



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


A__	      =       get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")





@require_sentencepiece
@require_tokenizers
class 					__lowerCAmelCase (     lowerCamelCase__       ,						unittest.TestCase       ):
				__lowerCamelCase =				PegasusTokenizer
				__lowerCamelCase =				PegasusTokenizerFast
				__lowerCamelCase =				True
				__lowerCamelCase =				True




				def 							snake_case   (							self		):



									"""simple docstring"""





									super().setUp()

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




				@cached_property
				def 							snake_case   (							self		):



									"""simple docstring"""





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




				def 							snake_case   (							self						,				**_snake_case		):



									"""simple docstring"""





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




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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 					__lowerCAmelCase (     lowerCamelCase__       ,						unittest.TestCase       ):
				__lowerCamelCase =				PegasusTokenizer
				__lowerCamelCase =				PegasusTokenizerFast
				__lowerCamelCase =				True
				__lowerCamelCase =				True




				def 							snake_case   (							self		):



									"""simple docstring"""





									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 							snake_case   (							self		):



									"""simple docstring"""





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




				def 							snake_case   (							self						,				**_snake_case		):



									"""simple docstring"""





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




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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 							snake_case   (							self		):



									"""simple docstring"""





									_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]						,				)








import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_snake_case		=  get_tests_dir("fixtures/test_sentencepiece_bpe.model")



class   UpperCAmelCase_    (       a   ,					unittest.TestCase):
							lowerCamelCase__   			=		BartphoTokenizer
							lowerCamelCase__   			=		False
							lowerCamelCase__   			=		True







							def    snake_case__      (   self):

														'''simple docstring'''

														super().setUp()

														_lowerCAmelCase     :							str    =    ["▁This", "▁is", "▁a", "▁t", "est"]
														_lowerCAmelCase     :							List[str]    =    dict(zip(__a,			range(len(__a))))
														_lowerCAmelCase     :							Optional[Any]    =    {"unk_token": "<unk>"}

														_lowerCAmelCase     :							Optional[int]    =    os.path.join(self.tmpdirname,			VOCAB_FILES_NAMES["monolingual_vocab_file"])
														with open(self.monolingual_vocab_file,			"w",			encoding="utf-8") as fp:
																					for token in vocab_tokens:
																												fp.write(f"{token} {vocab_tokens[token]}\n")

														_lowerCAmelCase     :							Optional[Any]    =    BartphoTokenizer(__a,			self.monolingual_vocab_file,			**self.special_tokens_map)
														tokenizer.save_pretrained(self.tmpdirname)







							def    snake_case__      (   self,			**__a):

														'''simple docstring'''

														kwargs.update(self.special_tokens_map)
														return BartphoTokenizer.from_pretrained(self.tmpdirname,			**__a)







							def    snake_case__      (   self,			__a):

														'''simple docstring'''

														_lowerCAmelCase     :							Union[str, Any]    =    "This is a là test"
														_lowerCAmelCase     :							Optional[int]    =    "This is a<unk><unk> test"
														return input_text, output_text







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[int]    =    BartphoTokenizer(__a,			self.monolingual_vocab_file,			**self.special_tokens_map)
														_lowerCAmelCase     :							List[Any]    =    "This is a là test"
														_lowerCAmelCase     :							str    =    "▁This ▁is ▁a ▁l à ▁t est".split()
														_lowerCAmelCase     :							str    =    tokenizer.tokenize(__a)
														self.assertListEqual(__a,			__a)

														_lowerCAmelCase     :							Tuple    =    tokens + [tokenizer.unk_token]
														_lowerCAmelCase     :							List[str]    =    [4, 5, 6, 3, 3, 7, 8, 3]
														self.assertListEqual(tokenizer.convert_tokens_to_ids(__a),			__a)
