| program(1.0) | |
| [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3401.3.1"}, {"coremlc-version", "3401.4.1"}})] | |
| { | |
| func main<ios16>(tensor<fp16, [1, 998, 80]> preprocessor_output_1, tensor<fp16, [1, 3, 589]> speaker_masks) { | |
| tensor<int32, []> var_12 = const()[name = tensor<string, []>("op_12"), val = tensor<int32, []>(1)]; | |
| tensor<int32, [3]> var_22 = const()[name = tensor<string, []>("op_22"), val = tensor<int32, [3]>([0, 2, 1])]; | |
| tensor<int32, [1]> input_1_axes_0 = const()[name = tensor<string, []>("input_1_axes_0"), val = tensor<int32, [1]>([1])]; | |
| tensor<fp16, [1, 80, 998]> fbank_cast_fp16 = transpose(perm = var_22, x = preprocessor_output_1)[name = tensor<string, []>("transpose_0")]; | |
| tensor<fp16, [1, 1, 80, 998]> input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = fbank_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")]; | |
| tensor<string, []> input_3_pad_type_0 = const()[name = tensor<string, []>("input_3_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_3_pad_0 = const()[name = tensor<string, []>("input_3_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_3_strides_0 = const()[name = tensor<string, []>("input_3_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_3_dilations_0 = const()[name = tensor<string, []>("input_3_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_3_groups_0 = const()[name = tensor<string, []>("input_3_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 1, 3, 3]> const_5_to_fp16 = const()[name = tensor<string, []>("const_5_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))]; | |
| tensor<fp16, [32]> const_6_to_fp16 = const()[name = tensor<string, []>("const_6_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(704)))]; | |
| tensor<fp16, [1, 32, 80, 998]> input_5_cast_fp16 = conv(bias = const_6_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = const_5_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_7_cast_fp16 = relu(x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")]; | |
| tensor<string, []> input_9_pad_type_0 = const()[name = tensor<string, []>("input_9_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_9_pad_0 = const()[name = tensor<string, []>("input_9_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_9_strides_0 = const()[name = tensor<string, []>("input_9_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_9_dilations_0 = const()[name = tensor<string, []>("input_9_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_9_groups_0 = const()[name = tensor<string, []>("input_9_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 32, 3, 3]> const_7_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6912]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7808))), name = tensor<string, []>("const_7_to_fp16_palettized"), shape = tensor<uint32, [4]>([32, 32, 3, 3])]; | |
| tensor<fp16, [32]> const_8_to_fp16 = const()[name = tensor<string, []>("const_8_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8000)))]; | |
| tensor<fp16, [1, 32, 80, 998]> input_11_cast_fp16 = conv(bias = const_8_to_fp16, dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = const_7_to_fp16_palettized, x = input_7_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_13_cast_fp16 = relu(x = input_11_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")]; | |
| tensor<string, []> input_15_pad_type_0 = const()[name = tensor<string, []>("input_15_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_15_pad_0 = const()[name = tensor<string, []>("input_15_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_15_strides_0 = const()[name = tensor<string, []>("input_15_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_15_dilations_0 = const()[name = tensor<string, []>("input_15_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_15_groups_0 = const()[name = tensor<string, []>("input_15_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 32, 3, 3]> const_9_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6912]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8128))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15104))), name = tensor<string, []>("const_9_to_fp16_palettized"), shape = tensor<uint32, [4]>([32, 32, 3, 3])]; | |
| tensor<fp16, [32]> const_10_to_fp16 = const()[name = tensor<string, []>("const_10_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15296)))]; | |
| tensor<fp16, [1, 32, 80, 998]> out_1_cast_fp16 = conv(bias = const_10_to_fp16, dilations = input_15_dilations_0, groups = input_15_groups_0, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = input_15_strides_0, weight = const_9_to_fp16_palettized, x = input_13_cast_fp16)[name = tensor<string, []>("out_1_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_17_cast_fp16 = add(x = out_1_cast_fp16, y = input_7_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_19_cast_fp16 = relu(x = input_17_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")]; | |
| tensor<string, []> input_21_pad_type_0 = const()[name = tensor<string, []>("input_21_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_21_pad_0 = const()[name = tensor<string, []>("input_21_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_21_strides_0 = const()[name = tensor<string, []>("input_21_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_21_dilations_0 = const()[name = tensor<string, []>("input_21_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_21_groups_0 = const()[name = tensor<string, []>("input_21_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 32, 3, 3]> const_11_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6912]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15424))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22400))), name = tensor<string, []>("const_11_to_fp16_palettized"), shape = tensor<uint32, [4]>([32, 32, 3, 3])]; | |
| tensor<fp16, [32]> const_12_to_fp16 = const()[name = tensor<string, []>("const_12_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22592)))]; | |
| tensor<fp16, [1, 32, 80, 998]> input_23_cast_fp16 = conv(bias = const_12_to_fp16, dilations = input_21_dilations_0, groups = input_21_groups_0, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = input_21_strides_0, weight = const_11_to_fp16_palettized, x = input_19_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_25_cast_fp16 = relu(x = input_23_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")]; | |
| tensor<string, []> input_27_pad_type_0 = const()[name = tensor<string, []>("input_27_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_27_pad_0 = const()[name = tensor<string, []>("input_27_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_27_strides_0 = const()[name = tensor<string, []>("input_27_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_27_dilations_0 = const()[name = tensor<string, []>("input_27_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_27_groups_0 = const()[name = tensor<string, []>("input_27_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 32, 3, 3]> const_13_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6912]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22720))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29696))), name = tensor<string, []>("const_13_to_fp16_palettized"), shape = tensor<uint32, [4]>([32, 32, 3, 3])]; | |
| tensor<fp16, [32]> const_14_to_fp16 = const()[name = tensor<string, []>("const_14_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29888)))]; | |
| tensor<fp16, [1, 32, 80, 998]> out_3_cast_fp16 = conv(bias = const_14_to_fp16, dilations = input_27_dilations_0, groups = input_27_groups_0, pad = input_27_pad_0, pad_type = input_27_pad_type_0, strides = input_27_strides_0, weight = const_13_to_fp16_palettized, x = input_25_cast_fp16)[name = tensor<string, []>("out_3_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_29_cast_fp16 = add(x = out_3_cast_fp16, y = input_19_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_31_cast_fp16 = relu(x = input_29_cast_fp16)[name = tensor<string, []>("input_31_cast_fp16")]; | |
| tensor<string, []> input_33_pad_type_0 = const()[name = tensor<string, []>("input_33_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_33_pad_0 = const()[name = tensor<string, []>("input_33_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_33_strides_0 = const()[name = tensor<string, []>("input_33_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_33_dilations_0 = const()[name = tensor<string, []>("input_33_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_33_groups_0 = const()[name = tensor<string, []>("input_33_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 32, 3, 3]> const_15_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6912]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30016))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36992))), name = tensor<string, []>("const_15_to_fp16_palettized"), shape = tensor<uint32, [4]>([32, 32, 3, 3])]; | |
| tensor<fp16, [32]> const_16_to_fp16 = const()[name = tensor<string, []>("const_16_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37184)))]; | |
| tensor<fp16, [1, 32, 80, 998]> input_35_cast_fp16 = conv(bias = const_16_to_fp16, dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = const_15_to_fp16_palettized, x = input_31_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_37_cast_fp16 = relu(x = input_35_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")]; | |
| tensor<string, []> input_39_pad_type_0 = const()[name = tensor<string, []>("input_39_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_39_pad_0 = const()[name = tensor<string, []>("input_39_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_39_strides_0 = const()[name = tensor<string, []>("input_39_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_39_dilations_0 = const()[name = tensor<string, []>("input_39_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_39_groups_0 = const()[name = tensor<string, []>("input_39_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [32, 32, 3, 3]> const_17_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6912]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(37312))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44288))), name = tensor<string, []>("const_17_to_fp16_palettized"), shape = tensor<uint32, [4]>([32, 32, 3, 3])]; | |
| tensor<fp16, [32]> const_18_to_fp16 = const()[name = tensor<string, []>("const_18_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44480)))]; | |
| tensor<fp16, [1, 32, 80, 998]> out_5_cast_fp16 = conv(bias = const_18_to_fp16, dilations = input_39_dilations_0, groups = input_39_groups_0, pad = input_39_pad_0, pad_type = input_39_pad_type_0, strides = input_39_strides_0, weight = const_17_to_fp16_palettized, x = input_37_cast_fp16)[name = tensor<string, []>("out_5_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_41_cast_fp16 = add(x = out_5_cast_fp16, y = input_31_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")]; | |
| tensor<fp16, [1, 32, 80, 998]> input_43_cast_fp16 = relu(x = input_41_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")]; | |
| tensor<string, []> input_45_pad_type_0 = const()[name = tensor<string, []>("input_45_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_45_pad_0 = const()[name = tensor<string, []>("input_45_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_45_strides_0 = const()[name = tensor<string, []>("input_45_strides_0"), val = tensor<int32, [2]>([2, 2])]; | |
| tensor<int32, [2]> input_45_dilations_0 = const()[name = tensor<string, []>("input_45_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_45_groups_0 = const()[name = tensor<string, []>("input_45_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 32, 3, 3]> const_19_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [13824]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44608))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58496))), name = tensor<string, []>("const_19_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 32, 3, 3])]; | |
| tensor<fp16, [64]> const_20_to_fp16 = const()[name = tensor<string, []>("const_20_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58688)))]; | |
| tensor<fp16, [1, 64, 40, 499]> input_47_cast_fp16 = conv(bias = const_20_to_fp16, dilations = input_45_dilations_0, groups = input_45_groups_0, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = input_45_strides_0, weight = const_19_to_fp16_palettized, x = input_43_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_49_cast_fp16 = relu(x = input_47_cast_fp16)[name = tensor<string, []>("input_49_cast_fp16")]; | |
| tensor<string, []> input_51_pad_type_0 = const()[name = tensor<string, []>("input_51_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_51_pad_0 = const()[name = tensor<string, []>("input_51_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_51_strides_0 = const()[name = tensor<string, []>("input_51_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_51_dilations_0 = const()[name = tensor<string, []>("input_51_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_51_groups_0 = const()[name = tensor<string, []>("input_51_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_21_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58880))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86592))), name = tensor<string, []>("const_21_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_22_to_fp16 = const()[name = tensor<string, []>("const_22_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86784)))]; | |
| tensor<fp16, [1, 64, 40, 499]> out_7_cast_fp16 = conv(bias = const_22_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_21_to_fp16_palettized, x = input_49_cast_fp16)[name = tensor<string, []>("out_7_cast_fp16")]; | |
| tensor<string, []> input_53_pad_type_0 = const()[name = tensor<string, []>("input_53_pad_type_0"), val = tensor<string, []>("valid")]; | |
| tensor<int32, [2]> input_53_strides_0 = const()[name = tensor<string, []>("input_53_strides_0"), val = tensor<int32, [2]>([2, 2])]; | |
| tensor<int32, [4]> input_53_pad_0 = const()[name = tensor<string, []>("input_53_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [2]> input_53_dilations_0 = const()[name = tensor<string, []>("input_53_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_53_groups_0 = const()[name = tensor<string, []>("input_53_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 32, 1, 1]> const_23_to_fp16 = const()[name = tensor<string, []>("const_23_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86976)))]; | |
| tensor<fp16, [64]> const_24_to_fp16 = const()[name = tensor<string, []>("const_24_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91136)))]; | |
| tensor<fp16, [1, 64, 40, 499]> var_171_cast_fp16 = conv(bias = const_24_to_fp16, dilations = input_53_dilations_0, groups = input_53_groups_0, pad = input_53_pad_0, pad_type = input_53_pad_type_0, strides = input_53_strides_0, weight = const_23_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("op_171_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_55_cast_fp16 = add(x = out_7_cast_fp16, y = var_171_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_57_cast_fp16 = relu(x = input_55_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")]; | |
| tensor<string, []> input_59_pad_type_0 = const()[name = tensor<string, []>("input_59_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_59_pad_0 = const()[name = tensor<string, []>("input_59_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_59_strides_0 = const()[name = tensor<string, []>("input_59_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_59_dilations_0 = const()[name = tensor<string, []>("input_59_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_59_groups_0 = const()[name = tensor<string, []>("input_59_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_25_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91328))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119040))), name = tensor<string, []>("const_25_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_26_to_fp16 = const()[name = tensor<string, []>("const_26_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119232)))]; | |
| tensor<fp16, [1, 64, 40, 499]> input_61_cast_fp16 = conv(bias = const_26_to_fp16, dilations = input_59_dilations_0, groups = input_59_groups_0, pad = input_59_pad_0, pad_type = input_59_pad_type_0, strides = input_59_strides_0, weight = const_25_to_fp16_palettized, x = input_57_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_63_cast_fp16 = relu(x = input_61_cast_fp16)[name = tensor<string, []>("input_63_cast_fp16")]; | |
| tensor<string, []> input_65_pad_type_0 = const()[name = tensor<string, []>("input_65_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_65_pad_0 = const()[name = tensor<string, []>("input_65_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_65_strides_0 = const()[name = tensor<string, []>("input_65_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_65_dilations_0 = const()[name = tensor<string, []>("input_65_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_65_groups_0 = const()[name = tensor<string, []>("input_65_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_27_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119424))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147136))), name = tensor<string, []>("const_27_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_28_to_fp16 = const()[name = tensor<string, []>("const_28_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147328)))]; | |
| tensor<fp16, [1, 64, 40, 499]> out_9_cast_fp16 = conv(bias = const_28_to_fp16, dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = const_27_to_fp16_palettized, x = input_63_cast_fp16)[name = tensor<string, []>("out_9_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_67_cast_fp16 = add(x = out_9_cast_fp16, y = input_57_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_69_cast_fp16 = relu(x = input_67_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")]; | |
| tensor<string, []> input_71_pad_type_0 = const()[name = tensor<string, []>("input_71_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_71_pad_0 = const()[name = tensor<string, []>("input_71_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_71_strides_0 = const()[name = tensor<string, []>("input_71_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_71_dilations_0 = const()[name = tensor<string, []>("input_71_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_71_groups_0 = const()[name = tensor<string, []>("input_71_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_29_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147520))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175232))), name = tensor<string, []>("const_29_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_30_to_fp16 = const()[name = tensor<string, []>("const_30_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175424)))]; | |
| tensor<fp16, [1, 64, 40, 499]> input_73_cast_fp16 = conv(bias = const_30_to_fp16, dilations = input_71_dilations_0, groups = input_71_groups_0, pad = input_71_pad_0, pad_type = input_71_pad_type_0, strides = input_71_strides_0, weight = const_29_to_fp16_palettized, x = input_69_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_75_cast_fp16 = relu(x = input_73_cast_fp16)[name = tensor<string, []>("input_75_cast_fp16")]; | |
| tensor<string, []> input_77_pad_type_0 = const()[name = tensor<string, []>("input_77_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_77_pad_0 = const()[name = tensor<string, []>("input_77_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_77_strides_0 = const()[name = tensor<string, []>("input_77_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_77_dilations_0 = const()[name = tensor<string, []>("input_77_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_77_groups_0 = const()[name = tensor<string, []>("input_77_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_31_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(175616))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203328))), name = tensor<string, []>("const_31_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_32_to_fp16 = const()[name = tensor<string, []>("const_32_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203520)))]; | |
| tensor<fp16, [1, 64, 40, 499]> out_11_cast_fp16 = conv(bias = const_32_to_fp16, dilations = input_77_dilations_0, groups = input_77_groups_0, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = input_77_strides_0, weight = const_31_to_fp16_palettized, x = input_75_cast_fp16)[name = tensor<string, []>("out_11_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_79_cast_fp16 = add(x = out_11_cast_fp16, y = input_69_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_81_cast_fp16 = relu(x = input_79_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")]; | |
| tensor<string, []> input_83_pad_type_0 = const()[name = tensor<string, []>("input_83_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_83_pad_0 = const()[name = tensor<string, []>("input_83_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_83_strides_0 = const()[name = tensor<string, []>("input_83_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_83_dilations_0 = const()[name = tensor<string, []>("input_83_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_83_groups_0 = const()[name = tensor<string, []>("input_83_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_33_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203712))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231424))), name = tensor<string, []>("const_33_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_34_to_fp16 = const()[name = tensor<string, []>("const_34_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231616)))]; | |
| tensor<fp16, [1, 64, 40, 499]> input_85_cast_fp16 = conv(bias = const_34_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = const_33_to_fp16_palettized, x = input_81_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_87_cast_fp16 = relu(x = input_85_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")]; | |
| tensor<string, []> input_89_pad_type_0 = const()[name = tensor<string, []>("input_89_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_89_pad_0 = const()[name = tensor<string, []>("input_89_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_89_strides_0 = const()[name = tensor<string, []>("input_89_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_89_dilations_0 = const()[name = tensor<string, []>("input_89_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_89_groups_0 = const()[name = tensor<string, []>("input_89_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [64, 64, 3, 3]> const_35_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [27648]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(231808))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259520))), name = tensor<string, []>("const_35_to_fp16_palettized"), shape = tensor<uint32, [4]>([64, 64, 3, 3])]; | |
| tensor<fp16, [64]> const_36_to_fp16 = const()[name = tensor<string, []>("const_36_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259712)))]; | |
| tensor<fp16, [1, 64, 40, 499]> out_13_cast_fp16 = conv(bias = const_36_to_fp16, dilations = input_89_dilations_0, groups = input_89_groups_0, pad = input_89_pad_0, pad_type = input_89_pad_type_0, strides = input_89_strides_0, weight = const_35_to_fp16_palettized, x = input_87_cast_fp16)[name = tensor<string, []>("out_13_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_91_cast_fp16 = add(x = out_13_cast_fp16, y = input_81_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")]; | |
| tensor<fp16, [1, 64, 40, 499]> input_93_cast_fp16 = relu(x = input_91_cast_fp16)[name = tensor<string, []>("input_93_cast_fp16")]; | |
| tensor<string, []> input_95_pad_type_0 = const()[name = tensor<string, []>("input_95_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_95_pad_0 = const()[name = tensor<string, []>("input_95_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_95_strides_0 = const()[name = tensor<string, []>("input_95_strides_0"), val = tensor<int32, [2]>([2, 2])]; | |
| tensor<int32, [2]> input_95_dilations_0 = const()[name = tensor<string, []>("input_95_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_95_groups_0 = const()[name = tensor<string, []>("input_95_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 64, 3, 3]> const_37_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [55296]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259904))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(315264))), name = tensor<string, []>("const_37_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 64, 3, 3])]; | |
| tensor<fp16, [128]> const_38_to_fp16 = const()[name = tensor<string, []>("const_38_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(315456)))]; | |
| tensor<fp16, [1, 128, 20, 250]> input_97_cast_fp16 = conv(bias = const_38_to_fp16, dilations = input_95_dilations_0, groups = input_95_groups_0, pad = input_95_pad_0, pad_type = input_95_pad_type_0, strides = input_95_strides_0, weight = const_37_to_fp16_palettized, x = input_93_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_99_cast_fp16 = relu(x = input_97_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")]; | |
| tensor<string, []> input_101_pad_type_0 = const()[name = tensor<string, []>("input_101_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_101_pad_0 = const()[name = tensor<string, []>("input_101_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_101_strides_0 = const()[name = tensor<string, []>("input_101_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_101_dilations_0 = const()[name = tensor<string, []>("input_101_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_101_groups_0 = const()[name = tensor<string, []>("input_101_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_39_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(315776))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(426432))), name = tensor<string, []>("const_39_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_40_to_fp16 = const()[name = tensor<string, []>("const_40_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(426624)))]; | |
| tensor<fp16, [1, 128, 20, 250]> out_15_cast_fp16 = conv(bias = const_40_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_39_to_fp16_palettized, x = input_99_cast_fp16)[name = tensor<string, []>("out_15_cast_fp16")]; | |
| tensor<string, []> input_103_pad_type_0 = const()[name = tensor<string, []>("input_103_pad_type_0"), val = tensor<string, []>("valid")]; | |
| tensor<int32, [2]> input_103_strides_0 = const()[name = tensor<string, []>("input_103_strides_0"), val = tensor<int32, [2]>([2, 2])]; | |
| tensor<int32, [4]> input_103_pad_0 = const()[name = tensor<string, []>("input_103_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [2]> input_103_dilations_0 = const()[name = tensor<string, []>("input_103_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_103_groups_0 = const()[name = tensor<string, []>("input_103_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 64, 1, 1]> const_41_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [6144]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(426944))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433152))), name = tensor<string, []>("const_41_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 64, 1, 1])]; | |
| tensor<fp16, [128]> const_42_to_fp16 = const()[name = tensor<string, []>("const_42_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433344)))]; | |
| tensor<fp16, [1, 128, 20, 250]> var_307_cast_fp16 = conv(bias = const_42_to_fp16, dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = const_41_to_fp16_palettized, x = input_93_cast_fp16)[name = tensor<string, []>("op_307_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_105_cast_fp16 = add(x = out_15_cast_fp16, y = var_307_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_107_cast_fp16 = relu(x = input_105_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")]; | |
| tensor<string, []> input_109_pad_type_0 = const()[name = tensor<string, []>("input_109_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_109_pad_0 = const()[name = tensor<string, []>("input_109_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_109_strides_0 = const()[name = tensor<string, []>("input_109_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_109_dilations_0 = const()[name = tensor<string, []>("input_109_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_109_groups_0 = const()[name = tensor<string, []>("input_109_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_43_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433664))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(544320))), name = tensor<string, []>("const_43_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_44_to_fp16 = const()[name = tensor<string, []>("const_44_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(544512)))]; | |
| tensor<fp16, [1, 128, 20, 250]> input_111_cast_fp16 = conv(bias = const_44_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = const_43_to_fp16_palettized, x = input_107_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_113_cast_fp16 = relu(x = input_111_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")]; | |
| tensor<string, []> input_115_pad_type_0 = const()[name = tensor<string, []>("input_115_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_115_pad_0 = const()[name = tensor<string, []>("input_115_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_115_strides_0 = const()[name = tensor<string, []>("input_115_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_115_dilations_0 = const()[name = tensor<string, []>("input_115_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_115_groups_0 = const()[name = tensor<string, []>("input_115_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_45_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(544832))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(655488))), name = tensor<string, []>("const_45_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_46_to_fp16 = const()[name = tensor<string, []>("const_46_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(655680)))]; | |
| tensor<fp16, [1, 128, 20, 250]> out_17_cast_fp16 = conv(bias = const_46_to_fp16, dilations = input_115_dilations_0, groups = input_115_groups_0, pad = input_115_pad_0, pad_type = input_115_pad_type_0, strides = input_115_strides_0, weight = const_45_to_fp16_palettized, x = input_113_cast_fp16)[name = tensor<string, []>("out_17_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_117_cast_fp16 = add(x = out_17_cast_fp16, y = input_107_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_119_cast_fp16 = relu(x = input_117_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")]; | |
| tensor<string, []> input_121_pad_type_0 = const()[name = tensor<string, []>("input_121_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_121_pad_0 = const()[name = tensor<string, []>("input_121_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_121_strides_0 = const()[name = tensor<string, []>("input_121_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_121_dilations_0 = const()[name = tensor<string, []>("input_121_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_121_groups_0 = const()[name = tensor<string, []>("input_121_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_47_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(656000))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766656))), name = tensor<string, []>("const_47_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_48_to_fp16 = const()[name = tensor<string, []>("const_48_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(766848)))]; | |
| tensor<fp16, [1, 128, 20, 250]> input_123_cast_fp16 = conv(bias = const_48_to_fp16, dilations = input_121_dilations_0, groups = input_121_groups_0, pad = input_121_pad_0, pad_type = input_121_pad_type_0, strides = input_121_strides_0, weight = const_47_to_fp16_palettized, x = input_119_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_125_cast_fp16 = relu(x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")]; | |
| tensor<string, []> input_127_pad_type_0 = const()[name = tensor<string, []>("input_127_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_127_pad_0 = const()[name = tensor<string, []>("input_127_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_127_strides_0 = const()[name = tensor<string, []>("input_127_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_127_dilations_0 = const()[name = tensor<string, []>("input_127_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_127_groups_0 = const()[name = tensor<string, []>("input_127_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_49_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(767168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(877824))), name = tensor<string, []>("const_49_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_50_to_fp16 = const()[name = tensor<string, []>("const_50_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(878016)))]; | |
| tensor<fp16, [1, 128, 20, 250]> out_19_cast_fp16 = conv(bias = const_50_to_fp16, dilations = input_127_dilations_0, groups = input_127_groups_0, pad = input_127_pad_0, pad_type = input_127_pad_type_0, strides = input_127_strides_0, weight = const_49_to_fp16_palettized, x = input_125_cast_fp16)[name = tensor<string, []>("out_19_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_129_cast_fp16 = add(x = out_19_cast_fp16, y = input_119_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_131_cast_fp16 = relu(x = input_129_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")]; | |
| tensor<string, []> input_133_pad_type_0 = const()[name = tensor<string, []>("input_133_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_133_pad_0 = const()[name = tensor<string, []>("input_133_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_133_strides_0 = const()[name = tensor<string, []>("input_133_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_133_dilations_0 = const()[name = tensor<string, []>("input_133_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_133_groups_0 = const()[name = tensor<string, []>("input_133_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_51_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(878336))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(988992))), name = tensor<string, []>("const_51_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_52_to_fp16 = const()[name = tensor<string, []>("const_52_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(989184)))]; | |
| tensor<fp16, [1, 128, 20, 250]> input_135_cast_fp16 = conv(bias = const_52_to_fp16, dilations = input_133_dilations_0, groups = input_133_groups_0, pad = input_133_pad_0, pad_type = input_133_pad_type_0, strides = input_133_strides_0, weight = const_51_to_fp16_palettized, x = input_131_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_137_cast_fp16 = relu(x = input_135_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")]; | |
| tensor<string, []> input_139_pad_type_0 = const()[name = tensor<string, []>("input_139_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_139_pad_0 = const()[name = tensor<string, []>("input_139_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_139_strides_0 = const()[name = tensor<string, []>("input_139_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_139_dilations_0 = const()[name = tensor<string, []>("input_139_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_139_groups_0 = const()[name = tensor<string, []>("input_139_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_53_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(989504))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1100160))), name = tensor<string, []>("const_53_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_54_to_fp16 = const()[name = tensor<string, []>("const_54_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1100352)))]; | |
| tensor<fp16, [1, 128, 20, 250]> out_21_cast_fp16 = conv(bias = const_54_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = const_53_to_fp16_palettized, x = input_137_cast_fp16)[name = tensor<string, []>("out_21_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_141_cast_fp16 = add(x = out_21_cast_fp16, y = input_131_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_143_cast_fp16 = relu(x = input_141_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")]; | |
| tensor<string, []> input_145_pad_type_0 = const()[name = tensor<string, []>("input_145_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_145_pad_0 = const()[name = tensor<string, []>("input_145_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_145_strides_0 = const()[name = tensor<string, []>("input_145_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_145_dilations_0 = const()[name = tensor<string, []>("input_145_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_145_groups_0 = const()[name = tensor<string, []>("input_145_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_55_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1100672))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1211328))), name = tensor<string, []>("const_55_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_56_to_fp16 = const()[name = tensor<string, []>("const_56_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1211520)))]; | |
| tensor<fp16, [1, 128, 20, 250]> input_147_cast_fp16 = conv(bias = const_56_to_fp16, dilations = input_145_dilations_0, groups = input_145_groups_0, pad = input_145_pad_0, pad_type = input_145_pad_type_0, strides = input_145_strides_0, weight = const_55_to_fp16_palettized, x = input_143_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_149_cast_fp16 = relu(x = input_147_cast_fp16)[name = tensor<string, []>("input_149_cast_fp16")]; | |
| tensor<string, []> input_151_pad_type_0 = const()[name = tensor<string, []>("input_151_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_151_pad_0 = const()[name = tensor<string, []>("input_151_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_151_strides_0 = const()[name = tensor<string, []>("input_151_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_151_dilations_0 = const()[name = tensor<string, []>("input_151_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_151_groups_0 = const()[name = tensor<string, []>("input_151_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_57_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1211840))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1322496))), name = tensor<string, []>("const_57_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_58_to_fp16 = const()[name = tensor<string, []>("const_58_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1322688)))]; | |
| tensor<fp16, [1, 128, 20, 250]> out_23_cast_fp16 = conv(bias = const_58_to_fp16, dilations = input_151_dilations_0, groups = input_151_groups_0, pad = input_151_pad_0, pad_type = input_151_pad_type_0, strides = input_151_strides_0, weight = const_57_to_fp16_palettized, x = input_149_cast_fp16)[name = tensor<string, []>("out_23_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_153_cast_fp16 = add(x = out_23_cast_fp16, y = input_143_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_155_cast_fp16 = relu(x = input_153_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")]; | |
| tensor<string, []> input_157_pad_type_0 = const()[name = tensor<string, []>("input_157_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_157_pad_0 = const()[name = tensor<string, []>("input_157_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_157_strides_0 = const()[name = tensor<string, []>("input_157_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_157_dilations_0 = const()[name = tensor<string, []>("input_157_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_157_groups_0 = const()[name = tensor<string, []>("input_157_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_59_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1323008))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1433664))), name = tensor<string, []>("const_59_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_60_to_fp16 = const()[name = tensor<string, []>("const_60_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1433856)))]; | |
| tensor<fp16, [1, 128, 20, 250]> input_159_cast_fp16 = conv(bias = const_60_to_fp16, dilations = input_157_dilations_0, groups = input_157_groups_0, pad = input_157_pad_0, pad_type = input_157_pad_type_0, strides = input_157_strides_0, weight = const_59_to_fp16_palettized, x = input_155_cast_fp16)[name = tensor<string, []>("input_159_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_161_cast_fp16 = relu(x = input_159_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")]; | |
| tensor<string, []> input_163_pad_type_0 = const()[name = tensor<string, []>("input_163_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_163_pad_0 = const()[name = tensor<string, []>("input_163_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_163_strides_0 = const()[name = tensor<string, []>("input_163_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_163_dilations_0 = const()[name = tensor<string, []>("input_163_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_163_groups_0 = const()[name = tensor<string, []>("input_163_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [128, 128, 3, 3]> const_61_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [110592]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1434176))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1544832))), name = tensor<string, []>("const_61_to_fp16_palettized"), shape = tensor<uint32, [4]>([128, 128, 3, 3])]; | |
| tensor<fp16, [128]> const_62_to_fp16 = const()[name = tensor<string, []>("const_62_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1545024)))]; | |
| tensor<fp16, [1, 128, 20, 250]> out_25_cast_fp16 = conv(bias = const_62_to_fp16, dilations = input_163_dilations_0, groups = input_163_groups_0, pad = input_163_pad_0, pad_type = input_163_pad_type_0, strides = input_163_strides_0, weight = const_61_to_fp16_palettized, x = input_161_cast_fp16)[name = tensor<string, []>("out_25_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_165_cast_fp16 = add(x = out_25_cast_fp16, y = input_155_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")]; | |
| tensor<fp16, [1, 128, 20, 250]> input_167_cast_fp16 = relu(x = input_165_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")]; | |
| tensor<string, []> input_169_pad_type_0 = const()[name = tensor<string, []>("input_169_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_169_pad_0 = const()[name = tensor<string, []>("input_169_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_169_strides_0 = const()[name = tensor<string, []>("input_169_strides_0"), val = tensor<int32, [2]>([2, 2])]; | |
| tensor<int32, [2]> input_169_dilations_0 = const()[name = tensor<string, []>("input_169_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_169_groups_0 = const()[name = tensor<string, []>("input_169_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 128, 3, 3]> const_63_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [221184]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1545344))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1766592))), name = tensor<string, []>("const_63_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 128, 3, 3])]; | |
| tensor<fp16, [256]> const_64_to_fp16 = const()[name = tensor<string, []>("const_64_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1766784)))]; | |
| tensor<fp16, [1, 256, 10, 125]> input_171_cast_fp16 = conv(bias = const_64_to_fp16, dilations = input_169_dilations_0, groups = input_169_groups_0, pad = input_169_pad_0, pad_type = input_169_pad_type_0, strides = input_169_strides_0, weight = const_63_to_fp16_palettized, x = input_167_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_173_cast_fp16 = relu(x = input_171_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")]; | |
| tensor<string, []> input_175_pad_type_0 = const()[name = tensor<string, []>("input_175_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_175_pad_0 = const()[name = tensor<string, []>("input_175_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_175_strides_0 = const()[name = tensor<string, []>("input_175_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_175_dilations_0 = const()[name = tensor<string, []>("input_175_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_175_groups_0 = const()[name = tensor<string, []>("input_175_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 256, 3, 3]> const_65_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [442368]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1767360))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2209792))), name = tensor<string, []>("const_65_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 256, 3, 3])]; | |
| tensor<fp16, [256]> const_66_to_fp16 = const()[name = tensor<string, []>("const_66_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2209984)))]; | |
| tensor<fp16, [1, 256, 10, 125]> out_27_cast_fp16 = conv(bias = const_66_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_65_to_fp16_palettized, x = input_173_cast_fp16)[name = tensor<string, []>("out_27_cast_fp16")]; | |
| tensor<string, []> input_177_pad_type_0 = const()[name = tensor<string, []>("input_177_pad_type_0"), val = tensor<string, []>("valid")]; | |
| tensor<int32, [2]> input_177_strides_0 = const()[name = tensor<string, []>("input_177_strides_0"), val = tensor<int32, [2]>([2, 2])]; | |
| tensor<int32, [4]> input_177_pad_0 = const()[name = tensor<string, []>("input_177_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [2]> input_177_dilations_0 = const()[name = tensor<string, []>("input_177_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_177_groups_0 = const()[name = tensor<string, []>("input_177_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 128, 1, 1]> const_67_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [24576]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2210560))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2235200))), name = tensor<string, []>("const_67_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 128, 1, 1])]; | |
| tensor<fp16, [256]> const_68_to_fp16 = const()[name = tensor<string, []>("const_68_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2235392)))]; | |
| tensor<fp16, [1, 256, 10, 125]> var_498_cast_fp16 = conv(bias = const_68_to_fp16, dilations = input_177_dilations_0, groups = input_177_groups_0, pad = input_177_pad_0, pad_type = input_177_pad_type_0, strides = input_177_strides_0, weight = const_67_to_fp16_palettized, x = input_167_cast_fp16)[name = tensor<string, []>("op_498_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_179_cast_fp16 = add(x = out_27_cast_fp16, y = var_498_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_181_cast_fp16 = relu(x = input_179_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")]; | |
| tensor<string, []> input_183_pad_type_0 = const()[name = tensor<string, []>("input_183_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_183_pad_0 = const()[name = tensor<string, []>("input_183_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_183_strides_0 = const()[name = tensor<string, []>("input_183_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_183_dilations_0 = const()[name = tensor<string, []>("input_183_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_183_groups_0 = const()[name = tensor<string, []>("input_183_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 256, 3, 3]> const_69_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [442368]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2235968))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2678400))), name = tensor<string, []>("const_69_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 256, 3, 3])]; | |
| tensor<fp16, [256]> const_70_to_fp16 = const()[name = tensor<string, []>("const_70_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2678592)))]; | |
| tensor<fp16, [1, 256, 10, 125]> input_185_cast_fp16 = conv(bias = const_70_to_fp16, dilations = input_183_dilations_0, groups = input_183_groups_0, pad = input_183_pad_0, pad_type = input_183_pad_type_0, strides = input_183_strides_0, weight = const_69_to_fp16_palettized, x = input_181_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_187_cast_fp16 = relu(x = input_185_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")]; | |
| tensor<string, []> input_189_pad_type_0 = const()[name = tensor<string, []>("input_189_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_189_pad_0 = const()[name = tensor<string, []>("input_189_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_189_strides_0 = const()[name = tensor<string, []>("input_189_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_189_dilations_0 = const()[name = tensor<string, []>("input_189_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_189_groups_0 = const()[name = tensor<string, []>("input_189_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 256, 3, 3]> const_71_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [442368]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2679168))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3121600))), name = tensor<string, []>("const_71_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 256, 3, 3])]; | |
| tensor<fp16, [256]> const_72_to_fp16 = const()[name = tensor<string, []>("const_72_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3121792)))]; | |
| tensor<fp16, [1, 256, 10, 125]> out_29_cast_fp16 = conv(bias = const_72_to_fp16, dilations = input_189_dilations_0, groups = input_189_groups_0, pad = input_189_pad_0, pad_type = input_189_pad_type_0, strides = input_189_strides_0, weight = const_71_to_fp16_palettized, x = input_187_cast_fp16)[name = tensor<string, []>("out_29_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_191_cast_fp16 = add(x = out_29_cast_fp16, y = input_181_cast_fp16)[name = tensor<string, []>("input_191_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_193_cast_fp16 = relu(x = input_191_cast_fp16)[name = tensor<string, []>("input_193_cast_fp16")]; | |
| tensor<string, []> input_195_pad_type_0 = const()[name = tensor<string, []>("input_195_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_195_pad_0 = const()[name = tensor<string, []>("input_195_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_195_strides_0 = const()[name = tensor<string, []>("input_195_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_195_dilations_0 = const()[name = tensor<string, []>("input_195_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_195_groups_0 = const()[name = tensor<string, []>("input_195_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 256, 3, 3]> const_73_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [442368]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3122368))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3564800))), name = tensor<string, []>("const_73_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 256, 3, 3])]; | |
| tensor<fp16, [256]> const_74_to_fp16 = const()[name = tensor<string, []>("const_74_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3564992)))]; | |
| tensor<fp16, [1, 256, 10, 125]> input_197_cast_fp16 = conv(bias = const_74_to_fp16, dilations = input_195_dilations_0, groups = input_195_groups_0, pad = input_195_pad_0, pad_type = input_195_pad_type_0, strides = input_195_strides_0, weight = const_73_to_fp16_palettized, x = input_193_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_199_cast_fp16 = relu(x = input_197_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")]; | |
| tensor<string, []> input_201_pad_type_0 = const()[name = tensor<string, []>("input_201_pad_type_0"), val = tensor<string, []>("custom")]; | |
| tensor<int32, [4]> input_201_pad_0 = const()[name = tensor<string, []>("input_201_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])]; | |
| tensor<int32, [2]> input_201_strides_0 = const()[name = tensor<string, []>("input_201_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [2]> input_201_dilations_0 = const()[name = tensor<string, []>("input_201_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, []> input_201_groups_0 = const()[name = tensor<string, []>("input_201_groups_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [256, 256, 3, 3]> const_75_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [442368]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3565568))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4008000))), name = tensor<string, []>("const_75_to_fp16_palettized"), shape = tensor<uint32, [4]>([256, 256, 3, 3])]; | |
| tensor<fp16, [256]> const_76_to_fp16 = const()[name = tensor<string, []>("const_76_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4008192)))]; | |
| tensor<fp16, [1, 256, 10, 125]> out_cast_fp16 = conv(bias = const_76_to_fp16, dilations = input_201_dilations_0, groups = input_201_groups_0, pad = input_201_pad_0, pad_type = input_201_pad_type_0, strides = input_201_strides_0, weight = const_75_to_fp16_palettized, x = input_199_cast_fp16)[name = tensor<string, []>("out_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> input_203_cast_fp16 = add(x = out_cast_fp16, y = input_193_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")]; | |
| tensor<fp16, [1, 256, 10, 125]> x_cast_fp16 = relu(x = input_203_cast_fp16)[name = tensor<string, []>("x_cast_fp16")]; | |
| tensor<int32, [3]> var_577 = const()[name = tensor<string, []>("op_577"), val = tensor<int32, [3]>([1, 2560, 125])]; | |
| tensor<fp16, [1, 2560, 125]> sequences_cast_fp16 = reshape(shape = var_577, x = x_cast_fp16)[name = tensor<string, []>("sequences_cast_fp16")]; | |
| tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = tensor<string, []>("expand_dims_0_axes_0"), val = tensor<int32, [1]>([3])]; | |
| tensor<fp16, [1, 3, 589, 1]> expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = speaker_masks)[name = tensor<string, []>("expand_dims_0_cast_fp16")]; | |
| tensor<fp32, []> upsample_nearest_neighbor_0_scale_factor_height_0 = const()[name = tensor<string, []>("upsample_nearest_neighbor_0_scale_factor_height_0"), val = tensor<fp32, []>(0x1.b2a2a4p-3)]; | |
| tensor<fp32, []> upsample_nearest_neighbor_0_scale_factor_width_0 = const()[name = tensor<string, []>("upsample_nearest_neighbor_0_scale_factor_width_0"), val = tensor<fp32, []>(0x1p+0)]; | |
| tensor<fp16, [1, 3, 125, 1]> 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<string, []>("upsample_nearest_neighbor_0_cast_fp16")]; | |
| tensor<int32, [1]> weights_1_axes_0 = const()[name = tensor<string, []>("weights_1_axes_0"), val = tensor<int32, [1]>([3])]; | |
| tensor<fp16, [1, 3, 125]> weights_1_cast_fp16 = squeeze(axes = weights_1_axes_0, x = upsample_nearest_neighbor_0_cast_fp16)[name = tensor<string, []>("weights_1_cast_fp16")]; | |
| tensor<int32, [3]> var_583_begin_0 = const()[name = tensor<string, []>("op_583_begin_0"), val = tensor<int32, [3]>([0, 0, 0])]; | |
| tensor<int32, [3]> var_583_end_0 = const()[name = tensor<string, []>("op_583_end_0"), val = tensor<int32, [3]>([1, 1, 125])]; | |
| tensor<bool, [3]> var_583_end_mask_0 = const()[name = tensor<string, []>("op_583_end_mask_0"), val = tensor<bool, [3]>([true, false, true])]; | |
| tensor<bool, [3]> var_583_squeeze_mask_0 = const()[name = tensor<string, []>("op_583_squeeze_mask_0"), val = tensor<bool, [3]>([false, true, false])]; | |
| tensor<fp16, [1, 125]> var_583_cast_fp16 = slice_by_index(begin = var_583_begin_0, end = var_583_end_0, end_mask = var_583_end_mask_0, squeeze_mask = var_583_squeeze_mask_0, x = weights_1_cast_fp16)[name = tensor<string, []>("op_583_cast_fp16")]; | |
| tensor<int32, [1]> weights_5_axes_0 = const()[name = tensor<string, []>("weights_5_axes_0"), val = tensor<int32, [1]>([1])]; | |
| tensor<fp16, [1, 1, 125]> weights_5_cast_fp16 = expand_dims(axes = weights_5_axes_0, x = var_583_cast_fp16)[name = tensor<string, []>("weights_5_cast_fp16")]; | |
| tensor<int32, [1]> var_587_axes_0 = const()[name = tensor<string, []>("op_587_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_587_keep_dims_0 = const()[name = tensor<string, []>("op_587_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 1]> var_587_cast_fp16 = reduce_sum(axes = var_587_axes_0, keep_dims = var_587_keep_dims_0, x = weights_5_cast_fp16)[name = tensor<string, []>("op_587_cast_fp16")]; | |
| tensor<fp16, []> var_588_to_fp16 = const()[name = tensor<string, []>("op_588_to_fp16"), val = tensor<fp16, []>(0x1p-24)]; | |
| tensor<fp16, [1, 1]> v1_1_cast_fp16 = add(x = var_587_cast_fp16, y = var_588_to_fp16)[name = tensor<string, []>("v1_1_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_590_cast_fp16 = mul(x = sequences_cast_fp16, y = weights_5_cast_fp16)[name = tensor<string, []>("op_590_cast_fp16")]; | |
| tensor<int32, [1]> var_592_axes_0 = const()[name = tensor<string, []>("op_592_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_592_keep_dims_0 = const()[name = tensor<string, []>("op_592_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 2560]> var_592_cast_fp16 = reduce_sum(axes = var_592_axes_0, keep_dims = var_592_keep_dims_0, x = var_590_cast_fp16)[name = tensor<string, []>("op_592_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> mean_1_cast_fp16 = real_div(x = var_592_cast_fp16, y = v1_1_cast_fp16)[name = tensor<string, []>("mean_1_cast_fp16")]; | |
| tensor<int32, [1]> var_594_axes_0 = const()[name = tensor<string, []>("op_594_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<fp16, [1, 2560, 1]> var_594_cast_fp16 = expand_dims(axes = var_594_axes_0, x = mean_1_cast_fp16)[name = tensor<string, []>("op_594_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_595_cast_fp16 = sub(x = sequences_cast_fp16, y = var_594_cast_fp16)[name = tensor<string, []>("op_595_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> dx2_1_cast_fp16 = mul(x = var_595_cast_fp16, y = var_595_cast_fp16)[name = tensor<string, []>("dx2_1_cast_fp16")]; | |
| tensor<fp16, [1, 1, 125]> var_597_cast_fp16 = mul(x = weights_5_cast_fp16, y = weights_5_cast_fp16)[name = tensor<string, []>("op_597_cast_fp16")]; | |
| tensor<int32, [1]> v2_1_axes_0 = const()[name = tensor<string, []>("v2_1_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> v2_1_keep_dims_0 = const()[name = tensor<string, []>("v2_1_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 1]> v2_1_cast_fp16 = reduce_sum(axes = v2_1_axes_0, keep_dims = v2_1_keep_dims_0, x = var_597_cast_fp16)[name = tensor<string, []>("v2_1_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_600_cast_fp16 = mul(x = dx2_1_cast_fp16, y = weights_5_cast_fp16)[name = tensor<string, []>("op_600_cast_fp16")]; | |
| tensor<int32, [1]> var_602_axes_0 = const()[name = tensor<string, []>("op_602_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_602_keep_dims_0 = const()[name = tensor<string, []>("op_602_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 2560]> var_602_cast_fp16 = reduce_sum(axes = var_602_axes_0, keep_dims = var_602_keep_dims_0, x = var_600_cast_fp16)[name = tensor<string, []>("op_602_cast_fp16")]; | |
| tensor<fp16, [1, 1]> var_603_cast_fp16 = real_div(x = v2_1_cast_fp16, y = v1_1_cast_fp16)[name = tensor<string, []>("op_603_cast_fp16")]; | |
| tensor<fp16, [1, 1]> var_604_cast_fp16 = sub(x = v1_1_cast_fp16, y = var_603_cast_fp16)[name = tensor<string, []>("op_604_cast_fp16")]; | |
| tensor<fp16, []> var_605_to_fp16 = const()[name = tensor<string, []>("op_605_to_fp16"), val = tensor<fp16, []>(0x1p-24)]; | |
| tensor<fp16, [1, 1]> var_606_cast_fp16 = add(x = var_604_cast_fp16, y = var_605_to_fp16)[name = tensor<string, []>("op_606_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> var_1_cast_fp16 = real_div(x = var_602_cast_fp16, y = var_606_cast_fp16)[name = tensor<string, []>("var_1_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> std_1_cast_fp16 = sqrt(x = var_1_cast_fp16)[name = tensor<string, []>("std_1_cast_fp16")]; | |
| tensor<bool, []> var_610_interleave_0 = const()[name = tensor<string, []>("op_610_interleave_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 5120]> var_610_cast_fp16 = concat(axis = var_12, interleave = var_610_interleave_0, values = (mean_1_cast_fp16, std_1_cast_fp16))[name = tensor<string, []>("op_610_cast_fp16")]; | |
| tensor<int32, [3]> var_612_begin_0 = const()[name = tensor<string, []>("op_612_begin_0"), val = tensor<int32, [3]>([0, 1, 0])]; | |
| tensor<int32, [3]> var_612_end_0 = const()[name = tensor<string, []>("op_612_end_0"), val = tensor<int32, [3]>([1, 2, 125])]; | |
| tensor<bool, [3]> var_612_end_mask_0 = const()[name = tensor<string, []>("op_612_end_mask_0"), val = tensor<bool, [3]>([true, false, true])]; | |
| tensor<bool, [3]> var_612_squeeze_mask_0 = const()[name = tensor<string, []>("op_612_squeeze_mask_0"), val = tensor<bool, [3]>([false, true, false])]; | |
| tensor<fp16, [1, 125]> var_612_cast_fp16 = slice_by_index(begin = var_612_begin_0, end = var_612_end_0, end_mask = var_612_end_mask_0, squeeze_mask = var_612_squeeze_mask_0, x = weights_1_cast_fp16)[name = tensor<string, []>("op_612_cast_fp16")]; | |
| tensor<int32, [1]> weights_9_axes_0 = const()[name = tensor<string, []>("weights_9_axes_0"), val = tensor<int32, [1]>([1])]; | |
| tensor<fp16, [1, 1, 125]> weights_9_cast_fp16 = expand_dims(axes = weights_9_axes_0, x = var_612_cast_fp16)[name = tensor<string, []>("weights_9_cast_fp16")]; | |
| tensor<int32, [1]> var_616_axes_0 = const()[name = tensor<string, []>("op_616_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_616_keep_dims_0 = const()[name = tensor<string, []>("op_616_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 1]> var_616_cast_fp16 = reduce_sum(axes = var_616_axes_0, keep_dims = var_616_keep_dims_0, x = weights_9_cast_fp16)[name = tensor<string, []>("op_616_cast_fp16")]; | |
| tensor<fp16, []> var_617_to_fp16 = const()[name = tensor<string, []>("op_617_to_fp16"), val = tensor<fp16, []>(0x1p-24)]; | |
| tensor<fp16, [1, 1]> v1_3_cast_fp16 = add(x = var_616_cast_fp16, y = var_617_to_fp16)[name = tensor<string, []>("v1_3_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_619_cast_fp16 = mul(x = sequences_cast_fp16, y = weights_9_cast_fp16)[name = tensor<string, []>("op_619_cast_fp16")]; | |
| tensor<int32, [1]> var_621_axes_0 = const()[name = tensor<string, []>("op_621_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_621_keep_dims_0 = const()[name = tensor<string, []>("op_621_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 2560]> var_621_cast_fp16 = reduce_sum(axes = var_621_axes_0, keep_dims = var_621_keep_dims_0, x = var_619_cast_fp16)[name = tensor<string, []>("op_621_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> mean_3_cast_fp16 = real_div(x = var_621_cast_fp16, y = v1_3_cast_fp16)[name = tensor<string, []>("mean_3_cast_fp16")]; | |
| tensor<int32, [1]> var_623_axes_0 = const()[name = tensor<string, []>("op_623_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<fp16, [1, 2560, 1]> var_623_cast_fp16 = expand_dims(axes = var_623_axes_0, x = mean_3_cast_fp16)[name = tensor<string, []>("op_623_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_624_cast_fp16 = sub(x = sequences_cast_fp16, y = var_623_cast_fp16)[name = tensor<string, []>("op_624_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> dx2_3_cast_fp16 = mul(x = var_624_cast_fp16, y = var_624_cast_fp16)[name = tensor<string, []>("dx2_3_cast_fp16")]; | |
| tensor<fp16, [1, 1, 125]> var_626_cast_fp16 = mul(x = weights_9_cast_fp16, y = weights_9_cast_fp16)[name = tensor<string, []>("op_626_cast_fp16")]; | |
| tensor<int32, [1]> v2_3_axes_0 = const()[name = tensor<string, []>("v2_3_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> v2_3_keep_dims_0 = const()[name = tensor<string, []>("v2_3_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 1]> v2_3_cast_fp16 = reduce_sum(axes = v2_3_axes_0, keep_dims = v2_3_keep_dims_0, x = var_626_cast_fp16)[name = tensor<string, []>("v2_3_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_629_cast_fp16 = mul(x = dx2_3_cast_fp16, y = weights_9_cast_fp16)[name = tensor<string, []>("op_629_cast_fp16")]; | |
| tensor<int32, [1]> var_631_axes_0 = const()[name = tensor<string, []>("op_631_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_631_keep_dims_0 = const()[name = tensor<string, []>("op_631_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 2560]> var_631_cast_fp16 = reduce_sum(axes = var_631_axes_0, keep_dims = var_631_keep_dims_0, x = var_629_cast_fp16)[name = tensor<string, []>("op_631_cast_fp16")]; | |
| tensor<fp16, [1, 1]> var_632_cast_fp16 = real_div(x = v2_3_cast_fp16, y = v1_3_cast_fp16)[name = tensor<string, []>("op_632_cast_fp16")]; | |
| tensor<fp16, [1, 1]> var_633_cast_fp16 = sub(x = v1_3_cast_fp16, y = var_632_cast_fp16)[name = tensor<string, []>("op_633_cast_fp16")]; | |
| tensor<fp16, []> var_634_to_fp16 = const()[name = tensor<string, []>("op_634_to_fp16"), val = tensor<fp16, []>(0x1p-24)]; | |
| tensor<fp16, [1, 1]> var_635_cast_fp16 = add(x = var_633_cast_fp16, y = var_634_to_fp16)[name = tensor<string, []>("op_635_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> var_3_cast_fp16 = real_div(x = var_631_cast_fp16, y = var_635_cast_fp16)[name = tensor<string, []>("var_3_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> std_3_cast_fp16 = sqrt(x = var_3_cast_fp16)[name = tensor<string, []>("std_3_cast_fp16")]; | |
| tensor<bool, []> var_639_interleave_0 = const()[name = tensor<string, []>("op_639_interleave_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 5120]> var_639_cast_fp16 = concat(axis = var_12, interleave = var_639_interleave_0, values = (mean_3_cast_fp16, std_3_cast_fp16))[name = tensor<string, []>("op_639_cast_fp16")]; | |
| tensor<int32, [3]> var_641_begin_0 = const()[name = tensor<string, []>("op_641_begin_0"), val = tensor<int32, [3]>([0, 2, 0])]; | |
| tensor<int32, [3]> var_641_end_0 = const()[name = tensor<string, []>("op_641_end_0"), val = tensor<int32, [3]>([1, 3, 125])]; | |
| tensor<bool, [3]> var_641_end_mask_0 = const()[name = tensor<string, []>("op_641_end_mask_0"), val = tensor<bool, [3]>([true, false, true])]; | |
| tensor<bool, [3]> var_641_squeeze_mask_0 = const()[name = tensor<string, []>("op_641_squeeze_mask_0"), val = tensor<bool, [3]>([false, true, false])]; | |
| tensor<fp16, [1, 125]> var_641_cast_fp16 = slice_by_index(begin = var_641_begin_0, end = var_641_end_0, end_mask = var_641_end_mask_0, squeeze_mask = var_641_squeeze_mask_0, x = weights_1_cast_fp16)[name = tensor<string, []>("op_641_cast_fp16")]; | |
| tensor<int32, [1]> weights_axes_0 = const()[name = tensor<string, []>("weights_axes_0"), val = tensor<int32, [1]>([1])]; | |
| tensor<fp16, [1, 1, 125]> weights_cast_fp16 = expand_dims(axes = weights_axes_0, x = var_641_cast_fp16)[name = tensor<string, []>("weights_cast_fp16")]; | |
| tensor<int32, [1]> var_645_axes_0 = const()[name = tensor<string, []>("op_645_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_645_keep_dims_0 = const()[name = tensor<string, []>("op_645_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 1]> var_645_cast_fp16 = reduce_sum(axes = var_645_axes_0, keep_dims = var_645_keep_dims_0, x = weights_cast_fp16)[name = tensor<string, []>("op_645_cast_fp16")]; | |
| tensor<fp16, []> var_646_to_fp16 = const()[name = tensor<string, []>("op_646_to_fp16"), val = tensor<fp16, []>(0x1p-24)]; | |
| tensor<fp16, [1, 1]> v1_cast_fp16 = add(x = var_645_cast_fp16, y = var_646_to_fp16)[name = tensor<string, []>("v1_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_648_cast_fp16 = mul(x = sequences_cast_fp16, y = weights_cast_fp16)[name = tensor<string, []>("op_648_cast_fp16")]; | |
| tensor<int32, [1]> var_650_axes_0 = const()[name = tensor<string, []>("op_650_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_650_keep_dims_0 = const()[name = tensor<string, []>("op_650_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 2560]> var_650_cast_fp16 = reduce_sum(axes = var_650_axes_0, keep_dims = var_650_keep_dims_0, x = var_648_cast_fp16)[name = tensor<string, []>("op_650_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> mean_cast_fp16 = real_div(x = var_650_cast_fp16, y = v1_cast_fp16)[name = tensor<string, []>("mean_cast_fp16")]; | |
| tensor<int32, [1]> var_652_axes_0 = const()[name = tensor<string, []>("op_652_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<fp16, [1, 2560, 1]> var_652_cast_fp16 = expand_dims(axes = var_652_axes_0, x = mean_cast_fp16)[name = tensor<string, []>("op_652_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_653_cast_fp16 = sub(x = sequences_cast_fp16, y = var_652_cast_fp16)[name = tensor<string, []>("op_653_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> dx2_cast_fp16 = mul(x = var_653_cast_fp16, y = var_653_cast_fp16)[name = tensor<string, []>("dx2_cast_fp16")]; | |
| tensor<fp16, [1, 1, 125]> var_655_cast_fp16 = mul(x = weights_cast_fp16, y = weights_cast_fp16)[name = tensor<string, []>("op_655_cast_fp16")]; | |
| tensor<int32, [1]> v2_axes_0 = const()[name = tensor<string, []>("v2_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> v2_keep_dims_0 = const()[name = tensor<string, []>("v2_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 1]> v2_cast_fp16 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_655_cast_fp16)[name = tensor<string, []>("v2_cast_fp16")]; | |
| tensor<fp16, [1, 2560, 125]> var_658_cast_fp16 = mul(x = dx2_cast_fp16, y = weights_cast_fp16)[name = tensor<string, []>("op_658_cast_fp16")]; | |
| tensor<int32, [1]> var_660_axes_0 = const()[name = tensor<string, []>("op_660_axes_0"), val = tensor<int32, [1]>([2])]; | |
| tensor<bool, []> var_660_keep_dims_0 = const()[name = tensor<string, []>("op_660_keep_dims_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 2560]> var_660_cast_fp16 = reduce_sum(axes = var_660_axes_0, keep_dims = var_660_keep_dims_0, x = var_658_cast_fp16)[name = tensor<string, []>("op_660_cast_fp16")]; | |
| tensor<fp16, [1, 1]> var_661_cast_fp16 = real_div(x = v2_cast_fp16, y = v1_cast_fp16)[name = tensor<string, []>("op_661_cast_fp16")]; | |
| tensor<fp16, [1, 1]> var_662_cast_fp16 = sub(x = v1_cast_fp16, y = var_661_cast_fp16)[name = tensor<string, []>("op_662_cast_fp16")]; | |
| tensor<fp16, []> var_663_to_fp16 = const()[name = tensor<string, []>("op_663_to_fp16"), val = tensor<fp16, []>(0x1p-24)]; | |
| tensor<fp16, [1, 1]> var_664_cast_fp16 = add(x = var_662_cast_fp16, y = var_663_to_fp16)[name = tensor<string, []>("op_664_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> var_cast_fp16 = real_div(x = var_660_cast_fp16, y = var_664_cast_fp16)[name = tensor<string, []>("var_cast_fp16")]; | |
| tensor<fp16, [1, 2560]> std_cast_fp16 = sqrt(x = var_cast_fp16)[name = tensor<string, []>("std_cast_fp16")]; | |
| tensor<bool, []> var_668_interleave_0 = const()[name = tensor<string, []>("op_668_interleave_0"), val = tensor<bool, []>(false)]; | |
| tensor<fp16, [1, 5120]> var_668_cast_fp16 = concat(axis = var_12, interleave = var_668_interleave_0, values = (mean_cast_fp16, std_cast_fp16))[name = tensor<string, []>("op_668_cast_fp16")]; | |
| tensor<int32, []> input_axis_0 = const()[name = tensor<string, []>("input_axis_0"), val = tensor<int32, []>(1)]; | |
| tensor<fp16, [1, 3, 5120]> input_cast_fp16 = stack(axis = input_axis_0, values = (var_610_cast_fp16, var_639_cast_fp16, var_668_cast_fp16))[name = tensor<string, []>("input_cast_fp16")]; | |
| tensor<fp16, [256, 5120]> model_resnet_seg_1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor<uint8, [983040]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4008768))), lut = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4991872))), name = tensor<string, []>("model_resnet_seg_1_weight_to_fp16_palettized"), shape = tensor<uint32, [2]>([256, 5120])]; | |
| tensor<fp16, [256]> model_resnet_seg_1_bias_to_fp16 = const()[name = tensor<string, []>("model_resnet_seg_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4992064)))]; | |
| tensor<fp16, [1, 3, 256]> speaker_embeddings = linear(bias = model_resnet_seg_1_bias_to_fp16, weight = model_resnet_seg_1_weight_to_fp16_palettized, x = input_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")]; | |
| } -> (speaker_embeddings); | |
| } |