

'''simple docstring'''

def 							_UpperCamelCase				(   lowerCAmelCase__:					int   )      -> "list[int]":
							if upper_limit < 0:
														raise ValueError('Limit for the Catalan sequence must be ≥ 0'   )

							SCREAMING_SNAKE_CASE_				=				[0] * (upper_limit + 1)

							# Base case: C(0) = C(1) = 1
							SCREAMING_SNAKE_CASE_				=				1
							if upper_limit > 0:
														SCREAMING_SNAKE_CASE_				=				1

							# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
							for i in range(2		,upper_limit + 1   ):
														for j in range(lowerCAmelCase__   ):
																					catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

							return catalan_list


if __name__ == "__main__":
							print("\n********* Catalan Numbers Using Dynamic Programming ************\n")
							print("\n*** Enter -1 at any time to quit ***")
							print("\nEnter the upper limit (≥ 0) for the Catalan number sequence: ", end="")
							try:
														while True:
																					SCREAMING_SNAKE_CASE							:				Optional[Any]     	=			int(input().strip())
																					if N < 0:
																												print("\n********* Goodbye!! ************")
																												break
																					else:
																												print(f"The Catalan numbers from 0 through {N} are:")
																												print(catalan_numbers(N))
																												print("Try another upper limit for the sequence: ", end="")
							except (NameError, ValueError):
														print("\n********* Invalid input, goodbye! ************\n")

							import doctest

							doctest.testmod()








'''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

							SCREAMING_SNAKE_CASE							:				Dict     	=			True
except ImportError:
							SCREAMING_SNAKE_CASE							:				Optional[Any]     	=			False

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




def 							_UpperCamelCase				(   lowerCAmelCase__:					Namespace   )      -> Optional[Any]:
							return AddNewModelCommand(args.testing		,args.testing_file		,path=args.path   )






class    snake_case     (      lowercase_		):






				"""simple docstring"""



				@staticmethod
				def   a__					(    _lowercase       )     ->							Tuple:
											SCREAMING_SNAKE_CASE_				=				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,     _lowercase,     _lowercase,     _lowercase=None,     *_lowercase       )     ->							Optional[Any]:
											SCREAMING_SNAKE_CASE_				=				testing
											SCREAMING_SNAKE_CASE_				=				testing_file
											SCREAMING_SNAKE_CASE_				=				path





				def   a__					(    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
											SCREAMING_SNAKE_CASE_				=				[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.'       )

											SCREAMING_SNAKE_CASE_				=				(
											    Path(_lowercase       ).parent.parent.parent.parent if self._path is None else Path(self._path       ).parent.parent
											)
											SCREAMING_SNAKE_CASE_				=				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:
																									SCREAMING_SNAKE_CASE_				=				json.load(_lowercase       )

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

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

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

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

											SCREAMING_SNAKE_CASE_				=				'PyTorch' in generate_tensorflow_pytorch_and_flax
											SCREAMING_SNAKE_CASE_				=				'TensorFlow' in generate_tensorflow_pytorch_and_flax
											SCREAMING_SNAKE_CASE_				=				'Flax' in generate_tensorflow_pytorch_and_flax

											SCREAMING_SNAKE_CASE_				=				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(_lowercase       ):
																		with open(_lowercase,     'r'       ) as f:
																									SCREAMING_SNAKE_CASE_				=				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(_lowercase,     _lowercase,     _lowercase       ):
																		# Create temp file
																		SCREAMING_SNAKE_CASE_				,    SCREAMING_SNAKE_CASE_				=				mkstemp()
																		SCREAMING_SNAKE_CASE_				=				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:
																																														SCREAMING_SNAKE_CASE_				=				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(_lowercase       ):
																		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(_lowercase       ):
																		with open(_lowercase       ) as datafile:
																									SCREAMING_SNAKE_CASE_				=				[]
																									SCREAMING_SNAKE_CASE_				=				False
																									SCREAMING_SNAKE_CASE_				=				False
																									for line in datafile:
																																if "# To replace in: " in line and "##" not in line:
																																							SCREAMING_SNAKE_CASE_				=				line.split('"'       )[1]
																																							SCREAMING_SNAKE_CASE_				=				skip_units(_lowercase       )
																																elif "# Below: " in line and "##" not in line:
																																							SCREAMING_SNAKE_CASE_				=				line.split('"'       )[1]
																																							SCREAMING_SNAKE_CASE_				=				skip_units(_lowercase       )
																																elif "# End." in line and "##" not in line:
																																							if not skip_file and not skip_snippet:
																																														replace(_lowercase,     _lowercase,     _lowercase       )

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





