




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


lowerCamelCase__					:  int      							=				get_tests_dir('fixtures/test_sentencepiece.model')

lowerCamelCase__					:  int      							=				{'target_lang': 'fi', 'source_lang': 'en'}
lowerCamelCase__					:  List[Any]      							=				'>>zh<<'
lowerCamelCase__					:  Optional[Any]      							=				'Helsinki-NLP/'

if is_torch_available():
   lowerCamelCase__					:  List[str]      							=				'pt'
elif is_tf_available():
   lowerCamelCase__					:  int      							=				'tf'
else:
   lowerCamelCase__					:  Tuple      							=				'jax'





@require_sentencepiece
class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       MarianTokenizer
 lowercase_							       =       False
 lowercase_							       =       True



 def  lowerCAmelCase_    (				self    :						Dict		):
       super().setUp()
       SCREAMING_SNAKE_CASE_      		=     ['</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est', '\u0120', '<pad>']
       SCREAMING_SNAKE_CASE_      		=     dict(zip(_lowerCAmelCase							,							range(len(_lowerCAmelCase		)		)		)		)
       SCREAMING_SNAKE_CASE_      		=     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']		)

       SCREAMING_SNAKE_CASE_      		=     MarianTokenizer.from_pretrained(self.tmpdirname		)
       tokenizer.save_pretrained(self.tmpdirname		)



 def  lowerCAmelCase_    (				self    :						List[Any]							,							**_lowerCAmelCase    :						int		):
       return MarianTokenizer.from_pretrained(self.tmpdirname							,							**_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Optional[Any]							,							_lowerCAmelCase    :						int		):
       return (
           "This is a test",
           "This is a test",
       )



 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     '</s>'
       SCREAMING_SNAKE_CASE_      		=     0

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



 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     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  lowerCAmelCase_    (				self    :						str		):
       self.assertEqual(self.get_tokenizer().vocab_size							,							9		)



 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     MarianTokenizer.from_pretrained(F"{ORG_NAME}opus-mt-en-de"		)
       SCREAMING_SNAKE_CASE_      		=     en_de_tokenizer(['I am a small frog']							,							return_tensors=_lowerCAmelCase		)
       self.assertIsInstance(_lowerCAmelCase							,							_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     [38, 121, 14, 697, 38_848, 0]
       self.assertListEqual(_lowerCAmelCase							,							batch.input_ids[0]		)

       SCREAMING_SNAKE_CASE_      		=     tempfile.mkdtemp()
       en_de_tokenizer.save_pretrained(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     [x.name for x in Path(_lowerCAmelCase		).glob('*'		)]
       self.assertIn('source.spm'							,							_lowerCAmelCase		)
       MarianTokenizer.from_pretrained(_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						int		):
       SCREAMING_SNAKE_CASE_      		=     self.get_tokenizer()

       SCREAMING_SNAKE_CASE_      		=     tok(
           ['I am a small frog' * 1_000, 'I am a small frog']							,							padding=_lowerCAmelCase							,							truncation=_lowerCAmelCase							,							return_tensors=_lowerCAmelCase		)
       self.assertIsInstance(_lowerCAmelCase							,							_lowerCAmelCase		)
       self.assertEqual(batch.input_ids.shape							,							(2, 512)		)



 def  lowerCAmelCase_    (				self    :						int		):
       SCREAMING_SNAKE_CASE_      		=     self.get_tokenizer()
       SCREAMING_SNAKE_CASE_      		=     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, 10)		)



 @slow
 def  lowerCAmelCase_    (				self    :						List[str]		):
       # fmt: off
       SCREAMING_SNAKE_CASE_      		=     {'input_ids': [[43_495, 462, 20, 42_164, 1_369, 52, 464, 132, 1_703, 492, 13, 7_491, 38_999, 6, 8, 464, 132, 1_703, 492, 13, 4_669, 37_867, 13, 7_525, 27, 1_593, 988, 13, 33_972, 7_029, 6, 20, 8_251, 383, 2, 270, 5_866, 3_788, 2, 2_353, 8_251, 12_338, 2, 13_958, 387, 2, 3_629, 6_953, 188, 2_900, 2, 13_958, 8_011, 11_501, 23, 8_460, 4_073, 34_009, 20, 435, 11_439, 27, 8, 8_460, 4_073, 6_004, 20, 9_988, 375, 27, 33, 266, 1_945, 1_076, 1_350, 37_867, 3_288, 5, 577, 1_076, 4_374, 8, 5_082, 5, 26_453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10_767, 6, 316, 304, 4_239, 3, 0], [148, 15_722, 19, 1_839, 12, 1_350, 13, 22_327, 5_082, 5_418, 47_567, 35_938, 59, 318, 19_552, 108, 2_183, 54, 14_976, 4_835, 32, 547, 1_114, 8, 315, 2_417, 5, 92, 19_088, 3, 0, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100], [36, 6_395, 12_570, 39_147, 11_597, 6, 266, 4, 45_405, 7_296, 3, 0, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100]], '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  lowerCAmelCase_    (				self    :						Tuple		):
       SCREAMING_SNAKE_CASE_      		=     MarianTokenizer.from_pretrained('hf-internal-testing/test-marian-two-vocabs'		)

       SCREAMING_SNAKE_CASE_      		=     'Tämä on testi'
       SCREAMING_SNAKE_CASE_      		=     'This is a test'

       SCREAMING_SNAKE_CASE_      		=     [76, 7, 2_047, 2]
       SCREAMING_SNAKE_CASE_      		=     [69, 12, 11, 940, 2]

       SCREAMING_SNAKE_CASE_      		=     tokenizer(_lowerCAmelCase		).input_ids
       self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer(text_target=_lowerCAmelCase		).input_ids
       self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.decode(_lowerCAmelCase							,							skip_special_tokens=_lowerCAmelCase		)
       self.assertEqual(_lowerCAmelCase							,							_lowerCAmelCase		)

from __future__ import annotations
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     list[int | float]			,							UpperCAmelCase_	:     int			,							UpperCAmelCase_	:     int				)			->						int | float:
       if len(UpperCAmelCase_				) == 0:
              raise ValueError('''find_max() arg is an empty sequence'''				)
       if (
           left >= len(UpperCAmelCase_				)
           or left < -len(UpperCAmelCase_				)
           or right >= len(UpperCAmelCase_				)
           or right < -len(UpperCAmelCase_				)
       ):
              raise IndexError('''list index out of range'''				)
       if left == right:
              return nums[left]
       SCREAMING_SNAKE_CASE_							:				Optional[int]		=(left + right) >> 1  # the middle
       SCREAMING_SNAKE_CASE_							:				Dict		=find_max(UpperCAmelCase_			,							UpperCAmelCase_			,							UpperCAmelCase_				)  # find max in range[left, mid]
       SCREAMING_SNAKE_CASE_							:				Dict		=find_max(UpperCAmelCase_			,							mid + 1			,							UpperCAmelCase_				)  # find max in range[mid + 1, right]

       return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)
