


'''simple docstring'''



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 OwlViTImageProcessor, OwlViTProcessor





@require_vision
class   UpperCAmelCase_    (unittest.TestCase    ):





    """simple docstring"""






    def  lowercase_							(				self      )							->	Optional[Any]:
         __lowerCamelCase  :      Tuple														=						tempfile.mkdtemp()

         # fmt: off
         __lowerCamelCase  :      int														=						['', '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
         __lowerCamelCase  :      Any														=						dict(zip(SCREAMING_SNAKE_CASE_     ,	range(len(SCREAMING_SNAKE_CASE_      )      )      )      )
         __lowerCamelCase  :      List[Any]														=						['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
         __lowerCamelCase  :      Dict														=						{'unk_token': '<unk>'}

         __lowerCamelCase  :      int														=						os.path.join(self.tmpdirname     ,	VOCAB_FILES_NAMES['vocab_file']      )
         __lowerCamelCase  :      List[str]														=						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_      )      )

         __lowerCamelCase  :      Tuple														=						{
             'do_resize': True,
             'size': 20,
             'do_center_crop': True,
             'crop_size': 18,
             'do_normalize': True,
             'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
             'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
         }
         __lowerCamelCase  :      Optional[int]														=						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  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Any:
         return CLIPTokenizer.from_pretrained(self.tmpdirname     ,	pad_token='!'     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	int:
         return CLIPTokenizerFast.from_pretrained(self.tmpdirname     ,	pad_token='!'     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Optional[Any]:
         return OwlViTImageProcessor.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self      )							->	List[str]:
         shutil.rmtree(self.tmpdirname      )







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      List[Any]														=						[np.random.randint(2_55     ,	size=(3, 30, 4_00)     ,	dtype=np.uinta      )]

         __lowerCamelCase  :      List[str]														=						[Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE_     ,	0     ,	-1      )      ) for x in image_inputs]

         return image_inputs







    def  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      Optional[Any]														=						self.get_tokenizer()
         __lowerCamelCase  :      int														=						self.get_rust_tokenizer()
         __lowerCamelCase  :      List[Any]														=						self.get_image_processor()

         __lowerCamelCase  :      Tuple														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )
         processor_slow.save_pretrained(self.tmpdirname      )
         __lowerCamelCase  :      int														=						OwlViTProcessor.from_pretrained(self.tmpdirname     ,	use_fast=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Optional[Any]														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )
         processor_fast.save_pretrained(self.tmpdirname      )
         __lowerCamelCase  :      Optional[Any]														=						OwlViTProcessor.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  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Union[str, Any]														=						OwlViTProcessor(tokenizer=self.get_tokenizer()     ,	image_processor=self.get_image_processor()      )
         processor.save_pretrained(self.tmpdirname      )

         __lowerCamelCase  :      Optional[int]														=						self.get_tokenizer(bos_token='(BOS)'     ,	eos_token='(EOS)'      )
         __lowerCamelCase  :      str														=						self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[str]														=						OwlViTProcessor.from_pretrained(
             self.tmpdirname     ,	bos_token='(BOS)'     ,	eos_token='(EOS)'     ,	do_normalize=SCREAMING_SNAKE_CASE_      )

         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  lowercase_							(				self      )							->	Any:
         __lowerCamelCase  :      str														=						self.get_image_processor()
         __lowerCamelCase  :      str														=						self.get_tokenizer()

         __lowerCamelCase  :      Optional[int]														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Union[str, Any]														=						self.prepare_image_inputs()

         __lowerCamelCase  :      Dict														=						image_processor(SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )
         __lowerCamelCase  :      Union[str, Any]														=						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  lowercase_							(				self      )							->	int:
         __lowerCamelCase  :      Tuple														=						self.get_image_processor()
         __lowerCamelCase  :      Tuple														=						self.get_tokenizer()

         __lowerCamelCase  :      List[Any]														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[Any]														=						'lower newer'

         __lowerCamelCase  :      Optional[int]														=						processor(text=SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )

         __lowerCamelCase  :      Optional[Any]														=						tokenizer(SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )

         for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key][0].tolist()     ,	encoded_processor[key][0].tolist()      )







    def  lowercase_							(				self      )							->	List[Any]:
         __lowerCamelCase  :      Optional[int]														=						self.get_image_processor()
         __lowerCamelCase  :      List[Any]														=						self.get_tokenizer()

         __lowerCamelCase  :      int														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Dict														=						'lower newer'
         __lowerCamelCase  :      Dict														=						self.prepare_image_inputs()

         __lowerCamelCase  :      int														=						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  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      int														=						'google/owlvit-base-patch32'
         __lowerCamelCase  :      Any														=						OwlViTProcessor.from_pretrained(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Tuple														=						['cat', 'nasa badge']
         __lowerCamelCase  :      Optional[Any]														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Dict														=						16
         self.assertListEqual(list(inputs.keys()      )     ,	['input_ids', 'attention_mask']      )
         self.assertEqual(inputs['input_ids'].shape     ,	(2, seq_length)      )

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







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Tuple														=						'google/owlvit-base-patch32'
         __lowerCamelCase  :      List[str]														=						OwlViTProcessor.from_pretrained(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						[['cat', 'nasa badge'], ['person']]
         __lowerCamelCase  :      int														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Any														=						16
         __lowerCamelCase  :      Optional[int]														=						len(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						max([len(SCREAMING_SNAKE_CASE_      ) for texts in input_texts]      )

         self.assertListEqual(list(inputs.keys()      )     ,	['input_ids', 'attention_mask']      )
         self.assertEqual(inputs['input_ids'].shape     ,	(batch_size * num_max_text_queries, seq_length)      )

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







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      List[Any]														=						'google/owlvit-base-patch32'
         __lowerCamelCase  :      Optional[Any]														=						OwlViTProcessor.from_pretrained(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Tuple														=						['cat', 'nasa badge']
         __lowerCamelCase  :      int														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Any														=						16
         __lowerCamelCase  :      Union[str, Any]														=						inputs['input_ids']
         __lowerCamelCase  :      Any														=						[
             [4_94_06, 23_68, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
             [4_94_06, 68_41, 1_13_01, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
         ]

         self.assertListEqual(list(inputs.keys()      )     ,	['input_ids', 'attention_mask']      )
         self.assertEqual(inputs['input_ids'].shape     ,	(2, seq_length)      )
         self.assertListEqual(list(input_ids[0]      )     ,	predicted_ids[0]      )
         self.assertListEqual(list(input_ids[1]      )     ,	predicted_ids[1]      )







    def  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      int														=						self.get_image_processor()
         __lowerCamelCase  :      List[str]														=						self.get_tokenizer()

         __lowerCamelCase  :      Union[str, Any]														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						self.prepare_image_inputs()
         __lowerCamelCase  :      Tuple														=						self.prepare_image_inputs()

         __lowerCamelCase  :      Optional[Any]														=						processor(images=SCREAMING_SNAKE_CASE_     ,	query_images=SCREAMING_SNAKE_CASE_      )

         self.assertListEqual(list(inputs.keys()      )     ,	['query_pixel_values', 'pixel_values']      )

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







    def  lowercase_							(				self      )							->	Any:
         __lowerCamelCase  :      Union[str, Any]														=						self.get_image_processor()
         __lowerCamelCase  :      Any														=						self.get_tokenizer()

         __lowerCamelCase  :      Dict														=						OwlViTProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[Any]														=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         __lowerCamelCase  :      List[str]														=						processor.batch_decode(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Optional[Any]														=						tokenizer.batch_decode(SCREAMING_SNAKE_CASE_      )

         self.assertListEqual(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )








"""simple docstring"""






from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE							=     {
    'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
    'feature_extraction_mctct': ['MCTCTFeatureExtractor'],
    'processing_mctct': ['MCTCTProcessor'],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __SCREAMING_SNAKE_CASE							=     [
     'MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'MCTCTForCTC',
     'MCTCTModel',
     'MCTCTPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
 from .feature_extraction_mctct import MCTCTFeatureExtractor
 from .processing_mctct import MCTCTProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
 import sys

 __SCREAMING_SNAKE_CASE							=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
