chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,294 @@
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import os
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import pathlib
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import re
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import sys
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from typing import List
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import click
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import torch
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root_dir = pathlib.Path(__file__).resolve().parent.parent
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os.environ['PYTHONPATH'] = str(root_dir)
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sys.path.insert(0, str(root_dir))
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from utils.hparams import set_hparams, hparams
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def find_exp(exp):
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if not (root_dir / 'checkpoints' / exp).exists():
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for subdir in (root_dir / 'checkpoints').iterdir():
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if not subdir.is_dir():
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continue
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if subdir.name.startswith(exp):
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print(f'| match ckpt by prefix: {subdir.name}')
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exp = subdir.name
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break
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else:
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raise click.BadParameter(
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f'There are no matching exp starting with \'{exp}\' in \'checkpoints\' folder. '
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'Please specify \'--exp\' as the folder name or prefix.'
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)
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else:
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print(f'| found ckpt by name: {exp}')
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return exp
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def parse_spk_settings(export_spk, freeze_spk):
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if export_spk is None:
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export_spk = []
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else:
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export_spk = list(export_spk)
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from utils.infer_utils import parse_commandline_spk_mix
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spk_name_pattern = r'[0-9A-Za-z_-]+'
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export_spk_mix = []
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for spk in export_spk:
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assert '=' in spk or '|' not in spk, \
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'You must specify an alias with \'NAME=\' for each speaker mix.'
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if '=' in spk:
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alias, mix = spk.split('=', maxsplit=1)
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assert re.fullmatch(spk_name_pattern, alias) is not None, f'Invalid alias \'{alias}\' for speaker mix.'
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export_spk_mix.append((alias, parse_commandline_spk_mix(mix)))
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else:
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export_spk_mix.append((spk, {spk: 1.0}))
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freeze_spk_mix = None
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if freeze_spk is not None:
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assert '=' in freeze_spk or '|' not in freeze_spk, \
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'You must specify an alias with \'NAME=\' for each speaker mix.'
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if '=' in freeze_spk:
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alias, mix = freeze_spk.split('=', maxsplit=1)
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assert re.fullmatch(spk_name_pattern, alias) is not None, f'Invalid alias \'{alias}\' for speaker mix.'
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freeze_spk_mix = (alias, parse_commandline_spk_mix(mix))
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else:
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freeze_spk_mix = (freeze_spk, {freeze_spk: 1.0})
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return export_spk_mix, freeze_spk_mix
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@click.group()
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def main():
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pass
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@main.command(help='Export DiffSinger acoustic model to ONNX format.')
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@click.option(
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'--exp', type=click.STRING,
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required=True, metavar='EXP', callback=lambda ctx, param, value: find_exp(value),
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help='Choose an experiment to export.'
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)
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@click.option(
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'--ckpt', type=click.IntRange(min=0),
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required=False, metavar='STEPS',
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help='Checkpoint training steps.'
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)
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@click.option(
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'--out', type=click.Path(
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dir_okay=True, file_okay=False,
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path_type=pathlib.Path, resolve_path=True
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),
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required=False,
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help='Output directory for the artifacts.'
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)
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@click.option(
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'--freeze_gender', type=click.FloatRange(min=-1, max=1),
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help='(for random pitch shifting) Freeze gender value into the model.'
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)
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@click.option(
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'--freeze_velocity', is_flag=True,
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help='(for random time stretching) Freeze default velocity value into the model.'
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)
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@click.option(
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'--export_spk', type=click.STRING,
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required=False, multiple=True,
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help='(for multi-speaker models) Export one or more speaker or speaker mixture keys.'
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)
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@click.option(
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'--freeze_spk', type=click.STRING,
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required=False,
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help='(for multi-speaker models) Freeze one speaker or speaker mixture into the model.'
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)
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def acoustic(
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exp: str,
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ckpt: int = None,
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out: pathlib.Path = None,
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freeze_gender: float = 0.,
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freeze_velocity: bool = False,
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export_spk: List[str] = None,
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freeze_spk: str = None
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):
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# Validate arguments
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if export_spk and freeze_spk:
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print('--export_spk is exclusive to --freeze_spk.')
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exit(-1)
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if out is None:
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out = root_dir / 'artifacts' / exp
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export_spk_mix, freeze_spk_mix = parse_spk_settings(export_spk, freeze_spk)
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# Load configurations
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sys.argv = [
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sys.argv[0],
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'--exp_name',
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exp,
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'--infer'
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]
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set_hparams()
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# Export artifacts
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from deployment.exporters import DiffSingerAcousticExporter
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print(f'| Exporter: {DiffSingerAcousticExporter}')
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exporter = DiffSingerAcousticExporter(
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device=torch.device('cuda' if torch.cuda.is_available() else 'cpu'),
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cache_dir=root_dir / 'deployment' / 'cache',
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ckpt_steps=ckpt,
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freeze_gender=freeze_gender,
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freeze_velocity=freeze_velocity,
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export_spk=export_spk_mix,
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freeze_spk=freeze_spk_mix
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)
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try:
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exporter.export(out)
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except KeyboardInterrupt:
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exit(-1)
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@main.command(help='Export DiffSinger variance model to ONNX format.')
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@click.option(
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'--exp', type=click.STRING,
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required=True, metavar='EXP', callback=lambda ctx, param, value: find_exp(value),
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help='Choose an experiment to export.'
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)
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@click.option(
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'--ckpt', type=click.IntRange(min=0),
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required=False, metavar='STEPS',
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help='Checkpoint training steps.'
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)
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@click.option(
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'--out', type=click.Path(
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dir_okay=True, file_okay=False,
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path_type=pathlib.Path, resolve_path=True
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),
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required=False,
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help='Output directory for the artifacts.'
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)
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@click.option(
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'--freeze_glide', is_flag=True,
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help='Freeze default glide embedding into the model.'
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)
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@click.option(
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'--freeze_expr', is_flag=True,
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help='Freeze default pitch expressiveness factor into the model.'
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)
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@click.option(
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'--export_spk', type=click.STRING,
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required=False, multiple=True,
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help='(for multi-speaker models) Export one or more speaker or speaker mixture keys.'
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)
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@click.option(
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'--freeze_spk', type=click.STRING,
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required=False,
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help='(for multi-speaker models) Freeze one speaker or speaker mixture into the model.'
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)
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def variance(
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exp: str,
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ckpt: int = None,
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out: str = None,
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freeze_glide: bool = False,
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freeze_expr: bool = False,
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export_spk: List[str] = None,
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freeze_spk: str = None
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):
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# Validate arguments
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if export_spk and freeze_spk:
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print('--export_spk is exclusive to --freeze_spk.')
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exit(-1)
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if out is None:
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out = root_dir / 'artifacts' / exp
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export_spk_mix, freeze_spk_mix = parse_spk_settings(export_spk, freeze_spk)
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# Load configurations
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sys.argv = [
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sys.argv[0],
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'--exp_name',
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exp,
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'--infer'
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]
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set_hparams()
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from deployment.exporters import DiffSingerVarianceExporter
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print(f'| Exporter: {DiffSingerVarianceExporter}')
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exporter = DiffSingerVarianceExporter(
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device=torch.device('cuda' if torch.cuda.is_available() else 'cpu'),
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cache_dir=root_dir / 'deployment' / 'cache',
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ckpt_steps=ckpt,
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freeze_glide=freeze_glide,
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freeze_expr=freeze_expr,
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export_spk=export_spk_mix,
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freeze_spk=freeze_spk_mix
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)
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try:
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exporter.export(out)
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except KeyboardInterrupt:
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exit(-1)
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@main.command(help='Export NSF-HiFiGAN vocoder model to ONNX format.')
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@click.option(
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'--config', type=click.Path(
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exists=True, file_okay=True, dir_okay=False, readable=True,
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path_type=pathlib.Path, resolve_path=True
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),
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required=True,
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help='Specify a configuration file for the vocoder.'
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)
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@click.option(
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'--ckpt', type=click.Path(
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exists=True, file_okay=True, dir_okay=False, readable=True,
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path_type=pathlib.Path, resolve_path=True
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),
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required=False,
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help='Specify a model path of the vocoder checkpoint.'
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)
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@click.option(
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'--out', type=click.Path(
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dir_okay=True, file_okay=False,
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path_type=pathlib.Path, resolve_path=True
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),
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required=False,
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help='Output directory for the artifacts.'
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)
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@click.option(
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'--name', type=click.STRING,
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required=False, default='nsf_hifigan', show_default=False,
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help='Specify filename (without suffix) of the target model file.'
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)
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def nsf_hifigan(
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config: pathlib.Path,
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ckpt: pathlib.Path = None,
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out: pathlib.Path = None,
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name: str = None
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):
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# Check arguments
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if out is None:
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out = root_dir / 'artifacts' / 'nsf_hifigan'
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# Load configurations
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set_hparams(config.as_posix())
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if ckpt is None:
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model_path = pathlib.Path(hparams['vocoder_ckpt']).resolve()
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else:
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model_path = ckpt
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# Export artifacts
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from deployment.exporters import NSFHiFiGANExporter
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print(f'| Exporter: {NSFHiFiGANExporter}')
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exporter = NSFHiFiGANExporter(
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device=torch.device('cuda' if torch.cuda.is_available() else 'cpu'),
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cache_dir=root_dir / 'deployment' / 'cache',
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model_path=model_path,
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model_name=name
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)
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try:
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exporter.export(out)
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except KeyboardInterrupt:
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exit(-1)
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if __name__ == '__main__':
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main()
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