# 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) class LoadFromFile(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): with values as f: # parse arguments in the file and store them in the target namespace parser.parse_args(f.read().split(), namespace) def default_argument_parser(parser=None): 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 """ if parser is None: parser = argparse.ArgumentParser() parser.register('action', 'extend', ExtendAction) parser.add_argument( '--conf', type=open, action=LoadFromFile, help="config file.") 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