Georgios Pinitas | c936917 | 2018-09-26 11:25:40 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2018 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 | #ifndef ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FUSION_FIXTURE |
| 25 | #define ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FUSION_FIXTURE |
| 26 | |
| 27 | #include "arm_compute/core/TensorShape.h" |
| 28 | #include "arm_compute/core/Types.h" |
| 29 | #include "tests/AssetsLibrary.h" |
| 30 | #include "tests/Globals.h" |
| 31 | #include "tests/IAccessor.h" |
| 32 | #include "tests/framework/Asserts.h" |
| 33 | #include "tests/framework/Fixture.h" |
| 34 | #include "tests/validation/Helpers.h" |
| 35 | #include "tests/validation/reference/BatchNormalizationLayer.h" |
| 36 | #include "tests/validation/reference/ConvolutionLayer.h" |
| 37 | |
| 38 | namespace arm_compute |
| 39 | { |
| 40 | namespace test |
| 41 | { |
| 42 | namespace validation |
| 43 | { |
| 44 | template <typename TensorType, typename AccessorType, typename ConvolutionFunctionType, typename FusionFunctionType, typename T> |
| 45 | class BatchNormalizationLayerFusionValidationFixture : public framework::Fixture |
| 46 | { |
| 47 | public: |
| 48 | template <typename...> |
| 49 | void setup(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, |
| 50 | bool use_conv_b, bool use_beta, bool use_gamma, float epsilon, DataType dt, DataLayout data_layout) |
| 51 | { |
| 52 | ARM_COMPUTE_UNUSED(dilation); |
| 53 | |
| 54 | _data_type = dt; |
| 55 | _data_layout = data_layout; |
| 56 | _use_conv_b = use_conv_b; |
| 57 | _use_beta = use_beta; |
| 58 | _use_gamma = use_gamma; |
| 59 | |
| 60 | _target = compute_target(src_shape, w_shape, b_shape, dst_shape, info, epsilon); |
| 61 | _reference = compute_reference(src_shape, w_shape, b_shape, dst_shape, info, epsilon); |
| 62 | } |
| 63 | |
| 64 | protected: |
| 65 | template <typename U> |
| 66 | void fill(U &&src, U &&w_tensor, U &&b_tensor, U &&mean_tensor, U &&var_tensor, U &&beta_tensor, U &&gamma_tensor) |
| 67 | { |
| 68 | std::uniform_real_distribution<> distribution(-1.f, 1.f); |
| 69 | std::uniform_real_distribution<> distribution_gz(0, 1.f); |
| 70 | |
| 71 | library->fill(src, distribution, 0); |
| 72 | library->fill(w_tensor, distribution, 1); |
| 73 | library->fill(mean_tensor, distribution, 2); |
| 74 | library->fill(var_tensor, distribution_gz, 3); |
| 75 | _use_conv_b ? library->fill(b_tensor, distribution, 4) : library->fill_tensor_value(b_tensor, 0.f); |
| 76 | _use_beta ? library->fill(beta_tensor, distribution, 5) : library->fill_tensor_value(beta_tensor, 0.f); |
| 77 | _use_gamma ? library->fill(gamma_tensor, distribution, 6) : library->fill_tensor_value(gamma_tensor, 1.f); |
| 78 | } |
| 79 | |
| 80 | TensorType compute_target(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, float epsilon) |
| 81 | { |
| 82 | if(_data_layout == DataLayout::NHWC) |
| 83 | { |
| 84 | permute(src_shape, PermutationVector(2U, 0U, 1U)); |
| 85 | permute(w_shape, PermutationVector(2U, 0U, 1U)); |
| 86 | permute(dst_shape, PermutationVector(2U, 0U, 1U)); |
| 87 | } |
| 88 | |
| 89 | // Create tensors |
| 90 | TensorType src = create_tensor<TensorType>(src_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 91 | TensorType conv_w = create_tensor<TensorType>(w_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 92 | TensorType conv_b = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 93 | TensorType bn_mean = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 94 | TensorType bn_var = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 95 | TensorType bn_beta = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 96 | TensorType bn_gamma = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 97 | TensorType fused_w = create_tensor<TensorType>(w_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 98 | TensorType fused_b = create_tensor<TensorType>(b_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 99 | TensorType dst = create_tensor<TensorType>(dst_shape, _data_type, 1, QuantizationInfo(), _data_layout); |
| 100 | |
| 101 | // Create and configure function |
| 102 | FusionFunctionType fuse_fn; |
| 103 | ConvolutionFunctionType conv_fn; |
| 104 | TensorType *conv_b_ptr = _use_conv_b ? &conv_b : nullptr; |
| 105 | TensorType *beta_ptr = _use_beta ? &bn_beta : nullptr; |
| 106 | TensorType *gamma_ptr = _use_gamma ? &bn_gamma : nullptr; |
| 107 | fuse_fn.configure(&conv_w, &bn_mean, &bn_var, &fused_w, &fused_b, conv_b_ptr, beta_ptr, gamma_ptr, epsilon); |
| 108 | conv_fn.configure(&src, &fused_w, &fused_b, &dst, info); |
| 109 | |
| 110 | ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 111 | ARM_COMPUTE_EXPECT(conv_w.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 112 | ARM_COMPUTE_EXPECT(conv_b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 113 | ARM_COMPUTE_EXPECT(bn_mean.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 114 | ARM_COMPUTE_EXPECT(bn_var.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 115 | ARM_COMPUTE_EXPECT(bn_beta.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 116 | ARM_COMPUTE_EXPECT(bn_gamma.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 117 | ARM_COMPUTE_EXPECT(fused_w.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 118 | ARM_COMPUTE_EXPECT(fused_b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 119 | ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 120 | |
| 121 | // Allocate tensors |
| 122 | src.allocator()->allocate(); |
| 123 | conv_w.allocator()->allocate(); |
| 124 | conv_b.allocator()->allocate(); |
| 125 | bn_mean.allocator()->allocate(); |
| 126 | bn_var.allocator()->allocate(); |
| 127 | bn_beta.allocator()->allocate(); |
| 128 | bn_gamma.allocator()->allocate(); |
| 129 | fused_w.allocator()->allocate(); |
| 130 | fused_b.allocator()->allocate(); |
| 131 | dst.allocator()->allocate(); |
| 132 | |
| 133 | ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 134 | ARM_COMPUTE_EXPECT(!conv_w.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 135 | ARM_COMPUTE_EXPECT(!conv_b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 136 | ARM_COMPUTE_EXPECT(!bn_mean.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 137 | ARM_COMPUTE_EXPECT(!bn_var.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 138 | ARM_COMPUTE_EXPECT(!bn_beta.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 139 | ARM_COMPUTE_EXPECT(!bn_gamma.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 140 | ARM_COMPUTE_EXPECT(!fused_w.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 141 | ARM_COMPUTE_EXPECT(!fused_b.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 142 | ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 143 | |
| 144 | // Fill tensors |
| 145 | fill(AccessorType(src), |
| 146 | AccessorType(conv_w), AccessorType(conv_b), |
| 147 | AccessorType(bn_mean), AccessorType(bn_var), AccessorType(bn_beta), AccessorType(bn_gamma)); |
| 148 | |
| 149 | // Compute function |
| 150 | fuse_fn.run(); |
| 151 | conv_fn.run(); |
| 152 | |
| 153 | return dst; |
| 154 | } |
| 155 | |
| 156 | SimpleTensor<T> compute_reference(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, float epsilon) |
| 157 | { |
| 158 | // Create reference |
| 159 | SimpleTensor<T> src{ src_shape, _data_type, 1 }; |
| 160 | SimpleTensor<T> conv_w{ w_shape, _data_type, 1 }; |
| 161 | SimpleTensor<T> conv_b{ b_shape, _data_type, 1 }; |
| 162 | SimpleTensor<T> bn_var{ b_shape, _data_type, 1 }; |
| 163 | SimpleTensor<T> bn_mean{ b_shape, _data_type, 1 }; |
| 164 | SimpleTensor<T> bn_beta{ b_shape, _data_type, 1 }; |
| 165 | SimpleTensor<T> bn_gamma{ b_shape, _data_type, 1 }; |
| 166 | |
| 167 | // Fill reference |
| 168 | fill(src, conv_w, conv_b, bn_mean, bn_var, bn_beta, bn_gamma); |
| 169 | |
| 170 | // Calculate Conv + BN |
| 171 | auto conv_res = reference::convolution_layer(src, conv_w, conv_b, dst_shape, info); |
| 172 | return reference::batch_normalization_layer(conv_res, bn_mean, bn_var, bn_beta, bn_gamma, epsilon, ActivationLayerInfo()); |
| 173 | } |
| 174 | |
| 175 | TensorType _target{}; |
| 176 | SimpleTensor<T> _reference{}; |
| 177 | DataType _data_type{}; |
| 178 | DataLayout _data_layout{}; |
| 179 | bool _use_conv_b{}; |
| 180 | bool _use_beta{}; |
| 181 | bool _use_gamma{}; |
| 182 | }; |
| 183 | } // namespace validation |
| 184 | } // namespace test |
| 185 | } // namespace arm_compute |
| 186 | #endif /* ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FUSION_FIXTURE */ |