giuros01 | acce504 | 2019-02-21 17:32:34 +0000 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2019 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 | |
Michalis Spyrou | f464337 | 2019-11-29 16:17:13 +0000 | [diff] [blame] | 25 | #ifndef ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_FUNCTION_H |
| 26 | #define ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_FUNCTION_H |
giuros01 | acce504 | 2019-02-21 17:32:34 +0000 | [diff] [blame] | 27 | |
| 28 | #include "arm_compute/core/Types.h" |
| 29 | #include "arm_compute/runtime/IFunction.h" |
| 30 | |
| 31 | namespace arm_compute |
| 32 | { |
| 33 | namespace graph |
| 34 | { |
| 35 | namespace backends |
| 36 | { |
| 37 | /** Wrapper function to first apply {NE, CL}BatchNormalizationLayer on the weights and then run {NE, CL}ConvolutionLayer with the modified weights */ |
| 38 | template <typename TargetInfo, typename FusedLayerTypes> |
| 39 | class FusedConvolutionBatchNormalizationFunction : public IFunction |
| 40 | { |
| 41 | public: |
| 42 | using TensorType = typename TargetInfo::TensorType; |
| 43 | using TensorConcreteType = typename TargetInfo::TensorConcreteType; |
| 44 | |
Gian Marco Iodice | 5dea19e | 2019-11-08 12:13:48 +0000 | [diff] [blame] | 45 | FusedConvolutionBatchNormalizationFunction(std::shared_ptr<IMemoryManager> memory_manager = nullptr) |
| 46 | : _conv_layer(memory_manager), _fused_batch_norm_layer(), _fused_bias(), _is_prepared(false) |
giuros01 | acce504 | 2019-02-21 17:32:34 +0000 | [diff] [blame] | 47 | { |
| 48 | } |
| 49 | |
| 50 | /** Set the input and output tensors. |
| 51 | * |
| 52 | * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], |
| 53 | * while every optional dimension from 4 and above represent a batch of inputs. |
| 54 | * Data types supported: QASYMM8/F16/F32. |
| 55 | * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input. |
| 56 | * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. |
Manuel Bottini | bffb41e | 2019-06-20 16:00:27 +0100 | [diff] [blame] | 57 | * Data type supported: Should match @p input data type. |
giuros01 | acce504 | 2019-02-21 17:32:34 +0000 | [diff] [blame] | 58 | * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. |
| 59 | * Data types supported: Same as @p input. |
| 60 | * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input |
| 61 | * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input |
| 62 | * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input |
| 63 | * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input |
| 64 | * @param[in] epsilon Small value to avoid division with zero. Default value is 0.001f. |
| 65 | * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. |
| 66 | * @param[in] num_groups Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout |
| 67 | * @param[in] fast_math Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation |
| 68 | * available which may introduce a drop of accuracy as well. Default is false |
| 69 | * @param[in] fused_act Activation layer information in case of a fused activation. |
| 70 | * |
| 71 | */ |
| 72 | void configure(TensorType *input, |
| 73 | TensorType *weights, |
| 74 | TensorType *bias, |
| 75 | TensorType *output, |
| 76 | const TensorType *mean, |
| 77 | const TensorType *var, |
| 78 | const TensorType *beta, |
| 79 | const TensorType *gamma, |
| 80 | float epsilon, const PadStrideInfo &conv_info, unsigned int num_groups, bool fast_math, ActivationLayerInfo const &fused_act) |
| 81 | { |
| 82 | // We don't run any validate, as we assume that the layers have been already validated |
| 83 | const bool has_bias = (bias != nullptr); |
| 84 | const TensorType *bias_to_use; |
| 85 | |
| 86 | // We check if the layer has a bias. If yes, use it in-place. If not, we need to create one |
| 87 | // as batch normalization might end up with a bias != 0 |
| 88 | if(has_bias) |
| 89 | { |
| 90 | _fused_batch_norm_layer.configure(weights, mean, var, nullptr, nullptr, bias, beta, gamma, epsilon); |
| 91 | bias_to_use = bias; |
| 92 | } |
| 93 | else |
| 94 | { |
| 95 | _fused_batch_norm_layer.configure(weights, mean, var, nullptr, &_fused_bias, nullptr, beta, gamma, epsilon); |
| 96 | bias_to_use = &_fused_bias; |
| 97 | } |
| 98 | |
| 99 | _conv_layer.configure(input, weights, bias_to_use, output, conv_info, WeightsInfo(), Size2D(1U, 1U), fused_act, fast_math, num_groups); |
| 100 | |
| 101 | if(!has_bias) |
| 102 | { |
| 103 | _fused_bias.allocator()->allocate(); |
| 104 | } |
| 105 | } |
| 106 | |
| 107 | // Inherited methods overridden: |
| 108 | void run() |
| 109 | { |
| 110 | prepare(); |
| 111 | _conv_layer.run(); |
| 112 | } |
| 113 | |
| 114 | void prepare() |
| 115 | { |
| 116 | if(!_is_prepared) |
| 117 | { |
| 118 | _fused_batch_norm_layer.run(); |
| 119 | _is_prepared = true; |
| 120 | } |
| 121 | } |
| 122 | |
| 123 | private: |
| 124 | typename FusedLayerTypes::ConvolutionLayer _conv_layer; |
| 125 | typename FusedLayerTypes::FuseBatchNormalization _fused_batch_norm_layer; |
| 126 | TensorConcreteType _fused_bias; |
| 127 | bool _is_prepared; |
| 128 | }; |
| 129 | } // namespace backends |
| 130 | } // namespace graph |
| 131 | } // namespace arm_compute |
| 132 | |
Michalis Spyrou | f464337 | 2019-11-29 16:17:13 +0000 | [diff] [blame] | 133 | #endif /* ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_FUNCTION_H */ |