vae_m1.py 文件源码

def __init__(self):
        self.image_width = 28
        self.image_height = 28
        self.ndim_x = 28 * 28
        self.ndim_z = 100
        self.batchnorm_before_activation = True

        # gaussianmarg | gaussian
        # We recommend you to use "gaussianmarg" when decoder is gaussian.
        self.type_pz = "gaussianmarg"
        self.type_qz = "gaussianmarg"

        # e.g.
        # ndim_x (input) -> 2000 -> 1000 -> 100 (output)
        # encoder_hidden_units = [2000, 1000]
        self.encoder_hidden_units = [600, 600]
        self.encoder_activation_function = "softplus"
        self.encoder_apply_dropout = True
        self.encoder_apply_batchnorm = True
        self.encoder_apply_batchnorm_to_input = True

        self.decoder_hidden_units = [600, 600]
        self.decoder_activation_function = "softplus"
        self.decoder_apply_dropout = True
        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 = 1.0