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PaddleSpeech/deepspeech/training/cli.py

109 lines
3.7 KiB

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
class ExtendAction(argparse.Action):
"""
[Since Python 3.8, the "extend" is available directly in stdlib]
(https://docs.python.org/3.8/library/argparse.html#action).
If you only have to support 3.8+ then defining it yourself is no longer required.
Usage of stdlib "extend" action is exactly the same way as this answer originally described:
"""
def __call__(self, parser, namespace, values, option_string=None):
items = getattr(namespace, self.dest) or []
items.extend(values)
setattr(namespace, self.dest, items)
def default_argument_parser():
r"""A simple yet genral argument parser for experiments with parakeet.
This is used in examples with parakeet. And it is intended to be used by
other experiments with parakeet. It requires a minimal set of command line
arguments to start a training script.
The ``--config`` and ``--opts`` are used for overwrite the deault
configuration.
The ``--data`` and ``--output`` specifies the data path and output path.
Resuming training from existing progress at the output directory is the
intended default behavior.
The ``--checkpoint_path`` specifies the checkpoint to load from.
The ``--nprocs`` specifies how to run the training.
See Also
--------
parakeet.training.experiment
Returns
-------
argparse.ArgumentParser
the parser
"""
parser = argparse.ArgumentParser()
parser.register('action', 'extend', ExtendAction)
train_group = parser.add_argument_group(
title='Train Options', description=None)
train_group.add_argument(
"--seed",
type=int,
default=None,
help="seed to use for paddle, np and random. None or 0 for random, else set seed."
)
train_group.add_argument(
"--nprocs",
type=int,
default=1,
help="number of parallel processes. 0 for cpu.")
train_group.add_argument(
"--config", metavar="CONFIG_FILE", help="config file.")
train_group.add_argument(
"--output", metavar="CKPT_DIR", help="path to save checkpoint.")
train_group.add_argument(
"--checkpoint_path", type=str, help="path to load checkpoint")
train_group.add_argument(
"--opts",
action='extend',
nargs=2,
metavar=('key', 'val'),
help="overwrite --config field, passing (KEY VALUE) pairs")
train_group.add_argument(
"--dump-config", metavar="FILE", help="dump config to `this` file.")
profile_group = parser.add_argument_group(
title='Benchmark Options', description=None)
profile_group.add_argument(
'--profiler-options',
type=str,
default=None,
help='The option of profiler, which should be in format \"key1=value1;key2=value2;key3=value3\".'
)
profile_group.add_argument(
'--benchmark-batch-size',
type=int,
default=None,
help='batch size for benchmark.')
profile_group.add_argument(
'--benchmark-max-step',
type=int,
default=None,
help='max iteration for benchmark.')
return parser