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author | Giorgio Arena <giorgio.arena@arm.com> | 2018-06-12 11:30:50 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:52:54 +0000 |
commit | e083771a1f28c34485f0d0054e2645070df98846 (patch) | |
tree | d9798d0605cfc916cac8acf145a09ecf74e2f94e /examples/graph_alexnet.cpp | |
parent | 5cb37732db883e2fb9d96fc3698df8837dbcc8db (diff) | |
download | ComputeLibrary-e083771a1f28c34485f0d0054e2645070df98846.tar.gz |
COMPMID-1160 Turn Graph hints into heuristics
Change-Id: Id24c2f07c59d863f8e1af6a1afbf6a542b2b9954
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/135142
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'examples/graph_alexnet.cpp')
-rw-r--r-- | examples/graph_alexnet.cpp | 12 |
1 files changed, 3 insertions, 9 deletions
diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp index 9e6d91962e..5328662b6d 100644 --- a/examples/graph_alexnet.cpp +++ b/examples/graph_alexnet.cpp @@ -53,13 +53,9 @@ public: std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON - const int target = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0; - Target target_hint = set_target_hint(target); - - const bool is_neon = (target_hint == Target::NEON); - ConvolutionMethod convolution_5x5_hint = is_neon ? ConvolutionMethod::GEMM : ConvolutionMethod::DIRECT; - ConvolutionMethod convolution_3x3_hint = ConvolutionMethod::DEFAULT; - FastMathHint fast_math_hint = FastMathHint::DISABLED; + const int target = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0; + Target target_hint = set_target_hint(target); + FastMathHint fast_math_hint = FastMathHint::DISABLED; // Parse arguments if(argc < 2) @@ -117,7 +113,6 @@ public: << 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( 5U, 5U, 256U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_w.npy"), @@ -127,7 +122,6 @@ public: << 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( 3U, 3U, 384U, |