
'''simple docstring'''
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 FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor


@require_vision
class      _lowerCAmelCase       (       unittest.TestCase ):







							'''simple docstring'''

							def 			lowercase				(self    )	->  int:
														_snake_case  =    tempfile.mkdtemp()

														_snake_case  =    [
														    '[UNK]',
														    '[CLS]',
														    '[SEP]',
														    '[PAD]',
														    '[MASK]',
														    '的',
														    '价',
														    '格',
														    '是',
														    '15',
														    '便',
														    'alex',
														    '##andra',
														    '，',
														    '。',
														    '-',
														    't',
														    'shirt',
														]
														_snake_case  =    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]    )    )

														_snake_case  =    {
														    'do_resize': True,
														    'size': {'height': 224, 'width': 224},
														    'do_center_crop': True,
														    'crop_size': {'height': 18, 'width': 18},
														    'do_normalize': True,
														    'image_mean': [0.4814_5466, 0.457_8275, 0.4082_1073],
														    'image_std': [0.2686_2954, 0.2613_0258, 0.2757_7711],
														    'do_convert_rgb': True,
														}
														_snake_case  =    os.path.join(self.tmpdirname    ,    __UpperCAmelCase    )
														with open(self.image_processor_file    ,    """w"""    ,    encoding="""utf-8"""    ) as fp:
																					json.dump(__UpperCAmelCase    ,    __UpperCAmelCase    )

							def 			lowercase				(self    ,    **UpperCAmelCase    )	->  Any:
														return BertTokenizer.from_pretrained(self.tmpdirname    ,    **__UpperCAmelCase    )

							def 			lowercase				(self    ,    **UpperCAmelCase    )	->  Optional[Any]:
														return BertTokenizerFast.from_pretrained(self.tmpdirname    ,    **__UpperCAmelCase    )

							def 			lowercase				(self    ,    **UpperCAmelCase    )	->  Union[str, Any]:
														return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname    ,    **__UpperCAmelCase    )

							def 			lowercase				(self    )	->  Optional[Any]:
														shutil.rmtree(self.tmpdirname    )

							def 			lowercase				(self    )	->  int:
														_snake_case  =    [np.random.randint(255    ,    size=(3, 30, 400)    ,    dtype=np.uinta    )]

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

														return image_inputs

							def 			lowercase				(self    )	->  Any:
														_snake_case  =    self.get_tokenizer()
														_snake_case  =    self.get_rust_tokenizer()
														_snake_case  =    self.get_image_processor()

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )
														processor_slow.save_pretrained(self.tmpdirname    )
														_snake_case  =    ChineseCLIPProcessor.from_pretrained(self.tmpdirname    ,    use_fast=__UpperCAmelCase    )

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )
														processor_fast.save_pretrained(self.tmpdirname    )
														_snake_case  =    ChineseCLIPProcessor.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    ,    __UpperCAmelCase    )
														self.assertIsInstance(processor_fast.tokenizer    ,    __UpperCAmelCase    )

														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    ,    __UpperCAmelCase    )
														self.assertIsInstance(processor_fast.image_processor    ,    __UpperCAmelCase    )

							def 			lowercase				(self    )	->  Optional[Any]:
														_snake_case  =    ChineseCLIPProcessor(tokenizer=self.get_tokenizer()    ,    image_processor=self.get_image_processor()    )
														processor.save_pretrained(self.tmpdirname    )

														_snake_case  =    self.get_tokenizer(cls_token="""(CLS)"""    ,    sep_token="""(SEP)"""    )
														_snake_case  =    self.get_image_processor(do_normalize=__UpperCAmelCase    )

														_snake_case  =    ChineseCLIPProcessor.from_pretrained(
														    self.tmpdirname    ,    cls_token="""(CLS)"""    ,    sep_token="""(SEP)"""    ,    do_normalize=__UpperCAmelCase    )

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

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

							def 			lowercase				(self    )	->  Tuple:
														_snake_case  =    self.get_image_processor()
														_snake_case  =    self.get_tokenizer()

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )

														_snake_case  =    self.prepare_image_inputs()

														_snake_case  =    image_processor(__UpperCAmelCase    ,    return_tensors="""np"""    )
														_snake_case  =    processor(images=__UpperCAmelCase    ,    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 			lowercase				(self    )	->  Any:
														_snake_case  =    self.get_image_processor()
														_snake_case  =    self.get_tokenizer()

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )

														_snake_case  =    'Alexandra，T-shirt的价格是15便士。'

														_snake_case  =    processor(text=__UpperCAmelCase    )

														_snake_case  =    tokenizer(__UpperCAmelCase    )

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

							def 			lowercase				(self    )	->  Dict:
														_snake_case  =    self.get_image_processor()
														_snake_case  =    self.get_tokenizer()

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )

														_snake_case  =    'Alexandra，T-shirt的价格是15便士。'
														_snake_case  =    self.prepare_image_inputs()

														_snake_case  =    processor(text=__UpperCAmelCase    ,    images=__UpperCAmelCase    )

														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(__UpperCAmelCase    ):
																					processor()

							def 			lowercase				(self    )	->  List[Any]:
														_snake_case  =    self.get_image_processor()
														_snake_case  =    self.get_tokenizer()

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )

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

														_snake_case  =    processor.batch_decode(__UpperCAmelCase    )
														_snake_case  =    tokenizer.batch_decode(__UpperCAmelCase    )

														self.assertListEqual(__UpperCAmelCase    ,    __UpperCAmelCase    )





							def 			lowercase				(self    )	->  Optional[Any]:
														_snake_case  =    self.get_image_processor()
														_snake_case  =    self.get_tokenizer()

														_snake_case  =    ChineseCLIPProcessor(tokenizer=__UpperCAmelCase    ,    image_processor=__UpperCAmelCase    )

														_snake_case  =    'Alexandra，T-shirt的价格是15便士。'
														_snake_case  =    self.prepare_image_inputs()

														_snake_case  =    processor(text=__UpperCAmelCase    ,    images=__UpperCAmelCase    )

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






"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


__A											=						{}


try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						["""MLukeTokenizer"""]

if TYPE_CHECKING:
  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_mluke import MLukeTokenizer


else:
  import sys

  __A											=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
