| /* |
| * Copyright (c) 2018-2019 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. |
| */ |
| #ifndef ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE |
| #define ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE |
| |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/Tensor.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/ReductionOperation.h" |
| #include "tests/validation/reference/ReshapeLayer.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class ReduceMeanValidationFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info) |
| { |
| _target = compute_target(shape, data_type, axis, keep_dims, quantization_info); |
| _reference = compute_reference(shape, data_type, axis, keep_dims, quantization_info); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&tensor) |
| { |
| if(!is_data_type_quantized(tensor.data_type())) |
| { |
| std::uniform_real_distribution<> distribution(-1.0f, 1.0f); |
| library->fill(tensor, distribution, 0); |
| } |
| else |
| { |
| std::pair<int, int> bounds = get_quantized_bounds(tensor.quantization_info(), -1.0f, 1.0f); |
| std::uniform_int_distribution<> distribution(bounds.first, bounds.second); |
| |
| library->fill(tensor, distribution, 0); |
| } |
| } |
| |
| TensorType compute_target(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info) |
| { |
| // Create tensors |
| TensorType src = create_tensor<TensorType>(src_shape, data_type, 1, quantization_info); |
| TensorType dst; |
| |
| // Create and configure function |
| FunctionType reduction_mean; |
| reduction_mean.configure(&src, axis, keep_dims, &dst); |
| |
| ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Allocate tensors |
| src.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Fill tensors |
| fill(AccessorType(src)); |
| |
| // Compute function |
| reduction_mean.run(); |
| |
| return dst; |
| } |
| |
| SimpleTensor<T> compute_reference(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info) |
| { |
| // Create reference |
| SimpleTensor<T> src{ src_shape, data_type, 1, quantization_info }; |
| |
| // Fill reference |
| fill(src); |
| |
| SimpleTensor<T> out; |
| for(unsigned int i = 0; i < axis.num_dimensions(); ++i) |
| { |
| TensorShape output_shape = i == 0 ? src_shape : out.shape(); |
| output_shape.set(axis[i], 1); |
| out = reference::reduction_operation<T, T>(i == 0 ? src : out, output_shape, axis[i], ReductionOperation::MEAN_SUM); |
| } |
| |
| if(!keep_dims) |
| { |
| TensorShape output_shape = src_shape; |
| std::sort(axis.begin(), axis.begin() + axis.num_dimensions()); |
| for(unsigned int i = 0; i < axis.num_dimensions(); ++i) |
| { |
| output_shape.remove_dimension(axis[i] - i); |
| } |
| |
| out = reference::reshape_layer(out, output_shape); |
| } |
| return out; |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class ReduceMeanQuantizedFixture : public ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info = QuantizationInfo()) |
| { |
| ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, quantization_info); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class ReduceMeanFixture : public ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims) |
| { |
| ReduceMeanValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, axis, keep_dims, QuantizationInfo()); |
| } |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE */ |