
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip 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 CLIPImageProcessor, CLIPProcessor
@require_vision
class       _lowerCAmelCase  (		unittest.TestCase							):

 """simple docstring"""

 def      __lowerCAmelCase  (						self			:			Optional[Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					tempfile.mkdtemp()

      # fmt: off
      UpperCamelCase						    =					['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
      # fmt: on
      UpperCamelCase						    =					dict(zip(SCREAMING_SNAKE_CASE__					, range(len(SCREAMING_SNAKE_CASE__   )   )   )   )
      UpperCamelCase						    =					['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
      UpperCamelCase						    =					{'unk_token': '<unk>'}

      UpperCamelCase						    =					os.path.join(self.tmpdirname					, VOCAB_FILES_NAMES['vocab_file']   )
      UpperCamelCase						    =					os.path.join(self.tmpdirname					, VOCAB_FILES_NAMES['merges_file']   )
      with open(self.vocab_file					, 'w'					, encoding='utf-8'   ) as fp:
           fp.write(json.dumps(SCREAMING_SNAKE_CASE__   ) + '\n'   )
      with open(self.merges_file					, 'w'					, encoding='utf-8'   ) as fp:
           fp.write('\n'.join(SCREAMING_SNAKE_CASE__   )   )

      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			:			Any					, **SCREAMING_SNAKE_CASE__			:			List[Any]   ):






      """simple docstring"""



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

 def      __lowerCAmelCase  (						self			:			Dict					, **SCREAMING_SNAKE_CASE__			:			int   ):






      """simple docstring"""



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

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






      """simple docstring"""



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

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






      """simple docstring"""



      shutil.rmtree(self.tmpdirname   )

 def      __lowerCAmelCase  (						self			:			Optional[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			:			int   ):






      """simple docstring"""



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

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

      UpperCamelCase						    =					CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )
      processor_fast.save_pretrained(self.tmpdirname   )
      UpperCamelCase						    =					CLIPProcessor.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			:			List[str]   ):






      """simple docstring"""



      UpperCamelCase						    =					CLIPProcessor(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						    =					CLIPProcessor.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			:			List[str]   ):






      """simple docstring"""



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

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

      UpperCamelCase						    =					'lower newer'

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					tokenizer(SCREAMING_SNAKE_CASE__   )

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

 def      __lowerCAmelCase  (						self			:			Dict   ):






      """simple docstring"""



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

      UpperCamelCase						    =					CLIPProcessor(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', 'attention_mask', 'pixel_values']   )

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

 def      __lowerCAmelCase  (						self			:			Any   ):






      """simple docstring"""



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

      UpperCamelCase						    =					CLIPProcessor(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			:			Optional[int]   ):






      """simple docstring"""



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

      UpperCamelCase						    =					CLIPProcessor(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   )




from functools import lru_cache

@lru_cache
def  __lowerCamelCase					( _lowercase			)       ->      int:
     if num < 0:
          raise ValueError('Number should not be negative.'			)

     return 1 if num in (0, 1) else num * factorial(num - 1			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


