code: def add_mvn(self, name, input_name, output_name, across_channels = True, normalize_variance = True, epsilon = 1e-5):
          
  
          spec = self.spec
          nn_spec = self.nn_spec
  
          # Add a new layer
          spec_layer = nn_spec.layers.add()
          spec_layer.name = name
          spec_layer.input.append(input_name)
          spec_layer.output.append(output_name)
  
          spec_layer_params = spec_layer.mvn
          spec_layer_params.acrossChannels = across_channels
          spec_layer_params.normalizeVariance = normalize_variance
          spec_layer_params.epsilon = epsilon
docs: Add an MVN (mean variance normalization) layer. Computes mean, variance and normalizes the input.
  
          Parameters
          ----------
          name: str
              The name of this layer.
  
          input_name: str
              The input blob name of this layer.
          output_name: str
              The output blob name of this layer.
  
          across_channels: boolean
              If False, each channel plane is normalized separately
              If True, mean/variance is computed across all C, H and W dimensions
  
          normalize_variance: boolean
              If False, only mean subtraction is performed.
  
          epsilon: float
              small bias to avoid division by zero.
  
  
          See Also
          --------
          add_l2_normalize, add_lrn