


import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase   :    int     =		"▁"

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







@require_sentencepiece
class        __lowercase       (							a_			,							unittest.TestCase  ):



		"""simple docstring"""

		UpperCamelCase     :					List[Any]			       =		BertGenerationTokenizer
		UpperCamelCase     :					int			       =		False
		UpperCamelCase     :					Optional[int]			       =		True







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







					'''simple docstring'''







					super().setUp()

					lowerCamelCase    		=  BertGenerationTokenizer(A		,      keep_accents=A	)
					tokenizer.save_pretrained(self.tmpdirname	)







		def 					__A   ( self	)  -> str:







					'''simple docstring'''







					lowerCamelCase    		=  """<s>"""
					lowerCamelCase    		=  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	)  -> Union[str, Any]:







					'''simple docstring'''







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

					self.assertEqual(vocab_keys[0]		,      """<unk>"""	)
					self.assertEqual(vocab_keys[1]		,      """<s>"""	)
					self.assertEqual(vocab_keys[-1]		,      """<pad>"""	)
					self.assertEqual(len(A	)		,      10_02	)







		def 					__A   ( self	)  -> List[str]:







					'''simple docstring'''







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







		def 					__A   ( self	)  -> str:







					'''simple docstring'''







					lowerCamelCase    		=  BertGenerationTokenizer(A		,      keep_accents=A	)

					lowerCamelCase    		=  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]		,      )

					lowerCamelCase    		=  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""",
					        """.""",
					    ]		,      )
					lowerCamelCase    		=  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]		,      )

					lowerCamelCase    		=  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>""",
					        """.""",
					    ]		,      )







		@cached_property
		def 					__A   ( self	)  -> Tuple:







					'''simple docstring'''







					return BertGenerationTokenizer.from_pretrained("""google/bert_for_seq_generation_L-24_bbc_encoder"""	)







		@slow
		def 					__A   ( self	)  -> Any:







					'''simple docstring'''







					lowerCamelCase    		=  """Hello World!"""
					lowerCamelCase    		=  [1_85_36, 22_60, 1_01]

					self.assertListEqual(A		,      self.big_tokenizer.encode(A	)	)







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







					'''simple docstring'''







					lowerCamelCase    		=  (
					    """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
					    """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
					)
					lowerCamelCase    		=  [
					    8_71,
					    4_19,
					    3_58,
					    9_46,
					    9_91,
					    25_21,
					    4_52,
					    3_58,
					    13_57,
					    3_87,
					    77_51,
					    35_36,
					    1_12,
					    9_85,
					    4_56,
					    1_26,
					    8_65,
					    9_38,
					    54_00,
					    57_34,
					    4_58,
					    13_68,
					    4_67,
					    7_86,
					    24_62,
					    52_46,
					    11_59,
					    6_33,
					    8_65,
					    45_19,
					    4_57,
					    5_82,
					    8_52,
					    25_57,
					    4_27,
					    9_16,
					    5_08,
					    4_05,
					    3_43_24,
					    4_97,
					    3_91,
					    4_08,
					    1_13_42,
					    12_44,
					    3_85,
					    1_00,
					    9_38,
					    9_85,
					    4_56,
					    5_74,
					    3_62,
					    1_25_97,
					    32_00,
					    31_29,
					    11_72,
					]

					self.assertListEqual(A		,      self.big_tokenizer.encode(A	)	)







		@require_torch
		@slow
		def 					__A   ( self	)  -> Tuple:







					'''simple docstring'''







					import torch

					from transformers import BertGenerationConfig, BertGenerationEncoder

					# Build sequence
					lowerCamelCase    		=  list(self.big_tokenizer.get_vocab().keys()	)[:10]
					lowerCamelCase    		=  """ """.join(A	)
					lowerCamelCase    		=  self.big_tokenizer.encode_plus(A		,      return_tensors="""pt"""		,      return_token_type_ids=A	)
					lowerCamelCase    		=  self.big_tokenizer.batch_encode_plus(
					    [sequence + """ """ + sequence]		,      return_tensors="""pt"""		,      return_token_type_ids=A	)

					lowerCamelCase    		=  BertGenerationConfig()
					lowerCamelCase    		=  BertGenerationEncoder(A	)

					assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

					with torch.no_grad():
								model(**A	)
								model(**A	)







		@slow
		def 					__A   ( self	)  -> Any:







					'''simple docstring'''







					lowerCamelCase    		=  {"""input_ids""": [[3_92_86, 4_58, 3_63_35, 20_01, 4_56, 1_30_73, 1_32_66, 4_55, 1_13, 77_46, 17_41, 1_11_57, 3_91, 1_30_73, 1_32_66, 4_55, 1_13, 39_67, 3_54_12, 1_13, 49_36, 1_09, 38_70, 23_77, 1_13, 3_00_84, 4_57_20, 4_58, 1_34, 1_74_96, 1_12, 5_03, 1_16_72, 1_13, 1_18, 1_12, 56_65, 1_33_47, 3_86_87, 1_12, 14_96, 3_13_89, 1_12, 32_68, 4_72_64, 1_34, 9_62, 1_12, 1_63_77, 80_35, 2_31_30, 4_30, 1_21_69, 1_55_18, 2_85_92, 4_58, 1_46, 4_16_97, 1_09, 3_91, 1_21_69, 1_55_18, 1_66_89, 4_58, 1_46, 4_13_58, 1_09, 4_52, 7_26, 40_34, 1_11, 7_63, 3_54_12, 50_82, 3_88, 19_03, 1_11, 90_51, 3_91, 28_70, 4_89_18, 19_00, 11_23, 5_50, 9_98, 1_12, 95_86, 1_59_85, 4_55, 3_91, 4_10, 2_29_55, 3_76_36, 1_14], [4_48, 1_74_96, 4_19, 36_63, 3_85, 7_63, 1_13, 2_75_33, 28_70, 32_83, 1_30_43, 16_39, 2_47_13, 5_23, 6_56, 2_40_13, 1_85_50, 25_21, 5_17, 2_70_14, 2_12_44, 4_20, 12_12, 14_65, 3_91, 9_27, 48_33, 3_88, 5_78, 1_17_86, 1_14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [4_84, 21_69, 76_87, 2_19_32, 1_81_46, 7_26, 3_63, 1_70_32, 33_91, 1_14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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], [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]]}  # noqa: E501
					# fmt: on

					self.tokenizer_integration_test_util(
					    expected_encoding=A		,      model_name="""google/bert_for_seq_generation_L-24_bbc_encoder"""		,      revision="""c817d1fd1be2ffa69431227a1fe320544943d4db"""		,      )





# Lint as: python3
import itertools
import os
import re


UpperCAmelCase   :    Any     =		re.compile(r"([A-Z]+)([A-Z][a-z])")
UpperCAmelCase   :    Optional[Any]     =		re.compile(r"([a-z\d])([A-Z])")

UpperCAmelCase   :    Optional[Any]     =		re.compile(r"(?<!_)_(?!_)")
UpperCAmelCase   :    Any     =		re.compile(r"(_{2,})")

UpperCAmelCase   :    List[Any]     =		r"^\w+(\.\w+)*$"

UpperCAmelCase   :    Any     =		r"<>:/\|?*"






def 	__lowerCamelCase						(							lowerCamelCase__		:						Tuple      ):





			'''simple docstring'''




			lowerCamelCase    		=  _uppercase_uppercase_re.sub(R"""\1_\2"""  ,							lowerCamelCase__      )
			lowerCamelCase    		=  _lowercase_uppercase_re.sub(R"""\1_\2"""  ,							lowerCamelCase__      )
			return name.lower()






def 	__lowerCamelCase						(							lowerCamelCase__		:						List[str]      ):





			'''simple docstring'''




			lowerCamelCase    		=  _single_underscore_re.split(lowerCamelCase__      )
			lowerCamelCase    		=  [_multiple_underscores_re.split(lowerCamelCase__      ) for n in name]
			return "".join(n.capitalize() for n in itertools.chain.from_iterable(lowerCamelCase__      ) if n != """"""      )






def 	__lowerCamelCase						(							lowerCamelCase__		:						Any      ):





			'''simple docstring'''




			if os.path.basename(lowerCamelCase__      ) != name:
						raise ValueError(f'Should be a dataset name, not a path: {name}'      )
			return camelcase_to_snakecase(lowerCamelCase__      )






def 	__lowerCamelCase						(							lowerCamelCase__		:						List[str]  ,							lowerCamelCase__		:						int      ):





			'''simple docstring'''




			if os.path.basename(lowerCamelCase__      ) != name:
						raise ValueError(f'Should be a dataset name, not a path: {name}'      )
			if not re.match(_split_re  ,							lowerCamelCase__      ):
						raise ValueError(f'Split name should match \'{_split_re}\'\' but got \'{split}\'.'      )
			return f'{filename_prefix_for_name(lowerCamelCase__      )}-{split}'






def 	__lowerCamelCase						(							lowerCamelCase__		:						List[Any]  ,							lowerCamelCase__		:						Optional[Any]  ,							lowerCamelCase__		:						List[Any]  ,							lowerCamelCase__		:						int=None      ):





			'''simple docstring'''




			lowerCamelCase    		=  filename_prefix_for_split(lowerCamelCase__  ,							lowerCamelCase__      )
			if filetype_suffix:
						prefix += f'.{filetype_suffix}'
			lowerCamelCase    		=  os.path.join(lowerCamelCase__  ,							lowerCamelCase__      )
			return f'{filepath}*'






def 	__lowerCamelCase						(							lowerCamelCase__		:						Dict  ,							lowerCamelCase__		:						List[Any]  ,							lowerCamelCase__		:						List[Any]  ,							lowerCamelCase__		:						int=None  ,							lowerCamelCase__		:						str=None      ):





			'''simple docstring'''




			lowerCamelCase    		=  filename_prefix_for_split(lowerCamelCase__  ,							lowerCamelCase__      )
			lowerCamelCase    		=  os.path.join(lowerCamelCase__  ,							lowerCamelCase__      )

			if shard_lengths:
						lowerCamelCase    		=  len(lowerCamelCase__      )
						lowerCamelCase    		=  [f'{prefix}-{shard_id:05d}-of-{num_shards:05d}' for shard_id in range(lowerCamelCase__      )]
						if filetype_suffix:
									lowerCamelCase    		=  [filename + f'.{filetype_suffix}' for filename in filenames]
						return filenames
			else:
						lowerCamelCase    		=  prefix
						if filetype_suffix:
									filename += f'.{filetype_suffix}'
						return [filename]

