25 #ifndef ARM_COMPUTE_GRAPH_BACKENDS_FUSED_DEPTHWISE_CONVOLUTION_BATCH_NORMALIZATION_FUNCTION_H 26 #define ARM_COMPUTE_GRAPH_BACKENDS_FUSED_DEPTHWISE_CONVOLUTION_BATCH_NORMALIZATION_FUNCTION_H 38 template <
typename TargetInfo,
typename FusedLayerTypes>
46 : _depth_conv_layer(memory_manager), _fused_batch_norm_layer(), _fused_bias(), _is_prepared(false)
81 const bool has_bias = (bias !=
nullptr);
94 bias_to_use = &_fused_bias;
101 _fused_bias.allocator()->allocate();
109 _depth_conv_layer.run();
116 _fused_batch_norm_layer.run();
123 typename FusedLayerTypes::FuseBatchNormalization _fused_batch_norm_layer;
Base class for all functions.
bool enabled() const
Check if initialised.
void prepare()
Prepare the function for executing.
Wrapper function to first apply {NE, CL}BatchNormalizationLayer on the weights and then run {NE,...
Activation Layer Information class.
Copyright (c) 2017-2021 Arm Limited.
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)
Set the input and output tensors.
Padding and stride information class.
typename TargetInfo::TensorConcreteType TensorConcreteType
typename TargetInfo::TensorType TensorType
void run()
Run the kernels contained in the function.
FusedDepthwiseConvolutionBatchNormalizationFunction(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
For Depthwise Convolution weights.