


lowerCAmelCase__			:      Union[str, Any]								='ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'






def 						a__			(				A__				):
			# Make sure the supplied data is a bytes-like object
			if not isinstance(A__,      A__				):
						SCREAMING_SNAKE_CASE_		:     int					=					F'''a bytes-like object is required, not \'{data.__class__.__name__}\''''
						raise TypeError(A__				)

			SCREAMING_SNAKE_CASE_		:     int					=					''.join(bin(A__				)[2:].zfill(8				) for byte in data				)

			SCREAMING_SNAKE_CASE_		:     Optional[int]					=					len(A__				) % 6 != 0

			if padding_needed:
						# The padding that will be added later
						SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					B'=' * ((6 - len(A__				) % 6) // 2)

						# Append binary_stream with arbitrary binary digits (0's by default) to make its
						# length a multiple of 6.
						binary_stream += "0" * (6 - len(A__				) % 6)
			else:
						SCREAMING_SNAKE_CASE_		:     Optional[int]					=					B''

			# Encode every 6 binary digits to their corresponding Base64 character
			return (
			    "".join(
			        B64_CHARSET[int(binary_stream[index : index + 6],      2				)]
			        for index in range(0,      len(A__				),      6				)				).encode()
			    + padding
			)






def 						a__			(				A__				):
			# Make sure encoded_data is either a string or a bytes-like object
			if not isinstance(A__,      A__				) and not isinstance(A__,      A__				):
						SCREAMING_SNAKE_CASE_		:     Dict					=					(
						    'argument should be a bytes-like object or ASCII string, '
						    F'''not \'{encoded_data.__class__.__name__}\''''
						)
						raise TypeError(A__				)

			# In case encoded_data is a bytes-like object, make sure it contains only
			# ASCII characters so we convert it to a string object
			if isinstance(A__,      A__				):
						try:
									SCREAMING_SNAKE_CASE_		:     Tuple					=					encoded_data.decode('utf-8'				)
						except UnicodeDecodeError:
									raise ValueError('base64 encoded data should only contain ASCII characters'				)

			SCREAMING_SNAKE_CASE_		:     str					=					encoded_data.count('='				)

			# Check if the encoded string contains non base64 characters
			if padding:
						assert all(
						    char in B64_CHARSET for char in encoded_data[:-padding]				), "Invalid base64 character(s) found."
			else:
						assert all(
						    char in B64_CHARSET for char in encoded_data				), "Invalid base64 character(s) found."

			# Check the padding
			assert len(A__				) % 4 == 0 and padding < 3, "Incorrect padding"

			if padding:
						# Remove padding if there is one
						SCREAMING_SNAKE_CASE_		:     Dict					=					encoded_data[:-padding]

						SCREAMING_SNAKE_CASE_		:     str					=					''.join(
						    bin(B64_CHARSET.index(A__				)				)[2:].zfill(6				) for char in encoded_data				)[: -padding * 2]
			else:
						SCREAMING_SNAKE_CASE_		:     Any					=					''.join(
						    bin(B64_CHARSET.index(A__				)				)[2:].zfill(6				) for char in encoded_data				)

			SCREAMING_SNAKE_CASE_		:     Tuple					=					[
			    int(binary_stream[index : index + 8],      2				)
			    for index in range(0,      len(A__				),      8				)
			]

			return bytes(A__				)


if __name__ == "__main__":
				import doctest

				doctest.testmod()









from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						["""image_processor""", """tokenizer"""]
							_UpperCAmelCase      =						"""Pix2StructImageProcessor"""
							_UpperCAmelCase      =						("""T5Tokenizer""", """T5TokenizerFast""")






							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					False
										super().__init__(lowerCAmelCase__			,						lowerCAmelCase__       )






							def __call__(      self			,						lowerCAmelCase__=None			,						lowerCAmelCase__ = None			,						lowerCAmelCase__ = True			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = None			,						lowerCAmelCase__ = None			,						lowerCAmelCase__ = 2_0_4_8			,						lowerCAmelCase__ = 0			,						lowerCAmelCase__ = None			,						lowerCAmelCase__ = None			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = True			,						lowerCAmelCase__ = None			,						**lowerCAmelCase__			,						):





										"""simple docstring"""




										if images is None and text is None:
													raise ValueError('You have to specify either images or text.'       )

										# Get only text
										if images is None and not self.image_processor.is_vqa:
													SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.tokenizer
													SCREAMING_SNAKE_CASE_		:     str					=					self.tokenizer(
													    text=lowerCAmelCase__			,						add_special_tokens=lowerCAmelCase__			,						padding=lowerCAmelCase__			,						truncation=lowerCAmelCase__			,						max_length=lowerCAmelCase__			,						stride=lowerCAmelCase__			,						pad_to_multiple_of=lowerCAmelCase__			,						return_attention_mask=lowerCAmelCase__			,						return_overflowing_tokens=lowerCAmelCase__			,						return_special_tokens_mask=lowerCAmelCase__			,						return_offsets_mapping=lowerCAmelCase__			,						return_token_type_ids=lowerCAmelCase__			,						return_length=lowerCAmelCase__			,						verbose=lowerCAmelCase__			,						return_tensors=lowerCAmelCase__			,						**lowerCAmelCase__			,						)
													return text_encoding

										if not self.image_processor.is_vqa:
													# add pixel_values
													SCREAMING_SNAKE_CASE_		:     List[Any]					=					self.image_processor(
													    lowerCAmelCase__			,						return_tensors=lowerCAmelCase__			,						max_patches=lowerCAmelCase__			,						**lowerCAmelCase__       )
										else:
													# add pixel_values and bbox
													SCREAMING_SNAKE_CASE_		:     Any					=					self.image_processor(
													    lowerCAmelCase__			,						return_tensors=lowerCAmelCase__			,						max_patches=lowerCAmelCase__			,						header_text=lowerCAmelCase__			,						**lowerCAmelCase__       )

										if text is not None and not self.image_processor.is_vqa:
													SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					self.tokenizer(
													    text=lowerCAmelCase__			,						add_special_tokens=lowerCAmelCase__			,						padding=lowerCAmelCase__			,						truncation=lowerCAmelCase__			,						max_length=lowerCAmelCase__			,						stride=lowerCAmelCase__			,						pad_to_multiple_of=lowerCAmelCase__			,						return_attention_mask=lowerCAmelCase__			,						return_overflowing_tokens=lowerCAmelCase__			,						return_special_tokens_mask=lowerCAmelCase__			,						return_offsets_mapping=lowerCAmelCase__			,						return_token_type_ids=lowerCAmelCase__			,						return_length=lowerCAmelCase__			,						verbose=lowerCAmelCase__			,						return_tensors=lowerCAmelCase__			,						**lowerCAmelCase__			,						)

													if "attention_mask" in text_encoding:
																SCREAMING_SNAKE_CASE_		:     Any					=					text_encoding.pop('attention_mask'       )
													if "input_ids" in text_encoding:
																SCREAMING_SNAKE_CASE_		:     List[str]					=					text_encoding.pop('input_ids'       )
										else:
													SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					None

										if text_encoding is not None:
													encoding_image_processor.update(lowerCAmelCase__       )

										return encoding_image_processor






							def 					UpperCamelCase__     (      self			,						*lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										return self.tokenizer.batch_decode(*lowerCAmelCase__			,						**lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self			,						*lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										return self.tokenizer.decode(*lowerCAmelCase__			,						**lowerCAmelCase__       )






							@property
							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     List[str]					=					self.tokenizer.model_input_names
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.image_processor.model_input_names
										return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names       )       )





