



from typing import TYPE_CHECKING

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


__UpperCAmelCase      = {
    '''configuration_flava''': [
        '''FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''FlavaConfig''',
        '''FlavaImageCodebookConfig''',
        '''FlavaImageConfig''',
        '''FlavaMultimodalConfig''',
        '''FlavaTextConfig''',
    ],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCAmelCase      = ['''FlavaFeatureExtractor''']
    __UpperCAmelCase      = ['''FlavaImageProcessor''']
    __UpperCAmelCase      = ['''FlavaProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCAmelCase      = [
        '''FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''FlavaForPreTraining''',
        '''FlavaImageCodebook''',
        '''FlavaImageModel''',
        '''FlavaModel''',
        '''FlavaMultimodalModel''',
        '''FlavaPreTrainedModel''',
        '''FlavaTextModel''',
    ]

if TYPE_CHECKING:
    from .configuration_flava import (
        FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
        FlavaConfig,
        FlavaImageCodebookConfig,
        FlavaImageConfig,
        FlavaMultimodalConfig,
        FlavaTextConfig,
    )

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_flava import FlavaFeatureExtractor
        from .image_processing_flava import FlavaImageProcessor
        from .processing_flava import FlavaProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flava import (
            FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
            FlavaForPreTraining,
            FlavaImageCodebook,
            FlavaImageModel,
            FlavaModel,
            FlavaMultimodalModel,
            FlavaPreTrainedModel,
            FlavaTextModel,
        )

else:
    import sys

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








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


__UpperCAmelCase      = logging.get_logger(__name__)

__UpperCAmelCase      = {
    '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json''',
}



class        lowerCAmelCase_	(						a__							):
       UpperCAmelCase__       :      Union[str, Any]       =						"mpnet"
       def __init__(    self,    SCREAMING_SNAKE_CASE_=3_0527,    SCREAMING_SNAKE_CASE_=768,    SCREAMING_SNAKE_CASE_=12,    SCREAMING_SNAKE_CASE_=12,    SCREAMING_SNAKE_CASE_=3072,    SCREAMING_SNAKE_CASE_="gelu",    SCREAMING_SNAKE_CASE_=0.1,    SCREAMING_SNAKE_CASE_=0.1,    SCREAMING_SNAKE_CASE_=512,    SCREAMING_SNAKE_CASE_=0.02,    SCREAMING_SNAKE_CASE_=1e-12,    SCREAMING_SNAKE_CASE_=32,    SCREAMING_SNAKE_CASE_=1,    SCREAMING_SNAKE_CASE_=0,    SCREAMING_SNAKE_CASE_=2,    **SCREAMING_SNAKE_CASE_,    )  ->	Optional[int]:
          super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_,    bos_token_id=SCREAMING_SNAKE_CASE_,    eos_token_id=SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_ )

          UpperCamelCase					:						Any					=			vocab_size
          UpperCamelCase					:						Optional[Any]					=			hidden_size
          UpperCamelCase					:						Union[str, Any]					=			num_hidden_layers
          UpperCamelCase					:						Optional[int]					=			num_attention_heads
          UpperCamelCase					:						Optional[Any]					=			hidden_act
          UpperCamelCase					:						str					=			intermediate_size
          UpperCamelCase					:						Optional[Any]					=			hidden_dropout_prob
          UpperCamelCase					:						Union[str, Any]					=			attention_probs_dropout_prob
          UpperCamelCase					:						List[Any]					=			max_position_embeddings
          UpperCamelCase					:						Union[str, Any]					=			initializer_range
          UpperCamelCase					:						List[str]					=			layer_norm_eps
          UpperCamelCase					:						str					=			relative_attention_num_buckets



