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+ {
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+ "architecture": "DFSMN",
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+ "frame_length_ms": 25,
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+ program(1.0)
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+ [buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3405.2.1"}, {"coremltools-component-torch", "2.7.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
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+ {
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+ func main<ios17>(tensor<fp32, [1, ?, 80]> features) [FlexibleShapeInformation = tuple<tuple<tensor<string, []>, dict<tensor<string, []>, tensor<int32, [?]>>>, tuple<tensor<string, []>, dict<tensor<string, []>, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"features", [1, 200, 80]}}), ("RangeDims", {{"features", [[1, 1], [1, 6000], [80, 80]]}})))] {
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+ tensor<string, []> features_to_fp16_dtype_0 = const()[name = tensor<string, []>("features_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
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+ tensor<fp16, [80]> cmvn_mean_to_fp16 = const()[name = tensor<string, []>("cmvn_mean_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
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+ tensor<fp16, [1, ?, 80]> features_to_fp16 = cast(dtype = features_to_fp16_dtype_0, x = features)[name = tensor<string, []>("cast_1")];
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+ tensor<fp16, [1, ?, 80]> var_24_cast_fp16 = sub(x = features_to_fp16, y = cmvn_mean_to_fp16)[name = tensor<string, []>("op_24_cast_fp16")];
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+ tensor<fp16, [80]> cmvn_inv_std_to_fp16 = const()[name = tensor<string, []>("cmvn_inv_std_to_fp16"), val = tensor<fp16, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(320)))];
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+ tensor<fp16, [1, ?, 80]> input_1_cast_fp16 = mul(x = var_24_cast_fp16, y = cmvn_inv_std_to_fp16)[name = tensor<string, []>("input_1_cast_fp16")];
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+ tensor<fp16, [256, 80]> fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(576)))];
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+ tensor<fp16, [256]> fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41600)))];
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+ tensor<fp16, [1, ?, 256]> linear_0_cast_fp16 = linear(bias = fc1_0_bias_to_fp16, weight = fc1_0_weight_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
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+ tensor<fp16, [1, ?, 256]> input_5_cast_fp16 = relu(x = linear_0_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
15
+ tensor<fp16, [128, 256]> fc2_0_weight_to_fp16 = const()[name = tensor<string, []>("fc2_0_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(42176)))];
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+ tensor<fp16, [128]> fc2_0_bias_to_fp16 = const()[name = tensor<string, []>("fc2_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107776)))];
17
+ tensor<fp16, [1, ?, 128]> linear_1_cast_fp16 = linear(bias = fc2_0_bias_to_fp16, weight = fc2_0_weight_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
18
+ tensor<fp16, [1, ?, 128]> inputs_1_cast_fp16 = relu(x = linear_1_cast_fp16)[name = tensor<string, []>("inputs_1_cast_fp16")];
19
+ tensor<int32, [3]> var_50 = const()[name = tensor<string, []>("op_50"), val = tensor<int32, [3]>([0, 2, 1])];
20
+ tensor<string, []> lookback_1_pad_type_0 = const()[name = tensor<string, []>("lookback_1_pad_type_0"), val = tensor<string, []>("custom")];
21
+ tensor<int32, [2]> lookback_1_pad_0 = const()[name = tensor<string, []>("lookback_1_pad_0"), val = tensor<int32, [2]>([19, 19])];
22
+ tensor<int32, []> lookback_1_groups_0 = const()[name = tensor<string, []>("lookback_1_groups_0"), val = tensor<int32, []>(128)];
23
+ tensor<int32, [1]> lookback_1_strides_0 = const()[name = tensor<string, []>("lookback_1_strides_0"), val = tensor<int32, [1]>([1])];
24
+ tensor<int32, [1]> lookback_1_dilations_0 = const()[name = tensor<string, []>("lookback_1_dilations_0"), val = tensor<int32, [1]>([1])];
25
+ tensor<fp16, [128, 1, 20]> fsmn1_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmn1_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108096)))];
26
+ tensor<fp16, [1, 128, ?]> var_51_cast_fp16 = transpose(perm = var_50, x = inputs_1_cast_fp16)[name = tensor<string, []>("transpose_15")];
27
+ tensor<fp16, [1, 128, ?]> lookback_1_cast_fp16 = conv(dilations = lookback_1_dilations_0, groups = lookback_1_groups_0, pad = lookback_1_pad_0, pad_type = lookback_1_pad_type_0, strides = lookback_1_strides_0, weight = fsmn1_lookback_filter_weight_to_fp16, x = var_51_cast_fp16)[name = tensor<string, []>("lookback_1_cast_fp16")];
28
+ tensor<int32, [3]> lookback_3_begin_0 = const()[name = tensor<string, []>("lookback_3_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
29
+ tensor<int32, [3]> lookback_3_end_0 = const()[name = tensor<string, []>("lookback_3_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
30
+ tensor<bool, [3]> lookback_3_end_mask_0 = const()[name = tensor<string, []>("lookback_3_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
31
+ tensor<fp16, [1, 128, ?]> lookback_3_cast_fp16 = slice_by_index(begin = lookback_3_begin_0, end = lookback_3_end_0, end_mask = lookback_3_end_mask_0, x = lookback_1_cast_fp16)[name = tensor<string, []>("lookback_3_cast_fp16")];
32
+ tensor<fp16, [1, 128, ?]> memory_1_cast_fp16 = add(x = var_51_cast_fp16, y = lookback_3_cast_fp16)[name = tensor<string, []>("memory_1_cast_fp16")];
33
+ tensor<string, []> lookahead_1_pad_type_0 = const()[name = tensor<string, []>("lookahead_1_pad_type_0"), val = tensor<string, []>("custom")];
34
+ tensor<int32, [2]> lookahead_1_pad_0 = const()[name = tensor<string, []>("lookahead_1_pad_0"), val = tensor<int32, [2]>([19, 19])];
35
+ tensor<int32, []> lookahead_1_groups_0 = const()[name = tensor<string, []>("lookahead_1_groups_0"), val = tensor<int32, []>(128)];
36
+ tensor<int32, [1]> lookahead_1_strides_0 = const()[name = tensor<string, []>("lookahead_1_strides_0"), val = tensor<int32, [1]>([1])];
37
+ tensor<int32, [1]> lookahead_1_dilations_0 = const()[name = tensor<string, []>("lookahead_1_dilations_0"), val = tensor<int32, [1]>([1])];
38
+ tensor<fp16, [128, 1, 20]> fsmn1_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmn1_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(113280)))];
39
+ tensor<fp16, [1, 128, ?]> lookahead_1_cast_fp16 = conv(dilations = lookahead_1_dilations_0, groups = lookahead_1_groups_0, pad = lookahead_1_pad_0, pad_type = lookahead_1_pad_type_0, strides = lookahead_1_strides_0, weight = fsmn1_lookahead_filter_weight_to_fp16, x = var_51_cast_fp16)[name = tensor<string, []>("lookahead_1_cast_fp16")];
40
+ tensor<int32, [3]> input_11_begin_0 = const()[name = tensor<string, []>("input_11_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
41
+ tensor<int32, [3]> input_11_end_0 = const()[name = tensor<string, []>("input_11_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
42
+ tensor<bool, [3]> input_11_end_mask_0 = const()[name = tensor<string, []>("input_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
43
+ tensor<fp16, [1, 128, ?]> input_11_cast_fp16 = slice_by_index(begin = input_11_begin_0, end = input_11_end_0, end_mask = input_11_end_mask_0, x = lookahead_1_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
44
+ tensor<int32, [6]> var_73_pad_0 = const()[name = tensor<string, []>("op_73_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
45
+ tensor<string, []> var_73_mode_0 = const()[name = tensor<string, []>("op_73_mode_0"), val = tensor<string, []>("constant")];
46
+ tensor<fp16, []> const_0_to_fp16 = const()[name = tensor<string, []>("const_0_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
47
+ tensor<fp16, [1, 128, ?]> var_73_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = var_73_mode_0, pad = var_73_pad_0, x = input_11_cast_fp16)[name = tensor<string, []>("op_73_cast_fp16")];
48
+ tensor<fp16, [1, 128, ?]> memory_3_cast_fp16 = add(x = memory_1_cast_fp16, y = var_73_cast_fp16)[name = tensor<string, []>("memory_3_cast_fp16")];
49
+ tensor<int32, [3]> var_75 = const()[name = tensor<string, []>("op_75"), val = tensor<int32, [3]>([0, 2, 1])];
50
+ tensor<fp16, [256, 128]> fsmns_0_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_0_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(118464)))];
51
+ tensor<fp16, [256]> fsmns_0_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_0_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184064)))];
52
+ tensor<fp16, [1, ?, 128]> var_76_cast_fp16 = transpose(perm = var_75, x = memory_3_cast_fp16)[name = tensor<string, []>("transpose_14")];
53
+ tensor<fp16, [1, ?, 256]> linear_2_cast_fp16 = linear(bias = fsmns_0_fc1_0_bias_to_fp16, weight = fsmns_0_fc1_0_weight_to_fp16, x = var_76_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
54
+ tensor<fp16, [1, ?, 256]> input_17_cast_fp16 = relu(x = linear_2_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
55
+ tensor<fp16, [128, 256]> fsmns_0_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_0_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184640)))];
56
+ tensor<fp16, [128]> linear_3_bias_0_to_fp16 = const()[name = tensor<string, []>("linear_3_bias_0_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(250240)))];
57
+ tensor<fp16, [1, ?, 128]> linear_3_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_0_fc2_weight_to_fp16, x = input_17_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
58
+ tensor<int32, [3]> var_102 = const()[name = tensor<string, []>("op_102"), val = tensor<int32, [3]>([0, 2, 1])];
59
+ tensor<string, []> lookback_5_pad_type_0 = const()[name = tensor<string, []>("lookback_5_pad_type_0"), val = tensor<string, []>("custom")];
60
+ tensor<int32, [2]> lookback_5_pad_0 = const()[name = tensor<string, []>("lookback_5_pad_0"), val = tensor<int32, [2]>([19, 19])];
61
+ tensor<int32, []> lookback_5_groups_0 = const()[name = tensor<string, []>("lookback_5_groups_0"), val = tensor<int32, []>(128)];
62
+ tensor<int32, [1]> lookback_5_strides_0 = const()[name = tensor<string, []>("lookback_5_strides_0"), val = tensor<int32, [1]>([1])];
63
+ tensor<int32, [1]> lookback_5_dilations_0 = const()[name = tensor<string, []>("lookback_5_dilations_0"), val = tensor<int32, [1]>([1])];
64
+ tensor<fp16, [128, 1, 20]> fsmns_0_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_0_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(250560)))];
65
+ tensor<fp16, [1, 128, ?]> var_103_cast_fp16 = transpose(perm = var_102, x = linear_3_cast_fp16)[name = tensor<string, []>("transpose_13")];
66
+ tensor<fp16, [1, 128, ?]> lookback_5_cast_fp16 = conv(dilations = lookback_5_dilations_0, groups = lookback_5_groups_0, pad = lookback_5_pad_0, pad_type = lookback_5_pad_type_0, strides = lookback_5_strides_0, weight = fsmns_0_fsmn_lookback_filter_weight_to_fp16, x = var_103_cast_fp16)[name = tensor<string, []>("lookback_5_cast_fp16")];
67
+ tensor<int32, [3]> lookback_7_begin_0 = const()[name = tensor<string, []>("lookback_7_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
68
+ tensor<int32, [3]> lookback_7_end_0 = const()[name = tensor<string, []>("lookback_7_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
69
+ tensor<bool, [3]> lookback_7_end_mask_0 = const()[name = tensor<string, []>("lookback_7_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
70
+ tensor<fp16, [1, 128, ?]> lookback_7_cast_fp16 = slice_by_index(begin = lookback_7_begin_0, end = lookback_7_end_0, end_mask = lookback_7_end_mask_0, x = lookback_5_cast_fp16)[name = tensor<string, []>("lookback_7_cast_fp16")];
71
+ tensor<fp16, [1, 128, ?]> memory_5_cast_fp16 = add(x = var_103_cast_fp16, y = lookback_7_cast_fp16)[name = tensor<string, []>("memory_5_cast_fp16")];
72
+ tensor<string, []> lookahead_3_pad_type_0 = const()[name = tensor<string, []>("lookahead_3_pad_type_0"), val = tensor<string, []>("custom")];
73
+ tensor<int32, [2]> lookahead_3_pad_0 = const()[name = tensor<string, []>("lookahead_3_pad_0"), val = tensor<int32, [2]>([19, 19])];
74
+ tensor<int32, []> lookahead_3_groups_0 = const()[name = tensor<string, []>("lookahead_3_groups_0"), val = tensor<int32, []>(128)];
75
+ tensor<int32, [1]> lookahead_3_strides_0 = const()[name = tensor<string, []>("lookahead_3_strides_0"), val = tensor<int32, [1]>([1])];
76
+ tensor<int32, [1]> lookahead_3_dilations_0 = const()[name = tensor<string, []>("lookahead_3_dilations_0"), val = tensor<int32, [1]>([1])];
77
+ tensor<fp16, [128, 1, 20]> fsmns_0_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_0_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(255744)))];
78
+ tensor<fp16, [1, 128, ?]> lookahead_3_cast_fp16 = conv(dilations = lookahead_3_dilations_0, groups = lookahead_3_groups_0, pad = lookahead_3_pad_0, pad_type = lookahead_3_pad_type_0, strides = lookahead_3_strides_0, weight = fsmns_0_fsmn_lookahead_filter_weight_to_fp16, x = var_103_cast_fp16)[name = tensor<string, []>("lookahead_3_cast_fp16")];
79
+ tensor<int32, [3]> input_21_begin_0 = const()[name = tensor<string, []>("input_21_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
80
+ tensor<int32, [3]> input_21_end_0 = const()[name = tensor<string, []>("input_21_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
81
+ tensor<bool, [3]> input_21_end_mask_0 = const()[name = tensor<string, []>("input_21_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
82
+ tensor<fp16, [1, 128, ?]> input_21_cast_fp16 = slice_by_index(begin = input_21_begin_0, end = input_21_end_0, end_mask = input_21_end_mask_0, x = lookahead_3_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
83
+ tensor<int32, [6]> var_125_pad_0 = const()[name = tensor<string, []>("op_125_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
84
+ tensor<string, []> var_125_mode_0 = const()[name = tensor<string, []>("op_125_mode_0"), val = tensor<string, []>("constant")];
85
+ tensor<fp16, []> const_1_to_fp16 = const()[name = tensor<string, []>("const_1_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
86
+ tensor<fp16, [1, 128, ?]> var_125_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = var_125_mode_0, pad = var_125_pad_0, x = input_21_cast_fp16)[name = tensor<string, []>("op_125_cast_fp16")];
87
+ tensor<fp16, [1, 128, ?]> memory_7_cast_fp16 = add(x = memory_5_cast_fp16, y = var_125_cast_fp16)[name = tensor<string, []>("memory_7_cast_fp16")];
88
+ tensor<int32, [3]> var_127 = const()[name = tensor<string, []>("op_127"), val = tensor<int32, [3]>([0, 2, 1])];
89
+ tensor<fp16, [1, ?, 128]> var_128_cast_fp16 = transpose(perm = var_127, x = memory_7_cast_fp16)[name = tensor<string, []>("transpose_12")];
90
+ tensor<fp16, [1, ?, 128]> input_23_cast_fp16 = add(x = var_128_cast_fp16, y = var_76_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")];
91
+ tensor<fp16, [256, 128]> fsmns_1_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_1_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(260928)))];
92
+ tensor<fp16, [256]> fsmns_1_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_1_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326528)))];
93
+ tensor<fp16, [1, ?, 256]> linear_4_cast_fp16 = linear(bias = fsmns_1_fc1_0_bias_to_fp16, weight = fsmns_1_fc1_0_weight_to_fp16, x = input_23_cast_fp16)[name = tensor<string, []>("linear_4_cast_fp16")];
94
+ tensor<fp16, [1, ?, 256]> input_27_cast_fp16 = relu(x = linear_4_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
95
+ tensor<fp16, [128, 256]> fsmns_1_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_1_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(327104)))];
96
+ tensor<fp16, [1, ?, 128]> linear_5_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_1_fc2_weight_to_fp16, x = input_27_cast_fp16)[name = tensor<string, []>("linear_5_cast_fp16")];
97
+ tensor<int32, [3]> var_155 = const()[name = tensor<string, []>("op_155"), val = tensor<int32, [3]>([0, 2, 1])];
98
+ tensor<string, []> lookback_9_pad_type_0 = const()[name = tensor<string, []>("lookback_9_pad_type_0"), val = tensor<string, []>("custom")];
99
+ tensor<int32, [2]> lookback_9_pad_0 = const()[name = tensor<string, []>("lookback_9_pad_0"), val = tensor<int32, [2]>([19, 19])];
100
+ tensor<int32, []> lookback_9_groups_0 = const()[name = tensor<string, []>("lookback_9_groups_0"), val = tensor<int32, []>(128)];
101
+ tensor<int32, [1]> lookback_9_strides_0 = const()[name = tensor<string, []>("lookback_9_strides_0"), val = tensor<int32, [1]>([1])];
102
+ tensor<int32, [1]> lookback_9_dilations_0 = const()[name = tensor<string, []>("lookback_9_dilations_0"), val = tensor<int32, [1]>([1])];
103
+ tensor<fp16, [128, 1, 20]> fsmns_1_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_1_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392704)))];
104
+ tensor<fp16, [1, 128, ?]> var_156_cast_fp16 = transpose(perm = var_155, x = linear_5_cast_fp16)[name = tensor<string, []>("transpose_11")];
105
+ tensor<fp16, [1, 128, ?]> lookback_9_cast_fp16 = conv(dilations = lookback_9_dilations_0, groups = lookback_9_groups_0, pad = lookback_9_pad_0, pad_type = lookback_9_pad_type_0, strides = lookback_9_strides_0, weight = fsmns_1_fsmn_lookback_filter_weight_to_fp16, x = var_156_cast_fp16)[name = tensor<string, []>("lookback_9_cast_fp16")];
106
+ tensor<int32, [3]> lookback_11_begin_0 = const()[name = tensor<string, []>("lookback_11_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
107
+ tensor<int32, [3]> lookback_11_end_0 = const()[name = tensor<string, []>("lookback_11_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
108
+ tensor<bool, [3]> lookback_11_end_mask_0 = const()[name = tensor<string, []>("lookback_11_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
109
+ tensor<fp16, [1, 128, ?]> lookback_11_cast_fp16 = slice_by_index(begin = lookback_11_begin_0, end = lookback_11_end_0, end_mask = lookback_11_end_mask_0, x = lookback_9_cast_fp16)[name = tensor<string, []>("lookback_11_cast_fp16")];
110
+ tensor<fp16, [1, 128, ?]> memory_11_cast_fp16 = add(x = var_156_cast_fp16, y = lookback_11_cast_fp16)[name = tensor<string, []>("memory_11_cast_fp16")];
111
+ tensor<string, []> lookahead_5_pad_type_0 = const()[name = tensor<string, []>("lookahead_5_pad_type_0"), val = tensor<string, []>("custom")];
112
+ tensor<int32, [2]> lookahead_5_pad_0 = const()[name = tensor<string, []>("lookahead_5_pad_0"), val = tensor<int32, [2]>([19, 19])];
113
+ tensor<int32, []> lookahead_5_groups_0 = const()[name = tensor<string, []>("lookahead_5_groups_0"), val = tensor<int32, []>(128)];
114
+ tensor<int32, [1]> lookahead_5_strides_0 = const()[name = tensor<string, []>("lookahead_5_strides_0"), val = tensor<int32, [1]>([1])];
115
+ tensor<int32, [1]> lookahead_5_dilations_0 = const()[name = tensor<string, []>("lookahead_5_dilations_0"), val = tensor<int32, [1]>([1])];
116
+ tensor<fp16, [128, 1, 20]> fsmns_1_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_1_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(397888)))];
117
+ tensor<fp16, [1, 128, ?]> lookahead_5_cast_fp16 = conv(dilations = lookahead_5_dilations_0, groups = lookahead_5_groups_0, pad = lookahead_5_pad_0, pad_type = lookahead_5_pad_type_0, strides = lookahead_5_strides_0, weight = fsmns_1_fsmn_lookahead_filter_weight_to_fp16, x = var_156_cast_fp16)[name = tensor<string, []>("lookahead_5_cast_fp16")];
118
+ tensor<int32, [3]> input_31_begin_0 = const()[name = tensor<string, []>("input_31_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
119
+ tensor<int32, [3]> input_31_end_0 = const()[name = tensor<string, []>("input_31_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
120
+ tensor<bool, [3]> input_31_end_mask_0 = const()[name = tensor<string, []>("input_31_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
121
+ tensor<fp16, [1, 128, ?]> input_31_cast_fp16 = slice_by_index(begin = input_31_begin_0, end = input_31_end_0, end_mask = input_31_end_mask_0, x = lookahead_5_cast_fp16)[name = tensor<string, []>("input_31_cast_fp16")];
122
+ tensor<int32, [6]> var_178_pad_0 = const()[name = tensor<string, []>("op_178_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
123
+ tensor<string, []> var_178_mode_0 = const()[name = tensor<string, []>("op_178_mode_0"), val = tensor<string, []>("constant")];
124
+ tensor<fp16, []> const_2_to_fp16 = const()[name = tensor<string, []>("const_2_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
125
+ tensor<fp16, [1, 128, ?]> var_178_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = var_178_mode_0, pad = var_178_pad_0, x = input_31_cast_fp16)[name = tensor<string, []>("op_178_cast_fp16")];
126
+ tensor<fp16, [1, 128, ?]> memory_13_cast_fp16 = add(x = memory_11_cast_fp16, y = var_178_cast_fp16)[name = tensor<string, []>("memory_13_cast_fp16")];
127
+ tensor<int32, [3]> var_180 = const()[name = tensor<string, []>("op_180"), val = tensor<int32, [3]>([0, 2, 1])];
128
+ tensor<fp16, [1, ?, 128]> var_181_cast_fp16 = transpose(perm = var_180, x = memory_13_cast_fp16)[name = tensor<string, []>("transpose_10")];
129
+ tensor<fp16, [1, ?, 128]> input_33_cast_fp16 = add(x = var_181_cast_fp16, y = input_23_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
130
+ tensor<fp16, [256, 128]> fsmns_2_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_2_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(403072)))];
131
+ tensor<fp16, [256]> fsmns_2_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_2_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(468672)))];
132
+ tensor<fp16, [1, ?, 256]> linear_6_cast_fp16 = linear(bias = fsmns_2_fc1_0_bias_to_fp16, weight = fsmns_2_fc1_0_weight_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("linear_6_cast_fp16")];
133
+ tensor<fp16, [1, ?, 256]> input_37_cast_fp16 = relu(x = linear_6_cast_fp16)[name = tensor<string, []>("input_37_cast_fp16")];
134
+ tensor<fp16, [128, 256]> fsmns_2_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_2_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(469248)))];
135
+ tensor<fp16, [1, ?, 128]> linear_7_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_2_fc2_weight_to_fp16, x = input_37_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
136
+ tensor<int32, [3]> var_208 = const()[name = tensor<string, []>("op_208"), val = tensor<int32, [3]>([0, 2, 1])];
137
+ tensor<string, []> lookback_13_pad_type_0 = const()[name = tensor<string, []>("lookback_13_pad_type_0"), val = tensor<string, []>("custom")];
138
+ tensor<int32, [2]> lookback_13_pad_0 = const()[name = tensor<string, []>("lookback_13_pad_0"), val = tensor<int32, [2]>([19, 19])];
139
+ tensor<int32, []> lookback_13_groups_0 = const()[name = tensor<string, []>("lookback_13_groups_0"), val = tensor<int32, []>(128)];
140
+ tensor<int32, [1]> lookback_13_strides_0 = const()[name = tensor<string, []>("lookback_13_strides_0"), val = tensor<int32, [1]>([1])];
141
+ tensor<int32, [1]> lookback_13_dilations_0 = const()[name = tensor<string, []>("lookback_13_dilations_0"), val = tensor<int32, [1]>([1])];
142
+ tensor<fp16, [128, 1, 20]> fsmns_2_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_2_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(534848)))];
143
+ tensor<fp16, [1, 128, ?]> var_209_cast_fp16 = transpose(perm = var_208, x = linear_7_cast_fp16)[name = tensor<string, []>("transpose_9")];
144
+ tensor<fp16, [1, 128, ?]> lookback_13_cast_fp16 = conv(dilations = lookback_13_dilations_0, groups = lookback_13_groups_0, pad = lookback_13_pad_0, pad_type = lookback_13_pad_type_0, strides = lookback_13_strides_0, weight = fsmns_2_fsmn_lookback_filter_weight_to_fp16, x = var_209_cast_fp16)[name = tensor<string, []>("lookback_13_cast_fp16")];
145
+ tensor<int32, [3]> lookback_15_begin_0 = const()[name = tensor<string, []>("lookback_15_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
146
+ tensor<int32, [3]> lookback_15_end_0 = const()[name = tensor<string, []>("lookback_15_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
147
+ tensor<bool, [3]> lookback_15_end_mask_0 = const()[name = tensor<string, []>("lookback_15_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
148
+ tensor<fp16, [1, 128, ?]> lookback_15_cast_fp16 = slice_by_index(begin = lookback_15_begin_0, end = lookback_15_end_0, end_mask = lookback_15_end_mask_0, x = lookback_13_cast_fp16)[name = tensor<string, []>("lookback_15_cast_fp16")];
149
+ tensor<fp16, [1, 128, ?]> memory_17_cast_fp16 = add(x = var_209_cast_fp16, y = lookback_15_cast_fp16)[name = tensor<string, []>("memory_17_cast_fp16")];
150
+ tensor<string, []> lookahead_7_pad_type_0 = const()[name = tensor<string, []>("lookahead_7_pad_type_0"), val = tensor<string, []>("custom")];
151
+ tensor<int32, [2]> lookahead_7_pad_0 = const()[name = tensor<string, []>("lookahead_7_pad_0"), val = tensor<int32, [2]>([19, 19])];
152
+ tensor<int32, []> lookahead_7_groups_0 = const()[name = tensor<string, []>("lookahead_7_groups_0"), val = tensor<int32, []>(128)];
153
+ tensor<int32, [1]> lookahead_7_strides_0 = const()[name = tensor<string, []>("lookahead_7_strides_0"), val = tensor<int32, [1]>([1])];
154
+ tensor<int32, [1]> lookahead_7_dilations_0 = const()[name = tensor<string, []>("lookahead_7_dilations_0"), val = tensor<int32, [1]>([1])];
155
+ tensor<fp16, [128, 1, 20]> fsmns_2_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_2_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540032)))];
156
+ tensor<fp16, [1, 128, ?]> lookahead_7_cast_fp16 = conv(dilations = lookahead_7_dilations_0, groups = lookahead_7_groups_0, pad = lookahead_7_pad_0, pad_type = lookahead_7_pad_type_0, strides = lookahead_7_strides_0, weight = fsmns_2_fsmn_lookahead_filter_weight_to_fp16, x = var_209_cast_fp16)[name = tensor<string, []>("lookahead_7_cast_fp16")];
157
+ tensor<int32, [3]> input_41_begin_0 = const()[name = tensor<string, []>("input_41_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
158
+ tensor<int32, [3]> input_41_end_0 = const()[name = tensor<string, []>("input_41_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
159
+ tensor<bool, [3]> input_41_end_mask_0 = const()[name = tensor<string, []>("input_41_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
160
+ tensor<fp16, [1, 128, ?]> input_41_cast_fp16 = slice_by_index(begin = input_41_begin_0, end = input_41_end_0, end_mask = input_41_end_mask_0, x = lookahead_7_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")];
161
+ tensor<int32, [6]> var_231_pad_0 = const()[name = tensor<string, []>("op_231_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
162
+ tensor<string, []> var_231_mode_0 = const()[name = tensor<string, []>("op_231_mode_0"), val = tensor<string, []>("constant")];
163
+ tensor<fp16, []> const_3_to_fp16 = const()[name = tensor<string, []>("const_3_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
164
+ tensor<fp16, [1, 128, ?]> var_231_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = var_231_mode_0, pad = var_231_pad_0, x = input_41_cast_fp16)[name = tensor<string, []>("op_231_cast_fp16")];
165
+ tensor<fp16, [1, 128, ?]> memory_19_cast_fp16 = add(x = memory_17_cast_fp16, y = var_231_cast_fp16)[name = tensor<string, []>("memory_19_cast_fp16")];
166
+ tensor<int32, [3]> var_233 = const()[name = tensor<string, []>("op_233"), val = tensor<int32, [3]>([0, 2, 1])];
167
+ tensor<fp16, [1, ?, 128]> var_234_cast_fp16 = transpose(perm = var_233, x = memory_19_cast_fp16)[name = tensor<string, []>("transpose_8")];
168
+ tensor<fp16, [1, ?, 128]> input_43_cast_fp16 = add(x = var_234_cast_fp16, y = input_33_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
169
+ tensor<fp16, [256, 128]> fsmns_3_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_3_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(545216)))];
170
+ tensor<fp16, [256]> fsmns_3_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_3_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(610816)))];
171
+ tensor<fp16, [1, ?, 256]> linear_8_cast_fp16 = linear(bias = fsmns_3_fc1_0_bias_to_fp16, weight = fsmns_3_fc1_0_weight_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("linear_8_cast_fp16")];
172
+ tensor<fp16, [1, ?, 256]> input_47_cast_fp16 = relu(x = linear_8_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")];
173
+ tensor<fp16, [128, 256]> fsmns_3_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_3_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(611392)))];
174
+ tensor<fp16, [1, ?, 128]> linear_9_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_3_fc2_weight_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("linear_9_cast_fp16")];
175
+ tensor<int32, [3]> var_261 = const()[name = tensor<string, []>("op_261"), val = tensor<int32, [3]>([0, 2, 1])];
176
+ tensor<string, []> lookback_17_pad_type_0 = const()[name = tensor<string, []>("lookback_17_pad_type_0"), val = tensor<string, []>("custom")];
177
+ tensor<int32, [2]> lookback_17_pad_0 = const()[name = tensor<string, []>("lookback_17_pad_0"), val = tensor<int32, [2]>([19, 19])];
178
+ tensor<int32, []> lookback_17_groups_0 = const()[name = tensor<string, []>("lookback_17_groups_0"), val = tensor<int32, []>(128)];
179
+ tensor<int32, [1]> lookback_17_strides_0 = const()[name = tensor<string, []>("lookback_17_strides_0"), val = tensor<int32, [1]>([1])];
180
+ tensor<int32, [1]> lookback_17_dilations_0 = const()[name = tensor<string, []>("lookback_17_dilations_0"), val = tensor<int32, [1]>([1])];
181
+ tensor<fp16, [128, 1, 20]> fsmns_3_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_3_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(676992)))];
182
+ tensor<fp16, [1, 128, ?]> var_262_cast_fp16 = transpose(perm = var_261, x = linear_9_cast_fp16)[name = tensor<string, []>("transpose_7")];
183
+ tensor<fp16, [1, 128, ?]> lookback_17_cast_fp16 = conv(dilations = lookback_17_dilations_0, groups = lookback_17_groups_0, pad = lookback_17_pad_0, pad_type = lookback_17_pad_type_0, strides = lookback_17_strides_0, weight = fsmns_3_fsmn_lookback_filter_weight_to_fp16, x = var_262_cast_fp16)[name = tensor<string, []>("lookback_17_cast_fp16")];
184
+ tensor<int32, [3]> lookback_19_begin_0 = const()[name = tensor<string, []>("lookback_19_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
185
+ tensor<int32, [3]> lookback_19_end_0 = const()[name = tensor<string, []>("lookback_19_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
186
+ tensor<bool, [3]> lookback_19_end_mask_0 = const()[name = tensor<string, []>("lookback_19_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
187
+ tensor<fp16, [1, 128, ?]> lookback_19_cast_fp16 = slice_by_index(begin = lookback_19_begin_0, end = lookback_19_end_0, end_mask = lookback_19_end_mask_0, x = lookback_17_cast_fp16)[name = tensor<string, []>("lookback_19_cast_fp16")];
188
+ tensor<fp16, [1, 128, ?]> memory_23_cast_fp16 = add(x = var_262_cast_fp16, y = lookback_19_cast_fp16)[name = tensor<string, []>("memory_23_cast_fp16")];
189
+ tensor<string, []> lookahead_9_pad_type_0 = const()[name = tensor<string, []>("lookahead_9_pad_type_0"), val = tensor<string, []>("custom")];
190
+ tensor<int32, [2]> lookahead_9_pad_0 = const()[name = tensor<string, []>("lookahead_9_pad_0"), val = tensor<int32, [2]>([19, 19])];
191
+ tensor<int32, []> lookahead_9_groups_0 = const()[name = tensor<string, []>("lookahead_9_groups_0"), val = tensor<int32, []>(128)];
192
+ tensor<int32, [1]> lookahead_9_strides_0 = const()[name = tensor<string, []>("lookahead_9_strides_0"), val = tensor<int32, [1]>([1])];
193
+ tensor<int32, [1]> lookahead_9_dilations_0 = const()[name = tensor<string, []>("lookahead_9_dilations_0"), val = tensor<int32, [1]>([1])];
194
+ tensor<fp16, [128, 1, 20]> fsmns_3_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_3_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(682176)))];
195
+ tensor<fp16, [1, 128, ?]> lookahead_9_cast_fp16 = conv(dilations = lookahead_9_dilations_0, groups = lookahead_9_groups_0, pad = lookahead_9_pad_0, pad_type = lookahead_9_pad_type_0, strides = lookahead_9_strides_0, weight = fsmns_3_fsmn_lookahead_filter_weight_to_fp16, x = var_262_cast_fp16)[name = tensor<string, []>("lookahead_9_cast_fp16")];
196
+ tensor<int32, [3]> input_51_begin_0 = const()[name = tensor<string, []>("input_51_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
197
+ tensor<int32, [3]> input_51_end_0 = const()[name = tensor<string, []>("input_51_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
198
+ tensor<bool, [3]> input_51_end_mask_0 = const()[name = tensor<string, []>("input_51_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
199
+ tensor<fp16, [1, 128, ?]> input_51_cast_fp16 = slice_by_index(begin = input_51_begin_0, end = input_51_end_0, end_mask = input_51_end_mask_0, x = lookahead_9_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
200
+ tensor<int32, [6]> var_284_pad_0 = const()[name = tensor<string, []>("op_284_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
201
+ tensor<string, []> var_284_mode_0 = const()[name = tensor<string, []>("op_284_mode_0"), val = tensor<string, []>("constant")];
202
+ tensor<fp16, []> const_4_to_fp16 = const()[name = tensor<string, []>("const_4_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
203
+ tensor<fp16, [1, 128, ?]> var_284_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = var_284_mode_0, pad = var_284_pad_0, x = input_51_cast_fp16)[name = tensor<string, []>("op_284_cast_fp16")];
204
+ tensor<fp16, [1, 128, ?]> memory_25_cast_fp16 = add(x = memory_23_cast_fp16, y = var_284_cast_fp16)[name = tensor<string, []>("memory_25_cast_fp16")];
205
+ tensor<int32, [3]> var_286 = const()[name = tensor<string, []>("op_286"), val = tensor<int32, [3]>([0, 2, 1])];
206
+ tensor<fp16, [1, ?, 128]> var_287_cast_fp16 = transpose(perm = var_286, x = memory_25_cast_fp16)[name = tensor<string, []>("transpose_6")];
207
+ tensor<fp16, [1, ?, 128]> input_53_cast_fp16 = add(x = var_287_cast_fp16, y = input_43_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
208
+ tensor<fp16, [256, 128]> fsmns_4_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_4_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687360)))];
209
+ tensor<fp16, [256]> fsmns_4_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_4_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(752960)))];
210
+ tensor<fp16, [1, ?, 256]> linear_10_cast_fp16 = linear(bias = fsmns_4_fc1_0_bias_to_fp16, weight = fsmns_4_fc1_0_weight_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("linear_10_cast_fp16")];
211
+ tensor<fp16, [1, ?, 256]> input_57_cast_fp16 = relu(x = linear_10_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")];
212
+ tensor<fp16, [128, 256]> fsmns_4_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_4_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(753536)))];
213
+ tensor<fp16, [1, ?, 128]> linear_11_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_4_fc2_weight_to_fp16, x = input_57_cast_fp16)[name = tensor<string, []>("linear_11_cast_fp16")];
214
+ tensor<int32, [3]> var_314 = const()[name = tensor<string, []>("op_314"), val = tensor<int32, [3]>([0, 2, 1])];
215
+ tensor<string, []> lookback_21_pad_type_0 = const()[name = tensor<string, []>("lookback_21_pad_type_0"), val = tensor<string, []>("custom")];
216
+ tensor<int32, [2]> lookback_21_pad_0 = const()[name = tensor<string, []>("lookback_21_pad_0"), val = tensor<int32, [2]>([19, 19])];
217
+ tensor<int32, []> lookback_21_groups_0 = const()[name = tensor<string, []>("lookback_21_groups_0"), val = tensor<int32, []>(128)];
218
+ tensor<int32, [1]> lookback_21_strides_0 = const()[name = tensor<string, []>("lookback_21_strides_0"), val = tensor<int32, [1]>([1])];
219
+ tensor<int32, [1]> lookback_21_dilations_0 = const()[name = tensor<string, []>("lookback_21_dilations_0"), val = tensor<int32, [1]>([1])];
220
+ tensor<fp16, [128, 1, 20]> fsmns_4_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_4_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819136)))];
221
+ tensor<fp16, [1, 128, ?]> var_315_cast_fp16 = transpose(perm = var_314, x = linear_11_cast_fp16)[name = tensor<string, []>("transpose_5")];
222
+ tensor<fp16, [1, 128, ?]> lookback_21_cast_fp16 = conv(dilations = lookback_21_dilations_0, groups = lookback_21_groups_0, pad = lookback_21_pad_0, pad_type = lookback_21_pad_type_0, strides = lookback_21_strides_0, weight = fsmns_4_fsmn_lookback_filter_weight_to_fp16, x = var_315_cast_fp16)[name = tensor<string, []>("lookback_21_cast_fp16")];
223
+ tensor<int32, [3]> lookback_23_begin_0 = const()[name = tensor<string, []>("lookback_23_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
224
+ tensor<int32, [3]> lookback_23_end_0 = const()[name = tensor<string, []>("lookback_23_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
225
+ tensor<bool, [3]> lookback_23_end_mask_0 = const()[name = tensor<string, []>("lookback_23_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
226
+ tensor<fp16, [1, 128, ?]> lookback_23_cast_fp16 = slice_by_index(begin = lookback_23_begin_0, end = lookback_23_end_0, end_mask = lookback_23_end_mask_0, x = lookback_21_cast_fp16)[name = tensor<string, []>("lookback_23_cast_fp16")];
227
+ tensor<fp16, [1, 128, ?]> memory_29_cast_fp16 = add(x = var_315_cast_fp16, y = lookback_23_cast_fp16)[name = tensor<string, []>("memory_29_cast_fp16")];
228
+ tensor<string, []> lookahead_11_pad_type_0 = const()[name = tensor<string, []>("lookahead_11_pad_type_0"), val = tensor<string, []>("custom")];
229
+ tensor<int32, [2]> lookahead_11_pad_0 = const()[name = tensor<string, []>("lookahead_11_pad_0"), val = tensor<int32, [2]>([19, 19])];
230
+ tensor<int32, []> lookahead_11_groups_0 = const()[name = tensor<string, []>("lookahead_11_groups_0"), val = tensor<int32, []>(128)];
231
+ tensor<int32, [1]> lookahead_11_strides_0 = const()[name = tensor<string, []>("lookahead_11_strides_0"), val = tensor<int32, [1]>([1])];
232
+ tensor<int32, [1]> lookahead_11_dilations_0 = const()[name = tensor<string, []>("lookahead_11_dilations_0"), val = tensor<int32, [1]>([1])];
233
+ tensor<fp16, [128, 1, 20]> fsmns_4_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_4_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(824320)))];
234
+ tensor<fp16, [1, 128, ?]> lookahead_11_cast_fp16 = conv(dilations = lookahead_11_dilations_0, groups = lookahead_11_groups_0, pad = lookahead_11_pad_0, pad_type = lookahead_11_pad_type_0, strides = lookahead_11_strides_0, weight = fsmns_4_fsmn_lookahead_filter_weight_to_fp16, x = var_315_cast_fp16)[name = tensor<string, []>("lookahead_11_cast_fp16")];
235
+ tensor<int32, [3]> input_61_begin_0 = const()[name = tensor<string, []>("input_61_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
236
+ tensor<int32, [3]> input_61_end_0 = const()[name = tensor<string, []>("input_61_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
237
+ tensor<bool, [3]> input_61_end_mask_0 = const()[name = tensor<string, []>("input_61_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
238
+ tensor<fp16, [1, 128, ?]> input_61_cast_fp16 = slice_by_index(begin = input_61_begin_0, end = input_61_end_0, end_mask = input_61_end_mask_0, x = lookahead_11_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
239
+ tensor<int32, [6]> var_337_pad_0 = const()[name = tensor<string, []>("op_337_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
240
+ tensor<string, []> var_337_mode_0 = const()[name = tensor<string, []>("op_337_mode_0"), val = tensor<string, []>("constant")];
241
+ tensor<fp16, []> const_5_to_fp16 = const()[name = tensor<string, []>("const_5_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
242
+ tensor<fp16, [1, 128, ?]> var_337_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = var_337_mode_0, pad = var_337_pad_0, x = input_61_cast_fp16)[name = tensor<string, []>("op_337_cast_fp16")];
243
+ tensor<fp16, [1, 128, ?]> memory_31_cast_fp16 = add(x = memory_29_cast_fp16, y = var_337_cast_fp16)[name = tensor<string, []>("memory_31_cast_fp16")];
244
+ tensor<int32, [3]> var_339 = const()[name = tensor<string, []>("op_339"), val = tensor<int32, [3]>([0, 2, 1])];
245
+ tensor<fp16, [1, ?, 128]> var_340_cast_fp16 = transpose(perm = var_339, x = memory_31_cast_fp16)[name = tensor<string, []>("transpose_4")];
246
+ tensor<fp16, [1, ?, 128]> input_63_cast_fp16 = add(x = var_340_cast_fp16, y = input_53_cast_fp16)[name = tensor<string, []>("input_63_cast_fp16")];
247
+ tensor<fp16, [256, 128]> fsmns_5_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_5_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(829504)))];
248
+ tensor<fp16, [256]> fsmns_5_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_5_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(895104)))];
249
+ tensor<fp16, [1, ?, 256]> linear_12_cast_fp16 = linear(bias = fsmns_5_fc1_0_bias_to_fp16, weight = fsmns_5_fc1_0_weight_to_fp16, x = input_63_cast_fp16)[name = tensor<string, []>("linear_12_cast_fp16")];
250
+ tensor<fp16, [1, ?, 256]> input_67_cast_fp16 = relu(x = linear_12_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
251
+ tensor<fp16, [128, 256]> fsmns_5_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_5_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(895680)))];
252
+ tensor<fp16, [1, ?, 128]> linear_13_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_5_fc2_weight_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("linear_13_cast_fp16")];
253
+ tensor<int32, [3]> var_367 = const()[name = tensor<string, []>("op_367"), val = tensor<int32, [3]>([0, 2, 1])];
254
+ tensor<string, []> lookback_25_pad_type_0 = const()[name = tensor<string, []>("lookback_25_pad_type_0"), val = tensor<string, []>("custom")];
255
+ tensor<int32, [2]> lookback_25_pad_0 = const()[name = tensor<string, []>("lookback_25_pad_0"), val = tensor<int32, [2]>([19, 19])];
256
+ tensor<int32, []> lookback_25_groups_0 = const()[name = tensor<string, []>("lookback_25_groups_0"), val = tensor<int32, []>(128)];
257
+ tensor<int32, [1]> lookback_25_strides_0 = const()[name = tensor<string, []>("lookback_25_strides_0"), val = tensor<int32, [1]>([1])];
258
+ tensor<int32, [1]> lookback_25_dilations_0 = const()[name = tensor<string, []>("lookback_25_dilations_0"), val = tensor<int32, [1]>([1])];
259
+ tensor<fp16, [128, 1, 20]> fsmns_5_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_5_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(961280)))];
260
+ tensor<fp16, [1, 128, ?]> var_368_cast_fp16 = transpose(perm = var_367, x = linear_13_cast_fp16)[name = tensor<string, []>("transpose_3")];
261
+ tensor<fp16, [1, 128, ?]> lookback_25_cast_fp16 = conv(dilations = lookback_25_dilations_0, groups = lookback_25_groups_0, pad = lookback_25_pad_0, pad_type = lookback_25_pad_type_0, strides = lookback_25_strides_0, weight = fsmns_5_fsmn_lookback_filter_weight_to_fp16, x = var_368_cast_fp16)[name = tensor<string, []>("lookback_25_cast_fp16")];
262
+ tensor<int32, [3]> lookback_27_begin_0 = const()[name = tensor<string, []>("lookback_27_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
263
+ tensor<int32, [3]> lookback_27_end_0 = const()[name = tensor<string, []>("lookback_27_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
264
+ tensor<bool, [3]> lookback_27_end_mask_0 = const()[name = tensor<string, []>("lookback_27_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
265
+ tensor<fp16, [1, 128, ?]> lookback_27_cast_fp16 = slice_by_index(begin = lookback_27_begin_0, end = lookback_27_end_0, end_mask = lookback_27_end_mask_0, x = lookback_25_cast_fp16)[name = tensor<string, []>("lookback_27_cast_fp16")];
266
+ tensor<fp16, [1, 128, ?]> memory_35_cast_fp16 = add(x = var_368_cast_fp16, y = lookback_27_cast_fp16)[name = tensor<string, []>("memory_35_cast_fp16")];
267
+ tensor<string, []> lookahead_13_pad_type_0 = const()[name = tensor<string, []>("lookahead_13_pad_type_0"), val = tensor<string, []>("custom")];
268
+ tensor<int32, [2]> lookahead_13_pad_0 = const()[name = tensor<string, []>("lookahead_13_pad_0"), val = tensor<int32, [2]>([19, 19])];
269
+ tensor<int32, []> lookahead_13_groups_0 = const()[name = tensor<string, []>("lookahead_13_groups_0"), val = tensor<int32, []>(128)];
270
+ tensor<int32, [1]> lookahead_13_strides_0 = const()[name = tensor<string, []>("lookahead_13_strides_0"), val = tensor<int32, [1]>([1])];
271
+ tensor<int32, [1]> lookahead_13_dilations_0 = const()[name = tensor<string, []>("lookahead_13_dilations_0"), val = tensor<int32, [1]>([1])];
272
+ tensor<fp16, [128, 1, 20]> fsmns_5_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_5_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966464)))];
273
+ tensor<fp16, [1, 128, ?]> lookahead_13_cast_fp16 = conv(dilations = lookahead_13_dilations_0, groups = lookahead_13_groups_0, pad = lookahead_13_pad_0, pad_type = lookahead_13_pad_type_0, strides = lookahead_13_strides_0, weight = fsmns_5_fsmn_lookahead_filter_weight_to_fp16, x = var_368_cast_fp16)[name = tensor<string, []>("lookahead_13_cast_fp16")];
274
+ tensor<int32, [3]> input_71_begin_0 = const()[name = tensor<string, []>("input_71_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
275
+ tensor<int32, [3]> input_71_end_0 = const()[name = tensor<string, []>("input_71_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
276
+ tensor<bool, [3]> input_71_end_mask_0 = const()[name = tensor<string, []>("input_71_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
277
+ tensor<fp16, [1, 128, ?]> input_71_cast_fp16 = slice_by_index(begin = input_71_begin_0, end = input_71_end_0, end_mask = input_71_end_mask_0, x = lookahead_13_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
278
+ tensor<int32, [6]> var_390_pad_0 = const()[name = tensor<string, []>("op_390_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
279
+ tensor<string, []> var_390_mode_0 = const()[name = tensor<string, []>("op_390_mode_0"), val = tensor<string, []>("constant")];
280
+ tensor<fp16, []> const_6_to_fp16 = const()[name = tensor<string, []>("const_6_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
281
+ tensor<fp16, [1, 128, ?]> var_390_cast_fp16 = pad(constant_val = const_6_to_fp16, mode = var_390_mode_0, pad = var_390_pad_0, x = input_71_cast_fp16)[name = tensor<string, []>("op_390_cast_fp16")];
282
+ tensor<fp16, [1, 128, ?]> memory_37_cast_fp16 = add(x = memory_35_cast_fp16, y = var_390_cast_fp16)[name = tensor<string, []>("memory_37_cast_fp16")];
283
+ tensor<int32, [3]> var_392 = const()[name = tensor<string, []>("op_392"), val = tensor<int32, [3]>([0, 2, 1])];
284
+ tensor<fp16, [1, ?, 128]> var_393_cast_fp16 = transpose(perm = var_392, x = memory_37_cast_fp16)[name = tensor<string, []>("transpose_2")];
285
+ tensor<fp16, [1, ?, 128]> input_73_cast_fp16 = add(x = var_393_cast_fp16, y = input_63_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
286
+ tensor<fp16, [256, 128]> fsmns_6_fc1_0_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_6_fc1_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(971648)))];
287
+ tensor<fp16, [256]> fsmns_6_fc1_0_bias_to_fp16 = const()[name = tensor<string, []>("fsmns_6_fc1_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1037248)))];
288
+ tensor<fp16, [1, ?, 256]> linear_14_cast_fp16 = linear(bias = fsmns_6_fc1_0_bias_to_fp16, weight = fsmns_6_fc1_0_weight_to_fp16, x = input_73_cast_fp16)[name = tensor<string, []>("linear_14_cast_fp16")];
289
+ tensor<fp16, [1, ?, 256]> input_77_cast_fp16 = relu(x = linear_14_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
290
+ tensor<fp16, [128, 256]> fsmns_6_fc2_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_6_fc2_weight_to_fp16"), val = tensor<fp16, [128, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1037824)))];
291
+ tensor<fp16, [1, ?, 128]> linear_15_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = fsmns_6_fc2_weight_to_fp16, x = input_77_cast_fp16)[name = tensor<string, []>("linear_15_cast_fp16")];
292
+ tensor<int32, [3]> var_420 = const()[name = tensor<string, []>("op_420"), val = tensor<int32, [3]>([0, 2, 1])];
293
+ tensor<string, []> lookback_29_pad_type_0 = const()[name = tensor<string, []>("lookback_29_pad_type_0"), val = tensor<string, []>("custom")];
294
+ tensor<int32, [2]> lookback_29_pad_0 = const()[name = tensor<string, []>("lookback_29_pad_0"), val = tensor<int32, [2]>([19, 19])];
295
+ tensor<int32, []> lookback_29_groups_0 = const()[name = tensor<string, []>("lookback_29_groups_0"), val = tensor<int32, []>(128)];
296
+ tensor<int32, [1]> lookback_29_strides_0 = const()[name = tensor<string, []>("lookback_29_strides_0"), val = tensor<int32, [1]>([1])];
297
+ tensor<int32, [1]> lookback_29_dilations_0 = const()[name = tensor<string, []>("lookback_29_dilations_0"), val = tensor<int32, [1]>([1])];
298
+ tensor<fp16, [128, 1, 20]> fsmns_6_fsmn_lookback_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_6_fsmn_lookback_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1103424)))];
299
+ tensor<fp16, [1, 128, ?]> var_421_cast_fp16 = transpose(perm = var_420, x = linear_15_cast_fp16)[name = tensor<string, []>("transpose_1")];
300
+ tensor<fp16, [1, 128, ?]> lookback_29_cast_fp16 = conv(dilations = lookback_29_dilations_0, groups = lookback_29_groups_0, pad = lookback_29_pad_0, pad_type = lookback_29_pad_type_0, strides = lookback_29_strides_0, weight = fsmns_6_fsmn_lookback_filter_weight_to_fp16, x = var_421_cast_fp16)[name = tensor<string, []>("lookback_29_cast_fp16")];
301
+ tensor<int32, [3]> lookback_begin_0 = const()[name = tensor<string, []>("lookback_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
302
+ tensor<int32, [3]> lookback_end_0 = const()[name = tensor<string, []>("lookback_end_0"), val = tensor<int32, [3]>([1, 128, -19])];
303
+ tensor<bool, [3]> lookback_end_mask_0 = const()[name = tensor<string, []>("lookback_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
304
+ tensor<fp16, [1, 128, ?]> lookback_cast_fp16 = slice_by_index(begin = lookback_begin_0, end = lookback_end_0, end_mask = lookback_end_mask_0, x = lookback_29_cast_fp16)[name = tensor<string, []>("lookback_cast_fp16")];
305
+ tensor<fp16, [1, 128, ?]> memory_41_cast_fp16 = add(x = var_421_cast_fp16, y = lookback_cast_fp16)[name = tensor<string, []>("memory_41_cast_fp16")];
306
+ tensor<string, []> lookahead_pad_type_0 = const()[name = tensor<string, []>("lookahead_pad_type_0"), val = tensor<string, []>("custom")];
307
+ tensor<int32, [2]> lookahead_pad_0 = const()[name = tensor<string, []>("lookahead_pad_0"), val = tensor<int32, [2]>([19, 19])];
308
+ tensor<int32, []> lookahead_groups_0 = const()[name = tensor<string, []>("lookahead_groups_0"), val = tensor<int32, []>(128)];
309
+ tensor<int32, [1]> lookahead_strides_0 = const()[name = tensor<string, []>("lookahead_strides_0"), val = tensor<int32, [1]>([1])];
310
+ tensor<int32, [1]> lookahead_dilations_0 = const()[name = tensor<string, []>("lookahead_dilations_0"), val = tensor<int32, [1]>([1])];
311
+ tensor<fp16, [128, 1, 20]> fsmns_6_fsmn_lookahead_filter_weight_to_fp16 = const()[name = tensor<string, []>("fsmns_6_fsmn_lookahead_filter_weight_to_fp16"), val = tensor<fp16, [128, 1, 20]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1108608)))];
312
+ tensor<fp16, [1, 128, ?]> lookahead_cast_fp16 = conv(dilations = lookahead_dilations_0, groups = lookahead_groups_0, pad = lookahead_pad_0, pad_type = lookahead_pad_type_0, strides = lookahead_strides_0, weight = fsmns_6_fsmn_lookahead_filter_weight_to_fp16, x = var_421_cast_fp16)[name = tensor<string, []>("lookahead_cast_fp16")];
313
+ tensor<int32, [3]> input_81_begin_0 = const()[name = tensor<string, []>("input_81_begin_0"), val = tensor<int32, [3]>([0, 0, 20])];
314
+ tensor<int32, [3]> input_81_end_0 = const()[name = tensor<string, []>("input_81_end_0"), val = tensor<int32, [3]>([1, 128, 0])];
315
+ tensor<bool, [3]> input_81_end_mask_0 = const()[name = tensor<string, []>("input_81_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
316
+ tensor<fp16, [1, 128, ?]> input_81_cast_fp16 = slice_by_index(begin = input_81_begin_0, end = input_81_end_0, end_mask = input_81_end_mask_0, x = lookahead_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
317
+ tensor<int32, [6]> var_443_pad_0 = const()[name = tensor<string, []>("op_443_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 1])];
318
+ tensor<string, []> var_443_mode_0 = const()[name = tensor<string, []>("op_443_mode_0"), val = tensor<string, []>("constant")];
319
+ tensor<fp16, []> const_7_to_fp16 = const()[name = tensor<string, []>("const_7_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
320
+ tensor<fp16, [1, 128, ?]> var_443_cast_fp16 = pad(constant_val = const_7_to_fp16, mode = var_443_mode_0, pad = var_443_pad_0, x = input_81_cast_fp16)[name = tensor<string, []>("op_443_cast_fp16")];
321
+ tensor<fp16, [1, 128, ?]> memory_43_cast_fp16 = add(x = memory_41_cast_fp16, y = var_443_cast_fp16)[name = tensor<string, []>("memory_43_cast_fp16")];
322
+ tensor<int32, [3]> var_445 = const()[name = tensor<string, []>("op_445"), val = tensor<int32, [3]>([0, 2, 1])];
323
+ tensor<fp16, [1, ?, 128]> var_446_cast_fp16 = transpose(perm = var_445, x = memory_43_cast_fp16)[name = tensor<string, []>("transpose_0")];
324
+ tensor<fp16, [1, ?, 128]> input_83_cast_fp16 = add(x = var_446_cast_fp16, y = input_73_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
325
+ tensor<fp16, [256, 128]> dnns_0_weight_to_fp16 = const()[name = tensor<string, []>("dnns_0_weight_to_fp16"), val = tensor<fp16, [256, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1113792)))];
326
+ tensor<fp16, [256]> dnns_0_bias_to_fp16 = const()[name = tensor<string, []>("dnns_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1179392)))];
327
+ tensor<fp16, [1, ?, 256]> linear_16_cast_fp16 = linear(bias = dnns_0_bias_to_fp16, weight = dnns_0_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("linear_16_cast_fp16")];
328
+ tensor<fp16, [1, ?, 256]> input_cast_fp16 = relu(x = linear_16_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
329
+ tensor<fp16, [1, 256]> out_weight_to_fp16 = const()[name = tensor<string, []>("out_weight_to_fp16"), val = tensor<fp16, [1, 256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1179968)))];
330
+ tensor<fp16, [1]> out_bias_to_fp16 = const()[name = tensor<string, []>("out_bias_to_fp16"), val = tensor<fp16, [1]>([0x1.9p-5])];
331
+ tensor<fp16, [1, ?, 1]> linear_17_cast_fp16 = linear(bias = out_bias_to_fp16, weight = out_weight_to_fp16, x = input_cast_fp16)[name = tensor<string, []>("linear_17_cast_fp16")];
332
+ tensor<fp16, [1, ?, 1]> probabilities = sigmoid(x = linear_17_cast_fp16)[name = tensor<string, []>("op_457_cast_fp16")];
333
+ } -> (probabilities);
334
+ }
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+ "name": "weights",
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+ "path": "com.apple.CoreML/weights"
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+ },
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+ "description": "CoreML Model Specification",
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