





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


_UpperCAmelCase				:       int	   =				{"""configuration_speech_encoder_decoder""": ["""SpeechEncoderDecoderConfig"""]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCAmelCase				:       Tuple	   =				["""SpeechEncoderDecoderModel"""]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCAmelCase				:       int	   =				["""FlaxSpeechEncoderDecoderModel"""]

if TYPE_CHECKING:
    from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
    import sys

    _UpperCAmelCase				:       Dict	   =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)












import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase				:       Optional[Any]	   =				"""▁"""

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

@require_sentencepiece
class    lowerCAmelCase							(					__UpperCamelCase,  unittest.TestCase			):
 UpperCAmelCase__													=		BertGenerationTokenizer
 UpperCAmelCase__													=		False
 UpperCAmelCase__													=		True
 def      A_	(      self  :      List[Any]	)			->	List[str]:
     super().setUp()

     lowerCamelCase__    :      Dict					 =		BertGenerationTokenizer(UpperCAmelCase			,     keep_accents=UpperCAmelCase	)
     tokenizer.save_pretrained(self.tmpdirname	)
 def      A_	(      self  :      Optional[Any]	)			->	Dict:
     lowerCamelCase__    :      List[str]					 =		'<s>'
     lowerCamelCase__    :      Optional[int]					 =		1

     self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase	)			,     UpperCAmelCase	)
     self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase	)			,     UpperCAmelCase	)
 def      A_	(      self  :      List[str]	)			->	Optional[int]:
     lowerCamelCase__    :      Optional[Any]					 =		list(self.get_tokenizer().get_vocab().keys()	)

     self.assertEqual(vocab_keys[0]			,     '<unk>'	)
     self.assertEqual(vocab_keys[1]			,     '<s>'	)
     self.assertEqual(vocab_keys[-1]			,     '<pad>'	)
     self.assertEqual(len(UpperCAmelCase	)			,     1002	)
 def      A_	(      self  :      List[Any]	)			->	Optional[Any]:
     self.assertEqual(self.get_tokenizer().vocab_size			,     1000	)
 def      A_	(      self  :      Union[str, Any]	)			->	List[Any]:
     lowerCamelCase__    :      Union[str, Any]					 =		BertGenerationTokenizer(UpperCAmelCase			,     keep_accents=UpperCAmelCase	)

     lowerCamelCase__    :      List[str]					 =		tokenizer.tokenize('This is a test'	)
     self.assertListEqual(UpperCAmelCase			,     ['▁This', '▁is', '▁a', '▁t', 'est']	)

     self.assertListEqual(
         tokenizer.convert_tokens_to_ids(UpperCAmelCase	)			,     [285, 46, 10, 170, 382]			,     )

     lowerCamelCase__    :      List[str]					 =		tokenizer.tokenize('I was born in 92000, and this is falsé.'	)
     self.assertListEqual(
         UpperCAmelCase			,     [
             SPIECE_UNDERLINE + 'I',
             SPIECE_UNDERLINE + 'was',
             SPIECE_UNDERLINE + 'b',
             'or',
             'n',
             SPIECE_UNDERLINE + 'in',
             SPIECE_UNDERLINE + '',
             '9',
             '2',
             '0',
             '0',
             '0',
             ',',
             SPIECE_UNDERLINE + 'and',
             SPIECE_UNDERLINE + 'this',
             SPIECE_UNDERLINE + 'is',
             SPIECE_UNDERLINE + 'f',
             'al',
             's',
             'é',
             '.',
         ]			,     )
     lowerCamelCase__    :      Optional[int]					 =		tokenizer.convert_tokens_to_ids(UpperCAmelCase	)
     self.assertListEqual(
         UpperCAmelCase			,     [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]			,     )

     lowerCamelCase__    :      Optional[Any]					 =		tokenizer.convert_ids_to_tokens(UpperCAmelCase	)
     self.assertListEqual(
         UpperCAmelCase			,     [
             SPIECE_UNDERLINE + 'I',
             SPIECE_UNDERLINE + 'was',
             SPIECE_UNDERLINE + 'b',
             'or',
             'n',
             SPIECE_UNDERLINE + 'in',
             SPIECE_UNDERLINE + '',
             '<unk>',
             '2',
             '0',
             '0',
             '0',
             ',',
             SPIECE_UNDERLINE + 'and',
             SPIECE_UNDERLINE + 'this',
             SPIECE_UNDERLINE + 'is',
             SPIECE_UNDERLINE + 'f',
             'al',
             's',
             '<unk>',
             '.',
         ]			,     )
 @cached_property
 def      A_	(      self  :      Dict	)			->	Tuple:
     return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'	)
 @slow
 def      A_	(      self  :      Optional[int]	)			->	List[str]:
     lowerCamelCase__    :      Union[str, Any]					 =		'Hello World!'
     lowerCamelCase__    :      Dict					 =		[18536, 2260, 101]

     self.assertListEqual(UpperCAmelCase			,     self.big_tokenizer.encode(UpperCAmelCase	)	)
 @slow
 def      A_	(      self  :      Optional[Any]	)			->	str:
     lowerCamelCase__    :      List[Any]					 =		(
         'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
         ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
     )
     lowerCamelCase__    :      Any					 =		[
         871,
         419,
         358,
         946,
         991,
         2521,
         452,
         358,
         1357,
         387,
         7751,
         3536,
         112,
         985,
         456,
         126,
         865,
         938,
         5400,
         5734,
         458,
         1368,
         467,
         786,
         2462,
         5246,
         1159,
         633,
         865,
         4519,
         457,
         582,
         852,
         2557,
         427,
         916,
         508,
         405,
         34324,
         497,
         391,
         408,
         11342,
         1244,
         385,
         100,
         938,
         985,
         456,
         574,
         362,
         12597,
         3200,
         3129,
         1172,
     ]

     self.assertListEqual(UpperCAmelCase			,     self.big_tokenizer.encode(UpperCAmelCase	)	)
 @require_torch
 @slow
 def      A_	(      self  :      int	)			->	Optional[Any]:
     import torch

     from transformers import BertGenerationConfig, BertGenerationEncoder

     # Build sequence
     lowerCamelCase__    :      str					 =		list(self.big_tokenizer.get_vocab().keys()	)[:10]
     lowerCamelCase__    :      int					 =		' '.join(UpperCAmelCase	)
     lowerCamelCase__    :      Union[str, Any]					 =		self.big_tokenizer.encode_plus(UpperCAmelCase			,     return_tensors='pt'			,     return_token_type_ids=UpperCAmelCase	)
     lowerCamelCase__    :      Optional[Any]					 =		self.big_tokenizer.batch_encode_plus(
         [sequence + ' ' + sequence]			,     return_tensors='pt'			,     return_token_type_ids=UpperCAmelCase	)

     lowerCamelCase__    :      Tuple					 =		BertGenerationConfig()
     lowerCamelCase__    :      Optional[Any]					 =		BertGenerationEncoder(UpperCAmelCase	)

     assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

     with torch.no_grad():
         model(**UpperCAmelCase	)
         model(**UpperCAmelCase	)







 @slow
 def      A_	(      self  :      Optional[int]	)			->	List[Any]:
     # fmt: off
     lowerCamelCase__    :      Any					 =		{'input_ids': [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=UpperCAmelCase			,     model_name='google/bert_for_seq_generation_L-24_bbc_encoder'			,     revision='c817d1fd1be2ffa69431227a1fe320544943d4db'			,     )





