


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

 SCREAMING_SNAKE_CASE__					:     List[str]       =     True
except ImportError:
 SCREAMING_SNAKE_CASE__					:     Optional[Any]       =     False

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




def    a__    (		snake_case__					:							Namespace     ):
  return AddNewModelCommand(args.testing						,   args.testing_file						,   path=args.path     )





class 		_SCREAMING_SNAKE_CASE     (						A     ):


     @staticmethod
     def        __snake_case(  A_    ):
       _UpperCAmelCase		:							int							=     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_    ):
       _UpperCAmelCase		:							Optional[Any]							=     testing
       _UpperCAmelCase		:							str							=     testing_file
       _UpperCAmelCase		:							str							=     path




     def        __snake_case(  self    ):
       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
       _UpperCAmelCase		:							List[Any]							=     [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."""    )

       _UpperCAmelCase		:							Tuple							=     (
           Path(A_    ).parent.parent.parent.parent if self._path is None else Path(self._path    ).parent.parent
       )
       _UpperCAmelCase		:							Optional[Any]							=     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:
           _UpperCAmelCase		:							Optional[int]							=     json.load(A_    )

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

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

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

       _UpperCAmelCase		:							Any							=     configuration["""lowercase_modelname"""]
       _UpperCAmelCase		:							Tuple							=     configuration["""generate_tensorflow_pytorch_and_flax"""]
       os.remove(F'''{directory}/configuration.json'''    )

       _UpperCAmelCase		:							Dict							=     """PyTorch""" in generate_tensorflow_pytorch_and_flax
       _UpperCAmelCase		:							Dict							=     """TensorFlow""" in generate_tensorflow_pytorch_and_flax
       _UpperCAmelCase		:							List[str]							=     """Flax""" in generate_tensorflow_pytorch_and_flax

       _UpperCAmelCase		:							List[str]							=     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:
           _UpperCAmelCase		:							Dict							=     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
         _UpperCAmelCase,_UpperCAmelCase		:							Optional[int]							=     mkstemp()
         _UpperCAmelCase		:							Any							=     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:
                 _UpperCAmelCase		:							Union[str, Any]							=     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:
           _UpperCAmelCase		:							List[Any]							=     []
           _UpperCAmelCase		:							str							=     False
           _UpperCAmelCase		:							Any							=     False
           for line in datafile:
             if "# To replace in: " in line and "##" not in line:
               _UpperCAmelCase		:							List[Any]							=     line.split("""\""""    )[1]
               _UpperCAmelCase		:							Dict							=     skip_units(A_    )
             elif "# Below: " in line and "##" not in line:
               _UpperCAmelCase		:							Any							=     line.split("""\""""    )[1]
               _UpperCAmelCase		:							int							=     skip_units(A_    )
             elif "# End." in line and "##" not in line:
               if not skip_file and not skip_snippet:
                 replace(A_							,					A_							,					A_    )

               _UpperCAmelCase		:							Optional[int]							=     []
             elif "# Replace with" in line and "##" not in line:
               _UpperCAmelCase		:							Dict							=     []
             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_    )









def    a__    (		snake_case__					:							Tuple     ):  # noqa: E741
  _UpperCAmelCase		:							Dict							=     len(snake_case__     )
  _UpperCAmelCase		:							Tuple							=     0
  _UpperCAmelCase		:							Union[str, Any]							=     [0] * n
  _UpperCAmelCase		:							Union[str, Any]							=     [False] * n
  _UpperCAmelCase		:							Tuple							=     [False] * n

  def dfs(snake_case__					:							List[str]						,   snake_case__					:							int						,   snake_case__					:							str						,   snake_case__					:							int     ):
    if parent == root:
      out_edge_count += 1
    _UpperCAmelCase		:							List[Any]							=     True
    _UpperCAmelCase		:							List[str]							=     at

    for to in l[at]:
      if to == parent:
        pass
      elif not visited[to]:
        _UpperCAmelCase		:							Optional[Any]							=     dfs(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__     )
        _UpperCAmelCase		:							Optional[Any]							=     min(low[at]						,   low[to]     )

        # AP found via bridge
        if at < low[to]:
          _UpperCAmelCase		:							List[str]							=     True
        # AP found via cycle
        if at == low[to]:
          _UpperCAmelCase		:							Optional[Any]							=     True
      else:
        _UpperCAmelCase		:							str							=     min(low[at]						,   snake_case__     )
    return out_edge_count

  for i in range(snake_case__     ):
    if not visited[i]:
      _UpperCAmelCase		:							List[Any]							=     0
      _UpperCAmelCase		:							List[str]							=     dfs(snake_case__						,   snake_case__						,   -1						,   snake_case__     )
      _UpperCAmelCase		:							Optional[Any]							=     out_edge_count > 1

  for x in range(len(snake_case__     )     ):
    if is_art[x] is True:
      print(snake_case__     )


# Adjacency list of graph
SCREAMING_SNAKE_CASE__					:     Optional[Any]       =     {
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}





compute_ap(data)





