

"""simple docstring"""






import copy
import re
class        _lowercase					:
     _lowerCamelCase     =       '''hp'''
     _lowerCamelCase     =       {}
     _lowerCamelCase     =       None







     @classmethod
     def 	lowerCAmelCase__    (      cls ,						UpperCamelCase_ ,						UpperCamelCase_       ):
      __magic_name__     =      prefix
      __magic_name__     =      defaults
      cls.build_naming_info()







     @staticmethod
     def 	lowerCAmelCase__    (      UpperCamelCase_ ,						UpperCamelCase_       ):
      if len(UpperCamelCase_       ) == 0:
       return ""
      __magic_name__     =      None
      if any(char.isdigit() for char in word       ):
       raise Exception(f'''Parameters should not contain numbers: \'{word}\' contains a number'''       )
      if word in info["short_word"]:
       return info["short_word"][word]
      for prefix_len in range(1 ,						len(UpperCamelCase_       ) + 1       ):
       __magic_name__     =      word[:prefix_len]
       if prefix in info["reverse_short_word"]:
        continue
       else:
        __magic_name__     =      prefix
        break

      if short_word is None:
       # Paranoid fallback
       def int_to_alphabetic(UpperCamelCase_       ):
        __magic_name__     =      ''''''
        while integer != 0:
         __magic_name__     =      chr(ord('''A'''       ) + integer % 10       ) + s
         integer //= 10
        return s

       __magic_name__     =      0
       while True:
        __magic_name__     =      word + '''#''' + int_to_alphabetic(UpperCamelCase_       )
        if sword in info["reverse_short_word"]:
         continue
        else:
         __magic_name__     =      sword
         break

      __magic_name__     =      short_word
      __magic_name__     =      word
      return short_word







     @staticmethod
     def 	lowerCAmelCase__    (      UpperCamelCase_ ,						UpperCamelCase_       ):
      __magic_name__     =      param_name.split('''_'''       )

      __magic_name__     =      [TrialShortNamer.shortname_for_word(UpperCamelCase_ ,						UpperCamelCase_       ) for word in words]

      # We try to create a separatorless short name, but if there is a collision we have to fallback
      # to a separated short name
      __magic_name__     =      ['''''', '''_''']

      for separator in separators:
       __magic_name__     =      separator.join(UpperCamelCase_       )
       if shortname not in info["reverse_short_param"]:
        __magic_name__     =      shortname
        __magic_name__     =      param_name
        return shortname

      return param_name







     @staticmethod
     def 	lowerCAmelCase__    (      UpperCamelCase_ ,						UpperCamelCase_       ):
      __magic_name__     =      TrialShortNamer.shortname_for_key(UpperCamelCase_ ,						UpperCamelCase_       )
      __magic_name__     =      short_name
      __magic_name__     =      param_name







     @classmethod
     def 	lowerCAmelCase__    (      cls       ):
      if cls.NAMING_INFO is not None:
       return

      __magic_name__     =      {
          '''short_word''': {},
          '''reverse_short_word''': {},
          '''short_param''': {},
          '''reverse_short_param''': {},
      }

      __magic_name__     =      list(cls.DEFAULTS.keys()       )

      for k in field_keys:
       cls.add_new_param_name(UpperCamelCase_ ,						UpperCamelCase_       )

      __magic_name__     =      info







     @classmethod
     def 	lowerCAmelCase__    (      cls ,						UpperCamelCase_       ):
      cls.build_naming_info()
      assert cls.PREFIX is not None
      __magic_name__     =      [copy.copy(cls.PREFIX       )]

      for k, v in params.items():
       if k not in cls.DEFAULTS:
        raise Exception(f'''You should provide a default value for the param name {k} with value {v}'''       )
       if v == cls.DEFAULTS[k]:
        # The default value is not added to the name
        continue

       __magic_name__     =      cls.NAMING_INFO['''short_param'''][k]

       if isinstance(UpperCamelCase_ ,						UpperCamelCase_       ):
        __magic_name__     =      1 if v else 0

       __magic_name__     =      '''''' if isinstance(UpperCamelCase_ ,						(int, float)       ) else '''-'''
       __magic_name__     =      f'''{key}{sep}{v}'''
       name.append(UpperCamelCase_       )

      return "_".join(UpperCamelCase_       )







     @classmethod
     def 	lowerCAmelCase__    (      cls ,						UpperCamelCase_       ):
      __magic_name__     =      repr[len(cls.PREFIX       ) + 1 :]
      if repr == "":
       __magic_name__     =      []
      else:
       __magic_name__     =      repr.split('''_'''       )

      __magic_name__     =      {}

      for value in values:
       if "-" in value:
        __magic_name__   ,						__magic_name__     =      value.split('''-'''       )
       else:
        __magic_name__     =      re.sub('''[0-9.]''' ,						'''''' ,						UpperCamelCase_       )
        __magic_name__     =      float(re.sub('''[^0-9.]''' ,						'''''' ,						UpperCamelCase_       )       )

       __magic_name__     =      cls.NAMING_INFO['''reverse_short_param'''][p_k]

       __magic_name__     =      p_v

      for k in cls.DEFAULTS:
       if k not in parameters:
        __magic_name__     =      cls.DEFAULTS[k]

      return parameters




"""simple docstring"""






import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
 from PIL import Image

 from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor
@require_tokenizers
@require_vision
class        _lowercase					(     unittest.TestCase     ):







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      tempfile.mkdtemp()

      # fmt: off
      __magic_name__     =      ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
      # fmt: on
      __magic_name__     =      os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''vocab_file''']       )
      with open(self.vocab_file ,						'''w''' ,						encoding='''utf-8'''       ) as vocab_writer:
       vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]       )       )

      __magic_name__     =      {
          '''do_resize''': True,
          '''size''': {'''height''': 18, '''width''': 18},
          '''do_normalize''': True,
          '''image_mean''': [0.5, 0.5, 0.5],
          '''image_std''': [0.5, 0.5, 0.5],
      }
      __magic_name__     =      os.path.join(self.tmpdirname ,						UpperCamelCase_       )
      with open(self.image_processor_file ,						'''w''' ,						encoding='''utf-8'''       ) as fp:
       json.dump(UpperCamelCase_ ,						UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						**UpperCamelCase_       ):
      return BertTokenizer.from_pretrained(self.tmpdirname ,						**UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						**UpperCamelCase_       ):
      return ViTImageProcessor.from_pretrained(self.tmpdirname ,						**UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self       ):
      shutil.rmtree(self.tmpdirname       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      [np.random.randint(255 ,						size=(3, 30, 400) ,						dtype=np.uinta       )]

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

      return image_inputs







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_tokenizer()
      __magic_name__     =      self.get_image_processor()

      __magic_name__     =      VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      processor.save_pretrained(self.tmpdirname       )
      __magic_name__     =      VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname       )

      self.assertEqual(processor.tokenizer.get_vocab() ,						tokenizer.get_vocab()       )
      self.assertIsInstance(processor.tokenizer ,						(BertTokenizer, BertTokenizerFast)       )

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      VisionTextDualEncoderProcessor(
          tokenizer=self.get_tokenizer() ,						image_processor=self.get_image_processor()       )
      processor.save_pretrained(self.tmpdirname       )

      __magic_name__     =      self.get_tokenizer(bos_token='''(BOS)''' ,						eos_token='''(EOS)'''       )
      __magic_name__     =      self.get_image_processor(do_normalize=UpperCamelCase_ ,						padding_value=1.0       )

      __magic_name__     =      VisionTextDualEncoderProcessor.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 ,						(BertTokenizer, BertTokenizerFast)       )

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      self.prepare_image_inputs()

      __magic_name__     =      image_processor(UpperCamelCase_ ,						return_tensors='''np'''       )
      __magic_name__     =      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       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      '''lower newer'''

      __magic_name__     =      processor(text=UpperCamelCase_       )

      __magic_name__     =      tokenizer(UpperCamelCase_       )

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      '''lower newer'''
      __magic_name__     =      self.prepare_image_inputs()

      __magic_name__     =      processor(text=UpperCamelCase_ ,						images=UpperCamelCase_       )

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

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

      __magic_name__     =      processor.batch_decode(UpperCamelCase_       )
      __magic_name__     =      tokenizer.batch_decode(UpperCamelCase_       )

      self.assertListEqual(UpperCamelCase_ ,						UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      '''lower newer'''
      __magic_name__     =      self.prepare_image_inputs()

      __magic_name__     =      processor(text=UpperCamelCase_ ,						images=UpperCamelCase_       )

      self.assertListEqual(list(inputs.keys()       ) ,						processor.model_input_names       )

