formatting
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0942092426
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@ -1,15 +1,10 @@
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dataset_conf:
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dataset_conf:
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filter_conf:
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filter_conf:
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max_length: 2048
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max_length: 2048
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min_length: 0
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min_length: 0
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resample_conf:
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resample_conf:
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resample_rate: 16000
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resample_rate: 16000
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speed_perturb: false
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speed_perturb: false
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feature_extraction_conf:
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feature_extraction_conf:
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feature_type: 'mfcc'
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feature_type: 'mfcc'
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num_ceps: 80
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num_ceps: 80
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@ -17,17 +12,13 @@ dataset_conf:
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frame_shift: 10
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frame_shift: 10
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frame_length: 25
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frame_length: 25
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dither: 1.0
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dither: 1.0
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feature_dither: 0.0
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feature_dither: 0.0
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spec_aug: true
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spec_aug: true
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spec_aug_conf:
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spec_aug_conf:
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#warp_for_time: false
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num_t_mask: 1
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num_t_mask: 1
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num_f_mask: 1
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num_f_mask: 1
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max_t: 20
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max_t: 20
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max_f: 40
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max_f: 40
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shuffle: true
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shuffle: true
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shuffle_conf:
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shuffle_conf:
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shuffle_size: 1500
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shuffle_size: 1500
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@ -35,8 +26,6 @@ dataset_conf:
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batch_size: 100
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batch_size: 100
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model:
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model:
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input_dim: 80
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output_dim: 2
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hidden_dim: 64
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hidden_dim: 64
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preprocessing:
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preprocessing:
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type: none
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type: none
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@ -50,7 +39,6 @@ model:
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optim: adam
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optim: adam
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optim_conf:
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optim_conf:
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lr: 0.001
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lr: 0.001
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#warmup_step: 2000
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training_config:
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training_config:
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grad_clip: 5
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grad_clip: 5
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@ -161,9 +161,9 @@ def main():
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# !!!IMPORTANT!!!
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# !!!IMPORTANT!!!
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# Try to export the model by script, if fails, we should refine
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# Try to export the model by script, if fails, we should refine
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# the code to satisfy the script export requirements
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# the code to satisfy the script export requirements
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#if args.rank == 0:
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# if args.rank == 0:
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#script_model = torch.jit.script(model)
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# script_model = torch.jit.script(model)
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#script_model.save(os.path.join(args.model_dir, 'init.zip'))
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# script_model.save(os.path.join(args.model_dir, 'init.zip'))
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executor = Executor()
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executor = Executor()
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# If specify checkpoint, load some info from checkpoint
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# If specify checkpoint, load some info from checkpoint
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if args.checkpoint is not None:
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if args.checkpoint is not None:
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@ -13,7 +13,6 @@
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# limitations under the License.
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# limitations under the License.
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import torch
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import torch
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import torch.nn.functional as F
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from kws.utils.mask import padding_mask
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from kws.utils.mask import padding_mask
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@ -13,8 +13,6 @@
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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import numpy as np
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import torch
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import torch
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import torch.nn as nn
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import torch.nn as nn
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import torch.nn.functional as F
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import torch.nn.functional as F
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@ -13,7 +13,7 @@
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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from typing import List, Optional
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from typing import Optional
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import torch
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import torch
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import torch.nn as nn
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import torch.nn as nn
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