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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 /tests/validation/CL/DilatedConvolutionLayer.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 'tests/validation/CL/DilatedConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/CL/DilatedConvolutionLayer.cpp | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tests/validation/CL/DilatedConvolutionLayer.cpp b/tests/validation/CL/DilatedConvolutionLayer.cpp index 9da7c32d7c..25931c0f4c 100644 --- a/tests/validation/CL/DilatedConvolutionLayer.cpp +++ b/tests/validation/CL/DilatedConvolutionLayer.cpp @@ -66,13 +66,13 @@ TEST_SUITE(DilatedConvolutionLayer) DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(23U, 27U, 23U, 4U), 1, DataType::F32, 0), TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) }), framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 23U, 21U), 1, DataType::F32, 0), TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) })), |