
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

						__a  			=					True
except ImportError:
						__a  			=					False

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




def 				a						(							snake_case__:					Namespace					):


				'''simple docstring'''
				return AddNewModelCommand(args.testing						,   args.testing_file						,   path=args.path					)


class  lowercase__(				_SCREAMING_SNAKE_CASE							):



	"""simple docstring"""




	@staticmethod
	def 						_lowercase  (       SCREAMING_SNAKE_CASE_  :			ArgumentParser       )       ->     int:
					lowercase_       =					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=SCREAMING_SNAKE_CASE_       ,							help='''Configuration file on which to run.'''       )
					add_new_model_parser.add_argument(
					    '''--path'''       ,							type=SCREAMING_SNAKE_CASE_       ,							help='''Path to cookiecutter. Should only be used for testing purposes.'''       )
					add_new_model_parser.set_defaults(func=SCREAMING_SNAKE_CASE_       )
	def __init__(       self  :			List[str]       ,							SCREAMING_SNAKE_CASE_  :			bool       ,							SCREAMING_SNAKE_CASE_  :			str       ,							SCREAMING_SNAKE_CASE_  :			Any=None       ,							*SCREAMING_SNAKE_CASE_  :			List[str]       )       ->     Optional[Any]:
					lowercase_       =					testing
					lowercase_       =					testing_file
					lowercase_       =					path




	def 						_lowercase  (       self  :			Tuple       )       ->     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
					lowercase_       =					[directory for directory in os.listdir() if """cookiecutter-template-""" == directory[:2_2]]
					if len(SCREAMING_SNAKE_CASE_       ) > 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.'''       )

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

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

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

					lowercase_       =					[directory for directory in os.listdir() if """cookiecutter-template-""" in directory[:2_2]][0]

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

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

					lowercase_       =					"""PyTorch""" in generate_tensorflow_pytorch_and_flax
					lowercase_       =					"""TensorFlow""" in generate_tensorflow_pytorch_and_flax
					lowercase_       =					"""Flax""" in generate_tensorflow_pytorch_and_flax

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

					# 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(SCREAMING_SNAKE_CASE_  :			Any       ):
									with open(SCREAMING_SNAKE_CASE_       ,							'''r'''       ) as f:
													lowercase_       =					f.readlines()
									with open(SCREAMING_SNAKE_CASE_       ,							'''w'''       ) as f:
													for line in lines:
																	if "# Copied from transformers." not in line:
																					f.write(SCREAMING_SNAKE_CASE_       )

					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(SCREAMING_SNAKE_CASE_  :			str       ,							SCREAMING_SNAKE_CASE_  :			str       ,							SCREAMING_SNAKE_CASE_  :			List[str]       ):
									# Create temp file
									lowercase_       =					mkstemp()
									lowercase_       =					False
									with fdopen(SCREAMING_SNAKE_CASE_       ,							'''w'''       ) as new_file:
													with open(SCREAMING_SNAKE_CASE_       ) as old_file:
																	for line in old_file:
																					new_file.write(SCREAMING_SNAKE_CASE_       )
																					if line_to_copy_below in line:
																									lowercase_       =					True
																									for line_to_copy in lines_to_copy:
																													new_file.write(SCREAMING_SNAKE_CASE_       )

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

					def skip_units(SCREAMING_SNAKE_CASE_  :			Optional[int]       ):
									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(SCREAMING_SNAKE_CASE_  :			Any       ):
									with open(SCREAMING_SNAKE_CASE_       ) as datafile:
													lowercase_       =					[]
													lowercase_       =					False
													lowercase_       =					False
													for line in datafile:
																	if "# To replace in: " in line and "##" not in line:
																					lowercase_       =					line.split('''\"'''       )[1]
																					lowercase_       =					skip_units(SCREAMING_SNAKE_CASE_       )
																	elif "# Below: " in line and "##" not in line:
																					lowercase_       =					line.split('''\"'''       )[1]
																					lowercase_       =					skip_units(SCREAMING_SNAKE_CASE_       )
																	elif "# End." in line and "##" not in line:
																					if not skip_file and not skip_snippet:
																									replace(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )

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

									remove(SCREAMING_SNAKE_CASE_       )

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








'''simple docstring'''






from statistics import mean, stdev







def 				UpperCamelCase_			(    A__					:   list							,    A__					:   int = 3					):
  '''simple docstring'''





  lowerCAmelCase_			:      List[str]			=   min(A__					)
  lowerCAmelCase_			:      Optional[int]			=   max(A__					)
  # normalize data
  return [round((x - x_min) / (x_max - x_min)							,    A__					) for x in data]







def 				UpperCamelCase_			(    A__					:   list							,    A__					:   int = 3					):
  '''simple docstring'''





  lowerCAmelCase_			:      str			=   mean(A__					)
  lowerCAmelCase_			:      List[Any]			=   stdev(A__					)
  # standardize data
  return [round((x - mu) / (sigma)							,    A__					) for x in data]



