

'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase :      str					 =     logging.get_logger(__name__)

lowerCamelCase :      Dict					 =     {
    "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 							A__    (       A__  ):
  A__		 =				'big_bird'





  def __init__(		self      :	Any							,					_a      :	Dict=5_0358							,					_a      :	int=768							,					_a      :	Tuple=12							,					_a      :	Dict=12							,					_a      :	Optional[Any]=3072							,					_a      :	Dict="gelu_new"							,					_a      :	str=0.1							,					_a      :	str=0.1							,					_a      :	Any=4096							,					_a      :	Dict=2							,					_a      :	Optional[Any]=0.02							,					_a      :	Union[str, Any]=1e-12							,					_a      :	List[Any]=True							,					_a      :	Dict=0							,					_a      :	Union[str, Any]=1							,					_a      :	List[str]=2							,					_a      :	int=66							,					_a      :	Optional[int]="block_sparse"							,					_a      :	Any=True							,					_a      :	Union[str, Any]=False							,					_a      :	str=64							,					_a      :	Optional[Any]=3							,					_a      :	List[str]=None							,					**_a      :	List[str]							,					)	->    str:





       '''simple docstring'''






       super().__init__(
           pad_token_id=_a							,					bos_token_id=_a							,					eos_token_id=_a							,					sep_token_id=_a							,					**_a							,					)

       _SCREAMING_SNAKE_CASE							    =vocab_size
       _SCREAMING_SNAKE_CASE							    =max_position_embeddings
       _SCREAMING_SNAKE_CASE							    =hidden_size
       _SCREAMING_SNAKE_CASE							    =num_hidden_layers
       _SCREAMING_SNAKE_CASE							    =num_attention_heads
       _SCREAMING_SNAKE_CASE							    =intermediate_size
       _SCREAMING_SNAKE_CASE							    =hidden_act
       _SCREAMING_SNAKE_CASE							    =hidden_dropout_prob
       _SCREAMING_SNAKE_CASE							    =attention_probs_dropout_prob
       _SCREAMING_SNAKE_CASE							    =initializer_range
       _SCREAMING_SNAKE_CASE							    =type_vocab_size
       _SCREAMING_SNAKE_CASE							    =layer_norm_eps
       _SCREAMING_SNAKE_CASE							    =use_cache

       _SCREAMING_SNAKE_CASE							    =rescale_embeddings
       _SCREAMING_SNAKE_CASE							    =attention_type
       _SCREAMING_SNAKE_CASE							    =use_bias
       _SCREAMING_SNAKE_CASE							    =block_size
       _SCREAMING_SNAKE_CASE							    =num_random_blocks
       _SCREAMING_SNAKE_CASE							    =classifier_dropout







class 							A__    (       A__  ):





  @property
  def 						A  (		self      :	Optional[int] )	->    Mapping[str, Mapping[int, str]]:





       '''simple docstring'''






       if self.task == "multiple-choice":
            _SCREAMING_SNAKE_CASE							    ={0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
            _SCREAMING_SNAKE_CASE							    ={0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
           ] )






__UpperCamelCase					:       Optional[int]    					=      {
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}

