
'''simple docstring'''


import math

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




def lowercase_	(   _lowercase			,       _lowercase			,       _lowercase = 1			,       _lowercase = 1			,       _lowercase = 1.0e4			,       _lowercase = False			,       _lowercase = 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"""
					lowerCamelCase_					:      int     =		float(embedding_dim // 2				)
					lowerCamelCase_					:      str     =		math.log(max_timescale / min_timescale				) / (num_timescales - freq_shift)
					lowerCamelCase_					:      int     =		min_timescale * jnp.exp(jnp.arange(_lowercase			,       dtype=jnp.floataa				) * -log_timescale_increment				)
					lowerCamelCase_					:      List[str]     =		jnp.expand_dims(_lowercase			,       1				) * jnp.expand_dims(_lowercase			,       0				)

					# scale embeddings
					lowerCamelCase_					:      Dict     =		scale * emb

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

class 	__lowercase				(  nn.Module    ):
			lowerCamelCase			:		int	      =			32
			lowerCamelCase			:		jnp.dtype	      =			jnp.floataa

			@nn.compact
			def __call__(self			,   A      ):
								lowerCamelCase_					:      Dict     =		nn.Dense(self.time_embed_dim			,   dtype=self.dtype			,   name='''linear_1'''      )(A      )
								lowerCamelCase_					:      Dict     =		nn.silu(A      )
								lowerCamelCase_					:      List[Any]     =		nn.Dense(self.time_embed_dim			,   dtype=self.dtype			,   name='''linear_2'''      )(A      )
								return temb

class 	__lowercase				(  nn.Module    ):
			lowerCamelCase			:		int	      =			32
			lowerCamelCase			:		bool	      =			False
			lowerCamelCase			:		float	      =			1

			@nn.compact
			def __call__(self			,   A      ):
								return get_sinusoidal_embeddings(
								    A			,   embedding_dim=self.dim			,   flip_sin_to_cos=self.flip_sin_to_cos			,   freq_shift=self.freq_shift      )




'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


__lowercase							:   List[Any]					=     {}


try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowercase							:   List[Any]					=     ['''MLukeTokenizer''']

if TYPE_CHECKING:
					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mluke import MLukeTokenizer


else:
					import sys

					__lowercase							:   List[str]					=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


