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


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

A   :     Tuple       =				{
    "tanreinama/GPTSAN-2.8B-spout_is_uniform": (
        "https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json"
    ),
}


class      lowerCamelCase    (SCREAMING_SNAKE_CASE__    ):
  """simple docstring"""







  lowerCamelCase__   =  '''gptsan-japanese'''
  lowerCamelCase__   =  [
      '''past_key_values''',
  ]
  lowerCamelCase__   =  {
      '''hidden_size''': '''d_model''',
      '''num_attention_heads''': '''num_heads''',
      '''num_hidden_layers''': '''num_layers''',
  }







  def __init__(							self       :				Tuple     ,   __magic_name__       :				Tuple=36_000     ,   __magic_name__       :				str=1_280     ,   __magic_name__       :				Any=1_024     ,   __magic_name__       :				Tuple=8_192     ,   __magic_name__       :				Optional[int]=4_096     ,   __magic_name__       :				Optional[Any]=128     ,   __magic_name__       :				int=10     ,   __magic_name__       :				Dict=0     ,   __magic_name__       :				Dict=16     ,   __magic_name__       :				Tuple=16     ,   __magic_name__       :				List[str]=128     ,   __magic_name__       :				str=0.0     ,   __magic_name__       :				List[str]=1e-5     ,   __magic_name__       :				Union[str, Any]=False     ,   __magic_name__       :				Tuple=0.0     ,   __magic_name__       :				Union[str, Any]="float32"     ,   __magic_name__       :				Union[str, Any]=False     ,   __magic_name__       :				str=False     ,   __magic_name__       :				Union[str, Any]=False     ,   __magic_name__       :				List[Any]=0.002     ,   __magic_name__       :				Tuple=False     ,   __magic_name__       :				str=True     ,   __magic_name__       :				Tuple=35_998     ,   __magic_name__       :				Optional[Any]=35_995     ,   __magic_name__       :				Union[str, Any]=35_999     ,   **__magic_name__       :				Union[str, Any]     ,   )     ->		str:
        SCREAMING_SNAKE_CASE_      =     vocab_size
        SCREAMING_SNAKE_CASE_      =     max_position_embeddings
        SCREAMING_SNAKE_CASE_      =     d_model
        SCREAMING_SNAKE_CASE_      =     d_ff
        SCREAMING_SNAKE_CASE_      =     d_ext
        SCREAMING_SNAKE_CASE_      =     d_spout
        SCREAMING_SNAKE_CASE_      =     num_switch_layers
        SCREAMING_SNAKE_CASE_      =     num_ext_layers
        SCREAMING_SNAKE_CASE_      =     num_switch_layers + num_ext_layers
        SCREAMING_SNAKE_CASE_      =     num_heads
        SCREAMING_SNAKE_CASE_      =     num_experts
        SCREAMING_SNAKE_CASE_      =     expert_capacity
        SCREAMING_SNAKE_CASE_      =     dropout_rate
        SCREAMING_SNAKE_CASE_      =     layer_norm_epsilon
        SCREAMING_SNAKE_CASE_      =     router_bias
        SCREAMING_SNAKE_CASE_      =     router_jitter_noise
        SCREAMING_SNAKE_CASE_      =     router_dtype
        SCREAMING_SNAKE_CASE_      =     router_ignore_padding_tokens
        SCREAMING_SNAKE_CASE_      =     output_hidden_states
        SCREAMING_SNAKE_CASE_      =     output_attentions
        SCREAMING_SNAKE_CASE_      =     initializer_factor
        SCREAMING_SNAKE_CASE_      =     output_router_logits
        SCREAMING_SNAKE_CASE_      =     use_cache

        super().__init__(
            separator_token_id=__magic_name__     ,   pad_token_id=__magic_name__     ,   eos_token_id=__magic_name__     ,   **__magic_name__     ,   )



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


A   :     str       =				logging.get_logger(__name__)

# TODO: upload to AWS
A   :     Dict       =				{
    "yjernite/retribert-base-uncased": (
        "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
    ),
}


class      lowerCamelCase    (SCREAMING_SNAKE_CASE__    ):
  """simple docstring"""







  lowerCamelCase__   =  '''retribert'''







  def __init__(							self       :				Optional[int]     ,   __magic_name__       :				Optional[Any]=30_522     ,   __magic_name__       :				int=768     ,   __magic_name__       :				Dict=8     ,   __magic_name__       :				List[Any]=12     ,   __magic_name__       :				Tuple=3_072     ,   __magic_name__       :				List[Any]="gelu"     ,   __magic_name__       :				Any=0.1     ,   __magic_name__       :				Any=0.1     ,   __magic_name__       :				Tuple=512     ,   __magic_name__       :				Dict=2     ,   __magic_name__       :				int=0.02     ,   __magic_name__       :				List[Any]=1e-12     ,   __magic_name__       :				List[str]=True     ,   __magic_name__       :				Dict=128     ,   __magic_name__       :				Union[str, Any]=0     ,   **__magic_name__       :				List[Any]     ,   )     ->		Dict:
        super().__init__(pad_token_id=__magic_name__     ,   **__magic_name__      )

        SCREAMING_SNAKE_CASE_      =     vocab_size
        SCREAMING_SNAKE_CASE_      =     hidden_size
        SCREAMING_SNAKE_CASE_      =     num_hidden_layers
        SCREAMING_SNAKE_CASE_      =     num_attention_heads
        SCREAMING_SNAKE_CASE_      =     hidden_act
        SCREAMING_SNAKE_CASE_      =     intermediate_size
        SCREAMING_SNAKE_CASE_      =     hidden_dropout_prob
        SCREAMING_SNAKE_CASE_      =     attention_probs_dropout_prob
        SCREAMING_SNAKE_CASE_      =     max_position_embeddings
        SCREAMING_SNAKE_CASE_      =     type_vocab_size
        SCREAMING_SNAKE_CASE_      =     initializer_range
        SCREAMING_SNAKE_CASE_      =     layer_norm_eps
        SCREAMING_SNAKE_CASE_      =     share_encoders
        SCREAMING_SNAKE_CASE_      =     projection_dim


