
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

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


if is_vision_available():
 from PIL import Image

 from transformers import AlignProcessor, EfficientNetImageProcessor
@require_vision
class       _lowerCAmelCase  (		unittest.TestCase							):

 """simple docstring"""

 def      __lowerCAmelCase  (						self			:			Any   ):






      """simple docstring"""



      UpperCamelCase						    =					tempfile.mkdtemp()

      UpperCamelCase						    =					[
          '[UNK]',
          '[CLS]',
          '[SEP]',
          '[PAD]',
          '[MASK]',
          'want',
          '##want',
          '##ed',
          'wa',
          'un',
          'runn',
          '##ing',
          ',',
          'low',
          'lowest',
      ]
      UpperCamelCase						    =					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]   )   )

      UpperCamelCase						    =					{
          'do_resize': True,
          'size': 20,
          'do_center_crop': True,
          'crop_size': 18,
          'do_normalize': True,
          'image_mean': [0.48145466, 0.4578275, 0.40821073],
          'image_std': [0.26862954, 0.26130258, 0.27577711],
      }
      UpperCamelCase						    =					os.path.join(self.tmpdirname					, SCREAMING_SNAKE_CASE__   )
      with open(self.image_processor_file					, 'w'					, encoding='utf-8'   ) as fp:
           json.dump(SCREAMING_SNAKE_CASE__					, SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			List[Any]					, **SCREAMING_SNAKE_CASE__			:			Optional[int]   ):






      """simple docstring"""



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

 def      __lowerCAmelCase  (						self			:			Optional[Any]					, **SCREAMING_SNAKE_CASE__			:			List[str]   ):






      """simple docstring"""



      return BertTokenizerFast.from_pretrained(self.tmpdirname					, **SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			Optional[Any]					, **SCREAMING_SNAKE_CASE__			:			Any   ):






      """simple docstring"""



      return EfficientNetImageProcessor.from_pretrained(self.tmpdirname					, **SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      shutil.rmtree(self.tmpdirname   )

 def      __lowerCAmelCase  (						self			:			List[Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					[np.random.randint(2_55					, size=(3, 30, 4_00)					, dtype=np.uinta   )]
      UpperCamelCase						    =					[Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE__					, 0					, -1   )   ) for x in image_inputs]
      return image_inputs

 def      __lowerCAmelCase  (						self			:			str   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_tokenizer()
      UpperCamelCase						    =					self.get_rust_tokenizer()
      UpperCamelCase						    =					self.get_image_processor()

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )
      processor_slow.save_pretrained(self.tmpdirname   )
      UpperCamelCase						    =					AlignProcessor.from_pretrained(self.tmpdirname					, use_fast=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )
      processor_fast.save_pretrained(self.tmpdirname   )
      UpperCamelCase						    =					AlignProcessor.from_pretrained(self.tmpdirname   )

      self.assertEqual(processor_slow.tokenizer.get_vocab()					, tokenizer_slow.get_vocab()   )
      self.assertEqual(processor_fast.tokenizer.get_vocab()					, tokenizer_fast.get_vocab()   )
      self.assertEqual(tokenizer_slow.get_vocab()					, tokenizer_fast.get_vocab()   )
      self.assertIsInstance(processor_slow.tokenizer					, SCREAMING_SNAKE_CASE__   )
      self.assertIsInstance(processor_fast.tokenizer					, SCREAMING_SNAKE_CASE__   )

      self.assertEqual(processor_slow.image_processor.to_json_string()					, image_processor.to_json_string()   )
      self.assertEqual(processor_fast.image_processor.to_json_string()					, image_processor.to_json_string()   )
      self.assertIsInstance(processor_slow.image_processor					, SCREAMING_SNAKE_CASE__   )
      self.assertIsInstance(processor_fast.image_processor					, SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			Optional[Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					AlignProcessor(tokenizer=self.get_tokenizer()					, image_processor=self.get_image_processor()   )
      processor.save_pretrained(self.tmpdirname   )

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

      UpperCamelCase						    =					AlignProcessor.from_pretrained(
          self.tmpdirname					, bos_token='(BOS)'					, eos_token='(EOS)'					, do_normalize=SCREAMING_SNAKE_CASE__					, padding_value=1.0   )

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

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

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					self.prepare_image_inputs()

      UpperCamelCase						    =					image_processor(SCREAMING_SNAKE_CASE__					, return_tensors='np'   )
      UpperCamelCase						    =					processor(images=SCREAMING_SNAKE_CASE__					, return_tensors='np'   )

      for key in input_image_proc.keys():
           self.assertAlmostEqual(input_image_proc[key].sum()					, input_processor[key].sum()					, delta=1e-2   )

 def      __lowerCAmelCase  (						self			:			str   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					'lower newer'

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					tokenizer(SCREAMING_SNAKE_CASE__					, padding='max_length'					, max_length=64   )

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

 def      __lowerCAmelCase  (						self			:			int   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

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

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__					, images=SCREAMING_SNAKE_CASE__   )

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

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

 def      __lowerCAmelCase  (						self			:			Optional[int]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

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

      UpperCamelCase						    =					processor.batch_decode(SCREAMING_SNAKE_CASE__   )
      UpperCamelCase						    =					tokenizer.batch_decode(SCREAMING_SNAKE_CASE__   )

      self.assertListEqual(SCREAMING_SNAKE_CASE__					, SCREAMING_SNAKE_CASE__   )






 def      __lowerCAmelCase  (						self			:			List[str]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					AlignProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

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

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__					, images=SCREAMING_SNAKE_CASE__   )

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




import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format
class       _lowerCAmelCase  :

 """simple docstring"""
 SCREAMING_SNAKE_CASE_				:					Optional[Any]       						=None

 def      __lowerCAmelCase  (						self			:			Union[str, Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.feature_extraction_class(**self.feat_extract_dict   )
      UpperCamelCase						    =					json.loads(feat_extract.to_json_string()   )
      for key, value in self.feat_extract_dict.items():
           self.assertEqual(obj[key]					, SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					self.feature_extraction_class(**self.feat_extract_dict   )

      with tempfile.TemporaryDirectory() as tmpdirname:
           UpperCamelCase						    =					os.path.join(SCREAMING_SNAKE_CASE__					, 'feat_extract.json'   )
           feat_extract_first.to_json_file(SCREAMING_SNAKE_CASE__   )
           UpperCamelCase						    =					self.feature_extraction_class.from_json_file(SCREAMING_SNAKE_CASE__   )

      self.assertEqual(feat_extract_second.to_dict()					, feat_extract_first.to_dict()   )

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					self.feature_extraction_class(**self.feat_extract_dict   )

      with tempfile.TemporaryDirectory() as tmpdirname:
           UpperCamelCase						    =					feat_extract_first.save_pretrained(SCREAMING_SNAKE_CASE__   )[0]
           check_json_file_has_correct_format(SCREAMING_SNAKE_CASE__   )
           UpperCamelCase						    =					self.feature_extraction_class.from_pretrained(SCREAMING_SNAKE_CASE__   )

      self.assertEqual(feat_extract_second.to_dict()					, feat_extract_first.to_dict()   )






 def      __lowerCAmelCase  (						self			:			Union[str, Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.feature_extraction_class()
      self.assertIsNotNone(SCREAMING_SNAKE_CASE__   )


