Medix-AI/coqui-tts
Medix-AI
/
coqui-tts
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

update tts training tests to use the trainer

This commit is contained in:
Eren Gölge 2021-05-27 10:26:31 +02:00
parent bb355b7441
commit 7dff6be871
5 changed files with 17 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
tests/tts_tests/test_align_tts_train.py
View File

@ -30,12 +30,13 @@ config.save_json(config_path)
# train the model for one epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_align_tts.py --config_path {config_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
f"--coqpit.output_path {output_path} "
"--coqpit.datasets.0.name ljspeech "
"--coqpit.datasets.0.meta_file_train metadata.csv "
"--coqpit.datasets.0.meta_file_val metadata.csv "
"--coqpit.datasets.0.path tests/data/ljspeech "
"--coqpit.test_delay_epochs -1"
)
run_cli(command_train)
@ -44,7 +45,7 @@ continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getm
# restore the model and continue training for one more epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_align_tts.py --continue_path {continue_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
)
run_cli(command_train)
shutil.rmtree(continue_path)

7
tests/tts_tests/test_glow_tts_train.py
View File

@ -31,13 +31,14 @@ config.save_json(config_path)
# train the model for one epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_glow_tts.py --config_path {config_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
f"--coqpit.output_path {output_path} "
"--coqpit.datasets.0.name ljspeech "
"--coqpit.datasets.0.meta_file_train metadata.csv "
"--coqpit.datasets.0.meta_file_val metadata.csv "
"--coqpit.datasets.0.path tests/data/ljspeech "
"--coqpit.datasets.0.meta_file_attn_mask tests/data/ljspeech/metadata_attn_mask.txt"
"--coqpit.datasets.0.meta_file_attn_mask tests/data/ljspeech/metadata_attn_mask.txt "
"--coqpit.test_delay_epochs 0"
)
run_cli(command_train)
@ -46,7 +47,7 @@ continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getm
# restore the model and continue training for one more epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_glow_tts.py --continue_path {continue_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
)
run_cli(command_train)
shutil.rmtree(continue_path)

7
tests/tts_tests/test_speedy_speech_train.py
View File

@ -30,13 +30,14 @@ config.save_json(config_path)
# train the model for one epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_speedy_speech.py --config_path {config_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
f"--coqpit.output_path {output_path} "
"--coqpit.datasets.0.name ljspeech "
"--coqpit.datasets.0.meta_file_train metadata.csv "
"--coqpit.datasets.0.meta_file_val metadata.csv "
"--coqpit.datasets.0.path tests/data/ljspeech "
"--coqpit.datasets.0.meta_file_attn_mask tests/data/ljspeech/metadata_attn_mask.txt"
"--coqpit.datasets.0.meta_file_attn_mask tests/data/ljspeech/metadata_attn_mask.txt "
"--coqpit.test_delay_epochs 0"
)
run_cli(command_train)
@ -45,7 +46,7 @@ continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getm
# restore the model and continue training for one more epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_speedy_speech.py --continue_path {continue_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
)
run_cli(command_train)
shutil.rmtree(continue_path)

5
tests/tts_tests/test_tacotron2_train.py
View File

@ -31,12 +31,13 @@ config.save_json(config_path)
# train the model for one epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tacotron.py --config_path {config_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
f"--coqpit.output_path {output_path} "
"--coqpit.datasets.0.name ljspeech "
"--coqpit.datasets.0.meta_file_train metadata.csv "
"--coqpit.datasets.0.meta_file_val metadata.csv "
"--coqpit.datasets.0.path tests/data/ljspeech "
"--coqpit.test_delay_epochs 0 "
)
run_cli(command_train)
@ -45,7 +46,7 @@ continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getm
# restore the model and continue training for one more epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tacotron.py --continue_path {continue_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
)
run_cli(command_train)
shutil.rmtree(continue_path)

5
tests/tts_tests/test_tacotron_train.py
View File

@ -30,12 +30,13 @@ config.save_json(config_path)
# train the model for one epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tacotron.py --config_path {config_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
f"--coqpit.output_path {output_path} "
"--coqpit.datasets.0.name ljspeech "
"--coqpit.datasets.0.meta_file_train metadata.csv "
"--coqpit.datasets.0.meta_file_val metadata.csv "
"--coqpit.datasets.0.path tests/data/ljspeech "
"--coqpit.test_delay_epochs 0"
)
run_cli(command_train)
@ -44,7 +45,7 @@ continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getm
# restore the model and continue training for one more epoch
command_train = (
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tacotron.py --continue_path {continue_path} "
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
)
run_cli(command_train)
shutil.rmtree(continue_path)