
'''simple docstring'''

from typing import Any







def 	A  (   UpperCamelCase_       :  list    ,						UpperCamelCase_       :  list    ,						UpperCamelCase_       :  dict    ,						UpperCamelCase_       :  dict    ,						UpperCamelCase_       :  dict    ,						)       ->							list:







			'''simple docstring'''



			_validation(
			    UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						)
			# Creates data structures and fill initial step
			lowerCAmelCase__										=				{}
			lowerCAmelCase__										=				{}
			for state in states_space:
						lowerCAmelCase__										=				observations_space[0]
						lowerCAmelCase__										=				(
						    initial_probabilities[state] * emission_probabilities[state][observation]
						)
						lowerCAmelCase__										=				None

			# Fills the data structure with the probabilities of
			# different transitions and pointers to previous states
			for o in range(1    ,						len(UpperCamelCase_   )   ):
						lowerCAmelCase__										=				observations_space[o]
						lowerCAmelCase__										=				observations_space[o - 1]
						for state in states_space:
									# Calculates the argmax for probability function
									lowerCAmelCase__										=				""
									lowerCAmelCase__										=				-1
									for k_state in states_space:
												lowerCAmelCase__										=				(
												    probabilities[(k_state, prior_observation)]
												    * transition_probabilities[k_state][state]
												    * emission_probabilities[state][observation]
												)
												if probability > max_probability:
															lowerCAmelCase__										=				probability
															lowerCAmelCase__										=				k_state

            # Update probabilities and pointers dicts
									lowerCAmelCase__										=				(
									    probabilities[(arg_max, prior_observation)]
									    * transition_probabilities[arg_max][state]
									    * emission_probabilities[state][observation]
									)

									lowerCAmelCase__										=				arg_max

    # The final observation
			lowerCAmelCase__										=				observations_space[len(UpperCamelCase_   ) - 1]

			# argmax for given final observation
			lowerCAmelCase__										=				""
			lowerCAmelCase__										=				-1
			for k_state in states_space:
						lowerCAmelCase__										=				probabilities[(k_state, final_observation)]
						if probability > max_probability:
									lowerCAmelCase__										=				probability
									lowerCAmelCase__										=				k_state
			lowerCAmelCase__										=				arg_max

			# Process pointers backwards
			lowerCAmelCase__										=				last_state
			lowerCAmelCase__										=				[]
			for o in range(len(UpperCamelCase_   ) - 1    ,						-1    ,						-1   ):
						result.append(UpperCamelCase_   )
						lowerCAmelCase__										=				pointers[previous, observations_space[o]]
			result.reverse()

			return result







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						)       ->							None:







			'''simple docstring'''



			_validate_not_empty(
			    UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						)
			_validate_lists(UpperCamelCase_    ,						UpperCamelCase_   )
			_validate_dicts(
			    UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_   )







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						)       ->							None:







			'''simple docstring'''



			if not all(
			    [
			        observations_space,
			        states_space,
			        initial_probabilities,
			        transition_probabilities,
			        emission_probabilities,
			    ]   ):
						raise ValueError("There's an empty parameter"   )







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any   )       ->							None:







			'''simple docstring'''



			_validate_list(UpperCamelCase_    ,						"observations_space"   )
			_validate_list(UpperCamelCase_    ,						"states_space"   )







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  str   )       ->							None:







			'''simple docstring'''



			if not isinstance(_object    ,						UpperCamelCase_   ):
						lowerCAmelCase__										=				F"""{var_name} must be a list"""
						raise ValueError(UpperCamelCase_   )
			else:
						for x in _object:
									if not isinstance(UpperCamelCase_    ,						UpperCamelCase_   ):
												lowerCAmelCase__										=				F"""{var_name} must be a list of strings"""
												raise ValueError(UpperCamelCase_   )







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  Any    ,						)       ->							None:







			'''simple docstring'''



			_validate_dict(UpperCamelCase_    ,						"initial_probabilities"    ,						UpperCamelCase_   )
			_validate_nested_dict(UpperCamelCase_    ,						"transition_probabilities"   )
			_validate_nested_dict(UpperCamelCase_    ,						"emission_probabilities"   )







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  str   )       ->							None:







			'''simple docstring'''



			_validate_dict(_object    ,						UpperCamelCase_    ,						UpperCamelCase_   )
			for x in _object.values():
						_validate_dict(UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_   )







def 	A  (   UpperCamelCase_       :  Any    ,						UpperCamelCase_       :  str    ,						UpperCamelCase_       :  type    ,						UpperCamelCase_       :  bool = False   )       ->							None:







			'''simple docstring'''



			if not isinstance(_object    ,						UpperCamelCase_   ):
						lowerCAmelCase__										=				F"""{var_name} must be a dict"""
						raise ValueError(UpperCamelCase_   )
			if not all(isinstance(UpperCamelCase_    ,						UpperCamelCase_   ) for x in _object   ):
						lowerCAmelCase__										=				F"""{var_name} all keys must be strings"""
						raise ValueError(UpperCamelCase_   )
			if not all(isinstance(UpperCamelCase_    ,						UpperCamelCase_   ) for x in _object.values()   ):
						lowerCAmelCase__										=				"nested dictionary " if nested else ""
						lowerCAmelCase__										=				F"""{var_name} {nested_text}all values must be {value_type.__name__}"""
						raise ValueError(UpperCamelCase_   )


if __name__ == "__main__":
		from doctest import testmod

		testmod()







'''simple docstring'''




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


lowercase     :							List[str]       						=     logging.get_logger(__name__)

lowercase     :							Optional[int]       						=     {
    'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
}





class 					A							(				__snake_case		):
     __magic_name__          =						'''switch_transformers'''
     __magic_name__          =						['''past_key_values''']
     __magic_name__          =						{'''hidden_size''': '''d_model''', '''num_attention_heads''': '''num_heads''', '''num_hidden_layers''': '''num_layers'''}





     def __init__(				self		,     SCREAMING_SNAKE_CASE=32128		,     SCREAMING_SNAKE_CASE=768		,     SCREAMING_SNAKE_CASE=64		,     SCREAMING_SNAKE_CASE=2048		,     SCREAMING_SNAKE_CASE=64		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=3		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=3		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=False		,     SCREAMING_SNAKE_CASE=0.01		,     SCREAMING_SNAKE_CASE="float32"		,     SCREAMING_SNAKE_CASE=False		,     SCREAMING_SNAKE_CASE=32		,     SCREAMING_SNAKE_CASE=128		,     SCREAMING_SNAKE_CASE=0.1		,     SCREAMING_SNAKE_CASE=1e-6		,     SCREAMING_SNAKE_CASE=0.001		,     SCREAMING_SNAKE_CASE=0.001		,     SCREAMING_SNAKE_CASE=1.0		,     SCREAMING_SNAKE_CASE="relu"		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=False		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=0		,     SCREAMING_SNAKE_CASE=1		,     **SCREAMING_SNAKE_CASE		,     )					->							List[Any]:






         """simple docstring"""






         A			:  Union[str, Any]   =		vocab_size
         A			:  Any   =		d_model
         A			:  Dict   =		d_kv
         A			:  Optional[Any]   =		d_ff

         A			:  List[Any]   =		num_sparse_encoder_layers

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

         A			:  List[Any]   =		num_heads
         A			:  str   =		num_experts
         A			:  Dict   =		expert_capacity
         A			:  Optional[int]   =		router_bias
         A			:  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}'      )
         A			:  Dict   =		router_dtype

         A			:  int   =		router_ignore_padding_tokens
         A			:  List[Any]   =		relative_attention_num_buckets
         A			:  Dict   =		relative_attention_max_distance

         A			:  Optional[int]   =		dropout_rate
         A			:  Dict   =		layer_norm_epsilon
         A			:  Optional[int]   =		initializer_factor
         A			:  Union[str, Any]   =		feed_forward_proj
         A			:  Any   =		use_cache
         A			:  Tuple   =		add_router_probs

         A			:  List[str]   =		router_z_loss_coef
         A			:  str   =		router_aux_loss_coef

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

         if len(SCREAMING_SNAKE_CASE      ) > 1 and act_info[0] != "gated" or len(SCREAMING_SNAKE_CASE      ) > 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":
             A			:  str   =		'''gelu_new'''

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




