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| author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-05-14 14:21:39 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:52:35 +0000 |
| commit | a8aef2916379402e241d9f2c5e0faf3f99c860f7 (patch) | |
| tree | accf1f74bb836766260dbdb90aad7b6048c675d2 /examples/graph_googlenet.cpp | |
| parent | cb0010b02281245c66d5c996fa9ef8b22f036a2d (diff) | |
| download | ComputeLibrary-a8aef2916379402e241d9f2c5e0faf3f99c860f7.tar.gz | |
COMPMID-792 - Re-enabled Winograd on NEON in all graph examples.
Since now the input transform can be multi-threaded, I re-ebaled Winograd in all graph examples
Change-Id: I39ef78243bb47fdae135e18dcae2102af0675b3b
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/131048
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'examples/graph_googlenet.cpp')
| -rw-r--r-- | examples/graph_googlenet.cpp | 8 |
1 files changed, 3 insertions, 5 deletions
diff --git a/examples/graph_googlenet.cpp b/examples/graph_googlenet.cpp index bac3c7c6d5..a47fc9d588 100644 --- a/examples/graph_googlenet.cpp +++ b/examples/graph_googlenet.cpp @@ -52,10 +52,9 @@ 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); - ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : 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) @@ -107,7 +106,6 @@ public: get_weights_accessor(data_path, "/cnn_data/googlenet_model/conv1/conv1_7x7_s2_w.npy"), get_weights_accessor(data_path, "/cnn_data/googlenet_model/conv1/conv1_7x7_s2_b.npy"), PadStrideInfo(2, 2, 3, 3)) - << convolution_hint << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL))) << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)) |