




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__			:       Any         =							{'target_lang': 'fi', 'source_lang': 'en'}
lowerCamelCase__			:       str         =							'>>zh<<'
lowerCamelCase__			:       Dict         =							'Helsinki-NLP/'

if is_torch_available():
   lowerCamelCase__			:       Tuple         =							'pt'
elif is_tf_available():
   lowerCamelCase__			:       Optional[int]         =							'tf'
else:
   lowerCamelCase__			:       Union[str, Any]         =							'jax'





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


 '''simple docstring'''







 lowercase_       =   MarianTokenizer
 lowercase_       =   False
 lowercase_       =   True



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

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



 def 				lowerCAmelCase_  (							self  :		Tuple    ,    **_lowerCAmelCase  :		int						):
       return MarianTokenizer.from_pretrained(self.tmpdirname    ,    **lowercase_						)



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



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      '</s>'
       SCREAMING_SNAKE_CASE_     						=      0

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



 def 				lowerCAmelCase_  (							self  :		str						):
       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(lowercase_						)    ,    9						)



 def 				lowerCAmelCase_  (							self  :		List[str]						):
       self.assertEqual(self.get_tokenizer().vocab_size    ,    9						)



 def 				lowerCAmelCase_  (							self  :		List[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=lowercase_						)
       self.assertIsInstance(lowercase_    ,    lowercase_						)
       SCREAMING_SNAKE_CASE_     						=      [38, 121, 14, 697, 38_848, 0]
       self.assertListEqual(lowercase_    ,    batch.input_ids[0]						)

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



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

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



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      tok(['I am a tiny frog', 'I am a small frog']    ,    padding=lowercase_    ,    return_tensors=lowercase_						)
       self.assertIsInstance(lowercase_    ,    lowercase_						)
       self.assertEqual(batch_smaller.input_ids.shape    ,    (2, 10)						)



 @slow
 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       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=lowercase_    ,    model_name='Helsinki-NLP/opus-mt-en-de'    ,    revision='1a8c2263da11e68e50938f97e10cd57820bd504c'    ,    decode_kwargs={'use_source_tokenizer': True}    ,    )




 def 				lowerCAmelCase_  (							self  :		int						):
       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(lowercase_						).input_ids
       self.assertListEqual(lowercase_    ,    lowercase_						)

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

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





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase__			:       Dict         =							logging.get_logger(__name__)

lowerCamelCase__			:       Any         =							{
    'facebook/s2t-small-librispeech-asr': (
        'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech_to_text
}





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   "speech_to_text"
 lowercase_       =   ["past_key_values"]
 lowercase_       =   {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}



 def __init__(							self  :		Union[str, Any]    ,    _lowerCAmelCase  :		Optional[int]=10_000    ,    _lowerCAmelCase  :		str=12    ,    _lowerCAmelCase  :		Tuple=2_048    ,    _lowerCAmelCase  :		str=4    ,    _lowerCAmelCase  :		Tuple=6    ,    _lowerCAmelCase  :		Optional[int]=2_048    ,    _lowerCAmelCase  :		Dict=4    ,    _lowerCAmelCase  :		List[Any]=0.0    ,    _lowerCAmelCase  :		int=0.0    ,    _lowerCAmelCase  :		Optional[int]=True    ,    _lowerCAmelCase  :		Union[str, Any]=True    ,    _lowerCAmelCase  :		Any="relu"    ,    _lowerCAmelCase  :		Any=256    ,    _lowerCAmelCase  :		List[str]=0.1    ,    _lowerCAmelCase  :		Optional[Any]=0.0    ,    _lowerCAmelCase  :		Optional[int]=0.0    ,    _lowerCAmelCase  :		Tuple=0.02    ,    _lowerCAmelCase  :		List[str]=2    ,    _lowerCAmelCase  :		Tuple=True    ,    _lowerCAmelCase  :		List[str]=1    ,    _lowerCAmelCase  :		Dict=0    ,    _lowerCAmelCase  :		Tuple=2    ,    _lowerCAmelCase  :		Optional[int]=6_000    ,    _lowerCAmelCase  :		Tuple=1_024    ,    _lowerCAmelCase  :		Any=2    ,    _lowerCAmelCase  :		str=(5, 5)    ,    _lowerCAmelCase  :		Optional[int]=1_024    ,    _lowerCAmelCase  :		List[Any]=80    ,    _lowerCAmelCase  :		List[Any]=1    ,    **_lowerCAmelCase  :		List[Any]    ,    ):
       SCREAMING_SNAKE_CASE_     						=      vocab_size
       SCREAMING_SNAKE_CASE_     						=      d_model
       SCREAMING_SNAKE_CASE_     						=      encoder_ffn_dim
       SCREAMING_SNAKE_CASE_     						=      encoder_layers
       SCREAMING_SNAKE_CASE_     						=      encoder_attention_heads
       SCREAMING_SNAKE_CASE_     						=      decoder_ffn_dim
       SCREAMING_SNAKE_CASE_     						=      decoder_layers
       SCREAMING_SNAKE_CASE_     						=      decoder_attention_heads
       SCREAMING_SNAKE_CASE_     						=      dropout
       SCREAMING_SNAKE_CASE_     						=      attention_dropout
       SCREAMING_SNAKE_CASE_     						=      activation_dropout
       SCREAMING_SNAKE_CASE_     						=      activation_function
       SCREAMING_SNAKE_CASE_     						=      init_std
       SCREAMING_SNAKE_CASE_     						=      encoder_layerdrop
       SCREAMING_SNAKE_CASE_     						=      decoder_layerdrop
       SCREAMING_SNAKE_CASE_     						=      use_cache
       SCREAMING_SNAKE_CASE_     						=      encoder_layers
       SCREAMING_SNAKE_CASE_     						=      scale_embedding  # scale factor will be sqrt(d_model) if True
       SCREAMING_SNAKE_CASE_     						=      max_source_positions
       SCREAMING_SNAKE_CASE_     						=      max_target_positions
       SCREAMING_SNAKE_CASE_     						=      num_conv_layers
       SCREAMING_SNAKE_CASE_     						=      list(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      conv_channels
       SCREAMING_SNAKE_CASE_     						=      input_feat_per_channel
       SCREAMING_SNAKE_CASE_     						=      input_channels

       if len(self.conv_kernel_sizes						) != self.num_conv_layers:
             raise ValueError(
                 'Configuration for convolutional module is incorrect. '
                 'It is required that `len(config.conv_kernel_sizes)` == `config.num_conv_layers` '
                 F"but is `len(config.conv_kernel_sizes) = {len(self.conv_kernel_sizes						)}`, "
                 F"`config.num_conv_layers = {self.num_conv_layers}`."						)

       super().__init__(
           pad_token_id=_lowerCAmelCase    ,    bos_token_id=_lowerCAmelCase    ,    eos_token_id=_lowerCAmelCase    ,    is_encoder_decoder=_lowerCAmelCase    ,    decoder_start_token_id=_lowerCAmelCase    ,    **_lowerCAmelCase    ,    )