File size: 5,605 Bytes
7934b29 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 |
# Copyright (c) 2020, NVIDIA CORPORATION. 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.
from argparse import ArgumentParser
from typing import Any, Dict, List, Optional, Union
def add_optimizer_args(
parent_parser: ArgumentParser,
optimizer: str = 'adam',
default_lr: float = None,
default_opt_args: Optional[Union[Dict[str, Any], List[str]]] = None,
) -> ArgumentParser:
"""Extends existing argparse with support for optimizers.
# Example of adding optimizer args to command line :
python train_script.py ... --optimizer "novograd" --lr 0.01 \
--opt_args betas=0.95,0.5 weight_decay=0.001
Args:
parent_parser (ArgumentParser): Custom CLI parser that will be extended.
optimizer (str): Default optimizer required.
default_lr (float): Default learning rate that should be overriden during training.
default_opt_args (list(str)): List of overriding arguments for the instantiated optimizer.
Returns:
ArgumentParser: Parser extended by Optimizers arguments.
"""
if default_opt_args is None:
default_opt_args = []
parser = ArgumentParser(parents=[parent_parser], add_help=True, conflict_handler='resolve')
parser.add_argument('--optimizer', type=str, default=optimizer, help='Name of the optimizer. Defaults to Adam.')
parser.add_argument('--lr', type=float, default=default_lr, help='Learning rate of the optimizer.')
parser.add_argument(
'--opt_args',
default=default_opt_args,
nargs='+',
type=str,
help='Overriding arguments for the optimizer. \n Must follow the pattern : \n name=value separated by spaces.'
'Example: --opt_args weight_decay=0.001 eps=1e-8 betas=0.9,0.999',
)
return parser
def add_scheduler_args(parent_parser: ArgumentParser) -> ArgumentParser:
"""Extends existing argparse with default LR scheduler args.
Args:
parent_parser (ArgumentParser): Custom CLI parser that will be extended.
Returns:
ArgumentParser: Parser extended by LR Scheduler arguments.
"""
parser = ArgumentParser(parents=[parent_parser], add_help=False, conflict_handler='resolve')
parser.add_argument("--warmup_steps", type=int, required=False, default=None, help="Number of warmup steps")
parser.add_argument(
"--warmup_ratio",
type=float,
required=False,
default=None,
help="Number of warmup steps as a percentage of total training steps",
)
parser.add_argument("--hold_steps", type=int, required=False, default=None, help="Number of hold LR steps")
parser.add_argument(
"--hold_ratio",
type=float,
required=False,
default=None,
help="Number of hold LR steps as a percentage of total training steps",
)
parser.add_argument("--min_lr", type=float, required=False, default=0.0, help="Minimum learning rate")
parser.add_argument(
"--last_epoch", type=int, required=False, default=-1, help="Last epoch id. -1 indicates training from scratch"
)
return parser
def add_asr_args(parent_parser: ArgumentParser) -> ArgumentParser:
"""Extends existing argparse with default ASR collection args.
Args:
parent_parser (ArgumentParser): Custom CLI parser that will be extended.
Returns:
ArgumentParser: Parser extended by NeMo ASR Collection arguments.
"""
parser = ArgumentParser(parents=[parent_parser], add_help=False, conflict_handler='resolve')
parser.add_argument("--asr_model", type=str, required=True, default="bad_quartznet15x5.yaml", help="")
parser.add_argument("--train_dataset", type=str, required=True, default=None, help="training dataset path")
parser.add_argument("--eval_dataset", type=str, required=True, help="evaluation dataset path")
return parser
def add_nlp_args(parent_parser: ArgumentParser) -> ArgumentParser:
"""Extends existing argparse with default NLP collection args.
Args:
parent_parser (ArgumentParser): Custom CLI parser that will be extended.
Returns:
ArgumentParser: Parser extended by NeMo NLP Collection arguments.
"""
parser = ArgumentParser(parents=[parent_parser], add_help=False, conflict_handler='resolve')
parser.add_argument(
"--data_dir", type=str, required=False, help="data directory to training or/and evaluation dataset"
)
parser.add_argument(
"--config_file", type=str, required=False, default=None, help="Huggingface model configuration file"
)
parser.add_argument(
"--pretrained_model_name", default='bert-base-uncased', type=str, required=False, help="pretrained model name"
)
parser.add_argument(
"--tokenizer_name", default='nemobert', type=str, choices=['sentencepiece', 'nemobert'], help="Tokenizer type"
)
parser.add_argument("--tokenizer_model", default=None, type=str, help="Tokenizer file for sentence piece")
parser.add_argument("--do_lower_case", action='store_true', required=False, help="lower case data")
return parser
|