import warnings

from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum

from ...processing_utils import ProcessorMixin


if is_torch_available():
		import torch







class        lowerCAmelCase__      (   __lowercase	):
						UpperCamelCase_							: str	=		"char"
						UpperCamelCase_							: Optional[int]	=		"bpe"
						UpperCamelCase_							: Optional[int]	=		"wp"




lowerCamelCase__	=							(DecodeType.CHARACTER, DecodeType.BPE, DecodeType.WORDPIECE)







class        lowerCAmelCase__      (   __lowercase	):
						UpperCamelCase_							: Tuple	=		["image_processor", "char_tokenizer"]
						UpperCamelCase_							: List[Any]	=		"ViTImageProcessor"
						UpperCamelCase_							: Union[str, Any]	=		"MgpstrTokenizer"

						def __init__(			self       ,							a=None       ,							a=None       ,							**a				)					->      int:


								'''simple docstring'''

								_UpperCamelCase						    =	None
								if "feature_extractor" in kwargs:
										warnings.warn(
										    """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
										    """ instead."""       ,							a       ,							)
										_UpperCamelCase						    =	kwargs.pop("""feature_extractor"""				)

								_UpperCamelCase						    =	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`."""				)

								_UpperCamelCase						    =	tokenizer
								_UpperCamelCase						    =	AutoTokenizer.from_pretrained("""gpt2"""				)
								_UpperCamelCase						    =	AutoTokenizer.from_pretrained("""bert-base-uncased"""				)

								super().__init__(a       ,							a				)

						def __call__(			self       ,							a=None       ,							a=None       ,							a=None       ,							**a				)					->      str:


								'''simple docstring'''

								if images is None and text is None:
										raise ValueError("""You need to specify either an `images` or `text` input to process."""				)

								if images is not None:
										_UpperCamelCase						    =	self.image_processor(a       ,							return_tensors=a       ,							**a				)
								if text is not None:
										_UpperCamelCase						    =	self.char_tokenizer(a       ,							return_tensors=a       ,							**a				)

								if text is None:
										return inputs
								elif images is None:
										return encodings
								else:
										_UpperCamelCase						    =	encodings["""input_ids"""]
										return inputs

						def  A_				(			self       ,							a				)					->      str:


								'''simple docstring'''

								_UpperCamelCase    ,	_UpperCamelCase    ,	_UpperCamelCase						    =	sequences
								_UpperCamelCase						    =	char_preds.size(0				)

								_UpperCamelCase    ,	_UpperCamelCase						    =	self._decode_helper(a       ,							"""char"""				)
								_UpperCamelCase    ,	_UpperCamelCase						    =	self._decode_helper(a       ,							"""bpe"""				)
								_UpperCamelCase    ,	_UpperCamelCase						    =	self._decode_helper(a       ,							"""wp"""				)

								_UpperCamelCase						    =	[]
								_UpperCamelCase						    =	[]
								for i in range(a				):
										_UpperCamelCase						    =	[char_scores[i], bpe_scores[i], wp_scores[i]]
										_UpperCamelCase						    =	[char_strs[i], bpe_strs[i], wp_strs[i]]
										_UpperCamelCase						    =	scores.index(max(a				)				)
										final_strs.append(strs[max_score_index]				)
										final_scores.append(scores[max_score_index]				)

								_UpperCamelCase						    =	{}
								_UpperCamelCase						    =	final_strs
								_UpperCamelCase						    =	final_scores
								_UpperCamelCase						    =	char_strs
								_UpperCamelCase						    =	bpe_strs
								_UpperCamelCase						    =	wp_strs
								return out

						def  A_				(			self       ,							a       ,							a				)					->      List[str]:


								'''simple docstring'''

								if format == DecodeType.CHARACTER:
										_UpperCamelCase						    =	self.char_decode
										_UpperCamelCase						    =	1
										_UpperCamelCase						    =	"""[s]"""
								elif format == DecodeType.BPE:
										_UpperCamelCase						    =	self.bpe_decode
										_UpperCamelCase						    =	2
										_UpperCamelCase						    =	"""#"""
								elif format == DecodeType.WORDPIECE:
										_UpperCamelCase						    =	self.wp_decode
										_UpperCamelCase						    =	1_02
										_UpperCamelCase						    =	"""[SEP]"""
								else:
										raise ValueError(F'Format {format} is not supported.'				)

								_UpperCamelCase    ,	_UpperCamelCase						    =	[], []
								_UpperCamelCase						    =	pred_logits.size(0				)
								_UpperCamelCase						    =	pred_logits.size(1				)
								_UpperCamelCase    ,	_UpperCamelCase						    =	pred_logits.topk(1       ,							dim=-1       ,							largest=a       ,							sorted=a				)
								_UpperCamelCase						    =	preds_index.view(-1       ,							a				)[:, 1:]
								_UpperCamelCase						    =	decoder(a				)
								_UpperCamelCase    ,	_UpperCamelCase						    =	torch.nn.functional.softmax(a       ,							dim=2				).max(dim=2				)
								_UpperCamelCase						    =	preds_max_prob[:, 1:]

								for index in range(a				):
										_UpperCamelCase						    =	preds_str[index].find(a				)
										_UpperCamelCase						    =	preds_str[index][:pred_eos]
										_UpperCamelCase						    =	preds_index[index].cpu().tolist()
										_UpperCamelCase						    =	pred_index.index(a				) if eos_token in pred_index else -1
										_UpperCamelCase						    =	preds_max_prob[index][: pred_eos_index + 1]
										_UpperCamelCase						    =	pred_max_prob.cumprod(dim=0				)[-1] if pred_max_prob.nelement() != 0 else 0.0
										dec_strs.append(a				)
										conf_scores.append(a				)

								return dec_strs, conf_scores

						def  A_				(			self       ,							a				)					->      Optional[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	[seq.replace(""" """       ,							""""""				) for seq in self.char_tokenizer.batch_decode(a				)]
								return decode_strs

						def  A_				(			self       ,							a				)					->      Tuple:


								'''simple docstring'''

								return self.bpe_tokenizer.batch_decode(a				)







						def  A_				(			self       ,							a				)					->      Optional[int]:


								'''simple docstring'''

								_UpperCamelCase						    =	[seq.replace(""" """       ,							""""""				) for seq in self.wp_tokenizer.batch_decode(a				)]
								return decode_strs





import unittest

from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase__	=							get_tests_dir("fixtures/test_sentencepiece.model")







@require_sentencepiece
@require_tokenizers
class        lowerCAmelCase__      (   __lowercase		,	unittest.TestCase	):
						UpperCamelCase_							: List[Any]	=		XLNetTokenizer
						UpperCamelCase_							: Optional[int]	=		XLNetTokenizerFast
						UpperCamelCase_							: Dict	=		True
						UpperCamelCase_							: Dict	=		True

						def  A_				(			self				)					->      Optional[int]:


								'''simple docstring'''

								super().setUp()

								# We have a SentencePiece fixture for testing
								_UpperCamelCase						    =	XLNetTokenizer(a       ,							keep_accents=a				)
								tokenizer.sanitize_special_tokens()
								tokenizer.save_pretrained(self.tmpdirname				)

						def  A_				(			self				)					->      Optional[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	"""<s>"""
								_UpperCamelCase						    =	1

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(a				)       ,							a				)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(a				)       ,							a				)

						def  A_				(			self				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	list(self.get_tokenizer().get_vocab().keys()				)

								self.assertEqual(vocab_keys[0]       ,							"""<unk>"""				)
								self.assertEqual(vocab_keys[1]       ,							"""<s>"""				)
								self.assertEqual(vocab_keys[-1]       ,							"""<eod>"""				)
								self.assertEqual(len(a				)       ,							10_06				)

						def  A_				(			self				)					->      Union[str, Any]:


								'''simple docstring'''

								self.assertEqual(self.get_tokenizer().vocab_size       ,							10_00				)

						def  A_				(			self				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	XLNetTokenizer(a       ,							keep_accents=a				)

								_UpperCamelCase						    =	tokenizer.tokenize("""This is a test"""				)
								self.assertListEqual(a       ,							["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]				)

								self.assertListEqual(tokenizer.convert_tokens_to_ids(a				)       ,							[2_85, 46, 10, 1_70, 3_82]				)

								_UpperCamelCase						    =	tokenizer.tokenize("""I was born in 92000, and this is falsé."""				)
								self.assertListEqual(
								    a       ,							[
								        SPIECE_UNDERLINE + """I""",
								        SPIECE_UNDERLINE + """was""",
								        SPIECE_UNDERLINE + """b""",
								        """or""",
								        """n""",
								        SPIECE_UNDERLINE + """in""",
								        SPIECE_UNDERLINE + """""",
								        """9""",
								        """2""",
								        """0""",
								        """0""",
								        """0""",
								        """,""",
								        SPIECE_UNDERLINE + """and""",
								        SPIECE_UNDERLINE + """this""",
								        SPIECE_UNDERLINE + """is""",
								        SPIECE_UNDERLINE + """f""",
								        """al""",
								        """s""",
								        """é""",
								        """.""",
								    ]       ,							)
								_UpperCamelCase						    =	tokenizer.convert_tokens_to_ids(a				)
								self.assertListEqual(a       ,							[8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]				)

								_UpperCamelCase						    =	tokenizer.convert_ids_to_tokens(a				)
								self.assertListEqual(
								    a       ,							[
								        SPIECE_UNDERLINE + """I""",
								        SPIECE_UNDERLINE + """was""",
								        SPIECE_UNDERLINE + """b""",
								        """or""",
								        """n""",
								        SPIECE_UNDERLINE + """in""",
								        SPIECE_UNDERLINE + """""",
								        """<unk>""",
								        """2""",
								        """0""",
								        """0""",
								        """0""",
								        """,""",
								        SPIECE_UNDERLINE + """and""",
								        SPIECE_UNDERLINE + """this""",
								        SPIECE_UNDERLINE + """is""",
								        SPIECE_UNDERLINE + """f""",
								        """al""",
								        """s""",
								        """<unk>""",
								        """.""",
								    ]       ,							)

						def  A_				(			self				)					->      int:


								'''simple docstring'''

								_UpperCamelCase						    =	XLNetTokenizer(a       ,							do_lower_case=a				)
								_UpperCamelCase						    =	tokenizer.tokenize("""I was born in 92000, and this is falsé."""				)
								self.assertListEqual(
								    a       ,							[
								        SPIECE_UNDERLINE + """""",
								        """i""",
								        SPIECE_UNDERLINE + """was""",
								        SPIECE_UNDERLINE + """b""",
								        """or""",
								        """n""",
								        SPIECE_UNDERLINE + """in""",
								        SPIECE_UNDERLINE + """""",
								        """9""",
								        """2""",
								        """0""",
								        """0""",
								        """0""",
								        """,""",
								        SPIECE_UNDERLINE + """and""",
								        SPIECE_UNDERLINE + """this""",
								        SPIECE_UNDERLINE + """is""",
								        SPIECE_UNDERLINE + """f""",
								        """al""",
								        """se""",
								        """.""",
								    ]       ,							)
								self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""				)       ,							["""▁he""", """ll""", """o"""]				)

						def  A_				(			self				)					->      Dict:


								'''simple docstring'''

								_UpperCamelCase						    =	XLNetTokenizer(a       ,							do_lower_case=a				)
								_UpperCamelCase						    =	tokenizer.tokenize("""I was born in 92000, and this is falsé."""				)
								self.assertListEqual(
								    a       ,							[
								        SPIECE_UNDERLINE + """I""",
								        SPIECE_UNDERLINE + """was""",
								        SPIECE_UNDERLINE + """b""",
								        """or""",
								        """n""",
								        SPIECE_UNDERLINE + """in""",
								        SPIECE_UNDERLINE + """""",
								        """9""",
								        """2""",
								        """0""",
								        """0""",
								        """0""",
								        """,""",
								        SPIECE_UNDERLINE + """and""",
								        SPIECE_UNDERLINE + """this""",
								        SPIECE_UNDERLINE + """is""",
								        SPIECE_UNDERLINE + """f""",
								        """al""",
								        """se""",
								        """.""",
								    ]       ,							)

						@slow
						def  A_				(			self				)					->      str:


								'''simple docstring'''

								_UpperCamelCase						    =	XLNetTokenizer.from_pretrained("""xlnet-base-cased"""				)

								_UpperCamelCase						    =	tokenizer.encode("""sequence builders"""       ,							add_special_tokens=a				)
								_UpperCamelCase						    =	tokenizer.encode("""multi-sequence build"""       ,							add_special_tokens=a				)

								_UpperCamelCase						    =	tokenizer.build_inputs_with_special_tokens(a				)
								_UpperCamelCase						    =	tokenizer.build_inputs_with_special_tokens(a       ,							a				)

								assert encoded_sentence == text + [4, 3]
								assert encoded_pair == text + [4] + text_a + [4, 3]







						@slow
						def  A_				(			self				)					->      int:


								'''simple docstring'''

								_UpperCamelCase						    =	{"""input_ids""": [[17, 2_14_42, 2_70, 17, 10, 1_46_45, 3_18, 34, 17, 45_46, 31_45, 7_87, 13, 77_52, 2_20_18, 23, 21, 17, 45_46, 31_45, 7_87, 13, 33_52, 1_44_31, 13, 55_00, 11, 11_76, 5_80, 13, 1_68_19, 47_97, 23, 17, 10, 1_71_35, 6_58, 19, 4_57, 79_32, 13, 1_84, 19, 31_54, 1_71_35, 64_68, 19, 14_04, 1_22_69, 19, 42_29, 53_56, 1_62_64, 46, 19, 17, 2_05_45, 1_03_95, 9, 9, 9, 11, 28, 64_21, 95_31, 2_07_29, 17, 10, 3_53, 1_70_22, 11, 21, 64_21, 95_31, 1_69_49, 17, 10, 1_15_09, 7_53, 11, 33, 95, 24_21, 73_85, 9_56, 1_44_31, 26_26, 25, 8_42, 73_85, 48_36, 21, 14_29, 22_72, 98_55, 31_20, 1_61, 2_47_38, 19, 1_32_03, 6_58, 2_18, 7_87, 21, 4_30, 1_84_82, 8_47, 26_37, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3_22, 2_21_78, 27, 10_64, 22, 9_56, 13, 1_11_01, 14_29, 58_54, 2_43_13, 1_89_53, 40, 4_22, 2_43_66, 68, 17_58, 37, 1_04_83, 1_42_57, 31, 2_07, 2_63, 21, 2_03, 37_73, 25, 71, 97_35, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 32, 20_49, 34_42, 17, 1_38_94, 33_80, 23, 95, 18, 1_76_34, 22_88, 9, 4, 3]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=a       ,							model_name="""xlnet-base-cased"""       ,							revision="""c841166438c31ec7ca9a106dee7bb312b73ae511"""       ,							)



