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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2018-07-20 13:23:44 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:54 +0000 |
commit | e2220551b7a64b929650ba9a60529c31e70c13c5 (patch) | |
tree | 5d609887f15b4392cdade7bb388710ceafc62260 /examples/graph_alexnet.cpp | |
parent | eff8d95991205e874091576e2d225f63246dd0bb (diff) | |
download | ComputeLibrary-e2220551b7a64b929650ba9a60529c31e70c13c5.tar.gz |
COMPMID-1367: Enable NHWC in graph examples
Change-Id: Iabc54a3a1bdcd46a9a921cda39c7c85fef672b72
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/141449
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'examples/graph_alexnet.cpp')
-rw-r--r-- | examples/graph_alexnet.cpp | 27 |
1 files changed, 16 insertions, 11 deletions
diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp index 63e7b16128..944a435c3b 100644 --- a/examples/graph_alexnet.cpp +++ b/examples/graph_alexnet.cpp @@ -60,7 +60,6 @@ public: // Checks ARM_COMPUTE_EXIT_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "Unsupported data type!"); - ARM_COMPUTE_EXIT_ON_MSG(common_params.data_layout == DataLayout::NHWC, "Unsupported data layout!"); // Print parameter values std::cout << common_params << std::endl; @@ -72,14 +71,20 @@ public: const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } }; std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + // Create input descriptor + const TensorShape tensor_shape = permute_shape(TensorShape(227U, 227U, 3U, 1U), DataLayout::NCHW, common_params.data_layout); + TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout); + + // Set weights trained layout + const DataLayout weights_layout = DataLayout::NCHW; + graph << common_params.target << common_params.fast_math_hint - << InputLayer(TensorDescriptor(TensorShape(227U, 227U, 3U, 1U), common_params.data_type), - get_input_accessor(common_params, std::move(preprocessor))) + << InputLayer(input_descriptor, get_input_accessor(common_params, std::move(preprocessor))) // Layer 1 << ConvolutionLayer( 11U, 11U, 96U, - get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv1_w.npy"), + get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv1_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv1_b.npy"), PadStrideInfo(4, 4, 0, 0)) .set_name("conv1") @@ -89,7 +94,7 @@ public: // Layer 2 << ConvolutionLayer( 5U, 5U, 256U, - get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_w.npy"), + get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_b.npy"), PadStrideInfo(1, 1, 2, 2), 2) .set_name("conv2") @@ -99,7 +104,7 @@ public: // Layer 3 << ConvolutionLayer( 3U, 3U, 384U, - get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv3_w.npy"), + get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv3_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv3_b.npy"), PadStrideInfo(1, 1, 1, 1)) .set_name("conv3") @@ -107,7 +112,7 @@ public: // 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_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv4_b.npy"), PadStrideInfo(1, 1, 1, 1), 2) .set_name("conv4") @@ -115,7 +120,7 @@ public: // 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_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv5_b.npy"), PadStrideInfo(1, 1, 1, 1), 2) .set_name("conv5") @@ -124,21 +129,21 @@ public: // 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_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc6_b.npy")) .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_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc7_b.npy")) .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_w.npy", weights_layout), get_weights_accessor(data_path, "/cnn_data/alexnet_model/fc8_b.npy")) .set_name("fc8") // Softmax |