| /* |
| * Copyright (c) 2020-2021 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_QLSTM_LAYER_NORMALIZATION_FIXTURE |
| #define ARM_COMPUTE_TEST_QLSTM_LAYER_NORMALIZATION_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/Helpers.h" |
| #include "tests/validation/reference/QLSTMLayerNormalization.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class QLSTMLayerNormalizationValidationFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, TensorShape weight_shape, TensorShape bias_shape, DataType data_type, QuantizationInfo weight_qinfo) |
| { |
| ARM_COMPUTE_ERROR_ON(data_type != DataType::QSYMM16); |
| |
| _data_type = data_type; |
| _qinfo = weight_qinfo; |
| |
| _target = compute_target(input_shape, weight_shape, bias_shape); |
| _reference = compute_reference(input_shape, weight_shape, bias_shape); |
| } |
| |
| protected: |
| template <typename InputType, typename BiasType> |
| void fill(InputType &&input_tensor, InputType &&weight_tensor, BiasType &&bias_tensor) |
| { |
| switch(_data_type) |
| { |
| case DataType::QSYMM16: |
| { |
| // Value ranges are based on reference implementation's test case. |
| constexpr int16_t input_min = -1000; |
| constexpr int16_t input_max = 1000; |
| constexpr int16_t weight_min = 19000; |
| constexpr int16_t weight_max = 27000; |
| constexpr int32_t bias_min = -16000000; |
| constexpr int32_t bias_max = -13000000; |
| |
| std::uniform_int_distribution<> input_distribution(input_min, input_max); |
| std::uniform_int_distribution<> weight_distribution(weight_min, weight_max); |
| std::uniform_int_distribution<> bias_distribution(bias_min, bias_max); |
| |
| library->fill(input_tensor, input_distribution, 0); |
| library->fill(weight_tensor, weight_distribution, 0); |
| library->fill(bias_tensor, bias_distribution, 0); |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("non-supported data type"); |
| break; |
| } |
| } |
| |
| void allocate_tensors(const std::vector<TensorType *> &tensors) |
| { |
| for(auto t : tensors) |
| { |
| ARM_COMPUTE_ASSERT(t->info()->is_resizable()); |
| t->allocator()->allocate(); |
| ARM_COMPUTE_ASSERT(!t->info()->is_resizable()); |
| } |
| } |
| |
| TensorType compute_target(const TensorShape &input_shape, const TensorShape &weight_shape, const TensorShape &bias_shape) |
| { |
| TensorType input = create_tensor<TensorType>(input_shape, _data_type, 1); |
| TensorType weight = create_tensor<TensorType>(weight_shape, _data_type, 1, _qinfo); |
| TensorType bias = create_tensor<TensorType>(bias_shape, DataType::S32, 1); |
| TensorType output = create_tensor<TensorType>(input_shape, _data_type, 1); |
| |
| FunctionType fn; |
| fn.configure(&input, &output, &weight, &bias); |
| allocate_tensors({ &input, &weight, &bias, &output }); |
| fill(AccessorType(input), AccessorType(weight), AccessorType(bias)); |
| fn.run(); |
| |
| return output; |
| } |
| |
| SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weight_shape, const TensorShape &bias_shape) |
| { |
| // Create reference |
| SimpleTensor<T> input{ input_shape, _data_type, 1 }; |
| SimpleTensor<T> weight{ weight_shape, _data_type, 1, _qinfo }; |
| SimpleTensor<int32_t> bias{ bias_shape, DataType::S32, 1 }; |
| |
| // Fill reference |
| fill(input, weight, bias); |
| |
| return reference::qlstm_layer_normalization(input, weight, bias); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| DataType _data_type{}; |
| QuantizationInfo _qinfo{}; |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| |
| #endif /* ARM_COMPUTE_TEST_QLSTM_LAYER_NORMALIZATION_FIXTURE */ |