From d36c8c88fc435aa4372e6c5564f0ff12fc7120e9 Mon Sep 17 00:00:00 2001
From: nunzip <np.scarh@gmail.com>
Date: Fri, 8 Mar 2019 01:34:10 +0000
Subject: add variable dropout
---
cgan.py | 7 ++++---
dcgan.py | 11 ++++++-----
2 files changed, 10 insertions(+), 8 deletions(-)
diff --git a/cgan.py b/cgan.py
index 6406244..68bb2cc 100755
--- a/cgan.py
+++ b/cgan.py
@@ -15,7 +15,7 @@ from tqdm import tqdm
import numpy as np
class CGAN():
- def __init__(self, dense_layers = 3):
+ def __init__(self, dense_layers = 3, dropout=0.4):
# Input shape
self.img_rows = 28
self.img_cols = 28
@@ -24,6 +24,7 @@ class CGAN():
self.num_classes = 10
self.latent_dim = 100
self.dense_layers = dense_layers
+ self.dropout = dropout
optimizer = Adam(0.0002, 0.5)
@@ -87,10 +88,10 @@ class CGAN():
model.add(LeakyReLU(alpha=0.2))
model.add(Dense(512))
model.add(LeakyReLU(alpha=0.2))
- model.add(Dropout(0.4))
+ model.add(Dropout(self.dropout))
model.add(Dense(512))
model.add(LeakyReLU(alpha=0.2))
- model.add(Dropout(0.4))
+ model.add(Dropout(self.dropout))
model.add(Dense(1, activation='sigmoid'))
#model.summary()
diff --git a/dcgan.py b/dcgan.py
index 347f61e..7844843 100644
--- a/dcgan.py
+++ b/dcgan.py
@@ -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(self.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(self.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(self.dropout))
model.add(Flatten())
model.add(Dense(1, activation='sigmoid'))
--
cgit v1.2.3-70-g09d2