


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_   :				Dict						      = logging.get_logger(__name__)

UpperCAmelCase_   :				int						      = {
    'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json',
    'google/bigbird-roberta-large': 'https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json',
    'google/bigbird-base-trivia-itc': 'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}
class 				SCREAMING_SNAKE_CASE__						(       lowercase__    ):
      snake_case__       :  Dict       =		'''big_bird'''
      def __init__( self       : int  ,							SCREAMING_SNAKE_CASE__       : Any=5_0_3_5_8  ,							SCREAMING_SNAKE_CASE__       : List[str]=7_6_8  ,							SCREAMING_SNAKE_CASE__       : Optional[int]=1_2  ,							SCREAMING_SNAKE_CASE__       : Tuple=1_2  ,							SCREAMING_SNAKE_CASE__       : Union[str, Any]=3_0_7_2  ,							SCREAMING_SNAKE_CASE__       : Tuple="gelu_new"  ,							SCREAMING_SNAKE_CASE__       : str=0.1  ,							SCREAMING_SNAKE_CASE__       : int=0.1  ,							SCREAMING_SNAKE_CASE__       : Optional[int]=4_0_9_6  ,							SCREAMING_SNAKE_CASE__       : Optional[int]=2  ,							SCREAMING_SNAKE_CASE__       : Union[str, Any]=0.02  ,							SCREAMING_SNAKE_CASE__       : Optional[Any]=1E-12  ,							SCREAMING_SNAKE_CASE__       : Optional[int]=True  ,							SCREAMING_SNAKE_CASE__       : List[Any]=0  ,							SCREAMING_SNAKE_CASE__       : Any=1  ,							SCREAMING_SNAKE_CASE__       : Optional[Any]=2  ,							SCREAMING_SNAKE_CASE__       : List[Any]=6_6  ,							SCREAMING_SNAKE_CASE__       : Any="block_sparse"  ,							SCREAMING_SNAKE_CASE__       : Union[str, Any]=True  ,							SCREAMING_SNAKE_CASE__       : Tuple=False  ,							SCREAMING_SNAKE_CASE__       : Dict=6_4  ,							SCREAMING_SNAKE_CASE__       : List[Any]=3  ,							SCREAMING_SNAKE_CASE__       : Dict=None  ,							**SCREAMING_SNAKE_CASE__       : str  ,							)	->    List[str]:
             super().__init__(
                 pad_token_id=SCREAMING_SNAKE_CASE__  ,							bos_token_id=SCREAMING_SNAKE_CASE__  ,							eos_token_id=SCREAMING_SNAKE_CASE__  ,							sep_token_id=SCREAMING_SNAKE_CASE__  ,							**SCREAMING_SNAKE_CASE__  ,							)

             a_      :	Optional[int]							=						vocab_size
             a_      :	Dict							=						max_position_embeddings
             a_      :	int							=						hidden_size
             a_      :	Tuple							=						num_hidden_layers
             a_      :	Union[str, Any]							=						num_attention_heads
             a_      :	Dict							=						intermediate_size
             a_      :	str							=						hidden_act
             a_      :	Tuple							=						hidden_dropout_prob
             a_      :	Any							=						attention_probs_dropout_prob
             a_      :	Any							=						initializer_range
             a_      :	str							=						type_vocab_size
             a_      :	List[str]							=						layer_norm_eps
             a_      :	int							=						use_cache

             a_      :	Optional[Any]							=						rescale_embeddings
             a_      :	Any							=						attention_type
             a_      :	Tuple							=						use_bias
             a_      :	str							=						block_size
             a_      :	Optional[Any]							=						num_random_blocks
             a_      :	int							=						classifier_dropout
class 				SCREAMING_SNAKE_CASE__						(       lowercase__    ):
      @property
      def  SCREAMING_SNAKE_CASE							( self       : Union[str, Any]  )	->    Mapping[str, Mapping[int, str]]:
             if self.task == "multiple-choice":
                    a_      :	Optional[int]							=						{0: 'batch', 1: 'choice', 2: 'sequence'}
             else:
                    a_      :	Union[str, Any]							=						{0: 'batch', 1: 'sequence'}
             return OrderedDict(
                 [
                     ('input_ids', dynamic_axis),
                     ('attention_mask', dynamic_axis),
                 ]  )






UpperCAmelCase_   :				Optional[int]						      = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

UpperCAmelCase_   :				List[str]						      = [{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCAmelCase_   :				int						      = {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}


