| /* |
| * Copyright (c) 2019 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. |
| */ |
| |
| #ifndef ARM_COMPUTE_GRAPH_BACKENDS_FUSED_DEPTHWISE_CONVOLUTION_BATCH_NORMALIZATION_FUNCTION_H |
| #define ARM_COMPUTE_GRAPH_BACKENDS_FUSED_DEPTHWISE_CONVOLUTION_BATCH_NORMALIZATION_FUNCTION_H |
| |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/IFunction.h" |
| |
| namespace arm_compute |
| { |
| namespace graph |
| { |
| namespace backends |
| { |
| /** Wrapper function to first apply {NE, CL}BatchNormalizationLayer on the weights and then run {NE, CL}DepthwiseConvolutionLayer with the modified weights */ |
| template <typename TargetInfo, typename FusedLayerTypes> |
| class FusedDepthwiseConvolutionBatchNormalizationFunction : public IFunction |
| { |
| public: |
| using TensorType = typename TargetInfo::TensorType; |
| using TensorConcreteType = typename TargetInfo::TensorConcreteType; |
| |
| FusedDepthwiseConvolutionBatchNormalizationFunction(std::shared_ptr<IMemoryManager> memory_manager = nullptr) |
| : _depth_conv_layer(memory_manager), _fused_batch_norm_layer(), _fused_bias(), _is_prepared(false) |
| { |
| } |
| |
| /** Set the input and output tensors. |
| * |
| * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], |
| * while every optional dimension from 4 and above represent a batch of inputs. |
| * Data types supported: F16/F32. |
| * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. |
| * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [IFM]. |
| * Data type supported: Should match @p input data type. |
| * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. |
| * Data types supported: Same as @p input. |
| * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input |
| * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input |
| * @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 |
| * @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 |
| * @param[in] epsilon Small value to avoid division with zero. Default value is 0.001f. |
| * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. |
| * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. |
| * @param[in] fused_act Activation layer information in case of a fused activation. |
| * |
| */ |
| void configure(TensorType *input, |
| TensorType *weights, |
| TensorType *bias, |
| TensorType *output, |
| const TensorType *mean, |
| const TensorType *var, |
| const TensorType *beta, |
| const TensorType *gamma, |
| float epsilon, const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo const &fused_act) |
| { |
| // We don't run any validate, as we assume that the layers have been already validated |
| const bool has_bias = (bias != nullptr); |
| const TensorType *bias_to_use; |
| |
| // We check if the layer has a bias. If yes, use it in-place. If not, we need to create one |
| // as batch normalization might end up with a bias != 0 |
| if(has_bias) |
| { |
| _fused_batch_norm_layer.configure(weights, mean, var, nullptr, nullptr, bias, beta, gamma, epsilon, FuseBatchNormalizationType::DEPTHWISECONVOLUTION); |
| bias_to_use = bias; |
| } |
| else |
| { |
| _fused_batch_norm_layer.configure(weights, mean, var, nullptr, &_fused_bias, nullptr, beta, gamma, epsilon, FuseBatchNormalizationType::DEPTHWISECONVOLUTION); |
| bias_to_use = &_fused_bias; |
| } |
| |
| _depth_conv_layer.configure(input, weights, bias_to_use, output, conv_info, depth_multiplier, fused_act.enabled() ? fused_act : ActivationLayerInfo()); |
| |
| if(!has_bias) |
| { |
| _fused_bias.allocator()->allocate(); |
| } |
| } |
| |
| // Inherited methods overridden: |
| void run() |
| { |
| prepare(); |
| _depth_conv_layer.run(); |
| } |
| |
| void prepare() |
| { |
| if(!_is_prepared) |
| { |
| _fused_batch_norm_layer.run(); |
| _is_prepared = true; |
| } |
| } |
| |
| private: |
| typename FusedLayerTypes::DepthwiseConvolutionLayer _depth_conv_layer; |
| typename FusedLayerTypes::FuseBatchNormalization _fused_batch_norm_layer; |
| TensorConcreteType _fused_bias; |
| bool _is_prepared; |
| }; |
| } // namespace backends |
| } // namespace graph |
| } // namespace arm_compute |
| |
| #endif /* ARM_COMPUTE_GRAPH_BACKENDS_FUSED_DEPTHWISE_CONVOLUTION_BATCH_NORMALIZATION_FUNCTION_H */ |