
'''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    lowerCAmelCase       (     unittest.TestCase  ):


 def    _A	(    self  : Optional[Any]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Any     		=	tempfile.mkdtemp()

  # fmt: off
  lowerCAmelCase__     :   List[str]     		=	["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest"]
  # fmt: on
  lowerCAmelCase__     :   Any     		=	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]    )    )

  lowerCAmelCase__     :   Optional[int]     		=	{
      "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],
  }
  lowerCAmelCase__     :   str     		=	os.path.join(self.tmpdirname			,							a__    )
  with open(self.image_processor_file			,							"w"			,							encoding="utf-8"    ) as fp:
   json.dump(a__			,							a__    )


 def    _A	(    self  : int			,							**a__  : Optional[Any]    ):
  '''simple docstring'''

  return BertTokenizer.from_pretrained(self.tmpdirname			,							**a__    )


 def    _A	(    self  : Union[str, Any]			,							**a__  : Optional[Any]    ):
  '''simple docstring'''

  return ViTImageProcessor.from_pretrained(self.tmpdirname			,							**a__    )


 def    _A	(    self  : Optional[Any]    ):
  '''simple docstring'''

  shutil.rmtree(self.tmpdirname    )


 def    _A	(    self  : int    ):
  '''simple docstring'''

  lowerCAmelCase__     :   List[str]     		=	[np.random.randint(255			,							size=(3, 30, 400)			,							dtype=np.uinta    )]

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

  return image_inputs


 def    _A	(    self  : List[str]    ):
  '''simple docstring'''

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

  lowerCAmelCase__     :   Any     		=	VisionTextDualEncoderProcessor(tokenizer=a__			,							image_processor=a__    )

  processor.save_pretrained(self.tmpdirname    )
  lowerCAmelCase__     :   Optional[Any]     		=	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			,							a__    )


 def    _A	(    self  : Any    ):
  '''simple docstring'''

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

  lowerCAmelCase__     :   Dict     		=	self.get_tokenizer(bos_token="(BOS)"			,							eos_token="(EOS)"    )
  lowerCAmelCase__     :   Optional[int]     		=	self.get_image_processor(do_normalize=a__			,							padding_value=1.0    )

  lowerCAmelCase__     :   str     		=	VisionTextDualEncoderProcessor.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			,							(BertTokenizer, BertTokenizerFast)    )

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


 def    _A	(    self  : List[str]    ):
  '''simple docstring'''

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

  lowerCAmelCase__     :   int     		=	VisionTextDualEncoderProcessor(tokenizer=a__			,							image_processor=a__    )

  lowerCAmelCase__     :   Optional[int]     		=	self.prepare_image_inputs()

  lowerCAmelCase__     :   Optional[Any]     		=	image_processor(a__			,							return_tensors="np"    )
  lowerCAmelCase__     :   Optional[Any]     		=	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    _A	(    self  : Union[str, Any]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Tuple     		=	self.get_image_processor()
  lowerCAmelCase__     :   Optional[int]     		=	self.get_tokenizer()

  lowerCAmelCase__     :   str     		=	VisionTextDualEncoderProcessor(tokenizer=a__			,							image_processor=a__    )

  lowerCAmelCase__     :   Any     		=	"lower newer"

  lowerCAmelCase__     :   str     		=	processor(text=a__    )

  lowerCAmelCase__     :   Optional[Any]     		=	tokenizer(a__    )

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


 def    _A	(    self  : List[str]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Tuple     		=	self.get_image_processor()
  lowerCAmelCase__     :   List[Any]     		=	self.get_tokenizer()

  lowerCAmelCase__     :   Optional[int]     		=	VisionTextDualEncoderProcessor(tokenizer=a__			,							image_processor=a__    )

  lowerCAmelCase__     :   Tuple     		=	"lower newer"
  lowerCAmelCase__     :   Tuple     		=	self.prepare_image_inputs()

  lowerCAmelCase__     :   int     		=	processor(text=a__			,							images=a__    )

  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(a__    ):
   processor()


 def    _A	(    self  : int    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Optional[int]     		=	self.get_image_processor()
  lowerCAmelCase__     :   Tuple     		=	self.get_tokenizer()

  lowerCAmelCase__     :   Union[str, Any]     		=	VisionTextDualEncoderProcessor(tokenizer=a__			,							image_processor=a__    )

  lowerCAmelCase__     :   List[str]     		=	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

  lowerCAmelCase__     :   Tuple     		=	processor.batch_decode(a__    )
  lowerCAmelCase__     :   str     		=	tokenizer.batch_decode(a__    )

  self.assertListEqual(a__			,							a__    )


 def    _A	(    self  : Optional[int]    ):
  '''simple docstring'''

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

  lowerCAmelCase__     :   Optional[int]     		=	VisionTextDualEncoderProcessor(tokenizer=a__			,							image_processor=a__    )

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

  lowerCAmelCase__     :   Optional[int]     		=	processor(text=a__			,							images=a__    )

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







'''simple docstring'''

def        UpperCAmelCase_ (  lowerCamelCase_			):







 """simple docstring"""


 return number & 1 == 0


if __name__ == "__main__":
     import doctest

     doctest.testmod()





