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export.py
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import os
import pathlib
import re
import sys
from typing import List
import click
import torch
root_dir = pathlib.Path(__file__).resolve().parent.parent
os.environ['PYTHONPATH'] = str(root_dir)
sys.path.insert(0, str(root_dir))
from utils.hparams import set_hparams, hparams
def check_pytorch_version():
# Require PyTorch version to be exactly 1.13.x
if torch.__version__.startswith('1.13.'):
return
raise RuntimeError('This script requires PyTorch 1.13.x. Please install the correct version.')
def find_exp(exp):
if not (root_dir / 'checkpoints' / exp).exists():
for subdir in (root_dir / 'checkpoints').iterdir():
if not subdir.is_dir():
continue
if subdir.name.startswith(exp):
print(f'| match ckpt by prefix: {subdir.name}')
exp = subdir.name
break
else:
raise click.BadParameter(
f'There are no matching exp starting with \'{exp}\' in \'checkpoints\' folder. '
'Please specify \'--exp\' as the folder name or prefix.'
)
else:
print(f'| found ckpt by name: {exp}')
return exp
def parse_spk_settings(export_spk, freeze_spk):
if export_spk is None:
export_spk = []
else:
export_spk = list(export_spk)
from utils.infer_utils import parse_commandline_spk_mix
spk_name_pattern = r'[0-9A-Za-z_-]+'
export_spk_mix = []
for spk in export_spk:
assert '=' in spk or '|' not in spk, \
'You must specify an alias with \'NAME=\' for each speaker mix.'
if '=' in spk:
alias, mix = spk.split('=', maxsplit=1)
assert re.fullmatch(spk_name_pattern, alias) is not None, f'Invalid alias \'{alias}\' for speaker mix.'
export_spk_mix.append((alias, parse_commandline_spk_mix(mix)))
else:
export_spk_mix.append((spk, {spk: 1.0}))
freeze_spk_mix = None
if freeze_spk is not None:
assert '=' in freeze_spk or '|' not in freeze_spk, \
'You must specify an alias with \'NAME=\' for each speaker mix.'
if '=' in freeze_spk:
alias, mix = freeze_spk.split('=', maxsplit=1)
assert re.fullmatch(spk_name_pattern, alias) is not None, f'Invalid alias \'{alias}\' for speaker mix.'
freeze_spk_mix = (alias, parse_commandline_spk_mix(mix))
else:
freeze_spk_mix = (freeze_spk, {freeze_spk: 1.0})
return export_spk_mix, freeze_spk_mix
@click.group()
def main():
pass
@main.command(help='Export DiffSinger acoustic model to ONNX format.')
@click.option(
'--exp', type=click.STRING,
required=True, metavar='EXP', callback=lambda ctx, param, value: find_exp(value),
help='Choose an experiment to export.'
)
@click.option(
'--ckpt', type=click.IntRange(min=0),
required=False, metavar='STEPS',
help='Checkpoint training steps.'
)
@click.option(
'--out', type=click.Path(
dir_okay=True, file_okay=False,
path_type=pathlib.Path, resolve_path=True
),
required=False,
help='Output directory for the artifacts.'
)
@click.option(
'--freeze_gender', type=click.FloatRange(min=-1, max=1),
help='(for random pitch shifting) Freeze gender value into the model.'
)
@click.option(
'--freeze_velocity', is_flag=True,
help='(for random time stretching) Freeze default velocity value into the model.'
)
@click.option(
'--export_spk', type=click.STRING,
required=False, multiple=True,
help='(for multi-speaker models) Export one or more speaker or speaker mixture keys.'
)
@click.option(
'--freeze_spk', type=click.STRING,
required=False,
help='(for multi-speaker models) Freeze one speaker or speaker mixture into the model.'
)
def acoustic(
exp: str,
ckpt: int = None,
out: pathlib.Path = None,
freeze_gender: float = 0.,
freeze_velocity: bool = False,
export_spk: List[str] = None,
freeze_spk: str = None
):
# Validate arguments
if export_spk and freeze_spk:
print('--export_spk is exclusive to --freeze_spk.')
exit(-1)
if out is None:
out = root_dir / 'artifacts' / exp
export_spk_mix, freeze_spk_mix = parse_spk_settings(export_spk, freeze_spk)
# Load configurations
sys.argv = [
sys.argv[0],
'--exp_name',
exp,
'--infer'
]
set_hparams()
# Export artifacts
from deployment.exporters import DiffSingerAcousticExporter
print(f'| Exporter: {DiffSingerAcousticExporter}')
exporter = DiffSingerAcousticExporter(
device=torch.device('cuda' if torch.cuda.is_available() else 'cpu'),
cache_dir=root_dir / 'deployment' / 'cache',
ckpt_steps=ckpt,
freeze_gender=freeze_gender,
freeze_velocity=freeze_velocity,
export_spk=export_spk_mix,
freeze_spk=freeze_spk_mix
)
try:
exporter.export(out)
except KeyboardInterrupt:
exit(-1)
@main.command(help='Export DiffSinger variance model to ONNX format.')
@click.option(
'--exp', type=click.STRING,
required=True, metavar='EXP', callback=lambda ctx, param, value: find_exp(value),
help='Choose an experiment to export.'
)
@click.option(
'--ckpt', type=click.IntRange(min=0),
required=False, metavar='STEPS',
help='Checkpoint training steps.'
)
@click.option(
'--out', type=click.Path(
dir_okay=True, file_okay=False,
path_type=pathlib.Path, resolve_path=True
),
required=False,
help='Output directory for the artifacts.'
)
@click.option(
'--freeze_glide', is_flag=True,
help='Freeze default glide embedding into the model.'
)
@click.option(
'--freeze_expr', is_flag=True,
help='Freeze default pitch expressiveness factor into the model.'
)
@click.option(
'--export_spk', type=click.STRING,
required=False, multiple=True,
help='(for multi-speaker models) Export one or more speaker or speaker mixture keys.'
)
@click.option(
'--freeze_spk', type=click.STRING,
required=False,
help='(for multi-speaker models) Freeze one speaker or speaker mixture into the model.'
)
def variance(
exp: str,
ckpt: int = None,
out: str = None,
freeze_glide: bool = False,
freeze_expr: bool = False,
export_spk: List[str] = None,
freeze_spk: str = None
):
# Validate arguments
if export_spk and freeze_spk:
print('--export_spk is exclusive to --freeze_spk.')
exit(-1)
if out is None:
out = root_dir / 'artifacts' / exp
export_spk_mix, freeze_spk_mix = parse_spk_settings(export_spk, freeze_spk)
# Load configurations
sys.argv = [
sys.argv[0],
'--exp_name',
exp,
'--infer'
]
set_hparams()
from deployment.exporters import DiffSingerVarianceExporter
print(f'| Exporter: {DiffSingerVarianceExporter}')
exporter = DiffSingerVarianceExporter(
device=torch.device('cuda' if torch.cuda.is_available() else 'cpu'),
cache_dir=root_dir / 'deployment' / 'cache',
ckpt_steps=ckpt,
freeze_glide=freeze_glide,
freeze_expr=freeze_expr,
export_spk=export_spk_mix,
freeze_spk=freeze_spk_mix
)
try:
exporter.export(out)
except KeyboardInterrupt:
exit(-1)
@main.command(help='Export NSF-HiFiGAN vocoder model to ONNX format.')
@click.option(
'--config', type=click.Path(
exists=True, file_okay=True, dir_okay=False, readable=True,
path_type=pathlib.Path, resolve_path=True
),
required=True,
help='Specify a configuration file for the vocoder.'
)
@click.option(
'--ckpt', type=click.Path(
exists=True, file_okay=True, dir_okay=False, readable=True,
path_type=pathlib.Path, resolve_path=True
),
required=False,
help='Specify a model path of the vocoder checkpoint.'
)
@click.option(
'--out', type=click.Path(
dir_okay=True, file_okay=False,
path_type=pathlib.Path, resolve_path=True
),
required=False,
help='Output directory for the artifacts.'
)
@click.option(
'--name', type=click.STRING,
required=False, default='nsf_hifigan', show_default=False,
help='Specify filename (without suffix) of the target model file.'
)
def nsf_hifigan(
config: pathlib.Path,
ckpt: pathlib.Path = None,
out: pathlib.Path = None,
name: str = None
):
# Check arguments
if out is None:
out = root_dir / 'artifacts' / 'nsf_hifigan'
# Load configurations
set_hparams(config.as_posix())
if ckpt is None:
model_path = pathlib.Path(hparams['vocoder_ckpt']).resolve()
else:
model_path = ckpt
# Export artifacts
from deployment.exporters import NSFHiFiGANExporter
print(f'| Exporter: {NSFHiFiGANExporter}')
exporter = NSFHiFiGANExporter(
device=torch.device('cuda' if torch.cuda.is_available() else 'cpu'),
cache_dir=root_dir / 'deployment' / 'cache',
model_path=model_path,
model_name=name
)
try:
exporter.export(out)
except KeyboardInterrupt:
exit(-1)
if __name__ == '__main__':
check_pytorch_version()
main()