


"""simple docstring"""


# Copyright 2022 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.

import argparse
import os
import platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available



def 	snake_case    (					_a:  Dict=None				)->		List[Any]:
      '''simple docstring'''


      if subparsers is not None:
            lowerCamelCase__							     =		subparsers.add_parser('env'				)
      else:
            lowerCamelCase__							     =		argparse.ArgumentParser('Accelerate env command'				)

      parser.add_argument(
          '--config_file'		, default=lowerCAmelCase_		, help='The config file to use for the default values in the launching script.'				)

      if subparsers is not None:
            parser.set_defaults(func=lowerCAmelCase_				)
      return parser



def 	snake_case    (					_a:  Optional[Any]				)->		Union[str, Any]:
      '''simple docstring'''


      lowerCamelCase__							     =		torch.__version__
      lowerCamelCase__							     =		torch.cuda.is_available()
      lowerCamelCase__							     =		is_xpu_available()
      lowerCamelCase__							     =		is_npu_available()

      lowerCamelCase__							     =		'Not found'
      # Get the default from the config file.
      if args.config_file is not None or os.path.isfile(lowerCAmelCase_				):
            lowerCamelCase__							     =		load_config_from_file(args.config_file				).to_dict()

      lowerCamelCase__							     =		{
          '`Accelerate` version': version,
          'Platform': platform.platform(),
          'Python version': platform.python_version(),
          'Numpy version': np.__version__,
          'PyTorch version (GPU?)': F'{pt_version} ({pt_cuda_available})',
          'PyTorch XPU available': str(lowerCAmelCase_				),
          'PyTorch NPU available': str(lowerCAmelCase_				),
          'System RAM': F'{psutil.virtual_memory().total / 1024 ** 3:.2f} GB',
      }
      if pt_cuda_available:
            lowerCamelCase__							     =		torch.cuda.get_device_name()

      print('\nCopy-and-paste the text below in your GitHub issue\n'				)
      print('\n'.join([F'- {prop}: {val}' for prop, val in info.items()]				)				)

      print('- `Accelerate` default config:' if args.config_file is None else '- `Accelerate` config passed:'				)
      lowerCamelCase__							     =		(
          '\n'.join([F'\t- {prop}: {val}' for prop, val in accelerate_config.items()]				)
          if isinstance(lowerCAmelCase_		, lowerCAmelCase_				)
          else F'\t{accelerate_config}'
      )
      print(lowerCAmelCase_				)

      lowerCamelCase__							     =		accelerate_config

      return info



def 	snake_case    (					)->		int:
      '''simple docstring'''


      lowerCamelCase__							     =		env_command_parser()
      lowerCamelCase__							     =		parser.parse_args()
      env_command(lowerCAmelCase_				)
      return 0


if __name__ == "__main__":
   raise SystemExit(main())







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE						:str			=  {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:List[str]			=  [
       '''UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''UniSpeechForCTC''',
       '''UniSpeechForPreTraining''',
       '''UniSpeechForSequenceClassification''',
       '''UniSpeechModel''',
       '''UniSpeechPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_unispeech import (
          UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
          UniSpeechForCTC,
          UniSpeechForPreTraining,
          UniSpeechForSequenceClassification,
          UniSpeechModel,
          UniSpeechPreTrainedModel,
      )

else:
   import sys

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




