"""simple docstring"""




import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class       a_      (     __a ,		unittest.TestCase			):
					UpperCamelCase_ :	Dict			=    None
					UpperCamelCase_ :	List[Any]			=    BloomTokenizerFast
					UpperCamelCase_ :	str			=    BloomTokenizerFast
					UpperCamelCase_ :	Optional[Any]			=    True
					UpperCamelCase_ :	Optional[Any]			=    False
					UpperCamelCase_ :	Optional[Any]			=    "tokenizer_file"
					UpperCamelCase_ :	Optional[Any]			=    {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]     ):
							super().setUp()
							lowerCAmelCase__        =   BloomTokenizerFast.from_pretrained("""bigscience/tokenizer"""     )
							tokenizer.save_pretrained(self.tmpdirname     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Tuple  ,						**snake_case__						:     Dict     ):
							kwargs.update(self.special_tokens_map     )
							return BloomTokenizerFast.from_pretrained(self.tmpdirname  ,						**A__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     int     ):
							lowerCAmelCase__        =   self.get_rust_tokenizer()

							lowerCAmelCase__        =   ["""The quick brown fox</s>""", """jumps over the lazy dog</s>"""]
							lowerCAmelCase__        =   [[2175, 23714, 73173, 144252, 2], [77, 132619, 3478, 368, 109586, 35433, 2]]

							lowerCAmelCase__        =   tokenizer.batch_encode_plus(A__     )["""input_ids"""]
							self.assertListEqual(A__  ,						A__     )

							lowerCAmelCase__        =   tokenizer.batch_decode(A__     )
							self.assertListEqual(A__  ,						A__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]  ,						snake_case__						:     List[str]=6     ):
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
											lowerCAmelCase__        =   self.rust_tokenizer_class.from_pretrained(A__  ,						**A__     )
											# tokenizer_r.pad_token = None # Hotfixing padding = None
											# Simple input
											lowerCAmelCase__        =   """This is a simple input"""
											lowerCAmelCase__        =   ["""This is a simple input 1""", """This is a simple input 2"""]
											lowerCAmelCase__        =   ("""This is a simple input""", """This is a pair""")
											lowerCAmelCase__        =   [
											    ("""This is a simple input 1""", """This is a simple input 2"""),
											    ("""This is a simple pair 1""", """This is a simple pair 2"""),
											]

											# Simple input tests
											try:
													tokenizer_r.encode(A__  ,						max_length=A__     )
													tokenizer_r.encode_plus(A__  ,						max_length=A__     )

													tokenizer_r.batch_encode_plus(A__  ,						max_length=A__     )
													tokenizer_r.encode(A__  ,						max_length=A__     )
													tokenizer_r.batch_encode_plus(A__  ,						max_length=A__     )
											except ValueError:
													self.fail("""Bloom Tokenizer should be able to deal with padding"""     )

											lowerCAmelCase__        =   None  # Hotfixing padding = None
											self.assertRaises(A__  ,						tokenizer_r.encode  ,						A__  ,						max_length=A__  ,						padding="""max_length"""     )

											# Simple input
											self.assertRaises(A__  ,						tokenizer_r.encode_plus  ,						A__  ,						max_length=A__  ,						padding="""max_length"""     )

											# Simple input
											self.assertRaises(
											    A__  ,						tokenizer_r.batch_encode_plus  ,						A__  ,						max_length=A__  ,						padding="""max_length"""  ,						)

											# Pair input
											self.assertRaises(A__  ,						tokenizer_r.encode  ,						A__  ,						max_length=A__  ,						padding="""max_length"""     )

											# Pair input
											self.assertRaises(A__  ,						tokenizer_r.encode_plus  ,						A__  ,						max_length=A__  ,						padding="""max_length"""     )

											# Pair input
											self.assertRaises(
											    A__  ,						tokenizer_r.batch_encode_plus  ,						A__  ,						max_length=A__  ,						padding="""max_length"""  ,						)




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]     ):
							lowerCAmelCase__        =   self.get_rust_tokenizer()
							lowerCAmelCase__        =   load_dataset("""xnli"""  ,						"""all_languages"""  ,						split="""test"""  ,						streaming=A__     )

							lowerCAmelCase__        =   next(iter(A__     )     )["""premise"""]  # pick up one data
							lowerCAmelCase__        =   list(sample_data.values()     )

							lowerCAmelCase__        =   list(map(tokenizer.encode  ,						A__     )     )
							lowerCAmelCase__        =   [tokenizer.decode(A__  ,						clean_up_tokenization_spaces=A__     ) for x in output_tokens]
							self.assertListEqual(A__  ,						A__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Any     ):
							# The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
							# any sequence length constraints. This test of the parent class will fail since it relies on the
							# maximum sequence length of the positoonal embeddings.
							self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map     )  ,						1     )
							self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()     )[0]     )  ,						1     )





"""simple docstring"""




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    :							Optional[Any]													=						get_tests_dir("fixtures/test_sentencepiece_no_bos.model")

@require_sentencepiece
@require_tokenizers
class       a_      (     __UpperCamelCase ,		unittest.TestCase			):
					UpperCamelCase_ :	Tuple			=    PegasusTokenizer
					UpperCamelCase_ :	Any			=    PegasusTokenizerFast
					UpperCamelCase_ :	int			=    True
					UpperCamelCase_ :	Any			=    True




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Tuple     ):
							super().setUp()

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




					@cached_property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]     ):
							return PegasusTokenizer.from_pretrained("""google/pegasus-large"""     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]  ,						**snake_case__						:     Optional[Any]     ):
							return PegasusTokenizer.from_pretrained(self.tmpdirname  ,						**snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Tuple  ,						snake_case__						:     Optional[Any]     ):
							return ("This is a test", "This is a test")




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Optional[Any]     ):
							lowerCAmelCase__        =   """</s>"""
							lowerCAmelCase__        =   1

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




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Union[str, Any]     ):
							lowerCAmelCase__        =   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(snake_case__     )  ,						1103     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Any     ):
							self.assertEqual(self.get_tokenizer().vocab_size  ,						1103     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Dict     ):
							lowerCAmelCase__        =   self.rust_tokenizer_class.from_pretrained(self.tmpdirname     )
							lowerCAmelCase__        =   self.tokenizer_class.from_pretrained(self.tmpdirname     )
							lowerCAmelCase__        =   (
							    """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>"""
							)
							lowerCAmelCase__        =   rust_tokenizer([raw_input_str]  ,						return_tensors=snake_case__  ,						add_special_tokens=snake_case__     ).input_ids[0]
							lowerCAmelCase__        =   py_tokenizer([raw_input_str]  ,						return_tensors=snake_case__  ,						add_special_tokens=snake_case__     ).input_ids[0]
							self.assertListEqual(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     Dict     ):
							lowerCAmelCase__        =   self._large_tokenizer
							# <mask_1> masks whole sentence while <mask_2> masks single word
							lowerCAmelCase__        =   """<mask_1> To ensure a <mask_2> flow of bank resolutions."""
							lowerCAmelCase__        =   [2, 413, 615, 114, 3, 1971, 113, 1679, 10710, 107, 1]
							lowerCAmelCase__        =   tokenizer([raw_input_str]  ,						return_tensors=snake_case__     ).input_ids[0]
							self.assertListEqual(snake_case__  ,						snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     int     ):
							lowerCAmelCase__        =   self._large_tokenizer
							# The tracebacks for the following asserts are **better** without messages or self.assertEqual
							assert tokenizer.vocab_size == 96103
							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
							lowerCAmelCase__        =   """To ensure a smooth flow of bank resolutions."""
							lowerCAmelCase__        =   [413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
							lowerCAmelCase__        =   tokenizer([raw_input_str]  ,						return_tensors=snake_case__     ).input_ids[0]
							self.assertListEqual(snake_case__  ,						snake_case__     )
							assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]     ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]




					@require_torch
					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]     ):
							lowerCAmelCase__        =   ["""This is going to be way too long.""" * 150, """short example"""]
							lowerCAmelCase__        =   ["""not super long but more than 5 tokens""", """tiny"""]
							lowerCAmelCase__        =   self._large_tokenizer(snake_case__  ,						padding=snake_case__  ,						truncation=snake_case__  ,						return_tensors="""pt"""     )
							lowerCAmelCase__        =   self._large_tokenizer(
							    text_target=snake_case__  ,						max_length=5  ,						padding=snake_case__  ,						truncation=snake_case__  ,						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(snake_case__     ) == 2  # input_ids, attention_mask.




					@slow
					def 						_SCREAMING_SNAKE_CASE						(	self						:     str     ):
							# fmt: off
							lowerCAmelCase__        =   {"""input_ids""": [[38979, 143, 18485, 606, 130, 26669, 87686, 121, 54189, 1129, 111, 26669, 87686, 121, 9114, 14787, 121, 13249, 158, 592, 956, 121, 14621, 31576, 143, 62613, 108, 9688, 930, 43430, 11562, 62613, 304, 108, 11443, 897, 108, 9314, 17415, 63399, 108, 11443, 7614, 18316, 118, 4284, 7148, 12430, 143, 1400, 25703, 158, 111, 4284, 7148, 11772, 143, 21297, 1064, 158, 122, 204, 3506, 1754, 1133, 14787, 1581, 115, 33224, 4482, 111, 1355, 110, 29173, 317, 50833, 108, 20147, 94665, 111, 77198, 107, 1], [110, 62613, 117, 638, 112, 1133, 121, 20098, 1355, 79050, 13872, 135, 1596, 53541, 1352, 141, 13039, 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, 18289, 17780, 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=snake_case__  ,						model_name="""google/bigbird-pegasus-large-arxiv"""  ,						revision="""ba85d0851d708441f91440d509690f1ab6353415"""  ,						)

@require_sentencepiece
@require_tokenizers
class       a_      (     __UpperCamelCase ,		unittest.TestCase			):
					UpperCamelCase_ :	str			=    PegasusTokenizer
					UpperCamelCase_ :	Optional[int]			=    PegasusTokenizerFast
					UpperCamelCase_ :	Union[str, Any]			=    True
					UpperCamelCase_ :	Optional[int]			=    True




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[str]     ):
							super().setUp()

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




					@cached_property
					def 						_SCREAMING_SNAKE_CASE						(	self						:     Dict     ):
							return PegasusTokenizer.from_pretrained("""google/bigbird-pegasus-large-arxiv"""     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]  ,						**snake_case__						:     List[Any]     ):
							return PegasusTokenizer.from_pretrained(self.tmpdirname  ,						**snake_case__     )




					def 						_SCREAMING_SNAKE_CASE						(	self						:     str  ,						snake_case__						:     Dict     ):
							return ("This is a test", "This is a test")




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




					@require_torch
					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]     ):
							lowerCAmelCase__        =   ["""This is going to be way too long.""" * 1000, """short example"""]
							lowerCAmelCase__        =   ["""not super long but more than 5 tokens""", """tiny"""]
							lowerCAmelCase__        =   self._large_tokenizer(snake_case__  ,						padding=snake_case__  ,						truncation=snake_case__  ,						return_tensors="""pt"""     )
							lowerCAmelCase__        =   self._large_tokenizer(
							    text_target=snake_case__  ,						max_length=5  ,						padding=snake_case__  ,						truncation=snake_case__  ,						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(snake_case__     ) == 2  # input_ids, attention_mask.




					def 						_SCREAMING_SNAKE_CASE						(	self						:     List[Any]     ):
							lowerCAmelCase__        =   (
							    """This is an example string that is used to test the original TF implementation against the HF"""
							    """ implementation"""
							)

							lowerCAmelCase__        =   self._large_tokenizer(snake_case__     ).input_ids

							self.assertListEqual(
							    snake_case__  ,						[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 25016, 3137, 464, 109, 26955, 3137, 1]  ,						)




