

"""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, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast







@require_vision
class        __lowercase     (      unittest.TestCase   ):

  def 				__lowercase    (					self						:     Optional[int]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					Dict   				=   tempfile.mkdtemp()

   UpperCAmelCase__   :					Dict   				=   CLIPImageProcessor()
   UpperCAmelCase__   :					List[str]   				=   BertTokenizer.from_pretrained(
       """hf-internal-testing/tiny-random-BertModel"""   ,model_input_names=["""input_ids""", """attention_mask"""]      )

   UpperCAmelCase__   :					Any   				=   GitProcessor(A   ,A      )

   processor.save_pretrained(self.tmpdirname      )

  def 				__lowercase    (					self						:     Union[str, Any]   ,**A						:     str      ):






   '''simple docstring'''
   return AutoProcessor.from_pretrained(self.tmpdirname   ,**A      ).tokenizer

  def 				__lowercase    (					self						:     Optional[Any]   ,**A						:     Tuple      ):






   '''simple docstring'''
   return AutoProcessor.from_pretrained(self.tmpdirname   ,**A      ).image_processor

  def 				__lowercase    (					self						:     str      ):






   '''simple docstring'''
   shutil.rmtree(self.tmpdirname      )

  def 				__lowercase    (					self						:     Optional[Any]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					Optional[Any]   				=   [np.random.randint(255   ,size=(3, 30, 400)   ,dtype=np.uinta      )]

   UpperCAmelCase__   :					Any   				=   [Image.fromarray(np.moveaxis(A   ,0   ,-1      )      ) for x in image_inputs]

   return image_inputs

  def 				__lowercase    (					self						:     str      ):






   '''simple docstring'''
   UpperCAmelCase__   :					int   				=   GitProcessor(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__   :					List[str]   				=   self.get_image_processor(do_normalize=A   ,padding_value=1.0      )

   UpperCAmelCase__   :					Any   				=   GitProcessor.from_pretrained(
       self.tmpdirname   ,bos_token="""(BOS)"""   ,eos_token="""(EOS)"""   ,do_normalize=A   ,padding_value=1.0      )

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

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

  def 				__lowercase    (					self						:     List[str]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					Union[str, Any]   				=   self.get_image_processor()
   UpperCAmelCase__   :					Union[str, Any]   				=   self.get_tokenizer()

   UpperCAmelCase__   :					Any   				=   GitProcessor(tokenizer=A   ,image_processor=A      )

   UpperCAmelCase__   :					str   				=   self.prepare_image_inputs()

   UpperCAmelCase__   :					Tuple   				=   image_processor(A   ,return_tensors="""np"""      )
   UpperCAmelCase__   :					Optional[int]   				=   processor(images=A   ,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						:     Union[str, Any]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					str   				=   self.get_image_processor()
   UpperCAmelCase__   :					Optional[Any]   				=   self.get_tokenizer()

   UpperCAmelCase__   :					int   				=   GitProcessor(tokenizer=A   ,image_processor=A      )

   UpperCAmelCase__   :					Union[str, Any]   				=   """lower newer"""

   UpperCAmelCase__   :					Any   				=   processor(text=A      )

   UpperCAmelCase__   :					str   				=   tokenizer(A   ,return_token_type_ids=A      )

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

  def 				__lowercase    (					self						:     List[str]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					int   				=   self.get_image_processor()
   UpperCAmelCase__   :					Optional[int]   				=   self.get_tokenizer()

   UpperCAmelCase__   :					List[str]   				=   GitProcessor(tokenizer=A   ,image_processor=A      )

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

   UpperCAmelCase__   :					Any   				=   processor(text=A   ,images=A      )

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

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

  def 				__lowercase    (					self						:     List[Any]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					str   				=   self.get_image_processor()
   UpperCAmelCase__   :					List[Any]   				=   self.get_tokenizer()

   UpperCAmelCase__   :					List[Any]   				=   GitProcessor(tokenizer=A   ,image_processor=A      )

   UpperCAmelCase__   :					Tuple   				=   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

   UpperCAmelCase__   :					List[Any]   				=   processor.batch_decode(A      )
   UpperCAmelCase__   :					Optional[Any]   				=   tokenizer.batch_decode(A      )

   self.assertListEqual(A   ,A      )




  def 				__lowercase    (					self						:     Optional[Any]      ):






   '''simple docstring'''
   UpperCAmelCase__   :					List[str]   				=   self.get_image_processor()
   UpperCAmelCase__   :					str   				=   self.get_tokenizer()

   UpperCAmelCase__   :					Union[str, Any]   				=   GitProcessor(tokenizer=A   ,image_processor=A      )

   UpperCAmelCase__   :					Dict   				=   """lower newer"""
   UpperCAmelCase__   :					Dict   				=   self.prepare_image_inputs()

   UpperCAmelCase__   :					List[str]   				=   processor(text=A   ,images=A      )

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








"""simple docstring"""




from __future__ import annotations
def 					lowerCAmelCase  (   __UpperCamelCase							,      __UpperCamelCase							,      __UpperCamelCase							,      __UpperCamelCase ):
 '''simple docstring'''





 UpperCAmelCase__				, UpperCAmelCase__   :					Optional[Any]   				=   m - 1, 0
 while i >= 0 and j < n:
  if key == mat[i][j]:
   print(F"Key {key} found at row- {i + 1} column- {j + 1}" )
   return
  if key < mat[i][j]:
   i -= 1
  else:
   j += 1
 print(F"Key {key} not found" )
def 					lowerCAmelCase  (   ):
 '''simple docstring'''





 UpperCAmelCase__   :					Union[str, Any]   				=   [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
 UpperCAmelCase__   :					int   				=   int(input("""Enter the element to be searched:""" ) )
 print(__UpperCamelCase )
 search_in_a_sorted_matrix(__UpperCamelCase							,      len(__UpperCamelCase )							,      len(mat[0] )							,      __UpperCamelCase )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()





