code: def forward(self, diffusion_step):
      x = self.embedding[diffusion_step]
      x = self.projection1(x)
      x = F.silu(x)
      x = self.projection2(x)
      x = F.silu(x)
      return x
  
imports: import math
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the DiffusionEmbedding obj's underlying member method code with example usage: obj.forward(diffusion_step) and returns: x