diff options
Diffstat (limited to 'src/backends/cl')
-rwxr-xr-x | src/backends/cl/test/ClLayerTests.cpp | 15 | ||||
-rw-r--r-- | src/backends/cl/workloads/ClSoftmaxBaseWorkload.cpp | 6 |
2 files changed, 0 insertions, 21 deletions
diff --git a/src/backends/cl/test/ClLayerTests.cpp b/src/backends/cl/test/ClLayerTests.cpp index 862648e4cc..10c177c8b8 100755 --- a/src/backends/cl/test/ClLayerTests.cpp +++ b/src/backends/cl/test/ClLayerTests.cpp @@ -121,21 +121,6 @@ ARMNN_AUTO_TEST_CASE(DepthwiseConvolution2dAsymmetricNhwc, ARMNN_AUTO_TEST_CASE(UnbiasedDepthwiseConvolution2dAsymmetricNhwc, DepthwiseConvolution2dAsymmetricTest, false, armnn::DataLayout::NHWC) -// Softmax -BOOST_AUTO_TEST_CASE(Softmax4dSupport) -{ - const unsigned int numDimensions = 4u; - std::array<unsigned int, numDimensions> dimensionSizes; - dimensionSizes.fill(1u); - - const armnn::TensorInfo inputInfo(numDimensions, &dimensionSizes.front(), armnn::DataType::Float32); - const armnn::TensorInfo outputInfo(numDimensions, &dimensionSizes.front(), armnn::DataType::Float32); - - // 4D Softmax should be reported as unsupported on the CL backend - armnn::ClLayerSupport layerSupport; - BOOST_TEST(!layerSupport.IsSoftmaxSupported(inputInfo, outputInfo, armnn::SoftmaxDescriptor())); -} - // Splitter ARMNN_AUTO_TEST_CASE(SimpleSplitter, SplitterTest) ARMNN_AUTO_TEST_CASE(SimpleSplitterUint8, SplitterUint8Test) diff --git a/src/backends/cl/workloads/ClSoftmaxBaseWorkload.cpp b/src/backends/cl/workloads/ClSoftmaxBaseWorkload.cpp index 48dd3984f1..b1dc404a6f 100644 --- a/src/backends/cl/workloads/ClSoftmaxBaseWorkload.cpp +++ b/src/backends/cl/workloads/ClSoftmaxBaseWorkload.cpp @@ -15,12 +15,6 @@ namespace armnn arm_compute::Status ClSoftmaxWorkloadValidate(const TensorInfo& input, const TensorInfo& output) { - // NOTE: We report 4D Softmax as unsupported until full support is added to ACL - if(input.GetShape().GetNumDimensions() >= 4u) - { - return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR, "4d softmax is not supported"); - } - const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output); |