bias = const_75, 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_74, x = input_185)[name = tensor<string, []>("input_189")]; |
| tensor<fp32, [1, 256, 10, 125]> input_191 = relu(x = input_189)[name = tensor<string, []>("input_191")]; |
| tensor<string, []> input_193_pad_type_0 = const()[name = tensor<string, []>("input_193_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_193_pad_0 = const()[name = tensor<string, []>("input_193_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_193_strides_0 = const()[name = tensor<string, []>("input_193_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_193_dilations_0 = const()[name = tensor<string, []>("input_193_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_193_groups_0 = const()[name = tensor<string, []>("input_193_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 256, 3, 3]> const_76 = const()[name = tensor<string, []>("const_76"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21223296)))]; |
| tensor<fp32, [256]> const_77 = const()[name = tensor<string, []>("const_77"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23582656)))]; |
| tensor<fp32, [1, 256, 10, 125]> out_29 = conv(bias = const_77, 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_76, x = input_191)[name = tensor<string, []>("out_29")]; |
| tensor<fp32, [1, 256, 10, 125]> input_195 = add(x = out_29, y = input_185)[name = tensor<string, []>("input_195")]; |
| tensor<fp32, [1, 256, 10, 125]> input_197 = relu(x = input_195)[name = tensor<string, []>("input_197")]; |
| tensor<string, []> input_199_pad_type_0 = const()[name = tensor<string, []>("input_199_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_199_pad_0 = const()[name = tensor<string, []>("input_199_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_199_strides_0 = const()[name = tensor<string, []>("input_199_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_199_dilations_0 = const()[name = tensor<string, []>("input_199_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_199_groups_0 = const()[name = tensor<string, []>("input_199_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 256, 3, 3]> const_78 = const()[name = tensor<string, []>("const_78"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23583744)))]; |
| tensor<fp32, [256]> const_79 = const()[name = tensor<string, []>("const_79"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25943104)))]; |
| tensor<fp32, [1, 256, 10, 125]> input_201 = conv(bias = const_79, 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_78, x = input_197)[name = tensor<string, []>("input_201")]; |
| tensor<fp32, [1, 256, 10, 125]> input_203 = relu(x = input_201)[name = tensor<string, []>("input_203")]; |
| tensor<string, []> input_205_pad_type_0 = const()[name = tensor<string, []>("input_205_pad_type_0"), val = tensor<string, []>("custom")]; |
| tensor<int32, [4]> input_205_pad_0 = const()[name = tensor<string, []>("input_205_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; |
| tensor<int32, [2]> input_205_strides_0 = const()[name = tensor<string, []>("input_205_strides_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, [2]> input_205_dilations_0 = const()[name = tensor<string, []>("input_205_dilations_0"), val = tensor<int32, [2]>([1, 1])]; |
| tensor<int32, []> input_205_groups_0 = const()[name = tensor<string, []>("input_205_groups_0"), val = tensor<int32, []>(1)]; |
| tensor<fp32, [256, 256, 3, 3]> const_80 = const()[name = tensor<string, []>("const_80"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25944192)))]; |
| tensor<fp32, [256]> const_81 = const()[name = tensor<string, []>("const_81"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28303552)))]; |
| tensor<fp32, [1, 256, 10, 125]> out = conv(bias = const_81, 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_80, x = input_203)[name = tensor<string, []>("out")]; |
| tensor<fp32, [1, 256, 10, 125]> input_207 = add(x = out, y = input_197)[name = tensor<string, []>("input_207")]; |
| tensor<fp32, [1, 256, 10, 125]> features = relu(x = input_207)[name = tensor<string, []>("features")]; |
| tensor<int32, [3]> var_680 = const()[name = tensor<string, []>("op_680"), val = tensor<int32, [3]>([1, 2560, 125])]; |
| tensor<fp32, [1, 2560, 125]> sequences = reshape(shape = var_680, x = features)[name = tensor<string, []>("sequences")]; |
| tensor<int32, [1]> weights_5_axes_0 = const()[name = tensor<string, []>("weights_5_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [1, 1, 125]> weights_5 = expand_dims(axes = weights_5_axes_0, x = weights_3)[name = tensor<string, []>("weights_5")]; |
| tensor<int32, [1]> weights_axes_0 = const()[name = tensor<string, []>("weights_axes_0"), val = tensor<int32, [1]>([2])]; |
| tensor<fp32, [1, 1, 1, 125]> weights_1 = expand_dims(axes = weights_axes_0, x = weights_5)[name = tensor<string, []>("weights")]; |
| tensor<int32, [1]> var_685_axes_0 = const()[name = tensor<string, []>("op_685_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<bool, []> var_685_keep_dims_0 = const()[name = tensor<string, []>("op_685_keep_dims_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 1, 1]> var_685 = reduce_sum(axes = var_685_axes_0, keep_dims = var_685_keep_dims_0, x = weights_1)[name = tensor<string, []>("op_685")]; |
| tensor<fp32, []> var_686 = const()[name = tensor<string, []>("op_686"), val = tensor<fp32, []>(0x1.5798eep-27)]; |
| tensor<fp32, [1, 1, 1]> v1 = add(x = var_685, y = var_686)[name = tensor<string, []>("v1")]; |
| tensor<int32, [1]> var_688_axes_0 = const()[name = tensor<string, []>("op_688_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [1, 1, 2560, 125]> var_688 = expand_dims(axes = var_688_axes_0, x = sequences)[name = tensor<string, []>("op_688")]; |
| tensor<fp32, [1, 1, 2560, 125]> weighted = mul(x = var_688, y = weights_1)[name = tensor<string, []>("weighted")]; |
| tensor<int32, [1]> var_691_axes_0 = const()[name = tensor<string, []>("op_691_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<bool, []> var_691_keep_dims_0 = const()[name = tensor<string, []>("op_691_keep_dims_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 1, 2560]> var_691 = reduce_sum(axes = var_691_axes_0, keep_dims = var_691_keep_dims_0, x = weighted)[name = tensor<string, []>("op_691")]; |
| tensor<fp32, [1, 1, 2560]> mean = real_div(x = var_691, y = v1)[name = tensor<string, []>("mean")]; |
| tensor<int32, [1]> var_694_axes_0 = const()[name = tensor<string, []>("op_694_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp32, [1, 1, 2560, 1]> var_694 = expand_dims(axes = var_694_axes_0, x = mean)[name = tensor<string, []>("op_694")]; |
| tensor<fp32, [1, 1, 2560, 125]> diff = sub(x = var_688, y = var_694)[name = tensor<string, []>("diff")]; |
| tensor<fp32, [1, 1, 1, 125]> var_696 = mul(x = weights_1, y = weights_1)[name = tensor<string, []>("op_696")]; |
| tensor<int32, [1]> v2_axes_0 = const()[name = tensor<string, []>("v2_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<bool, []> v2_keep_dims_0 = const()[name = tensor<string, []>("v2_keep_dims_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 1, 1]> v2 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_696)[name = tensor<string, []>("v2")]; |
| tensor<fp32, [1, 1, 1]> var_699 = real_div(x = v2, y = v1)[name = tensor<string, []>("op_699")]; |
| tensor<fp32, [1, 1, 1]> var_700 = sub(x = v1, y = var_699)[name = tensor<string, []>("op_700")]; |
| tensor<fp32, []> var_701 = const()[name = tensor<string, []>("op_701"), val = tensor<fp32, []>(0x1.5798eep-27)]; |
| tensor<fp32, [1, 1, 1]> denom = add(x = var_700, y = var_701)[name = tensor<string, []>("denom")]; |
| tensor<fp32, [1, 1, 2560, 125]> var_703 = mul(x = diff, y = diff)[name = tensor<string, []>("op_703")]; |
| tensor<fp32, [1, 1, 2560, 125]> var_704 = mul(x = var_703, y = weights_1)[name = tensor<string, []>("op_704")]; |
| tensor<int32, [1]> var_706_axes_0 = const()[name = tensor<string, []>("op_706_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<bool, []> var_706_keep_dims_0 = const()[name = tensor<string, []>("op_706_keep_dims_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 1, 2560]> var_706 = reduce_sum(axes = var_706_axes_0, keep_dims = var_706_keep_dims_0, x = var_704)[name = tensor<string, []>("op_706")]; |
| tensor<fp32, [1, 1, 2560]> var = real_div(x = var_706, y = denom)[name = tensor<string, []>("var")]; |
| tensor<fp32, []> const_8 = const()[name = tensor<string, []>("const_8"), val = tensor<fp32, []>(0x1.fffffep+127)]; |
| tensor<fp32, [1, 1, 2560]> clip_1 = clip(alpha = var_119, beta = const_8, x = var)[name = tensor<string, []>("clip_1")]; |
| tensor<fp32, [1, 1, 2560]> std = sqrt(x = clip_1)[name = tensor<string, []>("std")]; |
| tensor<bool, []> output_interleave_0 = const()[name = tensor<string, []>("output_interleave_0"), val = tensor<bool, []>(false)]; |
| tensor<fp32, [1, 1, 5120]> output = concat(axis = var_118, interleave = output_interleave_0, values = (mean, std))[name = tensor<string, []>("output")]; |
| tensor<int32, [1]> input_209_axes_0 = const()[name = tensor<string, []>("input_209_axes_0"), val = tensor<int32, [1]>([1])]; |
| tensor<fp32, [1, 5120]> input_209 = squeeze(axes = input_209_axes_0, x = output)[name = tensor<string, []>("input_209")]; |
| tensor<fp32, [1, 256]> input = linear(bias = resnet_seg_1_bias, weight = resnet_seg_1_weight, x = input_209)[name = tensor<string, []>("linear_0")]; |
| tensor<int32, [1]> var_718 = const()[name = tensor<string, []>("op_718"), val = tensor<int32, [1]>([-1])]; |
| tensor<bool, []> var_719 = const()[name = tensor<string, []>("op_719"), val = tensor<bool, []>(true)]; |
| tensor<fp32, [1, 1]> norms_1 = reduce_l2_norm(axes = var_718, keep_dims = var_719, x = input)[name = tensor<string, []>("norms_1")]; |
| tensor<fp32, []> var_722 = const()[name = tensor<string, []>("op_722"), val = tensor<fp32, []>(0x1.197998p-40)]; |
| tensor<fp32, []> const_9 = const()[name = tensor<string, []>("const_9"), val = tensor<fp32, []>(0x1.fffffep+127)]; |
| tensor<fp32, [1, 1]> clip_2 = clip(alpha = var_722, beta = const_9, x = norms_1)[name = tensor<string, []>("clip_2")]; |
| tensor<fp32, [1, 256]> embedding = real_div(x = input, y = clip_2)[name = tensor<string, []>("op_725")]; |
| } -> (embedding); |
| } |
