





'''simple docstring'''




# 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 						__A						(       lowerCamelCase_	,	lowerCamelCase_					):


		"""simple docstring"""



		if name != "training_function" and name != "main":
				raise ValueError(f'''Incorrect function name passed: {name}, choose either \'main\' or \'training_function\''''					)
		SCREAMING_SNAKE_CASE				:							Tuple						=	[], False
		for line in lines:
				if not found_start and f'''def {name}''' in line:
						SCREAMING_SNAKE_CASE				:							Optional[Any]						=	True
						good_lines.append(_SCREAMING_SNAKE_CASE					)
						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(_SCREAMING_SNAKE_CASE					)



def 						__A						(       lowerCamelCase_					):


		"""simple docstring"""



		return [line for line in lines if not line.lstrip().startswith("""#"""					) and line != "\n"]



def 						__A						(       lowerCamelCase_	,	lowerCamelCase_	,	lowerCamelCase_	,	lowerCamelCase_ = None					):


		"""simple docstring"""



		with open(_SCREAMING_SNAKE_CASE	,	"""r"""					) as f:
				SCREAMING_SNAKE_CASE				:							List[str]						=	f.readlines()
		with open(os.path.abspath(os.path.join("""examples"""	,	"""nlp_example.py"""					)					)	,	"""r"""					) as f:
				SCREAMING_SNAKE_CASE				:							Optional[Any]						=	f.readlines()
		with open(_SCREAMING_SNAKE_CASE	,	"""r"""					) as f:
				SCREAMING_SNAKE_CASE				:							Dict						=	f.readlines()
		if secondary_filename is not None:
				with open(_SCREAMING_SNAKE_CASE	,	"""r"""					) as f:
						SCREAMING_SNAKE_CASE				:							List[Any]						=	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:
				SCREAMING_SNAKE_CASE				:							Optional[int]						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""main"""					)					)
				SCREAMING_SNAKE_CASE				:							Any						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""main"""					)					)
				SCREAMING_SNAKE_CASE				:							Optional[int]						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""main"""					)					)
				if secondary_filename is not None:
						SCREAMING_SNAKE_CASE				:							Dict						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""main"""					)					)
		else:
				SCREAMING_SNAKE_CASE				:							Any						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""training_function"""					)					)
				SCREAMING_SNAKE_CASE				:							Dict						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""training_function"""					)					)
				SCREAMING_SNAKE_CASE				:							Tuple						=	clean_lines(get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""training_function"""					)					)
				if secondary_filename is not None:
						SCREAMING_SNAKE_CASE				:							Optional[int]						=	clean_lines(
						    get_function_contents_by_name(_SCREAMING_SNAKE_CASE	,	"""training_function"""					)					)

		SCREAMING_SNAKE_CASE				:							List[str]						=	"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
		SCREAMING_SNAKE_CASE				:							Tuple						=	[]
		SCREAMING_SNAKE_CASE				:							Union[str, Any]						=	[]  # We keep track of the idxs just in case it's a repeated statement
		SCREAMING_SNAKE_CASE				:							List[str]						=	iter(_SCREAMING_SNAKE_CASE					)
		for i in range(len(_SCREAMING_SNAKE_CASE					) - 1					):
				if i not in passed_idxs:
						SCREAMING_SNAKE_CASE				:							Dict						=	next(_SCREAMING_SNAKE_CASE					)
						if (line not in full_file_func) and (line.lstrip() != _dl_line):
								if "TESTING_MOCKED_DATALOADERS" not in line:
										new_feature_code.append(_SCREAMING_SNAKE_CASE					)
										passed_idxs.append(_SCREAMING_SNAKE_CASE					)
								else:
										# Skip over the `config['num_epochs'] = 2` statement
										SCREAMING_SNAKE_CASE				:							str						=	next(_SCREAMING_SNAKE_CASE					)

    # Extract out just the new parts from the full_file_training_func
		SCREAMING_SNAKE_CASE				:							int						=	[]
		SCREAMING_SNAKE_CASE				:							Any						=	[]  # We keep track of the idxs just in case it's a repeated statement
		for i, line in enumerate(_SCREAMING_SNAKE_CASE					):
				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(_SCREAMING_SNAKE_CASE					)
										passed_idxs.append(_SCREAMING_SNAKE_CASE					)

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

		return diff_from_example










'''simple docstring'''




import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


__UpperCAmelCase         =   logging.get_logger(__name__)




class       UpperCamelCase__			(			lowercase_	):




					"""simple docstring"""


					def __init__(		self							:	Dict     ,		*lowerCamelCase_							:	Optional[int]     ,		**lowerCamelCase_							:	Optional[int]		):

							'''simple docstring'''



							warnings.warn(
							    """The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use DetrImageProcessor instead."""     ,		lowerCamelCase_     ,		)
							super().__init__(*lowerCamelCase_     ,		**lowerCamelCase_		)



