
"""simple docstring"""


from collections import deque
from math import floor
from random import random
from time import time







class 				lowerCAmelCase_				:



						'''simple docstring'''


						def __init__( self     :      Dict      )     ->   int:
							A						   =   {}


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Any  ,A_     :      Union[str, Any]  ,A_     :      Any  ,A_     :      Optional[Any]=1      )     ->   int:
							if self.graph.get(A_      ):
								if self.graph[u].count([w, v]      ) == 0:
									self.graph[u].append([w, v]      )
							else:
								A						   =   [[w, v]]
							if not self.graph.get(A_      ):
								A						   =   []


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[str]      )     ->   Optional[int]:
							return list(self.graph      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Union[str, Any]  ,A_     :      Union[str, Any]  ,A_     :      Dict      )     ->   Optional[Any]:
							if self.graph.get(A_      ):
								for _ in self.graph[u]:
									if _[1] == v:
										self.graph[u].remove(A_      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Any  ,A_     :      int=-2  ,A_     :      Dict=-1      )     ->   str:
							if s == d:
								return []
							A						   =   []
							A						   =   []
							if s == -2:
								A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   s

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if visited.count(node[1]      ) < 1:
											if node[1] == d:
												visited.append(A_      )
												return visited
											else:
												stack.append(node[1]      )
												visited.append(node[1]      )
												A						   =   node[1]
												break

            # check if all the children are visited
								if s == ss:
									stack.pop()
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return visited


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[Any]  ,A_     :      Any=-1      )     ->   int:
							if c == -1:
								A						   =   floor(random() * 1_0000      ) + 10
							for i in range(A_      ):
								# every vertex has max 100 edges
								for _ in range(floor(random() * 102      ) + 1      ):
									A						   =   floor(random() * c      ) + 1
									if n != i:
										self.add_pair(A_  ,A_  ,1      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[Any]  ,A_     :      Union[str, Any]=-2      )     ->   Optional[Any]:
							A						   =   deque()
							A						   =   []
							if s == -2:
								A						   =   list(self.graph      )[0]
							d.append(A_      )
							visited.append(A_      )
							while d:
								A						   =   d.popleft()
								if len(self.graph[s]      ) != 0:
									for node in self.graph[s]:
										if visited.count(node[1]      ) < 1:
											d.append(node[1]      )
											visited.append(node[1]      )
							return visited


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Union[str, Any]  ,A_     :      Tuple      )     ->   Any:
							A						   =   0
							for x in self.graph:
								for y in self.graph[x]:
									if y[1] == u:
										count += 1
							return count


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Dict  ,A_     :      Union[str, Any]      )     ->   str:
							return len(self.graph[u]      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[int]  ,A_     :      Union[str, Any]=-2      )     ->   Any:
							A						   =   []
							A						   =   []
							if s == -2:
								A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   s
							A						   =   []

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if visited.count(node[1]      ) < 1:
											stack.append(node[1]      )
											visited.append(node[1]      )
											A						   =   node[1]
											break

            # check if all the children are visited
								if s == ss:
									sorted_nodes.append(stack.pop()      )
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return sorted_nodes


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[Any]      )     ->   Tuple:
							A						   =   []
							A						   =   []
							A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   -2
							A						   =   []
							A						   =   s
							A						   =   False
							A						   =   set()

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if (
										    visited.count(node[1]      ) > 0
										    and node[1] != parent
										    and indirect_parents.count(node[1]      ) > 0
										    and not on_the_way_back
										):
											A						   =   len(A_      ) - 1
											while len_stack >= 0:
												if stack[len_stack] == node[1]:
													anticipating_nodes.add(node[1]      )
													break
												else:
													anticipating_nodes.add(stack[len_stack]      )
													len_stack -= 1
										if visited.count(node[1]      ) < 1:
											stack.append(node[1]      )
											visited.append(node[1]      )
											A						   =   node[1]
											break

            # check if all the children are visited
								if s == ss:
									stack.pop()
									A						   =   True
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   False
									indirect_parents.append(A_      )
									A						   =   s
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return list(A_      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      int      )     ->   Optional[int]:
							A						   =   []
							A						   =   []
							A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   -2
							A						   =   []
							A						   =   s
							A						   =   False
							A						   =   set()

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if (
										    visited.count(node[1]      ) > 0
										    and node[1] != parent
										    and indirect_parents.count(node[1]      ) > 0
										    and not on_the_way_back
										):
											A						   =   len(A_      ) - 1
											while len_stack_minus_one >= 0:
												if stack[len_stack_minus_one] == node[1]:
													anticipating_nodes.add(node[1]      )
													break
												else:
													return True
										if visited.count(node[1]      ) < 1:
											stack.append(node[1]      )
											visited.append(node[1]      )
											A						   =   node[1]
											break

            # check if all the children are visited
								if s == ss:
									stack.pop()
									A						   =   True
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   False
									indirect_parents.append(A_      )
									A						   =   s
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return False


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Dict  ,A_     :      Tuple=-2  ,A_     :      List[str]=-1      )     ->   str:
							A						   =   time()
							self.dfs(A_  ,A_      )
							A						   =   time()
							return end - begin




						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[str]  ,A_     :      Union[str, Any]=-2      )     ->   Dict:
							A						   =   time()
							self.bfs(A_      )
							A						   =   time()
							return end - begin







class 				lowerCAmelCase_				:



						'''simple docstring'''


						def __init__( self     :      List[Any]      )     ->   Tuple:
							A						   =   {}


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Any  ,A_     :      Optional[Any]  ,A_     :      str  ,A_     :      List[str]=1      )     ->   Dict:
							# check if the u exists
							if self.graph.get(A_      ):
								# if there already is a edge
								if self.graph[u].count([w, v]      ) == 0:
									self.graph[u].append([w, v]      )
							else:
								# if u does not exist
								A						   =   [[w, v]]
							# add the other way
							if self.graph.get(A_      ):
								# if there already is a edge
								if self.graph[v].count([w, u]      ) == 0:
									self.graph[v].append([w, u]      )
							else:
								# if u does not exist
								A						   =   [[w, u]]


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[Any]  ,A_     :      List[Any]  ,A_     :      List[str]      )     ->   List[Any]:
							if self.graph.get(A_      ):
								for _ in self.graph[u]:
									if _[1] == v:
										self.graph[u].remove(A_      )
        # the other way round
							if self.graph.get(A_      ):
								for _ in self.graph[v]:
									if _[1] == u:
										self.graph[v].remove(A_      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[Any]  ,A_     :      List[str]=-2  ,A_     :      List[Any]=-1      )     ->   int:
							if s == d:
								return []
							A						   =   []
							A						   =   []
							if s == -2:
								A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   s

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if visited.count(node[1]      ) < 1:
											if node[1] == d:
												visited.append(A_      )
												return visited
											else:
												stack.append(node[1]      )
												visited.append(node[1]      )
												A						   =   node[1]
												break

            # check if all the children are visited
								if s == ss:
									stack.pop()
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return visited


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Union[str, Any]  ,A_     :      Optional[int]=-1      )     ->   List[Any]:
							if c == -1:
								A						   =   floor(random() * 1_0000      ) + 10
							for i in range(A_      ):
								# every vertex has max 100 edges
								for _ in range(floor(random() * 102      ) + 1      ):
									A						   =   floor(random() * c      ) + 1
									if n != i:
										self.add_pair(A_  ,A_  ,1      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[Any]  ,A_     :      Dict=-2      )     ->   List[Any]:
							A						   =   deque()
							A						   =   []
							if s == -2:
								A						   =   list(self.graph      )[0]
							d.append(A_      )
							visited.append(A_      )
							while d:
								A						   =   d.popleft()
								if len(self.graph[s]      ) != 0:
									for node in self.graph[s]:
										if visited.count(node[1]      ) < 1:
											d.append(node[1]      )
											visited.append(node[1]      )
							return visited


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Union[str, Any]  ,A_     :      Optional[Any]      )     ->   List[Any]:
							return len(self.graph[u]      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      List[str]      )     ->   List[Any]:
							A						   =   []
							A						   =   []
							A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   -2
							A						   =   []
							A						   =   s
							A						   =   False
							A						   =   set()

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if (
										    visited.count(node[1]      ) > 0
										    and node[1] != parent
										    and indirect_parents.count(node[1]      ) > 0
										    and not on_the_way_back
										):
											A						   =   len(A_      ) - 1
											while len_stack >= 0:
												if stack[len_stack] == node[1]:
													anticipating_nodes.add(node[1]      )
													break
												else:
													anticipating_nodes.add(stack[len_stack]      )
													len_stack -= 1
										if visited.count(node[1]      ) < 1:
											stack.append(node[1]      )
											visited.append(node[1]      )
											A						   =   node[1]
											break

            # check if all the children are visited
								if s == ss:
									stack.pop()
									A						   =   True
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   False
									indirect_parents.append(A_      )
									A						   =   s
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return list(A_      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[int]      )     ->   Any:
							A						   =   []
							A						   =   []
							A						   =   list(self.graph      )[0]
							stack.append(A_      )
							visited.append(A_      )
							A						   =   -2
							A						   =   []
							A						   =   s
							A						   =   False
							A						   =   set()

							while True:
								# check if there is any non isolated nodes
								if len(self.graph[s]      ) != 0:
									A						   =   s
									for node in self.graph[s]:
										if (
										    visited.count(node[1]      ) > 0
										    and node[1] != parent
										    and indirect_parents.count(node[1]      ) > 0
										    and not on_the_way_back
										):
											A						   =   len(A_      ) - 1
											while len_stack_minus_one >= 0:
												if stack[len_stack_minus_one] == node[1]:
													anticipating_nodes.add(node[1]      )
													break
												else:
													return True
										if visited.count(node[1]      ) < 1:
											stack.append(node[1]      )
											visited.append(node[1]      )
											A						   =   node[1]
											break

            # check if all the children are visited
								if s == ss:
									stack.pop()
									A						   =   True
									if len(A_      ) != 0:
										A						   =   stack[len(A_      ) - 1]
								else:
									A						   =   False
									indirect_parents.append(A_      )
									A						   =   s
									A						   =   ss

								# check if se have reached the starting point
								if len(A_      ) == 0:
									return False


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Dict      )     ->   Any:
							return list(self.graph      )


						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[int]  ,A_     :      Optional[Any]=-2  ,A_     :      List[str]=-1      )     ->   Any:
							A						   =   time()
							self.dfs(A_  ,A_      )
							A						   =   time()
							return end - begin




						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[Any]  ,A_     :      List[Any]=-2      )     ->   Union[str, Any]:
							A						   =   time()
							self.bfs(A_      )
							A						   =   time()
							return end - begin

"""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       _snake_case				(		snake_case__   :     Namespace     ):
	return AddNewModelCommand(args.testing	,      args.testing_file	,      path=args.path     )







class 				lowerCAmelCase_				(      _lowercase    ):



						'''simple docstring'''


						@staticmethod
						def 						_SCREAMING_SNAKE_CASE      ( A_     :      ArgumentParser      )     ->   Any:
							A						   =   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_     :      Tuple=None  ,*A_     :      List[str]      )     ->   Union[str, Any]:
							A						   =   testing
							A						   =   testing_file
							A						   =   path




						def 						_SCREAMING_SNAKE_CASE      ( self     :      int      )     ->   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
							A						   =   [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.'      )

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

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

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

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

							A						   =   configuration['lowercase_modelname']
							A						   =   configuration['generate_tensorflow_pytorch_and_flax']
							os.remove(F'{directory}/configuration.json'      )

							A						   =   'PyTorch' in generate_tensorflow_pytorch_and_flax
							A						   =   'TensorFlow' in generate_tensorflow_pytorch_and_flax
							A						   =   'Flax' in generate_tensorflow_pytorch_and_flax

							A						   =   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_     :      int      ):
								with open(A_  ,'r'      ) as f:
									A						   =   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
								A   ,      A						   =   mkstemp()
								A						   =   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:
												A						   =   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_     :      Dict      ):
								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_     :      Tuple      ):
								with open(A_      ) as datafile:
									A						   =   []
									A						   =   False
									A						   =   False
									for line in datafile:
										if "# To replace in: " in line and "##" not in line:
											A						   =   line.split('"'      )[1]
											A						   =   skip_units(A_      )
										elif "# Below: " in line and "##" not in line:
											A						   =   line.split('"'      )[1]
											A						   =   skip_units(A_      )
										elif "# End." in line and "##" not in line:
											if not skip_file and not skip_snippet:
												replace(A_  ,A_  ,A_      )

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