
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

							UpperCAmelCase__					:	Optional[int]							       =					True
except ImportError:
							UpperCAmelCase__					:	List[Any]							       =					False

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



def    _lowercase       (   __SCREAMING_SNAKE_CASE			)						->  str:
			return AddNewModelCommand(args.testing					,     args.testing_file					,     path=args.path			)



class       UpperCamelCase_      (    snake_case_ ):




							'''simple docstring'''

							@staticmethod
							def 							lowerCAmelCase__			(					UpperCamelCase)			->						List[str]:
										UpperCamelCase__     :		Dict	 =					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=__lowercase  ,    help='Configuration file on which to run.')
										add_new_model_parser.add_argument(
										    '--path'  ,    type=__lowercase  ,    help='Path to cookiecutter. Should only be used for testing purposes.')
										add_new_model_parser.set_defaults(func=__lowercase)
							def __init__(					self  ,    UpperCamelCase  ,    UpperCamelCase  ,    UpperCamelCase=None  ,    *UpperCamelCase)			->						Union[str, Any]:
										UpperCamelCase__     :		Dict	 =					testing
										UpperCamelCase__     :		Any	 =					testing_file
										UpperCamelCase__     :		Optional[Any]	 =					path






							def 							lowerCAmelCase__			(					self)			->						Optional[int]:
										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__     :		Any	 =					[directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:22]]
										if len(__lowercase) > 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__     :		Dict	 =					(
										    Path(__lowercase).parent.parent.parent.parent if self._path is None else Path(self._path).parent.parent
										)
										UpperCamelCase__     :		Optional[int]	 =					path_to_transformer_root / 'templates' / 'adding_a_new_model'

										# Execute cookiecutter
										if not self._testing:
													cookiecutter(str(__lowercase))
										else:
													with open(self._testing_file  ,    'r') as configuration_file:
																UpperCamelCase__     :		int	 =					json.load(__lowercase)

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

										UpperCamelCase__     :		List[str]	 =					[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__     :		int	 =					json.load(__lowercase)

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

										UpperCamelCase__     :		str	 =					'PyTorch' in generate_tensorflow_pytorch_and_flax
										UpperCamelCase__     :		Union[str, Any]	 =					'TensorFlow' in generate_tensorflow_pytorch_and_flax
										UpperCamelCase__     :		Dict	 =					'Flax' in generate_tensorflow_pytorch_and_flax

										UpperCamelCase__     :		Optional[Any]	 =					F"""{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}"""
										os.makedirs(__lowercase  ,    exist_ok=__lowercase)
										os.makedirs(F"""{path_to_transformer_root}/tests/models/{lowercase_model_name}"""  ,    exist_ok=__lowercase)

										# 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(UpperCamelCase):
													with open(__lowercase  ,    'r') as f:
																UpperCamelCase__     :		List[Any]	 =					f.readlines()
													with open(__lowercase  ,    'w') as f:
																for line in lines:
																			if "# Copied from transformers." not in line:
																						f.write(__lowercase)

										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(UpperCamelCase  ,    UpperCamelCase  ,    UpperCamelCase):
													# Create temp file
													UpperCamelCase__     :		Tuple	 =					mkstemp()
													UpperCamelCase__     :		int	 =					False
													with fdopen(__lowercase  ,    'w') as new_file:
																with open(__lowercase) as old_file:
																			for line in old_file:
																						new_file.write(__lowercase)
																						if line_to_copy_below in line:
																									UpperCamelCase__     :		Optional[Any]	 =					True
																									for line_to_copy in lines_to_copy:
																												new_file.write(__lowercase)

													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(__lowercase  ,    __lowercase)
													# Remove original file
													remove(__lowercase)
													# Move new file
													move(__lowercase  ,    __lowercase)

										def skip_units(UpperCamelCase):
													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(UpperCamelCase):
													with open(__lowercase) as datafile:
																UpperCamelCase__     :		Tuple	 =					[]
																UpperCamelCase__     :		Optional[Any]	 =					False
																UpperCamelCase__     :		Dict	 =					False
																for line in datafile:
																			if "# To replace in: " in line and "##" not in line:
																						UpperCamelCase__     :		List[str]	 =					line.split('"')[1]
																						UpperCamelCase__     :		Optional[int]	 =					skip_units(__lowercase)
																			elif "# Below: " in line and "##" not in line:
																						UpperCamelCase__     :		List[Any]	 =					line.split('"')[1]
																						UpperCamelCase__     :		Optional[int]	 =					skip_units(__lowercase)
																			elif "# End." in line and "##" not in line:
																						if not skip_file and not skip_snippet:
																									replace(__lowercase  ,    __lowercase  ,    __lowercase)

																						UpperCamelCase__     :		Tuple	 =					[]
																			elif "# Replace with" in line and "##" not in line:
																						UpperCamelCase__     :		Optional[Any]	 =					[]
																			elif "##" not in line:
																						lines_to_copy.append(__lowercase)

													remove(__lowercase)

										replace_in_files(F"""{directory}/to_replace_{lowercase_model_name}.py""")
										os.rmdir(__lowercase)







'''simple docstring'''
def       _lowercase							(					UpperCamelCase__							:       dict      ):
 __A	:		Dict	  =      set()
 # edges = list of graph's edges
 __A	:		Any	  =      get_edges(UpperCamelCase__      )

 # While there are still elements in edges list, take an arbitrary edge
 # (from_node, to_node) and add his extremity to chosen_vertices and then
 # remove all arcs adjacent to the from_node and to_node
 while edges:
  __A  ,__A	:		List[Any]	  =      edges.pop()
  chosen_vertices.add(UpperCamelCase__      )
  chosen_vertices.add(UpperCamelCase__      )
  for edge in edges.copy():
   if from_node in edge or to_node in edge:
    edges.discard(UpperCamelCase__      )
 return chosen_vertices


def       _lowercase							(					UpperCamelCase__							:       dict      ):
 __A	:		Any	  =      set()
 for from_node, to_nodes in graph.items():
  for to_node in to_nodes:
   edges.add((from_node, to_node)      )
 return edges


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 # graph = {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
 # print(f"Matching vertex cover:\n{matching_min_vertex_cover(graph)}")






