vall-e/vall_e/demo.py
2024-12-02 19:10:42 -06:00

430 lines
16 KiB
Python

"""
A helper script to generate a demo page.
Layout as expected:
./data/demo/:
{speaker ID}:
out:
ours.wav (generated)
ms_valle.wav
yourtts.wav
prompt.txt (text to generate)
prompt.wav (reference clip to serve as the prompt)
reference.wav (ground truth utterance)
Will also generate samples from a provided datset, if requested.
"""
import argparse
import base64
import random
import logging
import time
_logger = logging.getLogger(__name__)
from pathlib import Path
from .inference import TTS
from .config import cfg
from .data import create_train_dataloader, create_val_dataloader, get_random_prompt
from .emb.qnt import decode_to_file
from tqdm import tqdm, trange
def encode(path):
if path is None or not path.exists():
return ""
return "data:audio/wav;base64," + base64.b64encode(open(path, "rb").read()).decode('utf-8')
# Would be downright sugoi if I could incorporate this with into __main__
def main():
parser = argparse.ArgumentParser("VALL-E TTS Demo")
parser.add_argument("--yaml", type=Path, default=None)
parser.add_argument("--model", type=Path, default=None)
parser.add_argument("--demo-dir", type=Path, default=None)
parser.add_argument("--skip-existing", action="store_true")
parser.add_argument("--dataset-dir-name", type=str, default="dataset")
parser.add_argument("--dataset-dir-name-prefix", type=str, default=None)
parser.add_argument("--sample-from-dataset", action="store_true")
parser.add_argument("--skip-loading-dataloader", action="store_true")
parser.add_argument("--dataset-samples", type=int, default=0)
parser.add_argument("--audio-path-root", type=str, default=None)
parser.add_argument("--preamble", type=str, default=None)
parser.add_argument("--output-filename", type=str, default="index.html")
parser.add_argument("--language", type=str, default="en")
parser.add_argument("--task", type=str, default="tts")
parser.add_argument("--modality", type=str, default="auto")
parser.add_argument("--out-path", type=Path, default=None)
parser.add_argument("--max-duration", type=int, default=12 * cfg.dataset.frames_per_second)
parser.add_argument("--max-steps", type=int, default=25)
parser.add_argument("--max-levels", type=int, default=7)
parser.add_argument("--ar-temperature", type=float, default=1.0)
parser.add_argument("--nar-temperature", type=float, default=0.0)
parser.add_argument("--min-ar-temperature", type=float, default=-1.0)
parser.add_argument("--min-nar-temperature", type=float, default=-1.0)
parser.add_argument("--input-prompt-length", type=float, default=3.0)
parser.add_argument("--input-prompt-prefix", action="store_true")
parser.add_argument("--prefix-silence", type=float, default=0.0)
parser.add_argument("--cfg-strength", type=float, default=1.0)
parser.add_argument("--cfg-rescale", type=float, default=0.75)
parser.add_argument("--top-p", type=float, default=1.0)
parser.add_argument("--top-k", type=int, default=0)
parser.add_argument("--top-no", type=float, default=0.0)
parser.add_argument("--min-p", type=float, default=0.0)
parser.add_argument("--repetition-penalty", type=float, default=1.0)
parser.add_argument("--repetition-penalty-decay", type=float, default=0.0)
parser.add_argument("--length-penalty", type=float, default=0.0)
parser.add_argument("--beam-width", type=int, default=0)
parser.add_argument("--mirostat-tau", type=float, default=0)
parser.add_argument("--mirostat-eta", type=float, default=0)
parser.add_argument("--dry-multiplier", type=float, default=0)
parser.add_argument("--dry-base", type=float, default=1.75)
parser.add_argument("--dry-allowed-length", type=int, default=2)
parser.add_argument("--entropix-sampling", action="store_true")
parser.add_argument("--layer-skip", action="store_true")
parser.add_argument("--layer-skip-exit-layer", type=int, default=None)
parser.add_argument("--layer-skip-entropy-threshold", type=int, default=0.1)
parser.add_argument("--layer-skip-varentropy-threshold", type=int, default=0.1)
parser.add_argument("--refine-on-stop", action="store_true")
# experimental settings
parser.add_argument("--load-from-artifact", type=Path, default=None)
parser.add_argument("--denoise-start", type=float, default=0.0)
parser.add_argument("--seed", type=int, default=None)
parser.add_argument("--device", type=str, default=None)
parser.add_argument("--amp", action="store_true")
parser.add_argument("--dtype", type=str, default=None)
parser.add_argument("--random-prompts", action="store_true")
parser.add_argument("--lora", action="store_true")
parser.add_argument("--comparison", type=str, default=None)
args = parser.parse_args()
config = None
if args.yaml:
config = args.yaml
elif args.model:
config = args.model
tts = TTS( config=config, lora=args.lora, device=args.device, dtype=args.dtype, amp=args.amp )
if not args.demo_dir:
args.demo_dir = Path("./data/demo/")
if not args.preamble:
args.preamble = "<br>".join([
'Below are some samples from my VALL-E implementation: <a href="https://git.ecker.tech/mrq/vall-e/">https://git.ecker.tech/mrq/vall-e/</a>.',
'Unlike the original VALL-E demo page, I\'m placing emphasis on the input prompt, as the model adheres to it stronger than others.',
])
# comparison kwargs
comparison_kwargs = {
"titles": [],
"suffix": "diff",
"enabled": {},
"disabled": {}
}
if args.lora:
args.comparison = "lora"
# to-do: just make this mappable
if args.comparison == "lora":
comparison_kwargs["suffix"] = "no_lora"
comparison_kwargs["titles"] = ["LoRA", "No LoRA"]
comparison_kwargs["disabled"]["use_lora"] = True
comparison_kwargs["disabled"]["ar_temperature"] = 0.0
comparison_kwargs["enabled"]["use_lora"] = False
comparison_kwargs["enabled"]["ar_temperature"] = 0.95
elif args.comparison == "entropix-sampling":
comparison_kwargs["suffix"] = "entropix_sampling"
comparison_kwargs["titles"] = ["Without Entropix", "With Entropix"]
comparison_kwargs["disabled"]["entropix_sampling"] = False
comparison_kwargs["disabled"]["ar_temperature"] = args.ar_temperature
comparison_kwargs["disabled"]["top_k"] = args.top_k
comparison_kwargs["disabled"]["top_p"] = args.top_p
comparison_kwargs["enabled"]["entropix_sampling"] = True
comparison_kwargs["enabled"]["ar_temperature"] = 0.666
comparison_kwargs["enabled"]["top_k"] = 27
comparison_kwargs["enabled"]["top_p"] = 0.9
elif args.comparison == "layerskip":
comparison_kwargs["suffix"] = "layerskip"
comparison_kwargs["titles"] = [f"Without LayerSkip", "With LayerSkip"]
comparison_kwargs["disabled"]["layer_skip"] = False
comparison_kwargs["enabled"]["layer_skip"] = True
elif args.comparison == "refine-on-stop":
comparison_kwargs["suffix"] = "refine-on-stop"
comparison_kwargs["titles"] = [f"Without Ro<S>", "With Ro<S>"]
comparison_kwargs["disabled"]["refine_on_stop"] = False
comparison_kwargs["enabled"]["refine_on_stop"] = True
elif args.comparison == "ar-temp":
current_temperature = args.ar_temperature
other_temperature = 1.0
comparison_kwargs["suffix"] = "temperature"
comparison_kwargs["titles"] = [f"Temp: {current_temperature:.2f}", f"Temp: {other_temperature:.2f}"]
comparison_kwargs["disabled"]["ar_temperature"] = current_temperature
comparison_kwargs["enabled"]["ar_temperature"] = other_temperature
elif args.comparison == "input-prompt-length":
current_length = args.input_prompt_length
other_length = 3.0
comparison_kwargs["suffix"] = "input_prompt_length"
comparison_kwargs["titles"] = [f"Prompt Length: {current_length:.2f}s", f"Prompt Length: {other_length:.2f}s"]
comparison_kwargs["disabled"]["input_prompt_length"] = current_length
comparison_kwargs["enabled"]["input_prompt_length"] = other_length
elif args.comparison == "dtype":
current_dtype = cfg.inference.weight_dtype
other_dtype = "float32"
if current_dtype == "float16":
other_dtype = "bfloat16"
elif current_dtype == "bfloat16":
other_dtype = "float16"
comparison_kwargs["suffix"] = f"dtype_{other_dtype}"
comparison_kwargs["titles"] = [f"With {current_dtype}", f"With {other_dtype}"]
comparison_kwargs["disabled"]["dtype"] = current_dtype
comparison_kwargs["enabled"]["dtype"] = other_dtype
elif args.comparison == "amp":
current_amp = cfg.inference.weight_amp
other_amp = not current_amp
comparison_kwargs["suffix"] = f"with{'out' if not other_amp else ''}_amp"
comparison_kwargs["titles"] = [f"With {current_amp}", f"With {other_amp}"]
comparison_kwargs["disabled"]["amp"] = current_amp
comparison_kwargs["enabled"]["amp"] = other_amp
elif args.comparison == "modality":
comparison_kwargs["suffix"] = "modality"
comparison_kwargs["titles"] = [f"AR+NAR", f"NAR-len"]
comparison_kwargs["disabled"]["modality"] = "ar+nar"
comparison_kwargs["disabled"]["cfg_strength"] = 0.0
comparison_kwargs["enabled"]["modality"] = "nar-len"
comparison_kwargs["enabled"]["cfg_strength"] = 3.0
elif args.comparison == "cfg-strength":
current_cfg_strength = 3.0
other_cfg_strength = 0.0
comparison_kwargs["suffix"] = f"no_cfg_strength"
comparison_kwargs["titles"] = [f"CFG {current_cfg_strength}", f"CFG {other_cfg_strength}"]
comparison_kwargs["disabled"]["cfg_strength"] = current_cfg_strength
comparison_kwargs["enabled"]["cfg_strength"] = other_cfg_strength
elif args.comparison:
raise Exception(f"Unrecognized comparison flag: {args.comparison}")
# read html template
html = open(args.demo_dir / "index.template.html", "r", encoding="utf-8").read()
sampling_kwargs = dict(
task=args.task,
modality=args.modality,
max_steps=args.max_steps,
max_levels=args.max_levels,
max_duration=args.max_duration,
ar_temperature=args.ar_temperature, nar_temperature=args.nar_temperature,
min_ar_temperature=args.min_ar_temperature, min_nar_temperature=args.min_nar_temperature,
top_p=args.top_p, top_k=args.top_k, top_no=args.top_no,min_p=args.min_p,
repetition_penalty=args.repetition_penalty, repetition_penalty_decay=args.repetition_penalty_decay,
length_penalty=args.length_penalty,
beam_width=args.beam_width,
mirostat_tau=args.mirostat_tau, mirostat_eta=args.mirostat_eta,
dry_multiplier=args.dry_multiplier, dry_base=args.dry_base, dry_allowed_length=args.dry_allowed_length,
entropix_sampling=args.entropix_sampling,
layer_skip=args.layer_skip,
layer_skip_exit_layer=args.layer_skip_exit_layer,
layer_skip_entropy_threshold=args.layer_skip_entropy_threshold,
layer_skip_varentropy_threshold=args.layer_skip_varentropy_threshold,
refine_on_stop=args.refine_on_stop,
denoise_start=args.denoise_start,
input_prompt_length=args.input_prompt_length,
input_prompt_prefix=args.input_prompt_prefix,
prefix_silence=args.prefix_silence,
cfg_strength=args.cfg_strength,
cfg_rescale=args.cfg_rescale,
)
# replace values in our template
html = html.replace(r"${PREAMBLE}", args.preamble )
html = html.replace(r"${SETTINGS}", str(sampling_kwargs))
# pull from provided samples
samples_dirs = {
"librispeech": args.demo_dir / "librispeech",
}
if (args.demo_dir / args.dataset_dir_name).exists():
samples_dirs["dataset"] = args.demo_dir / args.dataset_dir_name
# pull from dataset samples
if args.sample_from_dataset:
cfg.dataset.cache = False
cfg.dataset.sample_type = "path" if len(cfg.dataset.training) < cfg.evaluation.batch_size else "speaker"
cfg.dataset.sample_order = "random"
cfg.dataset.tasks_list = [ 'tts' ]
samples_dirs["dataset"] = args.demo_dir / args.dataset_dir_name
_logger.info("Loading dataloader...")
dataloader = create_train_dataloader()
_logger.info("Loaded dataloader.")
length = min(len( dataloader.dataset ), cfg.evaluation.batch_size)
num = args.dataset_samples if args.dataset_samples else length
for i in trange( num, desc="Sampling dataset for samples" ):
index = i if not cfg.dataset.sample_shuffle else random.randint( 0, len( dataloader.dataset ) )
batch = dataloader.dataset[i]
if args.dataset_dir_name_prefix:
dir = args.demo_dir / args.dataset_dir_name / f'{args.dataset_dir_name_prefix}_{i}'
else:
dir = args.demo_dir / args.dataset_dir_name / f'{i}'
(dir / "out").mkdir(parents=True, exist_ok=True)
metadata = batch["metadata"]
text = get_random_prompt() if args.random_prompts else metadata["text"]
#text = get_random_prompt() if i >= (num // 2) else metadata["text"]
language = metadata["language"].lower()
prompt = dir / "prompt.wav"
reference = dir / "reference.wav"
out_path = dir / "out" / "ours.wav"
if args.skip_existing and out_path.exists():
continue
open( dir / "prompt.txt", "w", encoding="utf-8" ).write( text )
open( dir / "language.txt", "w", encoding="utf-8" ).write( language )
decode_to_file( batch["proms"].to("cuda"), prompt, device="cuda" )
decode_to_file( batch["resps"].to("cuda"), reference, device="cuda" )
for k, sample_dir in samples_dirs.items():
if not sample_dir.exists():
continue
samples = []
speakers = [ dir for dir in sample_dir.iterdir() if dir.is_dir() ]
sources = [ "ms_valle", "f5" ]
# generate demo output
for dir in tqdm(speakers, desc=f"Generating demo for {k}"):
text = open(dir / "prompt.txt", encoding="utf-8").read()
language = open(dir / "language.txt").read() if (dir / "language.txt").exists() else "en"
prompt = dir / "prompt.wav"
reference = dir / "reference.wav"
out_path = dir / "out" / "ours.wav"
out_path_comparison = dir / "out" / f"ours_{comparison_kwargs['suffix']}.wav"
external_sources = [ dir / "out" / f"{source}.wav" for source in sources ]
audio_samples = [ prompt, out_path ]
if args.comparison:
audio_samples += [ out_path_comparison ]
audio_samples += [ p if p.exists() else None for p in external_sources ]
if not args.random_prompts or k == "librispeech":
audio_samples += [ reference ]
samples.append((
text,
audio_samples,
))
seed = args.seed if args.seed else int(time.time())
"""
# manual invocation
cmd = f'python3 -m vall_e --yaml="{args.yaml}" "{reference}" "{text}" --out-path={out_path}'
# F5
cmd = f'python inference-cli.py --model "F5-TTS" --ref_audio "{reference}" --gen_text "{text}" --output_dir "{out_path.parent}"'
"""
kwargs = dict(
text=text,
references=[prompt],
language=language,
seed=seed,
tqdm=False,
**sampling_kwargs,
)
def safe_inference( out_path=out_path ):
if args.skip_existing and out_path.exists():
return
# swap model config swap
"""
if "dtype" in kwargs or "amp" in kwargs:
dtype = kwargs.pop("dtype", args.dtype)
amp = kwargs.pop("amp", args.amp)
del tts
tts = TTS( config=args.yaml, device=args.device, dtype=dtype, amp=amp )
"""
try:
tts.inference( out_path=out_path, **kwargs )
except Exception as e:
raise e
print(f'Error while processing {out_path}: {e}')
if args.comparison:
kwargs.update( comparison_kwargs["enabled"] )
safe_inference(out_path_comparison)
kwargs.update( comparison_kwargs["disabled"] )
safe_inference()
# collate entries into HTML
samples = [
f'\n\t\t\t<tr>\n\t\t\t\t<td>{text}</td>'+
"".join( [
f'\n\t\t\t\t<td><audio controls="controls" preload="none"><source src="{str(audio).replace(str(args.demo_dir), args.audio_path_root) if args.audio_path_root else encode(audio)}"/></audio></td>'
for audio in audios
] )+
'\n\t\t\t</tr>'
for text, audios in samples
]
# write audio into template
html = html.replace("${"+k.upper()+"_SAMPLES}", "\n".join( samples ) )
if args.comparison:
disabled, enabled = comparison_kwargs["titles"]
if args.random_prompts:
html = html.replace("<th>Our VALL-E</th>\n\t\t\t\t\t<th>Ground Truth</th>", f"<th>Our VALL-E ({disabled})</th>\n\t\t\t\t\t<th>Our VALL-E ({enabled})</th>")
else:
html = html.replace("<th>Our VALL-E</th>", f"<th>Our VALL-E ({disabled})</th>\n\t\t\t\t\t<th>Our VALL-E ({enabled})</th>")
# write demo page
open( args.demo_dir / args.output_filename, "w", encoding="utf-8" ).write( html )
if __name__ == "__main__":
main()