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