
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):
							lowercase_			:			int			   =['''image_processor''', '''tokenizer''']
							lowercase_			:			Optional[Any]			   ='''EfficientNetImageProcessor'''
							lowercase_			:			List[Any]			   =('''BertTokenizer''', '''BertTokenizerFast''')




							def __init__(							self  ,A__  ,A__):
												super().__init__(A__  ,A__)




							def __call__(							self  ,A__=None  ,A__=None  ,A__="max_length"  ,A__=6_4  ,A__=None  ,**A__):
												if text is None and images is None:
																	raise ValueError('''You have to specify either text or images. Both cannot be none.''')

												if text is not None:
																	lowercase		      =		self.tokenizer(
																	    A__  ,padding=A__  ,max_length=A__  ,return_tensors=A__  ,**A__)

												if images is not None:
																	lowercase		      =		self.image_processor(A__  ,return_tensors=A__  ,**A__)

												if text is not None and images is not None:
																	lowercase		      =		image_features.pixel_values
																	return encoding
												elif text is not None:
																	return encoding
												else:
																	return BatchEncoding(data=dict(**A__)  ,tensor_type=A__)




							def 					A__ (							self  ,*A__  ,**A__):
												return self.tokenizer.batch_decode(*A__  ,**A__)




							def 					A__ (							self  ,*A__  ,**A__):
												return self.tokenizer.decode(*A__  ,**A__)





							@property
							def 					A__ (							self):
												lowercase		      =		self.tokenizer.model_input_names
												lowercase		      =		self.image_processor.model_input_names
												return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))






# 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 			UpperCamelCase       (				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\''						)
					lowercase      ,		lowercase		      =		[], False
					for line in lines:
										if not found_start and f'def {name}' in line:
															lowercase		      =		True
															good_lines.append(lowerCAmelCase__						)
															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(lowerCAmelCase__						)



def 			UpperCamelCase       (				lowerCAmelCase__						):
					'''simple docstring'''
					return [line for line in lines if not line.lstrip().startswith('''#'''						) and line != "\n"]



def 			UpperCamelCase       (				lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__ = None						):
					'''simple docstring'''
					with open(lowerCAmelCase__					,     '''r'''						) as f:
										lowercase		      =		f.readlines()
					with open(os.path.abspath(os.path.join('''examples'''					,     '''nlp_example.py'''						)						)					,     '''r'''						) as f:
										lowercase		      =		f.readlines()
					with open(lowerCAmelCase__					,     '''r'''						) as f:
										lowercase		      =		f.readlines()
					if secondary_filename is not None:
										with open(lowerCAmelCase__					,     '''r'''						) as f:
															lowercase		      =		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:
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
										if secondary_filename is not None:
															lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
					else:
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)
										if secondary_filename is not None:
															lowercase		      =		clean_lines(
															    get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)

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

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

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

					return diff_from_example




