code: def forward(self, inputs, **kwargs):
      # inputs: [..., input_dim]
      # return: [..., ]
  
      prefix_shape = list(inputs.shape[:-1])
      inputs = inputs.reshape(-1, self.input_dim)
  
      outputs = freq_encode(inputs, self.degree, self.output_dim)
  
      outputs = outputs.reshape(prefix_shape + [self.output_dim])
  
      return outputs
  
file_path: NeMo/nemo/collections/multimodal/modules/nerf/utils/torch_ngp/freqencoder.py
imports: import _freqencoder
  import torch
  import torch.nn
  from torch.autograd import Function
  from torch.cuda.amp import custom_bwd, custom_fwd
label_desc: Use image node_id 3 for calling the FreqEncoder obj's underlying member method code with example usage: obj.forward(inputs) and returns: outputs