





'''simple docstring'''

import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
      from cookiecutter.main import cookiecutter

      lowercase_					= True
except ImportError:
      lowercase_					= False

lowercase_					= logging.get_logger(__name__)  # pylint: disable=invalid-name





def lowerCamelCase						(     __lowerCamelCase :    Namespace    )						->Optional[Any]:
    return AddNewModelCommand(args.testing					,       args.testing_file					,       path=args.path    )






class 					a_     (				snake_case_       ):

    '''simple docstring'''


    @staticmethod
    def 			snake_case_(		A       )		->   Tuple:
        _SCREAMING_SNAKE_CASE									=			parser.add_parser("""add-new-model"""       )
        add_new_model_parser.add_argument("""--testing""" ,		action="""store_true""" ,		help="""If in testing mode."""       )
        add_new_model_parser.add_argument("""--testing_file""" ,		type=A ,		help="""Configuration file on which to run."""       )
        add_new_model_parser.add_argument(
            """--path""" ,		type=A ,		help="""Path to cookiecutter. Should only be used for testing purposes."""       )
        add_new_model_parser.set_defaults(func=A       )


    def __init__(		self ,		A ,		A ,		A=None ,		*A       )		->   Union[str, Any]:
        _SCREAMING_SNAKE_CASE									=			testing
        _SCREAMING_SNAKE_CASE									=			testing_file
        _SCREAMING_SNAKE_CASE									=			path





    def 			snake_case_(		self       )		->   List[str]:
        warnings.warn(
            """The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. """
            """It is not actively maintained anymore, so might give a result that won't pass all tests and quality """
            """checks, you should use `transformers-cli add-new-model-like` instead."""       )
        if not _has_cookiecutter:
            raise ImportError(
                """Model creation dependencies are required to use the `add_new_model` command. Install them by running """
                """the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n"""       )
        # Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
        _SCREAMING_SNAKE_CASE									=			[directory for directory in os.listdir() if """cookiecutter-template-""" == directory[:22]]
        if len(A       ) > 0:
            raise ValueError(
                """Several directories starting with `cookiecutter-template-` in current working directory. """
                """Please clean your directory by removing all folders starting with `cookiecutter-template-` or """
                """change your working directory."""       )

        _SCREAMING_SNAKE_CASE									=			(
            Path(A       ).parent.parent.parent.parent if self._path is None else Path(self._path       ).parent.parent
        )
        _SCREAMING_SNAKE_CASE									=			path_to_transformer_root / """templates""" / """adding_a_new_model"""

        # Execute cookiecutter
        if not self._testing:
            cookiecutter(str(A       )       )
        else:
            with open(self._testing_file ,		"""r"""       ) as configuration_file:
                _SCREAMING_SNAKE_CASE									=			json.load(A       )

            cookiecutter(
                str(path_to_cookiecutter if self._path is None else self._path       ) ,		no_input=A ,		extra_context=A ,		)

        _SCREAMING_SNAKE_CASE									=			[directory for directory in os.listdir() if """cookiecutter-template-""" in directory[:22]][0]

        # Retrieve configuration
        with open(directory + """/configuration.json""" ,		"""r"""       ) as configuration_file:
            _SCREAMING_SNAKE_CASE									=			json.load(A       )

        _SCREAMING_SNAKE_CASE									=			configuration["""lowercase_modelname"""]
        _SCREAMING_SNAKE_CASE									=			configuration["""generate_tensorflow_pytorch_and_flax"""]
        os.remove(f'{directory}/configuration.json'       )

        _SCREAMING_SNAKE_CASE									=			"""PyTorch""" in generate_tensorflow_pytorch_and_flax
        _SCREAMING_SNAKE_CASE									=			"""TensorFlow""" in generate_tensorflow_pytorch_and_flax
        _SCREAMING_SNAKE_CASE									=			"""Flax""" in generate_tensorflow_pytorch_and_flax

        _SCREAMING_SNAKE_CASE									=			f'{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'
        os.makedirs(A ,		exist_ok=A       )
        os.makedirs(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}' ,		exist_ok=A       )

        # Tests require submodules as they have parent imports
        with open(f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py' ,		"""w"""       ):
            pass

        shutil.move(
            f'{directory}/__init__.py' ,		f'{model_dir}/__init__.py' ,		)
        shutil.move(
            f'{directory}/configuration_{lowercase_model_name}.py' ,		f'{model_dir}/configuration_{lowercase_model_name}.py' ,		)

        def remove_copy_lines(A       ):
            with open(A ,		"""r"""       ) as f:
                _SCREAMING_SNAKE_CASE									=			f.readlines()
            with open(A ,		"""w"""       ) as f:
                for line in lines:
                    if "# Copied from transformers." not in line:
                        f.write(A       )

        if output_pytorch:
            if not self._testing:
                remove_copy_lines(f'{directory}/modeling_{lowercase_model_name}.py'       )

            shutil.move(
                f'{directory}/modeling_{lowercase_model_name}.py' ,		f'{model_dir}/modeling_{lowercase_model_name}.py' ,		)

            shutil.move(
                f'{directory}/test_modeling_{lowercase_model_name}.py' ,		f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py' ,		)
        else:
            os.remove(f'{directory}/modeling_{lowercase_model_name}.py'       )
            os.remove(f'{directory}/test_modeling_{lowercase_model_name}.py'       )

        if output_tensorflow:
            if not self._testing:
                remove_copy_lines(f'{directory}/modeling_tf_{lowercase_model_name}.py'       )

            shutil.move(
                f'{directory}/modeling_tf_{lowercase_model_name}.py' ,		f'{model_dir}/modeling_tf_{lowercase_model_name}.py' ,		)

            shutil.move(
                f'{directory}/test_modeling_tf_{lowercase_model_name}.py' ,		f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py' ,		)
        else:
            os.remove(f'{directory}/modeling_tf_{lowercase_model_name}.py'       )
            os.remove(f'{directory}/test_modeling_tf_{lowercase_model_name}.py'       )

        if output_flax:
            if not self._testing:
                remove_copy_lines(f'{directory}/modeling_flax_{lowercase_model_name}.py'       )

            shutil.move(
                f'{directory}/modeling_flax_{lowercase_model_name}.py' ,		f'{model_dir}/modeling_flax_{lowercase_model_name}.py' ,		)

            shutil.move(
                f'{directory}/test_modeling_flax_{lowercase_model_name}.py' ,		f'{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py' ,		)
        else:
            os.remove(f'{directory}/modeling_flax_{lowercase_model_name}.py'       )
            os.remove(f'{directory}/test_modeling_flax_{lowercase_model_name}.py'       )

        shutil.move(
            f'{directory}/{lowercase_model_name}.md' ,		f'{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md' ,		)

        shutil.move(
            f'{directory}/tokenization_{lowercase_model_name}.py' ,		f'{model_dir}/tokenization_{lowercase_model_name}.py' ,		)

        shutil.move(
            f'{directory}/tokenization_fast_{lowercase_model_name}.py' ,		f'{model_dir}/tokenization_{lowercase_model_name}_fast.py' ,		)

        from os import fdopen, remove
        from shutil import copymode, move
        from tempfile import mkstemp

        def replace(A ,		A ,		A       ):
            # Create temp file
            _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE									=			mkstemp()
            _SCREAMING_SNAKE_CASE									=			False
            with fdopen(A ,		"""w"""       ) as new_file:
                with open(A       ) as old_file:
                    for line in old_file:
                        new_file.write(A       )
                        if line_to_copy_below in line:
                            _SCREAMING_SNAKE_CASE									=			True
                            for line_to_copy in lines_to_copy:
                                new_file.write(A       )

            if not line_found:
                raise ValueError(f'Line {line_to_copy_below} was not found in file.'       )

            # Copy the file permissions from the old file to the new file
            copymode(A ,		A       )
            # Remove original file
            remove(A       )
            # Move new file
            move(A ,		A       )

        def skip_units(A       ):
            return (
                ("generating PyTorch" in line and not output_pytorch)
                or ("generating TensorFlow" in line and not output_tensorflow)
                or ("generating Flax" in line and not output_flax)
            )

        def replace_in_files(A       ):
            with open(A       ) as datafile:
                _SCREAMING_SNAKE_CASE									=			[]
                _SCREAMING_SNAKE_CASE									=			False
                _SCREAMING_SNAKE_CASE									=			False
                for line in datafile:
                    if "# To replace in: " in line and "##" not in line:
                        _SCREAMING_SNAKE_CASE									=			line.split("""\""""       )[1]
                        _SCREAMING_SNAKE_CASE									=			skip_units(A       )
                    elif "# Below: " in line and "##" not in line:
                        _SCREAMING_SNAKE_CASE									=			line.split("""\""""       )[1]
                        _SCREAMING_SNAKE_CASE									=			skip_units(A       )
                    elif "# End." in line and "##" not in line:
                        if not skip_file and not skip_snippet:
                            replace(A ,		A ,		A       )

                        _SCREAMING_SNAKE_CASE									=			[]
                    elif "# Replace with" in line and "##" not in line:
                        _SCREAMING_SNAKE_CASE									=			[]
                    elif "##" not in line:
                        lines_to_copy.append(A       )

            remove(A       )

        replace_in_files(f'{directory}/to_replace_{lowercase_model_name}.py'       )
        os.rmdir(A       )









lowerCamelCase				:		Tuple     =   [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       Optional[Any]	,							lowercase	:       int	,							lowercase	:       Optional[Any]	,							lowercase	:       List[Any]     ):


      '''simple docstring'''



      lowerCamelCase_		     =    [False] * len(lowercase     )
      lowerCamelCase_		     =    [s]
      lowerCamelCase_		     =    True

      while queue:
            lowerCamelCase_		     =    queue.pop(0     )
            for ind in range(len(graph[u]     )     ):
                  if visited[ind] is False and graph[u][ind] > 0:
                        queue.append(lowercase     )
                        lowerCamelCase_		     =    True
                        lowerCamelCase_		     =    u

      return visited[t]

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       List[str]	,							lowercase	:       Tuple	,							lowercase	:       Tuple     ):


      '''simple docstring'''



      lowerCamelCase_		     =    [-1] * (len(lowercase     ))
      lowerCamelCase_		     =    0
      lowerCamelCase_		     =    []
      lowerCamelCase_		     =    [i[:] for i in graph]  # Record original cut, copy.
      while bfs(lowercase	,							lowercase	,							lowercase	,							lowercase     ):
            lowerCamelCase_		     =    float('Inf'     )
            lowerCamelCase_		     =    sink

            while s != source:
                  # Find the minimum value in select path
                  lowerCamelCase_		     =    min(lowercase	,							graph[parent[s]][s]     )
                  lowerCamelCase_		     =    parent[s]

            max_flow += path_flow
            lowerCamelCase_		     =    sink

            while v != source:
                  lowerCamelCase_		     =    parent[v]
                  graph[u][v] -= path_flow
                  graph[v][u] += path_flow
                  lowerCamelCase_		     =    parent[v]

      for i in range(len(lowercase     )     ):
            for j in range(len(graph[0]     )     ):
                  if graph[i][j] == 0 and temp[i][j] > 0:
                        res.append((i, j)     )

      return res


if __name__ == "__main__":
 print(mincut(test_graph, source=0, sink=5))



