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,