






"""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


a			:    List[str]				 =		get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")


@require_sentencepiece
@require_tokenizers
class    __UpperCAmelCase(       SCREAMING_SNAKE_CASE__  ,  unittest.TestCase							):




						"""simple docstring"""




						__lowerCamelCase    	= PegasusTokenizer
						__lowerCamelCase    	= PegasusTokenizerFast
						__lowerCamelCase    	= True
						__lowerCamelCase    	= True




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												super().setUp()

												# We have a SentencePiece fixture for testing
												lowercase__    :				List[str]=	PegasusTokenizer(snake_case__      )
												tokenizer.save_pretrained(self.tmpdirname      )




						@cached_property
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return PegasusTokenizer.from_pretrained("google/pegasus-large"      )




						def 		UpperCAmelCase_	(       self	,  **snake_case__      ):
												'''simple docstring'''
												return PegasusTokenizer.from_pretrained(self.tmpdirname	,  **snake_case__      )




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												return ("This is a test", "This is a test")




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				int=	"</s>"
												lowercase__    :				List[Any]=	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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Dict=	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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												self.assertEqual(self.get_tokenizer().vocab_size	,  1103      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Tuple=	self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
												lowercase__    :				List[Any]=	self.tokenizer_class.from_pretrained(self.tmpdirname      )
												lowercase__    :				Optional[int]=	(
												    "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>"
												)
												lowercase__    :				Union[str, Any]=	rust_tokenizer([raw_input_str]	,  return_tensors=snake_case__	,  add_special_tokens=snake_case__      ).input_ids[0]
												lowercase__    :				Tuple=	py_tokenizer([raw_input_str]	,  return_tensors=snake_case__	,  add_special_tokens=snake_case__      ).input_ids[0]
												self.assertListEqual(snake_case__	,  snake_case__      )




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




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Optional[int]=	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
												lowercase__    :				Optional[int]=	"To ensure a smooth flow of bank resolutions."
												lowercase__    :				int=	[413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
												lowercase__    :				Union[str, Any]=	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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Any=	["This is going to be way too long." * 150, "short example"]
												lowercase__    :				Any=	["not super long but more than 5 tokens", "tiny"]
												lowercase__    :				Optional[int]=	self._large_tokenizer(snake_case__	,  padding=snake_case__	,  truncation=snake_case__	,  return_tensors="pt"      )
												lowercase__    :				Optional[int]=	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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												# fmt: off
												lowercase__    :				int=	{"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    __UpperCAmelCase(       SCREAMING_SNAKE_CASE__  ,  unittest.TestCase							):




						"""simple docstring"""




						__lowerCamelCase    	= PegasusTokenizer
						__lowerCamelCase    	= PegasusTokenizerFast
						__lowerCamelCase    	= True
						__lowerCamelCase    	= True




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												super().setUp()

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




						@cached_property
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return PegasusTokenizer.from_pretrained("google/bigbird-pegasus-large-arxiv"      )




						def 		UpperCAmelCase_	(       self	,  **snake_case__      ):
												'''simple docstring'''
												return PegasusTokenizer.from_pretrained(self.tmpdirname	,  **snake_case__      )




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												return ("This is a test", "This is a test")




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Optional[int]=	self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
												lowercase__    :				Union[str, Any]=	self.tokenizer_class.from_pretrained(self.tmpdirname      )
												lowercase__    :				List[Any]=	(
												    "Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"
												    " <pad> <pad> <pad>"
												)
												lowercase__    :				List[str]=	rust_tokenizer([raw_input_str]	,  return_tensors=snake_case__	,  add_special_tokens=snake_case__      ).input_ids[0]
												lowercase__    :				Dict=	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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[str]=	["This is going to be way too long." * 1000, "short example"]
												lowercase__    :				Dict=	["not super long but more than 5 tokens", "tiny"]
												lowercase__    :				int=	self._large_tokenizer(snake_case__	,  padding=snake_case__	,  truncation=snake_case__	,  return_tensors="pt"      )
												lowercase__    :				int=	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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Optional[Any]=	(
												    "This is an example string that is used to test the original TF implementation against the HF"
												    " implementation"
												)

												lowercase__    :				Tuple=	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]	,  )














"""simple docstring"""







from __future__ import annotations





def 						lowercase__(A						)    ->int:




						"""simple docstring"""



						for i in range(1 ,		len(matrix[0]						)						):
												matrix[0][i] += matrix[0][i - 1]

						# preprocessing the first column
						for i in range(1 ,		len(A						)						):
												matrix[i][0] += matrix[i - 1][0]

						# updating the path cost for current position
						for i in range(1 ,		len(A						)						):
												for j in range(1 ,		len(matrix[0]						)						):
																		matrix[i][j] += min(matrix[i - 1][j] ,		matrix[i][j - 1]						)

						return matrix[-1][-1]


if __name__ == "__main__":
			import doctest

			doctest.testmod()






