diff options
| -rw-r--r-- | dcgan.py | 11 |
1 files changed, 6 insertions, 5 deletions
@@ -17,7 +17,7 @@ import sys import numpy as np class DCGAN(): - def __init__(self, conv_layers = 1): + def __init__(self, conv_layers = 1, dropout=0.25): # Input shape self.img_rows = 28 self.img_cols = 28 @@ -25,6 +25,7 @@ class DCGAN(): self.img_shape = (self.img_rows, self.img_cols, self.channels) self.latent_dim = 100 self.conv_layers = conv_layers + self.dropout = dropout optimizer = Adam(0.002, 0.5) @@ -88,20 +89,20 @@ class DCGAN(): model.add(Conv2D(32, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same")) model.add(LeakyReLU(alpha=0.2)) - model.add(Dropout(0.25)) + model.add(Dropout(self.dropout)) model.add(Conv2D(64, kernel_size=3, strides=2, padding="same")) model.add(ZeroPadding2D(padding=((0,1),(0,1)))) model.add(BatchNormalization()) model.add(LeakyReLU(alpha=0.2)) - model.add(Dropout(0.25)) + model.add(Dropout(dropout)) model.add(Conv2D(128, kernel_size=3, strides=2, padding="same")) model.add(BatchNormalization()) model.add(LeakyReLU(alpha=0.2)) - model.add(Dropout(0.25)) + model.add(Dropout(dropout)) model.add(Conv2D(256, kernel_size=3, strides=1, padding="same")) model.add(BatchNormalization()) model.add(LeakyReLU(alpha=0.2)) - model.add(Dropout(0.25)) + model.add(Dropout(dropout)) model.add(Flatten()) model.add(Dense(1, activation='sigmoid')) |