COMPMID-1740: Fuse batch normalization with Convolution Layer at graph level
Change-Id: I77ca51c2c72783cc26a099a6a9c3210cdbbe822d
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/797
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/graph/INodeVisitor.h b/arm_compute/graph/INodeVisitor.h
index 573d642..842ca4b 100644
--- a/arm_compute/graph/INodeVisitor.h
+++ b/arm_compute/graph/INodeVisitor.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -91,6 +91,11 @@
* @param[in] n Node to visit.
*/
virtual void visit(FullyConnectedLayerNode &n) = 0;
+ /** Visit FusedConvolutionBatchNormalizationNode.
+ *
+ * @param[in] n Node to visit.
+ */
+ virtual void visit(FusedConvolutionBatchNormalizationNode &n) = 0;
/** Visit InputNode.
*
* @param[in] n Node to visit.
@@ -195,6 +200,10 @@
{
default_visit();
}
+ virtual void visit(FusedConvolutionBatchNormalizationNode &n) override
+ {
+ default_visit();
+ }
virtual void visit(InputNode &n) override
{
default_visit();
diff --git a/arm_compute/graph/TypePrinter.h b/arm_compute/graph/TypePrinter.h
index ca62d4e..b1cfbcf 100644
--- a/arm_compute/graph/TypePrinter.h
+++ b/arm_compute/graph/TypePrinter.h
@@ -98,6 +98,9 @@
case NodeType::FullyConnectedLayer:
os << "FullyConnectedLayer";
break;
+ case NodeType::FusedConvolutionBatchNormalizationLayer:
+ os << "FusedConvolutionBatchNormalizationLayer";
+ break;
case NodeType::GenerateProposalsLayer:
os << "GenerateProposalsLayer";
break;
diff --git a/arm_compute/graph/Types.h b/arm_compute/graph/Types.h
index 8377253..2905dfcb 100644
--- a/arm_compute/graph/Types.h
+++ b/arm_compute/graph/Types.h
@@ -138,6 +138,7 @@
EltwiseLayer,
FlattenLayer,
FullyConnectedLayer,
+ FusedConvolutionBatchNormalizationLayer,
GenerateProposalsLayer,
NormalizationLayer,
NormalizePlanarYUVLayer,
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 7242bc6..d0035d9 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -28,6 +28,7 @@
#include "arm_compute/graph/Tensor.h"
#include "arm_compute/graph/TypePrinter.h"
#include "arm_compute/graph/Types.h"
+#include "arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h"
#include "arm_compute/graph/backends/Utils.h"
#include "arm_compute/graph/nodes/Nodes.h"
@@ -135,11 +136,12 @@
validate_node<TargetInfo>(node, 5 /* expected inputs */, 1 /* expected outputs */);
// Extract IO and info
- typename TargetInfo::TensorType *input = get_backing_tensor<TargetInfo>(node.input(0));
- typename TargetInfo::TensorType *mean = get_backing_tensor<TargetInfo>(node.input(1));
- typename TargetInfo::TensorType *var = get_backing_tensor<TargetInfo>(node.input(2));
- typename TargetInfo::TensorType *beta = get_backing_tensor<TargetInfo>(node.input(3));
- typename TargetInfo::TensorType *gamma = get_backing_tensor<TargetInfo>(node.input(4));
+ typename TargetInfo::TensorType *input = get_backing_tensor<TargetInfo>(node.input(0));
+ typename TargetInfo::TensorType *mean = get_backing_tensor<TargetInfo>(node.input(1));
+ typename TargetInfo::TensorType *var = get_backing_tensor<TargetInfo>(node.input(2));
+ typename TargetInfo::TensorType *beta = get_backing_tensor<TargetInfo>(node.input(3));
+ typename TargetInfo::TensorType *gamma = get_backing_tensor<TargetInfo>(node.input(4));
+
typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
const float epsilon = node.epsilon();
const ActivationLayerInfo fused_act = node.fused_activation();
@@ -163,6 +165,61 @@
return std::move(func);
}
+/** Create a backend batch normalization layer function
+ *
+ * @tparam BatchNormalizationLayerFunction Backend batch normalization function
+ * @tparam TargetInfo Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend batch normalization layer function
+ */
+template <typename FusedLayerTypes, typename TargetInfo>
+std::unique_ptr<IFunction> create_fused_convolution_batch_normalization_layer(FusedConvolutionBatchNormalizationNode &node)
+{
+ validate_node<TargetInfo>(node, 7 /* expected inputs */, 1 /* expected outputs */);
+
+ // Extract IO and info
+ typename TargetInfo::TensorType *input = get_backing_tensor<TargetInfo>(node.input(0));
+ typename TargetInfo::TensorType *weights = get_backing_tensor<TargetInfo>(node.input(1));
+ typename TargetInfo::TensorType *biases = get_backing_tensor<TargetInfo>(node.input(2));
+ typename TargetInfo::TensorType *mean = get_backing_tensor<TargetInfo>(node.input(3));
+ typename TargetInfo::TensorType *var = get_backing_tensor<TargetInfo>(node.input(4));
+ typename TargetInfo::TensorType *beta = get_backing_tensor<TargetInfo>(node.input(5));
+ typename TargetInfo::TensorType *gamma = get_backing_tensor<TargetInfo>(node.input(6));
+
+ typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
+
+ const PadStrideInfo conv_info = node.convolution_info();
+ const unsigned int num_groups = node.num_groups();
+ const bool fast_math = node.fast_math_hint() == FastMathHint::Enabled;
+ const ActivationLayerInfo fused_act = node.fused_activation();
+ const float epsilon = node.epsilon();
+
+ const bool is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type());
+ if(is_quantized && biases != nullptr)
+ {
+ biases->info()->set_data_type(DataType::S32);
+ }
+
+ // Create and configure function
+ auto func = support::cpp14::make_unique<FusedConvolutionBatchNormalizationFunction<TargetInfo, FusedLayerTypes>>();
+ func->configure(input, weights, biases, output, mean, var, beta, gamma, epsilon, conv_info, num_groups, fast_math, fused_act);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+ << node.name()
+ << " Type: " << node.name()
+ << " Target: " << TargetInfo::TargetType
+ << " Data Type: " << input->info()->data_type()
+ << " Input shape: " << input->info()->tensor_shape()
+ << " Weights shape: " << weights->info()->tensor_shape()
+ << " Output shape: " << output->info()->tensor_shape()
+ << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "")
+ << std::endl);
+ return std::move(func);
+}
+
/** Create a backend bounding box transform layer function
*
* @tparam BoundingBoxTransformLayerFunction Backend bounding box transform function
diff --git a/arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h b/arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h
new file mode 100644
index 0000000..92af17b
--- /dev/null
+++ b/arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h
@@ -0,0 +1,133 @@
+/*
+ * 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_CONVOLUTION_BATCH_NORMAZLIZATION_FUNCTION_H__
+#define __ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_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}ConvolutionLayer with the modified weights */
+template <typename TargetInfo, typename FusedLayerTypes>
+class FusedConvolutionBatchNormalizationFunction : public IFunction
+{
+public:
+ using TensorType = typename TargetInfo::TensorType;
+ using TensorConcreteType = typename TargetInfo::TensorConcreteType;
+
+ FusedConvolutionBatchNormalizationFunction()
+ : _conv_layer(), _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: QASYMM8/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
+ * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+ * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 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] num_groups Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
+ * @param[in] fast_math Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
+ * @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 num_groups, bool fast_math, 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);
+ bias_to_use = bias;
+ }
+ else
+ {
+ _fused_batch_norm_layer.configure(weights, mean, var, nullptr, &_fused_bias, nullptr, beta, gamma, epsilon);
+ bias_to_use = &_fused_bias;
+ }
+
+ _conv_layer.configure(input, weights, bias_to_use, output, conv_info, WeightsInfo(), Size2D(1U, 1U), fused_act, fast_math, num_groups);
+
+ if(!has_bias)
+ {
+ _fused_bias.allocator()->allocate();
+ }
+ }
+
+ // Inherited methods overridden:
+ void run()
+ {
+ prepare();
+ _conv_layer.run();
+ }
+
+ void prepare()
+ {
+ if(!_is_prepared)
+ {
+ _fused_batch_norm_layer.run();
+ _is_prepared = true;
+ }
+ }
+
+private:
+ typename FusedLayerTypes::ConvolutionLayer _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_CONVOLUTION_BATCH_NORMAZLIZATION_FUNCTION_H__ */
diff --git a/arm_compute/graph/mutators/NodeFusionMutator.h b/arm_compute/graph/mutators/NodeFusionMutator.h
index 8f16c65..b9ca464 100644
--- a/arm_compute/graph/mutators/NodeFusionMutator.h
+++ b/arm_compute/graph/mutators/NodeFusionMutator.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -24,21 +24,13 @@
#ifndef __ARM_COMPUTE_GRAPH_NODE_FUSION_MUTATOR_H__
#define __ARM_COMPUTE_GRAPH_NODE_FUSION_MUTATOR_H__
+#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/IGraphMutator.h"
namespace arm_compute
{
namespace graph
{
-namespace detail
-{
-/** Fused batch normalization with activation
- *
- * @param[in] g Graph to perform operation fusion on
- */
-void fuse_batch_norm_with_activation(Graph &g);
-} // namespace detail
-
/** Mutation pass to fuss nodes */
class NodeFusionMutator final : public IGraphMutator
{
diff --git a/arm_compute/graph/nodes/ActivationLayerNode.h b/arm_compute/graph/nodes/ActivationLayerNode.h
index 570351b..7231206 100644
--- a/arm_compute/graph/nodes/ActivationLayerNode.h
+++ b/arm_compute/graph/nodes/ActivationLayerNode.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -51,6 +51,9 @@
TensorDescriptor configure_output(size_t idx) const override;
void accept(INodeVisitor &v) override;
+public:
+ static constexpr NodeType node_type = NodeType::ActivationLayer;
+
private:
ActivationLayerInfo _info;
};
diff --git a/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h b/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h
new file mode 100644
index 0000000..9b0f5b7
--- /dev/null
+++ b/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h
@@ -0,0 +1,144 @@
+/*
+ * 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_FUSED_CONVOLUTION_BATCH_NORMALIZATION_NODE_H__
+#define __ARM_COMPUTE_GRAPH_FUSED_CONVOLUTION_BATCH_NORMALIZATION_NODE_H__
+
+#include "arm_compute/graph/INode.h"
+
+namespace arm_compute
+{
+namespace graph
+{
+/** Batch Normalization node */
+class FusedConvolutionBatchNormalizationNode final : public INode
+{
+public:
+ /** Constructor
+ *
+ * @param[in] epsilon Epsilon parameter.
+ * @param[in] info Convolution layer attributes.
+ * @param[in] num_groups (Optional) Number of groups (Defaults to 1)
+ * @param[in] method (Optional) Convolution method to use
+ * @param[in] fast_math_hint (Optional) Fast math hint
+ * @param[in] out_quant_info (Optional) Output quantization info
+ * @param[in] fused_activation (Optional) Fused activation layer. Disabled if not specified
+ */
+ FusedConvolutionBatchNormalizationNode(float epsilon, PadStrideInfo info,
+ unsigned int num_groups = 1,
+ ConvolutionMethod method = ConvolutionMethod::Default,
+ FastMathHint fast_math_hint = FastMathHint::Disabled,
+ QuantizationInfo out_quant_info = QuantizationInfo(), ActivationLayerInfo fused_activation = ActivationLayerInfo());
+
+ /** Epsilon parameter accessor
+ *
+ * @return Epsilon parameter
+ */
+ float epsilon() const;
+
+ /** Returns fused activation
+ *
+ * @return Fused activation
+ */
+ ActivationLayerInfo fused_activation() const;
+
+ /** Sets fused activation
+ *
+ * @param[in] fused_activation Fused activation to set
+ */
+ void set_fused_activation(ActivationLayerInfo fused_activation);
+
+ /** Computes convolution output descriptor
+ *
+ * @param[in] input_descriptor Input descriptor
+ * @param[in] weights_descriptor Weights descriptor
+ * @param[in] info Convolution operation attributes
+ *
+ * @return Output descriptor
+ */
+ static TensorDescriptor compute_output_descriptor(const TensorDescriptor &input_descriptor,
+ const TensorDescriptor &weights_descriptor,
+ const PadStrideInfo &info);
+
+ /** Sets the convolution layer method to use
+ *
+ * @param[in] method Method to use for convolution
+ */
+ void set_convolution_method(ConvolutionMethod method);
+
+ /** Number of groups in convolution accessor
+ *
+ * @return Number of groups in convolution
+ */
+ unsigned int num_groups() const;
+
+ /** Convolution layer method accessor
+ *
+ * @note This is an indication on which convolution layer implementation to use,
+ * if it fails to be created the library's heuristic approach will be used
+ *
+ * @return Convolution layer method to be used by the node
+ */
+ ConvolutionMethod convolution_method() const;
+
+ /** Sets the fast math fast hint
+ *
+ * @param[in] hint Hint to use for convolution
+ */
+ void set_fast_math_hint(FastMathHint hint);
+
+ /** Fast math hint accessor
+ *
+ * @return Fast math hint to be used by the node
+ */
+ FastMathHint fast_math_hint() const;
+
+ /** Convolution metadata accessor
+ *
+ * @return Convolution information
+ */
+ PadStrideInfo convolution_info() const;
+
+ // Inherited overridden methods:
+ NodeType type() const override;
+ bool forward_descriptors() override;
+ TensorDescriptor configure_output(size_t idx) const override;
+ void accept(INodeVisitor &v) override;
+
+public:
+ static constexpr NodeType node_type = NodeType::FusedConvolutionBatchNormalizationLayer;
+
+private:
+ float _epsilon;
+
+ PadStrideInfo _info;
+ unsigned int _num_groups;
+ ConvolutionMethod _method;
+ FastMathHint _fast_math_hint;
+ QuantizationInfo _out_quant_info;
+ ActivationLayerInfo _fused_activation;
+};
+
+} // namespace graph
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_GRAPH_BATCH_NORMALIZATION_LAYER_NODE_H__ */
diff --git a/arm_compute/graph/nodes/Nodes.h b/arm_compute/graph/nodes/Nodes.h
index 2406485..e23b2b9 100644
--- a/arm_compute/graph/nodes/Nodes.h
+++ b/arm_compute/graph/nodes/Nodes.h
@@ -38,6 +38,7 @@
#include "arm_compute/graph/nodes/EltwiseLayerNode.h"
#include "arm_compute/graph/nodes/FlattenLayerNode.h"
#include "arm_compute/graph/nodes/FullyConnectedLayerNode.h"
+#include "arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h"
#include "arm_compute/graph/nodes/GenerateProposalsLayerNode.h"
#include "arm_compute/graph/nodes/InputNode.h"
#include "arm_compute/graph/nodes/NormalizationLayerNode.h"
diff --git a/arm_compute/graph/nodes/NodesFwd.h b/arm_compute/graph/nodes/NodesFwd.h
index cbda309..80576d4 100644
--- a/arm_compute/graph/nodes/NodesFwd.h
+++ b/arm_compute/graph/nodes/NodesFwd.h
@@ -44,6 +44,7 @@
class EltwiseLayerNode;
class FlattenLayerNode;
class FullyConnectedLayerNode;
+class FusedConvolutionBatchNormalizationNode;
class GenerateProposalsLayerNode;
class InputNode;
class NormalizationLayerNode;
diff --git a/arm_compute/graph/printers/DotGraphPrinter.h b/arm_compute/graph/printers/DotGraphPrinter.h
index d4cf692..9d2ea46 100644
--- a/arm_compute/graph/printers/DotGraphPrinter.h
+++ b/arm_compute/graph/printers/DotGraphPrinter.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -56,6 +56,7 @@
void visit(ConvolutionLayerNode &n) override;
void visit(DepthwiseConvolutionLayerNode &n) override;
void visit(EltwiseLayerNode &n) override;
+ void visit(FusedConvolutionBatchNormalizationNode &n) override;
void visit(NormalizationLayerNode &n) override;
void visit(PoolingLayerNode &n) override;
void default_visit() override;