code: def __init__(
      self,
      opts,
      num_embeddings: int,
      embedding_dim: int,
      padding_idx: Optional[int] = None,
      sequence_first: Optional[bool] = False,
      interpolation_mode: Optional[str] = "bilinear",
      *args,
      **kwargs,
  ):
      super().__init__()
      self.padding_idx = padding_idx
      self.num_embeddings = num_embeddings
      self.embedding_dim = embedding_dim
      self.sequence_first = sequence_first
      self.interpolation_mode = interpolation_mode
      self.register_buffer("pos_embed", self.get_weights())
  
imports: import math
  from typing import Optional
  import torch
  from torch import Tensor, nn
  from torch.nn import functional
  from cvnets.layers import BaseLayer
label_desc: Use image node_id 1 to create a new SinusoidalPositionalEmbedding object from inherited base classes: nn with example: obj = SinusoidalPositionalEmbedding(opts, num_embeddings, embedding_dim, padding_idx, sequence_first, interpolation_mode)