



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


lowercase_:  Dict     						=					get_tests_dir('fixtures/test_sentencepiece.model')

lowercase_:  int     						=					{'target_lang': 'fi', 'source_lang': 'en'}
lowercase_:  List[str]     						=					'>>zh<<'
lowercase_:  Tuple     						=					'Helsinki-NLP/'

if is_torch_available():
 lowercase_:  Any     						=					'pt'
elif is_tf_available():
 lowercase_:  Optional[int]     						=					'tf'
else:
 lowercase_:  List[str]     						=					'jax'



@require_sentencepiece
class 						lowercase__      (__snake_case						,      unittest.TestCase						):

     """simple docstring"""






     __UpperCamelCase    :	Optional[int]		=       MarianTokenizer
     __UpperCamelCase    :	Optional[int]		=       False
     __UpperCamelCase    :	Any		=       True


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

      snake_case__				:							str      							= MarianTokenizer.from_pretrained(self.tmpdirname )
      tokenizer.save_pretrained(self.tmpdirname )


     def 		lowercase   ( self :	Optional[int]   ,			**__a :	str ):
      return MarianTokenizer.from_pretrained(self.tmpdirname   ,			**lowerCamelCase__ )


     def 		lowercase   ( self :	List[str]   ,			__a :	Optional[Any] ):
      return (
          "This is a test",
          "This is a test",
      )


     def 		lowercase   ( self :	List[Any] ):
      snake_case__				:							Optional[int]      							= """</s>"""
      snake_case__				:							Optional[Any]      							= 0

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


     def 		lowercase   ( self :	List[Any] ):
      snake_case__				:							Union[str, Any]      							= 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(lowerCamelCase__ )   ,			9 )


     def 		lowercase   ( self :	Dict ):
      self.assertEqual(self.get_tokenizer().vocab_size   ,			9 )


     def 		lowercase   ( self :	Any ):
      snake_case__				:							int      							= MarianTokenizer.from_pretrained(f'{ORG_NAME}opus-mt-en-de' )
      snake_case__				:							int      							= en_de_tokenizer(["""I am a small frog"""]   ,			return_tensors=lowerCamelCase__ )
      self.assertIsInstance(lowerCamelCase__   ,			lowerCamelCase__ )
      snake_case__				:							Dict      							= [3_8, 1_2_1, 1_4, 6_9_7, 3_8_8_4_8, 0]
      self.assertListEqual(lowerCamelCase__   ,			batch.input_ids[0] )

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


     def 		lowercase   ( self :	str ):
      snake_case__				:							Any      							= self.get_tokenizer()

      snake_case__				:							Tuple      							= tok(
          ["""I am a small frog""" * 1_0_0_0, """I am a small frog"""]   ,			padding=lowerCamelCase__   ,			truncation=lowerCamelCase__   ,			return_tensors=lowerCamelCase__ )
      self.assertIsInstance(lowerCamelCase__   ,			lowerCamelCase__ )
      self.assertEqual(batch.input_ids.shape   ,			(2, 5_1_2) )


     def 		lowercase   ( self :	List[str] ):
      snake_case__				:							str      							= self.get_tokenizer()
      snake_case__				:							int      							= tok(["""I am a tiny frog""", """I am a small frog"""]   ,			padding=lowerCamelCase__   ,			return_tensors=lowerCamelCase__ )
      self.assertIsInstance(lowerCamelCase__   ,			lowerCamelCase__ )
      self.assertEqual(batch_smaller.input_ids.shape   ,			(2, 1_0) )


     @slow
     def 		lowercase   ( self :	Optional[int] ):
      snake_case__				:							Union[str, Any]      							= {"""input_ids""": [[4_3_4_9_5, 4_6_2, 2_0, 4_2_1_6_4, 1_3_6_9, 5_2, 4_6_4, 1_3_2, 1_7_0_3, 4_9_2, 1_3, 7_4_9_1, 3_8_9_9_9, 6, 8, 4_6_4, 1_3_2, 1_7_0_3, 4_9_2, 1_3, 4_6_6_9, 3_7_8_6_7, 1_3, 7_5_2_5, 2_7, 1_5_9_3, 9_8_8, 1_3, 3_3_9_7_2, 7_0_2_9, 6, 2_0, 8_2_5_1, 3_8_3, 2, 2_7_0, 5_8_6_6, 3_7_8_8, 2, 2_3_5_3, 8_2_5_1, 1_2_3_3_8, 2, 1_3_9_5_8, 3_8_7, 2, 3_6_2_9, 6_9_5_3, 1_8_8, 2_9_0_0, 2, 1_3_9_5_8, 8_0_1_1, 1_1_5_0_1, 2_3, 8_4_6_0, 4_0_7_3, 3_4_0_0_9, 2_0, 4_3_5, 1_1_4_3_9, 2_7, 8, 8_4_6_0, 4_0_7_3, 6_0_0_4, 2_0, 9_9_8_8, 3_7_5, 2_7, 3_3, 2_6_6, 1_9_4_5, 1_0_7_6, 1_3_5_0, 3_7_8_6_7, 3_2_8_8, 5, 5_7_7, 1_0_7_6, 4_3_7_4, 8, 5_0_8_2, 5, 2_6_4_5_3, 2_5_7, 5_5_6, 4_0_3, 2, 2_4_2, 1_3_2, 3_8_3, 3_1_6, 4_9_2, 8, 1_0_7_6_7, 6, 3_1_6, 3_0_4, 4_2_3_9, 3, 0], [1_4_8, 1_5_7_2_2, 1_9, 1_8_3_9, 1_2, 1_3_5_0, 1_3, 2_2_3_2_7, 5_0_8_2, 5_4_1_8, 4_7_5_6_7, 3_5_9_3_8, 5_9, 3_1_8, 1_9_5_5_2, 1_0_8, 2_1_8_3, 5_4, 1_4_9_7_6, 4_8_3_5, 3_2, 5_4_7, 1_1_1_4, 8, 3_1_5, 2_4_1_7, 5, 9_2, 1_9_0_8_8, 3, 0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0], [3_6, 6_3_9_5, 1_2_5_7_0, 3_9_1_4_7, 1_1_5_9_7, 6, 2_6_6, 4, 4_5_4_0_5, 7_2_9_6, 3, 0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_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, 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=lowerCamelCase__   ,			model_name="""Helsinki-NLP/opus-mt-en-de"""   ,			revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""   ,			decode_kwargs={"""use_source_tokenizer""": True}   ,			)


     def 		lowercase   ( self :	Dict ):
      snake_case__				:							Optional[int]      							= MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs""" )

      snake_case__				:							int      							= """Tämä on testi"""
      snake_case__				:							Optional[Any]      							= """This is a test"""

      snake_case__				:							Tuple      							= [7_6, 7, 2_0_4_7, 2]
      snake_case__				:							List[str]      							= [6_9, 1_2, 1_1, 9_4_0, 2]

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

      snake_case__				:							str      							= tokenizer(text_target=lowerCamelCase__ ).input_ids
      self.assertListEqual(lowerCamelCase__   ,			lowerCamelCase__ )

      snake_case__				:							Union[str, Any]      							= tokenizer.decode(lowerCamelCase__   ,			skip_special_tokens=lowerCamelCase__ )
      self.assertEqual(lowerCamelCase__   ,			lowerCamelCase__ )










def      lowerCamelCase_						(			UpperCamelCase__							: str					,	UpperCamelCase__							: int )	->			list:





				"""simple docstring"""


				__lowerCamelCase									=       word.split()

				def justify(UpperCamelCase__							: list					,	UpperCamelCase__							: int					,	UpperCamelCase__							: int ) -> str:
								__lowerCamelCase									=       max_width - width
								__lowerCamelCase									=       len(UpperCamelCase__ )
								if len(UpperCamelCase__ ) == 1:
												# if there is only word in line
												# just insert overall_spaces_count for the remainder of line
												return line[0] + " " * overall_spaces_count
								else:
												__lowerCamelCase									=       words_count - 1
												# num_spaces_between_words_list[i] : tells you to insert
												# num_spaces_between_words_list[i] spaces
												# after word on line[i]
												__lowerCamelCase									=       spaces_to_insert_between_words * [
												    overall_spaces_count // spaces_to_insert_between_words
												]
												__lowerCamelCase									=       (
												    overall_spaces_count % spaces_to_insert_between_words
												)
												# distribute spaces via round robin to the left words
												for i in range(UpperCamelCase__ ):
																num_spaces_between_words_list[i] += 1
												__lowerCamelCase									=       []
												for i in range(UpperCamelCase__ ):
																# add the word
																aligned_words_list.append(line[i] )
																# add the spaces to insert
																aligned_words_list.append(num_spaces_between_words_list[i] * ' ' )
												# just add the last word to the sentence
												aligned_words_list.append(line[-1] )
												# join the aligned words list to form a justified line
												return "".join(UpperCamelCase__ )

				__lowerCamelCase									=       []
				__lowerCamelCase									=       []
				__lowerCamelCase									=       0
				for word in words:
								if width + len(UpperCamelCase__ ) + len(UpperCamelCase__ ) <= max_width:
												# keep adding words until we can fill out max_width
												# width = sum of length of all words (without overall_spaces_count)
												# len(word) = length of current word
												# len(line) = number of overall_spaces_count to insert between words
												line.append(UpperCamelCase__ )
												width += len(UpperCamelCase__ )
								else:
												# justify the line and add it to result
												answer.append(justify(UpperCamelCase__					,	UpperCamelCase__					,	UpperCamelCase__ ) )
												# reset new line and new width
												__lowerCamelCase			,		__lowerCamelCase									=       [word], len(UpperCamelCase__ )
				__lowerCamelCase									=       max_width - width - len(UpperCamelCase__ )
				answer.append(' '.join(UpperCamelCase__ ) + (remaining_spaces + 1) * ' ' )
				return answer


if __name__ == "__main__":
					from doctest import testmod

					testmod()


