7272af90d4f5916f61f8bc5660e5605e730bbd78,examples/securenn/network_d.py,ModelTrainer,build_training_graph,#ModelTrainer#Any#,97

Before Change

                              self.KERNEL,
                              self.IN_CHANNELS,
                              self.HIDDEN_CHANNELS], 1.)
    bconv1 = bias_variable([1, 1, self.HIDDEN_CHANNELS])
    wfc1 = weight_variable([self.HIDDEN_FC1, self.HIDDEN_FC2], 1.)
    bfc1 = bias_variable([self.HIDDEN_FC2])
    wfc2 = weight_variable([self.HIDDEN_FC2, self.OUT_N], 1.)
    bfc2 = bias_variable([self.OUT_N])

After Change

    
    // model parameters and initial values
    model = keras.Sequential()
    model.add(keras.layers.Conv2D(self.HIDDEN_CHANNELS,
                                  (self.KERNEL, self.KERNEL),
                                  batch_input_shape=(self.BATCH_SIZE,
                                                     self.IN_DIM,
                                                     self.IN_DIM,
                                                     self.IN_CHANNELS)))
    model.add(keras.layers.Activation("relu"))
    model.add(keras.layers.AveragePooling2D())
    model.add(keras.layers.Flatten())

Instances