





import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict






@pytest.mark.parametrize(
    """split_dict"""   ,   [
        SplitDict(),
        SplitDict({"""train""": SplitInfo(name="""train"""   ,   num_bytes=1_337   ,   num_examples=42   ,   dataset_name="""my_dataset"""   )}   ),
        SplitDict({"""train""": SplitInfo(name="""train"""   ,   num_bytes=1_337   ,   num_examples=42   )}   ),
        SplitDict({"""train""": SplitInfo()}   ),
    ]   ,   )
def 	_SCREAMING_SNAKE_CASE		(				SCREAMING_SNAKE_CASE		:SplitDict   )      ->   Tuple:
 __lowerCAmelCase					:	Tuple      =       split_dict._to_yaml_list()
 assert len(lowerCAmelCase__   ) == len(lowerCAmelCase__   )
 __lowerCAmelCase					:	Tuple      =       SplitDict._from_yaml_list(lowerCAmelCase__   )
 for split_name, split_info in split_dict.items():
  # dataset_name field is deprecated, and is therefore not part of the YAML dump
  __lowerCAmelCase					:	Dict      =       None
  # the split name of split_dict takes over the name of the split info object
  __lowerCAmelCase					:	Optional[Any]      =       split_name
 assert split_dict == reloaded







@pytest.mark.parametrize(
    """split_info"""   ,   [SplitInfo(), SplitInfo(dataset_name=lowerCAmelCase__   ), SplitInfo(dataset_name="""my_dataset"""   )]   )
def 	_SCREAMING_SNAKE_CASE		(				SCREAMING_SNAKE_CASE		:Dict   )      ->   List[Any]:
 __lowerCAmelCase					:	Optional[Any]      =       asdict(SplitDict({"""train""": split_info}   )   )
 assert "dataset_name" in split_dict_asdict["train"]
 assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name






from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class        snake_case_    (		__lowercase						):
  A_      							=   'biogpt'






  def __init__(							self			:					int       ,  _snake_case			:					Any=42384       ,  _snake_case			:					Any=1024       ,  _snake_case			:					List[Any]=24       ,  _snake_case			:					Any=16       ,  _snake_case			:					List[str]=4096       ,  _snake_case			:					Dict="gelu"       ,  _snake_case			:					Tuple=0.1       ,  _snake_case			:					str=0.1       ,  _snake_case			:					Tuple=1024       ,  _snake_case			:					Tuple=0.02       ,  _snake_case			:					Tuple=1E-12       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Any=0.0       ,  _snake_case			:					Tuple=0.0       ,  _snake_case			:					str=1       ,  _snake_case			:					Dict=0       ,  _snake_case			:					str=2       ,  **_snake_case			:					Union[str, Any]       ,  )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       vocab_size
   __lowerCAmelCase					:	Dict      =       max_position_embeddings
   __lowerCAmelCase					:	str      =       hidden_size
   __lowerCAmelCase					:	Dict      =       num_hidden_layers
   __lowerCAmelCase					:	List[Any]      =       num_attention_heads
   __lowerCAmelCase					:	Optional[Any]      =       intermediate_size
   __lowerCAmelCase					:	int      =       hidden_act
   __lowerCAmelCase					:	Any      =       hidden_dropout_prob
   __lowerCAmelCase					:	Any      =       attention_probs_dropout_prob
   __lowerCAmelCase					:	Any      =       initializer_range
   __lowerCAmelCase					:	int      =       layer_norm_eps
   __lowerCAmelCase					:	Optional[int]      =       scale_embedding
   __lowerCAmelCase					:	List[Any]      =       use_cache
   __lowerCAmelCase					:	str      =       layerdrop
   __lowerCAmelCase					:	Dict      =       activation_dropout
   super().__init__(pad_token_id=_snake_case       ,  bos_token_id=_snake_case       ,  eos_token_id=_snake_case       ,  **_snake_case      )