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diff --git a/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h b/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h
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-/*
- * Copyright (c) 2017-2018 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/TensorShape.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.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/fixtures/ConvolutionLayerFixture.h"
-#include "tests/validation/reference/ConvolutionLayer.h"
-
-#include <random>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DirectConvolutionValidationGenericTensorShiftFixture : public framework::Fixture
-{
-public:
- using TBias = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, int32_t, T>::type;
-
-public:
- template <typename...>
- void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels,
- DataType data_type, QuantizationInfo quantization_info)
- {
- _quantization_info = quantization_info;
- _data_type = data_type;
-
- const TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels);
- const TensorShape bias_shape(num_kernels);
- const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR);
- const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info);
- const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
-
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
- }
-
- template <typename...>
- void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y,
- DataType data_type, QuantizationInfo quantization_info)
- {
- ARM_COMPUTE_UNUSED(dilation_x, dilation_y);
-
- _quantization_info = quantization_info;
- _data_type = data_type;
-
- const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
-
- _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info);
- }
-
-protected:
- template <typename U>
- void fill(U &&tensor, int i)
- {
- switch(tensor.data_type())
- {
- case DataType::QASYMM8:
- {
- std::uniform_int_distribution<uint8_t> distribution(0, 50);
- library->fill(tensor, distribution, i);
- break;
- }
- case DataType::F16:
- case DataType::F32:
- {
- std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
- library->fill(tensor, distribution, i);
- break;
- }
- case DataType::S32:
- {
- std::uniform_int_distribution<int32_t> distribution(-5, 5);
- library->fill(tensor, distribution, i);
- break;
- }
- default:
- library->fill_tensor_uniform(tensor, i);
- }
- }
-
- TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
- DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info)
- {
- // Create tensors
- TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, quantization_info);
- TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, quantization_info);
- TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, quantization_info);
- TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, quantization_info);
-
- TensorShape output_shape1 = get_output_shape(output_shape, weights_shape, info);
- TensorType dst1 = create_tensor<TensorType>(output_shape1, data_type, 1, quantization_info);
-
- // Create and configure function
- FunctionType conv;
- conv.configure(&src, &weights, &bias, &dst, info);
- FunctionType conv1;
- conv1.configure(&dst, &weights, &bias, &dst1, info);
-
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst1.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Allocate tensors
- src.allocator()->allocate();
- weights.allocator()->allocate();
- bias.allocator()->allocate();
- dst.allocator()->allocate();
- dst1.allocator()->allocate();
-
- ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!dst1.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Fill tensors
- fill(AccessorType(src), 0);
- fill(AccessorType(weights), 1);
- fill(AccessorType(bias), 2);
-
- // Compute NEConvolutionLayer function
- GCScheduler::get().memory_barrier();
- conv.run();
- GCScheduler::get().memory_barrier();
- conv1.run();
-
- return dst1;
- }
-
- SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
- DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info)
- {
- // Create reference
- SimpleTensor<T> src{ input_shape, data_type, 1, quantization_info };
- SimpleTensor<T> weights{ weights_shape, data_type, 1, quantization_info };
- SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, quantization_info };
-
- SimpleTensor<T> dst{ output_shape, data_type, 1, quantization_info };
- TensorShape output_shape1 = get_output_shape(output_shape, weights_shape, info);
-
- // Fill reference
- fill(src, 0);
- fill(weights, 1);
- fill(bias, 2);
-
- dst = reference::convolution_layer<T>(src, weights, bias, output_shape, info);
- return reference::convolution_layer<T>(dst, weights, bias, output_shape1, info);
- }
-
- TensorType _target{};
- SimpleTensor<T> _reference{};
- QuantizationInfo _quantization_info{};
- DataType _data_type{};
-
-private:
- TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info)
- {
- TensorShape out_shape(in_shape);
- const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(),
- in_shape.y(),
- kernel_shape.x(),
- kernel_shape.y(),
- info);
- out_shape.set(0, scaled_dims.first);
- out_shape.set(1, scaled_dims.second);
- out_shape.set(2, kernel_shape[3]);
- return out_shape;
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DirectConvolutionValidationTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type)
- {
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type,
- QuantizationInfo());
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DirectConvolutionValidationQuantizedTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info)
- {
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type,
- quantization_info);
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DirectConvolutionValidationWithTensorShapesQuantizedTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y,
- DataType data_type, QuantizationInfo quantization_info)
- {
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type,
- quantization_info);
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DirectConvolutionValidationWithTensorShapesTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y,
- DataType data_type)
- {
- DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type,
- QuantizationInfo());
- }
-};
-
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-05 19:37:07 +0000