y = T.ivector("label")
idx = T.lscalar()
corruption_level = T.fscalar()
images = X.reshape((batch_size, 1, 32, 32))
layer_0_en = ReLUConvLayer(filter_size=(4, 4),
num_filters=128,
num_channels=1,
fm_size=(32, 32),
batch_size=batch_size,
border_mode="same")
layer_0_de = SigmoidConvLayer(filter_size=(4, 4),
num_filters=1,
num_channels=128,
fm_size=(32, 32),
batch_size=batch_size,
border_mode="same")
layer_1_en = ReLUConvLayer(filter_size=(2, 2),
num_filters=128,
num_channels=128,
fm_size=(8, 8),
batch_size=batch_size,
border_mode="same")
layer_1_de = SigmoidConvLayer(filter_size=(2, 2),
num_filters=128,
num_channels=128,
fm_size=(8, 8),
batch_size=batch_size,
X = T.matrix("data")
y = T.ivector("label")
idx = T.lscalar()
corruption_level = T.fscalar()
images = X.reshape((batch_size, 1, 32, 32))
layer_0_en = ReLUConvLayer(filter_size=(7, 7),
num_filters=50,
num_channels=1,
fm_size=(32, 32),
batch_size=batch_size)
layer_0_de = SigmoidConvLayer(filter_size=(7, 7),
num_filters=1,
num_channels=50,
fm_size=(26, 26),
batch_size=batch_size,
border_mode="full")
layer_1_en = ReLUConvLayer(filter_size=(5, 5),
num_filters=50,
num_channels=50,
fm_size=(26, 26),
batch_size=batch_size)
layer_1_de = SigmoidConvLayer(filter_size=(5, 5),
num_filters=50,
num_channels=50,
fm_size=(22, 22),
batch_size=batch_size,
border_mode="full")
X = T.matrix("data")
y = T.ivector("label")
idx = T.lscalar()
corruption_level = T.fscalar()
images = X.reshape((batch_size, 1, 32, 32))
layer_0_en = ReLUConvLayer(filter_size=(5, 5),
num_filters=50,
num_channels=1,
fm_size=(32, 32),
batch_size=batch_size)
layer_0_de = SigmoidConvLayer(filter_size=(5, 5),
num_filters=1,
num_channels=50,
fm_size=(28, 28),
batch_size=batch_size,
border_mode="full")
layer_1_en = ReLUConvLayer(filter_size=(5, 5),
num_filters=50,
num_channels=50,
fm_size=(14, 14),
batch_size=batch_size)
layer_1_de = SigmoidConvLayer(filter_size=(5, 5),
num_filters=50,
num_channels=50,
fm_size=(10, 10),
batch_size=batch_size,
border_mode="full")
y=T.ivector("label")
idx=T.lscalar()
corruption_level=T.fscalar()
images=X.reshape((batch_size, 1, 32, 32))
layer_0_en=LCNLayer(filter_size=(4,4),
num_filters=128,
num_channels=1,
fm_size=(32,32),
batch_size=batch_size,
border_mode="same")
layer_0_de=SigmoidConvLayer(filter_size=(4,4),
num_filters=1,
num_channels=128,
fm_size=(32,32),
batch_size=batch_size,
border_mode="same")
# layer_1_en=ReLUConvLayer(filter_size=(2,2),
# num_filters=128,
# num_channels=128,
# fm_size=(8,8),
# batch_size=batch_size,
# border_mode="same")
# layer_1_de=SigmoidConvLayer(filter_size=(2,2),
# num_filters=128,
# num_channels=128,
# fm_size=(8,8),
# batch_size=batch_size,