





"""simple docstring"""





import math

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


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_ = 1  ,			UpperCAmelCase_ = 1  ,			UpperCAmelCase_ = 1.0e4  ,			UpperCAmelCase_ = False  ,			UpperCAmelCase_ = 1.0  ,			)						->jnp.ndarray:





  """simple docstring"""


  assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
  assert embedding_dim % 2 == 0, f'''Embedding dimension {embedding_dim} should be even'''
  __UpperCAmelCase    :						List[str]       =						float(embedding_dim // 2  )
  __UpperCAmelCase    :						int       =						math.log(max_timescale / min_timescale  ) / (num_timescales - freq_shift)
  __UpperCAmelCase    :						Tuple       =						min_timescale * jnp.exp(jnp.arange(UpperCAmelCase_  ,			dtype=jnp.floataa  ) * -log_timescale_increment  )
  __UpperCAmelCase    :						int       =						jnp.expand_dims(UpperCAmelCase_  ,			1  ) * jnp.expand_dims(UpperCAmelCase_  ,			0  )

  # scale embeddings
  __UpperCAmelCase    :						Union[str, Any]       =						scale * emb

  if flip_sin_to_cos:
    __UpperCAmelCase    :						Any       =						jnp.concatenate([jnp.cos(UpperCAmelCase_  ), jnp.sin(UpperCAmelCase_  )]  ,			axis=1  )
  else:
    __UpperCAmelCase    :						Optional[Any]       =						jnp.concatenate([jnp.sin(UpperCAmelCase_  ), jnp.cos(UpperCAmelCase_  )]  ,			axis=1  )
  __UpperCAmelCase    :						List[Any]       =						jnp.reshape(UpperCAmelCase_  ,			[jnp.shape(UpperCAmelCase_  )[0], embedding_dim]  )
  return signal




class 							snake_case							(			nn.Module ):

      '''simple docstring'''



      _A     :       int         =       32
      _A     :       jnp.dtype         =       jnp.floataa

      @nn.compact
      def __call__(							self       :      Any						,				__lowercase       :      List[str] ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						nn.Dense(self.time_embed_dim						,				dtype=self.dtype						,				name='''linear_1''' )(__lowercase )
        __UpperCAmelCase    :						Union[str, Any]       =						nn.silu(__lowercase )
        __UpperCAmelCase    :						Tuple       =						nn.Dense(self.time_embed_dim						,				dtype=self.dtype						,				name='''linear_2''' )(__lowercase )
        return temb




class 							snake_case							(			nn.Module ):

      '''simple docstring'''



      _A     :       int         =       32
      _A     :       bool         =       False
      _A     :       float         =       1

      @nn.compact
      def __call__(							self       :      Union[str, Any]						,				__lowercase       :      Union[str, Any] ):


        '''simple docstring'''




        return get_sinusoidal_embeddings(
            __lowercase						,				embedding_dim=self.dim						,				flip_sin_to_cos=self.flip_sin_to_cos						,				freq_shift=self.freq_shift )






"""simple docstring"""





def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->bool:





  """simple docstring"""


  return numa ^ numa < 0


if __name__ == "__main__":
  import doctest

  doctest.testmod()