Hugging Face's logo

seba
/
VoxCPM-ANE

Text-to-Speech
English
CoreML
Model card Files
xet
 Community
seba commited on
Commit
7286520
·
verified ·
1 Parent(s): 3077a55

Upload folder using huggingface_hub

Browse files
Files changed (4) hide show
  1. voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/analytics/coremldata.bin +3 -0
  2. voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/coremldata.bin +3 -0
  3. voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/model.mil +554 -0
  4. voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/weights/weight.bin +3 -0
voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/analytics/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c2c2b0b8a5c0ddd35a003c5da5687132e7fb60d1de6706f75971fe16939ccd76
3
+ size 243
voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0f56ee14b885d16cbb26737f055d3157a66d5d3a2d13f13b5e7fe7bc1f7e3f4d
3
+ size 285
voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/model.mil ADDED
@@ -0,0 +1,554 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ program(1.3)
2
+ [buildInfo = dict<string, string>({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3405.2.1"}})]
3
+ {
4
+ func main<ios18>(tensor<fp16, [1, 1, ?]> x) [FlexibleShapeInformation = tuple<tuple<string, dict<string, tensor<int32, [?]>>>, tuple<string, dict<string, dict<string, tensor<int32, [?]>>>>>((("DefaultShapes", {{"x", [1, 1, 17920]}}), ("EnumeratedShapes", {{"21ddf14a", {{"x", [1, 1, 38400]}}}, {"46cafac7", {{"x", [1, 1, 20480]}}}, {"4daf687d", {{"x", [1, 1, 23040]}}}, {"613e9f61", {{"x", [1, 1, 33280]}}}, {"72f4a7b6", {{"x", [1, 1, 30720]}}}, {"76776988", {{"x", [1, 1, 17920]}}}, {"7e3de538", {{"x", [1, 1, 40960]}}}, {"85be4c9b", {{"x", [1, 1, 28160]}}}, {"96f2e361", {{"x", [1, 1, 15360]}}}, {"9ef27b02", {{"x", [1, 1, 12800]}}}, {"a7dde9f1", {{"x", [1, 1, 35840]}}}, {"b6d84956", {{"x", [1, 1, 7680]}}}, {"da13dc07", {{"x", [1, 1, 5120]}}}, {"e994de2a", {{"x", [1, 1, 2560]}}}, {"f0a51cc3", {{"x", [1, 1, 25600]}}}, {"f2441bf6", {{"x", [1, 1, 10240]}}}})))] {
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, 1, ?]> input_1_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_1_mode_0, pad = input_1_pad_0, x = x)[name = string("input_1_cast_fp16")];
9
+ string x_3_pad_type_0 = const()[name = string("x_3_pad_type_0"), val = string("valid")];
10
+ tensor<int32, [1]> x_3_strides_0 = const()[name = string("x_3_strides_0"), val = tensor<int32, [1]>([1])];
11
+ tensor<int32, [2]> x_3_pad_0 = const()[name = string("x_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
12
+ tensor<int32, [1]> x_3_dilations_0 = const()[name = string("x_3_dilations_0"), val = tensor<int32, [1]>([1])];
13
+ int32 x_3_groups_0 = const()[name = string("x_3_groups_0"), val = int32(1)];
14
+ tensor<fp16, [128, 1, 7]> weight_1_to_fp16 = const()[name = string("weight_1_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
15
+ tensor<fp16, [128]> block_0_bias_to_fp16 = const()[name = string("block_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1920)))];
16
+ tensor<fp16, [1, 128, ?]> x_3_cast_fp16 = conv(bias = block_0_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_1_to_fp16, x = input_1_cast_fp16)[name = string("x_3_cast_fp16")];
17
+ tensor<fp16, [1, 128, 1]> block_1_block_0_block_0_alpha_to_fp16 = const()[name = string("block_1_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2240)))];
18
+ tensor<fp16, [1, 128, ?]> var_71_cast_fp16 = mul(x = block_1_block_0_block_0_alpha_to_fp16, y = x_3_cast_fp16)[name = string("op_71_cast_fp16")];
19
+ tensor<fp16, [1, 128, ?]> var_72_cast_fp16 = sin(x = var_71_cast_fp16)[name = string("op_72_cast_fp16")];
20
+ fp16 var_18_promoted_to_fp16 = const()[name = string("op_18_promoted_to_fp16"), val = fp16(0x1p+1)];
21
+ tensor<fp16, [1, 128, ?]> var_73_cast_fp16 = pow(x = var_72_cast_fp16, y = var_18_promoted_to_fp16)[name = string("op_73_cast_fp16")];
22
+ tensor<fp16, [1, 128, 1]> var_70_to_fp16 = const()[name = string("op_70_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2560)))];
23
+ tensor<fp16, [1, 128, ?]> var_74_cast_fp16 = mul(x = var_70_to_fp16, y = var_73_cast_fp16)[name = string("op_74_cast_fp16")];
24
+ tensor<fp16, [1, 128, ?]> input_3_cast_fp16 = add(x = x_3_cast_fp16, y = var_74_cast_fp16)[name = string("input_3_cast_fp16")];
25
+ tensor<int32, [6]> input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
26
+ string input_5_mode_0 = const()[name = string("input_5_mode_0"), val = string("constant")];
27
+ fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
28
+ tensor<fp16, [1, 128, ?]> input_5_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_5_mode_0, pad = input_5_pad_0, x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
29
+ string x_5_pad_type_0 = const()[name = string("x_5_pad_type_0"), val = string("valid")];
30
+ int32 x_5_groups_0 = const()[name = string("x_5_groups_0"), val = int32(128)];
31
+ tensor<int32, [1]> x_5_strides_0 = const()[name = string("x_5_strides_0"), val = tensor<int32, [1]>([1])];
32
+ tensor<int32, [2]> x_5_pad_0 = const()[name = string("x_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
33
+ tensor<int32, [1]> x_5_dilations_0 = const()[name = string("x_5_dilations_0"), val = tensor<int32, [1]>([1])];
34
+ tensor<fp16, [128, 1, 7]> weight_3_to_fp16 = const()[name = string("weight_3_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2880)))];
35
+ tensor<fp16, [128]> block_1_block_0_block_1_bias_to_fp16 = const()[name = string("block_1_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736)))];
36
+ tensor<fp16, [1, 128, ?]> x_5_cast_fp16 = conv(bias = block_1_block_0_block_1_bias_to_fp16, dilations = x_5_dilations_0, groups = x_5_groups_0, pad = x_5_pad_0, pad_type = x_5_pad_type_0, strides = x_5_strides_0, weight = weight_3_to_fp16, x = input_5_cast_fp16)[name = string("x_5_cast_fp16")];
37
+ tensor<fp16, [1, 128, 1]> block_1_block_0_block_2_alpha_to_fp16 = const()[name = string("block_1_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5056)))];
38
+ tensor<fp16, [1, 128, ?]> var_89_cast_fp16 = mul(x = block_1_block_0_block_2_alpha_to_fp16, y = x_5_cast_fp16)[name = string("op_89_cast_fp16")];
39
+ tensor<fp16, [1, 128, ?]> var_90_cast_fp16 = sin(x = var_89_cast_fp16)[name = string("op_90_cast_fp16")];
40
+ fp16 var_18_promoted_1_to_fp16 = const()[name = string("op_18_promoted_1_to_fp16"), val = fp16(0x1p+1)];
41
+ tensor<fp16, [1, 128, ?]> var_91_cast_fp16 = pow(x = var_90_cast_fp16, y = var_18_promoted_1_to_fp16)[name = string("op_91_cast_fp16")];
42
+ tensor<fp16, [1, 128, 1]> var_88_to_fp16 = const()[name = string("op_88_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5376)))];
43
+ tensor<fp16, [1, 128, ?]> var_92_cast_fp16 = mul(x = var_88_to_fp16, y = var_91_cast_fp16)[name = string("op_92_cast_fp16")];
44
+ tensor<fp16, [1, 128, ?]> input_7_cast_fp16 = add(x = x_5_cast_fp16, y = var_92_cast_fp16)[name = string("input_7_cast_fp16")];
45
+ string y_1_pad_type_0 = const()[name = string("y_1_pad_type_0"), val = string("valid")];
46
+ tensor<int32, [1]> y_1_strides_0 = const()[name = string("y_1_strides_0"), val = tensor<int32, [1]>([1])];
47
+ tensor<int32, [2]> y_1_pad_0 = const()[name = string("y_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
48
+ tensor<int32, [1]> y_1_dilations_0 = const()[name = string("y_1_dilations_0"), val = tensor<int32, [1]>([1])];
49
+ int32 y_1_groups_0 = const()[name = string("y_1_groups_0"), val = int32(1)];
50
+ tensor<fp16, [128, 128, 1]> weight_5_to_fp16 = const()[name = string("weight_5_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5696)))];
51
+ tensor<fp16, [128]> block_1_block_0_block_3_bias_to_fp16 = const()[name = string("block_1_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38528)))];
52
+ tensor<fp16, [1, 128, ?]> y_1_cast_fp16 = conv(bias = block_1_block_0_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_5_to_fp16, x = input_7_cast_fp16)[name = string("y_1_cast_fp16")];
53
+ tensor<fp16, [1, 128, ?]> x_7_cast_fp16 = add(x = x_3_cast_fp16, y = y_1_cast_fp16)[name = string("x_7_cast_fp16")];
54
+ tensor<fp16, [1, 128, 1]> block_1_block_1_block_0_alpha_to_fp16 = const()[name = string("block_1_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38848)))];
55
+ tensor<fp16, [1, 128, ?]> var_121_cast_fp16 = mul(x = block_1_block_1_block_0_alpha_to_fp16, y = x_7_cast_fp16)[name = string("op_121_cast_fp16")];
56
+ tensor<fp16, [1, 128, ?]> var_122_cast_fp16 = sin(x = var_121_cast_fp16)[name = string("op_122_cast_fp16")];
57
+ fp16 var_18_promoted_2_to_fp16 = const()[name = string("op_18_promoted_2_to_fp16"), val = fp16(0x1p+1)];
58
+ tensor<fp16, [1, 128, ?]> var_123_cast_fp16 = pow(x = var_122_cast_fp16, y = var_18_promoted_2_to_fp16)[name = string("op_123_cast_fp16")];
59
+ tensor<fp16, [1, 128, 1]> var_120_to_fp16 = const()[name = string("op_120_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39168)))];
60
+ tensor<fp16, [1, 128, ?]> var_124_cast_fp16 = mul(x = var_120_to_fp16, y = var_123_cast_fp16)[name = string("op_124_cast_fp16")];
61
+ tensor<fp16, [1, 128, ?]> input_11_cast_fp16 = add(x = x_7_cast_fp16, y = var_124_cast_fp16)[name = string("input_11_cast_fp16")];
62
+ tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
63
+ string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("constant")];
64
+ fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
65
+ tensor<fp16, [1, 128, ?]> input_13_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
66
+ string x_9_pad_type_0 = const()[name = string("x_9_pad_type_0"), val = string("valid")];
67
+ tensor<int32, [1]> x_9_dilations_0 = const()[name = string("x_9_dilations_0"), val = tensor<int32, [1]>([3])];
68
+ int32 x_9_groups_0 = const()[name = string("x_9_groups_0"), val = int32(128)];
69
+ tensor<int32, [1]> x_9_strides_0 = const()[name = string("x_9_strides_0"), val = tensor<int32, [1]>([1])];
70
+ tensor<int32, [2]> x_9_pad_0 = const()[name = string("x_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
71
+ tensor<fp16, [128, 1, 7]> weight_7_to_fp16 = const()[name = string("weight_7_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39488)))];
72
+ tensor<fp16, [128]> block_1_block_1_block_1_bias_to_fp16 = const()[name = string("block_1_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41344)))];
73
+ tensor<fp16, [1, 128, ?]> x_9_cast_fp16 = conv(bias = block_1_block_1_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_7_to_fp16, x = input_13_cast_fp16)[name = string("x_9_cast_fp16")];
74
+ tensor<fp16, [1, 128, 1]> block_1_block_1_block_2_alpha_to_fp16 = const()[name = string("block_1_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41664)))];
75
+ tensor<fp16, [1, 128, ?]> var_139_cast_fp16 = mul(x = block_1_block_1_block_2_alpha_to_fp16, y = x_9_cast_fp16)[name = string("op_139_cast_fp16")];
76
+ tensor<fp16, [1, 128, ?]> var_140_cast_fp16 = sin(x = var_139_cast_fp16)[name = string("op_140_cast_fp16")];
77
+ fp16 var_18_promoted_3_to_fp16 = const()[name = string("op_18_promoted_3_to_fp16"), val = fp16(0x1p+1)];
78
+ tensor<fp16, [1, 128, ?]> var_141_cast_fp16 = pow(x = var_140_cast_fp16, y = var_18_promoted_3_to_fp16)[name = string("op_141_cast_fp16")];
79
+ tensor<fp16, [1, 128, 1]> var_138_to_fp16 = const()[name = string("op_138_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41984)))];
80
+ tensor<fp16, [1, 128, ?]> var_142_cast_fp16 = mul(x = var_138_to_fp16, y = var_141_cast_fp16)[name = string("op_142_cast_fp16")];
81
+ tensor<fp16, [1, 128, ?]> input_15_cast_fp16 = add(x = x_9_cast_fp16, y = var_142_cast_fp16)[name = string("input_15_cast_fp16")];
82
+ string y_3_pad_type_0 = const()[name = string("y_3_pad_type_0"), val = string("valid")];
83
+ tensor<int32, [1]> y_3_strides_0 = const()[name = string("y_3_strides_0"), val = tensor<int32, [1]>([1])];
84
+ tensor<int32, [2]> y_3_pad_0 = const()[name = string("y_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
85
+ tensor<int32, [1]> y_3_dilations_0 = const()[name = string("y_3_dilations_0"), val = tensor<int32, [1]>([1])];
86
+ int32 y_3_groups_0 = const()[name = string("y_3_groups_0"), val = int32(1)];
87
+ tensor<fp16, [128, 128, 1]> weight_9_to_fp16 = const()[name = string("weight_9_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(42304)))];
88
+ tensor<fp16, [128]> block_1_block_1_block_3_bias_to_fp16 = const()[name = string("block_1_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75136)))];
89
+ tensor<fp16, [1, 128, ?]> y_3_cast_fp16 = conv(bias = block_1_block_1_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_9_to_fp16, x = input_15_cast_fp16)[name = string("y_3_cast_fp16")];
90
+ tensor<fp16, [1, 128, ?]> x_11_cast_fp16 = add(x = x_7_cast_fp16, y = y_3_cast_fp16)[name = string("x_11_cast_fp16")];
91
+ tensor<fp16, [1, 128, 1]> block_1_block_2_block_0_alpha_to_fp16 = const()[name = string("block_1_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75456)))];
92
+ tensor<fp16, [1, 128, ?]> var_171_cast_fp16 = mul(x = block_1_block_2_block_0_alpha_to_fp16, y = x_11_cast_fp16)[name = string("op_171_cast_fp16")];
93
+ tensor<fp16, [1, 128, ?]> var_172_cast_fp16 = sin(x = var_171_cast_fp16)[name = string("op_172_cast_fp16")];
94
+ fp16 var_18_promoted_4_to_fp16 = const()[name = string("op_18_promoted_4_to_fp16"), val = fp16(0x1p+1)];
95
+ tensor<fp16, [1, 128, ?]> var_173_cast_fp16 = pow(x = var_172_cast_fp16, y = var_18_promoted_4_to_fp16)[name = string("op_173_cast_fp16")];
96
+ tensor<fp16, [1, 128, 1]> var_170_to_fp16 = const()[name = string("op_170_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75776)))];
97
+ tensor<fp16, [1, 128, ?]> var_174_cast_fp16 = mul(x = var_170_to_fp16, y = var_173_cast_fp16)[name = string("op_174_cast_fp16")];
98
+ tensor<fp16, [1, 128, ?]> input_19_cast_fp16 = add(x = x_11_cast_fp16, y = var_174_cast_fp16)[name = string("input_19_cast_fp16")];
99
+ tensor<int32, [6]> input_21_pad_0 = const()[name = string("input_21_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
100
+ string input_21_mode_0 = const()[name = string("input_21_mode_0"), val = string("constant")];
101
+ fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
102
+ tensor<fp16, [1, 128, ?]> input_21_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_21_mode_0, pad = input_21_pad_0, x = input_19_cast_fp16)[name = string("input_21_cast_fp16")];
103
+ string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("valid")];
104
+ tensor<int32, [1]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [1]>([9])];
105
+ int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(128)];
106
+ tensor<int32, [1]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [1]>([1])];
107
+ tensor<int32, [2]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
108
+ tensor<fp16, [128, 1, 7]> weight_11_to_fp16 = const()[name = string("weight_11_to_fp16"), val = tensor<fp16, [128, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76096)))];
109
+ tensor<fp16, [128]> block_1_block_2_block_1_bias_to_fp16 = const()[name = string("block_1_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77952)))];
110
+ tensor<fp16, [1, 128, ?]> x_13_cast_fp16 = conv(bias = block_1_block_2_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_11_to_fp16, x = input_21_cast_fp16)[name = string("x_13_cast_fp16")];
111
+ tensor<fp16, [1, 128, 1]> block_1_block_2_block_2_alpha_to_fp16 = const()[name = string("block_1_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78272)))];
112
+ tensor<fp16, [1, 128, ?]> var_189_cast_fp16 = mul(x = block_1_block_2_block_2_alpha_to_fp16, y = x_13_cast_fp16)[name = string("op_189_cast_fp16")];
113
+ tensor<fp16, [1, 128, ?]> var_190_cast_fp16 = sin(x = var_189_cast_fp16)[name = string("op_190_cast_fp16")];
114
+ fp16 var_18_promoted_5_to_fp16 = const()[name = string("op_18_promoted_5_to_fp16"), val = fp16(0x1p+1)];
115
+ tensor<fp16, [1, 128, ?]> var_191_cast_fp16 = pow(x = var_190_cast_fp16, y = var_18_promoted_5_to_fp16)[name = string("op_191_cast_fp16")];
116
+ tensor<fp16, [1, 128, 1]> var_188_to_fp16 = const()[name = string("op_188_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78592)))];
117
+ tensor<fp16, [1, 128, ?]> var_192_cast_fp16 = mul(x = var_188_to_fp16, y = var_191_cast_fp16)[name = string("op_192_cast_fp16")];
118
+ tensor<fp16, [1, 128, ?]> input_23_cast_fp16 = add(x = x_13_cast_fp16, y = var_192_cast_fp16)[name = string("input_23_cast_fp16")];
119
+ string y_5_pad_type_0 = const()[name = string("y_5_pad_type_0"), val = string("valid")];
120
+ tensor<int32, [1]> y_5_strides_0 = const()[name = string("y_5_strides_0"), val = tensor<int32, [1]>([1])];
121
+ tensor<int32, [2]> y_5_pad_0 = const()[name = string("y_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
122
+ tensor<int32, [1]> y_5_dilations_0 = const()[name = string("y_5_dilations_0"), val = tensor<int32, [1]>([1])];
123
+ int32 y_5_groups_0 = const()[name = string("y_5_groups_0"), val = int32(1)];
124
+ tensor<fp16, [128, 128, 1]> weight_13_to_fp16 = const()[name = string("weight_13_to_fp16"), val = tensor<fp16, [128, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78912)))];
125
+ tensor<fp16, [128]> block_1_block_2_block_3_bias_to_fp16 = const()[name = string("block_1_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111744)))];
126
+ tensor<fp16, [1, 128, ?]> y_5_cast_fp16 = conv(bias = block_1_block_2_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_13_to_fp16, x = input_23_cast_fp16)[name = string("y_5_cast_fp16")];
127
+ tensor<fp16, [1, 128, ?]> x_15_cast_fp16 = add(x = x_11_cast_fp16, y = y_5_cast_fp16)[name = string("x_15_cast_fp16")];
128
+ tensor<fp16, [1, 128, 1]> block_1_block_3_alpha_to_fp16 = const()[name = string("block_1_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(112064)))];
129
+ tensor<fp16, [1, 128, ?]> var_208_cast_fp16 = mul(x = block_1_block_3_alpha_to_fp16, y = x_15_cast_fp16)[name = string("op_208_cast_fp16")];
130
+ tensor<fp16, [1, 128, ?]> var_209_cast_fp16 = sin(x = var_208_cast_fp16)[name = string("op_209_cast_fp16")];
131
+ fp16 var_18_promoted_6_to_fp16 = const()[name = string("op_18_promoted_6_to_fp16"), val = fp16(0x1p+1)];
132
+ tensor<fp16, [1, 128, ?]> var_210_cast_fp16 = pow(x = var_209_cast_fp16, y = var_18_promoted_6_to_fp16)[name = string("op_210_cast_fp16")];
133
+ tensor<fp16, [1, 128, 1]> var_207_to_fp16 = const()[name = string("op_207_to_fp16"), val = tensor<fp16, [1, 128, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(112384)))];
134
+ tensor<fp16, [1, 128, ?]> var_211_cast_fp16 = mul(x = var_207_to_fp16, y = var_210_cast_fp16)[name = string("op_211_cast_fp16")];
135
+ tensor<fp16, [1, 128, ?]> input_27_cast_fp16 = add(x = x_15_cast_fp16, y = var_211_cast_fp16)[name = string("input_27_cast_fp16")];
136
+ tensor<int32, [6]> input_29_pad_0 = const()[name = string("input_29_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
137
+ string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("constant")];
138
+ fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(0x0p+0)];
139
+ tensor<fp16, [1, 128, ?]> input_29_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = input_29_mode_0, pad = input_29_pad_0, x = input_27_cast_fp16)[name = string("input_29_cast_fp16")];
140
+ string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
141
+ tensor<int32, [1]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [1]>([2])];
142
+ tensor<int32, [2]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
143
+ tensor<int32, [1]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [1]>([1])];
144
+ int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(1)];
145
+ tensor<fp16, [256, 128, 4]> weight_15_to_fp16 = const()[name = string("weight_15_to_fp16"), val = tensor<fp16, [256, 128, 4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(112704)))];
146
+ tensor<fp16, [256]> block_1_block_4_bias_to_fp16 = const()[name = string("block_1_block_4_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374912)))];
147
+ tensor<fp16, [1, 256, ?]> x_17_cast_fp16 = conv(bias = block_1_block_4_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_15_to_fp16, x = input_29_cast_fp16)[name = string("x_17_cast_fp16")];
148
+ tensor<fp16, [1, 256, 1]> block_2_block_0_block_0_alpha_to_fp16 = const()[name = string("block_2_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(375488)))];
149
+ tensor<fp16, [1, 256, ?]> var_249_cast_fp16 = mul(x = block_2_block_0_block_0_alpha_to_fp16, y = x_17_cast_fp16)[name = string("op_249_cast_fp16")];
150
+ tensor<fp16, [1, 256, ?]> var_250_cast_fp16 = sin(x = var_249_cast_fp16)[name = string("op_250_cast_fp16")];
151
+ fp16 var_18_promoted_7_to_fp16 = const()[name = string("op_18_promoted_7_to_fp16"), val = fp16(0x1p+1)];
152
+ tensor<fp16, [1, 256, ?]> var_251_cast_fp16 = pow(x = var_250_cast_fp16, y = var_18_promoted_7_to_fp16)[name = string("op_251_cast_fp16")];
153
+ tensor<fp16, [1, 256, 1]> var_248_to_fp16 = const()[name = string("op_248_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376064)))];
154
+ tensor<fp16, [1, 256, ?]> var_252_cast_fp16 = mul(x = var_248_to_fp16, y = var_251_cast_fp16)[name = string("op_252_cast_fp16")];
155
+ tensor<fp16, [1, 256, ?]> input_31_cast_fp16 = add(x = x_17_cast_fp16, y = var_252_cast_fp16)[name = string("input_31_cast_fp16")];
156
+ tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
157
+ string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("constant")];
158
+ fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
159
+ tensor<fp16, [1, 256, ?]> input_33_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
160
+ string x_19_pad_type_0 = const()[name = string("x_19_pad_type_0"), val = string("valid")];
161
+ int32 x_19_groups_0 = const()[name = string("x_19_groups_0"), val = int32(256)];
162
+ tensor<int32, [1]> x_19_strides_0 = const()[name = string("x_19_strides_0"), val = tensor<int32, [1]>([1])];
163
+ tensor<int32, [2]> x_19_pad_0 = const()[name = string("x_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
164
+ tensor<int32, [1]> x_19_dilations_0 = const()[name = string("x_19_dilations_0"), val = tensor<int32, [1]>([1])];
165
+ tensor<fp16, [256, 1, 7]> weight_17_to_fp16 = const()[name = string("weight_17_to_fp16"), val = tensor<fp16, [256, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
166
+ tensor<fp16, [256]> block_2_block_0_block_1_bias_to_fp16 = const()[name = string("block_2_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(380288)))];
167
+ tensor<fp16, [1, 256, ?]> x_19_cast_fp16 = conv(bias = block_2_block_0_block_1_bias_to_fp16, dilations = x_19_dilations_0, groups = x_19_groups_0, pad = x_19_pad_0, pad_type = x_19_pad_type_0, strides = x_19_strides_0, weight = weight_17_to_fp16, x = input_33_cast_fp16)[name = string("x_19_cast_fp16")];
168
+ tensor<fp16, [1, 256, 1]> block_2_block_0_block_2_alpha_to_fp16 = const()[name = string("block_2_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(380864)))];
169
+ tensor<fp16, [1, 256, ?]> var_267_cast_fp16 = mul(x = block_2_block_0_block_2_alpha_to_fp16, y = x_19_cast_fp16)[name = string("op_267_cast_fp16")];
170
+ tensor<fp16, [1, 256, ?]> var_268_cast_fp16 = sin(x = var_267_cast_fp16)[name = string("op_268_cast_fp16")];
171
+ fp16 var_18_promoted_8_to_fp16 = const()[name = string("op_18_promoted_8_to_fp16"), val = fp16(0x1p+1)];
172
+ tensor<fp16, [1, 256, ?]> var_269_cast_fp16 = pow(x = var_268_cast_fp16, y = var_18_promoted_8_to_fp16)[name = string("op_269_cast_fp16")];
173
+ tensor<fp16, [1, 256, 1]> var_266_to_fp16 = const()[name = string("op_266_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(381440)))];
174
+ tensor<fp16, [1, 256, ?]> var_270_cast_fp16 = mul(x = var_266_to_fp16, y = var_269_cast_fp16)[name = string("op_270_cast_fp16")];
175
+ tensor<fp16, [1, 256, ?]> input_35_cast_fp16 = add(x = x_19_cast_fp16, y = var_270_cast_fp16)[name = string("input_35_cast_fp16")];
176
+ string y_7_pad_type_0 = const()[name = string("y_7_pad_type_0"), val = string("valid")];
177
+ tensor<int32, [1]> y_7_strides_0 = const()[name = string("y_7_strides_0"), val = tensor<int32, [1]>([1])];
178
+ tensor<int32, [2]> y_7_pad_0 = const()[name = string("y_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
179
+ tensor<int32, [1]> y_7_dilations_0 = const()[name = string("y_7_dilations_0"), val = tensor<int32, [1]>([1])];
180
+ int32 y_7_groups_0 = const()[name = string("y_7_groups_0"), val = int32(1)];
181
+ tensor<fp16, [256, 256, 1]> weight_19_to_fp16 = const()[name = string("weight_19_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(382016)))];
182
+ tensor<fp16, [256]> block_2_block_0_block_3_bias_to_fp16 = const()[name = string("block_2_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(513152)))];
183
+ tensor<fp16, [1, 256, ?]> y_7_cast_fp16 = conv(bias = block_2_block_0_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_35_cast_fp16)[name = string("y_7_cast_fp16")];
184
+ tensor<fp16, [1, 256, ?]> x_21_cast_fp16 = add(x = x_17_cast_fp16, y = y_7_cast_fp16)[name = string("x_21_cast_fp16")];
185
+ tensor<fp16, [1, 256, 1]> block_2_block_1_block_0_alpha_to_fp16 = const()[name = string("block_2_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(513728)))];
186
+ tensor<fp16, [1, 256, ?]> var_299_cast_fp16 = mul(x = block_2_block_1_block_0_alpha_to_fp16, y = x_21_cast_fp16)[name = string("op_299_cast_fp16")];
187
+ tensor<fp16, [1, 256, ?]> var_300_cast_fp16 = sin(x = var_299_cast_fp16)[name = string("op_300_cast_fp16")];
188
+ fp16 var_18_promoted_9_to_fp16 = const()[name = string("op_18_promoted_9_to_fp16"), val = fp16(0x1p+1)];
189
+ tensor<fp16, [1, 256, ?]> var_301_cast_fp16 = pow(x = var_300_cast_fp16, y = var_18_promoted_9_to_fp16)[name = string("op_301_cast_fp16")];
190
+ tensor<fp16, [1, 256, 1]> var_298_to_fp16 = const()[name = string("op_298_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(514304)))];
191
+ tensor<fp16, [1, 256, ?]> var_302_cast_fp16 = mul(x = var_298_to_fp16, y = var_301_cast_fp16)[name = string("op_302_cast_fp16")];
192
+ tensor<fp16, [1, 256, ?]> input_39_cast_fp16 = add(x = x_21_cast_fp16, y = var_302_cast_fp16)[name = string("input_39_cast_fp16")];
193
+ tensor<int32, [6]> input_41_pad_0 = const()[name = string("input_41_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
194
+ string input_41_mode_0 = const()[name = string("input_41_mode_0"), val = string("constant")];
195
+ fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
196
+ tensor<fp16, [1, 256, ?]> input_41_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_41_mode_0, pad = input_41_pad_0, x = input_39_cast_fp16)[name = string("input_41_cast_fp16")];
197
+ string x_23_pad_type_0 = const()[name = string("x_23_pad_type_0"), val = string("valid")];
198
+ tensor<int32, [1]> x_23_dilations_0 = const()[name = string("x_23_dilations_0"), val = tensor<int32, [1]>([3])];
199
+ int32 x_23_groups_0 = const()[name = string("x_23_groups_0"), val = int32(256)];
200
+ tensor<int32, [1]> x_23_strides_0 = const()[name = string("x_23_strides_0"), val = tensor<int32, [1]>([1])];
201
+ tensor<int32, [2]> x_23_pad_0 = const()[name = string("x_23_pad_0"), val = tensor<int32, [2]>([0, 0])];
202
+ tensor<fp16, [256, 1, 7]> weight_21_to_fp16 = const()[name = string("weight_21_to_fp16"), val = tensor<fp16, [256, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(514880)))];
203
+ tensor<fp16, [256]> block_2_block_1_block_1_bias_to_fp16 = const()[name = string("block_2_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(518528)))];
204
+ tensor<fp16, [1, 256, ?]> x_23_cast_fp16 = conv(bias = block_2_block_1_block_1_bias_to_fp16, dilations = x_23_dilations_0, groups = x_23_groups_0, pad = x_23_pad_0, pad_type = x_23_pad_type_0, strides = x_23_strides_0, weight = weight_21_to_fp16, x = input_41_cast_fp16)[name = string("x_23_cast_fp16")];
205
+ tensor<fp16, [1, 256, 1]> block_2_block_1_block_2_alpha_to_fp16 = const()[name = string("block_2_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(519104)))];
206
+ tensor<fp16, [1, 256, ?]> var_317_cast_fp16 = mul(x = block_2_block_1_block_2_alpha_to_fp16, y = x_23_cast_fp16)[name = string("op_317_cast_fp16")];
207
+ tensor<fp16, [1, 256, ?]> var_318_cast_fp16 = sin(x = var_317_cast_fp16)[name = string("op_318_cast_fp16")];
208
+ fp16 var_18_promoted_10_to_fp16 = const()[name = string("op_18_promoted_10_to_fp16"), val = fp16(0x1p+1)];
209
+ tensor<fp16, [1, 256, ?]> var_319_cast_fp16 = pow(x = var_318_cast_fp16, y = var_18_promoted_10_to_fp16)[name = string("op_319_cast_fp16")];
210
+ tensor<fp16, [1, 256, 1]> var_316_to_fp16 = const()[name = string("op_316_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(519680)))];
211
+ tensor<fp16, [1, 256, ?]> var_320_cast_fp16 = mul(x = var_316_to_fp16, y = var_319_cast_fp16)[name = string("op_320_cast_fp16")];
212
+ tensor<fp16, [1, 256, ?]> input_43_cast_fp16 = add(x = x_23_cast_fp16, y = var_320_cast_fp16)[name = string("input_43_cast_fp16")];
213
+ string y_9_pad_type_0 = const()[name = string("y_9_pad_type_0"), val = string("valid")];
214
+ tensor<int32, [1]> y_9_strides_0 = const()[name = string("y_9_strides_0"), val = tensor<int32, [1]>([1])];
215
+ tensor<int32, [2]> y_9_pad_0 = const()[name = string("y_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
216
+ tensor<int32, [1]> y_9_dilations_0 = const()[name = string("y_9_dilations_0"), val = tensor<int32, [1]>([1])];
217
+ int32 y_9_groups_0 = const()[name = string("y_9_groups_0"), val = int32(1)];
218
+ tensor<fp16, [256, 256, 1]> weight_23_to_fp16 = const()[name = string("weight_23_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(520256)))];
219
+ tensor<fp16, [256]> block_2_block_1_block_3_bias_to_fp16 = const()[name = string("block_2_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(651392)))];
220
+ tensor<fp16, [1, 256, ?]> y_9_cast_fp16 = conv(bias = block_2_block_1_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_43_cast_fp16)[name = string("y_9_cast_fp16")];
221
+ tensor<fp16, [1, 256, ?]> x_25_cast_fp16 = add(x = x_21_cast_fp16, y = y_9_cast_fp16)[name = string("x_25_cast_fp16")];
222
+ tensor<fp16, [1, 256, 1]> block_2_block_2_block_0_alpha_to_fp16 = const()[name = string("block_2_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(651968)))];
223
+ tensor<fp16, [1, 256, ?]> var_349_cast_fp16 = mul(x = block_2_block_2_block_0_alpha_to_fp16, y = x_25_cast_fp16)[name = string("op_349_cast_fp16")];
224
+ tensor<fp16, [1, 256, ?]> var_350_cast_fp16 = sin(x = var_349_cast_fp16)[name = string("op_350_cast_fp16")];
225
+ fp16 var_18_promoted_11_to_fp16 = const()[name = string("op_18_promoted_11_to_fp16"), val = fp16(0x1p+1)];
226
+ tensor<fp16, [1, 256, ?]> var_351_cast_fp16 = pow(x = var_350_cast_fp16, y = var_18_promoted_11_to_fp16)[name = string("op_351_cast_fp16")];
227
+ tensor<fp16, [1, 256, 1]> var_348_to_fp16 = const()[name = string("op_348_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(652544)))];
228
+ tensor<fp16, [1, 256, ?]> var_352_cast_fp16 = mul(x = var_348_to_fp16, y = var_351_cast_fp16)[name = string("op_352_cast_fp16")];
229
+ tensor<fp16, [1, 256, ?]> input_47_cast_fp16 = add(x = x_25_cast_fp16, y = var_352_cast_fp16)[name = string("input_47_cast_fp16")];
230
+ tensor<int32, [6]> input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
231
+ string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("constant")];
232
+ fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
233
+ tensor<fp16, [1, 256, ?]> input_49_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_49_mode_0, pad = input_49_pad_0, x = input_47_cast_fp16)[name = string("input_49_cast_fp16")];
234
+ string x_27_pad_type_0 = const()[name = string("x_27_pad_type_0"), val = string("valid")];
235
+ tensor<int32, [1]> x_27_dilations_0 = const()[name = string("x_27_dilations_0"), val = tensor<int32, [1]>([9])];
236
+ int32 x_27_groups_0 = const()[name = string("x_27_groups_0"), val = int32(256)];
237
+ tensor<int32, [1]> x_27_strides_0 = const()[name = string("x_27_strides_0"), val = tensor<int32, [1]>([1])];
238
+ tensor<int32, [2]> x_27_pad_0 = const()[name = string("x_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
239
+ tensor<fp16, [256, 1, 7]> weight_25_to_fp16 = const()[name = string("weight_25_to_fp16"), val = tensor<fp16, [256, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(653120)))];
240
+ tensor<fp16, [256]> block_2_block_2_block_1_bias_to_fp16 = const()[name = string("block_2_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(656768)))];
241
+ tensor<fp16, [1, 256, ?]> x_27_cast_fp16 = conv(bias = block_2_block_2_block_1_bias_to_fp16, dilations = x_27_dilations_0, groups = x_27_groups_0, pad = x_27_pad_0, pad_type = x_27_pad_type_0, strides = x_27_strides_0, weight = weight_25_to_fp16, x = input_49_cast_fp16)[name = string("x_27_cast_fp16")];
242
+ tensor<fp16, [1, 256, 1]> block_2_block_2_block_2_alpha_to_fp16 = const()[name = string("block_2_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657344)))];
243
+ tensor<fp16, [1, 256, ?]> var_367_cast_fp16 = mul(x = block_2_block_2_block_2_alpha_to_fp16, y = x_27_cast_fp16)[name = string("op_367_cast_fp16")];
244
+ tensor<fp16, [1, 256, ?]> var_368_cast_fp16 = sin(x = var_367_cast_fp16)[name = string("op_368_cast_fp16")];
245
+ fp16 var_18_promoted_12_to_fp16 = const()[name = string("op_18_promoted_12_to_fp16"), val = fp16(0x1p+1)];
246
+ tensor<fp16, [1, 256, ?]> var_369_cast_fp16 = pow(x = var_368_cast_fp16, y = var_18_promoted_12_to_fp16)[name = string("op_369_cast_fp16")];
247
+ tensor<fp16, [1, 256, 1]> var_366_to_fp16 = const()[name = string("op_366_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(657920)))];
248
+ tensor<fp16, [1, 256, ?]> var_370_cast_fp16 = mul(x = var_366_to_fp16, y = var_369_cast_fp16)[name = string("op_370_cast_fp16")];
249
+ tensor<fp16, [1, 256, ?]> input_51_cast_fp16 = add(x = x_27_cast_fp16, y = var_370_cast_fp16)[name = string("input_51_cast_fp16")];
250
+ string y_11_pad_type_0 = const()[name = string("y_11_pad_type_0"), val = string("valid")];
251
+ tensor<int32, [1]> y_11_strides_0 = const()[name = string("y_11_strides_0"), val = tensor<int32, [1]>([1])];
252
+ tensor<int32, [2]> y_11_pad_0 = const()[name = string("y_11_pad_0"), val = tensor<int32, [2]>([0, 0])];
253
+ tensor<int32, [1]> y_11_dilations_0 = const()[name = string("y_11_dilations_0"), val = tensor<int32, [1]>([1])];
254
+ int32 y_11_groups_0 = const()[name = string("y_11_groups_0"), val = int32(1)];
255
+ tensor<fp16, [256, 256, 1]> weight_27_to_fp16 = const()[name = string("weight_27_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658496)))];
256
+ tensor<fp16, [256]> block_2_block_2_block_3_bias_to_fp16 = const()[name = string("block_2_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(789632)))];
257
+ tensor<fp16, [1, 256, ?]> y_11_cast_fp16 = conv(bias = block_2_block_2_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_51_cast_fp16)[name = string("y_11_cast_fp16")];
258
+ tensor<fp16, [1, 256, ?]> x_29_cast_fp16 = add(x = x_25_cast_fp16, y = y_11_cast_fp16)[name = string("x_29_cast_fp16")];
259
+ tensor<fp16, [1, 256, 1]> block_2_block_3_alpha_to_fp16 = const()[name = string("block_2_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(790208)))];
260
+ tensor<fp16, [1, 256, ?]> var_386_cast_fp16 = mul(x = block_2_block_3_alpha_to_fp16, y = x_29_cast_fp16)[name = string("op_386_cast_fp16")];
261
+ tensor<fp16, [1, 256, ?]> var_387_cast_fp16 = sin(x = var_386_cast_fp16)[name = string("op_387_cast_fp16")];
262
+ fp16 var_18_promoted_13_to_fp16 = const()[name = string("op_18_promoted_13_to_fp16"), val = fp16(0x1p+1)];
263
+ tensor<fp16, [1, 256, ?]> var_388_cast_fp16 = pow(x = var_387_cast_fp16, y = var_18_promoted_13_to_fp16)[name = string("op_388_cast_fp16")];
264
+ tensor<fp16, [1, 256, 1]> var_385_to_fp16 = const()[name = string("op_385_to_fp16"), val = tensor<fp16, [1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(790784)))];
265
+ tensor<fp16, [1, 256, ?]> var_389_cast_fp16 = mul(x = var_385_to_fp16, y = var_388_cast_fp16)[name = string("op_389_cast_fp16")];
266
+ tensor<fp16, [1, 256, ?]> input_55_cast_fp16 = add(x = x_29_cast_fp16, y = var_389_cast_fp16)[name = string("input_55_cast_fp16")];
267
+ tensor<int32, [6]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
268
+ string input_57_mode_0 = const()[name = string("input_57_mode_0"), val = string("constant")];
269
+ fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
270
+ tensor<fp16, [1, 256, ?]> input_57_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_57_mode_0, pad = input_57_pad_0, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")];
271
+ string x_31_pad_type_0 = const()[name = string("x_31_pad_type_0"), val = string("valid")];
272
+ tensor<int32, [1]> x_31_strides_0 = const()[name = string("x_31_strides_0"), val = tensor<int32, [1]>([5])];
273
+ tensor<int32, [2]> x_31_pad_0 = const()[name = string("x_31_pad_0"), val = tensor<int32, [2]>([0, 0])];
274
+ tensor<int32, [1]> x_31_dilations_0 = const()[name = string("x_31_dilations_0"), val = tensor<int32, [1]>([1])];
275
+ int32 x_31_groups_0 = const()[name = string("x_31_groups_0"), val = int32(1)];
276
+ tensor<fp16, [512, 256, 10]> weight_29_to_fp16 = const()[name = string("weight_29_to_fp16"), val = tensor<fp16, [512, 256, 10]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(791360)))];
277
+ tensor<fp16, [512]> block_2_block_4_bias_to_fp16 = const()[name = string("block_2_block_4_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3412864)))];
278
+ tensor<fp16, [1, 512, ?]> x_31_cast_fp16 = conv(bias = block_2_block_4_bias_to_fp16, dilations = x_31_dilations_0, groups = x_31_groups_0, pad = x_31_pad_0, pad_type = x_31_pad_type_0, strides = x_31_strides_0, weight = weight_29_to_fp16, x = input_57_cast_fp16)[name = string("x_31_cast_fp16")];
279
+ tensor<fp16, [1, 512, 1]> block_3_block_0_block_0_alpha_to_fp16 = const()[name = string("block_3_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3413952)))];
280
+ tensor<fp16, [1, 512, ?]> var_427_cast_fp16 = mul(x = block_3_block_0_block_0_alpha_to_fp16, y = x_31_cast_fp16)[name = string("op_427_cast_fp16")];
281
+ tensor<fp16, [1, 512, ?]> var_428_cast_fp16 = sin(x = var_427_cast_fp16)[name = string("op_428_cast_fp16")];
282
+ fp16 var_18_promoted_14_to_fp16 = const()[name = string("op_18_promoted_14_to_fp16"), val = fp16(0x1p+1)];
283
+ tensor<fp16, [1, 512, ?]> var_429_cast_fp16 = pow(x = var_428_cast_fp16, y = var_18_promoted_14_to_fp16)[name = string("op_429_cast_fp16")];
284
+ tensor<fp16, [1, 512, 1]> var_426_to_fp16 = const()[name = string("op_426_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3415040)))];
285
+ tensor<fp16, [1, 512, ?]> var_430_cast_fp16 = mul(x = var_426_to_fp16, y = var_429_cast_fp16)[name = string("op_430_cast_fp16")];
286
+ tensor<fp16, [1, 512, ?]> input_59_cast_fp16 = add(x = x_31_cast_fp16, y = var_430_cast_fp16)[name = string("input_59_cast_fp16")];
287
+ tensor<int32, [6]> input_61_pad_0 = const()[name = string("input_61_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
288
+ string input_61_mode_0 = const()[name = string("input_61_mode_0"), val = string("constant")];
289
+ fp16 const_15_to_fp16 = const()[name = string("const_15_to_fp16"), val = fp16(0x0p+0)];
290
+ tensor<fp16, [1, 512, ?]> input_61_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = input_61_mode_0, pad = input_61_pad_0, x = input_59_cast_fp16)[name = string("input_61_cast_fp16")];
291
+ string x_33_pad_type_0 = const()[name = string("x_33_pad_type_0"), val = string("valid")];
292
+ int32 x_33_groups_0 = const()[name = string("x_33_groups_0"), val = int32(512)];
293
+ tensor<int32, [1]> x_33_strides_0 = const()[name = string("x_33_strides_0"), val = tensor<int32, [1]>([1])];
294
+ tensor<int32, [2]> x_33_pad_0 = const()[name = string("x_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
295
+ tensor<int32, [1]> x_33_dilations_0 = const()[name = string("x_33_dilations_0"), val = tensor<int32, [1]>([1])];
296
+ tensor<fp16, [512, 1, 7]> weight_31_to_fp16 = const()[name = string("weight_31_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3416128)))];
297
+ tensor<fp16, [512]> block_3_block_0_block_1_bias_to_fp16 = const()[name = string("block_3_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3423360)))];
298
+ tensor<fp16, [1, 512, ?]> x_33_cast_fp16 = conv(bias = block_3_block_0_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_31_to_fp16, x = input_61_cast_fp16)[name = string("x_33_cast_fp16")];
299
+ tensor<fp16, [1, 512, 1]> block_3_block_0_block_2_alpha_to_fp16 = const()[name = string("block_3_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3424448)))];
300
+ tensor<fp16, [1, 512, ?]> var_445_cast_fp16 = mul(x = block_3_block_0_block_2_alpha_to_fp16, y = x_33_cast_fp16)[name = string("op_445_cast_fp16")];
301
+ tensor<fp16, [1, 512, ?]> var_446_cast_fp16 = sin(x = var_445_cast_fp16)[name = string("op_446_cast_fp16")];
302
+ fp16 var_18_promoted_15_to_fp16 = const()[name = string("op_18_promoted_15_to_fp16"), val = fp16(0x1p+1)];
303
+ tensor<fp16, [1, 512, ?]> var_447_cast_fp16 = pow(x = var_446_cast_fp16, y = var_18_promoted_15_to_fp16)[name = string("op_447_cast_fp16")];
304
+ tensor<fp16, [1, 512, 1]> var_444_to_fp16 = const()[name = string("op_444_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3425536)))];
305
+ tensor<fp16, [1, 512, ?]> var_448_cast_fp16 = mul(x = var_444_to_fp16, y = var_447_cast_fp16)[name = string("op_448_cast_fp16")];
306
+ tensor<fp16, [1, 512, ?]> input_63_cast_fp16 = add(x = x_33_cast_fp16, y = var_448_cast_fp16)[name = string("input_63_cast_fp16")];
307
+ string y_13_pad_type_0 = const()[name = string("y_13_pad_type_0"), val = string("valid")];
308
+ tensor<int32, [1]> y_13_strides_0 = const()[name = string("y_13_strides_0"), val = tensor<int32, [1]>([1])];
309
+ tensor<int32, [2]> y_13_pad_0 = const()[name = string("y_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
310
+ tensor<int32, [1]> y_13_dilations_0 = const()[name = string("y_13_dilations_0"), val = tensor<int32, [1]>([1])];
311
+ int32 y_13_groups_0 = const()[name = string("y_13_groups_0"), val = int32(1)];
312
+ tensor<fp16, [512, 512, 1]> weight_33_to_fp16 = const()[name = string("weight_33_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3426624)))];
313
+ tensor<fp16, [512]> block_3_block_0_block_3_bias_to_fp16 = const()[name = string("block_3_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3950976)))];
314
+ tensor<fp16, [1, 512, ?]> y_13_cast_fp16 = conv(bias = block_3_block_0_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_33_to_fp16, x = input_63_cast_fp16)[name = string("y_13_cast_fp16")];
315
+ tensor<fp16, [1, 512, ?]> x_35_cast_fp16 = add(x = x_31_cast_fp16, y = y_13_cast_fp16)[name = string("x_35_cast_fp16")];
316
+ tensor<fp16, [1, 512, 1]> block_3_block_1_block_0_alpha_to_fp16 = const()[name = string("block_3_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952064)))];
317
+ tensor<fp16, [1, 512, ?]> var_477_cast_fp16 = mul(x = block_3_block_1_block_0_alpha_to_fp16, y = x_35_cast_fp16)[name = string("op_477_cast_fp16")];
318
+ tensor<fp16, [1, 512, ?]> var_478_cast_fp16 = sin(x = var_477_cast_fp16)[name = string("op_478_cast_fp16")];
319
+ fp16 var_18_promoted_16_to_fp16 = const()[name = string("op_18_promoted_16_to_fp16"), val = fp16(0x1p+1)];
320
+ tensor<fp16, [1, 512, ?]> var_479_cast_fp16 = pow(x = var_478_cast_fp16, y = var_18_promoted_16_to_fp16)[name = string("op_479_cast_fp16")];
321
+ tensor<fp16, [1, 512, 1]> var_476_to_fp16 = const()[name = string("op_476_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3953152)))];
322
+ tensor<fp16, [1, 512, ?]> var_480_cast_fp16 = mul(x = var_476_to_fp16, y = var_479_cast_fp16)[name = string("op_480_cast_fp16")];
323
+ tensor<fp16, [1, 512, ?]> input_67_cast_fp16 = add(x = x_35_cast_fp16, y = var_480_cast_fp16)[name = string("input_67_cast_fp16")];
324
+ tensor<int32, [6]> input_69_pad_0 = const()[name = string("input_69_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
325
+ string input_69_mode_0 = const()[name = string("input_69_mode_0"), val = string("constant")];
326
+ fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
327
+ tensor<fp16, [1, 512, ?]> input_69_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_69_mode_0, pad = input_69_pad_0, x = input_67_cast_fp16)[name = string("input_69_cast_fp16")];
328
+ string x_37_pad_type_0 = const()[name = string("x_37_pad_type_0"), val = string("valid")];
329
+ tensor<int32, [1]> x_37_dilations_0 = const()[name = string("x_37_dilations_0"), val = tensor<int32, [1]>([3])];
330
+ int32 x_37_groups_0 = const()[name = string("x_37_groups_0"), val = int32(512)];
331
+ tensor<int32, [1]> x_37_strides_0 = const()[name = string("x_37_strides_0"), val = tensor<int32, [1]>([1])];
332
+ tensor<int32, [2]> x_37_pad_0 = const()[name = string("x_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
333
+ tensor<fp16, [512, 1, 7]> weight_35_to_fp16 = const()[name = string("weight_35_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954240)))];
334
+ tensor<fp16, [512]> block_3_block_1_block_1_bias_to_fp16 = const()[name = string("block_3_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3961472)))];
335
+ tensor<fp16, [1, 512, ?]> x_37_cast_fp16 = conv(bias = block_3_block_1_block_1_bias_to_fp16, dilations = x_37_dilations_0, groups = x_37_groups_0, pad = x_37_pad_0, pad_type = x_37_pad_type_0, strides = x_37_strides_0, weight = weight_35_to_fp16, x = input_69_cast_fp16)[name = string("x_37_cast_fp16")];
336
+ tensor<fp16, [1, 512, 1]> block_3_block_1_block_2_alpha_to_fp16 = const()[name = string("block_3_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3962560)))];
337
+ tensor<fp16, [1, 512, ?]> var_495_cast_fp16 = mul(x = block_3_block_1_block_2_alpha_to_fp16, y = x_37_cast_fp16)[name = string("op_495_cast_fp16")];
338
+ tensor<fp16, [1, 512, ?]> var_496_cast_fp16 = sin(x = var_495_cast_fp16)[name = string("op_496_cast_fp16")];
339
+ fp16 var_18_promoted_17_to_fp16 = const()[name = string("op_18_promoted_17_to_fp16"), val = fp16(0x1p+1)];
340
+ tensor<fp16, [1, 512, ?]> var_497_cast_fp16 = pow(x = var_496_cast_fp16, y = var_18_promoted_17_to_fp16)[name = string("op_497_cast_fp16")];
341
+ tensor<fp16, [1, 512, 1]> var_494_to_fp16 = const()[name = string("op_494_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3963648)))];
342
+ tensor<fp16, [1, 512, ?]> var_498_cast_fp16 = mul(x = var_494_to_fp16, y = var_497_cast_fp16)[name = string("op_498_cast_fp16")];
343
+ tensor<fp16, [1, 512, ?]> input_71_cast_fp16 = add(x = x_37_cast_fp16, y = var_498_cast_fp16)[name = string("input_71_cast_fp16")];
344
+ string y_15_pad_type_0 = const()[name = string("y_15_pad_type_0"), val = string("valid")];
345
+ tensor<int32, [1]> y_15_strides_0 = const()[name = string("y_15_strides_0"), val = tensor<int32, [1]>([1])];
346
+ tensor<int32, [2]> y_15_pad_0 = const()[name = string("y_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
347
+ tensor<int32, [1]> y_15_dilations_0 = const()[name = string("y_15_dilations_0"), val = tensor<int32, [1]>([1])];
348
+ int32 y_15_groups_0 = const()[name = string("y_15_groups_0"), val = int32(1)];
349
+ tensor<fp16, [512, 512, 1]> weight_37_to_fp16 = const()[name = string("weight_37_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3964736)))];
350
+ tensor<fp16, [512]> block_3_block_1_block_3_bias_to_fp16 = const()[name = string("block_3_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4489088)))];
351
+ tensor<fp16, [1, 512, ?]> y_15_cast_fp16 = conv(bias = block_3_block_1_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_37_to_fp16, x = input_71_cast_fp16)[name = string("y_15_cast_fp16")];
352
+ tensor<fp16, [1, 512, ?]> x_39_cast_fp16 = add(x = x_35_cast_fp16, y = y_15_cast_fp16)[name = string("x_39_cast_fp16")];
353
+ tensor<fp16, [1, 512, 1]> block_3_block_2_block_0_alpha_to_fp16 = const()[name = string("block_3_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4490176)))];
354
+ tensor<fp16, [1, 512, ?]> var_527_cast_fp16 = mul(x = block_3_block_2_block_0_alpha_to_fp16, y = x_39_cast_fp16)[name = string("op_527_cast_fp16")];
355
+ tensor<fp16, [1, 512, ?]> var_528_cast_fp16 = sin(x = var_527_cast_fp16)[name = string("op_528_cast_fp16")];
356
+ fp16 var_18_promoted_18_to_fp16 = const()[name = string("op_18_promoted_18_to_fp16"), val = fp16(0x1p+1)];
357
+ tensor<fp16, [1, 512, ?]> var_529_cast_fp16 = pow(x = var_528_cast_fp16, y = var_18_promoted_18_to_fp16)[name = string("op_529_cast_fp16")];
358
+ tensor<fp16, [1, 512, 1]> var_526_to_fp16 = const()[name = string("op_526_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4491264)))];
359
+ tensor<fp16, [1, 512, ?]> var_530_cast_fp16 = mul(x = var_526_to_fp16, y = var_529_cast_fp16)[name = string("op_530_cast_fp16")];
360
+ tensor<fp16, [1, 512, ?]> input_75_cast_fp16 = add(x = x_39_cast_fp16, y = var_530_cast_fp16)[name = string("input_75_cast_fp16")];
361
+ tensor<int32, [6]> input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
362
+ string input_77_mode_0 = const()[name = string("input_77_mode_0"), val = string("constant")];
363
+ fp16 const_19_to_fp16 = const()[name = string("const_19_to_fp16"), val = fp16(0x0p+0)];
364
+ tensor<fp16, [1, 512, ?]> input_77_cast_fp16 = pad(constant_val = const_19_to_fp16, mode = input_77_mode_0, pad = input_77_pad_0, x = input_75_cast_fp16)[name = string("input_77_cast_fp16")];
365
+ string x_41_pad_type_0 = const()[name = string("x_41_pad_type_0"), val = string("valid")];
366
+ tensor<int32, [1]> x_41_dilations_0 = const()[name = string("x_41_dilations_0"), val = tensor<int32, [1]>([9])];
367
+ int32 x_41_groups_0 = const()[name = string("x_41_groups_0"), val = int32(512)];
368
+ tensor<int32, [1]> x_41_strides_0 = const()[name = string("x_41_strides_0"), val = tensor<int32, [1]>([1])];
369
+ tensor<int32, [2]> x_41_pad_0 = const()[name = string("x_41_pad_0"), val = tensor<int32, [2]>([0, 0])];
370
+ tensor<fp16, [512, 1, 7]> weight_39_to_fp16 = const()[name = string("weight_39_to_fp16"), val = tensor<fp16, [512, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4492352)))];
371
+ tensor<fp16, [512]> block_3_block_2_block_1_bias_to_fp16 = const()[name = string("block_3_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4499584)))];
372
+ tensor<fp16, [1, 512, ?]> x_41_cast_fp16 = conv(bias = block_3_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_39_to_fp16, x = input_77_cast_fp16)[name = string("x_41_cast_fp16")];
373
+ tensor<fp16, [1, 512, 1]> block_3_block_2_block_2_alpha_to_fp16 = const()[name = string("block_3_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4500672)))];
374
+ tensor<fp16, [1, 512, ?]> var_545_cast_fp16 = mul(x = block_3_block_2_block_2_alpha_to_fp16, y = x_41_cast_fp16)[name = string("op_545_cast_fp16")];
375
+ tensor<fp16, [1, 512, ?]> var_546_cast_fp16 = sin(x = var_545_cast_fp16)[name = string("op_546_cast_fp16")];
376
+ fp16 var_18_promoted_19_to_fp16 = const()[name = string("op_18_promoted_19_to_fp16"), val = fp16(0x1p+1)];
377
+ tensor<fp16, [1, 512, ?]> var_547_cast_fp16 = pow(x = var_546_cast_fp16, y = var_18_promoted_19_to_fp16)[name = string("op_547_cast_fp16")];
378
+ tensor<fp16, [1, 512, 1]> var_544_to_fp16 = const()[name = string("op_544_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4501760)))];
379
+ tensor<fp16, [1, 512, ?]> var_548_cast_fp16 = mul(x = var_544_to_fp16, y = var_547_cast_fp16)[name = string("op_548_cast_fp16")];
380
+ tensor<fp16, [1, 512, ?]> input_79_cast_fp16 = add(x = x_41_cast_fp16, y = var_548_cast_fp16)[name = string("input_79_cast_fp16")];
381
+ string y_17_pad_type_0 = const()[name = string("y_17_pad_type_0"), val = string("valid")];
382
+ tensor<int32, [1]> y_17_strides_0 = const()[name = string("y_17_strides_0"), val = tensor<int32, [1]>([1])];
383
+ tensor<int32, [2]> y_17_pad_0 = const()[name = string("y_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
384
+ tensor<int32, [1]> y_17_dilations_0 = const()[name = string("y_17_dilations_0"), val = tensor<int32, [1]>([1])];
385
+ int32 y_17_groups_0 = const()[name = string("y_17_groups_0"), val = int32(1)];
386
+ tensor<fp16, [512, 512, 1]> weight_41_to_fp16 = const()[name = string("weight_41_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4502848)))];
387
+ tensor<fp16, [512]> block_3_block_2_block_3_bias_to_fp16 = const()[name = string("block_3_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5027200)))];
388
+ tensor<fp16, [1, 512, ?]> y_17_cast_fp16 = conv(bias = block_3_block_2_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_41_to_fp16, x = input_79_cast_fp16)[name = string("y_17_cast_fp16")];
389
+ tensor<fp16, [1, 512, ?]> x_43_cast_fp16 = add(x = x_39_cast_fp16, y = y_17_cast_fp16)[name = string("x_43_cast_fp16")];
390
+ tensor<fp16, [1, 512, 1]> block_3_block_3_alpha_to_fp16 = const()[name = string("block_3_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5028288)))];
391
+ tensor<fp16, [1, 512, ?]> var_564_cast_fp16 = mul(x = block_3_block_3_alpha_to_fp16, y = x_43_cast_fp16)[name = string("op_564_cast_fp16")];
392
+ tensor<fp16, [1, 512, ?]> var_565_cast_fp16 = sin(x = var_564_cast_fp16)[name = string("op_565_cast_fp16")];
393
+ fp16 var_18_promoted_20_to_fp16 = const()[name = string("op_18_promoted_20_to_fp16"), val = fp16(0x1p+1)];
394
+ tensor<fp16, [1, 512, ?]> var_566_cast_fp16 = pow(x = var_565_cast_fp16, y = var_18_promoted_20_to_fp16)[name = string("op_566_cast_fp16")];
395
+ tensor<fp16, [1, 512, 1]> var_563_to_fp16 = const()[name = string("op_563_to_fp16"), val = tensor<fp16, [1, 512, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5029376)))];
396
+ tensor<fp16, [1, 512, ?]> var_567_cast_fp16 = mul(x = var_563_to_fp16, y = var_566_cast_fp16)[name = string("op_567_cast_fp16")];
397
+ tensor<fp16, [1, 512, ?]> input_83_cast_fp16 = add(x = x_43_cast_fp16, y = var_567_cast_fp16)[name = string("input_83_cast_fp16")];
398
+ tensor<int32, [6]> input_85_pad_0 = const()[name = string("input_85_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 0])];
399
+ string input_85_mode_0 = const()[name = string("input_85_mode_0"), val = string("constant")];
400
+ fp16 const_21_to_fp16 = const()[name = string("const_21_to_fp16"), val = fp16(0x0p+0)];
401
+ tensor<fp16, [1, 512, ?]> input_85_cast_fp16 = pad(constant_val = const_21_to_fp16, mode = input_85_mode_0, pad = input_85_pad_0, x = input_83_cast_fp16)[name = string("input_85_cast_fp16")];
402
+ string x_45_pad_type_0 = const()[name = string("x_45_pad_type_0"), val = string("valid")];
403
+ tensor<int32, [1]> x_45_strides_0 = const()[name = string("x_45_strides_0"), val = tensor<int32, [1]>([8])];
404
+ tensor<int32, [2]> x_45_pad_0 = const()[name = string("x_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
405
+ tensor<int32, [1]> x_45_dilations_0 = const()[name = string("x_45_dilations_0"), val = tensor<int32, [1]>([1])];
406
+ int32 x_45_groups_0 = const()[name = string("x_45_groups_0"), val = int32(1)];
407
+ tensor<fp16, [1024, 512, 16]> weight_43_to_fp16 = const()[name = string("weight_43_to_fp16"), val = tensor<fp16, [1024, 512, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5030464)))];
408
+ tensor<fp16, [1024]> block_3_block_4_bias_to_fp16 = const()[name = string("block_3_block_4_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21807744)))];
409
+ tensor<fp16, [1, 1024, ?]> x_45_cast_fp16 = conv(bias = block_3_block_4_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_43_to_fp16, x = input_85_cast_fp16)[name = string("x_45_cast_fp16")];
410
+ tensor<fp16, [1, 1024, 1]> block_4_block_0_block_0_alpha_to_fp16 = const()[name = string("block_4_block_0_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21809856)))];
411
+ tensor<fp16, [1, 1024, ?]> var_605_cast_fp16 = mul(x = block_4_block_0_block_0_alpha_to_fp16, y = x_45_cast_fp16)[name = string("op_605_cast_fp16")];
412
+ tensor<fp16, [1, 1024, ?]> var_606_cast_fp16 = sin(x = var_605_cast_fp16)[name = string("op_606_cast_fp16")];
413
+ fp16 var_18_promoted_21_to_fp16 = const()[name = string("op_18_promoted_21_to_fp16"), val = fp16(0x1p+1)];
414
+ tensor<fp16, [1, 1024, ?]> var_607_cast_fp16 = pow(x = var_606_cast_fp16, y = var_18_promoted_21_to_fp16)[name = string("op_607_cast_fp16")];
415
+ tensor<fp16, [1, 1024, 1]> var_604_to_fp16 = const()[name = string("op_604_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21811968)))];
416
+ tensor<fp16, [1, 1024, ?]> var_608_cast_fp16 = mul(x = var_604_to_fp16, y = var_607_cast_fp16)[name = string("op_608_cast_fp16")];
417
+ tensor<fp16, [1, 1024, ?]> input_87_cast_fp16 = add(x = x_45_cast_fp16, y = var_608_cast_fp16)[name = string("input_87_cast_fp16")];
418
+ tensor<int32, [6]> input_89_pad_0 = const()[name = string("input_89_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
419
+ string input_89_mode_0 = const()[name = string("input_89_mode_0"), val = string("constant")];
420
+ fp16 const_22_to_fp16 = const()[name = string("const_22_to_fp16"), val = fp16(0x0p+0)];
421
+ tensor<fp16, [1, 1024, ?]> input_89_cast_fp16 = pad(constant_val = const_22_to_fp16, mode = input_89_mode_0, pad = input_89_pad_0, x = input_87_cast_fp16)[name = string("input_89_cast_fp16")];
422
+ string x_47_pad_type_0 = const()[name = string("x_47_pad_type_0"), val = string("valid")];
423
+ int32 x_47_groups_0 = const()[name = string("x_47_groups_0"), val = int32(1024)];
424
+ tensor<int32, [1]> x_47_strides_0 = const()[name = string("x_47_strides_0"), val = tensor<int32, [1]>([1])];
425
+ tensor<int32, [2]> x_47_pad_0 = const()[name = string("x_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
426
+ tensor<int32, [1]> x_47_dilations_0 = const()[name = string("x_47_dilations_0"), val = tensor<int32, [1]>([1])];
427
+ tensor<fp16, [1024, 1, 7]> weight_45_to_fp16 = const()[name = string("weight_45_to_fp16"), val = tensor<fp16, [1024, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21814080)))];
428
+ tensor<fp16, [1024]> block_4_block_0_block_1_bias_to_fp16 = const()[name = string("block_4_block_0_block_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21828480)))];
429
+ tensor<fp16, [1, 1024, ?]> x_47_cast_fp16 = conv(bias = block_4_block_0_block_1_bias_to_fp16, dilations = x_47_dilations_0, groups = x_47_groups_0, pad = x_47_pad_0, pad_type = x_47_pad_type_0, strides = x_47_strides_0, weight = weight_45_to_fp16, x = input_89_cast_fp16)[name = string("x_47_cast_fp16")];
430
+ tensor<fp16, [1, 1024, 1]> block_4_block_0_block_2_alpha_to_fp16 = const()[name = string("block_4_block_0_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21830592)))];
431
+ tensor<fp16, [1, 1024, ?]> var_623_cast_fp16 = mul(x = block_4_block_0_block_2_alpha_to_fp16, y = x_47_cast_fp16)[name = string("op_623_cast_fp16")];
432
+ tensor<fp16, [1, 1024, ?]> var_624_cast_fp16 = sin(x = var_623_cast_fp16)[name = string("op_624_cast_fp16")];
433
+ fp16 var_18_promoted_22_to_fp16 = const()[name = string("op_18_promoted_22_to_fp16"), val = fp16(0x1p+1)];
434
+ tensor<fp16, [1, 1024, ?]> var_625_cast_fp16 = pow(x = var_624_cast_fp16, y = var_18_promoted_22_to_fp16)[name = string("op_625_cast_fp16")];
435
+ tensor<fp16, [1, 1024, 1]> var_622_to_fp16 = const()[name = string("op_622_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21832704)))];
436
+ tensor<fp16, [1, 1024, ?]> var_626_cast_fp16 = mul(x = var_622_to_fp16, y = var_625_cast_fp16)[name = string("op_626_cast_fp16")];
437
+ tensor<fp16, [1, 1024, ?]> input_91_cast_fp16 = add(x = x_47_cast_fp16, y = var_626_cast_fp16)[name = string("input_91_cast_fp16")];
438
+ string y_19_pad_type_0 = const()[name = string("y_19_pad_type_0"), val = string("valid")];
439
+ tensor<int32, [1]> y_19_strides_0 = const()[name = string("y_19_strides_0"), val = tensor<int32, [1]>([1])];
440
+ tensor<int32, [2]> y_19_pad_0 = const()[name = string("y_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
441
+ tensor<int32, [1]> y_19_dilations_0 = const()[name = string("y_19_dilations_0"), val = tensor<int32, [1]>([1])];
442
+ int32 y_19_groups_0 = const()[name = string("y_19_groups_0"), val = int32(1)];
443
+ tensor<fp16, [1024, 1024, 1]> weight_47_to_fp16 = const()[name = string("weight_47_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21834816)))];
444
+ tensor<fp16, [1024]> block_4_block_0_block_3_bias_to_fp16 = const()[name = string("block_4_block_0_block_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23932032)))];
445
+ tensor<fp16, [1, 1024, ?]> y_19_cast_fp16 = conv(bias = block_4_block_0_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_47_to_fp16, x = input_91_cast_fp16)[name = string("y_19_cast_fp16")];
446
+ tensor<fp16, [1, 1024, ?]> x_49_cast_fp16 = add(x = x_45_cast_fp16, y = y_19_cast_fp16)[name = string("x_49_cast_fp16")];
447
+ tensor<fp16, [1, 1024, 1]> block_4_block_1_block_0_alpha_to_fp16 = const()[name = string("block_4_block_1_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23934144)))];
448
+ tensor<fp16, [1, 1024, ?]> var_655_cast_fp16 = mul(x = block_4_block_1_block_0_alpha_to_fp16, y = x_49_cast_fp16)[name = string("op_655_cast_fp16")];
449
+ tensor<fp16, [1, 1024, ?]> var_656_cast_fp16 = sin(x = var_655_cast_fp16)[name = string("op_656_cast_fp16")];
450
+ fp16 var_18_promoted_23_to_fp16 = const()[name = string("op_18_promoted_23_to_fp16"), val = fp16(0x1p+1)];
451
+ tensor<fp16, [1, 1024, ?]> var_657_cast_fp16 = pow(x = var_656_cast_fp16, y = var_18_promoted_23_to_fp16)[name = string("op_657_cast_fp16")];
452
+ tensor<fp16, [1, 1024, 1]> var_654_to_fp16 = const()[name = string("op_654_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23936256)))];
453
+ tensor<fp16, [1, 1024, ?]> var_658_cast_fp16 = mul(x = var_654_to_fp16, y = var_657_cast_fp16)[name = string("op_658_cast_fp16")];
454
+ tensor<fp16, [1, 1024, ?]> input_95_cast_fp16 = add(x = x_49_cast_fp16, y = var_658_cast_fp16)[name = string("input_95_cast_fp16")];
455
+ tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
456
+ string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("constant")];
457
+ fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
458
+ tensor<fp16, [1, 1024, ?]> input_97_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
459
+ string x_51_pad_type_0 = const()[name = string("x_51_pad_type_0"), val = string("valid")];
460
+ tensor<int32, [1]> x_51_dilations_0 = const()[name = string("x_51_dilations_0"), val = tensor<int32, [1]>([3])];
461
+ int32 x_51_groups_0 = const()[name = string("x_51_groups_0"), val = int32(1024)];
462
+ tensor<int32, [1]> x_51_strides_0 = const()[name = string("x_51_strides_0"), val = tensor<int32, [1]>([1])];
463
+ tensor<int32, [2]> x_51_pad_0 = const()[name = string("x_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
464
+ tensor<fp16, [1024, 1, 7]> weight_49_to_fp16 = const()[name = string("weight_49_to_fp16"), val = tensor<fp16, [1024, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23938368)))];
465
+ tensor<fp16, [1024]> block_4_block_1_block_1_bias_to_fp16 = const()[name = string("block_4_block_1_block_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23952768)))];
466
+ tensor<fp16, [1, 1024, ?]> x_51_cast_fp16 = conv(bias = block_4_block_1_block_1_bias_to_fp16, dilations = x_51_dilations_0, groups = x_51_groups_0, pad = x_51_pad_0, pad_type = x_51_pad_type_0, strides = x_51_strides_0, weight = weight_49_to_fp16, x = input_97_cast_fp16)[name = string("x_51_cast_fp16")];
467
+ tensor<fp16, [1, 1024, 1]> block_4_block_1_block_2_alpha_to_fp16 = const()[name = string("block_4_block_1_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23954880)))];
468
+ tensor<fp16, [1, 1024, ?]> var_673_cast_fp16 = mul(x = block_4_block_1_block_2_alpha_to_fp16, y = x_51_cast_fp16)[name = string("op_673_cast_fp16")];
469
+ tensor<fp16, [1, 1024, ?]> var_674_cast_fp16 = sin(x = var_673_cast_fp16)[name = string("op_674_cast_fp16")];
470
+ fp16 var_18_promoted_24_to_fp16 = const()[name = string("op_18_promoted_24_to_fp16"), val = fp16(0x1p+1)];
471
+ tensor<fp16, [1, 1024, ?]> var_675_cast_fp16 = pow(x = var_674_cast_fp16, y = var_18_promoted_24_to_fp16)[name = string("op_675_cast_fp16")];
472
+ tensor<fp16, [1, 1024, 1]> var_672_to_fp16 = const()[name = string("op_672_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23956992)))];
473
+ tensor<fp16, [1, 1024, ?]> var_676_cast_fp16 = mul(x = var_672_to_fp16, y = var_675_cast_fp16)[name = string("op_676_cast_fp16")];
474
+ tensor<fp16, [1, 1024, ?]> input_99_cast_fp16 = add(x = x_51_cast_fp16, y = var_676_cast_fp16)[name = string("input_99_cast_fp16")];
475
+ string y_21_pad_type_0 = const()[name = string("y_21_pad_type_0"), val = string("valid")];
476
+ tensor<int32, [1]> y_21_strides_0 = const()[name = string("y_21_strides_0"), val = tensor<int32, [1]>([1])];
477
+ tensor<int32, [2]> y_21_pad_0 = const()[name = string("y_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
478
+ tensor<int32, [1]> y_21_dilations_0 = const()[name = string("y_21_dilations_0"), val = tensor<int32, [1]>([1])];
479
+ int32 y_21_groups_0 = const()[name = string("y_21_groups_0"), val = int32(1)];
480
+ tensor<fp16, [1024, 1024, 1]> weight_51_to_fp16 = const()[name = string("weight_51_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23959104)))];
481
+ tensor<fp16, [1024]> block_4_block_1_block_3_bias_to_fp16 = const()[name = string("block_4_block_1_block_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26056320)))];
482
+ tensor<fp16, [1, 1024, ?]> y_21_cast_fp16 = conv(bias = block_4_block_1_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_51_to_fp16, x = input_99_cast_fp16)[name = string("y_21_cast_fp16")];
483
+ tensor<fp16, [1, 1024, ?]> x_53_cast_fp16 = add(x = x_49_cast_fp16, y = y_21_cast_fp16)[name = string("x_53_cast_fp16")];
484
+ tensor<fp16, [1, 1024, 1]> block_4_block_2_block_0_alpha_to_fp16 = const()[name = string("block_4_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26058432)))];
485
+ tensor<fp16, [1, 1024, ?]> var_705_cast_fp16 = mul(x = block_4_block_2_block_0_alpha_to_fp16, y = x_53_cast_fp16)[name = string("op_705_cast_fp16")];
486
+ tensor<fp16, [1, 1024, ?]> var_706_cast_fp16 = sin(x = var_705_cast_fp16)[name = string("op_706_cast_fp16")];
487
+ fp16 var_18_promoted_25_to_fp16 = const()[name = string("op_18_promoted_25_to_fp16"), val = fp16(0x1p+1)];
488
+ tensor<fp16, [1, 1024, ?]> var_707_cast_fp16 = pow(x = var_706_cast_fp16, y = var_18_promoted_25_to_fp16)[name = string("op_707_cast_fp16")];
489
+ tensor<fp16, [1, 1024, 1]> var_704_to_fp16 = const()[name = string("op_704_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26060544)))];
490
+ tensor<fp16, [1, 1024, ?]> var_708_cast_fp16 = mul(x = var_704_to_fp16, y = var_707_cast_fp16)[name = string("op_708_cast_fp16")];
491
+ tensor<fp16, [1, 1024, ?]> input_103_cast_fp16 = add(x = x_53_cast_fp16, y = var_708_cast_fp16)[name = string("input_103_cast_fp16")];
492
+ tensor<int32, [6]> input_105_pad_0 = const()[name = string("input_105_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
493
+ string input_105_mode_0 = const()[name = string("input_105_mode_0"), val = string("constant")];
494
+ fp16 const_26_to_fp16 = const()[name = string("const_26_to_fp16"), val = fp16(0x0p+0)];
495
+ tensor<fp16, [1, 1024, ?]> input_105_cast_fp16 = pad(constant_val = const_26_to_fp16, mode = input_105_mode_0, pad = input_105_pad_0, x = input_103_cast_fp16)[name = string("input_105_cast_fp16")];
496
+ string x_55_pad_type_0 = const()[name = string("x_55_pad_type_0"), val = string("valid")];
497
+ tensor<int32, [1]> x_55_dilations_0 = const()[name = string("x_55_dilations_0"), val = tensor<int32, [1]>([9])];
498
+ int32 x_55_groups_0 = const()[name = string("x_55_groups_0"), val = int32(1024)];
499
+ tensor<int32, [1]> x_55_strides_0 = const()[name = string("x_55_strides_0"), val = tensor<int32, [1]>([1])];
500
+ tensor<int32, [2]> x_55_pad_0 = const()[name = string("x_55_pad_0"), val = tensor<int32, [2]>([0, 0])];
501
+ tensor<fp16, [1024, 1, 7]> weight_53_to_fp16 = const()[name = string("weight_53_to_fp16"), val = tensor<fp16, [1024, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26062656)))];
502
+ tensor<fp16, [1024]> block_4_block_2_block_1_bias_to_fp16 = const()[name = string("block_4_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26077056)))];
503
+ tensor<fp16, [1, 1024, ?]> x_55_cast_fp16 = conv(bias = block_4_block_2_block_1_bias_to_fp16, dilations = x_55_dilations_0, groups = x_55_groups_0, pad = x_55_pad_0, pad_type = x_55_pad_type_0, strides = x_55_strides_0, weight = weight_53_to_fp16, x = input_105_cast_fp16)[name = string("x_55_cast_fp16")];
504
+ tensor<fp16, [1, 1024, 1]> block_4_block_2_block_2_alpha_to_fp16 = const()[name = string("block_4_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26079168)))];
505
+ tensor<fp16, [1, 1024, ?]> var_723_cast_fp16 = mul(x = block_4_block_2_block_2_alpha_to_fp16, y = x_55_cast_fp16)[name = string("op_723_cast_fp16")];
506
+ tensor<fp16, [1, 1024, ?]> var_724_cast_fp16 = sin(x = var_723_cast_fp16)[name = string("op_724_cast_fp16")];
507
+ fp16 var_18_promoted_26_to_fp16 = const()[name = string("op_18_promoted_26_to_fp16"), val = fp16(0x1p+1)];
508
+ tensor<fp16, [1, 1024, ?]> var_725_cast_fp16 = pow(x = var_724_cast_fp16, y = var_18_promoted_26_to_fp16)[name = string("op_725_cast_fp16")];
509
+ tensor<fp16, [1, 1024, 1]> var_722_to_fp16 = const()[name = string("op_722_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26081280)))];
510
+ tensor<fp16, [1, 1024, ?]> var_726_cast_fp16 = mul(x = var_722_to_fp16, y = var_725_cast_fp16)[name = string("op_726_cast_fp16")];
511
+ tensor<fp16, [1, 1024, ?]> input_107_cast_fp16 = add(x = x_55_cast_fp16, y = var_726_cast_fp16)[name = string("input_107_cast_fp16")];
512
+ string y_pad_type_0 = const()[name = string("y_pad_type_0"), val = string("valid")];
513
+ tensor<int32, [1]> y_strides_0 = const()[name = string("y_strides_0"), val = tensor<int32, [1]>([1])];
514
+ tensor<int32, [2]> y_pad_0 = const()[name = string("y_pad_0"), val = tensor<int32, [2]>([0, 0])];
515
+ tensor<int32, [1]> y_dilations_0 = const()[name = string("y_dilations_0"), val = tensor<int32, [1]>([1])];
516
+ int32 y_groups_0 = const()[name = string("y_groups_0"), val = int32(1)];
517
+ tensor<fp16, [1024, 1024, 1]> weight_55_to_fp16 = const()[name = string("weight_55_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26083392)))];
518
+ tensor<fp16, [1024]> block_4_block_2_block_3_bias_to_fp16 = const()[name = string("block_4_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28180608)))];
519
+ tensor<fp16, [1, 1024, ?]> y_cast_fp16 = conv(bias = block_4_block_2_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_55_to_fp16, x = input_107_cast_fp16)[name = string("y_cast_fp16")];
520
+ tensor<fp16, [1, 1024, ?]> x_cast_fp16 = add(x = x_53_cast_fp16, y = y_cast_fp16)[name = string("x_cast_fp16")];
521
+ tensor<fp16, [1, 1024, 1]> block_4_block_3_alpha_to_fp16 = const()[name = string("block_4_block_3_alpha_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28182720)))];
522
+ tensor<fp16, [1, 1024, ?]> var_742_cast_fp16 = mul(x = block_4_block_3_alpha_to_fp16, y = x_cast_fp16)[name = string("op_742_cast_fp16")];
523
+ tensor<fp16, [1, 1024, ?]> var_743_cast_fp16 = sin(x = var_742_cast_fp16)[name = string("op_743_cast_fp16")];
524
+ fp16 var_18_promoted_27_to_fp16 = const()[name = string("op_18_promoted_27_to_fp16"), val = fp16(0x1p+1)];
525
+ tensor<fp16, [1, 1024, ?]> var_744_cast_fp16 = pow(x = var_743_cast_fp16, y = var_18_promoted_27_to_fp16)[name = string("op_744_cast_fp16")];
526
+ tensor<fp16, [1, 1024, 1]> var_741_to_fp16 = const()[name = string("op_741_to_fp16"), val = tensor<fp16, [1, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28184832)))];
527
+ tensor<fp16, [1, 1024, ?]> var_745_cast_fp16 = mul(x = var_741_to_fp16, y = var_744_cast_fp16)[name = string("op_745_cast_fp16")];
528
+ tensor<fp16, [1, 1024, ?]> input_111_cast_fp16 = add(x = x_cast_fp16, y = var_745_cast_fp16)[name = string("input_111_cast_fp16")];
529
+ tensor<int32, [6]> input_113_pad_0 = const()[name = string("input_113_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 0])];
530
+ string input_113_mode_0 = const()[name = string("input_113_mode_0"), val = string("constant")];
531
+ fp16 const_28_to_fp16 = const()[name = string("const_28_to_fp16"), val = fp16(0x0p+0)];
532
+ tensor<fp16, [1, 1024, ?]> input_113_cast_fp16 = pad(constant_val = const_28_to_fp16, mode = input_113_mode_0, pad = input_113_pad_0, x = input_111_cast_fp16)[name = string("input_113_cast_fp16")];
533
+ string input_115_pad_type_0 = const()[name = string("input_115_pad_type_0"), val = string("valid")];
534
+ tensor<int32, [1]> input_115_strides_0 = const()[name = string("input_115_strides_0"), val = tensor<int32, [1]>([8])];
535
+ tensor<int32, [2]> input_115_pad_0 = const()[name = string("input_115_pad_0"), val = tensor<int32, [2]>([0, 0])];
536
+ tensor<int32, [1]> input_115_dilations_0 = const()[name = string("input_115_dilations_0"), val = tensor<int32, [1]>([1])];
537
+ int32 input_115_groups_0 = const()[name = string("input_115_groups_0"), val = int32(1)];
538
+ tensor<fp16, [2048, 1024, 16]> weight_57_to_fp16 = const()[name = string("weight_57_to_fp16"), val = tensor<fp16, [2048, 1024, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28186944)))];
539
+ tensor<fp16, [2048]> block_4_block_4_bias_to_fp16 = const()[name = string("block_4_block_4_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(95295872)))];
540
+ tensor<fp16, [1, 2048, ?]> input_115_cast_fp16 = conv(bias = block_4_block_4_bias_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 = weight_57_to_fp16, x = input_113_cast_fp16)[name = string("input_115_cast_fp16")];
541
+ tensor<int32, [6]> input_pad_0 = const()[name = string("input_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 0])];
542
+ string input_mode_0 = const()[name = string("input_mode_0"), val = string("constant")];
543
+ fp16 const_29_to_fp16 = const()[name = string("const_29_to_fp16"), val = fp16(0x0p+0)];
544
+ tensor<fp16, [1, 2048, ?]> input_cast_fp16 = pad(constant_val = const_29_to_fp16, mode = input_mode_0, pad = input_pad_0, x = input_115_cast_fp16)[name = string("input_cast_fp16")];
545
+ string var_772_pad_type_0 = const()[name = string("op_772_pad_type_0"), val = string("valid")];
546
+ tensor<int32, [1]> var_772_strides_0 = const()[name = string("op_772_strides_0"), val = tensor<int32, [1]>([1])];
547
+ tensor<int32, [2]> var_772_pad_0 = const()[name = string("op_772_pad_0"), val = tensor<int32, [2]>([0, 0])];
548
+ tensor<int32, [1]> var_772_dilations_0 = const()[name = string("op_772_dilations_0"), val = tensor<int32, [1]>([1])];
549
+ int32 var_772_groups_0 = const()[name = string("op_772_groups_0"), val = int32(1)];
550
+ tensor<fp16, [64, 2048, 3]> weight_to_fp16 = const()[name = string("weight_to_fp16"), val = tensor<fp16, [64, 2048, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(95300032)))];
551
+ tensor<fp16, [64]> fc_mu_bias_to_fp16 = const()[name = string("fc_mu_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(96086528)))];
552
+ tensor<fp16, [1, 64, ?]> output = conv(bias = fc_mu_bias_to_fp16, dilations = var_772_dilations_0, groups = var_772_groups_0, pad = var_772_pad_0, pad_type = var_772_pad_type_0, strides = var_772_strides_0, weight = weight_to_fp16, x = input_cast_fp16)[name = string("op_772_cast_fp16")];
553
+ } -> (output);
554
+ }
voxcpm_audio_vae_encoder_enum_length_17920.mlmodelc/weights/weight.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1af02090815264409381a85492d123e6c14be2096260b4de077e97c1574408d4
3
+ size 96086720