





'''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,
	    BertTokenizerFast,
	    BlipImageProcessor,
	    GPTaTokenizer,
	    InstructBlipProcessor,
	    PreTrainedTokenizerFast,
	)




@require_vision
class  _A (					unittest.TestCase		):

		def 	lowercase__     (   self					:   Optional[int]			)					->    Dict:


					"""simple docstring"""

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

					__snake_case					:      List[str]							      =     BlipImageProcessor()
					__snake_case					:      Tuple							      =     GPTaTokenizer.from_pretrained("""hf-internal-testing/tiny-random-GPT2Model"""			)
					__snake_case					:      str							      =     BertTokenizerFast.from_pretrained("""hf-internal-testing/tiny-random-bert"""			)

					__snake_case					:      Dict							      =     InstructBlipProcessor(__magic_name__  ,      __magic_name__  ,      __magic_name__			)

					processor.save_pretrained(self.tmpdirname			)

		def 	lowercase__     (   self					:   List[Any]  ,      **__magic_name__					:   Tuple			)					->    Union[str, Any]:


					"""simple docstring"""

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

		def 	lowercase__     (   self					:   Optional[int]  ,      **__magic_name__					:   Optional[Any]			)					->    List[Any]:


					"""simple docstring"""

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

		def 	lowercase__     (   self					:   int  ,      **__magic_name__					:   Dict			)					->    Optional[int]:


					"""simple docstring"""

					return AutoProcessor.from_pretrained(self.tmpdirname  ,      **__magic_name__			).qformer_tokenizer

		def 	lowercase__     (   self					:   Any			)					->    Tuple:


					"""simple docstring"""

					shutil.rmtree(self.tmpdirname			)

		def 	lowercase__     (   self					:   List[str]			)					->    Tuple:


					"""simple docstring"""

					__snake_case					:      Any							      =     [np.random.randint(2_55  ,      size=(3, 30, 4_00)  ,      dtype=np.uinta			)]

					__snake_case					:      Union[str, Any]							      =     [Image.fromarray(np.moveaxis(__magic_name__  ,      0  ,      -1			)			) for x in image_inputs]

					return image_inputs

		def 	lowercase__     (   self					:   int			)					->    List[Any]:


					"""simple docstring"""

					__snake_case					:      List[Any]							      =     InstructBlipProcessor(
					    tokenizer=self.get_tokenizer()  ,      image_processor=self.get_image_processor()  ,      qformer_tokenizer=self.get_qformer_tokenizer()  ,      )
					processor.save_pretrained(self.tmpdirname			)

					__snake_case					:      List[Any]							      =     self.get_tokenizer(bos_token="""(BOS)"""  ,      eos_token="""(EOS)"""			)
					__snake_case					:      Optional[Any]							      =     self.get_image_processor(do_normalize=__magic_name__  ,      padding_value=1.0			)

					__snake_case					:      Optional[Any]							      =     InstructBlipProcessor.from_pretrained(
					    self.tmpdirname  ,      bos_token="""(BOS)"""  ,      eos_token="""(EOS)"""  ,      do_normalize=__magic_name__  ,      padding_value=1.0			)

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

					self.assertEqual(processor.image_processor.to_json_string()  ,      image_processor_add_kwargs.to_json_string()			)
					self.assertIsInstance(processor.image_processor  ,      __magic_name__			)
					self.assertIsInstance(processor.qformer_tokenizer  ,      __magic_name__			)

		def 	lowercase__     (   self					:   Union[str, Any]			)					->    int:


					"""simple docstring"""

					__snake_case					:      Optional[int]							      =     self.get_image_processor()
					__snake_case					:      str							      =     self.get_tokenizer()
					__snake_case					:      str							      =     self.get_qformer_tokenizer()

					__snake_case					:      List[str]							      =     InstructBlipProcessor(
					    tokenizer=__magic_name__  ,      image_processor=__magic_name__  ,      qformer_tokenizer=__magic_name__			)

					__snake_case					:      List[Any]							      =     self.prepare_image_inputs()

					__snake_case					:      Dict							      =     image_processor(__magic_name__  ,      return_tensors="""np"""			)
					__snake_case					:      Any							      =     processor(images=__magic_name__  ,      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 	lowercase__     (   self					:   Optional[int]			)					->    Optional[Any]:


					"""simple docstring"""

					__snake_case					:      List[str]							      =     self.get_image_processor()
					__snake_case					:      Tuple							      =     self.get_tokenizer()
					__snake_case					:      str							      =     self.get_qformer_tokenizer()

					__snake_case					:      str							      =     InstructBlipProcessor(
					    tokenizer=__magic_name__  ,      image_processor=__magic_name__  ,      qformer_tokenizer=__magic_name__			)

					__snake_case					:      List[Any]							      =     """lower newer"""

					__snake_case					:      List[str]							      =     processor(text=__magic_name__			)

					__snake_case					:      Union[str, Any]							      =     tokenizer(__magic_name__  ,      return_token_type_ids=__magic_name__			)
					__snake_case					:      Tuple							      =     qformer_tokenizer(__magic_name__  ,      return_token_type_ids=__magic_name__			)

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

					for key in encoded_tokens_qformer.keys():
								self.assertListEqual(encoded_tokens_qformer[key]  ,      encoded_processor["""qformer_""" + key]			)

		def 	lowercase__     (   self					:   List[str]			)					->    List[Any]:


					"""simple docstring"""

					__snake_case					:      Union[str, Any]							      =     self.get_image_processor()
					__snake_case					:      Union[str, Any]							      =     self.get_tokenizer()
					__snake_case					:      Optional[int]							      =     self.get_qformer_tokenizer()

					__snake_case					:      Tuple							      =     InstructBlipProcessor(
					    tokenizer=__magic_name__  ,      image_processor=__magic_name__  ,      qformer_tokenizer=__magic_name__			)

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

					__snake_case					:      int							      =     processor(text=__magic_name__  ,      images=__magic_name__			)

					self.assertListEqual(
					    list(inputs.keys()			)  ,      ["""input_ids""", """attention_mask""", """qformer_input_ids""", """qformer_attention_mask""", """pixel_values"""]  ,      )

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

		def 	lowercase__     (   self					:   Any			)					->    List[str]:


					"""simple docstring"""

					__snake_case					:      Union[str, Any]							      =     self.get_image_processor()
					__snake_case					:      Union[str, Any]							      =     self.get_tokenizer()
					__snake_case					:      Tuple							      =     self.get_qformer_tokenizer()

					__snake_case					:      Dict							      =     InstructBlipProcessor(
					    tokenizer=__magic_name__  ,      image_processor=__magic_name__  ,      qformer_tokenizer=__magic_name__			)

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

					__snake_case					:      int							      =     processor.batch_decode(__magic_name__			)
					__snake_case					:      str							      =     tokenizer.batch_decode(__magic_name__			)

					self.assertListEqual(__magic_name__  ,      __magic_name__			)

		def 	lowercase__     (   self					:   Union[str, Any]			)					->    str:


					"""simple docstring"""

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

					__snake_case					:      Dict							      =     InstructBlipProcessor(
					    tokenizer=__magic_name__  ,      image_processor=__magic_name__  ,      qformer_tokenizer=__magic_name__			)

					__snake_case					:      Optional[int]							      =     """lower newer"""
					__snake_case					:      List[Any]							      =     self.prepare_image_inputs()

					__snake_case					:      Optional[Any]							      =     processor(text=__magic_name__  ,      images=__magic_name__			)

					self.assertListEqual(
					    list(inputs.keys()			)  ,      ["""input_ids""", """attention_mask""", """qformer_input_ids""", """qformer_attention_mask""", """pixel_values"""]  ,      )









'''simple docstring'''






from __future__ import annotations

from typing import Any




class  _A :

		def __init__(   self					:   str  ,      __magic_name__					:   int  ,      __magic_name__					:   int  ,      __magic_name__					:   float = 0			)					->    None:


					"""simple docstring"""

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

		def __str__(   self					:   List[Any]			)					->    str:


					"""simple docstring"""

					__snake_case					:      Dict							      =     f'''Matrix consist of {self.row} rows and {self.column} columns\n'''

					# Make string identifier
					__snake_case					:      Optional[int]							      =     0
					for row_vector in self.array:
								for obj in row_vector:
											__snake_case					:      Optional[int]							      =     max(__magic_name__  ,      len(str(__magic_name__			)			)			)
					__snake_case					:      str							      =     f'''%{max_element_length}s'''

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

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

		def __repr__(   self					:   Optional[int]			)					->    str:


					"""simple docstring"""

					return str(self			)

		def 	lowercase__     (   self					:   Dict  ,      __magic_name__					:   tuple[int, int]			)					->    bool:


					"""simple docstring"""

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

		def __getitem__(   self					:   int  ,      __magic_name__					:   tuple[int, int]			)					->    Any:


					"""simple docstring"""

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

		def __setitem__(   self					:   List[str]  ,      __magic_name__					:   tuple[int, int]  ,      __magic_name__					:   float			)					->    None:


					"""simple docstring"""

					assert self.validate_indicies(__magic_name__			)
					__snake_case					:      Optional[int]							      =     value

		def __add__(   self					:   Any  ,      __magic_name__					:   Matrix			)					->    Matrix:


					"""simple docstring"""

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

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

		def __neg__(   self					:   Tuple			)					->    Matrix:


					"""simple docstring"""

					__snake_case					:      Tuple							      =     Matrix(self.row  ,      self.column			)
					for r in range(self.row			):
								for c in range(self.column			):
											__snake_case					:      List[Any]							      =     -self[r, c]
					return result

		def __sub__(   self					:   Optional[int]  ,      __magic_name__					:   Matrix			)					->    Matrix:


					"""simple docstring"""

					return self + (-another)

		def __mul__(   self					:   List[Any]  ,      __magic_name__					:   int | float | Matrix			)					->    Matrix:


					"""simple docstring"""

					if isinstance(__magic_name__  ,      (int, float)			):  # Scalar multiplication
								__snake_case					:      Optional[int]							      =     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(__magic_name__  ,      __magic_name__			):  # Matrix multiplication
								assert self.column == another.row
								__snake_case					:      Dict							      =     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					:      Optional[int]							      =     f'''Unsupported type given for another ({type(__magic_name__			)})'''
								raise TypeError(__magic_name__			)

		def 	lowercase__     (   self					:   str			)					->    Matrix:


					"""simple docstring"""

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

		def 	lowercase__     (   self					:   Union[str, Any]  ,      __magic_name__					:   Matrix  ,      __magic_name__					:   Matrix			)					->    Any:


					"""simple docstring"""

					assert isinstance(__magic_name__  ,      __magic_name__			) and isinstance(__magic_name__  ,      __magic_name__			)
					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					:      List[str]							      =     v.transpose()
					__snake_case					:      Tuple							      =     (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						(       ) ->				None:



				"""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					:      Dict							      =     Matrix(3    ,	1    ,	0 )
				__snake_case      ,     __snake_case      ,     __snake_case					:      Union[str, Any]							      =     1, 2, -3
				__snake_case					:      str							      =     Matrix(3    ,	1    ,	0 )
				__snake_case      ,     __snake_case      ,     __snake_case					:      Tuple							      =     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						(       ) ->				None:



				"""simple docstring"""


				import doctest

				doctest.testmod()

	testa()


