





'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__							:							Optional[int] =logging.get_logger(__name__)

a__							:							Optional[int] ={
    '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}

class      snake_case     (    __lowerCamelCase       ):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_	:					Tuple					="mgp-str"






 def __init__(       self       :							List[str]							,	__A       :							Tuple=[3_2, 1_2_8]							,	__A       :							Optional[int]=4							,	__A       :							str=3							,	__A       :							Any=2_7							,	__A       :							Optional[Any]=3_8							,	__A       :							int=5_0_2_5_7							,	__A       :							int=3_0_5_2_2							,	__A       :							Tuple=7_6_8							,	__A       :							str=1_2							,	__A       :							List[Any]=1_2							,	__A       :							List[Any]=4.0							,	__A       :							Dict=True							,	__A       :							List[str]=False							,	__A       :							Optional[Any]=1e-5							,	__A       :							Any=0.0							,	__A       :							int=0.0							,	__A       :							Optional[Any]=0.0							,	__A       :							str=False							,	__A       :							List[Any]=0.02							,	**__A       :							List[Any]							,	):
        super().__init__(**__A	)

        __UpperCamelCase       =  image_size
        __UpperCamelCase       =  patch_size
        __UpperCamelCase       =  num_channels
        __UpperCamelCase       =  max_token_length
        __UpperCamelCase       =  num_character_labels
        __UpperCamelCase       =  num_bpe_labels
        __UpperCamelCase       =  num_wordpiece_labels
        __UpperCamelCase       =  hidden_size
        __UpperCamelCase       =  num_hidden_layers
        __UpperCamelCase       =  num_attention_heads
        __UpperCamelCase       =  mlp_ratio
        __UpperCamelCase       =  distilled
        __UpperCamelCase       =  layer_norm_eps
        __UpperCamelCase       =  drop_rate
        __UpperCamelCase       =  qkv_bias
        __UpperCamelCase       =  attn_drop_rate
        __UpperCamelCase       =  drop_path_rate
        __UpperCamelCase       =  output_aa_attentions
        __UpperCamelCase       =  initializer_range







'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__							:							List[str] ={
    '''configuration_bigbird_pegasus''': [
        '''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BigBirdPegasusConfig''',
        '''BigBirdPegasusOnnxConfig''',
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    a__							:							Any =[
        '''BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''BigBirdPegasusForCausalLM''',
        '''BigBirdPegasusForConditionalGeneration''',
        '''BigBirdPegasusForQuestionAnswering''',
        '''BigBirdPegasusForSequenceClassification''',
        '''BigBirdPegasusModel''',
        '''BigBirdPegasusPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
        BigBirdPegasusConfig,
        BigBirdPegasusOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_bigbird_pegasus import (
            BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
            BigBirdPegasusForCausalLM,
            BigBirdPegasusForConditionalGeneration,
            BigBirdPegasusForQuestionAnswering,
            BigBirdPegasusForSequenceClassification,
            BigBirdPegasusModel,
            BigBirdPegasusPreTrainedModel,
        )


else:
    import sys

    a__							:							str =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
