


# Copyright 2021 The HuggingFace Team. 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 accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser







def 							lowerCAmelCase_	(   ):
							__snake_case						:     int									=  ArgumentParser("Accelerate CLI tool"				,      usage="accelerate <command> [<args>]"				,      allow_abbrev=__lowerCamelCase      )
							__snake_case						:     Dict									=  parser.add_subparsers(help="accelerate command helpers"      )

							# Register commands
							get_config_parser(subparsers=__lowerCamelCase      )
							env_command_parser(subparsers=__lowerCamelCase      )
							launch_command_parser(subparsers=__lowerCamelCase      )
							tpu_command_parser(subparsers=__lowerCamelCase      )
							test_command_parser(subparsers=__lowerCamelCase      )

							# Let's go
							__snake_case						:     Any									=  parser.parse_args()

							if not hasattr(__lowerCamelCase				,      "func"      ):
														parser.print_help()
														exit(1      )

							# Run
							args.func(__lowerCamelCase      )


if __name__ == "__main__":
			main()






'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A__    :   Optional[Any]           =					{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   Tuple           =					['''SqueezeBertTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   str           =					[
        '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''SqueezeBertForMaskedLM''',
        '''SqueezeBertForMultipleChoice''',
        '''SqueezeBertForQuestionAnswering''',
        '''SqueezeBertForSequenceClassification''',
        '''SqueezeBertForTokenClassification''',
        '''SqueezeBertModel''',
        '''SqueezeBertModule''',
        '''SqueezeBertPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_squeezebert import (
        SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SqueezeBertConfig,
        SqueezeBertOnnxConfig,
    )
    from .tokenization_squeezebert import SqueezeBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_squeezebert import (
            SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            SqueezeBertForMaskedLM,
            SqueezeBertForMultipleChoice,
            SqueezeBertForQuestionAnswering,
            SqueezeBertForSequenceClassification,
            SqueezeBertForTokenClassification,
            SqueezeBertModel,
            SqueezeBertModule,
            SqueezeBertPreTrainedModel,
        )

else:
    import sys

    A__    :   List[Any]           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



