Giorgio Arena | 16def8d | 2021-10-07 11:03:12 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2021 Arm Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| 25 | #include "tests/framework/Fixture.h" |
| 26 | #include "tests/validation/reference/ActivationLayer.h" |
| 27 | #include "tests/validation/reference/Conv3D.h" |
| 28 | |
| 29 | #include <random> |
| 30 | |
| 31 | namespace arm_compute |
| 32 | { |
| 33 | namespace test |
| 34 | { |
| 35 | namespace validation |
| 36 | { |
| 37 | using namespace arm_compute::misc::shape_calculator; |
| 38 | |
| 39 | template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| 40 | class DirectConvolution3DValidationGenericFixture : public framework::Fixture |
| 41 | { |
| 42 | public: |
| 43 | template <typename...> |
| 44 | 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, |
| 45 | unsigned int num_kernels, bool has_bias, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout) |
| 46 | { |
| 47 | ARM_COMPUTE_ERROR_ON(data_layout != DataLayout::NDHWC); |
| 48 | |
| 49 | TensorShape weights_shape(num_kernels, input_shape[0], kernel_width, kernel_height, kernel_depth); |
| 50 | const TensorShape bias_shape(num_kernels); |
| 51 | const Conv3dInfo conv3d_info(Size3D(stride_x, stride_y, stride_z), Padding3D(pad_x, pad_y, pad_z), act_info, Size3D(), DimensionRoundingType::FLOOR, false); |
| 52 | const TensorShape output_shape = compute_conv3d_shape(input_shape, weights_shape, conv3d_info); |
| 53 | |
| 54 | _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, conv3d_info, has_bias, data_type, data_layout); |
| 55 | _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, conv3d_info, has_bias, data_type); |
| 56 | } |
| 57 | |
| 58 | protected: |
| 59 | template <typename U> |
| 60 | void fill(U &&tensor, int i) |
| 61 | { |
| 62 | switch(tensor.data_type()) |
| 63 | { |
| 64 | case DataType::F16: |
| 65 | { |
| 66 | arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f }; |
| 67 | library->fill(tensor, distribution, i); |
| 68 | break; |
| 69 | } |
| 70 | case DataType::F32: |
| 71 | { |
| 72 | std::uniform_real_distribution<float> distribution(-1.0f, 1.0f); |
| 73 | library->fill(tensor, distribution, i); |
| 74 | break; |
| 75 | } |
| 76 | default: |
| 77 | library->fill_tensor_uniform(tensor, i); |
| 78 | } |
| 79 | } |
| 80 | |
| 81 | TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const Conv3dInfo &conv3d_info, |
| 82 | bool has_bias, const DataType &data_type, const DataLayout &data_layout) |
| 83 | { |
| 84 | // Create tensors |
| 85 | TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout); |
| 86 | TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, QuantizationInfo(), data_layout); |
| 87 | TensorType bias = has_bias ? create_tensor<TensorType>(bias_shape, data_type, 1, QuantizationInfo()) : TensorType(); |
| 88 | TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo(), data_layout); |
| 89 | |
| 90 | add_padding_x({ &src, &dst, &weights }, data_layout); |
| 91 | |
| 92 | if(has_bias) |
| 93 | { |
| 94 | add_padding_x({ &bias }, data_layout); |
| 95 | } |
| 96 | |
| 97 | // Create and configure function |
| 98 | FunctionType conv{}; |
| 99 | conv.configure(&src, &weights, has_bias ? &bias : nullptr, &dst, conv3d_info); |
| 100 | |
| 101 | ARM_COMPUTE_ASSERT(src.info()->is_resizable()); |
| 102 | ARM_COMPUTE_ASSERT(weights.info()->is_resizable()); |
| 103 | ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); |
| 104 | |
| 105 | // Allocate tensors |
| 106 | src.allocator()->allocate(); |
| 107 | weights.allocator()->allocate(); |
| 108 | dst.allocator()->allocate(); |
| 109 | |
| 110 | ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); |
| 111 | ARM_COMPUTE_ASSERT(!weights.info()->is_resizable()); |
| 112 | ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); |
| 113 | |
| 114 | // Fill tensors |
| 115 | fill(AccessorType(src), 0); |
| 116 | fill(AccessorType(weights), 1); |
| 117 | |
| 118 | if(has_bias) |
| 119 | { |
| 120 | ARM_COMPUTE_ASSERT(bias.info()->is_resizable()); |
| 121 | bias.allocator()->allocate(); |
| 122 | ARM_COMPUTE_ASSERT(!bias.info()->is_resizable()); |
| 123 | fill(AccessorType(bias), 2); |
| 124 | } |
| 125 | |
| 126 | // Compute Direct Convolution 3D function |
| 127 | conv.run(); |
| 128 | |
| 129 | return dst; |
| 130 | } |
| 131 | |
| 132 | SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const Conv3dInfo &conv3d_info, |
| 133 | bool has_bias, const DataType &data_type) |
| 134 | { |
| 135 | // Create reference |
| 136 | SimpleTensor<T> src{ input_shape, data_type }; |
| 137 | SimpleTensor<T> weights{ weights_shape, data_type }; |
| 138 | SimpleTensor<T> bias{ bias_shape, data_type }; |
| 139 | SimpleTensor<T> dst{ output_shape, data_type }; |
| 140 | |
| 141 | // Fill reference |
| 142 | fill(src, 0); |
| 143 | fill(weights, 1); |
| 144 | |
| 145 | if(has_bias) |
| 146 | { |
| 147 | fill(bias, 2); |
| 148 | } |
| 149 | |
| 150 | return reference::activation_layer(reference::conv3d<T>(src, weights, bias, dst, conv3d_info), conv3d_info.act_info); |
| 151 | } |
| 152 | |
| 153 | TensorType _target{}; |
| 154 | SimpleTensor<T> _reference{}; |
| 155 | }; |
| 156 | |
| 157 | template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| 158 | class DirectConvolution3DValidationFixture : public DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| 159 | { |
| 160 | public: |
| 161 | template <typename...> |
| 162 | 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, |
| 163 | unsigned int num_kernels, bool has_bias, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout) |
| 164 | { |
| 165 | DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, stride_z, pad_x, pad_y, pad_z, kernel_width, kernel_height, |
| 166 | kernel_depth, num_kernels, has_bias, act_info, data_type, data_layout); |
| 167 | } |
| 168 | }; |
| 169 | } // namespace validation |
| 170 | } // namespace test |
| 171 | } // namespace arm_compute |