

from typing import Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
	from PIL import Image

	from ..image_utils import load_image

if is_torch_available():
	from ..models.auto.modeling_auto import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING

lowerCAmelCase__	   = logging.get_logger(__name__)

@add_end_docstrings(snake_case			)
class 					a__						(					snake_case			):
			"""simple docstring"""







			def __init__(    self      ,      *lowercase      ,      **lowercase       )  ->						str:
							'''simple docstring'''






							super().__init__(*lowercase      ,      **lowercase       )
							self.check_model_type(lowercase       )


			def      UpperCamelCase		(    self      ,      lowercase=None      ,      lowercase=None      ,      lowercase=None      ,      **lowercase       )  ->						Optional[int]:
							'''simple docstring'''






							A__    ,				A__        =			{}, {}
							if padding is not None:
											A__        =			padding
							if truncation is not None:
											A__        =			truncation
							if top_k is not None:
											A__        =			top_k
							return preprocess_params, {}, postprocess_params


			def __call__(    self      ,      lowercase      ,      lowercase = None      ,      **lowercase       )  ->						List[Any]:
							'''simple docstring'''






							if isinstance(lowercase      ,      (Image.Image, str)       ) and isinstance(lowercase      ,      lowercase       ):
											A__        =			{"image": image, "question": question}
							else:
											A__        =			image
							A__        =			super().__call__(lowercase      ,      **lowercase       )
							return results


			def      UpperCamelCase		(    self      ,      lowercase      ,      lowercase=False      ,      lowercase=False       )  ->						Union[str, Any]:
							'''simple docstring'''






							A__        =			load_image(inputs["image"]       )
							A__        =			self.tokenizer(
							    inputs["question"]      ,      return_tensors=self.framework      ,      padding=lowercase      ,      truncation=lowercase       )
							A__        =			self.image_processor(images=lowercase      ,      return_tensors=self.framework       )
							model_inputs.update(lowercase       )
							return model_inputs


			def      UpperCamelCase		(    self      ,      lowercase       )  ->						Tuple:
							'''simple docstring'''






							A__        =			self.model(**lowercase       )
							return model_outputs


			def      UpperCamelCase		(    self      ,      lowercase      ,      lowercase=5       )  ->						Optional[int]:
							'''simple docstring'''






							if top_k > self.model.config.num_labels:
											A__        =			self.model.config.num_labels

							if self.framework == "pt":
											A__        =			model_outputs.logits.sigmoid()[0]
											A__    ,				A__        =			probs.topk(lowercase       )
							else:
											raise ValueError(F'Unsupported framework: {self.framework}'       )

							A__        =			scores.tolist()
							A__        =			ids.tolist()
							return [{"score": score, "answer": self.model.config.idalabel[_id]} for score, _id in zip(lowercase      ,      lowercase       )]




lowerCAmelCase__	   = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							bytes      )			->      bytes:




				'''simple docstring'''





				if not isinstance(SCREAMING_SNAKE_CASE_	,       SCREAMING_SNAKE_CASE_      ):
								A__        =			F'a bytes-like object is required, not \'{data.__class__.__name__}\''
								raise TypeError(SCREAMING_SNAKE_CASE_      )

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

				A__        =			len(SCREAMING_SNAKE_CASE_      ) % 6 != 0

				if padding_needed:
								# The padding that will be added later
								A__        =			b"=" * ((6 - len(SCREAMING_SNAKE_CASE_      ) % 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(SCREAMING_SNAKE_CASE_      ) % 6)
				else:
								A__        =			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(SCREAMING_SNAKE_CASE_      )	,       6      )      ).encode()
				    + padding
				)



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							str      )			->      bytes:




				'''simple docstring'''





				if not isinstance(SCREAMING_SNAKE_CASE_	,       SCREAMING_SNAKE_CASE_      ) and not isinstance(SCREAMING_SNAKE_CASE_	,       SCREAMING_SNAKE_CASE_      ):
								A__        =			(
								    "argument should be a bytes-like object or ASCII string, "
								    F'not \'{encoded_data.__class__.__name__}\''
								)
								raise TypeError(SCREAMING_SNAKE_CASE_      )

				# 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(SCREAMING_SNAKE_CASE_	,       SCREAMING_SNAKE_CASE_      ):
								try:
												A__        =			encoded_data.decode("utf-8"      )
								except UnicodeDecodeError:
												raise ValueError("base64 encoded data should only contain ASCII characters"      )

				A__        =			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(SCREAMING_SNAKE_CASE_      ) % 4 == 0 and padding < 3, "Incorrect padding"

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

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

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

				return bytes(SCREAMING_SNAKE_CASE_      )


if __name__ == "__main__":
	import doctest

	doctest.testmod()

