


"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

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


__snake_case             =   logging.get_logger(__name__)

__snake_case             =   {
    """roberta-base""": """https://huggingface.co/roberta-base/resolve/main/config.json""",
    """roberta-large""": """https://huggingface.co/roberta-large/resolve/main/config.json""",
    """roberta-large-mnli""": """https://huggingface.co/roberta-large-mnli/resolve/main/config.json""",
    """distilroberta-base""": """https://huggingface.co/distilroberta-base/resolve/main/config.json""",
    """roberta-base-openai-detector""": """https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json""",
    """roberta-large-openai-detector""": """https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json""",
}







class _lowerCAmelCase    (				snake_case_     ):
   __UpperCAmelCase			:	Optional[Any]							  =  '''roberta'''







   def __init__(     self						,     UpperCamelCase__=5_0265						,     UpperCamelCase__=768						,     UpperCamelCase__=12						,     UpperCamelCase__=12						,     UpperCamelCase__=3072						,     UpperCamelCase__="gelu"						,     UpperCamelCase__=0.1						,     UpperCamelCase__=0.1						,     UpperCamelCase__=512						,     UpperCamelCase__=2						,     UpperCamelCase__=0.02						,     UpperCamelCase__=1e-12						,     UpperCamelCase__=1						,     UpperCamelCase__=0						,     UpperCamelCase__=2						,     UpperCamelCase__="absolute"						,     UpperCamelCase__=True						,     UpperCamelCase__=None						,     **UpperCamelCase__						,     )     ->		Dict:

       '''simple docstring'''




       super().__init__(pad_token_id=UpperCamelCase__						,     bos_token_id=UpperCamelCase__						,     eos_token_id=UpperCamelCase__						,     **UpperCamelCase__						)

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







class _lowerCAmelCase    (				snake_case_     ):







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

       '''simple docstring'''




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









"""simple docstring"""



from __future__ import annotations

import numpy as np







def   __lowerCAmelCase						(						lowercase  :  list[float]			)     ->						Any:


    """simple docstring"""





    return np.maximum(0						,							lowercase			)


if __name__ == "__main__":
  print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]





