






from ...configuration_utils import PretrainedConfig


class     _a							(	UpperCAmelCase__     ):






  """simple docstring"""





  A_						       = """bert-generation"""




  def __init__(  self		,		_UpperCAmelCase=50358		,		_UpperCAmelCase=1024		,		_UpperCAmelCase=24		,		_UpperCAmelCase=16		,		_UpperCAmelCase=4096		,		_UpperCAmelCase="gelu"		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=512		,		_UpperCAmelCase=0.0_2		,		_UpperCAmelCase=1e-12		,		_UpperCAmelCase=0		,		_UpperCAmelCase=2		,		_UpperCAmelCase=1		,		_UpperCAmelCase="absolute"		,		_UpperCAmelCase=True		,		**_UpperCAmelCase		,		)      ->			Optional[int]:
     super().__init__(pad_token_id=_UpperCAmelCase		,		bos_token_id=_UpperCAmelCase		,		eos_token_id=_UpperCAmelCase		,		**_UpperCAmelCase			)

     UpperCamelCase_						=  vocab_size
     UpperCamelCase_						=  hidden_size
     UpperCamelCase_						=  num_hidden_layers
     UpperCamelCase_						=  num_attention_heads
     UpperCamelCase_						=  hidden_act
     UpperCamelCase_						=  intermediate_size
     UpperCamelCase_						=  hidden_dropout_prob
     UpperCamelCase_						=  attention_probs_dropout_prob
     UpperCamelCase_						=  max_position_embeddings
     UpperCamelCase_						=  initializer_range
     UpperCamelCase_						=  layer_norm_eps
     UpperCamelCase_						=  position_embedding_type
     UpperCamelCase_						=  use_cache






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[Any]            =    get_tests_dir("""fixtures/test_sentencepiece.model""")

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

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

@require_sentencepiece
class 					_lowercase    (     UpperCAmelCase__ ,  unittest.TestCase			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				str          =    MarianTokenizer
    SCREAMING_SNAKE_CASE:				Tuple          =    False
    SCREAMING_SNAKE_CASE:				Optional[int]          =    True




    def      _a    (    self ):
       super().setUp()
       lowerCAmelCase_:							Optional[Any]       =	["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
       lowerCAmelCase_:							Optional[Any]       =	dict(zip(lowerCamelCase__       ,						range(len(lowerCamelCase__ ) ) ) )
       lowerCAmelCase_:							Any       =	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"] )

       lowerCAmelCase_:							Any       =	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 ):
       lowerCAmelCase_:							Optional[Any]       =	"</s>"
       lowerCAmelCase_:							Tuple       =	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 ):
       lowerCAmelCase_:							Dict       =	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 ):
       lowerCAmelCase_:							Union[str, Any]       =	MarianTokenizer.from_pretrained(F'''{ORG_NAME}opus-mt-en-de''' )
       lowerCAmelCase_:							List[str]       =	en_de_tokenizer(["I am a small frog"]       ,						return_tensors=lowerCamelCase__ )
       self.assertIsInstance(lowerCamelCase__       ,						lowerCamelCase__ )
       lowerCAmelCase_:							List[Any]       =	[38, 121, 14, 697, 38_848, 0]
       self.assertListEqual(lowerCamelCase__       ,						batch.input_ids[0] )

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




    def      _a    (    self ):
       lowerCAmelCase_:							Union[str, Any]       =	self.get_tokenizer()

       lowerCAmelCase_:							Tuple       =	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      _a    (    self ):
       lowerCAmelCase_:							str       =	self.get_tokenizer()
       lowerCAmelCase_:							List[Any]       =	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      _a    (    self ):
       # fmt: off
       lowerCAmelCase_:							int       =	{"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      _a    (    self ):
       lowerCAmelCase_:							Dict       =	MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs" )

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

       lowerCAmelCase_:							List[str]       =	[76, 7, 2_047, 2]
       lowerCAmelCase_:							str       =	[69, 12, 11, 940, 2]

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

       lowerCAmelCase_:							List[Any]       =	tokenizer(text_target=lowerCamelCase__ ).input_ids
       self.assertListEqual(lowerCamelCase__       ,						lowerCamelCase__ )

       lowerCAmelCase_:							Any       =	tokenizer.decode(lowerCamelCase__       ,						skip_special_tokens=lowerCamelCase__ )
       self.assertEqual(lowerCamelCase__       ,						lowerCamelCase__ )