


'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__    					=      logging.get_logger(__name__)

UpperCamelCase__    					=      {
    '''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}




class 			lowerCamelCase_   (	__snake_case      ):
      lowerCAmelCase__		     =     """switch_transformers"""
      lowerCAmelCase__		     =     ["""past_key_values"""]
      lowerCAmelCase__		     =     {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}






      def __init__(					self				:    List[str]						,						_A				:    List[str]=32_128						,						_A				:    str=768						,						_A				:    Union[str, Any]=64						,						_A				:    Optional[int]=2_048						,						_A				:    Dict=64						,						_A				:    List[str]=12						,						_A				:    Dict=3						,						_A				:    Any=12						,						_A				:    Dict=3						,						_A				:    Dict=12						,						_A				:    List[str]=8						,						_A				:    Optional[Any]=False						,						_A				:    Optional[int]=0.0_1						,						_A				:    Optional[int]="float32"						,						_A				:    Any=False						,						_A				:    Dict=32						,						_A				:    Union[str, Any]=128						,						_A				:    Union[str, Any]=0.1						,						_A				:    Optional[int]=1e-6						,						_A				:    Optional[Any]=0.0_0_1						,						_A				:    Dict=0.0_0_1						,						_A				:    int=1.0						,						_A				:    str="relu"						,						_A				:    int=True						,						_A				:    Any=False						,						_A				:    str=True						,						_A				:    Tuple=0						,						_A				:    str=1						,						**_A				:    Tuple						,						):


          '''simple docstring'''


          UpperCAmelCase__			:		int													=				vocab_size
          UpperCAmelCase__			:		str													=				d_model
          UpperCAmelCase__			:		str													=				d_kv
          UpperCAmelCase__			:		str													=				d_ff

          UpperCAmelCase__			:		List[str]													=				num_sparse_encoder_layers

          UpperCAmelCase__			:		List[Any]													=				num_layers
          UpperCAmelCase__			:		Optional[Any]													=				(
              num_decoder_layers if num_decoder_layers is not None else self.num_layers
          )  # default = symmetry
          UpperCAmelCase__			:		Tuple													=				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:
              UpperCAmelCase__			:		int													=				self.num_layers // self.num_sparse_encoder_layers
          else:
              UpperCAmelCase__			:		Union[str, 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:
              UpperCAmelCase__			:		Dict													=				self.num_decoder_layers // self.num_sparse_decoder_layers
          else:
              UpperCAmelCase__			:		Any													=				self.num_decoder_layers  # HACK: this will create 0 sparse layers

          UpperCAmelCase__			:		Dict													=				num_heads
          UpperCAmelCase__			:		Dict													=				num_experts
          UpperCAmelCase__			:		Any													=				expert_capacity
          UpperCAmelCase__			:		List[Any]													=				router_bias
          UpperCAmelCase__			:		int													=				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}""" )
          UpperCAmelCase__			:		Dict													=				router_dtype

          UpperCAmelCase__			:		Optional[Any]													=				router_ignore_padding_tokens
          UpperCAmelCase__			:		Union[str, Any]													=				relative_attention_num_buckets
          UpperCAmelCase__			:		str													=				relative_attention_max_distance

          UpperCAmelCase__			:		Optional[int]													=				dropout_rate
          UpperCAmelCase__			:		Optional[Any]													=				layer_norm_epsilon
          UpperCAmelCase__			:		int													=				initializer_factor
          UpperCAmelCase__			:		Tuple													=				feed_forward_proj
          UpperCAmelCase__			:		int													=				use_cache
          UpperCAmelCase__			:		int													=				add_router_probs

          UpperCAmelCase__			:		Optional[Any]													=				router_z_loss_coef
          UpperCAmelCase__			:		Dict													=				router_aux_loss_coef

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

          if len(UpperCamelCase__ ) > 1 and act_info[0] != "gated" or len(UpperCamelCase__ ) > 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":
              UpperCAmelCase__			:		List[str]													=				"gelu_new"

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



"""simple docstring"""


from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url






@pytest.mark.parametrize("repo_id"					, ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path"					, ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parametrize("revision"					, [None, "v2"] )
def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE )	->	List[str]:
		__lowerCAmelCase:       Optional[Any]          =			hf_hub_url(repo_id=__SCREAMING_SNAKE_CASE					, path=__SCREAMING_SNAKE_CASE					, revision=__SCREAMING_SNAKE_CASE )
		assert url == F"https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(__SCREAMING_SNAKE_CASE )}"


