




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

 lowerCamelCase    :		Any			   =       True
except ImportError:
 lowerCamelCase    :		Any			   =       False

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

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	Namespace					):


      '''simple docstring'''



      return AddNewModelCommand(args.testing     ,							args.testing_file     ,							path=args.path					)







class   A(						UpperCamelCase       ):



 '''simple docstring'''


 @staticmethod
 def     a__			(    A_ :  ArgumentParser  )       ->     int:

       """simple docstring"""






       lowerCamelCase_							=   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 :  Tuple						,							A_ :  bool						,							A_ :  str						,							A_ :  str=None						,							*A_ :  int  )       ->     Optional[int]:

       """simple docstring"""






       lowerCamelCase_							=   testing
       lowerCamelCase_							=   testing_file
       lowerCamelCase_							=   path





 def     a__			(    self :  Dict  )       ->     Dict:

       """simple docstring"""






       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
       lowerCamelCase_							=   [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.'  )

       lowerCamelCase_							=   (
           Path(A_  ).parent.parent.parent.parent if self._path is None else Path(self._path  ).parent.parent
       )
       lowerCamelCase_							=   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:
                   lowerCamelCase_							=   json.load(A_  )

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

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

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

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

       lowerCamelCase_							=   'PyTorch' in generate_tensorflow_pytorch_and_flax
       lowerCamelCase_							=   'TensorFlow' in generate_tensorflow_pytorch_and_flax
       lowerCamelCase_							=   'Flax' in generate_tensorflow_pytorch_and_flax

       lowerCamelCase_							=   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_ :  Tuple  ):
             with open(A_						,							'r'  ) as f:
                   lowerCamelCase_							=   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_ :  str						,							A_ :  str						,							A_ :  List[str]  ):
             # Create temp file
             lowerCamelCase_					,    lowerCamelCase_							=   mkstemp()
             lowerCamelCase_							=   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:
                                     lowerCamelCase_							=   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_ :  Union[str, Any]  ):
             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_ :  str  ):
             with open(A_  ) as datafile:
                   lowerCamelCase_							=   []
                   lowerCamelCase_							=   False
                   lowerCamelCase_							=   False
                   for line in datafile:
                         if "# To replace in: " in line and "##" not in line:
                               lowerCamelCase_							=   line.split('"'  )[1]
                               lowerCamelCase_							=   skip_units(A_  )
                         elif "# Below: " in line and "##" not in line:
                               lowerCamelCase_							=   line.split('"'  )[1]
                               lowerCamelCase_							=   skip_units(A_  )
                         elif "# End." in line and "##" not in line:
                               if not skip_file and not skip_snippet:
                                     replace(A_						,							A_						,							A_  )

                               lowerCamelCase_							=   []
                         elif "# Replace with" in line and "##" not in line:
                               lowerCamelCase_							=   []
                         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_  )









from __future__ import annotations

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	dict     ,							lowercase     :	str					):


      '''simple docstring'''



      lowerCamelCase_					,    lowerCamelCase_							=   set(lowercase					), [start]

      while stack:
            lowerCamelCase_							=   stack.pop()
            explored.add(lowercase					)
            # Differences from BFS:
            # 1) pop last element instead of first one
            # 2) add adjacent elements to stack without exploring them
            for adj in reversed(graph[v]					):
                  if adj not in explored:
                        stack.append(lowercase					)
      return explored


lowerCamelCase    :		int			   =       {
    "A": ["B", "C", "D"],
    "B": ["A", "D", "E"],
    "C": ["A", "F"],
    "D": ["B", "D"],
    "E": ["B", "F"],
    "F": ["C", "E", "G"],
    "G": ["F"],
}

if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(depth_first_search(G, "A"))



