





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     a__ (      unittest.TestCase   ):







     def     lowerCAmelCase_       (			self				)						->					Optional[int]:



          '''simple docstring'''



          a											=   tempfile.mkdtemp()

          a											=   CLIPImageProcessor()
          a											=   BertTokenizer.from_pretrained(
              "hf-internal-testing/tiny-random-BertModel"						,	model_input_names=["input_ids", "attention_mask"]				)

          a											=   GitProcessor(a_						,	a_				)

          processor.save_pretrained(self.tmpdirname				)







     def     lowerCAmelCase_       (			self						,	**A				)						->					Dict:



          '''simple docstring'''



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







     def     lowerCAmelCase_       (			self						,	**A				)						->					Union[str, Any]:



          '''simple docstring'''



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







     def     lowerCAmelCase_       (			self				)						->					Dict:



          '''simple docstring'''



          shutil.rmtree(self.tmpdirname				)







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



          '''simple docstring'''



          a											=   [np.random.randint(255						,	size=(3, 30, 400)						,	dtype=np.uinta				)]

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

          return image_inputs







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



          '''simple docstring'''



          a											=   GitProcessor(tokenizer=self.get_tokenizer()						,	image_processor=self.get_image_processor()				)
          processor.save_pretrained(self.tmpdirname				)

          a											=   self.get_tokenizer(bos_token="(BOS)"						,	eos_token="(EOS)"				)
          a											=   self.get_image_processor(do_normalize=a_						,	padding_value=1.0				)

          a											=   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     lowerCAmelCase_       (			self				)						->					List[str]:



          '''simple docstring'''



          a											=   self.get_image_processor()
          a											=   self.get_tokenizer()

          a											=   GitProcessor(tokenizer=a_						,	image_processor=a_				)

          a											=   self.prepare_image_inputs()

          a											=   image_processor(a_						,	return_tensors="np"				)
          a											=   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     lowerCAmelCase_       (			self				)						->					str:



          '''simple docstring'''



          a											=   self.get_image_processor()
          a											=   self.get_tokenizer()

          a											=   GitProcessor(tokenizer=a_						,	image_processor=a_				)

          a											=   "lower newer"

          a											=   processor(text=a_				)

          a											=   tokenizer(a_						,	return_token_type_ids=a_				)

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







     def     lowerCAmelCase_       (			self				)						->					List[Any]:



          '''simple docstring'''



          a											=   self.get_image_processor()
          a											=   self.get_tokenizer()

          a											=   GitProcessor(tokenizer=a_						,	image_processor=a_				)

          a											=   "lower newer"
          a											=   self.prepare_image_inputs()

          a											=   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     lowerCAmelCase_       (			self				)						->					Tuple:



          '''simple docstring'''



          a											=   self.get_image_processor()
          a											=   self.get_tokenizer()

          a											=   GitProcessor(tokenizer=a_						,	image_processor=a_				)

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

          a											=   processor.batch_decode(a_				)
          a											=   tokenizer.batch_decode(a_				)

          self.assertListEqual(a_						,	a_				)







     def     lowerCAmelCase_       (			self				)						->					Dict:



          '''simple docstring'''



          a											=   self.get_image_processor()
          a											=   self.get_tokenizer()

          a											=   GitProcessor(tokenizer=a_						,	image_processor=a_				)

          a											=   "lower newer"
          a											=   self.prepare_image_inputs()

          a											=   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"]				)







import safs




class     a__ (      safs.SaFileSystem   ):
     pass

