



from typing import TYPE_CHECKING

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


__UpperCAmelCase      = {
    '''configuration_mobilevitv2''': [
        '''MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileViTV2Config''',
        '''MobileViTV2OnnxConfig''',
    ],
}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCAmelCase      = [
        '''MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MobileViTV2ForImageClassification''',
        '''MobileViTV2ForSemanticSegmentation''',
        '''MobileViTV2Model''',
        '''MobileViTV2PreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_mobilevitva import (
        MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        MobileViTVaConfig,
        MobileViTVaOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mobilevitva import (
            MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            MobileViTVaForImageClassification,
            MobileViTVaForSemanticSegmentation,
            MobileViTVaModel,
            MobileViTVaPreTrainedModel,
        )

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



