

"""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     (    UpperCAmelCase_  :					Union[str, Any]=None			):
     if subparsers is not None:
          A__										=  subparsers.add_parser("""env"""			)
     else:
          A__										=  argparse.ArgumentParser("""Accelerate env command"""			)

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

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





def  _snake_case     (    UpperCAmelCase_  :					Any			):
     A__										=  torch.__version__
     A__										=  torch.cuda.is_available()
     A__										=  is_xpu_available()
     A__										=  is_npu_available()

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

     A__										=  {
         """`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(UpperCAmelCase_			),
         """PyTorch NPU available""": str(UpperCAmelCase_			),
         """System RAM""": F"""{psutil.virtual_memory().total / 1024 ** 3:.2f} GB""",
     }
     if pt_cuda_available:
          A__										=  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:"""			)
     A__										=  (
         """\n""".join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]			)
         if isinstance(UpperCAmelCase_					,   UpperCAmelCase_			)
         else F"""\t{accelerate_config}"""
     )
     print(UpperCAmelCase_			)

     A__										=  accelerate_config

     return info





def  _snake_case     (    ):
     A__										=  env_command_parser()
     A__										=  parser.parse_args()
     env_command(UpperCAmelCase_			)
     return 0


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









"""simple docstring"""



import warnings

from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor


SCREAMING_SNAKE_CASE_					:	List[Any]							  =						logging.get_logger(__name__)



class 					a						(       _lowerCamelCase				):



    """simple docstring"""



    def __init__(     self: Tuple    ,						*UpperCamelCase: Optional[int]    ,						**UpperCamelCase: Tuple       ):






         """simple docstring"""


         warnings.warn(
             """The class VideoMAEFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
             """ Please use VideoMAEImageProcessor instead."""    ,						UpperCamelCase    ,						)
         super().__init__(*UpperCamelCase    ,						**UpperCamelCase       )






