code: def forward(self, inputs, cur_iter=None):
      if self.mapping == "rotate":
          assert inputs.shape[-1] == 3
          pts_flat = torch.cat(
              [
                  torch.sin(inputs @ self.bvals.T),
                  torch.cos(inputs @ self.bvals.T),
              ],
              axis=-1,
          )
          if self.include_input:
              pts_flat = torch.cat([inputs, pts_flat], -1)
          return pts_flat
      else:
          assert cur_iter is None
          return torch.cat([fn(inputs) for fn in self.embed_fns], -1)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import numpy
label_desc: Use image node_id 4 for calling the Embedder obj's underlying member method code with example usage: obj.forward(inputs, cur_iter) and returns: pts_flat, torch