

'''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, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast




@require_vision
class     a			(				unittest.TestCase       ):






						"""simple docstring"""




						def       __magic_name__							(							self					:      Tuple  ):



								'''simple docstring'''



								snake_case__						:       int       						=  tempfile.mkdtemp()

								snake_case__						:       Dict       						=  BlipImageProcessor()
								snake_case__						:       int       						=  BertTokenizer.from_pretrained('''hf-internal-testing/tiny-random-BertModel'''  )

								snake_case__						:       Tuple       						=  BlipProcessor(snake_case_			,			snake_case_  )

								processor.save_pretrained(self.tmpdirname  )







						def       __magic_name__							(							self					:      Union[str, Any]			,			**snake_case_					:      List[Any]  ):



								'''simple docstring'''



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







						def       __magic_name__							(							self					:      int			,			**snake_case_					:      Optional[Any]  ):



								'''simple docstring'''



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







						def       __magic_name__							(							self					:      Optional[Any]  ):



								'''simple docstring'''



								shutil.rmtree(self.tmpdirname  )







						def       __magic_name__							(							self					:      str  ):



								'''simple docstring'''



								snake_case__						:       Union[str, Any]       						=  [np.random.randint(2_5_5			,			size=(3, 3_0, 4_0_0)			,			dtype=np.uinta  )]

								snake_case__						:       int       						=  [Image.fromarray(np.moveaxis(snake_case_			,			0			,			-1  )  ) for x in image_inputs]

								return image_inputs







						def       __magic_name__							(							self					:      int  ):



								'''simple docstring'''



								snake_case__						:       Union[str, Any]       						=  BlipProcessor(tokenizer=self.get_tokenizer()			,			image_processor=self.get_image_processor()  )
								processor.save_pretrained(self.tmpdirname  )

								snake_case__						:       Optional[int]       						=  self.get_tokenizer(bos_token='''(BOS)'''			,			eos_token='''(EOS)'''  )
								snake_case__						:       str       						=  self.get_image_processor(do_normalize=snake_case_			,			padding_value=1.0  )

								snake_case__						:       Dict       						=  BlipProcessor.from_pretrained(
								    self.tmpdirname			,			bos_token='''(BOS)'''			,			eos_token='''(EOS)'''			,			do_normalize=snake_case_			,			padding_value=1.0  )

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

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







						def       __magic_name__							(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       Dict       						=  self.get_image_processor()
								snake_case__						:       Optional[Any]       						=  self.get_tokenizer()

								snake_case__						:       Dict       						=  BlipProcessor(tokenizer=snake_case_			,			image_processor=snake_case_  )

								snake_case__						:       int       						=  self.prepare_image_inputs()

								snake_case__						:       Optional[int]       						=  image_processor(snake_case_			,			return_tensors='''np'''  )
								snake_case__						:       int       						=  processor(images=snake_case_			,			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       __magic_name__							(							self					:      Tuple  ):



								'''simple docstring'''



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

								snake_case__						:       Union[str, Any]       						=  BlipProcessor(tokenizer=snake_case_			,			image_processor=snake_case_  )

								snake_case__						:       Tuple       						=  '''lower newer'''

								snake_case__						:       Union[str, Any]       						=  processor(text=snake_case_  )

								snake_case__						:       str       						=  tokenizer(snake_case_			,			return_token_type_ids=snake_case_  )

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







						def       __magic_name__							(							self					:      Any  ):



								'''simple docstring'''



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

								snake_case__						:       str       						=  BlipProcessor(tokenizer=snake_case_			,			image_processor=snake_case_  )

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

								snake_case__						:       Union[str, Any]       						=  processor(text=snake_case_			,			images=snake_case_  )

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

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







						def       __magic_name__							(							self					:      Any  ):



								'''simple docstring'''



								snake_case__						:       List[str]       						=  self.get_image_processor()
								snake_case__						:       Optional[int]       						=  self.get_tokenizer()

								snake_case__						:       Tuple       						=  BlipProcessor(tokenizer=snake_case_			,			image_processor=snake_case_  )

								snake_case__						:       Optional[Any]       						=  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

								snake_case__						:       Optional[Any]       						=  processor.batch_decode(snake_case_  )
								snake_case__						:       List[str]       						=  tokenizer.batch_decode(snake_case_  )

								self.assertListEqual(snake_case_			,			snake_case_  )







						def       __magic_name__							(							self					:      Optional[Any]  ):



								'''simple docstring'''



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

								snake_case__						:       Union[str, Any]       						=  BlipProcessor(tokenizer=snake_case_			,			image_processor=snake_case_  )

								snake_case__						:       List[Any]       						=  '''lower newer'''
								snake_case__						:       Union[str, Any]       						=  self.prepare_image_inputs()

								snake_case__						:       Union[str, Any]       						=  processor(text=snake_case_			,			images=snake_case_  )

								# 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 typing import Any




class     a			:






						"""simple docstring"""




						def __init__(							self					:      Tuple			,			snake_case_					:      int			,			snake_case_					:      int			,			snake_case_					:      float = 0  ):



								'''simple docstring'''



								snake_case__						,       snake_case__						:       Optional[Any]       						=  row, column
								snake_case__						:       Dict       						=  [[default_value for c in range(snake_case_  )] for r in range(snake_case_  )]







						def __str__(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       Optional[int]       						=  F"""Matrix consist of {self.row} rows and {self.column} columns\n"""

								# Make string identifier
								snake_case__						:       List[str]       						=  0
								for row_vector in self.array:
										for obj in row_vector:
												snake_case__						:       str       						=  max(snake_case_			,			len(str(snake_case_  )  )  )
								snake_case__						:       Dict       						=  F"""%{max_element_length}s"""

								# Make string and return
								def single_line(snake_case_					:      list[float]  ) -> str:
										nonlocal string_format_identifier
										snake_case__						:       str       						=  '''['''
										line += ", ".join(string_format_identifier % (obj,) for obj in row_vector  )
										line += "]"
										return line

								s += "\n".join(single_line(snake_case_  ) for row_vector in self.array  )
								return s







						def __repr__(							self					:      Optional[int]  ):



								'''simple docstring'''



								return str(self  )







						def       __magic_name__							(							self					:      Optional[int]			,			snake_case_					:      tuple[int, int]  ):



								'''simple docstring'''



								if not (isinstance(snake_case_			,			(list, tuple)  ) and len(snake_case_  ) == 2):
										return False
								elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
										return False
								else:
										return True







						def __getitem__(							self					:      List[str]			,			snake_case_					:      tuple[int, int]  ):



								'''simple docstring'''



								assert self.validate_indicies(snake_case_  )
								return self.array[loc[0]][loc[1]]







						def __setitem__(							self					:      int			,			snake_case_					:      tuple[int, int]			,			snake_case_					:      float  ):



								'''simple docstring'''



								assert self.validate_indicies(snake_case_  )
								snake_case__						:       Optional[Any]       						=  value







						def __add__(							self					:      Dict			,			snake_case_					:      Matrix  ):



								'''simple docstring'''



								assert isinstance(snake_case_			,			snake_case_  )
								assert self.row == another.row and self.column == another.column

								# Add
								snake_case__						:       str       						=  Matrix(self.row			,			self.column  )
								for r in range(self.row  ):
										for c in range(self.column  ):
												snake_case__						:       Optional[Any]       						=  self[r, c] + another[r, c]
								return result







						def __neg__(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       int       						=  Matrix(self.row			,			self.column  )
								for r in range(self.row  ):
										for c in range(self.column  ):
												snake_case__						:       str       						=  -self[r, c]
								return result







						def __sub__(							self					:      Optional[int]			,			snake_case_					:      Matrix  ):



								'''simple docstring'''



								return self + (-another)







						def __mul__(							self					:      int			,			snake_case_					:      int | float | Matrix  ):



								'''simple docstring'''



								if isinstance(snake_case_			,			(int, float)  ):  # Scalar multiplication
										snake_case__						:       Dict       						=  Matrix(self.row			,			self.column  )
										for r in range(self.row  ):
												for c in range(self.column  ):
														snake_case__						:       Tuple       						=  self[r, c] * another
										return result
								elif isinstance(snake_case_			,			snake_case_  ):  # Matrix multiplication
										assert self.column == another.row
										snake_case__						:       List[Any]       						=  Matrix(self.row			,			another.column  )
										for r in range(self.row  ):
												for c in range(another.column  ):
														for i in range(self.column  ):
																result[r, c] += self[r, i] * another[i, c]
										return result
								else:
										snake_case__						:       Union[str, Any]       						=  F"""Unsupported type given for another ({type(snake_case_  )})"""
										raise TypeError(snake_case_  )







						def       __magic_name__							(							self					:      List[str]  ):



								'''simple docstring'''



								snake_case__						:       Optional[int]       						=  Matrix(self.column			,			self.row  )
								for r in range(self.row  ):
										for c in range(self.column  ):
												snake_case__						:       List[Any]       						=  self[r, c]
								return result







						def       __magic_name__							(							self					:      Tuple			,			snake_case_					:      Matrix			,			snake_case_					:      Matrix  ):



								'''simple docstring'''



								assert isinstance(snake_case_			,			snake_case_  ) and isinstance(snake_case_			,			snake_case_  )
								assert self.row == self.column == u.row == v.row  # u, v should be column vector
								assert u.column == v.column == 1  # u, v should be column vector

								# Calculate
								snake_case__						:       Tuple       						=  v.transpose()
								snake_case__						:       Optional[Any]       						=  (v_t * self * u)[0, 0] + 1
								if numerator_factor == 0:
										return None  # It's not invertable
								return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":




					def 	_a       (				):

							"""simple docstring"""

							snake_case__						:       Tuple       						=  Matrix(3   ,							3   ,							0     )
							for i in range(3     ):
									snake_case__						:       Any       						=  1
							print(F"""a^(-1) is {ainv}"""     )
							# u, v
							snake_case__						:       int       						=  Matrix(3   ,							1   ,							0     )
							snake_case__						,       snake_case__						,       snake_case__						:       List[Any]       						=  1, 2, -3
							snake_case__						:       Any       						=  Matrix(3   ,							1   ,							0     )
							snake_case__						,       snake_case__						,       snake_case__						:       Optional[int]       						=  4, -2, 5
							print(F"""u is {u}"""     )
							print(F"""v is {v}"""     )
							print(F"""uv^T is {u * v.transpose()}"""     )
							# Sherman Morrison
							print(F"""(a + uv^T)^(-1) is {ainv.sherman_morrison(__lowerCAmelCase   ,							__lowerCAmelCase     )}"""     )




					def 	_a       (				):

							"""simple docstring"""

							import doctest

							doctest.testmod()





					testa()



