parameters: (weight_file)
return_statement: return torch.nn.Parameter(
          data=torch.from_numpy(data),
          requires_grad=False
      )
docstring: Create a PyTorch Parameter object with weights from LBANN.
  
      Weight file is assumed to have been created by the "dump weights"
      callback in LBANN.
docstring_summary: Create a PyTorch Parameter object with weights from LBANN.
docstring_tokens: Create a PyTorch Parameter object with weights from LBANN .
function: def load_parameter(weight_file):
      """Create a PyTorch Parameter object with weights from LBANN.
  
      Weight file is assumed to have been created by the "dump weights"
      callback in LBANN.
  
      """
      data = np.loadtxt(weight_file, dtype=np.float32)
      return torch.nn.Parameter(
          data=torch.from_numpy(data),
          requires_grad=False
      )
function_tokens: def load_parameter ( weight_file ) : data = np . loadtxt ( weight_file , dtype = np . float32 ) return torch . nn . Parameter ( data = torch . from_numpy ( data ) , requires_grad = False )