




import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Union[str, Any]				)  ->							Tuple:
    return EnvironmentCommand()




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Any				)  ->							Dict:
    return EnvironmentCommand(args.accelerate_config_file				)



class       a					(       _A      ):

     '''simple docstring'''





     @staticmethod
     def   lowerCamelCase_       (     __snake_case       :      ArgumentParser    ):
         UpperCAmelCase_										=					parser.add_parser('''env'''    )
         download_parser.set_defaults(func=__snake_case    )
         download_parser.add_argument(
             '''--accelerate-config_file''' ,   default=__snake_case ,   help='''The accelerate config file to use for the default values in the launching script.''' ,   )
         download_parser.set_defaults(func=__snake_case    )
     def __init__(     self       :      Dict ,   __snake_case       :      Optional[int] ,   *__snake_case       :      Optional[Any]    ):
         UpperCAmelCase_										=					accelerate_config_file
     def   lowerCamelCase_       (     self       :      Optional[int]    ):
         UpperCAmelCase_										=					'''not installed'''
         if is_safetensors_available():
             import safetensors

             UpperCAmelCase_										=					safetensors.__version__
         elif importlib.util.find_spec('''safetensors'''    ) is not None:
             import safetensors

             UpperCAmelCase_										=					F'{safetensors.__version__} but is ignored because of PyTorch version too old.'

         UpperCAmelCase_										=					'''not installed'''
         UpperCAmelCase_										=					UpperCAmelCase_										=					'''not found'''
         if is_accelerate_available():
             import accelerate
             from accelerate.commands.config import default_config_file, load_config_from_file

             UpperCAmelCase_										=					accelerate.__version__
             # Get the default from the config file.
             if self._accelerate_config_file is not None or os.path.isfile(__snake_case    ):
                 UpperCAmelCase_										=					load_config_from_file(self._accelerate_config_file    ).to_dict()

             UpperCAmelCase_										=					(
                 '''\n'''.join([F'\t- {prop}: {val}' for prop, val in accelerate_config.items()]    )
                 if isinstance(__snake_case ,   __snake_case    )
                 else F'\t{accelerate_config}'
             )

         UpperCAmelCase_										=					'''not installed'''
         UpperCAmelCase_										=					'''NA'''
         if is_torch_available():
             import torch

             UpperCAmelCase_										=					torch.__version__
             UpperCAmelCase_										=					torch.cuda.is_available()

         UpperCAmelCase_										=					'''not installed'''
         UpperCAmelCase_										=					'''NA'''
         if is_tf_available():
             import tensorflow as tf

             UpperCAmelCase_										=					tf.__version__
             try:
                 # deprecated in v2.1
                 UpperCAmelCase_										=					tf.test.is_gpu_available()
             except AttributeError:
                 # returns list of devices, convert to bool
                 UpperCAmelCase_										=					bool(tf.config.list_physical_devices('''GPU'''    )    )

         UpperCAmelCase_										=					'''not installed'''
         UpperCAmelCase_										=					'''not installed'''
         UpperCAmelCase_										=					'''not installed'''
         UpperCAmelCase_										=					'''NA'''
         if is_flax_available():
             import flax
             import jax
             import jaxlib

             UpperCAmelCase_										=					flax.__version__
             UpperCAmelCase_										=					jax.__version__
             UpperCAmelCase_										=					jaxlib.__version__
             UpperCAmelCase_										=					jax.lib.xla_bridge.get_backend().platform

         UpperCAmelCase_										=					{
             '''`transformers` version''': version,
             '''Platform''': platform.platform(),
             '''Python version''': platform.python_version(),
             '''Huggingface_hub version''': huggingface_hub.__version__,
             '''Safetensors version''': F'{safetensors_version}',
             '''Accelerate version''': F'{accelerate_version}',
             '''Accelerate config''': F'{accelerate_config_str}',
             '''PyTorch version (GPU?)''': F'{pt_version} ({pt_cuda_available})',
             '''Tensorflow version (GPU?)''': F'{tf_version} ({tf_cuda_available})',
             '''Flax version (CPU?/GPU?/TPU?)''': F'{flax_version} ({jax_backend})',
             '''Jax version''': F'{jax_version}',
             '''JaxLib version''': F'{jaxlib_version}',
             '''Using GPU in script?''': '''<fill in>''',
             '''Using distributed or parallel set-up in script?''': '''<fill in>''',
         }

         print('''\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'''    )
         print(self.format_dict(__snake_case    )    )

         return info




     @staticmethod
     def   lowerCamelCase_       (     __snake_case       :      Union[str, Any]    ):
         return "\n".join([F'- {prop}: {val}' for prop, val in d.items()]    ) + "\n"











from __future__ import annotations

_lowerCamelCase      			=						list[list[int]]

# assigning initial values to the grid
_lowerCamelCase      			=						[
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
_lowerCamelCase      			=						[
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Matrix	,					__UpperCamelCase      :						int	,					__UpperCamelCase      :						int	,					__UpperCamelCase      :						int				)  ->							bool:
    for i in range(9				):
        if grid[row][i] == n or grid[i][column] == n:
            return False

    for i in range(3				):
        for j in range(3				):
            if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
                return False

    return True




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Matrix				)  ->							tuple[int, int] | None:
    for i in range(9				):
        for j in range(9				):
            if grid[i][j] == 0:
                return i, j
    return None




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Matrix				)  ->							Matrix | None:
    if location := find_empty_location(__UpperCamelCase				):
        UpperCAmelCase_			,							UpperCAmelCase_										=					location
    else:
        # If the location is ``None``, then the grid is solved.
        return grid

    for digit in range(1	,					10				):
        if is_safe(__UpperCamelCase	,					__UpperCamelCase	,					__UpperCamelCase	,					__UpperCamelCase				):
            UpperCAmelCase_										=					digit

            if sudoku(__UpperCamelCase				) is not None:
                return grid

            UpperCAmelCase_										=					0

    return None




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Matrix				)  ->							None:
    for row in grid:
        for cell in row:
            print(__UpperCamelCase	,					end=''' '''				)
        print()


if __name__ == "__main__":
 # make a copy of grid so that you can compare with the unmodified grid
 for example_grid in (initial_grid, no_solution):
  print('\nExample grid:\n' + '=' * 20)
  print_solution(example_grid)
  print('\nExample grid solution:')
  _lowerCamelCase      			=						sudoku(example_grid)
  if solution is not None:
   print_solution(solution)
  else:
   print('Cannot find a solution.')





