Delete ASR-model

delete old ASR-model

ASR-model/TransformerLM_seg_char/env.log

@@ -1,195 +0,0 @@
-SpeechBrain system description
-==============================
-Python version:
-3.8.10 (default, Jun  2 2021, 10:49:15) 
-[GCC 9.4.0]
-==============================
-Installed Python packages:
-appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-keyring==18.0.1
-kiwisolver==1.3.1
-language-selector==0.1
-launchpadlib==1.10.13
-lazr.restfulclient==0.14.2
-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-nvidia-ml-py3==7.352.0
-oauthlib==3.1.0
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-==============================
-Git revision:
-e3e51338
-==============================
-Cuda version:
-10.2

ASR-model/TransformerLM_seg_char/hyperparams.yaml

@@ -1,95 +0,0 @@
-# Generated 2021-10-05 from:
-# /mnt/md0/user_wayne/speechbrain/recipes/MATBN/LM/hparams/TransformerLM_seg_char.yaml
-# yamllint disable
-output_folder: results/TransformerLM_seg_char
-save_folder: results/TransformerLM_seg_char/save
-train_log: results/TransformerLM_seg_char/train_log.txt
-num_workers: 4
-
-data_folder: results/prepare_seg
-
-tokenizer_file: results/tokenizer_seg_bpe5k_char/5000_char.model
-
-tokenizer: &id001 !new:sentencepiece.SentencePieceProcessor
-
-pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
-  collect_in: results/TransformerLM_seg_char/tokenizer
-  loadables:
-    tokenizer: *id001
-  paths:
-    tokenizer: results/tokenizer_seg_bpe5k_char/5000_char.model
-
-train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
-  save_file: results/TransformerLM_seg_char/train_log.txt
-
-# Training parameters
-number_of_epochs: 20
-batch_size: 64
-lr: 1
-accumulation_steps: 2
-ckpt_interval_minutes: 15
-
-epoch_counter: &id004 !new:speechbrain.utils.epoch_loop.EpochCounter
-
-  limit: 20
-
-# Dataloader options
-train_dataloader_opts:
-  batch_size: 64
-  num_workers: 4
-  shuffle: true
-  pin_memory: true
-
-valid_dataloader_opts:
-  batch_size: 64
-  num_workers: 4
-
-test_dataloader_opts:
-  batch_size: 64
-  num_workers: 4
-
-# Model parameters
-d_model: 576
-
-# Outputs
-output_neurons: 5000
-blank_index: 0
-bos_index: 1
-eos_index: 2
-unk_index: 0
-pad_index: 0
-
-model: &id002 !new:speechbrain.lobes.models.transformer.TransformerLM.TransformerLM
-
-  vocab: 5000
-  d_model: 576
-  nhead: 6
-  num_encoder_layers: 6
-  num_decoder_layers: 0
-  d_ffn: 1538
-  dropout: 0.2
-  activation: !name:torch.nn.GELU
-  normalize_before: false
-
-modules:
-  model: *id002
-lr_annealing: &id003 !new:speechbrain.nnet.schedulers.NoamScheduler
-  lr_initial: 1
-  n_warmup_steps: 1000
-  model_size: 576
-
-checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
-  checkpoints_dir: results/TransformerLM_seg_char/save
-  recoverables:
-    model: *id002
-    scheduler: *id003
-    counter: *id004
-log_softmax: !new:speechbrain.nnet.activations.Softmax
-  apply_log: true
-
-optimizer: !name:torch.optim.Adam
-  lr: 0
-  betas: (0.9, 0.98)
-  eps: 0.000000001
-
-compute_cost: !name:speechbrain.nnet.losses.nll_loss

ASR-model/TransformerLM_seg_char/log.txt

@@ -1,276 +0,0 @@
-2021-10-05 19:59:24,051 - speechbrain.core - INFO - Beginning experiment!
-2021-10-05 19:59:24,052 - speechbrain.core - INFO - Experiment folder: results/TransformerLM_seg_char
-2021-10-05 19:59:24,902 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-keyring==18.0.1
-kiwisolver==1.3.1
-language-selector==0.1
-launchpadlib==1.10.13
-lazr.restfulclient==0.14.2
-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-nvidia-ml-py3==7.352.0
-oauthlib==3.1.0
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-
-
-2021-10-05 19:59:24,907 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-10-05 19:59:24,936 - speechbrain.utils.parameter_transfer - DEBUG - Collecting files (or symlinks) for pretraining in results/TransformerLM_seg_char/tokenizer.
-2021-10-05 19:59:24,937 - speechbrain.pretrained.fetching - INFO - Fetch 5000_char.model: Linking to local file in /mnt/md0/user_wayne/speechbrain/recipes/MATBN/results/tokenizer_seg_bpe5k_char/5000_char.model.
-2021-10-05 19:59:24,937 - speechbrain.utils.parameter_transfer - INFO - Loading pretrained files for: tokenizer
-2021-10-05 19:59:25,190 - speechbrain.core - INFO - Info: ckpt_interval_minutes arg from hparam file is used
-2021-10-05 19:59:27,052 - speechbrain.core - INFO - 24.7M trainable parameters in LM
-2021-10-05 19:59:27,053 - speechbrain.utils.checkpoints - INFO - Would load a checkpoint here, but none found yet.
-2021-10-05 19:59:27,053 - speechbrain.utils.epoch_loop - INFO - Going into epoch 1
-2021-10-05 20:03:07,476 - speechbrain.utils.train_logger - INFO - epoch: 1, lr: 4.99e-04 - train loss: 4.23 - valid loss: 3.19
-2021-10-05 20:03:07,790 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-03-07+00
-2021-10-05 20:03:07,792 - speechbrain.utils.epoch_loop - INFO - Going into epoch 2
-2021-10-05 20:06:50,852 - speechbrain.utils.train_logger - INFO - epoch: 2, lr: 1.00e-03 - train loss: 2.95 - valid loss: 2.77
-2021-10-05 20:06:51,157 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-06-50+00
-2021-10-05 20:06:51,186 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-03-07+00
-2021-10-05 20:06:51,186 - speechbrain.utils.epoch_loop - INFO - Going into epoch 3
-2021-10-05 20:10:34,626 - speechbrain.utils.train_logger - INFO - epoch: 3, lr: 1.23e-03 - train loss: 2.73 - valid loss: 2.64
-2021-10-05 20:10:34,936 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-10-34+00
-2021-10-05 20:10:34,967 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-06-50+00
-2021-10-05 20:10:34,967 - speechbrain.utils.epoch_loop - INFO - Going into epoch 4
-2021-10-05 20:14:18,480 - speechbrain.utils.train_logger - INFO - epoch: 4, lr: 1.07e-03 - train loss: 2.60 - valid loss: 2.54
-2021-10-05 20:14:18,787 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-14-18+00
-2021-10-05 20:14:18,820 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-10-34+00
-2021-10-05 20:14:18,821 - speechbrain.utils.epoch_loop - INFO - Going into epoch 5
-2021-10-05 20:18:02,905 - speechbrain.utils.train_logger - INFO - epoch: 5, lr: 9.56e-04 - train loss: 2.49 - valid loss: 2.48
-2021-10-05 20:18:03,213 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-18-02+00
-2021-10-05 20:18:03,247 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-14-18+00
-2021-10-05 20:18:03,247 - speechbrain.utils.epoch_loop - INFO - Going into epoch 6
-2021-10-05 20:21:47,703 - speechbrain.utils.train_logger - INFO - epoch: 6, lr: 8.73e-04 - train loss: 2.41 - valid loss: 2.42
-2021-10-05 20:21:48,011 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-21-47+00
-2021-10-05 20:21:48,048 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-18-02+00
-2021-10-05 20:21:48,048 - speechbrain.utils.epoch_loop - INFO - Going into epoch 7
-2021-10-05 20:25:32,303 - speechbrain.utils.train_logger - INFO - epoch: 7, lr: 8.08e-04 - train loss: 2.35 - valid loss: 2.38
-2021-10-05 20:25:32,612 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-25-32+00
-2021-10-05 20:25:32,650 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-21-47+00
-2021-10-05 20:25:32,651 - speechbrain.utils.epoch_loop - INFO - Going into epoch 8
-2021-10-05 20:29:17,400 - speechbrain.utils.train_logger - INFO - epoch: 8, lr: 7.56e-04 - train loss: 2.29 - valid loss: 2.35
-2021-10-05 20:29:17,706 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-29-17+00
-2021-10-05 20:29:17,745 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-25-32+00
-2021-10-05 20:29:17,746 - speechbrain.utils.epoch_loop - INFO - Going into epoch 9
-2021-10-05 20:33:02,633 - speechbrain.utils.train_logger - INFO - epoch: 9, lr: 7.13e-04 - train loss: 2.24 - valid loss: 2.33
-2021-10-05 20:33:02,943 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-33-02+00
-2021-10-05 20:33:02,985 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-29-17+00
-2021-10-05 20:33:02,985 - speechbrain.utils.epoch_loop - INFO - Going into epoch 10
-2021-10-05 20:36:47,808 - speechbrain.utils.train_logger - INFO - epoch: 10, lr: 6.76e-04 - train loss: 2.19 - valid loss: 2.32
-2021-10-05 20:36:48,118 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-36-47+00
-2021-10-05 20:36:48,161 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-33-02+00
-2021-10-05 20:36:48,161 - speechbrain.utils.epoch_loop - INFO - Going into epoch 11
-2021-10-05 20:40:33,763 - speechbrain.utils.train_logger - INFO - epoch: 11, lr: 6.45e-04 - train loss: 2.15 - valid loss: 2.30
-2021-10-05 20:40:34,072 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-40-33+00
-2021-10-05 20:40:34,117 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-36-47+00
-2021-10-05 20:40:34,117 - speechbrain.utils.epoch_loop - INFO - Going into epoch 12
-2021-10-05 20:44:19,873 - speechbrain.utils.train_logger - INFO - epoch: 12, lr: 6.17e-04 - train loss: 2.11 - valid loss: 2.30
-2021-10-05 20:44:20,181 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-44-19+00
-2021-10-05 20:44:20,228 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-40-33+00
-2021-10-05 20:44:20,228 - speechbrain.utils.epoch_loop - INFO - Going into epoch 13
-2021-10-05 20:48:05,429 - speechbrain.utils.train_logger - INFO - epoch: 13, lr: 5.93e-04 - train loss: 2.08 - valid loss: 2.29
-2021-10-05 20:48:05,739 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-48-05+00
-2021-10-05 20:48:05,788 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-44-19+00
-2021-10-05 20:48:05,789 - speechbrain.utils.epoch_loop - INFO - Going into epoch 14
-2021-10-05 20:51:51,235 - speechbrain.utils.train_logger - INFO - epoch: 14, lr: 5.71e-04 - train loss: 2.04 - valid loss: 2.29
-2021-10-05 20:51:51,545 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-51-51+00
-2021-10-05 20:51:51,596 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-48-05+00
-2021-10-05 20:51:51,596 - speechbrain.utils.epoch_loop - INFO - Going into epoch 15
-2021-10-05 20:55:37,264 - speechbrain.utils.train_logger - INFO - epoch: 15, lr: 5.52e-04 - train loss: 2.01 - valid loss: 2.28
-2021-10-05 20:55:37,574 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00
-2021-10-05 20:55:37,626 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-51-51+00
-2021-10-05 20:55:37,627 - speechbrain.utils.epoch_loop - INFO - Going into epoch 16
-2021-10-05 20:59:22,956 - speechbrain.utils.train_logger - INFO - epoch: 16, lr: 5.34e-04 - train loss: 1.98 - valid loss: 2.28
-2021-10-05 20:59:23,263 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-59-22+00
-2021-10-05 20:59:23,293 - speechbrain.utils.epoch_loop - INFO - Going into epoch 17
-2021-10-05 21:03:08,924 - speechbrain.utils.train_logger - INFO - epoch: 17, lr: 5.18e-04 - train loss: 1.95 - valid loss: 2.29
-2021-10-05 21:03:09,230 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-03-08+00
-2021-10-05 21:03:09,301 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-59-22+00
-2021-10-05 21:03:09,301 - speechbrain.utils.epoch_loop - INFO - Going into epoch 18
-2021-10-05 21:06:55,028 - speechbrain.utils.train_logger - INFO - epoch: 18, lr: 5.04e-04 - train loss: 1.92 - valid loss: 2.29
-2021-10-05 21:06:55,335 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-06-55+00
-2021-10-05 21:06:55,408 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-03-08+00
-2021-10-05 21:06:55,409 - speechbrain.utils.epoch_loop - INFO - Going into epoch 19
-2021-10-05 21:10:40,930 - speechbrain.utils.train_logger - INFO - epoch: 19, lr: 4.90e-04 - train loss: 1.90 - valid loss: 2.30
-2021-10-05 21:10:41,237 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-10-40+00
-2021-10-05 21:10:41,312 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-06-55+00
-2021-10-05 21:10:41,312 - speechbrain.utils.epoch_loop - INFO - Going into epoch 20
-2021-10-05 21:14:27,278 - speechbrain.utils.train_logger - INFO - epoch: 20, lr: 4.78e-04 - train loss: 1.87 - valid loss: 2.30
-2021-10-05 21:14:27,586 - speechbrain.utils.checkpoints - INFO - Saved an end-of-epoch checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00
-2021-10-05 21:14:27,663 - speechbrain.utils.checkpoints - INFO - Deleted checkpoint in results/TransformerLM_seg_char/save/CKPT+2021-10-05+21-10-40+00
-2021-10-05 21:14:27,664 - speechbrain.utils.checkpoints - INFO - Loading a checkpoint from results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00
-2021-10-05 21:14:27,706 - root - DEBUG - SaveableDataLoader was requested to load a checkpoint, but the DataLoader has already been iterated. The DataLoader file will be ignored. This is normal in evaluation, when a checkpoint is loaded just to retrieve the best model.
-2021-10-05 21:14:31,760 - speechbrain.utils.train_logger - INFO - Epoch loaded: 15 - test loss: 2.68

ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/CKPT.yaml

@@ -1,4 +0,0 @@
-# yamllint disable
-end-of-epoch: true
-loss: 2.282208064707314
-unixtime: 1633438537.264693

ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/brain.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/counter.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/dataloader-TRAIN.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/model.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/optimizer.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/scheduler.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00/CKPT.yaml

@@ -1,4 +0,0 @@
-# yamllint disable
-end-of-epoch: true
-loss: 2.3031107332648304
-unixtime: 1633439667.279289

ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00/brain.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00/dataloader-TRAIN.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00/model.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00/optimizer.ckpt

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ASR-model/TransformerLM_seg_char/save/CKPT+2021-10-05+21-14-27+00/scheduler.ckpt

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ASR-model/TransformerLM_seg_char/train.py

@@ -1,150 +0,0 @@
-import sys
-
-import torch
-import speechbrain as sb
-from speechbrain.dataio import dataset
-from speechbrain.utils.distributed import run_on_main
-from hyperpyyaml import load_hyperpyyaml
-
-
-class LM(sb.core.Brain):
-    def compute_forward(self, batch, stage):
-        batch = batch.to(self.device)
-        tokens_bos, _ = batch.tokens_bos
-        logits = self.hparams.model(tokens_bos)
-        pred = self.hparams.log_softmax(logits)
-        return pred
-
-    def compute_objectives(self, predictions, batch, stage):
-        batch = batch.to(self.device)
-        tokens_eos, tokens_len = batch.tokens_eos
-        loss = self.hparams.compute_cost(
-            predictions, tokens_eos, length=tokens_len
-        )
-        return loss
-
-    def fit_batch(self, batch):
-        predictions = self.compute_forward(batch, sb.Stage.TRAIN)
-        loss = self.compute_objectives(predictions, batch, sb.Stage.TRAIN)
-
-        (loss / self.hparams.accumulation_steps).backward()
-
-        if self.step % self.hparams.accumulation_steps == 0:
-            self.check_gradients(loss)
-
-            self.optimizer.step()
-            self.optimizer.zero_grad()
-
-            if isinstance(
-                self.hparams.lr_annealing, sb.nnet.schedulers.NoamScheduler
-            ) or isinstance(
-                self.hparams.lr_annealing,
-                sb.nnet.schedulers.CyclicCosineScheduler,
-            ):
-                self.hparams.lr_annealing(self.optimizer)
-
-        return loss
-
-    def on_stage_end(self, stage, stage_loss, epoch):
-        stage_stats = {"loss": stage_loss}
-        if stage == sb.Stage.TRAIN:
-            self.train_stats = stage_stats
-
-        if stage == sb.Stage.VALID and sb.utils.distributed.if_main_process():
-            if not (
-                isinstance(
-                    self.hparams.lr_annealing, sb.nnet.schedulers.NoamScheduler
-                )
-                or isinstance(
-                    self.hparams.lr_annealing,
-                    sb.nnet.schedulers.CyclicCosineScheduler,
-                )
-            ):
-                old_lr, new_lr = self.hparams.lr_annealing(stage_loss)
-                sb.nnet.schedulers.update_learning_rate(self.optimizer, new_lr)
-            else:
-                old_lr = self.hparams.lr_annealing.current_lr
-
-            self.hparams.train_logger.log_stats(
-                stats_meta={"epoch": epoch, "lr": old_lr},
-                train_stats=self.train_stats,
-                valid_stats=stage_stats,
-            )
-            self.checkpointer.save_and_keep_only(
-                meta=stage_stats, min_keys=["loss"],
-            )
-
-        if stage == sb.Stage.TEST and sb.utils.distributed.if_main_process():
-            self.hparams.train_logger.log_stats(
-                stats_meta={"Epoch loaded": self.hparams.epoch_counter.current},
-                test_stats=stage_stats,
-            )
-
-
-def dataio_prepare(hparams):
-    @sb.utils.data_pipeline.takes("transcription")
-    @sb.utils.data_pipeline.provides(
-        "transcription", "tokens_bos", "tokens_eos"
-    )
-    def transcription_pipline(transcription):
-        yield transcription
-        tokens_list = hparams["tokenizer"].encode_as_ids(transcription)
-        tokens_bos = torch.LongTensor([hparams["bos_index"]] + (tokens_list))
-        yield tokens_bos
-        tokens_eos = torch.LongTensor(tokens_list + [hparams["eos_index"]])
-        yield tokens_eos
-
-    data_folder = hparams["data_folder"]
-    datasets = {}
-    for dataset_name in ["train", "dev", "test"]:
-        json_path = f"{data_folder}/{dataset_name}.json"
-        datasets[dataset_name] = dataset.DynamicItemDataset.from_json(
-            json_path=json_path,
-            replacements={"data_root": data_folder},
-            dynamic_items=[transcription_pipline],
-            output_keys=["transcription", "tokens_bos", "tokens_eos"],
-        )
-
-    return datasets
-
-
-if __name__ == "__main__":
-    hparams_file_path, run_opts, overrides = sb.parse_arguments(sys.argv[1:])
-    with open(hparams_file_path) as hparams_file:
-        hparams = load_hyperpyyaml(hparams_file, overrides)
-
-    sb.utils.distributed.ddp_init_group(run_opts)
-
-    sb.create_experiment_directory(
-        experiment_directory=hparams["output_folder"],
-        hyperparams_to_save=hparams_file_path,
-        overrides=overrides,
-    )
-
-    run_on_main(hparams["pretrainer"].collect_files)
-    hparams["pretrainer"].load_collected(device=run_opts["device"])
-
-    datasets = dataio_prepare(hparams)
-
-    lm_brain = LM(
-        modules=hparams["modules"],
-        opt_class=hparams["optimizer"],
-        hparams=hparams,
-        run_opts=run_opts,
-        checkpointer=hparams["checkpointer"],
-    )
-
-    lm_brain.fit(
-        lm_brain.hparams.epoch_counter,
-        datasets["train"],
-        datasets["dev"],
-        train_loader_kwargs=hparams["train_dataloader_opts"],
-        valid_loader_kwargs=hparams["valid_dataloader_opts"],
-    )
-
-    # evaluation
-    lm_brain.evaluate(
-        datasets["test"],
-        min_key="loss",
-        test_loader_kwargs=hparams["test_dataloader_opts"],
-    )

ASR-model/TransformerLM_seg_char/train_log.txt

@@ -1,21 +0,0 @@
-epoch: 1, lr: 4.99e-04 - train loss: 4.23 - valid loss: 3.19
-epoch: 2, lr: 1.00e-03 - train loss: 2.95 - valid loss: 2.77
-epoch: 3, lr: 1.23e-03 - train loss: 2.73 - valid loss: 2.64
-epoch: 4, lr: 1.07e-03 - train loss: 2.60 - valid loss: 2.54
-epoch: 5, lr: 9.56e-04 - train loss: 2.49 - valid loss: 2.48
-epoch: 6, lr: 8.73e-04 - train loss: 2.41 - valid loss: 2.42
-epoch: 7, lr: 8.08e-04 - train loss: 2.35 - valid loss: 2.38
-epoch: 8, lr: 7.56e-04 - train loss: 2.29 - valid loss: 2.35
-epoch: 9, lr: 7.13e-04 - train loss: 2.24 - valid loss: 2.33
-epoch: 10, lr: 6.76e-04 - train loss: 2.19 - valid loss: 2.32
-epoch: 11, lr: 6.45e-04 - train loss: 2.15 - valid loss: 2.30
-epoch: 12, lr: 6.17e-04 - train loss: 2.11 - valid loss: 2.30
-epoch: 13, lr: 5.93e-04 - train loss: 2.08 - valid loss: 2.29
-epoch: 14, lr: 5.71e-04 - train loss: 2.04 - valid loss: 2.29
-epoch: 15, lr: 5.52e-04 - train loss: 2.01 - valid loss: 2.28
-epoch: 16, lr: 5.34e-04 - train loss: 1.98 - valid loss: 2.28
-epoch: 17, lr: 5.18e-04 - train loss: 1.95 - valid loss: 2.29
-epoch: 18, lr: 5.04e-04 - train loss: 1.92 - valid loss: 2.29
-epoch: 19, lr: 4.90e-04 - train loss: 1.90 - valid loss: 2.30
-epoch: 20, lr: 4.78e-04 - train loss: 1.87 - valid loss: 2.30
-Epoch loaded: 15 - test loss: 2.68

ASR-model/asr_transformer_seg_char_ctc0.3/env.log

@@ -1,195 +0,0 @@
-SpeechBrain system description
-==============================
-Python version:
-3.8.10 (default, Sep 28 2021, 16:10:42) 
-[GCC 9.3.0]
-==============================
-Installed Python packages:
-appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-keyring==18.0.1
-kiwisolver==1.3.1
-language-selector==0.1
-launchpadlib==1.10.13
-lazr.restfulclient==0.14.2
-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-nvidia-ml-py3==7.352.0
-oauthlib==3.1.0
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-==============================
-Git revision:
-e3e51338
-==============================
-Cuda version:
-10.2

ASR-model/asr_transformer_seg_char_ctc0.3/hyperparams.yaml

@@ -1,241 +0,0 @@
-# Generated 2021-10-11 from:
-# /mnt/md0/user_wayne/speechbrain/recipes/MATBN/ASR/hparams/transformer_seg_LM_char_decode.yaml
-# yamllint disable
-output_folder: results/asr_transformer_seg_char
-cer_file: results/asr_transformer_seg_char/cer.txt
-train_log: results/asr_transformer_seg_char/train_log.txt
-save_folder: results/asr_transformer_seg_char/save
-ckpt_interval_minutes: 15
-num_workers: 4
-
-data_folder: results/prepare_seg
-tokenizer_file: results/tokenizer_seg_bpe5k_char/5000_char.model
-lm_file: results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/model.ckpt
-
-tokenizer: &id001 !new:sentencepiece.SentencePieceProcessor
-
-pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
-  collect_in: results/asr_transformer_seg_char/save
-  loadables:
-    lm: &id003 !new:speechbrain.lobes.models.transformer.TransformerLM.TransformerLM
-                                                                        # yamllint disable-line rule:line-length
-      vocab: 5000
-      d_model: 576
-      nhead: 6
-      num_encoder_layers: 6
-      num_decoder_layers: 0
-      d_ffn: 1538
-      dropout: 0.2
-      activation: !name:torch.nn.GELU
-      normalize_before: false
-
-    tokenizer: *id001
-  paths:
-    lm: results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/model.ckpt
-    tokenizer: results/tokenizer_seg_bpe5k_char/5000_char.model
-
-train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
-  save_file: results/asr_transformer_seg_char/train_log.txt
-
-# Feature parameters
-sample_rate: 16000
-n_fft: 400
-n_mels: 80
-hop_length: 10
-
-compute_features: !new:speechbrain.lobes.features.Fbank
-  sample_rate: 16000
-  n_fft: 400
-  n_mels: 80
-  hop_length: 10
-
-speed_perturb: !new:speechbrain.processing.speech_augmentation.SpeedPerturb
-  orig_freq: 16000
-  speeds: [90, 100, 110]
-
-# Training parameters
-number_of_epochs: 60
-batch_size: 1
-ctc_weight: 0.3
-gradient_accumulation: 32
-gradient_clipping: 5.0
-loss_reduction: batchmean
-sorting: random
-
-# stages related parameters
-stage_one_epochs: 40
-lr_adam: 1.0
-lr_sgd: 0.000025
-
-# Dataloader options
-train_dataloader_opts:
-  batch_size: 1
-  num_workers: 4
-  shuffle: true
-
-valid_dataloader_opts:
-  batch_size: 1
-  num_workers: 4
-
-test_dataloader_opts:
-  batch_size: 1
-  num_workers: 4
-
-####################### Model parameters ###########################
-# Transformer
-d_model: 256
-nhead: 4
-num_encoder_layers: 12
-num_decoder_layers: 6
-d_ffn: 2048
-transformer_dropout: 0.1
-activation: &id002 !name:torch.nn.GELU
-output_neurons: 5000
-vocab_size: 5000
-
-# Outputs
-blank_index: 0
-label_smoothing: 0.1
-pad_index: 0
-bos_index: 1
-eos_index: 2
-unk_index: 0
-
-# Decoding parameters
-min_decode_ratio: 0.0
-max_decode_ratio: 1.0 # 1.0
-valid_search_interval: 10
-valid_beam_size: 10
-test_beam_size: 10
-ctc_weight_decode: 0.30
-lm_weight: 0.9
-
-############################## models ################################
-
-CNN: &id004 !new:speechbrain.lobes.models.convolution.ConvolutionFrontEnd
-  input_shape: (8, 10, 80)
-  num_blocks: 2
-  num_layers_per_block: 1
-  out_channels: (256, 256)
-  kernel_sizes: (3, 3)
-  strides: (2, 2)
-  residuals: (False, False)
-
-Transformer: &id005 !new:speechbrain.lobes.models.transformer.TransformerASR.TransformerASR
-                                                                          # yamllint disable-line rule:line-length
-  input_size: 5120
-  tgt_vocab: 5000
-  d_model: 256
-  nhead: 4
-  num_encoder_layers: 12
-  num_decoder_layers: 6
-  d_ffn: 2048
-  dropout: 0.1
-  activation: *id002
-  normalize_before: true
-
-lm_model: *id003
-ctc_lin: &id007 !new:speechbrain.nnet.linear.Linear
-  input_size: 256
-  n_neurons: 5000
-
-seq_lin: &id006 !new:speechbrain.nnet.linear.Linear
-  input_size: 256
-  n_neurons: 5000
-
-modules:
-  CNN: *id004
-  Transformer: *id005
-  seq_lin: *id006
-  ctc_lin: *id007
-  normalize: &id010 !new:speechbrain.processing.features.InputNormalization
-
-    norm_type: global
-    update_until_epoch: 4
-
-model: &id008 !new:torch.nn.ModuleList
-- [*id004, *id005, *id006, *id007]
-Adam: !name:torch.optim.Adam
-  lr: 0
-  betas: (0.9, 0.98)
-  eps: 0.000000001
-
-SGD: !name:torch.optim.SGD
-  lr: 0.000025
-  momentum: 0.99
-  nesterov: true
-
-valid_search: !new:speechbrain.decoders.S2STransformerBeamSearch
-  modules: [*id005, *id006, *id007]
-  bos_index: 1
-  eos_index: 2
-  blank_index: 0
-  min_decode_ratio: 0.0
-  max_decode_ratio: 1.0
-  beam_size: 10
-  ctc_weight: 0.30
-  using_eos_threshold: false
-  length_normalization: true
-
-test_search: !new:speechbrain.decoders.S2STransformerBeamSearch
-  modules: [*id005, *id006, *id007]
-  bos_index: 1
-  eos_index: 2
-  blank_index: 0
-  min_decode_ratio: 0.0
-  max_decode_ratio: 1.0
-  beam_size: 10
-  ctc_weight: 0.30
-  lm_weight: 0.9
-  lm_modules: *id003
-  temperature: 1.15
-  temperature_lm: 1.15
-  using_eos_threshold: false
-  length_normalization: true
-
-log_softmax: !new:torch.nn.LogSoftmax
-  dim: -1
-
-ctc_cost: !name:speechbrain.nnet.losses.ctc_loss
-  blank_index: 0
-  reduction: batchmean
-
-seq_cost: !name:speechbrain.nnet.losses.kldiv_loss
-  label_smoothing: 0.1
-  reduction: batchmean
-
-noam_annealing: &id009 !new:speechbrain.nnet.schedulers.NoamScheduler
-  lr_initial: 1.0
-  n_warmup_steps: 25000
-  model_size: 256
-
-checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
-  checkpoints_dir: results/asr_transformer_seg_char/save
-  recoverables:
-    model: *id008
-    noam_scheduler: *id009
-    normalizer: *id010
-    counter: &id011 !new:speechbrain.utils.epoch_loop.EpochCounter
-
-      limit: 60
-
-epoch_counter: *id011
-normalize: *id010
-augmentation: !new:speechbrain.lobes.augment.SpecAugment
-  time_warp: true
-  time_warp_window: 5
-  time_warp_mode: bicubic
-  freq_mask: true
-  n_freq_mask: 2
-  time_mask: true
-  n_time_mask: 2
-  replace_with_zero: false
-  freq_mask_width: 30
-  time_mask_width: 40
-
-remove_spaces: true
-split_tokens: &id012 !apply:operator.not_ [true]
-
-cer_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
-  split_tokens: *id012
-acc_computer: !name:speechbrain.utils.Accuracy.AccuracyStats

ASR-model/asr_transformer_seg_char_ctc0.3/results/asr_transformer_seg_char/env.log

@@ -1,109 +0,0 @@
-SpeechBrain system description
-==============================
-Python version:
-3.8.16 (default, Jun 12 2023, 18:09:05) 
-[GCC 11.2.0]
-==============================
-Installed Python packages:
-antlr4-python3-runtime==4.8
-anyio==3.7.0
-astroid==2.15.5
-bitarray==2.7.6
-certifi==2023.5.7
-cffi==1.15.1
-cfgv==3.3.1
-charset-normalizer==3.1.0
-click==7.1.2
-cmake==3.26.4
-colorama==0.4.6
-Cython==0.29.36
-dill==0.3.6
-distlib==0.3.6
-exceptiongroup==1.1.2
-fairseq @ git+https://github.com/facebookresearch/fairseq.git@31fba013a070eaff69dec8642e68e7134d60ab0f
-fastapi==0.98.0
-filelock==3.12.2
-flake8==6.0.0
-fsspec==2023.6.0
-h11==0.14.0
-httpcore==0.17.2
-httptools==0.1.2
-httpx==0.24.1
-huggingface-hub==0.15.1
-hydra-core==1.0.7
-HyperPyYAML==1.2.1
-identify==2.5.24
-idna==3.4
-importlib-resources==5.12.0
-iniconfig==2.0.0
-isort==5.12.0
-jieba==0.42.1
-Jinja2==3.1.2
-joblib==1.3.1
-lazy-object-proxy==1.9.0
-lit==16.0.6
-lxml==4.9.2
-MarkupSafe==2.1.3
-mccabe==0.7.0
-mock==5.0.2
-mpmath==1.3.0
-networkx==3.1
-nodeenv==1.8.0
-numpy==1.24.4
-nvidia-cublas-cu11==11.10.3.66
-nvidia-cuda-cupti-cu11==11.7.101
-nvidia-cuda-nvrtc-cu11==11.7.99
-nvidia-cuda-runtime-cu11==11.7.99
-nvidia-cudnn-cu11==8.5.0.96
-nvidia-cufft-cu11==10.9.0.58
-nvidia-curand-cu11==10.2.10.91
-nvidia-cusolver-cu11==11.4.0.1
-nvidia-cusparse-cu11==11.7.4.91
-nvidia-nccl-cu11==2.14.3
-nvidia-nvtx-cu11==11.7.91
-omegaconf==2.0.6
-packaging==23.1
-platformdirs==3.8.0
-pluggy==1.2.0
-portalocker==2.7.0
-pre-commit==3.3.3
-pycodestyle==2.10.0
-pycparser==2.21
-pydantic==1.10.9
-pyflakes==3.0.1
-pylint==2.17.4
-pytest==7.4.0
-python-multipart==0.0.6
-PyYAML==6.0
-regex==2023.6.3
-requests==2.31.0
-ruamel.yaml==0.17.28
-ruamel.yaml.clib==0.2.7
-sacrebleu==2.3.1
-scikit-learn==1.3.0
-scipy==1.10.1
-sentencepiece==0.1.99
-sniffio==1.3.0
-speechbrain==0.5.14
-starlette==0.27.0
-subword-nmt==0.3.8
-sympy==1.12
-tabulate==0.9.0
-threadpoolctl==3.1.0
-tomli==2.0.1
-tomlkit==0.11.8
-torch==2.0.1
-torchaudio==2.0.2
-tqdm==4.65.0
-triton==2.0.0
-typing_extensions==4.7.1
-urllib3==2.0.3
-uvicorn==0.11.3
-uvloop==0.17.0
-virtualenv==20.23.1
-websockets==8.1
-wrapt==1.15.0
-zipp==3.15.0
-==============================
-Could not get git revision==============================
-CUDA not available

ASR-model/asr_transformer_seg_char_ctc0.3/results/asr_transformer_seg_char/hyperparams.yaml

@@ -1,244 +0,0 @@
-# Generated 2023-07-05 from:
-# /mnt/md0/user_sinica_axel/MATBN/results/asr_transformer_seg_char_ctc0.3/hyperparams.yaml
-# yamllint disable
-# Generated 2021-10-11 from:
-# /mnt/md0/user_wayne/speechbrain/recipes/MATBN/ASR/hparams/transformer_seg_LM_char_decode.yaml
-# yamllint disable
-output_folder: results/asr_transformer_seg_char
-cer_file: results/asr_transformer_seg_char/cer.txt
-train_log: results/asr_transformer_seg_char/train_log.txt
-save_folder: results/asr_transformer_seg_char/save
-ckpt_interval_minutes: 15
-num_workers: 4
-
-data_folder: results/prepare_seg
-tokenizer_file: results/tokenizer_seg_bpe5k_char/5000_char.model
-lm_file: results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/model.ckpt
-
-tokenizer: &id001 !new:sentencepiece.SentencePieceProcessor
-
-pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
-  collect_in: results/asr_transformer_seg_char/save
-  loadables:
-    lm: &id003 !new:speechbrain.lobes.models.transformer.TransformerLM.TransformerLM
-                                                                        # yamllint disable-line rule:line-length
-      vocab: 5000
-      d_model: 576
-      nhead: 6
-      num_encoder_layers: 6
-      num_decoder_layers: 0
-      d_ffn: 1538
-      dropout: 0.2
-      activation: !name:torch.nn.GELU
-      normalize_before: false
-
-    tokenizer: *id001
-  paths:
-    lm: results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00/model.ckpt
-    tokenizer: results/tokenizer_seg_bpe5k_char/5000_char.model
-
-train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
-  save_file: results/asr_transformer_seg_char/train_log.txt
-
-# Feature parameters
-sample_rate: 16000
-n_fft: 400
-n_mels: 80
-hop_length: 10
-
-compute_features: !new:speechbrain.lobes.features.Fbank
-  sample_rate: 16000
-  n_fft: 400
-  n_mels: 80
-  hop_length: 10
-
-speed_perturb: !new:speechbrain.processing.speech_augmentation.SpeedPerturb
-  orig_freq: 16000
-  speeds: [90, 100, 110]
-
-# Training parameters
-number_of_epochs: 60
-batch_size: 1
-ctc_weight: 0.3
-gradient_accumulation: 32
-gradient_clipping: 5.0
-loss_reduction: batchmean
-sorting: random
-
-# stages related parameters
-stage_one_epochs: 40
-lr_adam: 1.0
-lr_sgd: 0.000025
-
-# Dataloader options
-train_dataloader_opts:
-  batch_size: 1
-  num_workers: 4
-  shuffle: true
-
-valid_dataloader_opts:
-  batch_size: 1
-  num_workers: 4
-
-test_dataloader_opts:
-  batch_size: 1
-  num_workers: 4
-
-####################### Model parameters ###########################
-# Transformer
-d_model: 256
-nhead: 4
-num_encoder_layers: 12
-num_decoder_layers: 6
-d_ffn: 2048
-transformer_dropout: 0.1
-activation: &id002 !name:torch.nn.GELU
-output_neurons: 5000
-vocab_size: 5000
-
-# Outputs
-blank_index: 0
-label_smoothing: 0.1
-pad_index: 0
-bos_index: 1
-eos_index: 2
-unk_index: 0
-
-# Decoding parameters
-min_decode_ratio: 0.0
-max_decode_ratio: 1.0 # 1.0
-valid_search_interval: 10
-valid_beam_size: 10
-test_beam_size: 10
-ctc_weight_decode: 0.30
-lm_weight: 0.9
-
-############################## models ################################
-
-CNN: &id004 !new:speechbrain.lobes.models.convolution.ConvolutionFrontEnd
-  input_shape: (8, 10, 80)
-  num_blocks: 2
-  num_layers_per_block: 1
-  out_channels: (256, 256)
-  kernel_sizes: (3, 3)
-  strides: (2, 2)
-  residuals: (False, False)
-
-Transformer: &id005 !new:speechbrain.lobes.models.transformer.TransformerASR.TransformerASR
-                                                                          # yamllint disable-line rule:line-length
-  input_size: 5120
-  tgt_vocab: 5000
-  d_model: 256
-  nhead: 4
-  num_encoder_layers: 12
-  num_decoder_layers: 6
-  d_ffn: 2048
-  dropout: 0.1
-  activation: *id002
-  normalize_before: true
-
-lm_model: *id003
-ctc_lin: &id007 !new:speechbrain.nnet.linear.Linear
-  input_size: 256
-  n_neurons: 5000
-
-seq_lin: &id006 !new:speechbrain.nnet.linear.Linear
-  input_size: 256
-  n_neurons: 5000
-
-modules:
-  CNN: *id004
-  Transformer: *id005
-  seq_lin: *id006
-  ctc_lin: *id007
-  normalize: &id010 !new:speechbrain.processing.features.InputNormalization
-
-    norm_type: global
-    update_until_epoch: 4
-
-model: &id008 !new:torch.nn.ModuleList
-- [*id004, *id005, *id006, *id007]
-Adam: !name:torch.optim.Adam
-  lr: 0
-  betas: (0.9, 0.98)
-  eps: 0.000000001
-
-SGD: !name:torch.optim.SGD
-  lr: 0.000025
-  momentum: 0.99
-  nesterov: true
-
-valid_search: !new:speechbrain.decoders.S2STransformerBeamSearch
-  modules: [*id005, *id006, *id007]
-  bos_index: 1
-  eos_index: 2
-  blank_index: 0
-  min_decode_ratio: 0.0
-  max_decode_ratio: 1.0
-  beam_size: 10
-  ctc_weight: 0.30
-  using_eos_threshold: false
-  length_normalization: true
-
-test_search: !new:speechbrain.decoders.S2STransformerBeamSearch
-  modules: [*id005, *id006, *id007]
-  bos_index: 1
-  eos_index: 2
-  blank_index: 0
-  min_decode_ratio: 0.0
-  max_decode_ratio: 1.0
-  beam_size: 10
-  ctc_weight: 0.30
-  lm_weight: 0.9
-  lm_modules: *id003
-  temperature: 1.15
-  temperature_lm: 1.15
-  using_eos_threshold: false
-  length_normalization: true
-
-log_softmax: !new:torch.nn.LogSoftmax
-  dim: -1
-
-ctc_cost: !name:speechbrain.nnet.losses.ctc_loss
-  blank_index: 0
-  reduction: batchmean
-
-seq_cost: !name:speechbrain.nnet.losses.kldiv_loss
-  label_smoothing: 0.1
-  reduction: batchmean
-
-noam_annealing: &id009 !new:speechbrain.nnet.schedulers.NoamScheduler
-  lr_initial: 1.0
-  n_warmup_steps: 25000
-  model_size: 256
-
-checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
-  checkpoints_dir: results/asr_transformer_seg_char/save
-  recoverables:
-    model: *id008
-    noam_scheduler: *id009
-    normalizer: *id010
-    counter: &id011 !new:speechbrain.utils.epoch_loop.EpochCounter
-
-      limit: 60
-
-epoch_counter: *id011
-normalize: *id010
-augmentation: !new:speechbrain.lobes.augment.SpecAugment
-  time_warp: true
-  time_warp_window: 5
-  time_warp_mode: bicubic
-  freq_mask: true
-  n_freq_mask: 2
-  time_mask: true
-  n_time_mask: 2
-  replace_with_zero: false
-  freq_mask_width: 30
-  time_mask_width: 40
-
-remove_spaces: true
-split_tokens: &id012 !apply:operator.not_ [true]
-
-cer_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
-  split_tokens: *id012
-acc_computer: !name:speechbrain.utils.Accuracy.AccuracyStats

ASR-model/asr_transformer_seg_char_ctc0.3/results/asr_transformer_seg_char/log.txt

@@ -1,120 +0,0 @@
-2023-07-05 14:57:01,987 - speechbrain.core - INFO - Beginning experiment!
-2023-07-05 14:57:01,987 - speechbrain.core - INFO - Experiment folder: results/asr_transformer_seg_char
-2023-07-05 14:57:02,208 - speechbrain.utils.superpowers - DEBUG - antlr4-python3-runtime==4.8
-anyio==3.7.0
-astroid==2.15.5
-bitarray==2.7.6
-certifi==2023.5.7
-cffi==1.15.1
-cfgv==3.3.1
-charset-normalizer==3.1.0
-click==7.1.2
-cmake==3.26.4
-colorama==0.4.6
-Cython==0.29.36
-dill==0.3.6
-distlib==0.3.6
-exceptiongroup==1.1.2
-fairseq @ git+https://github.com/facebookresearch/fairseq.git@31fba013a070eaff69dec8642e68e7134d60ab0f
-fastapi==0.98.0
-filelock==3.12.2
-flake8==6.0.0
-fsspec==2023.6.0
-h11==0.14.0
-httpcore==0.17.2
-httptools==0.1.2
-httpx==0.24.1
-huggingface-hub==0.15.1
-hydra-core==1.0.7
-HyperPyYAML==1.2.1
-identify==2.5.24
-idna==3.4
-importlib-resources==5.12.0
-iniconfig==2.0.0
-isort==5.12.0
-jieba==0.42.1
-Jinja2==3.1.2
-joblib==1.3.1
-lazy-object-proxy==1.9.0
-lit==16.0.6
-lxml==4.9.2
-MarkupSafe==2.1.3
-mccabe==0.7.0
-mock==5.0.2
-mpmath==1.3.0
-networkx==3.1
-nodeenv==1.8.0
-numpy==1.24.4
-nvidia-cublas-cu11==11.10.3.66
-nvidia-cuda-cupti-cu11==11.7.101
-nvidia-cuda-nvrtc-cu11==11.7.99
-nvidia-cuda-runtime-cu11==11.7.99
-nvidia-cudnn-cu11==8.5.0.96
-nvidia-cufft-cu11==10.9.0.58
-nvidia-curand-cu11==10.2.10.91
-nvidia-cusolver-cu11==11.4.0.1
-nvidia-cusparse-cu11==11.7.4.91
-nvidia-nccl-cu11==2.14.3
-nvidia-nvtx-cu11==11.7.91
-omegaconf==2.0.6
-packaging==23.1
-platformdirs==3.8.0
-pluggy==1.2.0
-portalocker==2.7.0
-pre-commit==3.3.3
-pycodestyle==2.10.0
-pycparser==2.21
-pydantic==1.10.9
-pyflakes==3.0.1
-pylint==2.17.4
-pytest==7.4.0
-python-multipart==0.0.6
-PyYAML==6.0
-regex==2023.6.3
-requests==2.31.0
-ruamel.yaml==0.17.28
-ruamel.yaml.clib==0.2.7
-sacrebleu==2.3.1
-scikit-learn==1.3.0
-scipy==1.10.1
-sentencepiece==0.1.99
-sniffio==1.3.0
-speechbrain==0.5.14
-starlette==0.27.0
-subword-nmt==0.3.8
-sympy==1.12
-tabulate==0.9.0
-threadpoolctl==3.1.0
-tomli==2.0.1
-tomlkit==0.11.8
-torch==2.0.1
-torchaudio==2.0.2
-tqdm==4.65.0
-triton==2.0.0
-typing_extensions==4.7.1
-urllib3==2.0.3
-uvicorn==0.11.3
-uvloop==0.17.0
-virtualenv==20.23.1
-websockets==8.1
-wrapt==1.15.0
-zipp==3.15.0
-
-
-2023-07-05 14:57:02,231 - speechbrain.utils.parameter_transfer - DEBUG - Collecting files (or symlinks) for pretraining in results/asr_transformer_seg_char/save.
-2023-07-05 14:57:02,231 - speechbrain.pretrained.fetching - INFO - Fetch model.ckpt: Delegating to Huggingface hub, source results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00.
-2023-07-05 14:57:02,290 - speechbrain.core - ERROR - Exception:
-Traceback (most recent call last):
-  File "test.py", line 308, in <module>
-    run_on_main(hparams["pretrainer"].collect_files)
-  File "/home/sinica_axel/miniconda3/envs/asr_api/lib/python3.8/site-packages/speechbrain/utils/distributed.py", line 61, in run_on_main
-    func(*args, **kwargs)
-  File "/home/sinica_axel/miniconda3/envs/asr_api/lib/python3.8/site-packages/speechbrain/utils/parameter_transfer.py", line 202, in collect_files
-    path = fetch(
-  File "/home/sinica_axel/miniconda3/envs/asr_api/lib/python3.8/site-packages/speechbrain/pretrained/fetching.py", line 120, in fetch
-    fetched_file = huggingface_hub.hf_hub_download(
-  File "/home/sinica_axel/miniconda3/envs/asr_api/lib/python3.8/site-packages/huggingface_hub/utils/_validators.py", line 110, in _inner_fn
-    validate_repo_id(arg_value)
-  File "/home/sinica_axel/miniconda3/envs/asr_api/lib/python3.8/site-packages/huggingface_hub/utils/_validators.py", line 158, in validate_repo_id
-    raise HFValidationError(
-huggingface_hub.utils._validators.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': 'results/TransformerLM_seg_char/save/CKPT+2021-10-05+20-55-37+00'. Use `repo_type` argument if needed.

ASR-model/asr_transformer_seg_char_ctc0.3/results/asr_transformer_seg_char/test.py

@@ -1,331 +0,0 @@
-import sys
-
-import torch
-import speechbrain as sb
-from speechbrain.utils.distributed import run_on_main
-from hyperpyyaml import load_hyperpyyaml
-
-
-class ASR(sb.core.Brain):
-    def compute_forward(self, batch, stage):
-        batch = batch.to(self.device)
-        wavs, wavs_len = batch.sig
-        tokens_bos, _ = batch.tokens_bos
-
-        feats = self.hparams.compute_features(wavs)
-        current_epoch = self.hparams.epoch_counter.current
-        feats = self.hparams.normalize(feats, wavs_len, epoch=current_epoch)
-
-        # if stage == sb.Stage.TRAIN:
-        #     if hasattr(self.modules, "augmentation"):
-        #         feats = self.hparams.augmentation(feats)
-
-        src = self.modules.CNN(feats)
-        enc_out, pred = self.modules.Transformer(
-            src, tokens_bos, wavs_len, pad_idx=self.hparams.pad_index
-        )
-
-        logits = self.modules.ctc_lin(enc_out)
-        p_ctc = self.hparams.log_softmax(logits)
-
-        pred = self.hparams.seq_lin(pred)
-        p_seq = self.hparams.log_softmax(pred)
-
-        hyps = None
-        if stage == sb.Stage.TRAIN:
-            hyps = None
-        elif stage == sb.Stage.VALID:
-            hyps = None
-            current_epoch = self.hparams.epoch_counter.current
-            if current_epoch % self.hparams.valid_search_interval == 0:
-                # for the sake of efficiency, we only perform beamsearch with limited capacity
-                # and no LM to give user some idea of how the AM is doing
-                hyps, _ = self.hparams.valid_search(enc_out.detach(), wavs_len)
-        elif stage == sb.Stage.TEST:
-            hyps, _ = self.hparams.test_search(enc_out.detach(), wavs_len)
-
-        return p_ctc, p_seq, wavs_len, hyps
-
-    def compute_objectives(self, predictions, batch, stage):
-
-        (p_ctc, p_seq, wavs_len, hyps,) = predictions
-
-        ids = batch.id
-        tokens_eos, tokens_eos_len = batch.tokens_eos
-        tokens, tokens_len = batch.tokens
-
-        attention_loss = self.hparams.seq_cost(
-            p_seq, tokens_eos, tokens_eos_len
-        )
-        ctc_loss = self.hparams.ctc_cost(p_ctc, tokens, wavs_len, tokens_len)
-        loss = (
-            self.hparams.ctc_weight * ctc_loss
-            + (1 - self.hparams.ctc_weight) * attention_loss
-        )
-
-        if stage != sb.Stage.TRAIN:
-            current_epoch = self.hparams.epoch_counter.current
-            valid_search_interval = self.hparams.valid_search_interval
-
-            if current_epoch % valid_search_interval == 0 or (
-                stage == sb.Stage.TEST
-            ):
-                predictions = [
-                    self.hparams.tokenizer.decode_ids(utt_seq).split(" ")
-                    for utt_seq in hyps
-                ]
-                targets = [
-                    transcription.split(" ")
-                    for transcription in batch.transcription
-                ]
-                if self.hparams.remove_spaces:
-                    predictions = [
-                        "".join(prediction_words)
-                        for prediction_words in predictions
-                    ]
-                    targets = [
-                        "".join(target_words) for target_words in targets
-                    ]
-                    self.cer_metric.append(ids, predictions, targets)
-
-            self.acc_metric.append(p_seq, tokens_eos, tokens_eos_len)
-
-        return loss
-
-    def fit_batch(self, batch):
-        self.check_and_reset_optimizer()
-
-        predictions = self.compute_forward(batch, sb.Stage.TRAIN)
-        loss = self.compute_objectives(predictions, batch, sb.Stage.TRAIN)
-
-        (loss / self.hparams.gradient_accumulation).backward()
-
-        if self.step % self.hparams.gradient_accumulation == 0:
-            self.check_gradients(loss)
-
-            self.optimizer.step()
-            self.optimizer.zero_grad()
-
-            self.hparams.noam_annealing(self.optimizer)
-
-        return loss.detach()
-
-    def evaluate_batch(self, batch, stage):
-        with torch.no_grad():
-            predictions = self.compute_forward(batch, stage=stage)
-            loss = self.compute_objectives(predictions, batch, stage=stage)
-        # origin function is call loss.detach().cpu()
-        return loss.detach()
-
-    def on_stage_start(self, stage, epoch):
-        if stage != sb.Stage.TRAIN:
-            self.acc_metric = self.hparams.acc_computer()
-            self.cer_metric = self.hparams.cer_computer()
-
-    def on_stage_end(self, stage, stage_loss, epoch):
-        stage_stats = {"loss": stage_loss}
-        if stage == sb.Stage.TRAIN:
-            self.train_stats = stage_stats
-        else:
-            stage_stats["ACC"] = self.acc_metric.summarize()
-            current_epoch = self.hparams.epoch_counter.current
-            valid_search_interval = self.hparams.valid_search_interval
-            if (
-                current_epoch % valid_search_interval == 0
-                or stage == sb.Stage.TEST
-            ):
-                stage_stats["CER"] = self.cer_metric.summarize("error_rate")
-
-        if stage == sb.Stage.VALID and sb.utils.distributed.if_main_process():
-
-            current_epoch = self.hparams.epoch_counter.current
-            if current_epoch <= self.hparams.stage_one_epochs:
-                lr = self.hparams.noam_annealing.current_lr
-                steps = self.hparams.noam_annealing.n_steps
-                optimizer = self.optimizer.__class__.__name__
-            else:
-                lr = self.hparams.lr_sgd
-                steps = -1
-                optimizer = self.optimizer.__class__.__name__
-
-            epoch_stats = {
-                "epoch": epoch,
-                "lr": lr,
-                "steps": steps,
-                "optimizer": optimizer,
-            }
-            self.hparams.train_logger.log_stats(
-                stats_meta=epoch_stats,
-                train_stats=self.train_stats,
-                valid_stats=stage_stats,
-            )
-            self.checkpointer.save_and_keep_only(
-                meta={"ACC": stage_stats["ACC"], "epoch": epoch},
-                max_keys=["ACC"],
-                num_to_keep=10,
-            )
-
-        elif stage == sb.Stage.TEST:
-            self.hparams.train_logger.log_stats(
-                stats_meta={"Epoch loaded": self.hparams.epoch_counter.current},
-                test_stats=stage_stats,
-            )
-            with open(self.hparams.cer_file, "w") as cer_file:
-                self.cer_metric.write_stats(cer_file)
-
-            self.checkpointer.save_and_keep_only(
-                meta={"ACC": 1.1, "epoch": epoch},
-                max_keys=["ACC"],
-                num_to_keep=1,
-            )
-
-    def check_and_reset_optimizer(self):
-        current_epoch = self.hparams.epoch_counter.current
-        if not hasattr(self, "switched"):
-            self.switched = False
-            if isinstance(self.optimizer, torch.optim.SGD):
-                self.switched = True
-
-        if self.switched is True:
-            return
-
-        if current_epoch > self.hparams.stage_one_epochs:
-            self.optimizer = self.hparams.SGD(self.modules.parameters())
-
-            if self.checkpointer is not None:
-                self.checkpointer.add_recoverable("optimizer", self.optimizer)
-
-            self.switched = True
-
-    def on_fit_start(self):
-        """Initialize the right optimizer on the training start"""
-        super().on_fit_start()
-
-        current_epoch = self.hparams.epoch_counter.current
-        current_optimizer = self.optimizer
-        if current_epoch > self.hparams.stage_one_epochs:
-            del self.optimizer
-            self.optimizer = self.hparams.SGD(self.modules.parameters())
-
-            if self.checkpointer is not None:
-                group = current_optimizer.param_groups[0]
-                if "momentum" not in group:
-                    return
-                self.checkpointer.recover_if_possible(
-                    device=torch.device(self.device)
-                )
-
-    def on_evaluate_start(self, max_key=None, min_key=None):
-        super().on_evaluate_start()
-
-        checkpointer = self.checkpointer.find_checkpoints(
-            max_key=max_key, min_key=min_key
-        )
-        checkpointer = sb.utils.checkpoints.average_checkpoints(
-            checkpointer, recoverable_name="model", device=self.device
-        )
-
-        self.hparams.model.load_state_dict(checkpointer, strict=True)
-        self.hparams.model.eval()
-
-
-def dataio_prepare(hparams):
-    @sb.utils.data_pipeline.takes("transcription")
-    @sb.utils.data_pipeline.provides(
-        "transcription", "tokens_bos", "tokens_eos", "tokens"
-    )
-    def transcription_pipline(transcription):
-        yield transcription
-        tokens_list = hparams["tokenizer"].encode_as_ids(transcription)
-        tokens_bos = torch.LongTensor([hparams["bos_index"]] + (tokens_list))
-        yield tokens_bos
-        tokens_eos = torch.LongTensor(tokens_list + [hparams["eos_index"]])
-        yield tokens_eos
-        tokens = torch.LongTensor(tokens_list)
-        yield tokens
-
-    @sb.utils.data_pipeline.takes("wav")
-    @sb.utils.data_pipeline.provides("sig")
-    def audio_pipline(wav):
-        sig = sb.dataio.dataio.read_audio(wav)
-        return sig
-
-    @sb.utils.data_pipeline.takes("wav")
-    @sb.utils.data_pipeline.provides("sig")
-    def sp_audio_pipline(wav):
-        sig = sb.dataio.dataio.read_audio(wav)
-        sig = sig.unsqueeze(0)
-        sig = hparams["speed_perturb"](sig)
-        sig = sig.squeeze(0)
-        return sig
-
-    datasets = {}
-    data_folder = hparams["data_folder"]
-    output_keys = [
-        "transcription",
-        "tokens_bos",
-        "tokens_eos",
-        "tokens",
-        "sig",
-        "id",
-    ]
-    default_dynamic_items = [transcription_pipline, audio_pipline]
-    train_dynamic_item = [transcription_pipline, sp_audio_pipline]
-
-    for dataset_name in ["train", "dev", "test"]:
-        if dataset_name == "train":
-            dynamic_items = train_dynamic_item
-        else:
-            dynamic_items = default_dynamic_items
-
-        json_path = f"{data_folder}/{dataset_name}.json"
-        datasets[dataset_name] = sb.dataio.dataset.DynamicItemDataset.from_json(
-            json_path=json_path,
-            replacements={"data_root": data_folder},
-            dynamic_items=dynamic_items,
-            output_keys=output_keys,
-        )
-
-    return datasets
-
-
-if __name__ == "__main__":
-    #hparams_file_path, run_opts, overrides = sb.parse_arguments(sys.argv[1:])
-    hparams_file_path = "hyperparams.yaml"
-    run_opts = {"device": "cuda", "distributed_launch": False}
-    overrides = None
-    with open(hparams_file_path) as hparams_file:
-        hparams = load_hyperpyyaml(hparams_file, overrides)
-
-    sb.utils.distributed.ddp_init_group(run_opts)
-
-    sb.create_experiment_directory(
-        experiment_directory=hparams["output_folder"],
-        hyperparams_to_save=hparams_file_path,
-        overrides=overrides,
-    )
-
-    run_on_main(hparams["pretrainer"].collect_files)
-    hparams["pretrainer"].load_collected(device=run_opts["device"])
-
-    datasets = dataio_prepare(hparams)
-
-    asr_brain = ASR(
-        modules=hparams["modules"],
-        opt_class=hparams["Adam"],
-        hparams=hparams,
-        run_opts=run_opts,
-        checkpointer=hparams["checkpointer"],
-    )
-
-    # asr_brain.fit(
-    #     asr_brain.hparams.epoch_counter,
-    #     datasets["train"],
-    #     datasets["dev"],
-    #     train_loader_kwargs=hparams["train_dataloader_opts"],
-    #     valid_loader_kwargs=hparams["valid_dataloader_opts"],
-    # )
-
-    asr_brain.evaluate(
-        datasets["test"], max_key="ACC", test_loader_kwargs=hparams["test_dataloader_opts"]
-    )

ASR-model/asr_transformer_seg_char_ctc0.3/save/CKPT+2021-10-11+14-03-15+00/CKPT.yaml

@@ -1,5 +0,0 @@
-# yamllint disable
-ACC: 1.1
-end-of-epoch: true
-epoch: null
-unixtime: 1633932195.1636646

ASR-model/asr_transformer_seg_char_ctc0.3/save/CKPT+2021-10-11+14-03-15+00/brain.ckpt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:22e854e25aa2ad065885cf277f6017bfa7ab555eb84131dfa2da35605cb8fb14
-size 32

ASR-model/asr_transformer_seg_char_ctc0.3/save/CKPT+2021-10-11+14-03-15+00/counter.ckpt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:39fa9ec190eee7b6f4dff1100d6343e10918d044c75eac8f9e9a2596173f80c9
-size 2

ASR-model/asr_transformer_seg_char_ctc0.3/save/CKPT+2021-10-11+14-03-15+00/model.ckpt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9f325dfc2ecffc1332882e84cac08a9f05e500253413c2346a20f35baaeed705
-size 126713830

ASR-model/asr_transformer_seg_char_ctc0.3/save/CKPT+2021-10-11+14-03-15+00/noam_scheduler.ckpt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:35ce303ccbe8d1abb2b87a01a29e01ed6a7b345253ab6db9111cbd5eefbf503c
-size 431

ASR-model/asr_transformer_seg_char_ctc0.3/save/CKPT+2021-10-11+14-03-15+00/normalizer.ckpt

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3c4aa56041d2ead93019a7781f786d29cc577aaf24f4766574c47867a2078f80
-size 1782

ASR-model/asr_transformer_seg_char_ctc0.3/test.py

@@ -1,181 +0,0 @@
-import sys
-
-import torch
-import speechbrain as sb
-from speechbrain.utils.distributed import run_on_main
-from hyperpyyaml import load_hyperpyyaml
-
-
-class ASR(sb.core.Brain):
-    def compute_forward(self, batch, stage):
-        batch = batch.to(self.device)
-        wavs, wavs_len = batch.sig
-        tokens_bos, _ = batch.tokens_bos
-
-        feats = self.hparams.compute_features(wavs)
-        current_epoch = self.hparams.epoch_counter.current
-        feats = self.hparams.normalize(feats, wavs_len, epoch=current_epoch)
-
-        # if stage == sb.Stage.TRAIN:
-        #     if hasattr(self.modules, "augmentation"):
-        #         feats = self.hparams.augmentation(feats)
-
-        src = self.modules.CNN(feats)
-        enc_out, pred = self.modules.Transformer(
-            src, tokens_bos, wavs_len, pad_idx=self.hparams.pad_index
-        )
-
-        logits = self.modules.ctc_lin(enc_out)
-        p_ctc = self.hparams.log_softmax(logits)
-
-        pred = self.hparams.seq_lin(pred)
-        p_seq = self.hparams.log_softmax(pred)
-
-        hyps = None
-        if stage == sb.Stage.TRAIN:
-            hyps = None
-        elif stage == sb.Stage.VALID:
-            hyps = None
-            current_epoch = self.hparams.epoch_counter.current
-            if current_epoch % self.hparams.valid_search_interval == 0:
-                # for the sake of efficiency, we only perform beamsearch with limited capacity
-                # and no LM to give user some idea of how the AM is doing
-                hyps, _ = self.hparams.valid_search(enc_out.detach(), wavs_len)
-        elif stage == sb.Stage.TEST:
-            hyps, _ = self.hparams.test_search(enc_out.detach(), wavs_len)
-
-        return p_ctc, p_seq, wavs_len, hyps
-
-    def evaluate_batch(self, batch, stage):
-        with torch.no_grad():
-            predictions = self.compute_forward(batch, stage=stage)
-            loss = self.compute_objectives(predictions, batch, stage=stage)
-        # origin function is call loss.detach().cpu()
-        return loss.detach()
-
-    def on_stage_start(self, stage, epoch):
-        if stage != sb.Stage.TRAIN:
-            self.acc_metric = self.hparams.acc_computer()
-            self.cer_metric = self.hparams.cer_computer()
-
-    def on_stage_end(self, stage, stage_loss, epoch):
-        stage_stats = {"loss": stage_loss}
-        if stage == sb.Stage.TRAIN:
-            self.train_stats = stage_stats
-        else:
-            stage_stats["ACC"] = self.acc_metric.summarize()
-            current_epoch = self.hparams.epoch_counter.current
-            valid_search_interval = self.hparams.valid_search_interval
-            if (
-                current_epoch % valid_search_interval == 0
-                or stage == sb.Stage.TEST
-            ):
-                stage_stats["CER"] = self.cer_metric.summarize("error_rate")
-
-        if stage == sb.Stage.VALID and sb.utils.distributed.if_main_process():
-
-            current_epoch = self.hparams.epoch_counter.current
-            if current_epoch <= self.hparams.stage_one_epochs:
-                lr = self.hparams.noam_annealing.current_lr
-                steps = self.hparams.noam_annealing.n_steps
-                optimizer = self.optimizer.__class__.__name__
-            else:
-                lr = self.hparams.lr_sgd
-                steps = -1
-                optimizer = self.optimizer.__class__.__name__
-
-            epoch_stats = {
-                "epoch": epoch,
-                "lr": lr,
-                "steps": steps,
-                "optimizer": optimizer,
-            }
-            self.hparams.train_logger.log_stats(
-                stats_meta=epoch_stats,
-                train_stats=self.train_stats,
-                valid_stats=stage_stats,
-            )
-            self.checkpointer.save_and_keep_only(
-                meta={"ACC": stage_stats["ACC"], "epoch": epoch},
-                max_keys=["ACC"],
-                num_to_keep=10,
-            )
-
-        elif stage == sb.Stage.TEST:
-            self.hparams.train_logger.log_stats(
-                stats_meta={"Epoch loaded": self.hparams.epoch_counter.current},
-                test_stats=stage_stats,
-            )
-            with open(self.hparams.cer_file, "w") as cer_file:
-                self.cer_metric.write_stats(cer_file)
-
-            self.checkpointer.save_and_keep_only(
-                meta={"ACC": 1.1, "epoch": epoch},
-                max_keys=["ACC"],
-                num_to_keep=1,
-            )
-
-    def check_and_reset_optimizer(self):
-        current_epoch = self.hparams.epoch_counter.current
-        if not hasattr(self, "switched"):
-            self.switched = False
-            if isinstance(self.optimizer, torch.optim.SGD):
-                self.switched = True
-
-        if self.switched is True:
-            return
-
-        if current_epoch > self.hparams.stage_one_epochs:
-            self.optimizer = self.hparams.SGD(self.modules.parameters())
-
-            if self.checkpointer is not None:
-                self.checkpointer.add_recoverable("optimizer", self.optimizer)
-
-            self.switched = True
-
-    def on_fit_start(self):
-        """Initialize the right optimizer on the training start"""
-        super().on_fit_start()
-
-        current_epoch = self.hparams.epoch_counter.current
-        current_optimizer = self.optimizer
-        if current_epoch > self.hparams.stage_one_epochs:
-            del self.optimizer
-            self.optimizer = self.hparams.SGD(self.modules.parameters())
-
-            if self.checkpointer is not None:
-                group = current_optimizer.param_groups[0]
-                if "momentum" not in group:
-                    return
-                self.checkpointer.recover_if_possible(
-                    device=torch.device(self.device)
-                )
-
-    def on_evaluate_start(self, max_key=None, min_key=None):
-        super().on_evaluate_start()
-
-        checkpointer = self.checkpointer.find_checkpoints(
-            max_key=max_key, min_key=min_key
-        )
-        checkpointer = sb.utils.checkpoints.average_checkpoints(
-            checkpointer, recoverable_name="model", device=self.device
-        )
-
-        self.hparams.model.load_state_dict(checkpointer, strict=True)
-        self.hparams.model.eval()
-
-
-if __name__ == "__main__":
-    hparams_file_path = "hyperparams.yaml"
-    run_opts = {"device": "cuda", "distributed_launch": False}
-    with open(hparams_file_path) as hparams_file:
-        hparams = load_hyperpyyaml(hparams_file)
-
-    asr_brain = ASR(
-        modules=hparams["modules"],
-        opt_class=hparams["Adam"],
-        hparams=hparams,
-        run_opts=run_opts,
-        checkpointer=hparams["checkpointer"],
-    )
-

ASR-model/asr_transformer_seg_char_ctc0.3/train.py

@@ -1,322 +0,0 @@
-import sys
-
-import torch
-import speechbrain as sb
-from speechbrain.utils.distributed import run_on_main
-from hyperpyyaml import load_hyperpyyaml
-
-
-class ASR(sb.core.Brain):
-    def compute_forward(self, batch, stage):
-        batch = batch.to(self.device)
-        wavs, wavs_len = batch.sig
-        tokens_bos, _ = batch.tokens_bos
-        feats = self.hparams.compute_features(wavs)
-        current_epoch = self.hparams.epoch_counter.current
-        feats = self.modules.normalize(feats, wavs_len, epoch=current_epoch)
-
-        src = self.modules.CNN(feats)
-        enc_out, pred = self.modules.Transformer(
-            src, tokens_bos, wavs_len, pad_idx=self.hparams.pad_index
-        )
-
-        logits = self.modules.ctc_lin(enc_out)
-        p_ctc = self.hparams.log_softmax(logits)
-
-        pred = self.modules.seq_lin(pred)
-        p_seq = self.hparams.log_softmax(pred)
-
-        hyps = None
-        if stage == sb.Stage.TRAIN:
-            hyps = None
-        elif stage == sb.Stage.VALID:
-            hyps = None
-            current_epoch = self.hparams.epoch_counter.current
-            if current_epoch % self.hparams.valid_search_interval == 0:
-                hyps, _ = self.hparams.valid_search(enc_out.detach(), wavs_len)
-        elif stage == sb.Stage.TEST:
-            hyps, _ = self.hparams.test_search(enc_out.detach(), wavs_len)
-
-        return p_ctc, p_seq, wavs_len, hyps
-
-    def compute_objectives(self, predictions, batch, stage):
-
-        (p_ctc, p_seq, wavs_len, hyps,) = predictions
-
-        ids = batch.id
-        tokens_eos, tokens_eos_len = batch.tokens_eos
-        tokens, tokens_len = batch.tokens
-
-        attention_loss = self.hparams.seq_cost(
-            p_seq, tokens_eos, length=tokens_eos_len
-        )
-        ctc_loss = self.hparams.ctc_cost(p_ctc, tokens, wavs_len, tokens_len)
-        loss = (
-            self.hparams.ctc_weight * ctc_loss
-            + (1 - self.hparams.ctc_weight) * attention_loss
-        )
-
-        if stage != sb.Stage.TRAIN:
-            current_epoch = self.hparams.epoch_counter.current
-            valid_search_interval = self.hparams.valid_search_interval
-
-            if current_epoch % valid_search_interval == 0 or (
-                stage == sb.Stage.TEST
-            ):
-                predictions = [
-                    hparams["tokenizer"].decode_ids(utt_seq).split(" ")
-                    for utt_seq in hyps
-                ]
-                targets = [
-                    transcription.split(" ")
-                    for transcription in batch.transcription
-                ]
-                if self.hparams.remove_spaces:
-                    predictions = [
-                        "".join(prediction_words)
-                        for prediction_words in predictions
-                    ]
-                    targets = [
-                        "".join(target_words) for target_words in targets
-                    ]
-                    self.cer_metric.append(ids, predictions, targets)
-
-            self.acc_metric.append(p_seq, tokens_eos, tokens_eos_len)
-
-        return loss
-
-    def fit_batch(self, batch):
-        self.check_and_reset_optimizer()
-
-        predictions = self.compute_forward(batch, sb.Stage.TRAIN)
-        loss = self.compute_objectives(predictions, batch, sb.Stage.TRAIN)
-
-        (loss / self.hparams.gradient_accumulation).backward()
-
-        if self.step % self.hparams.gradient_accumulation == 0:
-            self.check_gradients(loss)
-
-            self.optimizer.step()
-            self.optimizer.zero_grad()
-
-            self.hparams.noam_annealing(self.optimizer)
-
-        return loss.detach()
-
-    def evaluate_batch(self, batch, stage):
-        with torch.no_grad():
-            predictions = self.compute_forward(batch, stage=stage)
-            loss = self.compute_objectives(predictions, batch, stage=stage)
-        # origin function is call loss.detach().cpu()
-        return loss.detach()
-
-    def on_stage_start(self, stage, epoch):
-        if stage != sb.Stage.TRAIN:
-            self.acc_metric = self.hparams.acc_computer()
-            self.cer_metric = self.hparams.cer_computer()
-
-    def on_stage_end(self, stage, stage_loss, epoch):
-        stage_stats = {"loss": stage_loss}
-        if stage == sb.Stage.TRAIN:
-            self.train_stats = stage_stats
-        else:
-            stage_stats["ACC"] = self.acc_metric.summarize()
-            current_epoch = self.hparams.epoch_counter.current
-            valid_search_interval = self.hparams.valid_search_interval
-            if (
-                current_epoch % valid_search_interval == 0
-                or stage == sb.Stage.TEST
-            ):
-                stage_stats["CER"] = self.cer_metric.summarize("error_rate")
-
-        if stage == sb.Stage.VALID and sb.utils.distributed.if_main_process():
-
-            current_epoch = self.hparams.epoch_counter.current
-            if current_epoch <= self.hparams.stage_one_epochs:
-                lr = self.hparams.noam_annealing.current_lr
-                steps = self.hparams.noam_annealing.n_steps
-                optimizer = self.optimizer.__class__.__name__
-            else:
-                lr = self.hparams.lr_sgd
-                steps = -1
-                optimizer = self.optimizer.__class__.__name__
-
-            epoch_stats = {
-                "epoch": epoch,
-                "lr": lr,
-                "steps": steps,
-                "optimizer": optimizer,
-            }
-            self.hparams.train_logger.log_stats(
-                stats_meta=epoch_stats,
-                train_stats=self.train_stats,
-                valid_stats=stage_stats,
-            )
-            self.checkpointer.save_and_keep_only(
-                meta={"ACC": stage_stats["ACC"], "epoch": epoch},
-                max_keys=["ACC"],
-                num_to_keep=10,
-            )
-
-        elif stage == sb.Stage.TEST:
-            self.hparams.train_logger.log_stats(
-                stats_meta={"Epoch loaded": self.hparams.epoch_counter.current},
-                test_stats=stage_stats,
-            )
-            with open(self.hparams.cer_file, "w") as cer_file:
-                self.cer_metric.write_stats(cer_file)
-
-            self.checkpointer.save_and_keep_only(
-                meta={"ACC": 1.1, "epoch": epoch},
-                max_keys=["ACC"],
-                num_to_keep=1,
-            )
-
-    def check_and_reset_optimizer(self):
-        current_epoch = self.hparams.epoch_counter.current
-        if not hasattr(self, "switched"):
-            self.switched = False
-            if isinstance(self.optimizer, torch.optim.SGD):
-                self.switched = True
-
-        if self.switched is True:
-            return
-
-        if current_epoch > self.hparams.stage_one_epochs:
-            self.optimizer = self.hparams.SGD(self.modules.parameters())
-
-            if self.checkpointer is not None:
-                self.checkpointer.add_recoverable("optimizer", self.optimizer)
-
-            self.switched = True
-
-    def on_fit_start(self):
-        """Initialize the right optimizer on the training start"""
-        super().on_fit_start()
-
-        current_epoch = self.hparams.epoch_counter.current
-        current_optimizer = self.optimizer
-        if current_epoch > self.hparams.stage_one_epochs:
-            del self.optimizer
-            self.optimizer = self.hparams.SGD(self.modules.parameters())
-
-            if self.checkpointer is not None:
-                group = current_optimizer.param_groups[0]
-                if "momentum" not in group:
-                    return
-                self.checkpointer.recover_if_possible(
-                    device=torch.device(self.device)
-                )
-
-    def on_evaluate_start(self, max_key=None, min_key=None):
-        super().on_evaluate_start()
-
-        checkpointers = self.checkpointer.find_checkpoints(
-            max_key=max_key, min_key=min_key
-        )
-        checkpointer = sb.utils.checkpoints.average_checkpoints(
-            checkpointers, recoverable_name="model", device=self.device
-        )
-
-        self.hparams.model.load_state_dict(checkpointer, strict=True)
-        self.hparams.model.eval()
-
-
-def dataio_prepare(hparams):
-    @sb.utils.data_pipeline.takes("transcription")
-    @sb.utils.data_pipeline.provides(
-        "transcription", "tokens_bos", "tokens_eos", "tokens"
-    )
-    def transcription_pipline(transcription):
-        yield transcription
-        tokens_list = hparams["tokenizer"].encode_as_ids(transcription)
-        tokens_bos = torch.LongTensor([hparams["bos_index"]] + (tokens_list))
-        yield tokens_bos
-        tokens_eos = torch.LongTensor(tokens_list + [hparams["eos_index"]])
-        yield tokens_eos
-        tokens = torch.LongTensor(tokens_list)
-        yield tokens
-
-    @sb.utils.data_pipeline.takes("wav")
-    @sb.utils.data_pipeline.provides("sig")
-    def audio_pipline(wav):
-        sig = sb.dataio.dataio.read_audio(wav)
-        return sig
-
-    @sb.utils.data_pipeline.takes("wav")
-    @sb.utils.data_pipeline.provides("sig")
-    def sp_audio_pipline(wav):
-        sig = sb.dataio.dataio.read_audio(wav)
-        sig = sig.unsqueeze(0)
-        sig = hparams["speed_perturb"](sig)
-        sig = sig.squeeze(0)
-        return sig
-
-    datasets = {}
-    data_folder = hparams["data_folder"]
-    output_keys = [
-        "transcription",
-        "tokens_bos",
-        "tokens_eos",
-        "tokens",
-        "sig",
-        "id",
-    ]
-    default_dynamic_items = [transcription_pipline, audio_pipline]
-    train_dynamic_item = [transcription_pipline, sp_audio_pipline]
-
-    for dataset_name in ["train", "dev", "test"]:
-        if dataset_name == "train":
-            dynamic_items = train_dynamic_item
-        else:
-            dynamic_items = default_dynamic_items
-
-        json_path = f"{data_folder}/{dataset_name}.json"
-        datasets[dataset_name] = sb.dataio.dataset.DynamicItemDataset.from_json(
-            json_path=json_path,
-            replacements={"data_root": data_folder},
-            dynamic_items=dynamic_items,
-            output_keys=output_keys,
-        )
-
-    return datasets
-
-
-if __name__ == "__main__":
-    hparams_file_path, run_opts, overrides = sb.parse_arguments(sys.argv[1:])
-
-    sb.utils.distributed.ddp_init_group(run_opts)
-
-    with open(hparams_file_path) as hparams_file:
-        hparams = load_hyperpyyaml(hparams_file, overrides)
-
-    sb.create_experiment_directory(
-        experiment_directory=hparams["output_folder"],
-        hyperparams_to_save=hparams_file_path,
-        overrides=overrides,
-    )
-
-    run_on_main(hparams["pretrainer"].collect_files)
-    hparams["pretrainer"].load_collected(device=run_opts["device"])
-
-    datasets = dataio_prepare(hparams)
-
-    asr_brain = ASR(
-        modules=hparams["modules"],
-        opt_class=hparams["Adam"],
-        hparams=hparams,
-        run_opts=run_opts,
-        checkpointer=hparams["checkpointer"],
-    )
-
-    asr_brain.fit(
-        asr_brain.hparams.epoch_counter,
-        datasets["train"],
-        datasets["dev"],
-        train_loader_kwargs=hparams["train_dataloader_opts"],
-        valid_loader_kwargs=hparams["valid_dataloader_opts"],
-    )
-
-    # asr_brain.evaluate(
-    #     datasets["test"],max_key="ACC", test_loader_kwargs=hparams["test_dataloader_opts"]
-    # )

ASR-model/asr_transformer_seg_char_ctc0.3/train_log.txt

@@ -1,70 +0,0 @@
-epoch: 1, lr: 2.40e-05, steps: 1520, optimizer: Adam - train loss: 3.41e+02 - valid loss: 2.52e+02, valid ACC: 4.07e-01
-epoch: 2, lr: 4.81e-05, steps: 3040, optimizer: Adam - train loss: 2.36e+02 - valid loss: 2.26e+02, valid ACC: 4.36e-01
-epoch: 3, lr: 7.21e-05, steps: 4560, optimizer: Adam - train loss: 2.17e+02 - valid loss: 2.12e+02, valid ACC: 4.66e-01
-epoch: 4, lr: 9.61e-05, steps: 6080, optimizer: Adam - train loss: 2.05e+02 - valid loss: 2.02e+02, valid ACC: 4.86e-01
-epoch: 5, lr: 1.20e-04, steps: 7600, optimizer: Adam - train loss: 1.96e+02 - valid loss: 1.92e+02, valid ACC: 4.98e-01
-epoch: 6, lr: 1.44e-04, steps: 9120, optimizer: Adam - train loss: 1.70e+02 - valid loss: 1.51e+02, valid ACC: 5.30e-01
-epoch: 7, lr: 1.68e-04, steps: 10640, optimizer: Adam - train loss: 1.37e+02 - valid loss: 1.14e+02, valid ACC: 6.31e-01
-epoch: 8, lr: 1.92e-04, steps: 12160, optimizer: Adam - train loss: 1.10e+02 - valid loss: 88.56, valid ACC: 7.21e-01
-epoch: 9, lr: 2.16e-04, steps: 13680, optimizer: Adam - train loss: 86.93 - valid loss: 67.36, valid ACC: 8.03e-01
-epoch: 10, lr: 2.40e-04, steps: 15200, optimizer: Adam - train loss: 64.60 - valid loss: 51.05, valid ACC: 8.61e-01, valid CER: 22.14
-epoch: 11, lr: 2.64e-04, steps: 16720, optimizer: Adam - train loss: 51.94 - valid loss: 42.96, valid ACC: 8.86e-01
-epoch: 12, lr: 2.88e-04, steps: 18240, optimizer: Adam - train loss: 44.10 - valid loss: 37.56, valid ACC: 8.99e-01
-epoch: 13, lr: 3.12e-04, steps: 19760, optimizer: Adam - train loss: 38.66 - valid loss: 33.39, valid ACC: 9.09e-01
-epoch: 14, lr: 3.36e-04, steps: 21280, optimizer: Adam - train loss: 34.66 - valid loss: 31.04, valid ACC: 9.16e-01
-epoch: 15, lr: 3.60e-04, steps: 22800, optimizer: Adam - train loss: 31.69 - valid loss: 29.01, valid ACC: 9.19e-01
-epoch: 16, lr: 3.85e-04, steps: 24320, optimizer: Adam - train loss: 29.34 - valid loss: 27.39, valid ACC: 9.24e-01
-epoch: 17, lr: 3.89e-04, steps: 25840, optimizer: Adam - train loss: 27.37 - valid loss: 25.86, valid ACC: 9.28e-01
-epoch: 18, lr: 3.78e-04, steps: 27360, optimizer: Adam - train loss: 25.12 - valid loss: 24.43, valid ACC: 9.32e-01
-epoch: 19, lr: 3.68e-04, steps: 28880, optimizer: Adam - train loss: 23.16 - valid loss: 23.26, valid ACC: 9.35e-01
-epoch: 20, lr: 3.58e-04, steps: 30400, optimizer: Adam - train loss: 21.53 - valid loss: 22.58, valid ACC: 9.37e-01, valid CER: 10.20
-epoch: 21, lr: 3.50e-04, steps: 31920, optimizer: Adam - train loss: 20.06 - valid loss: 21.66, valid ACC: 9.39e-01
-epoch: 22, lr: 3.42e-04, steps: 33440, optimizer: Adam - train loss: 18.83 - valid loss: 21.18, valid ACC: 9.41e-01
-epoch: 23, lr: 3.34e-04, steps: 34960, optimizer: Adam - train loss: 17.77 - valid loss: 20.92, valid ACC: 9.42e-01
-epoch: 24, lr: 3.27e-04, steps: 36480, optimizer: Adam - train loss: 16.80 - valid loss: 20.30, valid ACC: 9.43e-01
-epoch: 25, lr: 3.21e-04, steps: 38000, optimizer: Adam - train loss: 15.91 - valid loss: 19.68, valid ACC: 9.44e-01
-epoch: 26, lr: 3.14e-04, steps: 39520, optimizer: Adam - train loss: 15.12 - valid loss: 19.73, valid ACC: 9.45e-01
-epoch: 27, lr: 3.09e-04, steps: 41040, optimizer: Adam - train loss: 14.41 - valid loss: 19.30, valid ACC: 9.46e-01
-epoch: 28, lr: 3.03e-04, steps: 42560, optimizer: Adam - train loss: 13.79 - valid loss: 18.82, valid ACC: 9.47e-01
-epoch: 29, lr: 2.98e-04, steps: 44080, optimizer: Adam - train loss: 13.15 - valid loss: 19.04, valid ACC: 9.47e-01
-epoch: 30, lr: 2.93e-04, steps: 45600, optimizer: Adam - train loss: 12.66 - valid loss: 18.89, valid ACC: 9.47e-01, valid CER: 8.39
-epoch: 31, lr: 2.88e-04, steps: 47120, optimizer: Adam - train loss: 12.13 - valid loss: 18.66, valid ACC: 9.48e-01
-epoch: 32, lr: 2.83e-04, steps: 48640, optimizer: Adam - train loss: 11.64 - valid loss: 18.51, valid ACC: 9.48e-01
-epoch: 33, lr: 2.79e-04, steps: 50160, optimizer: Adam - train loss: 11.21 - valid loss: 18.36, valid ACC: 9.48e-01
-epoch: 34, lr: 2.75e-04, steps: 51680, optimizer: Adam - train loss: 10.79 - valid loss: 18.65, valid ACC: 9.48e-01
-epoch: 35, lr: 2.71e-04, steps: 53200, optimizer: Adam - train loss: 10.43 - valid loss: 18.40, valid ACC: 9.49e-01
-epoch: 36, lr: 2.67e-04, steps: 54720, optimizer: Adam - train loss: 10.11 - valid loss: 18.29, valid ACC: 9.49e-01
-epoch: 37, lr: 2.64e-04, steps: 56240, optimizer: Adam - train loss: 9.78 - valid loss: 18.32, valid ACC: 9.50e-01
-epoch: 38, lr: 2.60e-04, steps: 57760, optimizer: Adam - train loss: 9.46 - valid loss: 18.12, valid ACC: 9.50e-01
-epoch: 39, lr: 2.57e-04, steps: 59280, optimizer: Adam - train loss: 9.17 - valid loss: 18.36, valid ACC: 9.49e-01
-epoch: 40, lr: 2.53e-04, steps: 60800, optimizer: Adam - train loss: 8.88 - valid loss: 18.29, valid ACC: 9.49e-01, valid CER: 7.93
-epoch: 41, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 7.01 - valid loss: 17.34, valid ACC: 9.54e-01
-epoch: 42, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 6.32 - valid loss: 17.22, valid ACC: 9.54e-01
-epoch: 43, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.97 - valid loss: 17.15, valid ACC: 9.54e-01
-epoch: 44, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.76 - valid loss: 17.14, valid ACC: 9.55e-01
-epoch: 45, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.58 - valid loss: 17.19, valid ACC: 9.54e-01
-epoch: 46, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.45 - valid loss: 17.07, valid ACC: 9.55e-01
-epoch: 47, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.33 - valid loss: 17.07, valid ACC: 9.55e-01
-epoch: 48, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.22 - valid loss: 17.17, valid ACC: 9.55e-01
-epoch: 49, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.13 - valid loss: 17.24, valid ACC: 9.55e-01
-epoch: 50, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 5.04 - valid loss: 17.10, valid ACC: 9.55e-01, valid CER: 7.10
-epoch: 51, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.97 - valid loss: 17.26, valid ACC: 9.55e-01
-epoch: 52, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.88 - valid loss: 17.23, valid ACC: 9.55e-01
-epoch: 53, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.82 - valid loss: 17.17, valid ACC: 9.55e-01
-epoch: 54, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.76 - valid loss: 17.31, valid ACC: 9.55e-01
-epoch: 55, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.71 - valid loss: 17.37, valid ACC: 9.55e-01
-epoch: 56, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.66 - valid loss: 17.26, valid ACC: 9.55e-01
-epoch: 57, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.60 - valid loss: 17.43, valid ACC: 9.55e-01
-epoch: 58, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.54 - valid loss: 17.52, valid ACC: 9.55e-01
-epoch: 59, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.49 - valid loss: 17.42, valid ACC: 9.55e-01
-epoch: 60, lr: 2.50e-05, steps: -1, optimizer: SGD - train loss: 4.45 - valid loss: 17.53, valid ACC: 9.55e-01, valid CER: 7.11
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-Epoch loaded: 60 - test loss: 15.08, test ACC: 9.27e-01, test CER: 7.74 - RNNLM 0.2
-Epoch loaded: 60 - test loss: 10.06, test ACC: 9.27e-01, test CER: 7.97 - w/o LM
-Epoch loaded: 60 - test loss: 7.54, test ACC: 9.27e-01, test CER: 7.62 - TransformerLM 0.1
-Epoch loaded: 60 - test loss: 6.03, test ACC: 9.27e-01, test CER: 7.54 - TransformerLM 0.3
-Epoch loaded: 60 - test loss: 5.03, test ACC: 9.27e-01, test CER: 7.65 - TransformerLM 0.4
-Epoch loaded: 60 - test loss: 4.31, test ACC: 9.27e-01, test CER: 7.87 - TransformerLM 0.5
-Epoch loaded: 60 - test loss: 3.77, test ACC: 9.27e-01, test CER: 8.13 - TransformerLM 0.6
-Epoch loaded: 60 - test loss: 3.35, test ACC: 9.27e-01, test CER: 8.37 - TransformerLM 0.7
-Epoch loaded: 60 - test loss: 3.02, test ACC: 9.27e-01, test CER: 8.74 - TransformerLM 0.8

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ASR-model/tokenizer_seg_bpe5k_char/env.log

@@ -1,195 +0,0 @@
-SpeechBrain system description
-==============================
-Python version:
-3.8.10 (default, Jun  2 2021, 10:49:15) 
-[GCC 9.4.0]
-==============================
-Installed Python packages:
-appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
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-jupyterlab-pygments==0.1.2
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-keyring==18.0.1
-kiwisolver==1.3.1
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-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
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-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
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-nbclient==0.5.3
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-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
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-nvidia-ml-py3==7.352.0
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-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-==============================
-Git revision:
-e3e51338
-==============================
-Cuda version:
-10.2

ASR-model/tokenizer_seg_bpe5k_char/hyperparams.yaml

@@ -1,31 +0,0 @@
-# Generated 2021-10-04 from:
-# /mnt/md0/user_wayne/speechbrain/recipes/MATBN/Tokenizer/hparams/tokenizer_seg_bpe5k_char.yaml
-# yamllint disable
-dataset_folder: /home/wayne/CORPUS/MATBN_SEG
-prepare_folder: results/prepare_seg
-output_folder: results/tokenizer_seg_bpe5k_char
-keep_unk: false
-
-token_type: char # ["unigram", "bpe", "char"]
-token_output: 5000 # index(blank/eos/bos/unk) = 0
-character_coverage: 1.0
-annotation_read: transcription
-
-train_json: results/prepare_seg/train.json
-dev_json: results/prepare_seg/dev.json
-eval_json: results/prepare_seg/eval.json
-test_json: results/prepare_seg/test.json
-
-
-tokenizer: !name:speechbrain.tokenizers.SentencePiece.SentencePiece
-  model_dir: results/tokenizer_seg_bpe5k_char
-  vocab_size: 5000
-  annotation_train: results/prepare_seg/train.json
-  annotation_read: transcription
-  model_type: char              # ["unigram", "bpe", "char"]
-  character_coverage: 1.0
-  annotation_list_to_check: [results/prepare_seg/dev.json, results/prepare_seg/eval.json,
-    results/prepare_seg/test.json]
-  annotation_format: json
-  bos_id: 1
-  eos_id: 2

ASR-model/tokenizer_seg_bpe5k_char/log.txt

@@ -1,1037 +0,0 @@
-2021-09-16 18:20:17,572 - speechbrain.core - INFO - Beginning experiment!
-2021-09-16 18:20:17,572 - speechbrain.core - INFO - Experiment folder: results/tokenizer_seg_bpe5k_char
-2021-09-16 18:20:17,773 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==21.2.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-certifi==2021.5.30
-cffi==1.14.6
-cfgv==3.3.0
-charset-normalizer==2.0.4
-click==8.0.1
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-debugpy==1.3.0
-decorator==5.0.9
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-huggingface-hub==0.0.16
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==3.2
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-joblib==1.0.1
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-kiwisolver==1.3.1
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-mkl-fft==1.3.0
-mkl-random @ file:///tmp/build/80754af9/mkl_random_1626186064646/work
-mkl-service==2.4.0
-more-itertools==8.9.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-olefile @ file:///Users/ktietz/demo/mc3/conda-bld/olefile_1629805411829/work
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pycodestyle==2.5.0
-pycparser==2.20
-pydub @ file:///home/conda/feedstock_root/build_artifacts/pydub_1615612442567/work
-pyflakes==2.1.1
-Pygments==2.9.0
-pyparsing==2.4.7
-pytest==5.4.1
-python-dateutil==2.8.2
-pytube==10.9.3
-PyYAML==5.4.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.26.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scikit-learn @ file:///tmp/build/80754af9/scikit-learn_1621370412049/work
-scipy==1.7.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-six @ file:///tmp/build/80754af9/six_1623709665295/work
--e git+https://github.com/speechbrain/speechbrain.git@2ec4839746970875fc763aa354c44a3356685ef6#egg=speechbrain
-terminado==0.10.1
-testpath==0.5.0
-threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-urllib3==1.26.6
-virtualenv==20.6.0
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xxhash==2.0.2
-yamllint==1.23.0
-
-
-2021-09-16 18:20:17,777 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-09-16 18:20:19,582 - speechbrain.tokenizers.SentencePiece - INFO - Train tokenizer with type:char
-2021-09-16 18:20:19,582 - speechbrain.tokenizers.SentencePiece - INFO - Extract transcription sequences from:results/prepare_seg/train.json
-2021-09-16 18:20:19,788 - speechbrain.tokenizers.SentencePiece - INFO - Text file created at: results/prepare_seg/train.txt
-2021-09-16 18:20:20,080 - speechbrain.tokenizers.SentencePiece - INFO - ==== Loading Tokenizer ===
-2021-09-16 18:20:20,080 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer path: results/tokenizer_seg_bpe5k_char/5000_char.model
-2021-09-16 18:20:20,080 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer vocab_size: 5000
-2021-09-16 18:20:20,080 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer type: char
-2021-09-16 18:20:20,082 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-16 18:20:32,793 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/dev.json
-2021-09-16 18:20:32,793 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-16 18:20:32,793 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-16 18:20:32,793 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-16 18:20:45,713 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/eval.json
-2021-09-16 18:20:45,713 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-16 18:20:45,714 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-16 18:20:45,714 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-16 18:20:58,798 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/test.json
-2021-09-16 18:20:58,798 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-16 18:20:58,798 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-16 18:57:44,327 - speechbrain.core - INFO - Beginning experiment!
-2021-09-16 18:57:44,327 - speechbrain.core - INFO - Experiment folder: results/tokenizer_seg_bpe5k_char
-2021-09-16 18:57:44,526 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==21.2.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-certifi==2021.5.30
-cffi==1.14.6
-cfgv==3.3.0
-charset-normalizer==2.0.4
-click==8.0.1
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-debugpy==1.3.0
-decorator==5.0.9
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-huggingface-hub==0.0.16
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==3.2
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-joblib==1.0.1
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-kiwisolver==1.3.1
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-mkl-fft==1.3.0
-mkl-random @ file:///tmp/build/80754af9/mkl_random_1626186064646/work
-mkl-service==2.4.0
-more-itertools==8.9.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-olefile @ file:///Users/ktietz/demo/mc3/conda-bld/olefile_1629805411829/work
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pycodestyle==2.5.0
-pycparser==2.20
-pydub @ file:///home/conda/feedstock_root/build_artifacts/pydub_1615612442567/work
-pyflakes==2.1.1
-Pygments==2.9.0
-pyparsing==2.4.7
-pytest==5.4.1
-python-dateutil==2.8.2
-pytube==10.9.3
-PyYAML==5.4.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.26.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scikit-learn @ file:///tmp/build/80754af9/scikit-learn_1621370412049/work
-scipy==1.7.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-six @ file:///tmp/build/80754af9/six_1623709665295/work
--e git+https://github.com/speechbrain/speechbrain.git@2ec4839746970875fc763aa354c44a3356685ef6#egg=speechbrain
-terminado==0.10.1
-testpath==0.5.0
-threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-urllib3==1.26.6
-virtualenv==20.6.0
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xxhash==2.0.2
-yamllint==1.23.0
-
-
-2021-09-16 18:57:44,530 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-09-16 18:57:46,443 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer is already trained.
-2021-09-16 18:57:46,443 - speechbrain.tokenizers.SentencePiece - INFO - ==== Loading Tokenizer ===
-2021-09-16 18:57:46,443 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer path: results/tokenizer_seg_bpe5k_char/5000_char.model
-2021-09-16 18:57:46,443 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer vocab_size: 5000
-2021-09-16 18:57:46,444 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer type: char
-2021-09-16 18:57:46,447 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-16 18:57:59,747 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/dev.json
-2021-09-16 18:57:59,747 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-16 18:57:59,747 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-16 18:57:59,747 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-16 18:58:12,647 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/eval.json
-2021-09-16 18:58:12,647 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-16 18:58:12,647 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-16 18:58:12,647 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-16 18:58:25,444 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/test.json
-2021-09-16 18:58:25,444 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-16 18:58:25,444 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-18 01:09:55,556 - speechbrain.core - INFO - Beginning experiment!
-2021-09-18 01:09:55,576 - speechbrain.core - INFO - Experiment folder: results/tokenizer_seg_bpe5k_char
-2021-09-18 01:09:55,858 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==21.2.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-certifi==2021.5.30
-cffi==1.14.6
-cfgv==3.3.0
-charset-normalizer==2.0.4
-click==8.0.1
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-debugpy==1.3.0
-decorator==5.0.9
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-huggingface-hub==0.0.16
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==3.2
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-joblib==1.0.1
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-kiwisolver==1.3.1
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-mkl-fft==1.3.0
-mkl-random @ file:///tmp/build/80754af9/mkl_random_1626186064646/work
-mkl-service==2.4.0
-more-itertools==8.9.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-olefile @ file:///Users/ktietz/demo/mc3/conda-bld/olefile_1629805411829/work
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pycodestyle==2.5.0
-pycparser==2.20
-pydub @ file:///home/conda/feedstock_root/build_artifacts/pydub_1615612442567/work
-pyflakes==2.1.1
-Pygments==2.9.0
-pyparsing==2.4.7
-pytest==5.4.1
-python-dateutil==2.8.2
-pytube==10.9.3
-PyYAML==5.4.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.26.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scikit-learn @ file:///tmp/build/80754af9/scikit-learn_1621370412049/work
-scipy==1.7.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-six @ file:///tmp/build/80754af9/six_1623709665295/work
--e git+https://github.com/speechbrain/speechbrain.git@2ec4839746970875fc763aa354c44a3356685ef6#egg=speechbrain
-terminado==0.10.1
-testpath==0.5.0
-threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-urllib3==1.26.6
-virtualenv==20.6.0
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xxhash==2.0.2
-yamllint==1.23.0
-
-
-2021-09-18 01:09:55,862 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-09-18 01:09:57,778 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer is already trained.
-2021-09-18 01:09:57,778 - speechbrain.tokenizers.SentencePiece - INFO - ==== Loading Tokenizer ===
-2021-09-18 01:09:57,778 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer path: results/tokenizer_seg_bpe5k_char/5000_char.model
-2021-09-18 01:09:57,778 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer vocab_size: 5000
-2021-09-18 01:09:57,778 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer type: char
-2021-09-18 01:09:57,780 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-18 01:10:15,083 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/dev.json
-2021-09-18 01:10:15,083 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-18 01:10:15,083 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-18 01:10:15,083 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-18 01:10:32,413 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/eval.json
-2021-09-18 01:10:32,413 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-18 01:10:32,413 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-09-18 01:10:32,413 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-09-18 01:10:49,667 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/test.json
-2021-09-18 01:10:49,667 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-09-18 01:10:49,667 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-10-04 03:04:09,349 - speechbrain.core - INFO - Beginning experiment!
-2021-10-04 03:04:09,349 - speechbrain.core - INFO - Experiment folder: results/tokenizer_seg_bpe5k_char
-2021-10-04 03:04:09,986 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-keyring==18.0.1
-kiwisolver==1.3.1
-language-selector==0.1
-launchpadlib==1.10.13
-lazr.restfulclient==0.14.2
-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-nvidia-ml-py3==7.352.0
-oauthlib==3.1.0
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-
-
-2021-10-04 03:04:09,989 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-10-04 03:04:10,195 - speechbrain.core - ERROR - Exception:
-Traceback (most recent call last):
-  File "Tokenizer/train.py", line 21, in <module>
-    run_on_main(
-  File "/home/wayne/speechbrain/speechbrain/utils/distributed.py", line 61, in run_on_main
-    func(*args, **kwargs)
-  File "/mnt/md0/user_wayne/speechbrain/recipes/MATBN/Tokenizer/matbn_prepare.py", line 67, in prepare_matbn
-    segments_info = extract_segments_info(segments_path)
-  File "/mnt/md0/user_wayne/speechbrain/recipes/MATBN/Tokenizer/matbn_prepare.py", line 117, in extract_segments_info
-    with open(segments_path, "r", encoding="utf-8") as segments_file:
-FileNotFoundError: [Errno 2] No such file or directory: '/home/wayne/CORPUS/MATBN_SEG/data/eval/segments'
-2021-10-04 03:04:50,119 - speechbrain.core - INFO - Beginning experiment!
-2021-10-04 03:04:50,119 - speechbrain.core - INFO - Experiment folder: results/tokenizer_seg_bpe5k_char
-2021-10-04 03:04:50,727 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-keyring==18.0.1
-kiwisolver==1.3.1
-language-selector==0.1
-launchpadlib==1.10.13
-lazr.restfulclient==0.14.2
-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-nvidia-ml-py3==7.352.0
-oauthlib==3.1.0
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-
-
-2021-10-04 03:04:50,730 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-10-04 03:04:52,523 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer is already trained.
-2021-10-04 03:04:52,523 - speechbrain.tokenizers.SentencePiece - INFO - ==== Loading Tokenizer ===
-2021-10-04 03:04:52,523 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer path: results/tokenizer_seg_bpe5k_char/5000_char.model
-2021-10-04 03:04:52,523 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer vocab_size: 5000
-2021-10-04 03:04:52,523 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer type: char
-2021-10-04 03:04:52,558 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-10-04 03:05:04,514 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/dev.json
-2021-10-04 03:05:04,514 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-10-04 03:05:04,514 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-10-04 03:05:04,514 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-10-04 03:05:16,440 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/eval.json
-2021-10-04 03:05:16,440 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-10-04 03:05:16,440 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-10-04 03:05:16,440 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-10-04 03:05:28,162 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/test.json
-2021-10-04 03:05:28,162 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-10-04 03:05:28,162 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-10-04 19:38:40,556 - speechbrain.core - INFO - Beginning experiment!
-2021-10-04 19:38:40,556 - speechbrain.core - INFO - Experiment folder: results/tokenizer_seg_bpe5k_char
-2021-10-04 19:38:41,182 - speechbrain.utils.superpowers - DEBUG - appdirs==1.4.4
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==19.3.0
-Automat==0.8.0
-autopep8==1.5.7
-backcall==0.2.0
-backports.entry-points-selectable==1.1.0
-black==19.10b0
-bleach==3.3.1
-blessings==1.7
-blinker==1.4
-bottle==0.12.19
-certifi==2019.11.28
-cffi==1.14.6
-cfgv==3.3.0
-chardet==3.0.4
-Click==7.0
-cloud-init==21.2
-colorama==0.4.3
-command-not-found==0.3
-configobj==5.0.6
-constantly==15.1.0
-cryptography==2.8
-cupshelpers==1.0
-cycler==0.10.0
-d2l==0.16.6
-datasets==1.11.0
-dbus-python==1.2.16
-debugpy==1.3.0
-decorator==5.0.9
-defer==1.0.6
-defusedxml==0.7.1
-dill==0.3.4
-distlib==0.3.2
-distro==1.4.0
-distro-info===0.23ubuntu1
-entrypoints==0.3
-filelock==3.0.12
-flake8==3.7.9
-fsspec==2021.7.0
-gpustat==0.6.0
-gpuview==0.4.0
-httplib2==0.14.0
-huggingface-hub==0.0.16
-hyperlink==19.0.0
-HyperPyYAML==1.0.0
-identify==2.2.11
-idna==2.8
-importlib-metadata==1.5.0
-incremental==16.10.1
-ipykernel==6.0.2
-ipython==7.25.0
-ipython-genutils==0.2.0
-ipywidgets==7.6.3
-jedi==0.18.0
-Jinja2==2.10.1
-joblib==1.0.1
-jsonpatch==1.22
-jsonpointer==2.0
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client==6.1.12
-jupyter-console==6.4.0
-jupyter-core==4.7.1
-jupyterlab-pygments==0.1.2
-jupyterlab-widgets==1.0.0
-keyring==18.0.1
-kiwisolver==1.3.1
-language-selector==0.1
-launchpadlib==1.10.13
-lazr.restfulclient==0.14.2
-lazr.uri==1.0.3
-macaroonbakery==1.3.1
-MarkupSafe==1.1.0
-matplotlib==3.4.2
-matplotlib-inline==0.1.2
-mccabe==0.6.1
-mistune==0.8.4
-more-itertools==4.2.0
-multiprocess==0.70.12.2
-nbclient==0.5.3
-nbconvert==6.1.0
-nbformat==5.1.3
-nest-asyncio==1.5.1
-netifaces==0.10.4
-nodeenv==1.6.0
-notebook==6.4.0
-numpy==1.21.2
-nvidia-ml-py3==7.352.0
-oauthlib==3.1.0
-packaging==21.0
-pandas==1.3.0
-pandocfilters==1.4.3
-parso==0.8.2
-pathspec==0.9.0
-pexpect==4.6.0
-pickleshare==0.7.5
-Pillow==8.3.1
-platformdirs==2.0.2
-pluggy==0.13.1
-pre-commit==2.15.0
-prometheus-client==0.11.0
-prompt-toolkit==3.0.19
-protobuf==3.6.1
-psutil==5.8.0
-ptyprocess==0.7.0
-py==1.10.0
-pyarrow==5.0.0
-pyasn1==0.4.2
-pyasn1-modules==0.2.1
-pycairo==1.16.2
-pycodestyle==2.5.0
-pycparser==2.20
-pycups==1.9.73
-pyflakes==2.1.1
-Pygments==2.9.0
-PyGObject==3.36.0
-PyHamcrest==1.9.0
-PyJWT==1.7.1
-pymacaroons==0.13.0
-PyMySQL==1.0.2
-PyNaCl==1.3.0
-pyOpenSSL==19.0.0
-pyparsing==2.4.7
-pyRFC3339==1.1
-pyrsistent==0.15.5
-pyserial==3.4
-pytest==5.4.1
-python-apt==2.0.0+ubuntu0.20.4.5
-python-dateutil==2.8.2
-python-debian===0.1.36ubuntu1
-pytube==10.9.3
-pytz==2019.3
-PyYAML==5.3.1
-pyzmq==22.1.0
-qtconsole==5.1.1
-QtPy==1.9.0
-regex==2021.7.6
-requests==2.22.0
-requests-unixsocket==0.2.0
-ruamel.yaml==0.17.10
-ruamel.yaml.clib==0.2.6
-scipy==1.7.1
-screen-resolution-extra==0.0.0
-SecretStorage==2.3.1
-Send2Trash==1.7.1
-sentencepiece==0.1.96
-service-identity==18.1.0
-simplejson==3.16.0
-six==1.14.0
-sos==4.1
--e git+https://github.com/speechbrain/speechbrain.git@1d194bfc51ae20b9e38596d220cdf0f4977e69de#egg=speechbrain
-ssh-import-id==5.10
-supervisor==4.1.0
-systemd-python==234
-terminado==0.10.1
-testpath==0.5.0
-toml==0.10.2
-torch==1.8.1
-torchaudio==0.8.1
-torchvision==0.10.0
-tornado==6.1
-tqdm==4.62.2
-traitlets==5.0.5
-Twisted==18.9.0
-typed-ast==1.4.3
-typing-extensions==3.10.0.0
-ubuntu-advantage-tools==27.2
-ufw==0.36
-unattended-upgrades==0.1
-urllib3==1.25.8
-virtualenv==20.6.0
-wadllib==1.3.3
-wcwidth==0.2.5
-webencodings==0.5.1
-widgetsnbextension==3.5.1
-xkit==0.0.0
-xxhash==2.0.2
-yamllint==1.23.0
-zipp==1.0.0
-zope.interface==4.7.1
-
-
-2021-10-04 19:38:41,186 - speechbrain.utils.superpowers - DEBUG - e3e51338
-
-
-2021-10-04 19:38:43,292 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer is already trained.
-2021-10-04 19:38:43,292 - speechbrain.tokenizers.SentencePiece - INFO - ==== Loading Tokenizer ===
-2021-10-04 19:38:43,292 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer path: results/tokenizer_seg_bpe5k_char/5000_char.model
-2021-10-04 19:38:43,292 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer vocab_size: 5000
-2021-10-04 19:38:43,292 - speechbrain.tokenizers.SentencePiece - INFO - Tokenizer type: char
-2021-10-04 19:38:43,294 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-10-04 19:38:54,904 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/dev.json
-2021-10-04 19:38:54,904 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-10-04 19:38:54,904 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-10-04 19:38:54,904 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-10-04 19:39:06,509 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/eval.json
-2021-10-04 19:39:06,510 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-10-04 19:39:06,510 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0
-2021-10-04 19:39:06,510 - speechbrain.tokenizers.SentencePiece - INFO - ==== Accuracy checking for recovering text from tokenizer ===
-2021-10-04 19:39:18,349 - speechbrain.tokenizers.SentencePiece - INFO - recover words from: results/prepare_seg/test.json
-2021-10-04 19:39:18,349 - speechbrain.tokenizers.SentencePiece - INFO - Wrong recover words: 0
-2021-10-04 19:39:18,349 - speechbrain.tokenizers.SentencePiece - WARNING - accuracy recovering words: 1.0

ASR-model/tokenizer_seg_bpe5k_char/train.py

@@ -1,30 +0,0 @@
-import sys
-
-import speechbrain as sb
-from hyperpyyaml import load_hyperpyyaml
-from speechbrain.utils.distributed import run_on_main
-
-if __name__ == "__main__":
-    hparams_file_path, run_opts, overrides = sb.parse_arguments(sys.argv[1:])
-
-    with open(hparams_file_path) as hparams_file:
-        hparams = load_hyperpyyaml(hparams_file, overrides)
-
-    sb.create_experiment_directory(
-        experiment_directory=hparams["output_folder"],
-        hyperparams_to_save=hparams_file_path,
-        overrides=overrides,
-    )
-
-    from matbn_prepare import prepare_matbn
-
-    run_on_main(
-        prepare_matbn,
-        kwargs={
-            "dataset_folder": hparams["dataset_folder"],
-            "save_folder": hparams["prepare_folder"],
-            "keep_unk": hparams["keep_unk"],
-        },
-    )
-
-    hparams["tokenizer"]()