| /* |
| * Copyright (c) 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/utils/misc/ShapeCalculator.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/validation/reference/ActivationLayer.h" |
| #include "tests/validation/reference/Conv3D.h" |
| |
| #include <random> |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DirectConvolution3DValidationGenericFixture : public framework::Fixture |
| { |
| public: |
| using TBias = typename std::conditional < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int32_t, T >::type; |
| |
| template <typename...> |
| void setup(const TensorShape &input_shape, int stride_x, int stride_y, int stride_z, int pad_x, int pad_y, int pad_z, unsigned int kernel_width, int kernel_height, int kernel_depth, |
| unsigned int num_kernels, bool has_bias, const ActivationLayerInfo &act_info, const DataType &data_type, const DataLayout &data_layout, |
| const QuantizationInfo &src_qinfo = QuantizationInfo(), const QuantizationInfo &weights_qinfo = QuantizationInfo(), const QuantizationInfo &dst_qinfo = QuantizationInfo()) |
| { |
| ARM_COMPUTE_ERROR_ON(data_layout != DataLayout::NDHWC); |
| |
| const TensorShape weights_shape(num_kernels, input_shape[0], kernel_width, kernel_height, kernel_depth); |
| const TensorShape bias_shape(num_kernels); |
| const DataType bias_data_type = is_data_type_quantized(data_type) ? DataType::S32 : data_type; |
| const Conv3dInfo conv3d_info(Size3D(stride_x, stride_y, stride_z), Padding3D(pad_x, pad_y, pad_z), act_info, Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false); |
| const TensorShape output_shape = compute_conv3d_shape(input_shape, weights_shape, conv3d_info); |
| |
| _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, conv3d_info, has_bias, data_type, bias_data_type, data_layout, src_qinfo, weights_qinfo, dst_qinfo); |
| _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, conv3d_info, has_bias, data_type, bias_data_type, src_qinfo, weights_qinfo, dst_qinfo); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&tensor, int i) |
| { |
| switch(tensor.data_type()) |
| { |
| 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; |
| } |
| 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 Conv3dInfo &conv3d_info, |
| bool has_bias, const DataType &data_type, const DataType &bias_data_type, const DataLayout &data_layout, const QuantizationInfo &src_qinfo, |
| const QuantizationInfo &weights_qinfo, const QuantizationInfo &dst_qinfo) |
| { |
| // Create tensors |
| TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, src_qinfo, data_layout); |
| TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, weights_qinfo, data_layout); |
| TensorType bias = has_bias ? create_tensor<TensorType>(bias_shape, bias_data_type, 1, QuantizationInfo()) : TensorType(); |
| TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, dst_qinfo, data_layout); |
| |
| // Create and configure function |
| FunctionType conv{}; |
| conv.configure(&src, &weights, has_bias ? &bias : nullptr, &dst, conv3d_info); |
| |
| ARM_COMPUTE_ASSERT(src.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(weights.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); |
| |
| // Allocate tensors |
| src.allocator()->allocate(); |
| weights.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!weights.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); |
| |
| // Fill tensors |
| fill(AccessorType(src), 0); |
| fill(AccessorType(weights), 1); |
| |
| if(has_bias) |
| { |
| ARM_COMPUTE_ASSERT(bias.info()->is_resizable()); |
| bias.allocator()->allocate(); |
| ARM_COMPUTE_ASSERT(!bias.info()->is_resizable()); |
| fill(AccessorType(bias), 2); |
| } |
| |
| // Compute Direct Convolution 3D function |
| conv.run(); |
| |
| return dst; |
| } |
| |
| SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, |
| const Conv3dInfo &conv3d_info, bool has_bias, const DataType &data_type, const DataType &bias_data_type, const QuantizationInfo &src_qinfo, |
| const QuantizationInfo &weights_qinfo, const QuantizationInfo &dst_qinfo) |
| { |
| // Create reference |
| SimpleTensor<T> src{ input_shape, data_type, 1, src_qinfo }; |
| SimpleTensor<T> weights{ weights_shape, data_type, 1, weights_qinfo }; |
| SimpleTensor<TBias> bias{ bias_shape, bias_data_type }; |
| SimpleTensor<T> dst{ output_shape, data_type, 1, dst_qinfo }; |
| |
| // Fill reference |
| fill(src, 0); |
| fill(weights, 1); |
| |
| if(has_bias) |
| { |
| fill(bias, 2); |
| } |
| |
| return reference::activation_layer(reference::conv3d<T, TBias>(src, weights, bias, dst, conv3d_info), conv3d_info.act_info); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DirectConvolution3DValidationFixture : public DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, int stride_x, int stride_y, int stride_z, int pad_x, int pad_y, int pad_z, unsigned int kernel_width, int kernel_height, int kernel_depth, |
| unsigned int num_kernels, bool has_bias, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout) |
| { |
| DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, stride_z, pad_x, pad_y, pad_z, kernel_width, kernel_height, |
| kernel_depth, num_kernels, has_bias, act_info, data_type, data_layout); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DirectConvolution3DValidationQuantizedFixture : public DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, int stride_x, int stride_y, int stride_z, int pad_x, int pad_y, int pad_z, unsigned int kernel_width, int kernel_height, int kernel_depth, |
| unsigned int num_kernels, bool has_bias, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout, QuantizationInfo src_qinfo, QuantizationInfo weights_qinfo, |
| QuantizationInfo dst_qinfo) |
| { |
| DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, stride_z, pad_x, pad_y, pad_z, kernel_width, kernel_height, |
| kernel_depth, num_kernels, has_bias, act_info, data_type, data_layout, src_qinfo, |
| weights_qinfo, dst_qinfo); |
| } |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |