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VoxCPM-ANE

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  1. voxcpm_audio_vae_decoder_length_24.mlmodelc/analytics/coremldata.bin +3 -0
  2. voxcpm_audio_vae_decoder_length_24.mlmodelc/coremldata.bin +3 -0
  3. voxcpm_audio_vae_decoder_length_24.mlmodelc/model.mil +575 -0
  4. voxcpm_audio_vae_decoder_length_24.mlmodelc/weights/weight.bin +3 -0
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+ program(1.3)
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+ [buildInfo = dict<string, string>({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3405.2.1"}, {"coremltools-component-torch", "2.8.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})]
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+ {
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+ func main<ios18>(tensor<fp16, [1, 64, 24]> latent_pred) {
5
+ tensor<int32, [6]> input_1_pad_0 = const()[name = string("input_1_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
6
+ string input_1_mode_0 = const()[name = string("input_1_mode_0"), val = string("constant")];
7
+ fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
8
+ tensor<fp16, [1, 64, 30]> input_1_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_1_mode_0, pad = input_1_pad_0, x = latent_pred)[name = string("input_1_cast_fp16")];
9
+ string input_3_pad_type_0 = const()[name = string("input_3_pad_type_0"), val = string("valid")];
10
+ int32 input_3_groups_0 = const()[name = string("input_3_groups_0"), val = int32(64)];
11
+ tensor<int32, [1]> input_3_strides_0 = const()[name = string("input_3_strides_0"), val = tensor<int32, [1]>([1])];
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+ tensor<int32, [2]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
13
+ tensor<int32, [1]> input_3_dilations_0 = const()[name = string("input_3_dilations_0"), val = tensor<int32, [1]>([1])];
14
+ tensor<fp16, [64, 1, 7]> weight_1_to_fp16 = const()[name = string("weight_1_to_fp16"), val = tensor<fp16, [64, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
15
+ tensor<fp16, [64]> model_0_bias_to_fp16 = const()[name = string("model_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1024)))];
16
+ tensor<fp16, [1, 64, 24]> input_3_cast_fp16 = conv(bias = model_0_bias_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 = weight_1_to_fp16, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
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+ string x_3_pad_type_0 = const()[name = string("x_3_pad_type_0"), val = string("valid")];
18
+ tensor<int32, [1]> x_3_strides_0 = const()[name = string("x_3_strides_0"), val = tensor<int32, [1]>([1])];
19
+ tensor<int32, [2]> x_3_pad_0 = const()[name = string("x_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
20
+ tensor<int32, [1]> x_3_dilations_0 = const()[name = string("x_3_dilations_0"), val = tensor<int32, [1]>([1])];
21
+ int32 x_3_groups_0 = const()[name = string("x_3_groups_0"), val = int32(1)];
22
+ tensor<fp16, [1536, 64, 1]> weight_3_to_fp16 = const()[name = string("weight_3_to_fp16"), val = tensor<fp16, [1536, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1216)))];
23
+ tensor<fp16, [1536]> model_1_bias_to_fp16 = const()[name = string("model_1_bias_to_fp16"), val = tensor<fp16, [1536]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(197888)))];
24
+ tensor<fp16, [1, 1536, 24]> x_3_cast_fp16 = conv(bias = model_1_bias_to_fp16, dilations = x_3_dilations_0, groups = x_3_groups_0, pad = x_3_pad_0, pad_type = x_3_pad_type_0, strides = x_3_strides_0, weight = weight_3_to_fp16, x = input_3_cast_fp16)[name = string("x_3_cast_fp16")];
25
+ tensor<fp16, [1, 1536, 1]> model_2_block_0_alpha_to_fp16 = const()[name = string("model_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1536, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(201024)))];
26
+ tensor<fp16, [1, 1536, 24]> var_77_cast_fp16 = mul(x = model_2_block_0_alpha_to_fp16, y = x_3_cast_fp16)[name = string("op_77_cast_fp16")];
27
+ tensor<fp16, [1, 1536, 24]> var_78_cast_fp16 = sin(x = var_77_cast_fp16)[name = string("op_78_cast_fp16")];
28
+ fp16 var_16_promoted_to_fp16 = const()[name = string("op_16_promoted_to_fp16"), val = fp16(0x1p+1)];
29
+ tensor<fp16, [1, 1536, 24]> var_79_cast_fp16 = pow(x = var_78_cast_fp16, y = var_16_promoted_to_fp16)[name = string("op_79_cast_fp16")];
30
+ tensor<fp16, [1, 1536, 1]> var_76_to_fp16 = const()[name = string("op_76_to_fp16"), val = tensor<fp16, [1, 1536, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(204160)))];
31
+ tensor<fp16, [1, 1536, 24]> var_80_cast_fp16 = mul(x = var_76_to_fp16, y = var_79_cast_fp16)[name = string("op_80_cast_fp16")];
32
+ tensor<fp16, [1, 1536, 24]> input_7_cast_fp16 = add(x = x_3_cast_fp16, y = var_80_cast_fp16)[name = string("input_7_cast_fp16")];
33
+ string x_5_pad_type_0 = const()[name = string("x_5_pad_type_0"), val = string("valid")];
34
+ tensor<int32, [1]> x_5_strides_0 = const()[name = string("x_5_strides_0"), val = tensor<int32, [1]>([8])];
35
+ tensor<int32, [2]> x_5_pad_0 = const()[name = string("x_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
36
+ tensor<int32, [1]> x_5_dilations_0 = const()[name = string("x_5_dilations_0"), val = tensor<int32, [1]>([1])];
37
+ int32 x_5_groups_0 = const()[name = string("x_5_groups_0"), val = int32(1)];
38
+ tensor<int32, [3]> x_5_has_output_shape_output_shape_0 = const()[name = string("x_5_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 768, 200])];
39
+ tensor<fp16, [1536, 768, 16]> var_82_to_fp16 = const()[name = string("op_82_to_fp16"), val = tensor<fp16, [1536, 768, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(207296)))];
40
+ tensor<fp16, [768]> model_2_block_1_bias_to_fp16 = const()[name = string("model_2_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37956096)))];
41
+ tensor<fp16, [1, 768, 200]> x_5_has_output_shape_cast_fp16 = conv_transpose(bias = model_2_block_1_bias_to_fp16, dilations = x_5_dilations_0, groups = x_5_groups_0, output_shape = x_5_has_output_shape_output_shape_0, pad = x_5_pad_0, pad_type = x_5_pad_type_0, strides = x_5_strides_0, weight = var_82_to_fp16, x = input_7_cast_fp16)[name = string("x_5_has_output_shape_cast_fp16")];
42
+ tensor<int32, [3]> x_7_begin_0 = const()[name = string("x_7_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
43
+ tensor<int32, [3]> x_7_end_0 = const()[name = string("x_7_end_0"), val = tensor<int32, [3]>([1, 768, 192])];
44
+ tensor<bool, [3]> x_7_end_mask_0 = const()[name = string("x_7_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
45
+ tensor<fp16, [1, 768, 192]> x_7_cast_fp16 = slice_by_index(begin = x_7_begin_0, end = x_7_end_0, end_mask = x_7_end_mask_0, x = x_5_has_output_shape_cast_fp16)[name = string("x_7_cast_fp16")];
46
+ tensor<fp16, [1, 768, 1]> model_2_block_2_block_0_alpha_to_fp16 = const()[name = string("model_2_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37957696)))];
47
+ tensor<fp16, [1, 768, 192]> var_107_cast_fp16 = mul(x = model_2_block_2_block_0_alpha_to_fp16, y = x_7_cast_fp16)[name = string("op_107_cast_fp16")];
48
+ tensor<fp16, [1, 768, 192]> var_108_cast_fp16 = sin(x = var_107_cast_fp16)[name = string("op_108_cast_fp16")];
49
+ fp16 var_16_promoted_1_to_fp16 = const()[name = string("op_16_promoted_1_to_fp16"), val = fp16(0x1p+1)];
50
+ tensor<fp16, [1, 768, 192]> var_109_cast_fp16 = pow(x = var_108_cast_fp16, y = var_16_promoted_1_to_fp16)[name = string("op_109_cast_fp16")];
51
+ tensor<fp16, [1, 768, 1]> var_106_to_fp16 = const()[name = string("op_106_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37959296)))];
52
+ tensor<fp16, [1, 768, 192]> var_110_cast_fp16 = mul(x = var_106_to_fp16, y = var_109_cast_fp16)[name = string("op_110_cast_fp16")];
53
+ tensor<fp16, [1, 768, 192]> input_9_cast_fp16 = add(x = x_7_cast_fp16, y = var_110_cast_fp16)[name = string("input_9_cast_fp16")];
54
+ tensor<int32, [6]> input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
55
+ string input_11_mode_0 = const()[name = string("input_11_mode_0"), val = string("constant")];
56
+ fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
57
+ tensor<fp16, [1, 768, 198]> input_11_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_11_mode_0, pad = input_11_pad_0, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
58
+ string x_9_pad_type_0 = const()[name = string("x_9_pad_type_0"), val = string("valid")];
59
+ int32 x_9_groups_0 = const()[name = string("x_9_groups_0"), val = int32(768)];
60
+ tensor<int32, [1]> x_9_strides_0 = const()[name = string("x_9_strides_0"), val = tensor<int32, [1]>([1])];
61
+ tensor<int32, [2]> x_9_pad_0 = const()[name = string("x_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
62
+ tensor<int32, [1]> x_9_dilations_0 = const()[name = string("x_9_dilations_0"), val = tensor<int32, [1]>([1])];
63
+ tensor<fp16, [768, 1, 7]> weight_5_to_fp16 = const()[name = string("weight_5_to_fp16"), val = tensor<fp16, [768, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37960896)))];
64
+ tensor<fp16, [768]> model_2_block_2_block_1_bias_to_fp16 = const()[name = string("model_2_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37971712)))];
65
+ tensor<fp16, [1, 768, 192]> x_9_cast_fp16 = conv(bias = model_2_block_2_block_1_bias_to_fp16, dilations = x_9_dilations_0, groups = x_9_groups_0, pad = x_9_pad_0, pad_type = x_9_pad_type_0, strides = x_9_strides_0, weight = weight_5_to_fp16, x = input_11_cast_fp16)[name = string("x_9_cast_fp16")];
66
+ tensor<fp16, [1, 768, 1]> model_2_block_2_block_2_alpha_to_fp16 = const()[name = string("model_2_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37973312)))];
67
+ tensor<fp16, [1, 768, 192]> var_125_cast_fp16 = mul(x = model_2_block_2_block_2_alpha_to_fp16, y = x_9_cast_fp16)[name = string("op_125_cast_fp16")];
68
+ tensor<fp16, [1, 768, 192]> var_126_cast_fp16 = sin(x = var_125_cast_fp16)[name = string("op_126_cast_fp16")];
69
+ fp16 var_16_promoted_2_to_fp16 = const()[name = string("op_16_promoted_2_to_fp16"), val = fp16(0x1p+1)];
70
+ tensor<fp16, [1, 768, 192]> var_127_cast_fp16 = pow(x = var_126_cast_fp16, y = var_16_promoted_2_to_fp16)[name = string("op_127_cast_fp16")];
71
+ tensor<fp16, [1, 768, 1]> var_124_to_fp16 = const()[name = string("op_124_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37974912)))];
72
+ tensor<fp16, [1, 768, 192]> var_128_cast_fp16 = mul(x = var_124_to_fp16, y = var_127_cast_fp16)[name = string("op_128_cast_fp16")];
73
+ tensor<fp16, [1, 768, 192]> input_13_cast_fp16 = add(x = x_9_cast_fp16, y = var_128_cast_fp16)[name = string("input_13_cast_fp16")];
74
+ string y_1_pad_type_0 = const()[name = string("y_1_pad_type_0"), val = string("valid")];
75
+ tensor<int32, [1]> y_1_strides_0 = const()[name = string("y_1_strides_0"), val = tensor<int32, [1]>([1])];
76
+ tensor<int32, [2]> y_1_pad_0 = const()[name = string("y_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
77
+ tensor<int32, [1]> y_1_dilations_0 = const()[name = string("y_1_dilations_0"), val = tensor<int32, [1]>([1])];
78
+ int32 y_1_groups_0 = const()[name = string("y_1_groups_0"), val = int32(1)];
79
+ tensor<fp16, [768, 768, 1]> weight_7_to_fp16 = const()[name = string("weight_7_to_fp16"), val = tensor<fp16, [768, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37976512)))];
80
+ tensor<fp16, [768]> model_2_block_2_block_3_bias_to_fp16 = const()[name = string("model_2_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39156224)))];
81
+ tensor<fp16, [1, 768, 192]> y_1_cast_fp16 = conv(bias = model_2_block_2_block_3_bias_to_fp16, dilations = y_1_dilations_0, groups = y_1_groups_0, pad = y_1_pad_0, pad_type = y_1_pad_type_0, strides = y_1_strides_0, weight = weight_7_to_fp16, x = input_13_cast_fp16)[name = string("y_1_cast_fp16")];
82
+ tensor<fp16, [1, 768, 192]> x_11_cast_fp16 = add(x = x_7_cast_fp16, y = y_1_cast_fp16)[name = string("x_11_cast_fp16")];
83
+ tensor<fp16, [1, 768, 1]> model_2_block_3_block_0_alpha_to_fp16 = const()[name = string("model_2_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39157824)))];
84
+ tensor<fp16, [1, 768, 192]> var_157_cast_fp16 = mul(x = model_2_block_3_block_0_alpha_to_fp16, y = x_11_cast_fp16)[name = string("op_157_cast_fp16")];
85
+ tensor<fp16, [1, 768, 192]> var_158_cast_fp16 = sin(x = var_157_cast_fp16)[name = string("op_158_cast_fp16")];
86
+ fp16 var_16_promoted_3_to_fp16 = const()[name = string("op_16_promoted_3_to_fp16"), val = fp16(0x1p+1)];
87
+ tensor<fp16, [1, 768, 192]> var_159_cast_fp16 = pow(x = var_158_cast_fp16, y = var_16_promoted_3_to_fp16)[name = string("op_159_cast_fp16")];
88
+ tensor<fp16, [1, 768, 1]> var_156_to_fp16 = const()[name = string("op_156_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39159424)))];
89
+ tensor<fp16, [1, 768, 192]> var_160_cast_fp16 = mul(x = var_156_to_fp16, y = var_159_cast_fp16)[name = string("op_160_cast_fp16")];
90
+ tensor<fp16, [1, 768, 192]> input_17_cast_fp16 = add(x = x_11_cast_fp16, y = var_160_cast_fp16)[name = string("input_17_cast_fp16")];
91
+ tensor<int32, [6]> input_19_pad_0 = const()[name = string("input_19_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
92
+ string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("constant")];
93
+ fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
94
+ tensor<fp16, [1, 768, 210]> input_19_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_19_mode_0, pad = input_19_pad_0, x = input_17_cast_fp16)[name = string("input_19_cast_fp16")];
95
+ string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("valid")];
96
+ tensor<int32, [1]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [1]>([3])];
97
+ int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(768)];
98
+ tensor<int32, [1]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [1]>([1])];
99
+ tensor<int32, [2]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
100
+ tensor<fp16, [768, 1, 7]> weight_9_to_fp16 = const()[name = string("weight_9_to_fp16"), val = tensor<fp16, [768, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39161024)))];
101
+ tensor<fp16, [768]> model_2_block_3_block_1_bias_to_fp16 = const()[name = string("model_2_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39171840)))];
102
+ tensor<fp16, [1, 768, 192]> x_13_cast_fp16 = conv(bias = model_2_block_3_block_1_bias_to_fp16, dilations = x_13_dilations_0, groups = x_13_groups_0, pad = x_13_pad_0, pad_type = x_13_pad_type_0, strides = x_13_strides_0, weight = weight_9_to_fp16, x = input_19_cast_fp16)[name = string("x_13_cast_fp16")];
103
+ tensor<fp16, [1, 768, 1]> model_2_block_3_block_2_alpha_to_fp16 = const()[name = string("model_2_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39173440)))];
104
+ tensor<fp16, [1, 768, 192]> var_175_cast_fp16 = mul(x = model_2_block_3_block_2_alpha_to_fp16, y = x_13_cast_fp16)[name = string("op_175_cast_fp16")];
105
+ tensor<fp16, [1, 768, 192]> var_176_cast_fp16 = sin(x = var_175_cast_fp16)[name = string("op_176_cast_fp16")];
106
+ fp16 var_16_promoted_4_to_fp16 = const()[name = string("op_16_promoted_4_to_fp16"), val = fp16(0x1p+1)];
107
+ tensor<fp16, [1, 768, 192]> var_177_cast_fp16 = pow(x = var_176_cast_fp16, y = var_16_promoted_4_to_fp16)[name = string("op_177_cast_fp16")];
108
+ tensor<fp16, [1, 768, 1]> var_174_to_fp16 = const()[name = string("op_174_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39175040)))];
109
+ tensor<fp16, [1, 768, 192]> var_178_cast_fp16 = mul(x = var_174_to_fp16, y = var_177_cast_fp16)[name = string("op_178_cast_fp16")];
110
+ tensor<fp16, [1, 768, 192]> input_21_cast_fp16 = add(x = x_13_cast_fp16, y = var_178_cast_fp16)[name = string("input_21_cast_fp16")];
111
+ string y_3_pad_type_0 = const()[name = string("y_3_pad_type_0"), val = string("valid")];
112
+ tensor<int32, [1]> y_3_strides_0 = const()[name = string("y_3_strides_0"), val = tensor<int32, [1]>([1])];
113
+ tensor<int32, [2]> y_3_pad_0 = const()[name = string("y_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
114
+ tensor<int32, [1]> y_3_dilations_0 = const()[name = string("y_3_dilations_0"), val = tensor<int32, [1]>([1])];
115
+ int32 y_3_groups_0 = const()[name = string("y_3_groups_0"), val = int32(1)];
116
+ tensor<fp16, [768, 768, 1]> weight_11_to_fp16 = const()[name = string("weight_11_to_fp16"), val = tensor<fp16, [768, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39176640)))];
117
+ tensor<fp16, [768]> model_2_block_3_block_3_bias_to_fp16 = const()[name = string("model_2_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40356352)))];
118
+ tensor<fp16, [1, 768, 192]> y_3_cast_fp16 = conv(bias = model_2_block_3_block_3_bias_to_fp16, dilations = y_3_dilations_0, groups = y_3_groups_0, pad = y_3_pad_0, pad_type = y_3_pad_type_0, strides = y_3_strides_0, weight = weight_11_to_fp16, x = input_21_cast_fp16)[name = string("y_3_cast_fp16")];
119
+ tensor<fp16, [1, 768, 192]> x_15_cast_fp16 = add(x = x_11_cast_fp16, y = y_3_cast_fp16)[name = string("x_15_cast_fp16")];
120
+ tensor<fp16, [1, 768, 1]> model_2_block_4_block_0_alpha_to_fp16 = const()[name = string("model_2_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40357952)))];
121
+ tensor<fp16, [1, 768, 192]> var_207_cast_fp16 = mul(x = model_2_block_4_block_0_alpha_to_fp16, y = x_15_cast_fp16)[name = string("op_207_cast_fp16")];
122
+ tensor<fp16, [1, 768, 192]> var_208_cast_fp16 = sin(x = var_207_cast_fp16)[name = string("op_208_cast_fp16")];
123
+ fp16 var_16_promoted_5_to_fp16 = const()[name = string("op_16_promoted_5_to_fp16"), val = fp16(0x1p+1)];
124
+ tensor<fp16, [1, 768, 192]> var_209_cast_fp16 = pow(x = var_208_cast_fp16, y = var_16_promoted_5_to_fp16)[name = string("op_209_cast_fp16")];
125
+ tensor<fp16, [1, 768, 1]> var_206_to_fp16 = const()[name = string("op_206_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40359552)))];
126
+ tensor<fp16, [1, 768, 192]> var_210_cast_fp16 = mul(x = var_206_to_fp16, y = var_209_cast_fp16)[name = string("op_210_cast_fp16")];
127
+ tensor<fp16, [1, 768, 192]> input_25_cast_fp16 = add(x = x_15_cast_fp16, y = var_210_cast_fp16)[name = string("input_25_cast_fp16")];
128
+ tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
129
+ string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("constant")];
130
+ fp16 const_6_to_fp16 = const()[name = string("const_6_to_fp16"), val = fp16(0x0p+0)];
131
+ tensor<fp16, [1, 768, 246]> input_27_cast_fp16 = pad(constant_val = const_6_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
132
+ string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
133
+ tensor<int32, [1]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [1]>([9])];
134
+ int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(768)];
135
+ tensor<int32, [1]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [1]>([1])];
136
+ tensor<int32, [2]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
137
+ tensor<fp16, [768, 1, 7]> weight_13_to_fp16 = const()[name = string("weight_13_to_fp16"), val = tensor<fp16, [768, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40361152)))];
138
+ tensor<fp16, [768]> model_2_block_4_block_1_bias_to_fp16 = const()[name = string("model_2_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40371968)))];
139
+ tensor<fp16, [1, 768, 192]> x_17_cast_fp16 = conv(bias = model_2_block_4_block_1_bias_to_fp16, dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = weight_13_to_fp16, x = input_27_cast_fp16)[name = string("x_17_cast_fp16")];
140
+ tensor<fp16, [1, 768, 1]> model_2_block_4_block_2_alpha_to_fp16 = const()[name = string("model_2_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40373568)))];
141
+ tensor<fp16, [1, 768, 192]> var_225_cast_fp16 = mul(x = model_2_block_4_block_2_alpha_to_fp16, y = x_17_cast_fp16)[name = string("op_225_cast_fp16")];
142
+ tensor<fp16, [1, 768, 192]> var_226_cast_fp16 = sin(x = var_225_cast_fp16)[name = string("op_226_cast_fp16")];
143
+ fp16 var_16_promoted_6_to_fp16 = const()[name = string("op_16_promoted_6_to_fp16"), val = fp16(0x1p+1)];
144
+ tensor<fp16, [1, 768, 192]> var_227_cast_fp16 = pow(x = var_226_cast_fp16, y = var_16_promoted_6_to_fp16)[name = string("op_227_cast_fp16")];
145
+ tensor<fp16, [1, 768, 1]> var_224_to_fp16 = const()[name = string("op_224_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40375168)))];
146
+ tensor<fp16, [1, 768, 192]> var_228_cast_fp16 = mul(x = var_224_to_fp16, y = var_227_cast_fp16)[name = string("op_228_cast_fp16")];
147
+ tensor<fp16, [1, 768, 192]> input_29_cast_fp16 = add(x = x_17_cast_fp16, y = var_228_cast_fp16)[name = string("input_29_cast_fp16")];
148
+ string y_5_pad_type_0 = const()[name = string("y_5_pad_type_0"), val = string("valid")];
149
+ tensor<int32, [1]> y_5_strides_0 = const()[name = string("y_5_strides_0"), val = tensor<int32, [1]>([1])];
150
+ tensor<int32, [2]> y_5_pad_0 = const()[name = string("y_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
151
+ tensor<int32, [1]> y_5_dilations_0 = const()[name = string("y_5_dilations_0"), val = tensor<int32, [1]>([1])];
152
+ int32 y_5_groups_0 = const()[name = string("y_5_groups_0"), val = int32(1)];
153
+ tensor<fp16, [768, 768, 1]> weight_15_to_fp16 = const()[name = string("weight_15_to_fp16"), val = tensor<fp16, [768, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40376768)))];
154
+ tensor<fp16, [768]> model_2_block_4_block_3_bias_to_fp16 = const()[name = string("model_2_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41556480)))];
155
+ tensor<fp16, [1, 768, 192]> y_5_cast_fp16 = conv(bias = model_2_block_4_block_3_bias_to_fp16, dilations = y_5_dilations_0, groups = y_5_groups_0, pad = y_5_pad_0, pad_type = y_5_pad_type_0, strides = y_5_strides_0, weight = weight_15_to_fp16, x = input_29_cast_fp16)[name = string("y_5_cast_fp16")];
156
+ tensor<fp16, [1, 768, 192]> x_19_cast_fp16 = add(x = x_15_cast_fp16, y = y_5_cast_fp16)[name = string("x_19_cast_fp16")];
157
+ tensor<fp16, [1, 768, 1]> model_3_block_0_alpha_to_fp16 = const()[name = string("model_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41558080)))];
158
+ tensor<fp16, [1, 768, 192]> var_254_cast_fp16 = mul(x = model_3_block_0_alpha_to_fp16, y = x_19_cast_fp16)[name = string("op_254_cast_fp16")];
159
+ tensor<fp16, [1, 768, 192]> var_255_cast_fp16 = sin(x = var_254_cast_fp16)[name = string("op_255_cast_fp16")];
160
+ fp16 var_16_promoted_7_to_fp16 = const()[name = string("op_16_promoted_7_to_fp16"), val = fp16(0x1p+1)];
161
+ tensor<fp16, [1, 768, 192]> var_256_cast_fp16 = pow(x = var_255_cast_fp16, y = var_16_promoted_7_to_fp16)[name = string("op_256_cast_fp16")];
162
+ tensor<fp16, [1, 768, 1]> var_253_to_fp16 = const()[name = string("op_253_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41559680)))];
163
+ tensor<fp16, [1, 768, 192]> var_257_cast_fp16 = mul(x = var_253_to_fp16, y = var_256_cast_fp16)[name = string("op_257_cast_fp16")];
164
+ tensor<fp16, [1, 768, 192]> input_33_cast_fp16 = add(x = x_19_cast_fp16, y = var_257_cast_fp16)[name = string("input_33_cast_fp16")];
165
+ string x_21_pad_type_0 = const()[name = string("x_21_pad_type_0"), val = string("valid")];
166
+ tensor<int32, [1]> x_21_strides_0 = const()[name = string("x_21_strides_0"), val = tensor<int32, [1]>([8])];
167
+ tensor<int32, [2]> x_21_pad_0 = const()[name = string("x_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
168
+ tensor<int32, [1]> x_21_dilations_0 = const()[name = string("x_21_dilations_0"), val = tensor<int32, [1]>([1])];
169
+ int32 x_21_groups_0 = const()[name = string("x_21_groups_0"), val = int32(1)];
170
+ tensor<int32, [3]> x_21_has_output_shape_output_shape_0 = const()[name = string("x_21_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 384, 1544])];
171
+ tensor<fp16, [768, 384, 16]> var_259_to_fp16 = const()[name = string("op_259_to_fp16"), val = tensor<fp16, [768, 384, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41561280)))];
172
+ tensor<fp16, [384]> model_3_block_1_bias_to_fp16 = const()[name = string("model_3_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50998528)))];
173
+ tensor<fp16, [1, 384, 1544]> x_21_has_output_shape_cast_fp16 = conv_transpose(bias = model_3_block_1_bias_to_fp16, dilations = x_21_dilations_0, groups = x_21_groups_0, output_shape = x_21_has_output_shape_output_shape_0, pad = x_21_pad_0, pad_type = x_21_pad_type_0, strides = x_21_strides_0, weight = var_259_to_fp16, x = input_33_cast_fp16)[name = string("x_21_has_output_shape_cast_fp16")];
174
+ tensor<int32, [3]> x_23_begin_0 = const()[name = string("x_23_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
175
+ tensor<int32, [3]> x_23_end_0 = const()[name = string("x_23_end_0"), val = tensor<int32, [3]>([1, 384, 1536])];
176
+ tensor<bool, [3]> x_23_end_mask_0 = const()[name = string("x_23_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
177
+ tensor<fp16, [1, 384, 1536]> x_23_cast_fp16 = slice_by_index(begin = x_23_begin_0, end = x_23_end_0, end_mask = x_23_end_mask_0, x = x_21_has_output_shape_cast_fp16)[name = string("x_23_cast_fp16")];
178
+ tensor<fp16, [1, 384, 1]> model_3_block_2_block_0_alpha_to_fp16 = const()[name = string("model_3_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50999360)))];
179
+ tensor<fp16, [1, 384, 1536]> var_284_cast_fp16 = mul(x = model_3_block_2_block_0_alpha_to_fp16, y = x_23_cast_fp16)[name = string("op_284_cast_fp16")];
180
+ tensor<fp16, [1, 384, 1536]> var_285_cast_fp16 = sin(x = var_284_cast_fp16)[name = string("op_285_cast_fp16")];
181
+ fp16 var_16_promoted_8_to_fp16 = const()[name = string("op_16_promoted_8_to_fp16"), val = fp16(0x1p+1)];
182
+ tensor<fp16, [1, 384, 1536]> var_286_cast_fp16 = pow(x = var_285_cast_fp16, y = var_16_promoted_8_to_fp16)[name = string("op_286_cast_fp16")];
183
+ tensor<fp16, [1, 384, 1]> var_283_to_fp16 = const()[name = string("op_283_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51000192)))];
184
+ tensor<fp16, [1, 384, 1536]> var_287_cast_fp16 = mul(x = var_283_to_fp16, y = var_286_cast_fp16)[name = string("op_287_cast_fp16")];
185
+ tensor<fp16, [1, 384, 1536]> input_35_cast_fp16 = add(x = x_23_cast_fp16, y = var_287_cast_fp16)[name = string("input_35_cast_fp16")];
186
+ tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
187
+ string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("constant")];
188
+ fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
189
+ tensor<fp16, [1, 384, 1542]> input_37_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
190
+ string x_25_pad_type_0 = const()[name = string("x_25_pad_type_0"), val = string("valid")];
191
+ int32 x_25_groups_0 = const()[name = string("x_25_groups_0"), val = int32(384)];
192
+ tensor<int32, [1]> x_25_strides_0 = const()[name = string("x_25_strides_0"), val = tensor<int32, [1]>([1])];
193
+ tensor<int32, [2]> x_25_pad_0 = const()[name = string("x_25_pad_0"), val = tensor<int32, [2]>([0, 0])];
194
+ tensor<int32, [1]> x_25_dilations_0 = const()[name = string("x_25_dilations_0"), val = tensor<int32, [1]>([1])];
195
+ tensor<fp16, [384, 1, 7]> weight_17_to_fp16 = const()[name = string("weight_17_to_fp16"), val = tensor<fp16, [384, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51001024)))];
196
+ tensor<fp16, [384]> model_3_block_2_block_1_bias_to_fp16 = const()[name = string("model_3_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51006464)))];
197
+ tensor<fp16, [1, 384, 1536]> x_25_cast_fp16 = conv(bias = model_3_block_2_block_1_bias_to_fp16, dilations = x_25_dilations_0, groups = x_25_groups_0, pad = x_25_pad_0, pad_type = x_25_pad_type_0, strides = x_25_strides_0, weight = weight_17_to_fp16, x = input_37_cast_fp16)[name = string("x_25_cast_fp16")];
198
+ tensor<fp16, [1, 384, 1]> model_3_block_2_block_2_alpha_to_fp16 = const()[name = string("model_3_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51007296)))];
199
+ tensor<fp16, [1, 384, 1536]> var_302_cast_fp16 = mul(x = model_3_block_2_block_2_alpha_to_fp16, y = x_25_cast_fp16)[name = string("op_302_cast_fp16")];
200
+ tensor<fp16, [1, 384, 1536]> var_303_cast_fp16 = sin(x = var_302_cast_fp16)[name = string("op_303_cast_fp16")];
201
+ fp16 var_16_promoted_9_to_fp16 = const()[name = string("op_16_promoted_9_to_fp16"), val = fp16(0x1p+1)];
202
+ tensor<fp16, [1, 384, 1536]> var_304_cast_fp16 = pow(x = var_303_cast_fp16, y = var_16_promoted_9_to_fp16)[name = string("op_304_cast_fp16")];
203
+ tensor<fp16, [1, 384, 1]> var_301_to_fp16 = const()[name = string("op_301_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51008128)))];
204
+ tensor<fp16, [1, 384, 1536]> var_305_cast_fp16 = mul(x = var_301_to_fp16, y = var_304_cast_fp16)[name = string("op_305_cast_fp16")];
205
+ tensor<fp16, [1, 384, 1536]> input_39_cast_fp16 = add(x = x_25_cast_fp16, y = var_305_cast_fp16)[name = string("input_39_cast_fp16")];
206
+ string y_7_pad_type_0 = const()[name = string("y_7_pad_type_0"), val = string("valid")];
207
+ tensor<int32, [1]> y_7_strides_0 = const()[name = string("y_7_strides_0"), val = tensor<int32, [1]>([1])];
208
+ tensor<int32, [2]> y_7_pad_0 = const()[name = string("y_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
209
+ tensor<int32, [1]> y_7_dilations_0 = const()[name = string("y_7_dilations_0"), val = tensor<int32, [1]>([1])];
210
+ int32 y_7_groups_0 = const()[name = string("y_7_groups_0"), val = int32(1)];
211
+ tensor<fp16, [384, 384, 1]> weight_19_to_fp16 = const()[name = string("weight_19_to_fp16"), val = tensor<fp16, [384, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51008960)))];
212
+ tensor<fp16, [384]> model_3_block_2_block_3_bias_to_fp16 = const()[name = string("model_3_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51303936)))];
213
+ tensor<fp16, [1, 384, 1536]> y_7_cast_fp16 = conv(bias = model_3_block_2_block_3_bias_to_fp16, dilations = y_7_dilations_0, groups = y_7_groups_0, pad = y_7_pad_0, pad_type = y_7_pad_type_0, strides = y_7_strides_0, weight = weight_19_to_fp16, x = input_39_cast_fp16)[name = string("y_7_cast_fp16")];
214
+ tensor<fp16, [1, 384, 1536]> x_27_cast_fp16 = add(x = x_23_cast_fp16, y = y_7_cast_fp16)[name = string("x_27_cast_fp16")];
215
+ tensor<fp16, [1, 384, 1]> model_3_block_3_block_0_alpha_to_fp16 = const()[name = string("model_3_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51304768)))];
216
+ tensor<fp16, [1, 384, 1536]> var_334_cast_fp16 = mul(x = model_3_block_3_block_0_alpha_to_fp16, y = x_27_cast_fp16)[name = string("op_334_cast_fp16")];
217
+ tensor<fp16, [1, 384, 1536]> var_335_cast_fp16 = sin(x = var_334_cast_fp16)[name = string("op_335_cast_fp16")];
218
+ fp16 var_16_promoted_10_to_fp16 = const()[name = string("op_16_promoted_10_to_fp16"), val = fp16(0x1p+1)];
219
+ tensor<fp16, [1, 384, 1536]> var_336_cast_fp16 = pow(x = var_335_cast_fp16, y = var_16_promoted_10_to_fp16)[name = string("op_336_cast_fp16")];
220
+ tensor<fp16, [1, 384, 1]> var_333_to_fp16 = const()[name = string("op_333_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51305600)))];
221
+ tensor<fp16, [1, 384, 1536]> var_337_cast_fp16 = mul(x = var_333_to_fp16, y = var_336_cast_fp16)[name = string("op_337_cast_fp16")];
222
+ tensor<fp16, [1, 384, 1536]> input_43_cast_fp16 = add(x = x_27_cast_fp16, y = var_337_cast_fp16)[name = string("input_43_cast_fp16")];
223
+ tensor<int32, [6]> input_45_pad_0 = const()[name = string("input_45_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
224
+ string input_45_mode_0 = const()[name = string("input_45_mode_0"), val = string("constant")];
225
+ fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
226
+ tensor<fp16, [1, 384, 1554]> input_45_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_45_mode_0, pad = input_45_pad_0, x = input_43_cast_fp16)[name = string("input_45_cast_fp16")];
227
+ string x_29_pad_type_0 = const()[name = string("x_29_pad_type_0"), val = string("valid")];
228
+ tensor<int32, [1]> x_29_dilations_0 = const()[name = string("x_29_dilations_0"), val = tensor<int32, [1]>([3])];
229
+ int32 x_29_groups_0 = const()[name = string("x_29_groups_0"), val = int32(384)];
230
+ tensor<int32, [1]> x_29_strides_0 = const()[name = string("x_29_strides_0"), val = tensor<int32, [1]>([1])];
231
+ tensor<int32, [2]> x_29_pad_0 = const()[name = string("x_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
232
+ tensor<fp16, [384, 1, 7]> weight_21_to_fp16 = const()[name = string("weight_21_to_fp16"), val = tensor<fp16, [384, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51306432)))];
233
+ tensor<fp16, [384]> model_3_block_3_block_1_bias_to_fp16 = const()[name = string("model_3_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51311872)))];
234
+ tensor<fp16, [1, 384, 1536]> x_29_cast_fp16 = conv(bias = model_3_block_3_block_1_bias_to_fp16, dilations = x_29_dilations_0, groups = x_29_groups_0, pad = x_29_pad_0, pad_type = x_29_pad_type_0, strides = x_29_strides_0, weight = weight_21_to_fp16, x = input_45_cast_fp16)[name = string("x_29_cast_fp16")];
235
+ tensor<fp16, [1, 384, 1]> model_3_block_3_block_2_alpha_to_fp16 = const()[name = string("model_3_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51312704)))];
236
+ tensor<fp16, [1, 384, 1536]> var_352_cast_fp16 = mul(x = model_3_block_3_block_2_alpha_to_fp16, y = x_29_cast_fp16)[name = string("op_352_cast_fp16")];
237
+ tensor<fp16, [1, 384, 1536]> var_353_cast_fp16 = sin(x = var_352_cast_fp16)[name = string("op_353_cast_fp16")];
238
+ fp16 var_16_promoted_11_to_fp16 = const()[name = string("op_16_promoted_11_to_fp16"), val = fp16(0x1p+1)];
239
+ tensor<fp16, [1, 384, 1536]> var_354_cast_fp16 = pow(x = var_353_cast_fp16, y = var_16_promoted_11_to_fp16)[name = string("op_354_cast_fp16")];
240
+ tensor<fp16, [1, 384, 1]> var_351_to_fp16 = const()[name = string("op_351_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51313536)))];
241
+ tensor<fp16, [1, 384, 1536]> var_355_cast_fp16 = mul(x = var_351_to_fp16, y = var_354_cast_fp16)[name = string("op_355_cast_fp16")];
242
+ tensor<fp16, [1, 384, 1536]> input_47_cast_fp16 = add(x = x_29_cast_fp16, y = var_355_cast_fp16)[name = string("input_47_cast_fp16")];
243
+ string y_9_pad_type_0 = const()[name = string("y_9_pad_type_0"), val = string("valid")];
244
+ tensor<int32, [1]> y_9_strides_0 = const()[name = string("y_9_strides_0"), val = tensor<int32, [1]>([1])];
245
+ tensor<int32, [2]> y_9_pad_0 = const()[name = string("y_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
246
+ tensor<int32, [1]> y_9_dilations_0 = const()[name = string("y_9_dilations_0"), val = tensor<int32, [1]>([1])];
247
+ int32 y_9_groups_0 = const()[name = string("y_9_groups_0"), val = int32(1)];
248
+ tensor<fp16, [384, 384, 1]> weight_23_to_fp16 = const()[name = string("weight_23_to_fp16"), val = tensor<fp16, [384, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51314368)))];
249
+ tensor<fp16, [384]> model_3_block_3_block_3_bias_to_fp16 = const()[name = string("model_3_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51609344)))];
250
+ tensor<fp16, [1, 384, 1536]> y_9_cast_fp16 = conv(bias = model_3_block_3_block_3_bias_to_fp16, dilations = y_9_dilations_0, groups = y_9_groups_0, pad = y_9_pad_0, pad_type = y_9_pad_type_0, strides = y_9_strides_0, weight = weight_23_to_fp16, x = input_47_cast_fp16)[name = string("y_9_cast_fp16")];
251
+ tensor<fp16, [1, 384, 1536]> x_31_cast_fp16 = add(x = x_27_cast_fp16, y = y_9_cast_fp16)[name = string("x_31_cast_fp16")];
252
+ tensor<fp16, [1, 384, 1]> model_3_block_4_block_0_alpha_to_fp16 = const()[name = string("model_3_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51610176)))];
253
+ tensor<fp16, [1, 384, 1536]> var_384_cast_fp16 = mul(x = model_3_block_4_block_0_alpha_to_fp16, y = x_31_cast_fp16)[name = string("op_384_cast_fp16")];
254
+ tensor<fp16, [1, 384, 1536]> var_385_cast_fp16 = sin(x = var_384_cast_fp16)[name = string("op_385_cast_fp16")];
255
+ fp16 var_16_promoted_12_to_fp16 = const()[name = string("op_16_promoted_12_to_fp16"), val = fp16(0x1p+1)];
256
+ tensor<fp16, [1, 384, 1536]> var_386_cast_fp16 = pow(x = var_385_cast_fp16, y = var_16_promoted_12_to_fp16)[name = string("op_386_cast_fp16")];
257
+ tensor<fp16, [1, 384, 1]> var_383_to_fp16 = const()[name = string("op_383_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51611008)))];
258
+ tensor<fp16, [1, 384, 1536]> var_387_cast_fp16 = mul(x = var_383_to_fp16, y = var_386_cast_fp16)[name = string("op_387_cast_fp16")];
259
+ tensor<fp16, [1, 384, 1536]> input_51_cast_fp16 = add(x = x_31_cast_fp16, y = var_387_cast_fp16)[name = string("input_51_cast_fp16")];
260
+ tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
261
+ string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("constant")];
262
+ fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
263
+ tensor<fp16, [1, 384, 1590]> input_53_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
264
+ string x_33_pad_type_0 = const()[name = string("x_33_pad_type_0"), val = string("valid")];
265
+ tensor<int32, [1]> x_33_dilations_0 = const()[name = string("x_33_dilations_0"), val = tensor<int32, [1]>([9])];
266
+ int32 x_33_groups_0 = const()[name = string("x_33_groups_0"), val = int32(384)];
267
+ tensor<int32, [1]> x_33_strides_0 = const()[name = string("x_33_strides_0"), val = tensor<int32, [1]>([1])];
268
+ tensor<int32, [2]> x_33_pad_0 = const()[name = string("x_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
269
+ tensor<fp16, [384, 1, 7]> weight_25_to_fp16 = const()[name = string("weight_25_to_fp16"), val = tensor<fp16, [384, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51611840)))];
270
+ tensor<fp16, [384]> model_3_block_4_block_1_bias_to_fp16 = const()[name = string("model_3_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51617280)))];
271
+ tensor<fp16, [1, 384, 1536]> x_33_cast_fp16 = conv(bias = model_3_block_4_block_1_bias_to_fp16, dilations = x_33_dilations_0, groups = x_33_groups_0, pad = x_33_pad_0, pad_type = x_33_pad_type_0, strides = x_33_strides_0, weight = weight_25_to_fp16, x = input_53_cast_fp16)[name = string("x_33_cast_fp16")];
272
+ tensor<fp16, [1, 384, 1]> model_3_block_4_block_2_alpha_to_fp16 = const()[name = string("model_3_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51618112)))];
273
+ tensor<fp16, [1, 384, 1536]> var_402_cast_fp16 = mul(x = model_3_block_4_block_2_alpha_to_fp16, y = x_33_cast_fp16)[name = string("op_402_cast_fp16")];
274
+ tensor<fp16, [1, 384, 1536]> var_403_cast_fp16 = sin(x = var_402_cast_fp16)[name = string("op_403_cast_fp16")];
275
+ fp16 var_16_promoted_13_to_fp16 = const()[name = string("op_16_promoted_13_to_fp16"), val = fp16(0x1p+1)];
276
+ tensor<fp16, [1, 384, 1536]> var_404_cast_fp16 = pow(x = var_403_cast_fp16, y = var_16_promoted_13_to_fp16)[name = string("op_404_cast_fp16")];
277
+ tensor<fp16, [1, 384, 1]> var_401_to_fp16 = const()[name = string("op_401_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51618944)))];
278
+ tensor<fp16, [1, 384, 1536]> var_405_cast_fp16 = mul(x = var_401_to_fp16, y = var_404_cast_fp16)[name = string("op_405_cast_fp16")];
279
+ tensor<fp16, [1, 384, 1536]> input_55_cast_fp16 = add(x = x_33_cast_fp16, y = var_405_cast_fp16)[name = string("input_55_cast_fp16")];
280
+ string y_11_pad_type_0 = const()[name = string("y_11_pad_type_0"), val = string("valid")];
281
+ tensor<int32, [1]> y_11_strides_0 = const()[name = string("y_11_strides_0"), val = tensor<int32, [1]>([1])];
282
+ tensor<int32, [2]> y_11_pad_0 = const()[name = string("y_11_pad_0"), val = tensor<int32, [2]>([0, 0])];
283
+ tensor<int32, [1]> y_11_dilations_0 = const()[name = string("y_11_dilations_0"), val = tensor<int32, [1]>([1])];
284
+ int32 y_11_groups_0 = const()[name = string("y_11_groups_0"), val = int32(1)];
285
+ tensor<fp16, [384, 384, 1]> weight_27_to_fp16 = const()[name = string("weight_27_to_fp16"), val = tensor<fp16, [384, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51619776)))];
286
+ tensor<fp16, [384]> model_3_block_4_block_3_bias_to_fp16 = const()[name = string("model_3_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51914752)))];
287
+ tensor<fp16, [1, 384, 1536]> y_11_cast_fp16 = conv(bias = model_3_block_4_block_3_bias_to_fp16, dilations = y_11_dilations_0, groups = y_11_groups_0, pad = y_11_pad_0, pad_type = y_11_pad_type_0, strides = y_11_strides_0, weight = weight_27_to_fp16, x = input_55_cast_fp16)[name = string("y_11_cast_fp16")];
288
+ tensor<fp16, [1, 384, 1536]> x_35_cast_fp16 = add(x = x_31_cast_fp16, y = y_11_cast_fp16)[name = string("x_35_cast_fp16")];
289
+ tensor<fp16, [1, 384, 1]> model_4_block_0_alpha_to_fp16 = const()[name = string("model_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51915584)))];
290
+ tensor<fp16, [1, 384, 1536]> var_431_cast_fp16 = mul(x = model_4_block_0_alpha_to_fp16, y = x_35_cast_fp16)[name = string("op_431_cast_fp16")];
291
+ tensor<fp16, [1, 384, 1536]> var_432_cast_fp16 = sin(x = var_431_cast_fp16)[name = string("op_432_cast_fp16")];
292
+ fp16 var_16_promoted_14_to_fp16 = const()[name = string("op_16_promoted_14_to_fp16"), val = fp16(0x1p+1)];
293
+ tensor<fp16, [1, 384, 1536]> var_433_cast_fp16 = pow(x = var_432_cast_fp16, y = var_16_promoted_14_to_fp16)[name = string("op_433_cast_fp16")];
294
+ tensor<fp16, [1, 384, 1]> var_430_to_fp16 = const()[name = string("op_430_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51916416)))];
295
+ tensor<fp16, [1, 384, 1536]> var_434_cast_fp16 = mul(x = var_430_to_fp16, y = var_433_cast_fp16)[name = string("op_434_cast_fp16")];
296
+ tensor<fp16, [1, 384, 1536]> input_59_cast_fp16 = add(x = x_35_cast_fp16, y = var_434_cast_fp16)[name = string("input_59_cast_fp16")];
297
+ string x_37_pad_type_0 = const()[name = string("x_37_pad_type_0"), val = string("valid")];
298
+ tensor<int32, [1]> x_37_strides_0 = const()[name = string("x_37_strides_0"), val = tensor<int32, [1]>([5])];
299
+ tensor<int32, [2]> x_37_pad_0 = const()[name = string("x_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
300
+ tensor<int32, [1]> x_37_dilations_0 = const()[name = string("x_37_dilations_0"), val = tensor<int32, [1]>([1])];
301
+ int32 x_37_groups_0 = const()[name = string("x_37_groups_0"), val = int32(1)];
302
+ tensor<int32, [3]> x_37_has_output_shape_output_shape_0 = const()[name = string("x_37_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 192, 7685])];
303
+ tensor<fp16, [384, 192, 10]> var_436_to_fp16 = const()[name = string("op_436_to_fp16"), val = tensor<fp16, [384, 192, 10]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51917248)))];
304
+ tensor<fp16, [192]> model_4_block_1_bias_to_fp16 = const()[name = string("model_4_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53391872)))];
305
+ tensor<fp16, [1, 192, 7685]> x_37_has_output_shape_cast_fp16 = conv_transpose(bias = model_4_block_1_bias_to_fp16, dilations = x_37_dilations_0, groups = x_37_groups_0, output_shape = x_37_has_output_shape_output_shape_0, pad = x_37_pad_0, pad_type = x_37_pad_type_0, strides = x_37_strides_0, weight = var_436_to_fp16, x = input_59_cast_fp16)[name = string("x_37_has_output_shape_cast_fp16")];
306
+ tensor<int32, [3]> x_39_begin_0 = const()[name = string("x_39_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
307
+ tensor<int32, [3]> x_39_end_0 = const()[name = string("x_39_end_0"), val = tensor<int32, [3]>([1, 192, 7680])];
308
+ tensor<bool, [3]> x_39_end_mask_0 = const()[name = string("x_39_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
309
+ tensor<fp16, [1, 192, 7680]> x_39_cast_fp16 = slice_by_index(begin = x_39_begin_0, end = x_39_end_0, end_mask = x_39_end_mask_0, x = x_37_has_output_shape_cast_fp16)[name = string("x_39_cast_fp16")];
310
+ tensor<fp16, [1, 192, 1]> model_4_block_2_block_0_alpha_to_fp16 = const()[name = string("model_4_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53392320)))];
311
+ tensor<fp16, [1, 192, 7680]> var_461_cast_fp16 = mul(x = model_4_block_2_block_0_alpha_to_fp16, y = x_39_cast_fp16)[name = string("op_461_cast_fp16")];
312
+ tensor<fp16, [1, 192, 7680]> var_462_cast_fp16 = sin(x = var_461_cast_fp16)[name = string("op_462_cast_fp16")];
313
+ fp16 var_16_promoted_15_to_fp16 = const()[name = string("op_16_promoted_15_to_fp16"), val = fp16(0x1p+1)];
314
+ tensor<fp16, [1, 192, 7680]> var_463_cast_fp16 = pow(x = var_462_cast_fp16, y = var_16_promoted_15_to_fp16)[name = string("op_463_cast_fp16")];
315
+ tensor<fp16, [1, 192, 1]> var_460_to_fp16 = const()[name = string("op_460_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53392768)))];
316
+ tensor<fp16, [1, 192, 7680]> var_464_cast_fp16 = mul(x = var_460_to_fp16, y = var_463_cast_fp16)[name = string("op_464_cast_fp16")];
317
+ tensor<fp16, [1, 192, 7680]> input_61_cast_fp16 = add(x = x_39_cast_fp16, y = var_464_cast_fp16)[name = string("input_61_cast_fp16")];
318
+ tensor<int32, [6]> input_63_pad_0 = const()[name = string("input_63_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
319
+ string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("constant")];
320
+ fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
321
+ tensor<fp16, [1, 192, 7686]> input_63_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_63_mode_0, pad = input_63_pad_0, x = input_61_cast_fp16)[name = string("input_63_cast_fp16")];
322
+ string x_41_pad_type_0 = const()[name = string("x_41_pad_type_0"), val = string("valid")];
323
+ int32 x_41_groups_0 = const()[name = string("x_41_groups_0"), val = int32(192)];
324
+ tensor<int32, [1]> x_41_strides_0 = const()[name = string("x_41_strides_0"), val = tensor<int32, [1]>([1])];
325
+ tensor<int32, [2]> x_41_pad_0 = const()[name = string("x_41_pad_0"), val = tensor<int32, [2]>([0, 0])];
326
+ tensor<int32, [1]> x_41_dilations_0 = const()[name = string("x_41_dilations_0"), val = tensor<int32, [1]>([1])];
327
+ tensor<fp16, [192, 1, 7]> weight_29_to_fp16 = const()[name = string("weight_29_to_fp16"), val = tensor<fp16, [192, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53393216)))];
328
+ tensor<fp16, [192]> model_4_block_2_block_1_bias_to_fp16 = const()[name = string("model_4_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53395968)))];
329
+ tensor<fp16, [1, 192, 7680]> x_41_cast_fp16 = conv(bias = model_4_block_2_block_1_bias_to_fp16, dilations = x_41_dilations_0, groups = x_41_groups_0, pad = x_41_pad_0, pad_type = x_41_pad_type_0, strides = x_41_strides_0, weight = weight_29_to_fp16, x = input_63_cast_fp16)[name = string("x_41_cast_fp16")];
330
+ tensor<fp16, [1, 192, 1]> model_4_block_2_block_2_alpha_to_fp16 = const()[name = string("model_4_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53396416)))];
331
+ tensor<fp16, [1, 192, 7680]> var_479_cast_fp16 = mul(x = model_4_block_2_block_2_alpha_to_fp16, y = x_41_cast_fp16)[name = string("op_479_cast_fp16")];
332
+ tensor<fp16, [1, 192, 7680]> var_480_cast_fp16 = sin(x = var_479_cast_fp16)[name = string("op_480_cast_fp16")];
333
+ fp16 var_16_promoted_16_to_fp16 = const()[name = string("op_16_promoted_16_to_fp16"), val = fp16(0x1p+1)];
334
+ tensor<fp16, [1, 192, 7680]> var_481_cast_fp16 = pow(x = var_480_cast_fp16, y = var_16_promoted_16_to_fp16)[name = string("op_481_cast_fp16")];
335
+ tensor<fp16, [1, 192, 1]> var_478_to_fp16 = const()[name = string("op_478_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53396864)))];
336
+ tensor<fp16, [1, 192, 7680]> var_482_cast_fp16 = mul(x = var_478_to_fp16, y = var_481_cast_fp16)[name = string("op_482_cast_fp16")];
337
+ tensor<fp16, [1, 192, 7680]> input_65_cast_fp16 = add(x = x_41_cast_fp16, y = var_482_cast_fp16)[name = string("input_65_cast_fp16")];
338
+ string y_13_pad_type_0 = const()[name = string("y_13_pad_type_0"), val = string("valid")];
339
+ tensor<int32, [1]> y_13_strides_0 = const()[name = string("y_13_strides_0"), val = tensor<int32, [1]>([1])];
340
+ tensor<int32, [2]> y_13_pad_0 = const()[name = string("y_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
341
+ tensor<int32, [1]> y_13_dilations_0 = const()[name = string("y_13_dilations_0"), val = tensor<int32, [1]>([1])];
342
+ int32 y_13_groups_0 = const()[name = string("y_13_groups_0"), val = int32(1)];
343
+ tensor<fp16, [192, 192, 1]> weight_31_to_fp16 = const()[name = string("weight_31_to_fp16"), val = tensor<fp16, [192, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53397312)))];
344
+ tensor<fp16, [192]> model_4_block_2_block_3_bias_to_fp16 = const()[name = string("model_4_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53471104)))];
345
+ tensor<fp16, [1, 192, 7680]> y_13_cast_fp16 = conv(bias = model_4_block_2_block_3_bias_to_fp16, dilations = y_13_dilations_0, groups = y_13_groups_0, pad = y_13_pad_0, pad_type = y_13_pad_type_0, strides = y_13_strides_0, weight = weight_31_to_fp16, x = input_65_cast_fp16)[name = string("y_13_cast_fp16")];
346
+ tensor<fp16, [1, 192, 7680]> x_43_cast_fp16 = add(x = x_39_cast_fp16, y = y_13_cast_fp16)[name = string("x_43_cast_fp16")];
347
+ tensor<fp16, [1, 192, 1]> model_4_block_3_block_0_alpha_to_fp16 = const()[name = string("model_4_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53471552)))];
348
+ tensor<fp16, [1, 192, 7680]> var_511_cast_fp16 = mul(x = model_4_block_3_block_0_alpha_to_fp16, y = x_43_cast_fp16)[name = string("op_511_cast_fp16")];
349
+ tensor<fp16, [1, 192, 7680]> var_512_cast_fp16 = sin(x = var_511_cast_fp16)[name = string("op_512_cast_fp16")];
350
+ fp16 var_16_promoted_17_to_fp16 = const()[name = string("op_16_promoted_17_to_fp16"), val = fp16(0x1p+1)];
351
+ tensor<fp16, [1, 192, 7680]> var_513_cast_fp16 = pow(x = var_512_cast_fp16, y = var_16_promoted_17_to_fp16)[name = string("op_513_cast_fp16")];
352
+ tensor<fp16, [1, 192, 1]> var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53472000)))];
353
+ tensor<fp16, [1, 192, 7680]> var_514_cast_fp16 = mul(x = var_510_to_fp16, y = var_513_cast_fp16)[name = string("op_514_cast_fp16")];
354
+ tensor<fp16, [1, 192, 7680]> input_69_cast_fp16 = add(x = x_43_cast_fp16, y = var_514_cast_fp16)[name = string("input_69_cast_fp16")];
355
+ tensor<int32, [6]> input_71_pad_0 = const()[name = string("input_71_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
356
+ string input_71_mode_0 = const()[name = string("input_71_mode_0"), val = string("constant")];
357
+ fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
358
+ tensor<fp16, [1, 192, 7698]> input_71_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_71_mode_0, pad = input_71_pad_0, x = input_69_cast_fp16)[name = string("input_71_cast_fp16")];
359
+ string x_45_pad_type_0 = const()[name = string("x_45_pad_type_0"), val = string("valid")];
360
+ tensor<int32, [1]> x_45_dilations_0 = const()[name = string("x_45_dilations_0"), val = tensor<int32, [1]>([3])];
361
+ int32 x_45_groups_0 = const()[name = string("x_45_groups_0"), val = int32(192)];
362
+ tensor<int32, [1]> x_45_strides_0 = const()[name = string("x_45_strides_0"), val = tensor<int32, [1]>([1])];
363
+ tensor<int32, [2]> x_45_pad_0 = const()[name = string("x_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
364
+ tensor<fp16, [192, 1, 7]> weight_33_to_fp16 = const()[name = string("weight_33_to_fp16"), val = tensor<fp16, [192, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53472448)))];
365
+ tensor<fp16, [192]> model_4_block_3_block_1_bias_to_fp16 = const()[name = string("model_4_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53475200)))];
366
+ tensor<fp16, [1, 192, 7680]> x_45_cast_fp16 = conv(bias = model_4_block_3_block_1_bias_to_fp16, dilations = x_45_dilations_0, groups = x_45_groups_0, pad = x_45_pad_0, pad_type = x_45_pad_type_0, strides = x_45_strides_0, weight = weight_33_to_fp16, x = input_71_cast_fp16)[name = string("x_45_cast_fp16")];
367
+ tensor<fp16, [1, 192, 1]> model_4_block_3_block_2_alpha_to_fp16 = const()[name = string("model_4_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53475648)))];
368
+ tensor<fp16, [1, 192, 7680]> var_529_cast_fp16 = mul(x = model_4_block_3_block_2_alpha_to_fp16, y = x_45_cast_fp16)[name = string("op_529_cast_fp16")];
369
+ tensor<fp16, [1, 192, 7680]> var_530_cast_fp16 = sin(x = var_529_cast_fp16)[name = string("op_530_cast_fp16")];
370
+ fp16 var_16_promoted_18_to_fp16 = const()[name = string("op_16_promoted_18_to_fp16"), val = fp16(0x1p+1)];
371
+ tensor<fp16, [1, 192, 7680]> var_531_cast_fp16 = pow(x = var_530_cast_fp16, y = var_16_promoted_18_to_fp16)[name = string("op_531_cast_fp16")];
372
+ tensor<fp16, [1, 192, 1]> var_528_to_fp16 = const()[name = string("op_528_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53476096)))];
373
+ tensor<fp16, [1, 192, 7680]> var_532_cast_fp16 = mul(x = var_528_to_fp16, y = var_531_cast_fp16)[name = string("op_532_cast_fp16")];
374
+ tensor<fp16, [1, 192, 7680]> input_73_cast_fp16 = add(x = x_45_cast_fp16, y = var_532_cast_fp16)[name = string("input_73_cast_fp16")];
375
+ string y_15_pad_type_0 = const()[name = string("y_15_pad_type_0"), val = string("valid")];
376
+ tensor<int32, [1]> y_15_strides_0 = const()[name = string("y_15_strides_0"), val = tensor<int32, [1]>([1])];
377
+ tensor<int32, [2]> y_15_pad_0 = const()[name = string("y_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
378
+ tensor<int32, [1]> y_15_dilations_0 = const()[name = string("y_15_dilations_0"), val = tensor<int32, [1]>([1])];
379
+ int32 y_15_groups_0 = const()[name = string("y_15_groups_0"), val = int32(1)];
380
+ tensor<fp16, [192, 192, 1]> weight_35_to_fp16 = const()[name = string("weight_35_to_fp16"), val = tensor<fp16, [192, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53476544)))];
381
+ tensor<fp16, [192]> model_4_block_3_block_3_bias_to_fp16 = const()[name = string("model_4_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53550336)))];
382
+ tensor<fp16, [1, 192, 7680]> y_15_cast_fp16 = conv(bias = model_4_block_3_block_3_bias_to_fp16, dilations = y_15_dilations_0, groups = y_15_groups_0, pad = y_15_pad_0, pad_type = y_15_pad_type_0, strides = y_15_strides_0, weight = weight_35_to_fp16, x = input_73_cast_fp16)[name = string("y_15_cast_fp16")];
383
+ tensor<fp16, [1, 192, 7680]> x_47_cast_fp16 = add(x = x_43_cast_fp16, y = y_15_cast_fp16)[name = string("x_47_cast_fp16")];
384
+ tensor<fp16, [1, 192, 1]> model_4_block_4_block_0_alpha_to_fp16 = const()[name = string("model_4_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53550784)))];
385
+ tensor<fp16, [1, 192, 7680]> var_561_cast_fp16 = mul(x = model_4_block_4_block_0_alpha_to_fp16, y = x_47_cast_fp16)[name = string("op_561_cast_fp16")];
386
+ tensor<fp16, [1, 192, 7680]> var_562_cast_fp16 = sin(x = var_561_cast_fp16)[name = string("op_562_cast_fp16")];
387
+ fp16 var_16_promoted_19_to_fp16 = const()[name = string("op_16_promoted_19_to_fp16"), val = fp16(0x1p+1)];
388
+ tensor<fp16, [1, 192, 7680]> var_563_cast_fp16 = pow(x = var_562_cast_fp16, y = var_16_promoted_19_to_fp16)[name = string("op_563_cast_fp16")];
389
+ tensor<fp16, [1, 192, 1]> var_560_to_fp16 = const()[name = string("op_560_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53551232)))];
390
+ tensor<fp16, [1, 192, 7680]> var_564_cast_fp16 = mul(x = var_560_to_fp16, y = var_563_cast_fp16)[name = string("op_564_cast_fp16")];
391
+ tensor<fp16, [1, 192, 7680]> input_77_cast_fp16 = add(x = x_47_cast_fp16, y = var_564_cast_fp16)[name = string("input_77_cast_fp16")];
392
+ tensor<int32, [6]> input_79_pad_0 = const()[name = string("input_79_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
393
+ string input_79_mode_0 = const()[name = string("input_79_mode_0"), val = string("constant")];
394
+ fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
395
+ tensor<fp16, [1, 192, 7734]> input_79_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_79_mode_0, pad = input_79_pad_0, x = input_77_cast_fp16)[name = string("input_79_cast_fp16")];
396
+ string x_49_pad_type_0 = const()[name = string("x_49_pad_type_0"), val = string("valid")];
397
+ tensor<int32, [1]> x_49_dilations_0 = const()[name = string("x_49_dilations_0"), val = tensor<int32, [1]>([9])];
398
+ int32 x_49_groups_0 = const()[name = string("x_49_groups_0"), val = int32(192)];
399
+ tensor<int32, [1]> x_49_strides_0 = const()[name = string("x_49_strides_0"), val = tensor<int32, [1]>([1])];
400
+ tensor<int32, [2]> x_49_pad_0 = const()[name = string("x_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
401
+ tensor<fp16, [192, 1, 7]> weight_37_to_fp16 = const()[name = string("weight_37_to_fp16"), val = tensor<fp16, [192, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53551680)))];
402
+ tensor<fp16, [192]> model_4_block_4_block_1_bias_to_fp16 = const()[name = string("model_4_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53554432)))];
403
+ tensor<fp16, [1, 192, 7680]> x_49_cast_fp16 = conv(bias = model_4_block_4_block_1_bias_to_fp16, dilations = x_49_dilations_0, groups = x_49_groups_0, pad = x_49_pad_0, pad_type = x_49_pad_type_0, strides = x_49_strides_0, weight = weight_37_to_fp16, x = input_79_cast_fp16)[name = string("x_49_cast_fp16")];
404
+ tensor<fp16, [1, 192, 1]> model_4_block_4_block_2_alpha_to_fp16 = const()[name = string("model_4_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53554880)))];
405
+ tensor<fp16, [1, 192, 7680]> var_579_cast_fp16 = mul(x = model_4_block_4_block_2_alpha_to_fp16, y = x_49_cast_fp16)[name = string("op_579_cast_fp16")];
406
+ tensor<fp16, [1, 192, 7680]> var_580_cast_fp16 = sin(x = var_579_cast_fp16)[name = string("op_580_cast_fp16")];
407
+ fp16 var_16_promoted_20_to_fp16 = const()[name = string("op_16_promoted_20_to_fp16"), val = fp16(0x1p+1)];
408
+ tensor<fp16, [1, 192, 7680]> var_581_cast_fp16 = pow(x = var_580_cast_fp16, y = var_16_promoted_20_to_fp16)[name = string("op_581_cast_fp16")];
409
+ tensor<fp16, [1, 192, 1]> var_578_to_fp16 = const()[name = string("op_578_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53555328)))];
410
+ tensor<fp16, [1, 192, 7680]> var_582_cast_fp16 = mul(x = var_578_to_fp16, y = var_581_cast_fp16)[name = string("op_582_cast_fp16")];
411
+ tensor<fp16, [1, 192, 7680]> input_81_cast_fp16 = add(x = x_49_cast_fp16, y = var_582_cast_fp16)[name = string("input_81_cast_fp16")];
412
+ string y_17_pad_type_0 = const()[name = string("y_17_pad_type_0"), val = string("valid")];
413
+ tensor<int32, [1]> y_17_strides_0 = const()[name = string("y_17_strides_0"), val = tensor<int32, [1]>([1])];
414
+ tensor<int32, [2]> y_17_pad_0 = const()[name = string("y_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
415
+ tensor<int32, [1]> y_17_dilations_0 = const()[name = string("y_17_dilations_0"), val = tensor<int32, [1]>([1])];
416
+ int32 y_17_groups_0 = const()[name = string("y_17_groups_0"), val = int32(1)];
417
+ tensor<fp16, [192, 192, 1]> weight_39_to_fp16 = const()[name = string("weight_39_to_fp16"), val = tensor<fp16, [192, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53555776)))];
418
+ tensor<fp16, [192]> model_4_block_4_block_3_bias_to_fp16 = const()[name = string("model_4_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53629568)))];
419
+ tensor<fp16, [1, 192, 7680]> y_17_cast_fp16 = conv(bias = model_4_block_4_block_3_bias_to_fp16, dilations = y_17_dilations_0, groups = y_17_groups_0, pad = y_17_pad_0, pad_type = y_17_pad_type_0, strides = y_17_strides_0, weight = weight_39_to_fp16, x = input_81_cast_fp16)[name = string("y_17_cast_fp16")];
420
+ tensor<fp16, [1, 192, 7680]> x_51_cast_fp16 = add(x = x_47_cast_fp16, y = y_17_cast_fp16)[name = string("x_51_cast_fp16")];
421
+ tensor<fp16, [1, 192, 1]> model_5_block_0_alpha_to_fp16 = const()[name = string("model_5_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53630016)))];
422
+ tensor<fp16, [1, 192, 7680]> var_608_cast_fp16 = mul(x = model_5_block_0_alpha_to_fp16, y = x_51_cast_fp16)[name = string("op_608_cast_fp16")];
423
+ tensor<fp16, [1, 192, 7680]> var_609_cast_fp16 = sin(x = var_608_cast_fp16)[name = string("op_609_cast_fp16")];
424
+ fp16 var_16_promoted_21_to_fp16 = const()[name = string("op_16_promoted_21_to_fp16"), val = fp16(0x1p+1)];
425
+ tensor<fp16, [1, 192, 7680]> var_610_cast_fp16 = pow(x = var_609_cast_fp16, y = var_16_promoted_21_to_fp16)[name = string("op_610_cast_fp16")];
426
+ tensor<fp16, [1, 192, 1]> var_607_to_fp16 = const()[name = string("op_607_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53630464)))];
427
+ tensor<fp16, [1, 192, 7680]> var_611_cast_fp16 = mul(x = var_607_to_fp16, y = var_610_cast_fp16)[name = string("op_611_cast_fp16")];
428
+ tensor<fp16, [1, 192, 7680]> input_85_cast_fp16 = add(x = x_51_cast_fp16, y = var_611_cast_fp16)[name = string("input_85_cast_fp16")];
429
+ string x_53_pad_type_0 = const()[name = string("x_53_pad_type_0"), val = string("valid")];
430
+ tensor<int32, [1]> x_53_strides_0 = const()[name = string("x_53_strides_0"), val = tensor<int32, [1]>([2])];
431
+ tensor<int32, [2]> x_53_pad_0 = const()[name = string("x_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
432
+ tensor<int32, [1]> x_53_dilations_0 = const()[name = string("x_53_dilations_0"), val = tensor<int32, [1]>([1])];
433
+ int32 x_53_groups_0 = const()[name = string("x_53_groups_0"), val = int32(1)];
434
+ tensor<int32, [3]> x_53_has_output_shape_output_shape_0 = const()[name = string("x_53_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 96, 15362])];
435
+ tensor<fp16, [192, 96, 4]> var_613_to_fp16 = const()[name = string("op_613_to_fp16"), val = tensor<fp16, [192, 96, 4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53630912)))];
436
+ tensor<fp16, [96]> model_5_block_1_bias_to_fp16 = const()[name = string("model_5_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53778432)))];
437
+ tensor<fp16, [1, 96, 15362]> x_53_has_output_shape_cast_fp16 = conv_transpose(bias = model_5_block_1_bias_to_fp16, dilations = x_53_dilations_0, groups = x_53_groups_0, output_shape = x_53_has_output_shape_output_shape_0, pad = x_53_pad_0, pad_type = x_53_pad_type_0, strides = x_53_strides_0, weight = var_613_to_fp16, x = input_85_cast_fp16)[name = string("x_53_has_output_shape_cast_fp16")];
438
+ tensor<int32, [3]> x_55_begin_0 = const()[name = string("x_55_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
439
+ tensor<int32, [3]> x_55_end_0 = const()[name = string("x_55_end_0"), val = tensor<int32, [3]>([1, 96, 15360])];
440
+ tensor<bool, [3]> x_55_end_mask_0 = const()[name = string("x_55_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
441
+ tensor<fp16, [1, 96, 15360]> x_55_cast_fp16 = slice_by_index(begin = x_55_begin_0, end = x_55_end_0, end_mask = x_55_end_mask_0, x = x_53_has_output_shape_cast_fp16)[name = string("x_55_cast_fp16")];
442
+ tensor<fp16, [1, 96, 1]> model_5_block_2_block_0_alpha_to_fp16 = const()[name = string("model_5_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53778688)))];
443
+ tensor<fp16, [1, 96, 15360]> var_638_cast_fp16 = mul(x = model_5_block_2_block_0_alpha_to_fp16, y = x_55_cast_fp16)[name = string("op_638_cast_fp16")];
444
+ tensor<fp16, [1, 96, 15360]> var_639_cast_fp16 = sin(x = var_638_cast_fp16)[name = string("op_639_cast_fp16")];
445
+ fp16 var_16_promoted_22_to_fp16 = const()[name = string("op_16_promoted_22_to_fp16"), val = fp16(0x1p+1)];
446
+ tensor<fp16, [1, 96, 15360]> var_640_cast_fp16 = pow(x = var_639_cast_fp16, y = var_16_promoted_22_to_fp16)[name = string("op_640_cast_fp16")];
447
+ tensor<fp16, [1, 96, 1]> var_637_to_fp16 = const()[name = string("op_637_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53778944)))];
448
+ tensor<fp16, [1, 96, 15360]> var_641_cast_fp16 = mul(x = var_637_to_fp16, y = var_640_cast_fp16)[name = string("op_641_cast_fp16")];
449
+ tensor<fp16, [1, 96, 15360]> input_87_cast_fp16 = add(x = x_55_cast_fp16, y = var_641_cast_fp16)[name = string("input_87_cast_fp16")];
450
+ tensor<int32, [6]> input_89_pad_0 = const()[name = string("input_89_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
451
+ string input_89_mode_0 = const()[name = string("input_89_mode_0"), val = string("constant")];
452
+ fp16 const_20_to_fp16 = const()[name = string("const_20_to_fp16"), val = fp16(0x0p+0)];
453
+ tensor<fp16, [1, 96, 15366]> input_89_cast_fp16 = pad(constant_val = const_20_to_fp16, mode = input_89_mode_0, pad = input_89_pad_0, x = input_87_cast_fp16)[name = string("input_89_cast_fp16")];
454
+ string x_57_pad_type_0 = const()[name = string("x_57_pad_type_0"), val = string("valid")];
455
+ int32 x_57_groups_0 = const()[name = string("x_57_groups_0"), val = int32(96)];
456
+ tensor<int32, [1]> x_57_strides_0 = const()[name = string("x_57_strides_0"), val = tensor<int32, [1]>([1])];
457
+ tensor<int32, [2]> x_57_pad_0 = const()[name = string("x_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
458
+ tensor<int32, [1]> x_57_dilations_0 = const()[name = string("x_57_dilations_0"), val = tensor<int32, [1]>([1])];
459
+ tensor<fp16, [96, 1, 7]> weight_41_to_fp16 = const()[name = string("weight_41_to_fp16"), val = tensor<fp16, [96, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53779200)))];
460
+ tensor<fp16, [96]> model_5_block_2_block_1_bias_to_fp16 = const()[name = string("model_5_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53780608)))];
461
+ tensor<fp16, [1, 96, 15360]> x_57_cast_fp16 = conv(bias = model_5_block_2_block_1_bias_to_fp16, dilations = x_57_dilations_0, groups = x_57_groups_0, pad = x_57_pad_0, pad_type = x_57_pad_type_0, strides = x_57_strides_0, weight = weight_41_to_fp16, x = input_89_cast_fp16)[name = string("x_57_cast_fp16")];
462
+ tensor<fp16, [1, 96, 1]> model_5_block_2_block_2_alpha_to_fp16 = const()[name = string("model_5_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53780864)))];
463
+ tensor<fp16, [1, 96, 15360]> var_656_cast_fp16 = mul(x = model_5_block_2_block_2_alpha_to_fp16, y = x_57_cast_fp16)[name = string("op_656_cast_fp16")];
464
+ tensor<fp16, [1, 96, 15360]> var_657_cast_fp16 = sin(x = var_656_cast_fp16)[name = string("op_657_cast_fp16")];
465
+ fp16 var_16_promoted_23_to_fp16 = const()[name = string("op_16_promoted_23_to_fp16"), val = fp16(0x1p+1)];
466
+ tensor<fp16, [1, 96, 15360]> var_658_cast_fp16 = pow(x = var_657_cast_fp16, y = var_16_promoted_23_to_fp16)[name = string("op_658_cast_fp16")];
467
+ tensor<fp16, [1, 96, 1]> var_655_to_fp16 = const()[name = string("op_655_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53781120)))];
468
+ tensor<fp16, [1, 96, 15360]> var_659_cast_fp16 = mul(x = var_655_to_fp16, y = var_658_cast_fp16)[name = string("op_659_cast_fp16")];
469
+ tensor<fp16, [1, 96, 15360]> input_91_cast_fp16 = add(x = x_57_cast_fp16, y = var_659_cast_fp16)[name = string("input_91_cast_fp16")];
470
+ string y_19_pad_type_0 = const()[name = string("y_19_pad_type_0"), val = string("valid")];
471
+ tensor<int32, [1]> y_19_strides_0 = const()[name = string("y_19_strides_0"), val = tensor<int32, [1]>([1])];
472
+ tensor<int32, [2]> y_19_pad_0 = const()[name = string("y_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
473
+ tensor<int32, [1]> y_19_dilations_0 = const()[name = string("y_19_dilations_0"), val = tensor<int32, [1]>([1])];
474
+ int32 y_19_groups_0 = const()[name = string("y_19_groups_0"), val = int32(1)];
475
+ tensor<fp16, [96, 96, 1]> weight_43_to_fp16 = const()[name = string("weight_43_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53781376)))];
476
+ tensor<fp16, [96]> model_5_block_2_block_3_bias_to_fp16 = const()[name = string("model_5_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53799872)))];
477
+ tensor<fp16, [1, 96, 15360]> y_19_cast_fp16 = conv(bias = model_5_block_2_block_3_bias_to_fp16, dilations = y_19_dilations_0, groups = y_19_groups_0, pad = y_19_pad_0, pad_type = y_19_pad_type_0, strides = y_19_strides_0, weight = weight_43_to_fp16, x = input_91_cast_fp16)[name = string("y_19_cast_fp16")];
478
+ tensor<fp16, [1, 96, 15360]> x_59_cast_fp16 = add(x = x_55_cast_fp16, y = y_19_cast_fp16)[name = string("x_59_cast_fp16")];
479
+ tensor<fp16, [1, 96, 1]> model_5_block_3_block_0_alpha_to_fp16 = const()[name = string("model_5_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53800128)))];
480
+ tensor<fp16, [1, 96, 15360]> var_688_cast_fp16 = mul(x = model_5_block_3_block_0_alpha_to_fp16, y = x_59_cast_fp16)[name = string("op_688_cast_fp16")];
481
+ tensor<fp16, [1, 96, 15360]> var_689_cast_fp16 = sin(x = var_688_cast_fp16)[name = string("op_689_cast_fp16")];
482
+ fp16 var_16_promoted_24_to_fp16 = const()[name = string("op_16_promoted_24_to_fp16"), val = fp16(0x1p+1)];
483
+ tensor<fp16, [1, 96, 15360]> var_690_cast_fp16 = pow(x = var_689_cast_fp16, y = var_16_promoted_24_to_fp16)[name = string("op_690_cast_fp16")];
484
+ tensor<fp16, [1, 96, 1]> var_687_to_fp16 = const()[name = string("op_687_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53800384)))];
485
+ tensor<fp16, [1, 96, 15360]> var_691_cast_fp16 = mul(x = var_687_to_fp16, y = var_690_cast_fp16)[name = string("op_691_cast_fp16")];
486
+ tensor<fp16, [1, 96, 15360]> input_95_cast_fp16 = add(x = x_59_cast_fp16, y = var_691_cast_fp16)[name = string("input_95_cast_fp16")];
487
+ tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
488
+ string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("constant")];
489
+ fp16 const_22_to_fp16 = const()[name = string("const_22_to_fp16"), val = fp16(0x0p+0)];
490
+ tensor<fp16, [1, 96, 15378]> input_97_cast_fp16 = pad(constant_val = const_22_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
491
+ string x_61_pad_type_0 = const()[name = string("x_61_pad_type_0"), val = string("valid")];
492
+ tensor<int32, [1]> x_61_dilations_0 = const()[name = string("x_61_dilations_0"), val = tensor<int32, [1]>([3])];
493
+ int32 x_61_groups_0 = const()[name = string("x_61_groups_0"), val = int32(96)];
494
+ tensor<int32, [1]> x_61_strides_0 = const()[name = string("x_61_strides_0"), val = tensor<int32, [1]>([1])];
495
+ tensor<int32, [2]> x_61_pad_0 = const()[name = string("x_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
496
+ tensor<fp16, [96, 1, 7]> weight_45_to_fp16 = const()[name = string("weight_45_to_fp16"), val = tensor<fp16, [96, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53800640)))];
497
+ tensor<fp16, [96]> model_5_block_3_block_1_bias_to_fp16 = const()[name = string("model_5_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802048)))];
498
+ tensor<fp16, [1, 96, 15360]> x_61_cast_fp16 = conv(bias = model_5_block_3_block_1_bias_to_fp16, dilations = x_61_dilations_0, groups = x_61_groups_0, pad = x_61_pad_0, pad_type = x_61_pad_type_0, strides = x_61_strides_0, weight = weight_45_to_fp16, x = input_97_cast_fp16)[name = string("x_61_cast_fp16")];
499
+ tensor<fp16, [1, 96, 1]> model_5_block_3_block_2_alpha_to_fp16 = const()[name = string("model_5_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802304)))];
500
+ tensor<fp16, [1, 96, 15360]> var_706_cast_fp16 = mul(x = model_5_block_3_block_2_alpha_to_fp16, y = x_61_cast_fp16)[name = string("op_706_cast_fp16")];
501
+ tensor<fp16, [1, 96, 15360]> var_707_cast_fp16 = sin(x = var_706_cast_fp16)[name = string("op_707_cast_fp16")];
502
+ fp16 var_16_promoted_25_to_fp16 = const()[name = string("op_16_promoted_25_to_fp16"), val = fp16(0x1p+1)];
503
+ tensor<fp16, [1, 96, 15360]> var_708_cast_fp16 = pow(x = var_707_cast_fp16, y = var_16_promoted_25_to_fp16)[name = string("op_708_cast_fp16")];
504
+ tensor<fp16, [1, 96, 1]> var_705_to_fp16 = const()[name = string("op_705_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802560)))];
505
+ tensor<fp16, [1, 96, 15360]> var_709_cast_fp16 = mul(x = var_705_to_fp16, y = var_708_cast_fp16)[name = string("op_709_cast_fp16")];
506
+ tensor<fp16, [1, 96, 15360]> input_99_cast_fp16 = add(x = x_61_cast_fp16, y = var_709_cast_fp16)[name = string("input_99_cast_fp16")];
507
+ string y_21_pad_type_0 = const()[name = string("y_21_pad_type_0"), val = string("valid")];
508
+ tensor<int32, [1]> y_21_strides_0 = const()[name = string("y_21_strides_0"), val = tensor<int32, [1]>([1])];
509
+ tensor<int32, [2]> y_21_pad_0 = const()[name = string("y_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
510
+ tensor<int32, [1]> y_21_dilations_0 = const()[name = string("y_21_dilations_0"), val = tensor<int32, [1]>([1])];
511
+ int32 y_21_groups_0 = const()[name = string("y_21_groups_0"), val = int32(1)];
512
+ tensor<fp16, [96, 96, 1]> weight_47_to_fp16 = const()[name = string("weight_47_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802816)))];
513
+ tensor<fp16, [96]> model_5_block_3_block_3_bias_to_fp16 = const()[name = string("model_5_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53821312)))];
514
+ tensor<fp16, [1, 96, 15360]> y_21_cast_fp16 = conv(bias = model_5_block_3_block_3_bias_to_fp16, dilations = y_21_dilations_0, groups = y_21_groups_0, pad = y_21_pad_0, pad_type = y_21_pad_type_0, strides = y_21_strides_0, weight = weight_47_to_fp16, x = input_99_cast_fp16)[name = string("y_21_cast_fp16")];
515
+ tensor<fp16, [1, 96, 15360]> x_63_cast_fp16 = add(x = x_59_cast_fp16, y = y_21_cast_fp16)[name = string("x_63_cast_fp16")];
516
+ tensor<fp16, [1, 96, 1]> model_5_block_4_block_0_alpha_to_fp16 = const()[name = string("model_5_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53821568)))];
517
+ tensor<fp16, [1, 96, 15360]> var_738_cast_fp16 = mul(x = model_5_block_4_block_0_alpha_to_fp16, y = x_63_cast_fp16)[name = string("op_738_cast_fp16")];
518
+ tensor<fp16, [1, 96, 15360]> var_739_cast_fp16 = sin(x = var_738_cast_fp16)[name = string("op_739_cast_fp16")];
519
+ fp16 var_16_promoted_26_to_fp16 = const()[name = string("op_16_promoted_26_to_fp16"), val = fp16(0x1p+1)];
520
+ tensor<fp16, [1, 96, 15360]> var_740_cast_fp16 = pow(x = var_739_cast_fp16, y = var_16_promoted_26_to_fp16)[name = string("op_740_cast_fp16")];
521
+ tensor<fp16, [1, 96, 1]> var_737_to_fp16 = const()[name = string("op_737_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53821824)))];
522
+ tensor<fp16, [1, 96, 15360]> var_741_cast_fp16 = mul(x = var_737_to_fp16, y = var_740_cast_fp16)[name = string("op_741_cast_fp16")];
523
+ tensor<fp16, [1, 96, 15360]> input_103_cast_fp16 = add(x = x_63_cast_fp16, y = var_741_cast_fp16)[name = string("input_103_cast_fp16")];
524
+ tensor<int32, [6]> input_105_pad_0 = const()[name = string("input_105_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
525
+ string input_105_mode_0 = const()[name = string("input_105_mode_0"), val = string("constant")];
526
+ fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
527
+ tensor<fp16, [1, 96, 15414]> input_105_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_105_mode_0, pad = input_105_pad_0, x = input_103_cast_fp16)[name = string("input_105_cast_fp16")];
528
+ string x_65_pad_type_0 = const()[name = string("x_65_pad_type_0"), val = string("valid")];
529
+ tensor<int32, [1]> x_65_dilations_0 = const()[name = string("x_65_dilations_0"), val = tensor<int32, [1]>([9])];
530
+ int32 x_65_groups_0 = const()[name = string("x_65_groups_0"), val = int32(96)];
531
+ tensor<int32, [1]> x_65_strides_0 = const()[name = string("x_65_strides_0"), val = tensor<int32, [1]>([1])];
532
+ tensor<int32, [2]> x_65_pad_0 = const()[name = string("x_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
533
+ tensor<fp16, [96, 1, 7]> weight_49_to_fp16 = const()[name = string("weight_49_to_fp16"), val = tensor<fp16, [96, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53822080)))];
534
+ tensor<fp16, [96]> model_5_block_4_block_1_bias_to_fp16 = const()[name = string("model_5_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53823488)))];
535
+ tensor<fp16, [1, 96, 15360]> x_65_cast_fp16 = conv(bias = model_5_block_4_block_1_bias_to_fp16, dilations = x_65_dilations_0, groups = x_65_groups_0, pad = x_65_pad_0, pad_type = x_65_pad_type_0, strides = x_65_strides_0, weight = weight_49_to_fp16, x = input_105_cast_fp16)[name = string("x_65_cast_fp16")];
536
+ tensor<fp16, [1, 96, 1]> model_5_block_4_block_2_alpha_to_fp16 = const()[name = string("model_5_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53823744)))];
537
+ tensor<fp16, [1, 96, 15360]> var_756_cast_fp16 = mul(x = model_5_block_4_block_2_alpha_to_fp16, y = x_65_cast_fp16)[name = string("op_756_cast_fp16")];
538
+ tensor<fp16, [1, 96, 15360]> var_757_cast_fp16 = sin(x = var_756_cast_fp16)[name = string("op_757_cast_fp16")];
539
+ fp16 var_16_promoted_27_to_fp16 = const()[name = string("op_16_promoted_27_to_fp16"), val = fp16(0x1p+1)];
540
+ tensor<fp16, [1, 96, 15360]> var_758_cast_fp16 = pow(x = var_757_cast_fp16, y = var_16_promoted_27_to_fp16)[name = string("op_758_cast_fp16")];
541
+ tensor<fp16, [1, 96, 1]> var_755_to_fp16 = const()[name = string("op_755_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53824000)))];
542
+ tensor<fp16, [1, 96, 15360]> var_759_cast_fp16 = mul(x = var_755_to_fp16, y = var_758_cast_fp16)[name = string("op_759_cast_fp16")];
543
+ tensor<fp16, [1, 96, 15360]> input_107_cast_fp16 = add(x = x_65_cast_fp16, y = var_759_cast_fp16)[name = string("input_107_cast_fp16")];
544
+ string y_pad_type_0 = const()[name = string("y_pad_type_0"), val = string("valid")];
545
+ tensor<int32, [1]> y_strides_0 = const()[name = string("y_strides_0"), val = tensor<int32, [1]>([1])];
546
+ tensor<int32, [2]> y_pad_0 = const()[name = string("y_pad_0"), val = tensor<int32, [2]>([0, 0])];
547
+ tensor<int32, [1]> y_dilations_0 = const()[name = string("y_dilations_0"), val = tensor<int32, [1]>([1])];
548
+ int32 y_groups_0 = const()[name = string("y_groups_0"), val = int32(1)];
549
+ tensor<fp16, [96, 96, 1]> weight_51_to_fp16 = const()[name = string("weight_51_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53824256)))];
550
+ tensor<fp16, [96]> model_5_block_4_block_3_bias_to_fp16 = const()[name = string("model_5_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53842752)))];
551
+ tensor<fp16, [1, 96, 15360]> y_cast_fp16 = conv(bias = model_5_block_4_block_3_bias_to_fp16, dilations = y_dilations_0, groups = y_groups_0, pad = y_pad_0, pad_type = y_pad_type_0, strides = y_strides_0, weight = weight_51_to_fp16, x = input_107_cast_fp16)[name = string("y_cast_fp16")];
552
+ tensor<fp16, [1, 96, 15360]> x_cast_fp16 = add(x = x_63_cast_fp16, y = y_cast_fp16)[name = string("x_cast_fp16")];
553
+ tensor<fp16, [1, 96, 1]> model_6_alpha_to_fp16 = const()[name = string("model_6_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53843008)))];
554
+ tensor<fp16, [1, 96, 15360]> var_775_cast_fp16 = mul(x = model_6_alpha_to_fp16, y = x_cast_fp16)[name = string("op_775_cast_fp16")];
555
+ tensor<fp16, [1, 96, 15360]> var_776_cast_fp16 = sin(x = var_775_cast_fp16)[name = string("op_776_cast_fp16")];
556
+ fp16 var_16_promoted_28_to_fp16 = const()[name = string("op_16_promoted_28_to_fp16"), val = fp16(0x1p+1)];
557
+ tensor<fp16, [1, 96, 15360]> var_777_cast_fp16 = pow(x = var_776_cast_fp16, y = var_16_promoted_28_to_fp16)[name = string("op_777_cast_fp16")];
558
+ tensor<fp16, [1, 96, 1]> var_774_to_fp16 = const()[name = string("op_774_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53843264)))];
559
+ tensor<fp16, [1, 96, 15360]> var_778_cast_fp16 = mul(x = var_774_to_fp16, y = var_777_cast_fp16)[name = string("op_778_cast_fp16")];
560
+ tensor<fp16, [1, 96, 15360]> input_111_cast_fp16 = add(x = x_cast_fp16, y = var_778_cast_fp16)[name = string("input_111_cast_fp16")];
561
+ tensor<int32, [6]> input_113_pad_0 = const()[name = string("input_113_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
562
+ string input_113_mode_0 = const()[name = string("input_113_mode_0"), val = string("constant")];
563
+ fp16 const_26_to_fp16 = const()[name = string("const_26_to_fp16"), val = fp16(0x0p+0)];
564
+ tensor<fp16, [1, 96, 15366]> input_113_cast_fp16 = pad(constant_val = const_26_to_fp16, mode = input_113_mode_0, pad = input_113_pad_0, x = input_111_cast_fp16)[name = string("input_113_cast_fp16")];
565
+ string input_pad_type_0 = const()[name = string("input_pad_type_0"), val = string("valid")];
566
+ tensor<int32, [1]> input_strides_0 = const()[name = string("input_strides_0"), val = tensor<int32, [1]>([1])];
567
+ tensor<int32, [2]> input_pad_0 = const()[name = string("input_pad_0"), val = tensor<int32, [2]>([0, 0])];
568
+ tensor<int32, [1]> input_dilations_0 = const()[name = string("input_dilations_0"), val = tensor<int32, [1]>([1])];
569
+ int32 input_groups_0 = const()[name = string("input_groups_0"), val = int32(1)];
570
+ tensor<fp16, [1, 96, 7]> weight_to_fp16 = const()[name = string("weight_to_fp16"), val = tensor<fp16, [1, 96, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53843520)))];
571
+ tensor<fp16, [1]> model_7_bias_to_fp16 = const()[name = string("model_7_bias_to_fp16"), val = tensor<fp16, [1]>([0x1.108p-13])];
572
+ tensor<fp16, [1, 1, 15360]> input_cast_fp16 = conv(bias = model_7_bias_to_fp16, dilations = input_dilations_0, groups = input_groups_0, pad = input_pad_0, pad_type = input_pad_type_0, strides = input_strides_0, weight = weight_to_fp16, x = input_113_cast_fp16)[name = string("input_cast_fp16")];
573
+ tensor<fp16, [1, 1, 15360]> decoded_audio = tanh(x = input_cast_fp16)[name = string("op_789_cast_fp16")];
574
+ } -> (decoded_audio);
575
+ }
voxcpm_audio_vae_decoder_length_24.mlmodelc/weights/weight.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:f4c428d78f8e055ef6c6ef7d80234fcce4acb0deb2d1975bc3c044c23218f33d
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+ size 53844928