

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


SCREAMING_SNAKE_CASE_            = '▁'

SCREAMING_SNAKE_CASE_            = get_tests_dir('fixtures/test_sentencepiece.model')

@require_sentencepiece
class 			a					(		UpperCAmelCase							,	unittest.TestCase			):
						_lowercase        =     BertGenerationTokenizer
						_lowercase        =     False
						_lowercase        =     True


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										super().setUp()

										_UpperCAmelCase    :						List[str]							=      BertGenerationTokenizer(__UpperCAmelCase  ,   keep_accents=__UpperCAmelCase		)
										tokenizer.save_pretrained(self.tmpdirname		)


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Any							=      "<s>"
										_UpperCAmelCase    :						str							=      1

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


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Any							=      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(__UpperCAmelCase		)  ,   1002		)


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										self.assertEqual(self.get_tokenizer().vocab_size  ,   1000		)


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[str]							=      BertGenerationTokenizer(__UpperCAmelCase  ,   keep_accents=__UpperCAmelCase		)

										_UpperCAmelCase    :						Union[str, Any]							=      tokenizer.tokenize("This is a test"		)
										self.assertListEqual(__UpperCAmelCase  ,   ["▁This", "▁is", "▁a", "▁t", "est"]		)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(__UpperCAmelCase		)  ,   [285, 46, 10, 170, 382]  ,   )

										_UpperCAmelCase    :						Dict							=      tokenizer.tokenize("I was born in 92000, and this is falsé."		)
										self.assertListEqual(
										    __UpperCAmelCase  ,   [
										        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    :						Tuple							=      tokenizer.convert_tokens_to_ids(__UpperCAmelCase		)
										self.assertListEqual(
										    __UpperCAmelCase  ,   [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]  ,   )

										_UpperCAmelCase    :						Optional[Any]							=      tokenizer.convert_ids_to_tokens(__UpperCAmelCase		)
										self.assertListEqual(
										    __UpperCAmelCase  ,   [
										        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     _UpperCAmelCase			(    self		):







										'''simple docstring'''


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


						@slow
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Optional[Any]							=      "Hello World!"
										_UpperCAmelCase    :						Optional[int]							=      [18536, 2260, 101]

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


						@slow
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[Any]							=      (
										    "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"
										)
										_UpperCAmelCase    :						Optional[Any]							=      [
										    871,
										    419,
										    358,
										    946,
										    991,
										    2521,
										    452,
										    358,
										    1357,
										    387,
										    7751,
										    3536,
										    112,
										    985,
										    456,
										    126,
										    865,
										    938,
										    5400,
										    5734,
										    458,
										    1368,
										    467,
										    786,
										    2462,
										    5246,
										    1159,
										    633,
										    865,
										    4519,
										    457,
										    582,
										    852,
										    2557,
										    427,
										    916,
										    508,
										    405,
										    34324,
										    497,
										    391,
										    408,
										    11342,
										    1244,
										    385,
										    100,
										    938,
										    985,
										    456,
										    574,
										    362,
										    12597,
										    3200,
										    3129,
										    1172,
										]

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


						@require_torch
						@slow
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										import torch

										from transformers import BertGenerationConfig, BertGenerationEncoder

										# Build sequence
										_UpperCAmelCase    :						Any							=      list(self.big_tokenizer.get_vocab().keys()		)[:10]
										_UpperCAmelCase    :						Optional[int]							=      " ".join(__UpperCAmelCase		)
										_UpperCAmelCase    :						Union[str, Any]							=      self.big_tokenizer.encode_plus(__UpperCAmelCase  ,   return_tensors="pt"  ,   return_token_type_ids=__UpperCAmelCase		)
										_UpperCAmelCase    :						Any							=      self.big_tokenizer.batch_encode_plus(
										    [sequence + " " + sequence]  ,   return_tensors="pt"  ,   return_token_type_ids=__UpperCAmelCase		)

										_UpperCAmelCase    :						Dict							=      BertGenerationConfig()
										_UpperCAmelCase    :						Optional[Any]							=      BertGenerationEncoder(__UpperCAmelCase		)

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

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





						@slow
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						int							=      {"input_ids": [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=__UpperCAmelCase  ,   model_name="google/bert_for_seq_generation_L-24_bbc_encoder"  ,   revision="c817d1fd1be2ffa69431227a1fe320544943d4db"  ,   )





def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					str					, lowerCAmelCase:					str	)				->    bool:
				_UpperCAmelCase    :						Optional[Any]							=      len(lowerCAmelCase	) + 1
				_UpperCAmelCase    :						Optional[int]							=      len(lowerCAmelCase	) + 1

				# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
				# length i of input_string matches with prefix string of length j of
				# given pattern.
				# "dp" stands for dynamic programming.
				_UpperCAmelCase    :						List[str]							=      [[0 for i in range(lowerCAmelCase	)] for j in range(lowerCAmelCase	)]

				# since string of zero length match pattern of zero length
				_UpperCAmelCase    :						List[Any]							=      1

				# since pattern of zero length will never match with string of non-zero length
				for i in range(1					, lowerCAmelCase	):
								_UpperCAmelCase    :						Dict							=      0

				# since string of zero length will match with pattern where there
				# is at least one * alternatively
				for j in range(1					, lowerCAmelCase	):
								_UpperCAmelCase    :						Tuple							=      dp[0][j - 2] if pattern[j - 1] == "*" else 0

				# now using bottom-up approach to find for all remaining lengths
				for i in range(1					, lowerCAmelCase	):
								for j in range(1					, lowerCAmelCase	):
												if input_string[i - 1] == pattern[j - 1] or pattern[j - 1] == ".":
																_UpperCAmelCase    :						Optional[Any]							=      dp[i - 1][j - 1]

												elif pattern[j - 1] == "*":
																if dp[i][j - 2] == 1:
																				_UpperCAmelCase    :						List[str]							=      1
																elif pattern[j - 2] in (input_string[i - 1], "."):
																				_UpperCAmelCase    :						str							=      dp[i - 1][j]
																else:
																				_UpperCAmelCase    :						int							=      0
												else:
																_UpperCAmelCase    :						List[Any]							=      0

				return bool(dp[-1][-1]	)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					# inputing the strings
					# input_string = input("input a string :")
					# pattern = input("input a pattern :")

					SCREAMING_SNAKE_CASE_            = 'aab'
					SCREAMING_SNAKE_CASE_            = 'c*a*b'

					# using function to check whether given string matches the given pattern
					if match_pattern(input_string, pattern):
										print(F'''{input_string} matches the given pattern {pattern}''')
					else:
										print(F'''{input_string} does not match with the given pattern {pattern}''')


