mmr/tkDNN
Archived
1
0
Fork 0
Code Issues 46 Pull Requests 12 Releases 4 Activity

test ready

Browse Source
This commit is contained in:
Francesco Gatti
2017-06-29 12:26:51 +00:00
parent ba215c35c0
commit 0a0acb9b1d
3 changed files with 17 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/simple_dense.py
+8 -7
View File
@@ -17,18 +17,19 @@ def dense_model():
batch_input_shape=(1, 100, 100, 4), # 100by100by2
output_shape=(100, 100, 4, 1))) # 100by100by2
model.add(Convolution3D(16, kernel_size=(8, 8, 2), subsample=(4, 4, 1), border_mode="valid",
bias_initializer="random_uniform", activation="relu"))
#model.add(ELU())
bias_initializer="random_uniform"))
model.add(ELU())
model.add(AveragePooling3D(pool_size=(2, 2, 1)))
model.add(Convolution3D(16, kernel_size=(4, 4, 2), subsample=(2, 2, 1), border_mode="valid",
bias_initializer="random_uniform", activation="relu"))
bias_initializer="random_uniform"))
model.add(ELU())
model.add(Convolution3D(24, kernel_size=(3, 3, 2), subsample=(1, 1, 1), border_mode="valid",
bias_initializer="random_uniform", activation="relu"))
#model.add(ELU())
bias_initializer="random_uniform"))
model.add(ELU())
model.add(Flatten())
model.add(Dense(256, activation="relu", bias_initializer="random_uniform"))
model.add(Dense(256, bias_initializer="random_uniform"))
model.add(ELU())
model.add(Dense(32, activation="relu", bias_initializer="random_uniform"))
#model.add(ELU())
model.add(Dense(2, bias_initializer="random_uniform"))
sgd = keras.optimizers.Adam(lr=1e-4, decay=1e-8)