class_docstr: This module produces sinusoidal positional embeddings of any length.
class_docstr_tok: ["This","module","produces","sinusoidal","positional","embeddings","of","any","length","."]
code: def __init__(self, num_positions: int, embedding_dim: int) -> None:
      super().__init__(num_positions, embedding_dim)
      self.weight = self._init_weight(self.weight)
  
imports: from typing import Tuple
  import numpy
  import torch
  from torch import nn
  from gluonts.core.component import validated
  from gluonts.model import Input, InputSpec
  from gluonts.torch.distributions import StudentTOutput
  from gluonts.torch.scaler import StdScaler, MeanScaler, NOPScaler
  from gluonts.torch.util import unsqueeze_expand, weighted_average
  from gluonts.torch.model.simple_feedforward import make_linear_layer
label_desc: Use image node_id 1 to create a new SinusoidalPositionalEmbedding object from inherited base classes: nn with example: obj = SinusoidalPositionalEmbedding(num_positions, embedding_dim)