




'''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 							_UpperCAmelCase  (UpperCamelCase_ : Any=None       ):
				'''simple docstring'''
				if subparsers is not None:
								_lowerCAmelCase    :    Tuple										=      subparsers.add_parser("""env"""       )
				else:
								_lowerCAmelCase    :    int										=      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 							_UpperCAmelCase  (UpperCamelCase_ : Optional[int]       ):
				'''simple docstring'''
				_lowerCAmelCase    :    Tuple										=      torch.__version__
				_lowerCAmelCase    :    List[str]										=      torch.cuda.is_available()
				_lowerCAmelCase    :    str										=      is_xpu_available()
				_lowerCAmelCase    :    Optional[Any]										=      is_npu_available()

				_lowerCAmelCase    :    Optional[int]										=      """Not found"""
				# Get the default from the config file.
				if args.config_file is not None or os.path.isfile(UpperCamelCase_       ):
								_lowerCAmelCase    :    Dict										=      load_config_from_file(args.config_file       ).to_dict()

				_lowerCAmelCase    :    Optional[Any]										=      {
				    """`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:
								_lowerCAmelCase    :    Optional[Any]										=      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    :    List[str]										=      (
				    """\n""".join([F"\t- {prop}: {val}" for prop, val in accelerate_config.items()]       )
				    if isinstance(UpperCamelCase_      ,    UpperCamelCase_       )
				    else F"\t{accelerate_config}"
				)
				print(UpperCamelCase_       )

				_lowerCAmelCase    :    Tuple										=      accelerate_config

				return info




def 							_UpperCAmelCase  ():
				'''simple docstring'''
				_lowerCAmelCase    :    List[Any]										=      env_command_parser()
				_lowerCAmelCase    :    List[Any]										=      parser.parse_args()
				env_command(UpperCamelCase_       )
				return 0


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







import sys

_lowerCamelCase      :  Optional[Any]      						=						(
    "73167176531330624919225119674426574742355349194934"
    "96983520312774506326239578318016984801869478851843"
    "85861560789112949495459501737958331952853208805511"
    "12540698747158523863050715693290963295227443043557"
    "66896648950445244523161731856403098711121722383113"
    "62229893423380308135336276614282806444486645238749"
    "30358907296290491560440772390713810515859307960866"
    "70172427121883998797908792274921901699720888093776"
    "65727333001053367881220235421809751254540594752243"
    "52584907711670556013604839586446706324415722155397"
    "53697817977846174064955149290862569321978468622482"
    "83972241375657056057490261407972968652414535100474"
    "82166370484403199890008895243450658541227588666881"
    "16427171479924442928230863465674813919123162824586"
    "17866458359124566529476545682848912883142607690042"
    "24219022671055626321111109370544217506941658960408"
    "07198403850962455444362981230987879927244284909188"
    "84580156166097919133875499200524063689912560717606"
    "05886116467109405077541002256983155200055935729725"
    "71636269561882670428252483600823257530420752963450"
)




def 							_UpperCAmelCase  (UpperCamelCase_ : str = N       ):
				'''simple docstring'''
				_lowerCAmelCase    :    List[str]										=      -sys.maxsize - 1
				for i in range(len(UpperCamelCase_       ) - 12       ):
								_lowerCAmelCase    :    List[str]										=      1
								for j in range(13       ):
												product *= int(n[i + j]       )
								if product > largest_product:
												_lowerCAmelCase    :    Any										=      product
				return largest_product


if __name__ == "__main__":
	print(F'''{solution() = }''')

