


'''simple docstring'''
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
		from PIL import Image

		from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast
@require_vision
class   lowercase      (				unittest.TestCase   ):

		"""simple docstring"""

		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :List[str]				   =					tempfile.mkdtemp()

							UpperCamelCase__  :Union[str, Any]				   =					BlipImageProcessor()
							UpperCamelCase__  :Union[str, Any]				   =					GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''				)

							UpperCamelCase__  :Any				   =					BlipaProcessor(UpperCamelCase_       ,  UpperCamelCase_				)

							processor.save_pretrained(self.tmpdirname				)




		def        lowerCAmelCase__							(						self       ,  **UpperCamelCase_				):

							'''simple docstring'''


							return AutoProcessor.from_pretrained(self.tmpdirname       ,  **UpperCamelCase_				).tokenizer




		def        lowerCAmelCase__							(						self       ,  **UpperCamelCase_				):

							'''simple docstring'''


							return AutoProcessor.from_pretrained(self.tmpdirname       ,  **UpperCamelCase_				).image_processor




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							shutil.rmtree(self.tmpdirname				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :Tuple				   =					[np.random.randint(255       ,  size=(3, 30, 400)       ,  dtype=np.uinta				)]

							UpperCamelCase__  :Tuple				   =					[Image.fromarray(np.moveaxis(UpperCamelCase_       ,  0       ,  -1				)				) for x in image_inputs]

							return image_inputs




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :str				   =					BlipaProcessor(tokenizer=self.get_tokenizer()       ,  image_processor=self.get_image_processor()				)
							processor.save_pretrained(self.tmpdirname				)

							UpperCamelCase__  :List[Any]				   =					self.get_tokenizer(bos_token='''(BOS)'''       ,  eos_token='''(EOS)'''				)
							UpperCamelCase__  :Dict				   =					self.get_image_processor(do_normalize=UpperCamelCase_       ,  padding_value=1.0				)

							UpperCamelCase__  :str				   =					BlipaProcessor.from_pretrained(
							    self.tmpdirname       ,  bos_token='''(BOS)'''       ,  eos_token='''(EOS)'''       ,  do_normalize=UpperCamelCase_       ,  padding_value=1.0				)

							self.assertEqual(processor.tokenizer.get_vocab()       ,  tokenizer_add_kwargs.get_vocab()				)
							self.assertIsInstance(processor.tokenizer       ,  UpperCamelCase_				)

							self.assertEqual(processor.image_processor.to_json_string()       ,  image_processor_add_kwargs.to_json_string()				)
							self.assertIsInstance(processor.image_processor       ,  UpperCamelCase_				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :Any				   =					self.get_image_processor()
							UpperCamelCase__  :Optional[int]				   =					self.get_tokenizer()

							UpperCamelCase__  :List[Any]				   =					BlipaProcessor(tokenizer=UpperCamelCase_       ,  image_processor=UpperCamelCase_				)

							UpperCamelCase__  :List[str]				   =					self.prepare_image_inputs()

							UpperCamelCase__  :Optional[int]				   =					image_processor(UpperCamelCase_       ,  return_tensors='''np'''				)
							UpperCamelCase__  :Union[str, Any]				   =					processor(images=UpperCamelCase_       ,  return_tensors='''np'''				)

							for key in input_feat_extract.keys():
												self.assertAlmostEqual(input_feat_extract[key].sum()       ,  input_processor[key].sum()       ,  delta=1e-2				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :int				   =					self.get_image_processor()
							UpperCamelCase__  :List[Any]				   =					self.get_tokenizer()

							UpperCamelCase__  :Optional[int]				   =					BlipaProcessor(tokenizer=UpperCamelCase_       ,  image_processor=UpperCamelCase_				)

							UpperCamelCase__  :Union[str, Any]				   =					'''lower newer'''

							UpperCamelCase__  :List[str]				   =					processor(text=UpperCamelCase_				)

							UpperCamelCase__  :Optional[Any]				   =					tokenizer(UpperCamelCase_       ,  return_token_type_ids=UpperCamelCase_				)

							for key in encoded_tok.keys():
												self.assertListEqual(encoded_tok[key]       ,  encoded_processor[key]				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :str				   =					self.get_image_processor()
							UpperCamelCase__  :Union[str, Any]				   =					self.get_tokenizer()

							UpperCamelCase__  :Optional[Any]				   =					BlipaProcessor(tokenizer=UpperCamelCase_       ,  image_processor=UpperCamelCase_				)

							UpperCamelCase__  :int				   =					'''lower newer'''
							UpperCamelCase__  :Optional[Any]				   =					self.prepare_image_inputs()

							UpperCamelCase__  :str				   =					processor(text=UpperCamelCase_       ,  images=UpperCamelCase_				)

							self.assertListEqual(list(inputs.keys()				)       ,  ['''pixel_values''', '''input_ids''', '''attention_mask''']				)

							# test if it raises when no input is passed
							with pytest.raises(UpperCamelCase_				):
												processor()




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :List[Any]				   =					self.get_image_processor()
							UpperCamelCase__  :List[str]				   =					self.get_tokenizer()

							UpperCamelCase__  :str				   =					BlipaProcessor(tokenizer=UpperCamelCase_       ,  image_processor=UpperCamelCase_				)

							UpperCamelCase__  :int				   =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							UpperCamelCase__  :int				   =					processor.batch_decode(UpperCamelCase_				)
							UpperCamelCase__  :List[Any]				   =					tokenizer.batch_decode(UpperCamelCase_				)

							self.assertListEqual(UpperCamelCase_       ,  UpperCamelCase_				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :str				   =					self.get_image_processor()
							UpperCamelCase__  :Tuple				   =					self.get_tokenizer()

							UpperCamelCase__  :List[str]				   =					BlipaProcessor(tokenizer=UpperCamelCase_       ,  image_processor=UpperCamelCase_				)

							UpperCamelCase__  :Optional[int]				   =					'''lower newer'''
							UpperCamelCase__  :Any				   =					self.prepare_image_inputs()

							UpperCamelCase__  :str				   =					processor(text=UpperCamelCase_       ,  images=UpperCamelCase_				)

							# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
							self.assertListEqual(list(inputs.keys()				)       ,  ['''pixel_values''', '''input_ids''', '''attention_mask''']				)



'''simple docstring'''
from __future__ import annotations

from decimal import Decimal

from numpy import array


def      a (     __a  )    ->      list[list[float]]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(__a  ) == 2 and len(matrix[0]  ) == 2 and len(matrix[1]  ) == 2:
										# Calculate the determinant of the matrix
										UpperCamelCase__  :str				   =					float(
										    d(matrix[0][0]  ) * d(matrix[1][1]  ) - d(matrix[1][0]  ) * d(matrix[0][1]  )  )
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''  )

										# Creates a copy of the matrix with swapped positions of the elements
										UpperCamelCase__  :List[Any]				   =					[[0.0, 0.0], [0.0, 0.0]]
										UpperCamelCase__   ,							UpperCamelCase__  :Union[str, Any]				   =					matrix[1][1], matrix[0][0]
										UpperCamelCase__   ,							UpperCamelCase__  :Dict				   =					-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(__a  )  ) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(__a  ) == 3
					    and len(matrix[0]  ) == 3
					    and len(matrix[1]  ) == 3
					    and len(matrix[2]  ) == 3
					):
										# Calculate the determinant of the matrix using Sarrus rule
										UpperCamelCase__  :int				   =					float(
										    (
										        (d(matrix[0][0]  ) * d(matrix[1][1]  ) * d(matrix[2][2]  ))
										        + (d(matrix[0][1]  ) * d(matrix[1][2]  ) * d(matrix[2][0]  ))
										        + (d(matrix[0][2]  ) * d(matrix[1][0]  ) * d(matrix[2][1]  ))
										    )
										    - (
										        (d(matrix[0][2]  ) * d(matrix[1][1]  ) * d(matrix[2][0]  ))
										        + (d(matrix[0][1]  ) * d(matrix[1][0]  ) * d(matrix[2][2]  ))
										        + (d(matrix[0][0]  ) * d(matrix[1][2]  ) * d(matrix[2][1]  ))
										    )  )
										if determinant == 0:
															raise ValueError('''This matrix has no inverse.'''  )

										# Creating cofactor matrix
										UpperCamelCase__  :List[Any]				   =					[
										    [d(0.0  ), d(0.0  ), d(0.0  )],
										    [d(0.0  ), d(0.0  ), d(0.0  )],
										    [d(0.0  ), d(0.0  ), d(0.0  )],
										]
										UpperCamelCase__  :Tuple				   =					(d(matrix[1][1]  ) * d(matrix[2][2]  )) - (
										    d(matrix[1][2]  ) * d(matrix[2][1]  )
										)
										UpperCamelCase__  :List[str]				   =					-(
										    (d(matrix[1][0]  ) * d(matrix[2][2]  )) - (d(matrix[1][2]  ) * d(matrix[2][0]  ))
										)
										UpperCamelCase__  :Union[str, Any]				   =					(d(matrix[1][0]  ) * d(matrix[2][1]  )) - (
										    d(matrix[1][1]  ) * d(matrix[2][0]  )
										)
										UpperCamelCase__  :List[Any]				   =					-(
										    (d(matrix[0][1]  ) * d(matrix[2][2]  )) - (d(matrix[0][2]  ) * d(matrix[2][1]  ))
										)
										UpperCamelCase__  :Optional[int]				   =					(d(matrix[0][0]  ) * d(matrix[2][2]  )) - (
										    d(matrix[0][2]  ) * d(matrix[2][0]  )
										)
										UpperCamelCase__  :List[Any]				   =					-(
										    (d(matrix[0][0]  ) * d(matrix[2][1]  )) - (d(matrix[0][1]  ) * d(matrix[2][0]  ))
										)
										UpperCamelCase__  :List[Any]				   =					(d(matrix[0][1]  ) * d(matrix[1][2]  )) - (
										    d(matrix[0][2]  ) * d(matrix[1][1]  )
										)
										UpperCamelCase__  :List[str]				   =					-(
										    (d(matrix[0][0]  ) * d(matrix[1][2]  )) - (d(matrix[0][2]  ) * d(matrix[1][0]  ))
										)
										UpperCamelCase__  :Dict				   =					(d(matrix[0][0]  ) * d(matrix[1][1]  )) - (
										    d(matrix[0][1]  ) * d(matrix[1][0]  )
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										UpperCamelCase__  :Optional[Any]				   =					array(__a  )
										for i in range(3  ):
															for j in range(3  ):
																				UpperCamelCase__  :Optional[Any]				   =					cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
										UpperCamelCase__  :Any				   =					array(__a  )
										for i in range(3  ):
															for j in range(3  ):
																				inverse_matrix[i][j] /= d(__a  )

        # Calculate the inverse of the matrix
										return [[float(d(__a  )  ) or 0.0 for n in row] for row in inverse_matrix]
					raise ValueError('''Please provide a matrix of size 2x2 or 3x3.'''  )