



"""simple docstring"""

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


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

lowercase__					:						List[Any]												=			{
    '''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}




class  _UpperCAmelCase (    lowerCAmelCase__):
 _lowerCAmelCase     :    List[str]	      =	"""switch_transformers"""
 _lowerCAmelCase     :    List[str]	      =	["""past_key_values"""]
 _lowerCAmelCase     :    Optional[int]	      =	{"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}

 def __init__(  self	: Optional[Any]						,  lowercase_	: Any=32128						,  lowercase_	: Optional[Any]=768						,  lowercase_	: Any=64						,  lowercase_	: str=2048						,  lowercase_	: Union[str, Any]=64						,  lowercase_	: int=12						,  lowercase_	: List[Any]=3						,  lowercase_	: Any=12						,  lowercase_	: str=3						,  lowercase_	: Optional[int]=12						,  lowercase_	: Any=8						,  lowercase_	: Optional[Any]=False						,  lowercase_	: Tuple=0.01						,  lowercase_	: List[str]="float32"						,  lowercase_	: List[Any]=False						,  lowercase_	: Dict=32						,  lowercase_	: Tuple=128						,  lowercase_	: List[Any]=0.1						,  lowercase_	: Optional[Any]=1E-6						,  lowercase_	: Dict=0.0_01						,  lowercase_	: Dict=0.0_01						,  lowercase_	: List[Any]=1.0						,  lowercase_	: List[str]="relu"						,  lowercase_	: Union[str, Any]=True						,  lowercase_	: int=False						,  lowercase_	: List[str]=True						,  lowercase_	: Any=0						,  lowercase_	: Optional[Any]=1						,  **lowercase_	: Dict						,  ):
     snake_case_				:  Optional[Any]       =			vocab_size
     snake_case_				:  List[str]       =			d_model
     snake_case_				:  Tuple       =			d_kv
     snake_case_				:  Dict       =			d_ff

     snake_case_				:  int       =			num_sparse_encoder_layers

     snake_case_				:  Tuple       =			num_layers
     snake_case_				:  Optional[Any]       =			(
         num_decoder_layers if num_decoder_layers is not None else self.num_layers
     )  # default = symmetry
     snake_case_				:  Union[str, Any]       =			num_sparse_decoder_layers

     # This tells us, each how many encoder layer we'll have to set a sparse layer.
     if self.num_sparse_encoder_layers > 0:
         snake_case_				:  Optional[int]       =			self.num_layers // self.num_sparse_encoder_layers
     else:
         snake_case_				:  Optional[Any]       =			self.num_layers  # HACK: this will create 0 sparse layers

     # This tells us, each how many encoder layer we'll have to set a sparse layer.
     if self.num_sparse_decoder_layers > 0:
         snake_case_				:  Tuple       =			self.num_decoder_layers // self.num_sparse_decoder_layers
     else:
         snake_case_				:  Tuple       =			self.num_decoder_layers  # HACK: this will create 0 sparse layers

     snake_case_				:  Tuple       =			num_heads
     snake_case_				:  Optional[int]       =			num_experts
     snake_case_				:  str       =			expert_capacity
     snake_case_				:  Optional[int]       =			router_bias
     snake_case_				:  List[Any]       =			router_jitter_noise
     if router_dtype not in ["float32", "float16", "bfloat16"]:
         raise ValueError(f"`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}"       )
     snake_case_				:  Optional[int]       =			router_dtype

     snake_case_				:  List[str]       =			router_ignore_padding_tokens
     snake_case_				:  Dict       =			relative_attention_num_buckets
     snake_case_				:  int       =			relative_attention_max_distance

     snake_case_				:  Union[str, Any]       =			dropout_rate
     snake_case_				:  List[Any]       =			layer_norm_epsilon
     snake_case_				:  int       =			initializer_factor
     snake_case_				:  Dict       =			feed_forward_proj
     snake_case_				:  int       =			use_cache
     snake_case_				:  Dict       =			add_router_probs

     snake_case_				:  List[Any]       =			router_z_loss_coef
     snake_case_				:  Dict       =			router_aux_loss_coef

     snake_case_				:  int       =			self.feed_forward_proj.split('''-'''       )
     snake_case_				:  Any       =			act_info[-1]
     snake_case_				:  Union[str, Any]       =			act_info[0] == '''gated'''

     if len(lowercase_       ) > 1 and act_info[0] != "gated" or len(lowercase_       ) > 2:
         raise ValueError(
             f"`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."
             '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
             '''\'gated-gelu\' or \'relu\''''       )

     # for backwards compatibility
     if feed_forward_proj == "gated-gelu":
         snake_case_				:  List[Any]       =			'''gelu_new'''

     super().__init__(
         pad_token_id=lowercase_						,  eos_token_id=lowercase_						,  is_encoder_decoder=lowercase_						,  **lowercase_						,  )










"""simple docstring"""

from statistics import mean, stdev




def __lowercase    (							_a	,    _a = 3					):
    snake_case_				:  Optional[int]       =			min(_a					)
    snake_case_				:  str       =			max(_a					)
    # normalize data
    return [round((x - x_min) / (x_max - x_min)	,    _a					) for x in data]






def __lowercase    (							_a	,    _a = 3					):
    snake_case_				:  Any       =			mean(_a					)
    snake_case_				:  str       =			stdev(_a					)
    # standardize data
    return [round((x - mu) / (sigma)	,    _a					) for x in data]





