b656f8857d91b25d5de73de5e429638ece6b13ce,snntoolbox/model_libs/keras_input_lib.py,,extract,#Any#,28

Before Change

                    flattened = True
                if label in bn_layers:
                    parameters = next_layer.get_weights()  // W, b of next layer
                    print("Absorbing batch-normalization parameters into " +
                          "parameters of layer {}, {}.".format(k, label))
                    break
            parameters_norm = absorb_bn(parameters[0], parameters[1],
                                        bn_parameters[0], bn_parameters[1],
                                        bn_parameters[2], bn_parameters[3],

After Change

                                        layer.epsilon)
            // Remove Batch-normalization layer by setting gamma=1, beta=1,
            // mean=0, std=1
            zeros = np.zeros_like(bn_parameters[0])
            ones = np.ones_like(bn_parameters[0])
            layer.set_weights([ones, zeros, zeros, ones])
            // Replace parameters of preceding Conv or FC layer by parameters
            // that include the batch-normalization transformation.

Instances