


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

lowerCAmelCase           =		{'''target_lang''': '''fi''', '''source_lang''': '''en'''}
lowerCAmelCase           =		'''>>zh<<'''
lowerCAmelCase           =		'''Helsinki-NLP/'''

if is_torch_available():
	lowerCAmelCase           =		'''pt'''
elif is_tf_available():
	lowerCAmelCase           =		'''tf'''
else:
	lowerCAmelCase           =		'''jax'''





@require_sentencepiece
class       A    (   A_					,				unittest.TestCase ):
							UpperCamelCase_   :							str       =MarianTokenizer
							UpperCamelCase_   :							Any       =False
							UpperCamelCase_   :							Optional[int]       =True


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

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


							def 			_A       (self      ,				**lowerCAmelCase					):
									return MarianTokenizer.from_pretrained(self.tmpdirname      ,				**lowerCAmelCase					)


							def 			_A       (self      ,				lowerCAmelCase					):
									return (
									    "This is a test",
									    "This is a test",
									)


							def 			_A       (self					):
									__lowercase=			'</s>'
									__lowercase=			0

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


							def 			_A       (self					):
									__lowercase=			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 			_A       (self					):
									self.assertEqual(self.get_tokenizer().vocab_size      ,				9					)


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

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


							def 			_A       (self					):
									__lowercase=			self.get_tokenizer()

									__lowercase=			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 			_A       (self					):
									__lowercase=			self.get_tokenizer()
									__lowercase=			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 			_A       (self					):
									# fmt: off
									__lowercase=			{'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 			_A       (self					):
									__lowercase=			MarianTokenizer.from_pretrained('hf-internal-testing/test-marian-two-vocabs'					)

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

									__lowercase=			[7_6, 7, 2_0_4_7, 2]
									__lowercase=			[6_9, 1_2, 1_1, 9_4_0, 2]

									__lowercase=			tokenizer(lowerCAmelCase					).input_ids
									self.assertListEqual(lowerCAmelCase      ,				lowerCAmelCase					)

									__lowercase=			tokenizer(text_target=lowerCAmelCase					).input_ids
									self.assertListEqual(lowerCAmelCase      ,				lowerCAmelCase					)

									__lowercase=			tokenizer.decode(lowerCAmelCase      ,				skip_special_tokens=lowerCAmelCase					)
									self.assertEqual(lowerCAmelCase      ,				lowerCAmelCase					)










from __future__ import annotations







def        _lowerCamelCase(	lowercase__	)						->	list[int]:

		'''simple docstring'''







		__lowercase=			2
		__lowercase=			[]
		while i * i <= n:
				if n % i:
						i += 1
				else:
						n //= i
						factors.append(lowercase__	)
		if n > 1:
				factors.append(lowercase__	)
		return factors


if __name__ == "__main__":
	import doctest

	doctest.testmod()






