






"""simple docstring"""







import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
			from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


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

a			:    str				 =		{"""target_lang""": """fi""", """source_lang""": """en"""}
a			:    str				 =		""">>zh<<"""
a			:    Optional[Any]				 =		"""Helsinki-NLP/"""

if is_torch_available():
			a			:    List[str]				 =		"""pt"""
elif is_tf_available():
			a			:    Union[str, Any]				 =		"""tf"""
else:
			a			:    Optional[int]				 =		"""jax"""


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




						"""simple docstring"""




						__lowerCamelCase    	= MarianTokenizer
						__lowerCamelCase    	= False
						__lowerCamelCase    	= True




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												super().setUp()
												lowercase__    :				Any=	["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
												lowercase__    :				Any=	dict(zip(snake_case__	,  range(len(snake_case__      )      )      )      )
												lowercase__    :				Tuple=	Path(self.tmpdirname      )
												save_json(snake_case__	,  save_dir / VOCAB_FILES_NAMES["vocab"]      )
												save_json(snake_case__	,  save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"]      )
												if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
																		copyfile(snake_case__	,  save_dir / VOCAB_FILES_NAMES["source_spm"]      )
																		copyfile(snake_case__	,  save_dir / VOCAB_FILES_NAMES["target_spm"]      )

												lowercase__    :				Any=	MarianTokenizer.from_pretrained(self.tmpdirname      )
												tokenizer.save_pretrained(self.tmpdirname      )




						def 		UpperCAmelCase_	(       self	,  **snake_case__      ):
												'''simple docstring'''
												return MarianTokenizer.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__    :				Dict=	"</s>"
												lowercase__    :				Tuple=	0

												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__    :				int=	list(self.get_tokenizer().get_vocab().keys()      )

												self.assertEqual(vocab_keys[0]	,  "</s>"      )
												self.assertEqual(vocab_keys[1]	,  "<unk>"      )
												self.assertEqual(vocab_keys[-1]	,  "<pad>"      )
												self.assertEqual(len(snake_case__      )	,  9      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												self.assertEqual(self.get_tokenizer().vocab_size	,  9      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[str]=	MarianTokenizer.from_pretrained(F'''{ORG_NAME}opus-mt-en-de'''      )
												lowercase__    :				Union[str, Any]=	en_de_tokenizer(["I am a small frog"]	,  return_tensors=snake_case__      )
												self.assertIsInstance(snake_case__	,  snake_case__      )
												lowercase__    :				Optional[Any]=	[38, 121, 14, 697, 38848, 0]
												self.assertListEqual(snake_case__	,  batch.input_ids[0]      )

												lowercase__    :				List[Any]=	tempfile.mkdtemp()
												en_de_tokenizer.save_pretrained(snake_case__      )
												lowercase__    :				Optional[Any]=	[x.name for x in Path(snake_case__      ).glob("*"      )]
												self.assertIn("source.spm"	,  snake_case__      )
												MarianTokenizer.from_pretrained(snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				str=	self.get_tokenizer()

												lowercase__    :				List[Any]=	tok(
												    ["I am a small frog" * 1000, "I am a small frog"]	,  padding=snake_case__	,  truncation=snake_case__	,  return_tensors=snake_case__      )
												self.assertIsInstance(snake_case__	,  snake_case__      )
												self.assertEqual(batch.input_ids.shape	,  (2, 512)      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[Any]=	self.get_tokenizer()
												lowercase__    :				List[Any]=	tok(["I am a tiny frog", "I am a small frog"]	,  padding=snake_case__	,  return_tensors=snake_case__      )
												self.assertIsInstance(snake_case__	,  snake_case__      )
												self.assertEqual(batch_smaller.input_ids.shape	,  (2, 10)      )




						@slow
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												# fmt: off
												lowercase__    :				Any=	{"input_ids": [[43495, 462, 20, 42164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 38999, 6, 8, 464, 132, 1703, 492, 13, 4669, 37867, 13, 7525, 27, 1593, 988, 13, 33972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 12338, 2, 13958, 387, 2, 3629, 6953, 188, 2900, 2, 13958, 8011, 11501, 23, 8460, 4073, 34009, 20, 435, 11439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 37867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 26453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10767, 6, 316, 304, 4239, 3, 0], [148, 15722, 19, 1839, 12, 1350, 13, 22327, 5082, 5418, 47567, 35938, 59, 318, 19552, 108, 2183, 54, 14976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 19088, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100], [36, 6395, 12570, 39147, 11597, 6, 266, 4, 45405, 7296, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100]], "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, 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], [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, 0, 0, 0, 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="Helsinki-NLP/opus-mt-en-de"	,  revision="1a8c2263da11e68e50938f97e10cd57820bd504c"	,  decode_kwargs={"use_source_tokenizer": True}	,  )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				int=	MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs"      )

												lowercase__    :				Dict=	"Tämä on testi"
												lowercase__    :				Tuple=	"This is a test"

												lowercase__    :				Dict=	[76, 7, 2047, 2]
												lowercase__    :				List[Any]=	[69, 12, 11, 940, 2]

												lowercase__    :				Dict=	tokenizer(snake_case__      ).input_ids
												self.assertListEqual(snake_case__	,  snake_case__      )

												lowercase__    :				List[str]=	tokenizer(text_target=snake_case__      ).input_ids
												self.assertListEqual(snake_case__	,  snake_case__      )

												lowercase__    :				Optional[int]=	tokenizer.decode(snake_case__	,  skip_special_tokens=snake_case__      )
												self.assertEqual(snake_case__	,  snake_case__      )














"""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()






