code: def create_embedding_fn(self):
      embed_fns = []
      out_dim = 0
      if self.include_input:
          embed_fns.append(lambda x: x)
          out_dim += self.input_dims
  
      if self.log_sampling:
          freq_bands = 2.0 ** torch.linspace(
              self.min_freq, self.max_freq, steps=self.N_freqs
          )
      else:
          assert 0
          freq_bands = torch.linspace(
              2.0**0.0, 2.0**self.max_freq, steps=self.N_freqs
          )
  
      for freq in freq_bands:
          for p_fn in [torch.sin, torch.cos]:
              embed_fns.append(
                  lambda x, p_fn=p_fn, freq=freq: p_fn(x * freq)
              )
              out_dim += self.input_dims
  
      self.embed_fns = embed_fns
      self.out_dim = out_dim
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import numpy
label_desc: Use image node_id 3 for calling the Embedder obj's underlying member method code with example usage: obj.create_embedding_fn() without return types