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https://github.com/modelscope/FunASR
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2
.github/workflows/UnitTest.yml
vendored
2
.github/workflows/UnitTest.yml
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@ -6,9 +6,7 @@ on:
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- main
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- main
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push:
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push:
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branches:
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branches:
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- dev_wjm
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- dev_jy
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- dev_jy
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- dev_wjm_infer
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jobs:
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jobs:
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build:
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build:
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1
.github/workflows/main.yml
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1
.github/workflows/main.yml
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@ -5,7 +5,6 @@ on:
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- main
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- main
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push:
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push:
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branches:
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branches:
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- dev_wjm
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- main
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- main
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- dev_lyh
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- dev_lyh
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@ -34,20 +34,27 @@ decoder_conf:
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self_attention_dropout_rate: 0.
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self_attention_dropout_rate: 0.
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src_attention_dropout_rate: 0.
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src_attention_dropout_rate: 0.
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# frontend related
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frontend: wav_frontend
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frontend_conf:
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fs: 16000
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window: hamming
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n_mels: 80
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frame_length: 25
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frame_shift: 10
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lfr_m: 1
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lfr_n: 1
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# hybrid CTC/attention
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# hybrid CTC/attention
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model_conf:
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model_conf:
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ctc_weight: 0.3
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ctc_weight: 0.3
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lsm_weight: 0.1 # label smoothing option
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lsm_weight: 0.1 # label smoothing option
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length_normalized_loss: false
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length_normalized_loss: false
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# minibatch related
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batch_type: numel
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batch_bins: 25000000
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# optimization related
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# optimization related
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accum_grad: 1
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accum_grad: 1
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grad_clip: 5
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grad_clip: 5
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max_epoch: 60
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max_epoch: 180
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val_scheduler_criterion:
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val_scheduler_criterion:
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- valid
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- valid
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- acc
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- acc
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@ -65,10 +72,6 @@ scheduler: warmuplr
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scheduler_conf:
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scheduler_conf:
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warmup_steps: 35000
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warmup_steps: 35000
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num_workers: 4 # num of workers of data loader
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use_amp: true # automatic mixed precision
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unused_parameters: false # set as true if some params are unused in DDP
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specaug: specaug
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specaug: specaug
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specaug_conf:
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specaug_conf:
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apply_time_warp: true
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apply_time_warp: true
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@ -84,3 +87,18 @@ specaug_conf:
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- 0.
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- 0.
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- 0.05
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- 0.05
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num_time_mask: 10
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num_time_mask: 10
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dataset_conf:
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data_names: speech,text
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data_types: sound,text
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shuffle: True
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shuffle_conf:
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shuffle_size: 2048
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sort_size: 500
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batch_conf:
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batch_type: token
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batch_size: 25000
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num_workers: 8
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log_interval: 50
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normalize: None
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@ -3,8 +3,8 @@
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. ./path.sh || exit 1;
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. ./path.sh || exit 1;
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# machines configuration
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# machines configuration
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CUDA_VISIBLE_DEVICES="0,1"
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CUDA_VISIBLE_DEVICES="0,1,2,3"
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gpu_num=2
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gpu_num=4
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count=1
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count=1
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gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding
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gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding
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# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
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# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
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