


"""simple docstring"""





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


snake_case__						:   List[str]			 = logging.get_logger(__name__)

snake_case__						:   Tuple			 = {
    '''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json''',
    '''microsoft/markuplm-large''': '''https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json''',
}



class 						snake_case_(				a__	):
     __UpperCamelCase     =    '''markuplm'''






     def __init__(		self     :    Tuple    , UpperCamelCase_     :    Optional[int]=3_0_5_2_2    , UpperCamelCase_     :    Any=7_6_8    , UpperCamelCase_     :    str=1_2    , UpperCamelCase_     :    Dict=1_2    , UpperCamelCase_     :    str=3_0_7_2    , UpperCamelCase_     :    Any="gelu"    , UpperCamelCase_     :    Tuple=0.1    , UpperCamelCase_     :    int=0.1    , UpperCamelCase_     :    Optional[int]=5_1_2    , UpperCamelCase_     :    List[Any]=2    , UpperCamelCase_     :    Tuple=0.02    , UpperCamelCase_     :    int=1E-12    , UpperCamelCase_     :    Union[str, Any]=0    , UpperCamelCase_     :    Tuple=0    , UpperCamelCase_     :    Optional[int]=2    , UpperCamelCase_     :    Optional[int]=2_5_6    , UpperCamelCase_     :    Tuple=1_0_2_4    , UpperCamelCase_     :    Any=2_1_6    , UpperCamelCase_     :    int=1_0_0_1    , UpperCamelCase_     :    Union[str, Any]=3_2    , UpperCamelCase_     :    Dict=5_0    , UpperCamelCase_     :    Optional[int]="absolute"    , UpperCamelCase_     :    Dict=True    , UpperCamelCase_     :    List[Any]=None    , **UpperCamelCase_     :    str    , ):
           super().__init__(
               pad_token_id=UpperCamelCase_    , bos_token_id=UpperCamelCase_    , eos_token_id=UpperCamelCase_    , **UpperCamelCase_    , )
           lowerCAmelCase    :		List[Any]				=      vocab_size
           lowerCAmelCase    :		Tuple				=      hidden_size
           lowerCAmelCase    :		Optional[Any]				=      num_hidden_layers
           lowerCAmelCase    :		int				=      num_attention_heads
           lowerCAmelCase    :		str				=      hidden_act
           lowerCAmelCase    :		Dict				=      intermediate_size
           lowerCAmelCase    :		List[str]				=      hidden_dropout_prob
           lowerCAmelCase    :		Tuple				=      attention_probs_dropout_prob
           lowerCAmelCase    :		List[Any]				=      max_position_embeddings
           lowerCAmelCase    :		str				=      type_vocab_size
           lowerCAmelCase    :		Dict				=      initializer_range
           lowerCAmelCase    :		Union[str, Any]				=      layer_norm_eps
           lowerCAmelCase    :		str				=      position_embedding_type
           lowerCAmelCase    :		str				=      use_cache
           lowerCAmelCase    :		Tuple				=      classifier_dropout
           # additional properties
           lowerCAmelCase    :		List[str]				=      max_depth
           lowerCAmelCase    :		Optional[int]				=      max_xpath_tag_unit_embeddings
           lowerCAmelCase    :		str				=      max_xpath_subs_unit_embeddings
           lowerCAmelCase    :		List[str]				=      tag_pad_id
           lowerCAmelCase    :		int				=      subs_pad_id
           lowerCAmelCase    :		int				=      xpath_unit_hidden_size






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


lowerCAmelCase__      		= {
    'configuration_speecht5': [
        'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP',
        'SpeechT5Config',
        'SpeechT5HifiGanConfig',
    ],
    'feature_extraction_speecht5': ['SpeechT5FeatureExtractor'],
    'processing_speecht5': ['SpeechT5Processor'],
}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__      		= ['SpeechT5Tokenizer']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__      		= [
        'SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST',
        'SpeechT5ForSpeechToText',
        'SpeechT5ForSpeechToSpeech',
        'SpeechT5ForTextToSpeech',
        'SpeechT5Model',
        'SpeechT5PreTrainedModel',
        'SpeechT5HifiGan',
    ]

if TYPE_CHECKING:
    from .configuration_speechta import (
        SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
        SpeechTaConfig,
        SpeechTaHifiGanConfig,
    )
    from .feature_extraction_speechta import SpeechTaFeatureExtractor
    from .processing_speechta import SpeechTaProcessor

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_speechta import SpeechTaTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_speechta import (
            SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
            SpeechTaForSpeechToSpeech,
            SpeechTaForSpeechToText,
            SpeechTaForTextToSpeech,
            SpeechTaHifiGan,
            SpeechTaModel,
            SpeechTaPreTrainedModel,
        )

else:
    import sys

    lowerCAmelCase__      		= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
