From cf343e3798d2a8c2ad2fcac488e4b78e2b5c968d Mon Sep 17 00:00:00 2001 From: morgolock Date: Mon, 12 Oct 2020 14:00:43 +0100 Subject: COMPMID-3719: Remove OpenCL padding: CLGEMMLowpMatrixMultiplyNativeKernel Change-Id: Iee28abcbba1e7b9e2f3aaa55685936dce815d5a3 Signed-off-by: morgolock Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4141 Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- .../validation/CL/GEMMLowpMatrixMultiplyNative.cpp | 71 ++++++++++++++++++++++ 1 file changed, 71 insertions(+) (limited to 'tests/validation/CL') diff --git a/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp b/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp index ce000bd8e1..9e717dfac9 100644 --- a/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp +++ b/tests/validation/CL/GEMMLowpMatrixMultiplyNative.cpp @@ -88,10 +88,81 @@ 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