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author | nunzip <np.scarh@gmail.com> | 2019-03-07 21:36:32 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2019-03-07 21:36:32 +0000 |
commit | 4a534691c7b5875ce7ab50d69e517af7a9db14ce (patch) | |
tree | 0f00adbb2b886731dab7cba78f175989f5718e18 | |
parent | 4d53cc2ae5fa3340d46bc5840fb287ecf8594297 (diff) | |
download | e4-gan-tune_hyp.tar.gz e4-gan-tune_hyp.tar.bz2 e4-gan-tune_hyp.zip |
add dropouttune_hyp
-rwxr-xr-x | cgan.py | 7 |
1 files changed, 4 insertions, 3 deletions
@@ -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() |