vae_m2.py 文件源码

def __init__(self):
        self.image_width = 28
        self.image_height = 28
        self.ndim_x = 28 * 28
        self.ndim_y = 10
        self.ndim_z = 50

        # True : y = f(BN(Wx + b))
        # False: y = f(W*BN(x) + b)
        self.batchnorm_before_activation = True

        # gaussianmarg | gaussian
        self.type_pz = "gaussianmarg"
        self.type_qz = "gaussianmarg"

        self.encoder_xy_z_hidden_units = [500]
        self.encoder_xy_z_activation_function = "softplus"
        self.encoder_xy_z_apply_dropout = False
        self.encoder_xy_z_apply_batchnorm = True
        self.encoder_xy_z_apply_batchnorm_to_input = True

        self.encoder_x_y_hidden_units = [500]
        self.encoder_x_y_activation_function = "softplus"
        self.encoder_x_y_apply_dropout = False
        self.encoder_x_y_apply_batchnorm = True
        self.encoder_x_y_apply_batchnorm_to_input = True

        self.decoder_hidden_units = [500]
        self.decoder_activation_function = "softplus"
        self.decoder_apply_dropout = False
        self.decoder_apply_batchnorm = True
        self.decoder_apply_batchnorm_to_input = True

        self.gpu_enabled = True
        self.learning_rate = 0.0003
        self.gradient_momentum = 0.9
        self.gradient_clipping = 5.0