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| author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-05-09 14:11:34 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:51:37 +0000 |
| commit | c13021e335b3e395c9d1a3a9935baedb42aebf08 (patch) | |
| tree | 5ee995961cea6b76fe4c1aee2e60920ee845a83e /examples/graph_inception_v3.cpp | |
| parent | e29e0d4292a2e569ecad340438942632ae6a92e4 (diff) | |
| download | ComputeLibrary-c13021e335b3e395c9d1a3a9935baedb42aebf08.tar.gz | |
COMPMID-1109 - Enabling Winograd in the graph when possible
Change-Id: I524abd28188995ae9c7a43b189b1eb2d7546be93
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/130576
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'examples/graph_inception_v3.cpp')
| -rw-r--r-- | examples/graph_inception_v3.cpp | 9 |
1 files changed, 4 insertions, 5 deletions
diff --git a/examples/graph_inception_v3.cpp b/examples/graph_inception_v3.cpp index ed79ba65d8..01a4d0c49c 100644 --- a/examples/graph_inception_v3.cpp +++ b/examples/graph_inception_v3.cpp @@ -51,10 +51,9 @@ public: std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); // 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); - - ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM; + const int target = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0; + Target target_hint = set_target_hint(target); + ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT; // Parse arguments if(argc < 2) @@ -100,8 +99,8 @@ public: get_random_accessor(1.f, 1.f), get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_beta.npy"), 0.001f) - << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) << convolution_hint + << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) << ConvolutionLayer(3U, 3U, 32U, get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_weights.npy"), std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 0, 0)) |