





# 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							(    lowerCAmelCase_=None	)				->						str:
    if subparsers is not None:
        SCREAMING_SNAKE_CASE__											=			subparsers.add_parser('''env'''	)
    else:
        SCREAMING_SNAKE_CASE__											=			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							(    lowerCAmelCase_	)				->						Optional[int]:
    SCREAMING_SNAKE_CASE__											=			torch.__version__
    SCREAMING_SNAKE_CASE__											=			torch.cuda.is_available()
    SCREAMING_SNAKE_CASE__											=			is_xpu_available()
    SCREAMING_SNAKE_CASE__											=			is_npu_available()

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

    SCREAMING_SNAKE_CASE__											=			{
        '''`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 / 1_0_2_4 ** 3:.2f} GB''',
    }
    if pt_cuda_available:
        SCREAMING_SNAKE_CASE__											=			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:'''	)
    SCREAMING_SNAKE_CASE__											=			(
        '''\n'''.join([f'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()]	)
        if isinstance(lowerCAmelCase_ ,							lowerCAmelCase_	)
        else f'''\t{accelerate_config}'''
    )
    print(lowerCAmelCase_	)

    SCREAMING_SNAKE_CASE__											=			accelerate_config

    return info


def 							__snake_case							(    )				->						int:
    SCREAMING_SNAKE_CASE__											=			env_command_parser()
    SCREAMING_SNAKE_CASE__											=			parser.parse_args()
    env_command(lowerCAmelCase_	)
    return 0


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




class   SCREAMING_SNAKE_CASE_			:




       '''simple docstring'''



       def __init__(						self				:				List[Any]							)					->Tuple:
          lowerCamelCase_						:   Optional[Any]		= """"""
          lowerCamelCase_						:   Dict		= """"""
          lowerCamelCase_						:   Optional[Any]		= []



       def 				_lowerCAmelCase							(						self				:				Optional[Any]		,				__a				:				int		,				__a				:				int							)					->int:
          if m == -1:
             return n + 1
          elif n == -1:
             return m + 1
          elif self.dp[m][n] > -1:
             return self.dp[m][n]
          else:
             if self.worda[m] == self.worda[n]:
                lowerCamelCase_						:   Optional[Any]		= self.__min_dist_top_down_dp(m - 1		,				n - 1							)
             else:
                lowerCamelCase_						:   List[Any]		= self.__min_dist_top_down_dp(__a		,				n - 1							)
                lowerCamelCase_						:   Union[str, Any]		= self.__min_dist_top_down_dp(m - 1		,				__a							)
                lowerCamelCase_						:   Any		= self.__min_dist_top_down_dp(m - 1		,				n - 1							)
                lowerCamelCase_						:   Tuple		= 1 + min(__a		,				__a		,				__a							)

             return self.dp[m][n]



       def 				_lowerCAmelCase							(						self				:				Any		,				__a				:				str		,				__a				:				str							)					->int:
          lowerCamelCase_						:   Dict		= worda
          lowerCamelCase_						:   str		= worda
          lowerCamelCase_						:   Union[str, Any]		= [[-1 for _ in range(len(__a							)							)] for _ in range(len(__a							)							)]

          return self.__min_dist_top_down_dp(len(__a							) - 1		,				len(__a							) - 1							)




       def 				_lowerCAmelCase							(						self				:				int		,				__a				:				str		,				__a				:				str							)					->int:
          lowerCamelCase_						:   Tuple		= worda
          lowerCamelCase_						:   Optional[Any]		= worda
          lowerCamelCase_						:   Tuple		= len(__a							)
          lowerCamelCase_						:   Optional[Any]		= len(__a							)
          lowerCamelCase_						:   List[Any]		= [[0 for _ in range(n + 1							)] for _ in range(m + 1							)]

          for i in range(m + 1							):
             for j in range(n + 1							):
                if i == 0:  # first string is empty
                   lowerCamelCase_						:   Optional[Any]		= j
                elif j == 0:  # second string is empty
                   lowerCamelCase_						:   Any		= i
                elif worda[i - 1] == worda[j - 1]:  # last characters are equal
                   lowerCamelCase_						:   Tuple		= self.dp[i - 1][j - 1]
                else:
                   lowerCamelCase_						:   Dict		= self.dp[i][j - 1]
                   lowerCamelCase_						:   Union[str, Any]		= self.dp[i - 1][j]
                   lowerCamelCase_						:   Any		= self.dp[i - 1][j - 1]
                   lowerCamelCase_						:   Optional[int]		= 1 + min(__a		,				__a		,				__a							)
          return self.dp[m][n]


if __name__ == "__main__":
      snake_case__				:	Optional[Any]					       =					EditDistance()

      print('****************** Testing Edit Distance DP Algorithm ******************')
      print()

      snake_case__				:	Union[str, Any]					       =					input('Enter the first string: ').strip()
      snake_case__				:	List[Any]					       =					input('Enter the second string: ').strip()

      print()
      print(F'The minimum edit distance is: {solver.min_dist_top_down(Sa, Sa)}')
      print(F'The minimum edit distance is: {solver.min_dist_bottom_up(Sa, Sa)}')
      print()
      print('*************** End of Testing Edit Distance DP Algorithm ***************')





