1 /* 2 * Copyright (c) 2017-2018 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_FIXTURE 25 #define ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_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 37 namespace arm_compute 38 { 39 namespace test 40 { 41 namespace validation 42 { 43 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 44 class BatchNormalizationLayerValidationFixture : public framework::Fixture 45 { 46 public: 47 template <typename...> setup(TensorShape shape0,TensorShape shape1,float epsilon,bool use_beta,bool use_gamma,ActivationLayerInfo act_info,DataType dt,DataLayout data_layout)48 void setup(TensorShape shape0, TensorShape shape1, float epsilon, bool use_beta, bool use_gamma, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout) 49 { 50 _data_type = dt; 51 _use_beta = use_beta; 52 _use_gamma = use_gamma; 53 54 _target = compute_target(shape0, shape1, epsilon, act_info, dt, data_layout); 55 _reference = compute_reference(shape0, shape1, epsilon, act_info, dt); 56 } 57 58 protected: 59 template <typename U> fill(U && src_tensor,U && mean_tensor,U && var_tensor,U && beta_tensor,U && gamma_tensor)60 void fill(U &&src_tensor, U &&mean_tensor, U &&var_tensor, U &&beta_tensor, U &&gamma_tensor) 61 { 62 const float min_bound = -1.f; 63 const float max_bound = 1.f; 64 std::uniform_real_distribution<> distribution(min_bound, max_bound); 65 std::uniform_real_distribution<> distribution_var(0, max_bound); 66 library->fill(src_tensor, distribution, 0); 67 library->fill(mean_tensor, distribution, 1); 68 library->fill(var_tensor, distribution_var, 0); 69 if(_use_beta) 70 { 71 library->fill(beta_tensor, distribution, 3); 72 } 73 else 74 { 75 // Fill with default value 0.f 76 library->fill_tensor_value(beta_tensor, 0.f); 77 } 78 if(_use_gamma) 79 { 80 library->fill(gamma_tensor, distribution, 4); 81 } 82 else 83 { 84 // Fill with default value 1.f 85 library->fill_tensor_value(gamma_tensor, 1.f); 86 } 87 } 88 compute_target(TensorShape shape0,const TensorShape & shape1,float epsilon,ActivationLayerInfo act_info,DataType dt,DataLayout data_layout)89 TensorType compute_target(TensorShape shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout) 90 { 91 if(data_layout == DataLayout::NHWC) 92 { 93 permute(shape0, PermutationVector(2U, 0U, 1U)); 94 } 95 96 // Create tensors 97 TensorType src = create_tensor<TensorType>(shape0, dt, 1, QuantizationInfo(), data_layout); 98 TensorType dst = create_tensor<TensorType>(shape0, dt, 1, QuantizationInfo(), data_layout); 99 TensorType mean = create_tensor<TensorType>(shape1, dt, 1); 100 TensorType var = create_tensor<TensorType>(shape1, dt, 1); 101 TensorType beta = create_tensor<TensorType>(shape1, dt, 1); 102 TensorType gamma = create_tensor<TensorType>(shape1, dt, 1); 103 104 // Create and configure function 105 FunctionType norm; 106 TensorType *beta_ptr = _use_beta ? &beta : nullptr; 107 TensorType *gamma_ptr = _use_gamma ? &gamma : nullptr; 108 norm.configure(&src, &dst, &mean, &var, beta_ptr, gamma_ptr, epsilon, act_info); 109 110 ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); 111 ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); 112 ARM_COMPUTE_EXPECT(mean.info()->is_resizable(), framework::LogLevel::ERRORS); 113 ARM_COMPUTE_EXPECT(var.info()->is_resizable(), framework::LogLevel::ERRORS); 114 ARM_COMPUTE_EXPECT(beta.info()->is_resizable(), framework::LogLevel::ERRORS); 115 ARM_COMPUTE_EXPECT(gamma.info()->is_resizable(), framework::LogLevel::ERRORS); 116 117 // Allocate tensors 118 src.allocator()->allocate(); 119 dst.allocator()->allocate(); 120 mean.allocator()->allocate(); 121 var.allocator()->allocate(); 122 beta.allocator()->allocate(); 123 gamma.allocator()->allocate(); 124 125 ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); 126 ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); 127 ARM_COMPUTE_EXPECT(!mean.info()->is_resizable(), framework::LogLevel::ERRORS); 128 ARM_COMPUTE_EXPECT(!var.info()->is_resizable(), framework::LogLevel::ERRORS); 129 ARM_COMPUTE_EXPECT(!beta.info()->is_resizable(), framework::LogLevel::ERRORS); 130 ARM_COMPUTE_EXPECT(!gamma.info()->is_resizable(), framework::LogLevel::ERRORS); 131 132 // Fill tensors 133 fill(AccessorType(src), AccessorType(mean), AccessorType(var), AccessorType(beta), AccessorType(gamma)); 134 135 // Compute function 136 norm.run(); 137 138 return dst; 139 } 140 compute_reference(const TensorShape & shape0,const TensorShape & shape1,float epsilon,ActivationLayerInfo act_info,DataType dt)141 SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt) 142 { 143 // Create reference 144 SimpleTensor<T> ref_src{ shape0, dt, 1 }; 145 SimpleTensor<T> ref_mean{ shape1, dt, 1 }; 146 SimpleTensor<T> ref_var{ shape1, dt, 1 }; 147 SimpleTensor<T> ref_beta{ shape1, dt, 1 }; 148 SimpleTensor<T> ref_gamma{ shape1, dt, 1 }; 149 150 // Fill reference 151 fill(ref_src, ref_mean, ref_var, ref_beta, ref_gamma); 152 153 return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, act_info); 154 } 155 156 TensorType _target{}; 157 SimpleTensor<T> _reference{}; 158 DataType _data_type{}; 159 bool _use_beta{}; 160 bool _use_gamma{}; 161 }; 162 } // namespace validation 163 } // namespace test 164 } // namespace arm_compute 165 #endif /* ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FIXTURE */ 166