
"""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

		_lowerCamelCase  :			Optional[Any]        =       True
except ImportError:
		_lowerCamelCase  :			str        =       False

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

def 		lowercase_      (		_UpperCAmelCase	):




	"""simple docstring"""






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

class        lowercase      (    __UpperCAmelCase):







				@staticmethod
				def 					a_  (							_lowerCamelCase   :					ArgumentParser       ):



					"""simple docstring"""

					A_  :				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=_lowerCamelCase      ,     help='''Configuration file on which to run.'''       )
					add_new_model_parser.add_argument(
					    '''--path'''      ,     type=_lowerCamelCase      ,     help='''Path to cookiecutter. Should only be used for testing purposes.'''       )
					add_new_model_parser.set_defaults(func=_lowerCamelCase       )







				def __init__(							self   :					Any      ,     _lowerCamelCase   :					bool      ,     _lowerCamelCase   :					str      ,     _lowerCamelCase   :					Tuple=None      ,     *_lowerCamelCase   :					Tuple       ):



					"""simple docstring"""

					A_  :				str	   =		testing
					A_  :				List[Any]	   =		testing_file
					A_  :				str	   =		path







				def 					a_  (							self   :					Tuple       ):



					"""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
					A_  :				str	   =		[directory for directory in os.listdir() if '''cookiecutter-template-''' == directory[:22]]
					if len(_lowerCamelCase       ) > 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_  :				List[Any]	   =		(
					    Path(_lowerCamelCase       ).parent.parent.parent.parent if self._path is None else Path(self._path       ).parent.parent
					)
					A_  :				Tuple	   =		path_to_transformer_root / '''templates''' / '''adding_a_new_model'''

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

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

					A_  :				Optional[Any]	   =		[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_  :				str	   =		json.load(_lowerCamelCase       )

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

					A_  :				Tuple	   =		'''PyTorch''' in generate_tensorflow_pytorch_and_flax
					A_  :				Dict	   =		'''TensorFlow''' in generate_tensorflow_pytorch_and_flax
					A_  :				int	   =		'''Flax''' in generate_tensorflow_pytorch_and_flax

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

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

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

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

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

									A_  :				int	   =		[]
								elif "# Replace with" in line and "##" not in line:
									A_  :				Any	   =		[]
								elif "##" not in line:
									lines_to_copy.append(_lowerCamelCase       )

						remove(_lowerCamelCase       )

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











"""simple docstring"""

def 		lowercase_      (		_UpperCAmelCase	):




	"""simple docstring"""






	A_  :				int	   =		len(_UpperCAmelCase	)
	for i in range(length - 1	):
		A_  :				str	   =		i
		for k in range(i + 1  ,      _UpperCAmelCase	):
			if collection[k] < collection[least]:
				A_  :				Tuple	   =		k
		if least != i:
			A_   , A_  :				Optional[int]	   =		(collection[i], collection[least])
	return collection


if __name__ == "__main__":
		_lowerCamelCase  :			Optional[int]        =       input('Enter numbers separated by a comma:\n').strip()
		_lowerCamelCase  :			List[str]        =       [int(item) for item in user_input.split(',')]
		print(selection_sort(unsorted))





