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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/ConvolutionLayer.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/ConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/CL/ConvolutionLayer.cpp | 14 |
1 files changed, 10 insertions, 4 deletions
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp index 935a6ebefa..0c40953524 100644 --- a/tests/validation/CL/ConvolutionLayer.cpp +++ b/tests/validation/CL/ConvolutionLayer.cpp @@ -77,22 +77,25 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z 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, 31U, 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), - TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32, 0), TensorInfo(TensorShape(17U, 31U, 2U), 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, 31U, 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), - TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32, 0), TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0) })), framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0), TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0), TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0), TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, 0), @@ -101,6 +104,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(3, 2, 1, 0), PadStrideInfo(1, 1, 2, 2), @@ -109,6 +113,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z framework::dataset::make("GpuTarget", { GPUTarget::BIFROST, GPUTarget::MIDGARD, GPUTarget::G71, + GPUTarget::G71, GPUTarget::MIDGARD, GPUTarget::BIFROST, GPUTarget::BIFROST, @@ -122,12 +127,13 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z Size2D(1U, 1U), Size2D(1U, 1U), Size2D(1U, 1U), + Size2D(1U, 1U), Size2D(2U, 1U), })), -framework::dataset::make("EnableFastMath", { false, false, false, false, false, true, true })), +framework::dataset::make("EnableFastMath", { false, false, false, false, false, false, true, true })), framework::dataset::make("Expected", { - ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, + ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, })), input_info, weights_info, output_info, conv_info, gpu_target, dilation, enable_fast_math, expected) { |