





import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCamelCase   				=			get_tests_dir('fixtures/test_sentencepiece_no_bos.model')




@require_sentencepiece
@require_tokenizers
class   UpperCamelCase_       (     UpperCamelCase__				,  unittest.TestCase    ):
							lowerCamelCase_           =					PegasusTokenizer
							lowerCamelCase_           =					PegasusTokenizerFast
							lowerCamelCase_           =					True
							lowerCamelCase_           =					True


							def      _snake_case  (							self    :List[Any]		)   ->   int:



									"""simple docstring"""



									super().setUp()

									# We have a SentencePiece fixture for testing
									SCREAMING_SNAKE_CASE__			=      PegasusTokenizer(_a		)
									tokenizer.save_pretrained(self.tmpdirname		)


							@cached_property
							def      _snake_case  (							self    :Optional[Any]		)   ->   int:



									"""simple docstring"""



									return PegasusTokenizer.from_pretrained("""google/pegasus-large"""		)


							def      _snake_case  (							self    :str							,				**__A    :Dict		)   ->   PegasusTokenizer:



									"""simple docstring"""



									return PegasusTokenizer.from_pretrained(self.tmpdirname							,				**_a		)


							def      _snake_case  (							self    :int							,				__A    :str		)   ->   List[Any]:



									"""simple docstring"""



									return ("This is a test", "This is a test")


							def      _snake_case  (							self    :Any		)   ->   int:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      """</s>"""
									SCREAMING_SNAKE_CASE__			=      1

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


							def      _snake_case  (							self    :Tuple		)   ->   Dict:



									"""simple docstring"""



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

									self.assertEqual(vocab_keys[0]							,				"""<pad>"""		)
									self.assertEqual(vocab_keys[1]							,				"""</s>"""		)
									self.assertEqual(vocab_keys[-1]							,				"""v"""		)
									self.assertEqual(len(_a		)							,				1103		)


							def      _snake_case  (							self    :Union[str, Any]		)   ->   Optional[int]:



									"""simple docstring"""



									self.assertEqual(self.get_tokenizer().vocab_size							,				1103		)


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



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      self.rust_tokenizer_class.from_pretrained(self.tmpdirname		)
									SCREAMING_SNAKE_CASE__			=      self.tokenizer_class.from_pretrained(self.tmpdirname		)
									SCREAMING_SNAKE_CASE__			=      (
									    """Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"""
									    """ </s> <pad> <pad> <pad>"""
									)
									SCREAMING_SNAKE_CASE__			=      rust_tokenizer([raw_input_str]							,				return_tensors=_a							,				add_special_tokens=_a		).input_ids[0]
									SCREAMING_SNAKE_CASE__			=      py_tokenizer([raw_input_str]							,				return_tensors=_a							,				add_special_tokens=_a		).input_ids[0]
									self.assertListEqual(_a							,				_a		)


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



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer
									# <mask_1> masks whole sentence while <mask_2> masks single word
									SCREAMING_SNAKE_CASE__			=      """<mask_1> To ensure a <mask_2> flow of bank resolutions."""
									SCREAMING_SNAKE_CASE__			=      [2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
									SCREAMING_SNAKE_CASE__			=      tokenizer([raw_input_str]							,				return_tensors=_a		).input_ids[0]
									self.assertListEqual(_a							,				_a		)


							def      _snake_case  (							self    :Any		)   ->   List[str]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer
									# The tracebacks for the following asserts are **better** without messages or self.assertEqual
									assert tokenizer.vocab_size == 9_6103
									assert tokenizer.pad_token_id == 0
									assert tokenizer.eos_token_id == 1
									assert tokenizer.offset == 103
									assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
									assert tokenizer.unk_token == "<unk>"
									assert tokenizer.model_max_length == 1024
									SCREAMING_SNAKE_CASE__			=      """To ensure a smooth flow of bank resolutions."""
									SCREAMING_SNAKE_CASE__			=      [413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
									SCREAMING_SNAKE_CASE__			=      tokenizer([raw_input_str]							,				return_tensors=_a		).input_ids[0]
									self.assertListEqual(_a							,				_a		)
									assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]		) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]


							@require_torch
							def      _snake_case  (							self    :Tuple		)   ->   List[str]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      ["""This is going to be way too long.""" * 150, """short example"""]
									SCREAMING_SNAKE_CASE__			=      ["""not super long but more than 5 tokens""", """tiny"""]
									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer(_a							,				padding=_a							,				truncation=_a							,				return_tensors="""pt"""		)
									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer(
									    text_target=_a							,				max_length=5							,				padding=_a							,				truncation=_a							,				return_tensors="""pt"""		)

									assert batch.input_ids.shape == (2, 1024)
									assert batch.attention_mask.shape == (2, 1024)
									assert targets["input_ids"].shape == (2, 5)
									assert len(_a		) == 2  # input_ids, attention_mask.


							@slow
							def      _snake_case  (							self    :str		)   ->   Optional[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      {"""input_ids""": [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 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], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 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]], """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, 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], [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]]}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=_a							,				model_name="""google/bigbird-pegasus-large-arxiv"""							,				revision="""ba85d0851d708441f91440d509690f1ab6353415"""							,				)




@require_sentencepiece
@require_tokenizers
class   UpperCamelCase_       (     UpperCamelCase__				,  unittest.TestCase    ):
							lowerCamelCase_           =					PegasusTokenizer
							lowerCamelCase_           =					PegasusTokenizerFast
							lowerCamelCase_           =					True
							lowerCamelCase_           =					True


							def      _snake_case  (							self    :Optional[int]		)   ->   Optional[Any]:



									"""simple docstring"""



									super().setUp()

									# We have a SentencePiece fixture for testing
									SCREAMING_SNAKE_CASE__			=      PegasusTokenizer(_a							,				offset=0							,				mask_token_sent=_a							,				mask_token="""[MASK]"""		)
									tokenizer.save_pretrained(self.tmpdirname		)


							@cached_property
							def      _snake_case  (							self    :int		)   ->   Optional[Any]:



									"""simple docstring"""



									return PegasusTokenizer.from_pretrained("""google/bigbird-pegasus-large-arxiv"""		)


							def      _snake_case  (							self    :Dict							,				**__A    :Optional[int]		)   ->   PegasusTokenizer:



									"""simple docstring"""



									return PegasusTokenizer.from_pretrained(self.tmpdirname							,				**_a		)


							def      _snake_case  (							self    :Any							,				__A    :Dict		)   ->   List[str]:



									"""simple docstring"""



									return ("This is a test", "This is a test")


							def      _snake_case  (							self    :Tuple		)   ->   List[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      self.rust_tokenizer_class.from_pretrained(self.tmpdirname		)
									SCREAMING_SNAKE_CASE__			=      self.tokenizer_class.from_pretrained(self.tmpdirname		)
									SCREAMING_SNAKE_CASE__			=      (
									    """Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"""
									    """ <pad> <pad> <pad>"""
									)
									SCREAMING_SNAKE_CASE__			=      rust_tokenizer([raw_input_str]							,				return_tensors=_a							,				add_special_tokens=_a		).input_ids[0]
									SCREAMING_SNAKE_CASE__			=      py_tokenizer([raw_input_str]							,				return_tensors=_a							,				add_special_tokens=_a		).input_ids[0]
									self.assertListEqual(_a							,				_a		)


							@require_torch
							def      _snake_case  (							self    :Dict		)   ->   Optional[int]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      ["""This is going to be way too long.""" * 1000, """short example"""]
									SCREAMING_SNAKE_CASE__			=      ["""not super long but more than 5 tokens""", """tiny"""]
									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer(_a							,				padding=_a							,				truncation=_a							,				return_tensors="""pt"""		)
									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer(
									    text_target=_a							,				max_length=5							,				padding=_a							,				truncation=_a							,				return_tensors="""pt"""		)

									assert batch.input_ids.shape == (2, 4096)
									assert batch.attention_mask.shape == (2, 4096)
									assert targets["input_ids"].shape == (2, 5)
									assert len(_a		) == 2  # input_ids, attention_mask.


							def      _snake_case  (							self    :Optional[Any]		)   ->   Dict:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      (
									    """This is an example string that is used to test the original TF implementation against the HF"""
									    """ implementation"""
									)

									SCREAMING_SNAKE_CASE__			=      self._large_tokenizer(_a		).input_ids

									self.assertListEqual(
									    _a							,				[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1]							,				)






import warnings
from functools import wraps
from typing import Callable






def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							Callable    ):

		@wraps(UpperCamelCase__    )
		def _inner_fn(*UpperCamelCase__:							Dict					,   **UpperCamelCase__:							Any    ):
				warnings.warn(
				    (f'''\'{fn.__name__}\' is experimental and might be subject to breaking changes in the future.''')					,   UpperCamelCase__					,   )
				return fn(*UpperCamelCase__					,   **UpperCamelCase__    )

		return _inner_fn