






"""simple docstring"""
import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english



@require_tokenizers
class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE       ,       unittest.TestCase						):





	"""simple docstring"""




	_A       :				Any    =				RoCBertTokenizer
	_A       :				Optional[Any]    =				None
	_A       :				int    =				False
	_A       :				List[Any]    =				True
	_A       :				Union[str, Any]    =				filter_non_english





	def    lowerCamelCase(self							):
		super().setUp()

		A_		:						Dict	    =   ["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """你""", """好""", """是""", """谁""", """a""", """b""", """c""", """d"""]
		A_		:						Optional[int]	    =   {}
		A_		:						List[str]	    =   {}
		for i, value in enumerate(lowerCAmelCase_							):
			A_		:						List[Any]	    =   i
			A_		:						List[Any]	    =   i
		A_		:						int	    =   os.path.join(self.tmpdirname     ,     VOCAB_FILES_NAMES["""vocab_file"""]							)
		A_		:						Any	    =   os.path.join(self.tmpdirname     ,     VOCAB_FILES_NAMES["""word_shape_file"""]							)
		A_		:						Dict	    =   os.path.join(self.tmpdirname     ,     VOCAB_FILES_NAMES["""word_pronunciation_file"""]							)
		with open(self.vocab_file     ,     """w"""     ,     encoding="""utf-8"""							) as vocab_writer:
			vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]							)							)
		with open(self.word_shape_file     ,     """w"""     ,     encoding="""utf-8"""							) as word_shape_writer:
			json.dump(lowerCAmelCase_     ,     lowerCAmelCase_     ,     ensure_ascii=lowerCAmelCase_							)
		with open(self.word_pronunciation_file     ,     """w"""     ,     encoding="""utf-8"""							) as word_pronunciation_writer:
			json.dump(lowerCAmelCase_     ,     lowerCAmelCase_     ,     ensure_ascii=lowerCAmelCase_							)





	def    lowerCamelCase(self							):
		A_		:						int	    =   self.tokenizer_class(self.vocab_file     ,     self.word_shape_file     ,     self.word_pronunciation_file							)

		A_		:						Any	    =   tokenizer.tokenize("""你好[SEP]你是谁"""							)
		self.assertListEqual(lowerCAmelCase_     ,     ["""你""", """好""", """[SEP]""", """你""", """是""", """谁"""]							)
		self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_							)     ,     [5, 6, 2, 5, 7, 8]							)
		self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(lowerCAmelCase_							)     ,     [5, 6, 2, 5, 7, 8]							)
		self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(lowerCAmelCase_							)     ,     [5, 6, 2, 5, 7, 8]							)





	def    lowerCamelCase(self							):
		A_		:						Optional[int]	    =   RoCBertBasicTokenizer()

		self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz"""							)     ,     ["""ah""", """\u535A""", """\u63A8""", """zz"""]							)





	def    lowerCamelCase(self							):
		A_		:						List[str]	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """							)     ,     ["""hello""", """!""", """how""", """are""", """you""", """?"""]							)
		self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""							)     ,     ["""hello"""]							)





	def    lowerCamelCase(self							):
		A_		:						List[str]	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_     ,     strip_accents=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """							)     ,     ["""hällo""", """!""", """how""", """are""", """you""", """?"""]							)
		self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""							)     ,     ["""h\u00E9llo"""]							)





	def    lowerCamelCase(self							):
		A_		:						Any	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_     ,     strip_accents=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """							)     ,     ["""hallo""", """!""", """how""", """are""", """you""", """?"""]							)
		self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""							)     ,     ["""hello"""]							)





	def    lowerCamelCase(self							):
		A_		:						List[Any]	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """							)     ,     ["""hallo""", """!""", """how""", """are""", """you""", """?"""]							)
		self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""							)     ,     ["""hello"""]							)





	def    lowerCamelCase(self							):
		A_		:						int	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """							)     ,     ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]							)





	def    lowerCamelCase(self							):
		A_		:						Optional[Any]	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_     ,     strip_accents=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """							)     ,     ["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""]							)





	def    lowerCamelCase(self							):
		A_		:						Dict	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_     ,     strip_accents=lowerCAmelCase_							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """							)     ,     ["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""]							)





	def    lowerCamelCase(self							):
		A_		:						Optional[int]	    =   RoCBertBasicTokenizer(do_lower_case=lowerCAmelCase_     ,     never_split=["""[UNK]"""]							)

		self.assertListEqual(
		    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]"""							)     ,     ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""]							)





	def    lowerCamelCase(self							):
		A_		:						Dict	    =   ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

		A_		:						str	    =   {}
		for i, token in enumerate(lowerCAmelCase_							):
			A_		:						Any	    =   i
		A_		:						Any	    =   RoCBertWordpieceTokenizer(vocab=lowerCAmelCase_     ,     unk_token="""[UNK]"""							)

		self.assertListEqual(tokenizer.tokenize(""""""							)     ,     []							)

		self.assertListEqual(tokenizer.tokenize("""unwanted running"""							)     ,     ["""un""", """##want""", """##ed""", """runn""", """##ing"""]							)

		self.assertListEqual(tokenizer.tokenize("""unwantedX running"""							)     ,     ["""[UNK]""", """runn""", """##ing"""]							)





	def    lowerCamelCase(self							):
		self.assertTrue(_is_whitespace(""" """							)							)
		self.assertTrue(_is_whitespace("""\t"""							)							)
		self.assertTrue(_is_whitespace("""\r"""							)							)
		self.assertTrue(_is_whitespace("""\n"""							)							)
		self.assertTrue(_is_whitespace("""\u00A0"""							)							)

		self.assertFalse(_is_whitespace("""A"""							)							)
		self.assertFalse(_is_whitespace("""-"""							)							)





	def    lowerCamelCase(self							):
		self.assertTrue(_is_control("""\u0005"""							)							)

		self.assertFalse(_is_control("""A"""							)							)
		self.assertFalse(_is_control(""" """							)							)
		self.assertFalse(_is_control("""\t"""							)							)
		self.assertFalse(_is_control("""\r"""							)							)





	def    lowerCamelCase(self							):
		self.assertTrue(_is_punctuation("""-"""							)							)
		self.assertTrue(_is_punctuation("""$"""							)							)
		self.assertTrue(_is_punctuation("""`"""							)							)
		self.assertTrue(_is_punctuation("""."""							)							)

		self.assertFalse(_is_punctuation("""A"""							)							)
		self.assertFalse(_is_punctuation(""" """							)							)





	def    lowerCamelCase(self							):
		A_		:						List[str]	    =   self.get_tokenizer()

		# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
		self.assertListEqual([tokenizer.tokenize(lowerCAmelCase_							) for t in ["""Test""", """\xad""", """test"""]]     ,     [["""[UNK]"""], [], ["""[UNK]"""]]							)

		if self.test_rust_tokenizer:
			A_		:						Dict	    =   self.get_rust_tokenizer()
			self.assertListEqual(
			    [rust_tokenizer.tokenize(lowerCAmelCase_							) for t in ["""Test""", """\xad""", """test"""]]     ,     [["""[UNK]"""], [], ["""[UNK]"""]]							)





	def    lowerCamelCase(self							):
		for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
			with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""							):
				A_		:						Optional[Any]	    =   self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_     ,     **lowerCAmelCase_							)

				A_		:						List[str]	    =   f"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
				A_		:						Optional[int]	    =   tokenizer_r.encode_plus(
				    lowerCAmelCase_     ,     return_attention_mask=lowerCAmelCase_     ,     return_token_type_ids=lowerCAmelCase_     ,     return_offsets_mapping=lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_     ,     )

				A_		:						Any	    =   tokenizer_r.do_lower_case if hasattr(lowerCAmelCase_     ,     """do_lower_case"""							) else False
				A_		:						int	    =   (
				    [
				        ((0, 0), tokenizer_r.cls_token),
				        ((0, 1), """A"""),
				        ((1, 2), ""","""),
				        ((3, 5), """na"""),
				        ((5, 6), """##ï"""),
				        ((6, 8), """##ve"""),
				        ((9, 15), tokenizer_r.mask_token),
				        ((16, 21), """Allen"""),
				        ((21, 23), """##NL"""),
				        ((23, 24), """##P"""),
				        ((25, 33), """sentence"""),
				        ((33, 34), """."""),
				        ((0, 0), tokenizer_r.sep_token),
				    ]
				    if not do_lower_case
				    else [
				        ((0, 0), tokenizer_r.cls_token),
				        ((0, 1), """a"""),
				        ((1, 2), ""","""),
				        ((3, 8), """naive"""),
				        ((9, 15), tokenizer_r.mask_token),
				        ((16, 21), """allen"""),
				        ((21, 23), """##nl"""),
				        ((23, 24), """##p"""),
				        ((25, 33), """sentence"""),
				        ((33, 34), """."""),
				        ((0, 0), tokenizer_r.sep_token),
				    ]
				)

				self.assertEqual(
				    [e[1] for e in expected_results]     ,     tokenizer_r.convert_ids_to_tokens(tokens["""input_ids"""]							)							)
				self.assertEqual([e[0] for e in expected_results]     ,     tokens["""offset_mapping"""]							)





	def    lowerCamelCase(self							):
		A_		:						Union[str, Any]	    =   ["""的""", """人""", """有"""]
		A_		:						Dict	    =   """""".join(lowerCAmelCase_							)
		for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
			with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""							):
				A_		:						List[Any]	    =   True
				A_		:						Any	    =   self.tokenizer_class.from_pretrained(lowerCAmelCase_     ,     **lowerCAmelCase_							)
				A_		:						Union[str, Any]	    =   self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_     ,     **lowerCAmelCase_							)

				A_		:						str	    =   tokenizer_p.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				A_		:						Dict	    =   tokenizer_r.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)

				A_		:						str	    =   tokenizer_r.convert_ids_to_tokens(lowerCAmelCase_							)
				A_		:						int	    =   tokenizer_p.convert_ids_to_tokens(lowerCAmelCase_							)

				# it is expected that each Chinese character is not preceded by "##"
				self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)
				self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)

				A_		:						Dict	    =   False
				A_		:						Dict	    =   self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_     ,     **lowerCAmelCase_							)
				A_		:						Optional[int]	    =   self.tokenizer_class.from_pretrained(lowerCAmelCase_     ,     **lowerCAmelCase_							)

				A_		:						List[str]	    =   tokenizer_r.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				A_		:						Optional[Any]	    =   tokenizer_p.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)

				A_		:						Union[str, Any]	    =   tokenizer_r.convert_ids_to_tokens(lowerCAmelCase_							)
				A_		:						Any	    =   tokenizer_p.convert_ids_to_tokens(lowerCAmelCase_							)

				# it is expected that only the first Chinese character is not preceded by "##".
				A_		:						Dict	    =   [
				    f"""##{token}""" if idx != 0 else token for idx, token in enumerate(lowerCAmelCase_							)
				]
				self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)
				self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)





	@slow
	def    lowerCamelCase(self							):
		A_		:						List[str]	    =   self.tokenizer_class(self.vocab_file     ,     self.word_shape_file     ,     self.word_pronunciation_file							)

		A_		:						List[str]	    =   tokenizer.encode("""你好"""     ,     add_special_tokens=lowerCAmelCase_							)
		A_		:						List[Any]	    =   tokenizer.encode("""你是谁"""     ,     add_special_tokens=lowerCAmelCase_							)

		A_		:						Dict	    =   tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_							)
		A_		:						Union[str, Any]	    =   tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_     ,     lowerCAmelCase_							)

		assert encoded_sentence == [1] + text + [2]
		assert encoded_pair == [1] + text + [2] + text_a + [2]





	def    lowerCamelCase(self							):
		A_		:						List[Any]	    =   self.get_tokenizers(do_lower_case=lowerCAmelCase_							)
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				A_		:						Union[str, Any]	    =   """你好，你是谁"""
				A_		:						Tuple	    =   tokenizer.tokenize(lowerCAmelCase_							)
				A_		:						Optional[int]	    =   tokenizer.convert_tokens_to_ids(lowerCAmelCase_							)
				A_		:						Optional[int]	    =   tokenizer.convert_tokens_to_shape_ids(lowerCAmelCase_							)
				A_		:						Tuple	    =   tokenizer.convert_tokens_to_pronunciation_ids(lowerCAmelCase_							)
				A_		:						Tuple	    =   tokenizer.prepare_for_model(
				    lowerCAmelCase_     ,     lowerCAmelCase_     ,     lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)

				A_		:						int	    =   tokenizer.encode_plus(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)

				self.assertEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)









"""simple docstring"""
import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	_A       :				Optional[int]    =				["""image_processor""", """tokenizer"""]
	_A       :				List[Any]    =				"""ViTImageProcessor"""
	_A       :				Optional[Any]    =				("""CLIPTokenizer""", """CLIPTokenizerFast""")





	def __init__(self     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_=None     ,     **lowerCAmelCase_							):
		A_		:						Union[str, Any]	    =   None
		if "feature_extractor" in kwargs:
			warnings.warn(
			    """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
			    """ instead."""     ,     lowerCAmelCase_     ,     )
			A_		:						Union[str, Any]	    =   kwargs.pop("""feature_extractor"""							)

		A_		:						Optional[int]	    =   image_processor if image_processor is not None else feature_extractor
		if image_processor is None:
			raise ValueError("""You need to specify an `image_processor`."""							)
		if tokenizer is None:
			raise ValueError("""You need to specify a `tokenizer`."""							)

		super().__init__(lowerCAmelCase_     ,     lowerCAmelCase_							)





	def __call__(self     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_=None     ,     **lowerCAmelCase_							):
		if text is None and visual_prompt is None and images is None:
			raise ValueError("""You have to specify either text, visual prompt or images."""							)

		if text is not None and visual_prompt is not None:
			raise ValueError("""You have to specify exactly one type of prompt. Either text or visual prompt."""							)

		if text is not None:
			A_		:						Tuple	    =   self.tokenizer(lowerCAmelCase_     ,     return_tensors=lowerCAmelCase_     ,     **lowerCAmelCase_							)

		if visual_prompt is not None:
			A_		:						Union[str, Any]	    =   self.image_processor(lowerCAmelCase_     ,     return_tensors=lowerCAmelCase_     ,     **lowerCAmelCase_							)

		if images is not None:
			A_		:						Any	    =   self.image_processor(lowerCAmelCase_     ,     return_tensors=lowerCAmelCase_     ,     **lowerCAmelCase_							)

		if visual_prompt is not None and images is not None:
			A_		:						List[str]	    =   {
			    """pixel_values""": image_features.pixel_values,
			    """conditional_pixel_values""": prompt_features.pixel_values,
			}
			return encoding
		elif text is not None and images is not None:
			A_		:						str	    =   image_features.pixel_values
			return encoding
		elif text is not None:
			return encoding
		elif visual_prompt is not None:
			A_		:						Any	    =   {
			    """conditional_pixel_values""": prompt_features.pixel_values,
			}
			return encoding
		else:
			return BatchEncoding(data=dict(**lowerCAmelCase_							)     ,     tensor_type=lowerCAmelCase_							)





	def    lowerCamelCase(self     ,     *lowerCAmelCase_     ,     **lowerCAmelCase_							):
		return self.tokenizer.batch_decode(*lowerCAmelCase_     ,     **lowerCAmelCase_							)





	def    lowerCamelCase(self     ,     *lowerCAmelCase_     ,     **lowerCAmelCase_							):
		return self.tokenizer.decode(*lowerCAmelCase_     ,     **lowerCAmelCase_							)





	@property
	def    lowerCamelCase(self							):
		warnings.warn(
		    """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""     ,     lowerCAmelCase_     ,     )
		return self.image_processor_class





	@property
	def    lowerCamelCase(self							):
		warnings.warn(
		    """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""     ,     lowerCAmelCase_     ,     )
		return self.image_processor

