| /* |
| * Copyright (c) 2017 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. |
| */ |
| #ifndef ARM_COMPUTE_TEST_GEMMLOWP_FIXTURE |
| #define ARM_COMPUTE_TEST_GEMMLOWP_FIXTURE |
| |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "tests/AssetsLibrary.h" |
| #include "tests/Globals.h" |
| #include "tests/IAccessor.h" |
| #include "tests/framework/Asserts.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/validation/CPP/GEMMLowp.h" |
| #include "tests/validation/Helpers.h" |
| |
| #include <random> |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType> |
| class GEMMLowpOffsetValidationFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(size_t m, size_t n, size_t k, int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t c_mult_int, int32_t out_shift) |
| { |
| const TensorShape shape_a(k, m); |
| const TensorShape shape_b(n, k); |
| const TensorShape shape_c(n, m); |
| _target = compute_target(shape_a, shape_b, shape_c, a_offset, b_offset, c_offset, c_mult_int, out_shift); |
| _reference = compute_reference(shape_a, shape_b, shape_c, a_offset, b_offset, c_offset, c_mult_int, out_shift); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&tensor, int i) |
| { |
| ARM_COMPUTE_ERROR_ON(tensor.data_type() != DataType::U8); |
| std::uniform_int_distribution<> distribution(0, 3); |
| library->fill(tensor, distribution, i); |
| } |
| |
| TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, |
| int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t c_mult_int, int32_t out_shift) |
| { |
| // Create tensors |
| TensorType a = create_tensor<TensorType>(shape_a, DataType::U8, 1); |
| TensorType b = create_tensor<TensorType>(shape_b, DataType::U8, 1); |
| TensorType c = create_tensor<TensorType>(shape_c, DataType::U8, 1); |
| |
| // Create and configure function |
| FunctionType gemmlowp; |
| gemmlowp.configure(&a, &b, &c, a_offset, b_offset, c_offset, c_mult_int, out_shift); |
| |
| ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Allocate tensors |
| a.allocator()->allocate(); |
| b.allocator()->allocate(); |
| c.allocator()->allocate(); |
| |
| ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Fill tensors |
| fill(AccessorType(a), 0); |
| fill(AccessorType(b), 1); |
| fill(AccessorType(c), 2); |
| |
| // Compute GEMM function |
| gemmlowp.run(); |
| return c; |
| } |
| |
| SimpleTensor<uint8_t> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, |
| int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t c_mult_int, int32_t out_shift) |
| { |
| // Create reference |
| SimpleTensor<uint8_t> a{ shape_a, DataType::U8, 1 }; |
| SimpleTensor<uint8_t> b{ shape_b, DataType::U8, 1 }; |
| SimpleTensor<uint8_t> c{ shape_c, DataType::U8, 1 }; |
| |
| // Fill reference |
| fill(a, 0); |
| fill(b, 1); |
| fill(c, 2); |
| |
| return reference::gemmlowp<uint8_t>(a, b, c, a_offset, b_offset, c_offset, c_mult_int, out_shift); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<uint8_t> _reference{}; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType> |
| class GEMMLowpValidationFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(size_t m, size_t n, size_t k) |
| { |
| const TensorShape shape_a(k, m); |
| const TensorShape shape_b(n, k); |
| const TensorShape shape_c(n, m); |
| _target = compute_target(shape_a, shape_b, shape_c); |
| _reference = compute_reference(shape_a, shape_b, shape_c); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&tensor, int i, int lo, int hi) |
| { |
| std::uniform_int_distribution<> distribution(lo, hi); |
| library->fill(tensor, distribution, i); |
| } |
| |
| TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c) |
| { |
| // Create tensors |
| TensorType a = create_tensor<TensorType>(shape_a, DataType::U8, 1); |
| TensorType b = create_tensor<TensorType>(shape_b, DataType::U8, 1); |
| TensorType c = create_tensor<TensorType>(shape_c, DataType::U32, 1); |
| |
| // Create and configure function |
| FunctionType gemmlowp; |
| gemmlowp.configure(&a, &b, &c); |
| |
| ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Allocate tensors |
| a.allocator()->allocate(); |
| b.allocator()->allocate(); |
| c.allocator()->allocate(); |
| |
| ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Fill tensors |
| fill(AccessorType(a), 0, 0, 3); |
| fill(AccessorType(b), 1, 0, 3); |
| fill(AccessorType(c), 2, 0, 0); |
| |
| // Compute GEMM function |
| gemmlowp.run(); |
| return c; |
| } |
| |
| SimpleTensor<uint32_t> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c) |
| { |
| // Create reference |
| SimpleTensor<uint8_t> a{ shape_a, DataType::U8, 1 }; |
| SimpleTensor<uint8_t> b{ shape_b, DataType::U8, 1 }; |
| SimpleTensor<uint32_t> c{ shape_c, DataType::U32, 1 }; |
| |
| // Fill reference |
| fill(a, 0, 0, 3); |
| fill(b, 1, 0, 3); |
| fill(c, 2, 0, 0); |
| |
| return reference::gemmlowp(a, b, c); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<uint32_t> _reference{}; |
| }; |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_GEMMLOWP_FIXTURE */ |