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Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h | 261 |
1 files changed, 0 insertions, 261 deletions
diff --git a/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h b/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h deleted file mode 100644 index 6ef30d3c21..0000000000 --- a/tests/validation/fixtures/DirectConvolutionLayerTensorShiftFixture.h +++ /dev/null @@ -1,261 +0,0 @@ -/* - * Copyright (c) 2017-2021 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. - */ -#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/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: - { - arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f }; - library->fill(tensor, distribution, i); - break; - } - case DataType::F32: - { - std::uniform_real_distribution<float> 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 |