parameters: (self, conversion_parameters: typing.Mapping[str, typing.Any])
docstring: Return the appropriate ELL node
docstring_summary: Return the appropriate ELL node
docstring_tokens: Return the appropriate ELL node
function: def convert(self, conversion_parameters: typing.Mapping[str, typing.Any]):
          """
          Return the appropriate ELL node
          """
          layer_parameters = self.get_layer_parameters(conversion_parameters)
          activation = self.importer_node.attributes["activation"]
          alpha = 0.01
          if "alpha" in self.importer_node.attributes:
              alpha = self.importer_node.attributes["alpha"]
          if (activation == ell.neural.ActivationType.leaky):
              return ell.neural.LeakyReLUActivationLayer(layer_parameters, alpha)
          else:
              return ell.neural.ActivationLayer(layer_parameters, activation)
function_tokens: def convert ( self , conversion_parameters : typing . Mapping [ str , typing . Any ] ) : layer_parameters = self . get_layer_parameters ( conversion_parameters ) activation = self . importer_node . attributes [ "activation" ] alpha = 0.01 if "alpha" in self . importer_node . attributes : alpha = self . importer_node . attributes [ "alpha" ] if ( activation == ell . neural . ActivationType . leaky ) : return ell . neural . LeakyReLUActivationLayer ( layer_parameters , alpha ) else : return ell . neural . ActivationLayer ( layer_parameters , activation )