diff options
Diffstat (limited to 'examples/graph_alexnet.cpp')
| -rw-r--r-- | examples/graph_alexnet.cpp | 34 |
1 files changed, 21 insertions, 13 deletions
diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp index 6a3c14b7bb..d654f9ece9 100644 --- a/examples/graph_alexnet.cpp +++ b/examples/graph_alexnet.cpp @@ -103,9 +103,10 @@ public: get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv1_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv1_b.npy"), PadStrideInfo(4, 4, 0, 0)) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) - << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)) - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))) + .set_name("conv1") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu1") + << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)).set_name("norm1") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool1") // Layer 2 << convolution_5x5_hint << ConvolutionLayer( @@ -113,9 +114,10 @@ public: get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_b.npy"), PadStrideInfo(1, 1, 2, 2), 2) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) - << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)) - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))) + .set_name("conv2") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu2") + << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)).set_name("norm2") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool2") << convolution_3x3_hint // Layer 3 << ConvolutionLayer( @@ -123,41 +125,47 @@ public: get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv3_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv3_b.npy"), PadStrideInfo(1, 1, 1, 1)) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + .set_name("conv3") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu3") // Layer 4 << ConvolutionLayer( 3U, 3U, 384U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv4_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv4_b.npy"), PadStrideInfo(1, 1, 1, 1), 2) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + .set_name("conv4") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu4") // Layer 5 << ConvolutionLayer( 3U, 3U, 256U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv5_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv5_b.npy"), PadStrideInfo(1, 1, 1, 1), 2) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) - << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))) + .set_name("conv5") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu5") + << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool5") // Layer 6 << FullyConnectedLayer( 4096U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc6_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc6_b.npy")) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + .set_name("fc6") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu6") // Layer 7 << FullyConnectedLayer( 4096U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc7_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc7_b.npy")) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + .set_name("fc7") + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu7") // Layer 8 << FullyConnectedLayer( 1000U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc8_w.npy"), get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc8_b.npy")) + .set_name("fc8") // Softmax - << SoftmaxLayer() + << SoftmaxLayer().set_name("prob") << OutputLayer(get_output_accessor(label, 5)); // Finalize graph |