From adc5395ad72aceb2c9e7e6beb54d949959d35143 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Fri, 15 Feb 2019 11:10:31 +0000 Subject: COMPMID-2000: Implement CLGEMMMatrixMultiplyReshapedOnlyRHS - Transposed Change-Id: I364c7ec5a43ad391a73429489802b0e679ee0c6e Signed-off-by: Gian Marco Iodice Reviewed-on: https://review.mlplatform.org/c/732 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- .../CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp | 349 +++++++++++++++++++++ tests/validation/fixtures/GEMMFixture.h | 214 +++++++++++++ 2 files changed, 563 insertions(+) create mode 100644 tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp (limited to 'tests') diff --git a/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp b/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp new file mode 100644 index 0000000000..cbbc5922dd --- /dev/null +++ b/tests/validation/CL/GEMMMatrixMultiplyReshapedOnlyRHS.cpp @@ -0,0 +1,349 @@ +/* + * Copyright (c) 2019 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h" +#include "arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "tests/CL/CLAccessor.h" +#include "tests/CL/Helper.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/GEMMFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +using namespace arm_compute::misc::shape_calculator; + +// Create function for CLGEMMReshapeRHSMatrixKernel +using CLGEMMReshapeRHSMatrix = CLSynthetizeFunction; + +// Create function for CLGEMMMatrixMultiplyReshapedOnlyRHSKernel +using CLGEMMMatrixMultiplyReshapedOnlyRHS = CLSynthetizeFunction; + +// Fixture for CLGEMMMatrixMultiplyReshapedOnlyRHS +template +using CLGEMMMatrixMultiplyReshapedOnlyRHSFixture = GEMMMatrixMultiplyReshapedOnlyRHSValidationFixture; + +// Fixture for CLGEMMMatrixMultiplyReshapedOnlyRHS3D +template +using CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture = GEMMMatrixMultiplyReshapedOnlyRHS3DValidationFixture; + +namespace +{ +// *INDENT-OFF* +// clang-format off +RelativeTolerance rel_tolerance_f32(0.001f); +constexpr float abs_tolerance_f32(0.0001f); + +RelativeTolerance rel_tolerance_f16(half(0.2)); +constexpr float tolerance_num_f16 = 0.02f; + +/** Alpha values to test - Precommit */ +const auto a_values = framework::dataset::make("alpha", {1.0f, -0.75f} ); + +/** M values to test */ +const auto m_values = framework::dataset::make("M", 37); + +/** M_W values to test */ +const auto m_w_values = framework::dataset::make("M_W", 5); + +/** M_H values to test */ +const auto m_h_values = framework::dataset::make("M_H", 7); + +/** N values to test */ +const auto n_values = framework::dataset::make("N", 51); + +/** K values to test */ +const auto k_values = framework::dataset::make("K", 23); + +/** Batch size values to test */ +const auto b_values = framework::dataset::make("batch_size", 1, 3); + +/** M0 values to test - Precommit */ +const auto m0_values_precommit = framework::dataset::make("M0", {4, 6}); + +/** N0 values to test - Precommit */ +const auto n0_values_precommit = framework::dataset::make("N0", { 2, 4 }); + +/** K0 values to test - Precommit */ +const auto k0_values_precommit = framework::dataset::make("K0", { 4 }); + +/** H0 values to test - Precommit */ +const auto h0_values_precommit = framework::dataset::make("H0", 1, 3); + +/** M0 values to test - Nightly */ +const auto m0_values_nightly = framework::dataset::make("M0", 2, 8); + +/** N0 values to test - Nightly */ +const auto n0_values_nightly = framework::dataset::make("N0", { 2, 3, 4, 8 }); + +/** K0 values to test - Nightly */ +const auto k0_values_nightly = framework::dataset::make("K0", { 2, 3, 4, 8 }); + +/** H0 values to test - Nightly */ +const auto h0_values_nightly = framework::dataset::make("H0", 1, 4); + +/** Interleave values to test with RHS matrix */ +const auto i_values_rhs = framework::dataset::make("interleave_rhs", { true, false }); + +/** Transpose values to test with RHS matrix */ +const auto t_values_rhs = framework::dataset::make("transpose_rhs", { true }); + +/** Configuration test */ +void validate_configuration(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, unsigned int h0_value, bool i_value_rhs, DataType data_type) +{ + 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; + rhs_info.h0 = h0_value; + rhs_info.interleave = i_value_rhs; + rhs_info.transpose = true; + + GEMMReshapeInfo gemm_info(M, N, K); + + const TensorShape lhs_shape(K, M, b_value); + const TensorShape rhs_shape(N, K, b_value); + const TensorShape rhs_shape_reshaped = compute_rhs_reshaped_shape(TensorInfo(rhs_shape, 1, data_type), + rhs_info); + + const TensorShape dst_shape = compute_mm_shape(TensorInfo(lhs_shape, 1, data_type), + TensorInfo(rhs_shape_reshaped, 1, data_type), + gemm_info); + + // Create tensors + CLTensor lhs = create_tensor(lhs_shape, data_type); + CLTensor rhs_reshaped = create_tensor(rhs_shape_reshaped, data_type); + CLTensor dst = create_tensor(dst_shape, data_type); + + ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Create and configure function + CLGEMMMatrixMultiplyReshapedOnlyRHS gemm; + gemm.configure(&lhs, &rhs_reshaped, &dst, 1.0f, lhs_info, rhs_info, gemm_info); +} +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(GEMMMatrixMultiplyReshapedOnlyRHS) +TEST_SUITE(Float) +TEST_SUITE(FP32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + framework::dataset::make("batch_size", 1)), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + h0_values_precommit), + i_values_rhs), +m_value, n_value, k_value, b_value, m0_value, n0_value, k0_value, h0_value, i_value_rhs) +{ + validate_configuration(m_value, n_value, k_value, b_value, m0_value, n0_value, k0_value, h0_value, i_value_rhs, DataType::F32); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + h0_values_precommit), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F32)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + m0_values_nightly), + n0_values_nightly), + k0_values_nightly), + h0_values_nightly), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F32)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_w_values, + m_h_values), + n_values), + k_values), + b_values), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + h0_values_precommit), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F32)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_w_values, + m_h_values), + n_values), + k_values), + b_values), + m0_values_nightly), + n0_values_nightly), + k0_values_nightly), + h0_values_nightly), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F32)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32); +} +TEST_SUITE_END() // FP32 + +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + h0_values_precommit), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F16)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMMatrixMultiplyReshapedOnlyRHSFixture, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_values, + n_values), + k_values), + b_values), + m0_values_nightly), + n0_values_nightly), + k0_values_nightly), + h0_values_nightly), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F16)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); +} + +FIXTURE_DATA_TEST_CASE(RunSmall3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture, framework::DatasetMode::ALL, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_w_values, + m_h_values), + n_values), + k_values), + b_values), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + h0_values_precommit), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F16)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); +} + +FIXTURE_DATA_TEST_CASE(RunLarge3D, CLGEMMMatrixMultiplyReshapedOnlyRHS3DFixture, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(combine( + m_w_values, + m_h_values), + n_values), + k_values), + b_values), + m0_values_nightly), + n0_values_nightly), + k0_values_nightly), + h0_values_nightly), + i_values_rhs), + t_values_rhs), + framework::dataset::make("DataType", DataType::F16)), + a_values)) +{ + // Validate output + validate(CLAccessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16); +} +TEST_SUITE_END() // FP16 +TEST_SUITE_END() // Float +TEST_SUITE_END() // GEMMMatrixMulipltyReshapedOnlyRHS +TEST_SUITE_END() // CL +} // namespace validation +} // namespace test +} // namespace arm_compute \ No newline at end of file diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h index a6a3b67785..77d2ca61fb 100644 --- a/tests/validation/fixtures/GEMMFixture.h +++ b/tests/validation/fixtures/GEMMFixture.h @@ -383,6 +383,220 @@ protected: TensorType _target{}; SimpleTensor _reference{}; }; + +template +class GEMMMatrixMultiplyReshapedOnlyRHSValidationFixture : public framework::Fixture +{ +public: + template + void setup(unsigned int m, unsigned int n, unsigned int k, unsigned int batch_size, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int h0, + bool interleave_rhs, bool transpose_rhs, DataType data_type, float alpha) + { + GEMMLHSMatrixInfo lhs_info; + lhs_info.m0 = m0; + lhs_info.k0 = k0; + + GEMMRHSMatrixInfo rhs_info; + rhs_info.n0 = n0; + rhs_info.k0 = k0; + rhs_info.h0 = h0; + rhs_info.interleave = interleave_rhs; + rhs_info.transpose = transpose_rhs; + + // Set the tensor shapes for LHS and RHS matrices + const TensorShape lhs_shape(k, m, batch_size); + const TensorShape rhs_shape(n, k, batch_size); + + _target = compute_target(lhs_shape, rhs_shape, lhs_info, rhs_info, data_type, alpha); + _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha); + } + +protected: + template + void fill(U &&tensor, int i) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + + // Fill border with infinity in order to check the presence of NaN values (i.e. inf * 0) + std::uniform_real_distribution<> distribution_inf(std::numeric_limits::infinity(), std::numeric_limits::infinity()); + library->fill_borders_with_garbage(tensor, distribution_inf, i); + } + + TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, DataType data_type, float alpha) + { + // Create tensors + TensorType lhs = create_tensor(lhs_shape, data_type, 1); + TensorType rhs = create_tensor(rhs_shape, data_type, 1); + TensorType rhs_reshaped; + TensorType dst; + + const unsigned int M = lhs_shape[1]; + const unsigned int N = rhs_shape[0]; + const unsigned int K = lhs_shape[0]; + + // The output tensor will be auto-initialized within the function + + // Create and configure function + ReshapeRHSFunctionType reshape_rhs; + GEMMFunctionType gemm; + reshape_rhs.configure(&rhs, &rhs_reshaped, rhs_info); + gemm.configure(&lhs, &rhs_reshaped, &dst, alpha, lhs_info, rhs_info, GEMMReshapeInfo(M, N, K)); + + ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(rhs.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + lhs.allocator()->allocate(); + rhs.allocator()->allocate(); + rhs_reshaped.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!rhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(lhs), 0); + fill(AccessorType(rhs), 1); + + // Compute GEMM + reshape_rhs.run(); + gemm.run(); + + return dst; + } + + SimpleTensor compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha) + { + TensorShape dst_shape = lhs_shape; + dst_shape[0] = rhs_shape[0]; + dst_shape[1] = lhs_shape[1]; + + // Create reference + SimpleTensor lhs{ lhs_shape, data_type, 1 }; + SimpleTensor rhs{ rhs_shape, data_type, 1 }; + SimpleTensor c{ dst_shape, data_type, 1 }; + + // Fill reference + fill(lhs, 0); + fill(rhs, 1); + + return reference::gemm(lhs, rhs, c, alpha, 0.0f); + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; + +template +class GEMMMatrixMultiplyReshapedOnlyRHS3DValidationFixture : public framework::Fixture +{ +public: + template + void setup(unsigned int m_w, unsigned int m_h, unsigned int n, unsigned int k, unsigned int batch_size, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int h0, + bool interleave_rhs, bool transpose_rhs, DataType data_type, float alpha) + { + GEMMLHSMatrixInfo lhs_info; + lhs_info.m0 = m0; + lhs_info.k0 = k0; + + GEMMRHSMatrixInfo rhs_info; + rhs_info.n0 = n0; + rhs_info.k0 = k0; + rhs_info.h0 = h0; + rhs_info.interleave = interleave_rhs; + rhs_info.transpose = transpose_rhs; + + // In case of GEMM3D, m is the product between m_w and m_h + const unsigned int m = m_w * m_h; + + // Set the tensor shapes for LHS and RHS matrices + const TensorShape lhs_shape(k, m, batch_size); + const TensorShape rhs_shape(n, k, batch_size); + + _target = compute_target(lhs_shape, rhs_shape, lhs_info, rhs_info, data_type, alpha, m_h); + _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, m_h); + } + +protected: + template + void fill(U &&tensor, int i) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + } + + TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, DataType data_type, float alpha, + unsigned int m_h) + { + // Create tensors + TensorType lhs = create_tensor(lhs_shape, data_type, 1); + TensorType rhs = create_tensor(rhs_shape, data_type, 1); + TensorType rhs_reshaped; + TensorType dst; + + const unsigned int M = lhs_shape[1]; + const unsigned int N = rhs_shape[0]; + const unsigned int K = lhs_shape[0]; + + // The output tensor will be auto-initialized within the function + + // Create and configure function + ReshapeRHSFunctionType reshape_rhs; + GEMMFunctionType gemm; + reshape_rhs.configure(&rhs, &rhs_reshaped, rhs_info); + gemm.configure(&lhs, &rhs_reshaped, &dst, alpha, lhs_info, rhs_info, GEMMReshapeInfo(M, N, K, 1, 1, m_h)); + + ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(rhs.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + lhs.allocator()->allocate(); + rhs.allocator()->allocate(); + rhs_reshaped.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!lhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!rhs.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!rhs_reshaped.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(lhs), 0); + fill(AccessorType(rhs), 1); + + // Compute GEMM + reshape_rhs.run(); + gemm.run(); + + return dst; + } + + SimpleTensor compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, unsigned int m_h) + { + TensorShape dst_shape = lhs_shape; + dst_shape.set(0, rhs_shape[0]); + dst_shape.set(1, lhs_shape[1] / m_h); + dst_shape.set(2, m_h); + dst_shape.set(3, lhs_shape[2]); + + // Create reference + SimpleTensor lhs{ lhs_shape, data_type, 1 }; + SimpleTensor rhs{ rhs_shape, data_type, 1 }; + SimpleTensor c{ dst_shape, data_type, 1 }; + + // Fill reference + fill(lhs, 0); + fill(rhs, 1); + + return reference::gemm(lhs, rhs, c, alpha, 0.0f); + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; } // namespace validation } // namespace test } // namespace arm_compute -- cgit v1.2.1