





# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List







def 			_SCREAMING_SNAKE_CASE    (       a ,						a  )				->				Union[str, Any]:
					if name != "training_function" and name != "main":
										raise ValueError(F"""Incorrect function name passed: {name}, choose either 'main' or 'training_function'"""  )
					__A   ,    __A     :						Any          =    [], False
					for line in lines:
										if not found_start and F"""def {name}""" in line:
															__A     :						Optional[Any]          =    True
															good_lines.append(a  )
															continue
										if found_start:
															if name == "training_function" and "def main" in line:
																				return good_lines
															if name == "main" and "if __name__" in line:
																				return good_lines
															good_lines.append(a  )







def 			_SCREAMING_SNAKE_CASE    (       a  )				->				Optional[int]:
					return [line for line in lines if not line.lstrip().startswith('#'  ) and line != "\n"]







def 			_SCREAMING_SNAKE_CASE    (       a ,						a ,						a ,						a = None  )				->				Tuple:
					with open(a ,						'r'  ) as f:
										__A     :						Tuple          =    f.readlines()
					with open(os.path.abspath(os.path.join('examples' ,						'nlp_example.py'  )  ) ,						'r'  ) as f:
										__A     :						Tuple          =    f.readlines()
					with open(a ,						'r'  ) as f:
										__A     :						Tuple          =    f.readlines()
					if secondary_filename is not None:
										with open(a ,						'r'  ) as f:
															__A     :						str          =    f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
					if parser_only:
										__A     :						int          =    clean_lines(get_function_contents_by_name(a ,						'main'  )  )
										__A     :						Any          =    clean_lines(get_function_contents_by_name(a ,						'main'  )  )
										__A     :						Tuple          =    clean_lines(get_function_contents_by_name(a ,						'main'  )  )
										if secondary_filename is not None:
															__A     :						Union[str, Any]          =    clean_lines(get_function_contents_by_name(a ,						'main'  )  )
					else:
										__A     :						Optional[int]          =    clean_lines(get_function_contents_by_name(a ,						'training_function'  )  )
										__A     :						Union[str, Any]          =    clean_lines(get_function_contents_by_name(a ,						'training_function'  )  )
										__A     :						int          =    clean_lines(get_function_contents_by_name(a ,						'training_function'  )  )
										if secondary_filename is not None:
															__A     :						str          =    clean_lines(
															    get_function_contents_by_name(a ,						'training_function'  )  )

					__A     :						List[Any]          =    'train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n'

					# Specific code in our script that differs from the full version, aka what is new
					__A     :						Dict          =    []
					__A     :						Union[str, Any]          =    []  # We keep track of the idxs just in case it's a repeated statement
					__A     :						str          =    iter(a  )
					for i in range(len(a  ) - 1  ):
										if i not in passed_idxs:
															__A     :						Dict          =    next(a  )
															if (line not in full_file_func) and (line.lstrip() != _dl_line):
																				if "TESTING_MOCKED_DATALOADERS" not in line:
																									new_feature_code.append(a  )
																									passed_idxs.append(a  )
																				else:
																									# Skip over the `config['num_epochs'] = 2` statement
																									__A     :						Dict          =    next(a  )

    # Extract out just the new parts from the full_file_training_func
					__A     :						int          =    []
					__A     :						Optional[int]          =    []  # We keep track of the idxs just in case it's a repeated statement
					for i, line in enumerate(a  ):
										if i not in passed_idxs:
															if (line not in full_file_func) and (line.lstrip() != _dl_line):
																				if "TESTING_MOCKED_DATALOADERS" not in line:
																									new_full_example_parts.append(a  )
																									passed_idxs.append(a  )

    # Finally, get the overall diff
					__A     :						Optional[Any]          =    [line for line in new_feature_code if line not in new_full_example_parts]
					if secondary_filename is not None:
										__A     :						Optional[Any]          =    [line for line in full_file_contents if line not in secondary_file_func]
										__A     :						Optional[Any]          =    [line for line in diff_from_example if line not in diff_from_two]

					return diff_from_example











from __future__ import annotations

import math
import random







def 			_SCREAMING_SNAKE_CASE    (       a ,						a ,						a  )				->				list[int]:
					__A     :						int          =    d * e - 1
					__A     :						List[str]          =    0
					__A     :						Optional[Any]          =    0
					while p == 0:
										__A     :						List[Any]          =    random.randint(2 ,						n - 1  )
										__A     :						Optional[int]          =    k
										while True:
															if t % 2 == 0:
																				__A     :						Tuple          =    t // 2
																				__A     :						List[str]          =    (g**t) % n
																				__A     :						List[Any]          =    math.gcd(x - 1 ,						a  )
																				if x > 1 and y > 1:
																									__A     :						List[str]          =    y
																									__A     :						str          =    n // y
																									break  # find the correct factors
															else:
																				break  # t is not divisible by 2, break and choose another g
					return sorted([p, q]  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()




