
from __future__ import annotations

__a         =   '#'
class 					lowercase__:



	"""simple docstring"""




	def __init__(			self    :     Dict			)			->	None:
					lowercase_	    =   {}
	def 		_lowercase    (			self    :     str			,				SCREAMING_SNAKE_CASE_    :     str			)			->	None:
					lowercase_	    =   self._trie
					for char in text:
									if char not in trie:
													lowercase_	    =   {}
									lowercase_	    =   trie[char]
					lowercase_	    =   True
	def 		_lowercase    (			self    :     Dict			,				SCREAMING_SNAKE_CASE_    :     str			)			->	tuple | list:
					lowercase_	    =   self._trie
					for char in prefix:
									if char in trie:
													lowercase_	    =   trie[char]
									else:
													return []
					return self._elements(SCREAMING_SNAKE_CASE_			)




	def 		_lowercase    (			self    :     int			,				SCREAMING_SNAKE_CASE_    :     dict			)			->	tuple:
					lowercase_	    =   []
					for c, v in d.items():
									lowercase_	    =   [''' '''] if c == END else [(c + s) for s in self._elements(SCREAMING_SNAKE_CASE_			)]
									result.extend(SCREAMING_SNAKE_CASE_			)
					return tuple(SCREAMING_SNAKE_CASE_			)

__a         =   Trie()
__a         =   ('depart', 'detergent', 'daring', 'dog', 'deer', 'deal')
for word in words:
						trie.insert_word(word)




def 							a		(				snake_case__:   str   ):


				'''simple docstring'''
				lowercase_	    =   trie.find_word(snake_case__   )
				return tuple(string + word for word in suffixes   )




def 							a		(				):


				'''simple docstring'''
				print(autocomplete_using_trie('''de'''   )   )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()







'''simple docstring'''





import math

import flax.linen as nn
import jax.numpy as jnp






def 				_lowerCAmelCase			(   __magic_name__						:     jnp.ndarray   , __magic_name__						:     int   , __magic_name__						:     float = 1   , __magic_name__						:     float = 1   , __magic_name__						:     float = 1.0E4   , __magic_name__						:     bool = False   , __magic_name__						:     float = 1.0   , )				->  jnp.ndarray:
						assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
						assert embedding_dim % 2 == 0, f'''Embedding dimension {embedding_dim} should be even'''
						lowercase :							int    		=float(embedding_dim // 2						)
						lowercase :							Optional[int]    		=math.log(max_timescale / min_timescale						) / (num_timescales - freq_shift)
						lowercase :							Any    		=min_timescale * jnp.exp(jnp.arange(__magic_name__   , dtype=jnp.floataa						) * -log_timescale_increment						)
						lowercase :							List[Any]    		=jnp.expand_dims(__magic_name__   , 1						) * jnp.expand_dims(__magic_name__   , 0						)

						# scale embeddings
						lowercase :							Tuple    		=scale * emb

						if flip_sin_to_cos:
												lowercase :							Dict    		=jnp.concatenate([jnp.cos(__magic_name__						), jnp.sin(__magic_name__						)]   , axis=1						)
						else:
												lowercase :							Any    		=jnp.concatenate([jnp.sin(__magic_name__						), jnp.cos(__magic_name__						)]   , axis=1						)
						lowercase :							List[str]    		=jnp.reshape(__magic_name__   , [jnp.shape(__magic_name__						)[0], embedding_dim]						)
						return signal





class 		__SCREAMING_SNAKE_CASE							(			nn.Module      ):
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    jnp.floataa







				@nn.compact
				def __call__(       self     :		Tuple		,					UpperCAmelCase__     :		int   ):
										'''simple docstring'''
										lowercase :							List[Any]    		=nn.Dense(self.time_embed_dim		,					dtype=self.dtype		,					name='''linear_1'''   )(UpperCAmelCase__   )
										lowercase :							Any    		=nn.silu(UpperCAmelCase__   )
										lowercase :							int    		=nn.Dense(self.time_embed_dim		,					dtype=self.dtype		,					name='''linear_2'''   )(UpperCAmelCase__   )
										return temb





class 		__SCREAMING_SNAKE_CASE							(			nn.Module      ):
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    1







				@nn.compact
				def __call__(       self     :		int		,					UpperCAmelCase__     :		str   ):
										'''simple docstring'''
										return get_sinusoidal_embeddings(
										    UpperCAmelCase__		,					embedding_dim=self.dim		,					flip_sin_to_cos=self.flip_sin_to_cos		,					freq_shift=self.freq_shift   )





