Medix-AI/coqui-tts
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coqui-tts
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fix(bin.synthesize): correctly handle boolean arguments 

Previously, e.g. `--use_cuda false` would actually set use_cuda=True:
https://github.com/coqui-ai/TTS/discussions/3762
This commit is contained in:
Enno Hermann 2024-05-30 11:12:10 +02:00
parent a682fa8d56
commit 77722cb0dd
16 changed files with 57 additions and 80 deletions
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4
TTS/bin/compute_attention_masks.py
View File

@ -35,7 +35,7 @@ Example run:
--data_path /root/LJSpeech-1.1/
--batch_size 32
--dataset ljspeech
--use_cuda True
--use_cuda
""",
formatter_class=RawTextHelpFormatter,
)
@ -62,7 +62,7 @@ Example run:
help="Dataset metafile inclusing file paths with transcripts.",
)
parser.add_argument("--data_path", type=str, default="", help="Defines the data path. It overwrites config.json.")
parser.add_argument("--use_cuda", type=bool, default=False, help="enable/disable cuda.")
parser.add_argument("--use_cuda", action=argparse.BooleanOptionalAction, default=False, help="enable/disable cuda.")
parser.add_argument(
"--batch_size", default=16, type=int, help="Batch size for the model. Use batch_size=1 if you have no CUDA."

2
TTS/bin/compute_embeddings.py
View File

@ -150,7 +150,7 @@ if __name__ == "__main__":
default=False,
action="store_true",
)
parser.add_argument("--disable_cuda", type=bool, help="Flag to disable cuda.", default=False)
parser.add_argument("--disable_cuda", action="store_true", help="Flag to disable cuda.", default=False)
parser.add_argument("--no_eval", help="Do not compute eval?. Default False", default=False, action="store_true")
parser.add_argument(
"--formatter_name",

4
TTS/bin/eval_encoder.py
View File

@ -75,8 +75,8 @@ if __name__ == "__main__":
type=str,
help="Path to dataset config file.",
)
parser.add_argument("--use_cuda", type=bool, help="flag to set cuda.", default=True)
parser.add_argument("--eval", type=bool, help="compute eval.", default=True)
parser.add_argument("--use_cuda", action=argparse.BooleanOptionalAction, help="flag to set cuda.", default=True)
parser.add_argument("--eval", action=argparse.BooleanOptionalAction, help="compute eval.", default=True)
args = parser.parse_args()

2
TTS/bin/extract_tts_spectrograms.py
View File

@ -282,7 +282,7 @@ if __name__ == "__main__":
parser.add_argument("--debug", default=False, action="store_true", help="Save audio files for debug")
parser.add_argument("--save_audio", default=False, action="store_true", help="Save audio files")
parser.add_argument("--quantize_bits", type=int, default=0, help="Save quantized audio files if non-zero")
parser.add_argument("--eval", type=bool, help="compute eval.", default=True)
parser.add_argument("--eval", action=argparse.BooleanOptionalAction, help="compute eval.", default=True)
args = parser.parse_args()
c = load_config(args.config_path)

10
TTS/bin/remove_silence_using_vad.py
View File

@ -80,7 +80,7 @@ if __name__ == "__main__":
setup_logger("TTS", level=logging.INFO, screen=True, formatter=ConsoleFormatter())
parser = argparse.ArgumentParser(
description="python TTS/bin/remove_silence_using_vad.py -i=VCTK-Corpus/ -o=VCTK-Corpus-removed-silence/ -g=wav48_silence_trimmed/*/*_mic1.flac --trim_just_beginning_and_end True"
description="python TTS/bin/remove_silence_using_vad.py -i=VCTK-Corpus/ -o=VCTK-Corpus-removed-silence/ -g=wav48_silence_trimmed/*/*_mic1.flac --trim_just_beginning_and_end"
)
parser.add_argument("-i", "--input_dir", type=str, help="Dataset root dir", required=True)
parser.add_argument("-o", "--output_dir", type=str, help="Output Dataset dir", default="")
@ -95,20 +95,20 @@ if __name__ == "__main__":
parser.add_argument(
"-t",
"--trim_just_beginning_and_end",
type=bool,
action=argparse.BooleanOptionalAction,
default=True,
help="If True this script will trim just the beginning and end nonspeech parts. If False all nonspeech parts will be trim. Default True",
help="If True this script will trim just the beginning and end nonspeech parts. If False all nonspeech parts will be trimmed.",
)
parser.add_argument(
"-c",
"--use_cuda",
type=bool,
action=argparse.BooleanOptionalAction,
default=False,
help="If True use cuda",
)
parser.add_argument(
"--use_onnx",
type=bool,
action=argparse.BooleanOptionalAction,
default=False,
help="If True use onnx",
)

57
TTS/bin/synthesize.py
View File

@ -1,5 +1,6 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Command line interface."""
import argparse
import contextlib
@ -136,19 +137,8 @@ $ tts --out_path output/path/speech.wav --model_name "<language>/<dataset>/<mode
"""
def str2bool(v):
if isinstance(v, bool):
return v
if v.lower() in ("yes", "true", "t", "y", "1"):
return True
if v.lower() in ("no", "false", "f", "n", "0"):
return False
raise argparse.ArgumentTypeError("Boolean value expected.")
def main():
setup_logger("TTS", level=logging.INFO, screen=True, formatter=ConsoleFormatter())
def parse_args() -> argparse.Namespace:
"""Parse arguments."""
parser = argparse.ArgumentParser(
description=description.replace(" ```\n", ""),
formatter_class=RawTextHelpFormatter,
@ -156,10 +146,7 @@ def main():
parser.add_argument(
"--list_models",
type=str2bool,
nargs="?",
const=True,
default=False,
action="store_true",
help="list available pre-trained TTS and vocoder models.",
)
@ -207,7 +194,7 @@ def main():
default="tts_output.wav",
help="Output wav file path.",
)
parser.add_argument("--use_cuda", type=bool, help="Run model on CUDA.", default=False)
parser.add_argument("--use_cuda", action="store_true", help="Run model on CUDA.")
parser.add_argument("--device", type=str, help="Device to run model on.", default="cpu")
parser.add_argument(
"--vocoder_path",
@ -226,10 +213,7 @@ def main():
parser.add_argument(
"--pipe_out",
help="stdout the generated TTS wav file for shell pipe.",
type=str2bool,
nargs="?",
const=True,
default=False,
action="store_true",
)
# args for multi-speaker synthesis
@ -261,25 +245,18 @@ def main():
parser.add_argument(
"--list_speaker_idxs",
help="List available speaker ids for the defined multi-speaker model.",
type=str2bool,
nargs="?",
const=True,
default=False,
action="store_true",
)
parser.add_argument(
"--list_language_idxs",
help="List available language ids for the defined multi-lingual model.",
type=str2bool,
nargs="?",
const=True,
default=False,
action="store_true",
)
# aux args
parser.add_argument(
"--save_spectogram",
type=bool,
help="If true save raw spectogram for further (vocoder) processing in out_path.",
default=False,
action="store_true",
help="Save raw spectogram for further (vocoder) processing in out_path.",
)
parser.add_argument(
"--reference_wav",
@ -295,8 +272,8 @@ def main():
)
parser.add_argument(
"--progress_bar",
type=str2bool,
help="If true shows a progress bar for the model download. Defaults to True",
action=argparse.BooleanOptionalAction,
help="Show a progress bar for the model download.",
default=True,
)
@ -337,19 +314,23 @@ def main():
]
if not any(check_args):
parser.parse_args(["-h"])
return args
def main():
setup_logger("TTS", level=logging.INFO, screen=True, formatter=ConsoleFormatter())
args = parse_args()
pipe_out = sys.stdout if args.pipe_out else None
with contextlib.redirect_stdout(None if args.pipe_out else sys.stdout):
# Late-import to make things load faster
from TTS.api import TTS
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer
# load model manager
path = Path(__file__).parent / "../.models.json"
manager = ModelManager(path, progress_bar=args.progress_bar)
api = TTS()
tts_path = None
tts_config_path = None

2
TTS/encoder/README.md
View File

@ -14,5 +14,5 @@ To run the code, you need to follow the same flow as in TTS.
- Define 'config.json' for your needs. Note that, audio parameters should match your TTS model.
- Example training call ```python speaker_encoder/train.py --config_path speaker_encoder/config.json --data_path ~/Data/Libri-TTS/train-clean-360```
- Generate embedding vectors ```python speaker_encoder/compute_embeddings.py --use_cuda true /model/path/best_model.pth model/config/path/config.json dataset/path/ output_path``` . This code parses all .wav files at the given dataset path and generates the same folder structure under the output path with the generated embedding files.
- Generate embedding vectors ```python speaker_encoder/compute_embeddings.py --use_cuda /model/path/best_model.pth model/config/path/config.json dataset/path/ output_path``` . This code parses all .wav files at the given dataset path and generates the same folder structure under the output path with the generated embedding files.
- Watch training on Tensorboard as in TTS

2
TTS/server/README.md
View File

@ -15,7 +15,7 @@ Run the server with the official models.
```python TTS/server/server.py --model_name tts_models/en/ljspeech/tacotron2-DCA --vocoder_name vocoder_models/en/ljspeech/multiband-melgan```
Run the server with the official models on a GPU.
```CUDA_VISIBLE_DEVICES="0" python TTS/server/server.py --model_name tts_models/en/ljspeech/tacotron2-DCA --vocoder_name vocoder_models/en/ljspeech/multiband-melgan --use_cuda True```
```CUDA_VISIBLE_DEVICES="0" python TTS/server/server.py --model_name tts_models/en/ljspeech/tacotron2-DCA --vocoder_name vocoder_models/en/ljspeech/multiband-melgan --use_cuda```
Run the server with a custom models.
```python TTS/server/server.py --tts_checkpoint /path/to/tts/model.pth --tts_config /path/to/tts/config.json --vocoder_checkpoint /path/to/vocoder/model.pth --vocoder_config /path/to/vocoder/config.json```

4
docs/source/docker_images.md
View File

@ -32,7 +32,7 @@ For the GPU version, you need to have the latest NVIDIA drivers installed.
With `nvidia-smi` you can check the CUDA version supported, it must be >= 11.8
```bash
docker run --rm --gpus all -v ~/tts-output:/root/tts-output ghcr.io/coqui-ai/tts --text "Hello." --out_path /root/tts-output/hello.wav --use_cuda true
docker run --rm --gpus all -v ~/tts-output:/root/tts-output ghcr.io/coqui-ai/tts --text "Hello." --out_path /root/tts-output/hello.wav --use_cuda
```
## Start a server
@ -50,7 +50,7 @@ python3 TTS/server/server.py --model_name tts_models/en/vctk/vits
```bash
docker run --rm -it -p 5002:5002 --gpus all --entrypoint /bin/bash ghcr.io/coqui-ai/tts
python3 TTS/server/server.py --list_models #To get the list of available models
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits --use_cuda true
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits --use_cuda
```
Click [there](http://[::1]:5002/) and have fun with the server!

6
docs/source/models/bark.md
View File

@ -69,14 +69,12 @@ tts --model_name tts_models/multilingual/multi-dataset/bark \
--text "This is an example." \
--out_path "output.wav" \
--voice_dir bark_voices/ \
--speaker_idx "ljspeech" \
--progress_bar True
--speaker_idx "ljspeech"
# Random voice generation
tts --model_name tts_models/multilingual/multi-dataset/bark \
--text "This is an example." \
--out_path "output.wav" \
--progress_bar True
--out_path "output.wav"
```

6
docs/source/models/tortoise.md
View File

@ -57,14 +57,12 @@ tts --model_name tts_models/en/multi-dataset/tortoise-v2 \
--text "This is an example." \
--out_path "output.wav" \
--voice_dir path/to/tortoise/voices/dir/ \
--speaker_idx "lj" \
--progress_bar True
--speaker_idx "lj"
# Random voice generation
tts --model_name tts_models/en/multi-dataset/tortoise-v2 \
--text "This is an example." \
--out_path "output.wav" \
--progress_bar True
--out_path "output.wav"
```

8
docs/source/models/xtts.md
View File

@ -72,7 +72,7 @@ You can do inference using one of the available speakers using the following com
--text "It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent." \
--speaker_idx "Ana Florence" \
--language_idx en \
--use_cuda true
--use_cuda
```
##### Clone a voice
@ -85,7 +85,7 @@ You can clone a speaker voice using a single or multiple references:
--text "Bugün okula gitmek istemiyorum." \
--speaker_wav /path/to/target/speaker.wav \
--language_idx tr \
--use_cuda true
--use_cuda
```
###### Multiple references
@ -94,7 +94,7 @@ You can clone a speaker voice using a single or multiple references:
--text "Bugün okula gitmek istemiyorum." \
--speaker_wav /path/to/target/speaker.wav /path/to/target/speaker_2.wav /path/to/target/speaker_3.wav \
--language_idx tr \
--use_cuda true
--use_cuda
```
or for all wav files in a directory you can use:
@ -103,7 +103,7 @@ or for all wav files in a directory you can use:
--text "Bugün okula gitmek istemiyorum." \
--speaker_wav /path/to/target/*.wav \
--language_idx tr \
--use_cuda true
--use_cuda
```
#### 🐸TTS API

2
recipes/ljspeech/fast_pitch/train_fast_pitch.py
View File

@ -65,7 +65,7 @@ if not config.model_args.use_aligner:
model_path, config_path, _ = manager.download_model("tts_models/en/ljspeech/tacotron2-DCA")
# TODO: make compute_attention python callable
os.system(
f"python TTS/bin/compute_attention_masks.py --model_path {model_path} --config_path {config_path} --dataset ljspeech --dataset_metafile metadata.csv --data_path ./recipes/ljspeech/LJSpeech-1.1/ --use_cuda true"
f"python TTS/bin/compute_attention_masks.py --model_path {model_path} --config_path {config_path} --dataset ljspeech --dataset_metafile metadata.csv --data_path ./recipes/ljspeech/LJSpeech-1.1/ --use_cuda"
)
# INITIALIZE THE AUDIO PROCESSOR

2
recipes/ljspeech/fast_speech/train_fast_speech.py
View File

@ -64,7 +64,7 @@ if not config.model_args.use_aligner:
model_path, config_path, _ = manager.download_model("tts_models/en/ljspeech/tacotron2-DCA")
# TODO: make compute_attention python callable
os.system(
f"python TTS/bin/compute_attention_masks.py --model_path {model_path} --config_path {config_path} --dataset ljspeech --dataset_metafile metadata.csv --data_path ./recipes/ljspeech/LJSpeech-1.1/ --use_cuda true"
f"python TTS/bin/compute_attention_masks.py --model_path {model_path} --config_path {config_path} --dataset ljspeech --dataset_metafile metadata.csv --data_path ./recipes/ljspeech/LJSpeech-1.1/ --use_cuda"
)
# INITIALIZE THE AUDIO PROCESSOR

2
recipes/ljspeech/fastspeech2/train_fastspeech2.py
View File

@ -67,7 +67,7 @@ if not config.model_args.use_aligner:
model_path, config_path, _ = manager.download_model("tts_models/en/ljspeech/tacotron2-DCA")
# TODO: make compute_attention python callable
os.system(
f"python TTS/bin/compute_attention_masks.py --model_path {model_path} --config_path {config_path} --dataset ljspeech --dataset_metafile metadata.csv --data_path ./recipes/ljspeech/LJSpeech-1.1/ --use_cuda true"
f"python TTS/bin/compute_attention_masks.py --model_path {model_path} --config_path {config_path} --dataset ljspeech --dataset_metafile metadata.csv --data_path ./recipes/ljspeech/LJSpeech-1.1/ --use_cuda"
)
# INITIALIZE THE AUDIO PROCESSOR

24
tests/zoo_tests/test_models.py
View File

@ -50,13 +50,13 @@ def run_models(offset=0, step=1):
speaker_id = list(speaker_manager.name_to_id.keys())[0]
run_cli(
f"tts --model_name {model_name} "
f'--text "This is an example." --out_path "{output_path}" --speaker_idx "{speaker_id}" --language_idx "{language_id}" --progress_bar False'
f'--text "This is an example." --out_path "{output_path}" --speaker_idx "{speaker_id}" --language_idx "{language_id}" --no-progress_bar'
)
else:
# single-speaker model
run_cli(
f"tts --model_name {model_name} "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False'
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar'
)
# remove downloaded models
shutil.rmtree(local_download_dir)
@ -66,7 +66,7 @@ def run_models(offset=0, step=1):
reference_wav = os.path.join(get_tests_data_path(), "ljspeech", "wavs", "LJ001-0032.wav")
run_cli(
f"tts --model_name {model_name} "
f'--out_path "{output_path}" --source_wav "{speaker_wav}" --target_wav "{reference_wav}" --progress_bar False'
f'--out_path "{output_path}" --source_wav "{speaker_wav}" --target_wav "{reference_wav}" --no-progress_bar'
)
else:
# only download the model
@ -83,14 +83,14 @@ def test_xtts():
run_cli(
"yes | "
f"tts --model_name tts_models/multilingual/multi-dataset/xtts_v1.1 "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False --use_cuda True '
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar --use_cuda '
f'--speaker_wav "{speaker_wav}" --language_idx "en"'
)
else:
run_cli(
"yes | "
f"tts --model_name tts_models/multilingual/multi-dataset/xtts_v1.1 "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False '
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar '
f'--speaker_wav "{speaker_wav}" --language_idx "en"'
)
@ -138,14 +138,14 @@ def test_xtts_v2():
run_cli(
"yes | "
f"tts --model_name tts_models/multilingual/multi-dataset/xtts_v2 "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False --use_cuda True '
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar --use_cuda '
f'--speaker_wav "{speaker_wav}" "{speaker_wav_2}" --language_idx "en"'
)
else:
run_cli(
"yes | "
f"tts --model_name tts_models/multilingual/multi-dataset/xtts_v2 "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False '
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar '
f'--speaker_wav "{speaker_wav}" "{speaker_wav_2}" --language_idx "en"'
)
@ -215,12 +215,12 @@ def test_tortoise():
if use_gpu:
run_cli(
f" tts --model_name tts_models/en/multi-dataset/tortoise-v2 "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False --use_cuda True'
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar --use_cuda'
)
else:
run_cli(
f" tts --model_name tts_models/en/multi-dataset/tortoise-v2 "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False'
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar'
)
@ -231,12 +231,12 @@ def test_bark():
if use_gpu:
run_cli(
f" tts --model_name tts_models/multilingual/multi-dataset/bark "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False --use_cuda True'
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar --use_cuda'
)
else:
run_cli(
f" tts --model_name tts_models/multilingual/multi-dataset/bark "
f'--text "This is an example." --out_path "{output_path}" --progress_bar False'
f'--text "This is an example." --out_path "{output_path}" --no-progress_bar'
)
@ -249,7 +249,7 @@ def test_voice_conversion():
output_path = os.path.join(get_tests_output_path(), "output.wav")
run_cli(
f"tts --model_name {model_name}"
f" --out_path {output_path} --speaker_wav {speaker_wav} --reference_wav {reference_wav} --language_idx {language_id} --progress_bar False"
f" --out_path {output_path} --speaker_wav {speaker_wav} --reference_wav {reference_wav} --language_idx {language_id} --no-progress_bar"
)