from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE										=						{
    'configuration_clap': [
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapAudioConfig',
        'ClapConfig',
        'ClapTextConfig',
    ],
    'processing_clap': ['ClapProcessor'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _SCREAMING_SNAKE_CASE										=						[
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapModel',
        'ClapPreTrainedModel',
        'ClapTextModel',
        'ClapTextModelWithProjection',
        'ClapAudioModel',
        'ClapAudioModelWithProjection',
    ]
    _SCREAMING_SNAKE_CASE										=						['ClapFeatureExtractor']

if TYPE_CHECKING:
    from .configuration_clap import (
        CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
        ClapAudioConfig,
        ClapConfig,
        ClapTextConfig,
    )
    from .processing_clap import ClapProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_clap import ClapFeatureExtractor
        from .modeling_clap import (
            CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
            ClapAudioModel,
            ClapAudioModelWithProjection,
            ClapModel,
            ClapPreTrainedModel,
            ClapTextModel,
            ClapTextModelWithProjection,
        )


else:
    import sys

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





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


_SCREAMING_SNAKE_CASE										=						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE										=						{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}



class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:Any    			=		'''biogpt'''



 def __init__(					self		,				lowerCAmelCase_=4_23_84		,				lowerCAmelCase_=10_24		,				lowerCAmelCase_=24		,				lowerCAmelCase_=16		,				lowerCAmelCase_=40_96		,				lowerCAmelCase_="gelu"		,				lowerCAmelCase_=0.1		,				lowerCAmelCase_=0.1		,				lowerCAmelCase_=10_24		,				lowerCAmelCase_=0.02		,				lowerCAmelCase_=1E-12		,				lowerCAmelCase_=True		,				lowerCAmelCase_=True		,				lowerCAmelCase_=0.0		,				lowerCAmelCase_=0.0		,				lowerCAmelCase_=1		,				lowerCAmelCase_=0		,				lowerCAmelCase_=2		,				**lowerCAmelCase_		,				)  ->					Tuple:
        _A        =  vocab_size
        _A        =  max_position_embeddings
        _A        =  hidden_size
        _A        =  num_hidden_layers
        _A        =  num_attention_heads
        _A        =  intermediate_size
        _A        =  hidden_act
        _A        =  hidden_dropout_prob
        _A        =  attention_probs_dropout_prob
        _A        =  initializer_range
        _A        =  layer_norm_eps
        _A        =  scale_embedding
        _A        =  use_cache
        _A        =  layerdrop
        _A        =  activation_dropout
        super().__init__(pad_token_id=lowerCAmelCase_		,				bos_token_id=lowerCAmelCase_		,				eos_token_id=lowerCAmelCase_		,				**lowerCAmelCase_							)




