self._n_fms_out = n_fms_out
// Apply all the straightforward operations on the input, such as BN, activation function, dropout, pooling
(inputToConvTrain, inputToConvVal, inputToConvTest) = self._processInputWithBnNonLinearityDropoutPooling(rng,
inputToLayerTrain,
inputToLayerVal,
inputToLayerTest,
After Change
self._layers.append(self._bn_l)
else : //Not using batch normalization
//make the bias terms and apply them. Like the old days before BN"s own learnt bias terms.
bias_l = dm_layers.BiasLayer(n_fms_in)
self._layers.append(bias_l)
//------------ Apply Activation/ non-linearity -----------
act_l = dm_layers.get_act_layer(activationFunc, n_fms_in)
