From 27d92fd5da6ad16c9e3b38d82402a86cf7b208aa Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Tue, 27 Oct 2020 12:44:17 +0000 Subject: COMPMID-3928: Fix output conversion in gemmlowp_mm_native This patch solves the following issues that arose from nightly tests: - The accumulated result of gemmlowp_mm_native can be either uint or int and in order to be stored in memory we need to convert it to int. - The RHS matrix still needs padding on the X dimension. Hence, revert few changes to add the necessary padding elements. - Replace zero padding validation tests with assertion in the configure method of the kernel. Change-Id: Ib6614a91bd0e98f2b850f52eef14d4fbf55517c8 Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4259 Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins --- .../validation/CL/GEMMLowpMatrixMultiplyNative.cpp | 71 ---------------------- 1 file changed, 71 deletions(-) (limited to 'tests') diff --git a/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp b/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp index 9e717dfac9..ce000bd8e1 100644 --- a/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp +++ b/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp @@ -88,81 +88,10 @@ const auto n0_values_nightly = framework::dataset::make("N0", { 1, 2, 3, 4, 8 }) /** K0 values to test - Nightly */ const auto k0_values_nightly = framework::dataset::make("K0", { 1, 2, 3, 4, 8, 16 }); - -/** Zero padding test */ -bool validate_zero_padding(unsigned int m_value, unsigned int n_value, unsigned int k_value, unsigned int b_value, unsigned int m0_value, unsigned int n0_value, unsigned int k0_value, bool broadcast_bias, DataType data_type, const ActivationLayerInfo &act_info) -{ - const unsigned int M = m_value; - const unsigned int N = n_value; - const unsigned int K = k_value; - - GEMMLHSMatrixInfo lhs_info; - lhs_info.m0 = m0_value; - lhs_info.k0 = k0_value; - - GEMMRHSMatrixInfo rhs_info; - rhs_info.n0 = n0_value; - rhs_info.k0 = k0_value; - - GEMMKernelInfo kernel_info; - kernel_info.m = M; - kernel_info.n = N; - kernel_info.k = K; - kernel_info.broadcast_bias = broadcast_bias; - kernel_info.activation_info = act_info; - - const TensorShape lhs_shape(K, M, b_value); - const TensorShape rhs_shape(N, K, b_value); - const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape, 1, data_type), - TensorInfo(rhs_shape, 1, data_type), - kernel_info); - - // Create tensors - CLTensor lhs = create_tensor(lhs_shape, data_type); - CLTensor rhs = create_tensor(rhs_shape, data_type); - CLTensor dst = create_tensor(dst_shape, DataType::S32); - - ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(rhs.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Create and configure function - CLGEMMLowpMatrixMultiplyNative gemm; - gemm.configure(&lhs, &rhs, &dst, lhs_info, rhs_info, GEMMReshapeInfo(m_value, n_value, k_value)); - - // Padding can be added along rhs and bias's X dimension - return dst.info()->padding().empty() && lhs.info()->padding().empty() && rhs.info()->padding().empty(); -} } // namespace TEST_SUITE(CL) TEST_SUITE(GEMMLowpMatrixMultiplyNative) - -/** Validate zero padding tests - * - * A series of validation tests to check that no padding is added as part of configuration for 4 different scenarios. - * - * Checks performed in order: - * - No partial blocks in both x and y dimensions - * - Partial blocks in x dimension - * - Partial blocks in y dimension - * - Partial blocks in both x and y dimensions - * - No blocks in both x and y dimensions, scalar store (N0==1) - * - Special case: partial_n0 == 5 (vstore1 should be invoked instead of vstore_partial_1) - */ -DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip(zip(zip( -framework::dataset::make("M", { 24, 63, 1, 51, 255, }), -framework::dataset::make("N", { 47, 29, 122, 20, 21, })), -framework::dataset::make("M0", { 4, 8, 2, 1, 8, })), -framework::dataset::make("N0", { 4, 4, 3, 1, 8, })), -m_value, n_value, m0_value, n0_value) -{ - bool status = validate_zero_padding(m_value, n_value, 23, 1, m0_value, n0_value, 4, false, DataType::QASYMM8, ActivationLayerInfo()); - ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS); -} - - - FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyNativeFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(m_values, n_values), -- cgit v1.2.1