From 5ffa17b2381aa1f298f9d9457bda09a2d9907a9b Mon Sep 17 00:00:00 2001 From: Vasil Zlatanov Date: Mon, 4 Mar 2019 16:41:08 +0000 Subject: Add repeateable conv_layers to dcgan --- dcgan.py | 23 +++++++++++++++-------- 1 file changed, 15 insertions(+), 8 deletions(-) diff --git a/dcgan.py b/dcgan.py index b48e99f..a0a26c9 100644 --- a/dcgan.py +++ b/dcgan.py @@ -15,13 +15,14 @@ import sys import numpy as np class DCGAN(): - def __init__(self): + def __init__(self, conv_layers = 1): # Input shape self.img_rows = 28 self.img_cols = 28 self.channels = 1 self.img_shape = (self.img_rows, self.img_cols, self.channels) self.latent_dim = 100 + self.conv_layers = conv_layers optimizer = Adam(0.002, 0.5) @@ -56,13 +57,19 @@ class DCGAN(): model.add(Dense(128 * 7 * 7, activation="relu", input_dim=self.latent_dim)) model.add(Reshape((7, 7, 128))) model.add(UpSampling2D()) - model.add(Conv2D(128, kernel_size=3, padding="same")) - model.add(BatchNormalization()) - model.add(Activation("relu")) + + for i in range(self.conv_layers): + model.add(Conv2D(128, kernel_size=3, padding="same")) + model.add(BatchNormalization()) + model.add(Activation("relu")) + model.add(UpSampling2D()) - model.add(Conv2D(64, kernel_size=3, padding="same")) - model.add(BatchNormalization()) - model.add(Activation("relu")) + + for i in range(self.conv_layers): + model.add(Conv2D(64, kernel_size=3, padding="same")) + model.add(BatchNormalization()) + model.add(Activation("relu")) + model.add(Conv2D(self.channels, kernel_size=3, padding="same")) model.add(Activation("tanh")) @@ -183,4 +190,4 @@ class DCGAN(): if __name__ == '__main__': dcgan = DCGAN() dcgan.train(epochs=4000, batch_size=32, save_interval=50) -''' \ No newline at end of file +''' -- cgit v1.2.3-54-g00ecf