Upload folder using huggingface_hub
Browse files- cmvn.json +166 -0
- config.json +21 -0
- fireredvad.mlmodelc/analytics/coremldata.bin +3 -0
- fireredvad.mlmodelc/coremldata.bin +3 -0
- fireredvad.mlmodelc/model.mil +334 -0
- fireredvad.mlmodelc/weights/weight.bin +3 -0
- fireredvad.mlpackage/Data/com.apple.CoreML/model.mlmodel +3 -0
- fireredvad.mlpackage/Data/com.apple.CoreML/weights/weight.bin +3 -0
- fireredvad.mlpackage/Manifest.json +18 -0
cmvn.json
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}
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config.json
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{
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| 2 |
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"model_type": "fireredvad_coreml",
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| 3 |
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"architecture": "DFSMN",
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| 4 |
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"num_params": 588417,
|
| 5 |
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"sample_rate": 16000,
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| 6 |
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"frame_length_ms": 25,
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| 7 |
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"frame_shift_ms": 10,
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| 8 |
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"num_mel_bins": 80,
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| 9 |
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"dfsmn_blocks": 8,
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| 10 |
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"dnn_layers": 1,
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| 11 |
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"hidden_size": 256,
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| 12 |
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"projection_size": 128,
|
| 13 |
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"lookback_order": 20,
|
| 14 |
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"lookback_stride": 1,
|
| 15 |
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"lookahead_order": 20,
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| 16 |
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"lookahead_stride": 1,
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| 17 |
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"output_dim": 1,
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| 18 |
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"cmvn_embedded": true,
|
| 19 |
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"compute_precision": "float16",
|
| 20 |
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"quantization": null
|
| 21 |
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}
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fireredvad.mlmodelc/analytics/coremldata.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:9f1b7717caef2d4e56c0149d1b825829ed4587ce219c825ed34a32736ef8feb7
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| 3 |
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size 243
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fireredvad.mlmodelc/coremldata.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c9c698bf3dbe8c4792f3cc1fbc15b0995b8d0ab38b94475062b3d087ff292f4
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| 3 |
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size 398
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fireredvad.mlmodelc/model.mil
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|
| 1 |
+
program(1.0)
|
| 2 |
+
[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"}})]
|
| 3 |
+
{
|
| 4 |
+
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]]}})))] {
|
| 5 |
+
tensor<string, []> features_to_fp16_dtype_0 = const()[name = tensor<string, []>("features_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
|
| 6 |
+
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)))];
|
| 7 |
+
tensor<fp16, [1, ?, 80]> features_to_fp16 = cast(dtype = features_to_fp16_dtype_0, x = features)[name = tensor<string, []>("cast_1")];
|
| 8 |
+
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")];
|
| 9 |
+
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)))];
|
| 10 |
+
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")];
|
| 11 |
+
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)))];
|
| 12 |
+
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)))];
|
| 13 |
+
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")];
|
| 14 |
+
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)))];
|
| 16 |
+
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 |
+
}
|
fireredvad.mlmodelc/weights/weight.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3e33ae44922bcdaf668d4b18b16fc0e29acec582be810d6a5d58fc56cd27e81d
|
| 3 |
+
size 1180544
|
fireredvad.mlpackage/Data/com.apple.CoreML/model.mlmodel
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d7da93adc644b2cb07b21497afc2e60e6650ca4724e7b026761c1df01f5af378
|
| 3 |
+
size 52222
|
fireredvad.mlpackage/Data/com.apple.CoreML/weights/weight.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3e33ae44922bcdaf668d4b18b16fc0e29acec582be810d6a5d58fc56cd27e81d
|
| 3 |
+
size 1180544
|
fireredvad.mlpackage/Manifest.json
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"fileFormatVersion": "1.0.0",
|
| 3 |
+
"itemInfoEntries": {
|
| 4 |
+
"0BC5D808-AACD-44C4-B06A-48D630C404F5": {
|
| 5 |
+
"author": "com.apple.CoreML",
|
| 6 |
+
"description": "CoreML Model Weights",
|
| 7 |
+
"name": "weights",
|
| 8 |
+
"path": "com.apple.CoreML/weights"
|
| 9 |
+
},
|
| 10 |
+
"EE85C645-0DF9-48B2-AE17-CB463BA22FEF": {
|
| 11 |
+
"author": "com.apple.CoreML",
|
| 12 |
+
"description": "CoreML Model Specification",
|
| 13 |
+
"name": "model.mlmodel",
|
| 14 |
+
"path": "com.apple.CoreML/model.mlmodel"
|
| 15 |
+
}
|
| 16 |
+
},
|
| 17 |
+
"rootModelIdentifier": "EE85C645-0DF9-48B2-AE17-CB463BA22FEF"
|
| 18 |
+
}
|