Add graph level convolution fusion with post operator

Resolves: COMPMID-4701

Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Change-Id: I8a0d3c2ed4bf84489d94b8ae6641d6041aadaee5
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6557
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

6 files changed, 450 insertions, 5 deletions

diff --git a/src/graph/INodeVisitor.cpp b/src/graph/INodeVisitor.cpp
index 2bbf519cf5..ceaaeae7f2 100644
--- a/src/graph/INodeVisitor.cpp
+++ b/src/graph/INodeVisitor.cpp
@@ -85,6 +85,10 @@ void DefaultNodeVisitor::visit(FusedConvolutionBatchNormalizationNode &n)
 {
     default_visit(n);
 }
+void DefaultNodeVisitor::visit(FusedConvolutionWithPostOpNode &n)
+{
+    default_visit(n);
+}
 void DefaultNodeVisitor::visit(FusedDepthwiseConvolutionBatchNormalizationNode &n)
 {
     default_visit(n);
diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp
index 1cd3f9f9c7..838977e75c 100644
--- a/src/graph/backends/CL/CLFunctionsFactory.cpp
+++ b/src/graph/backends/CL/CLFunctionsFactory.cpp
@@ -81,6 +81,7 @@ struct CLFusedLayerTypes
     using ConvolutionLayer          = CLConvolutionLayer;
     using DepthwiseConvolutionLayer = CLDepthwiseConvolutionLayer;
     using FuseBatchNormalization    = CLFuseBatchNormalization;
+    using GEMMConvolutionLayer      = CLGEMMConvolutionLayer;
 };
 
 /** Wrapper for the CPP Function in the OpenCL backend **/
@@ -273,6 +274,8 @@ std::unique_ptr<IFunction> CLFunctionFactory::create(INode *node, GraphContext &
             return detail::create_fully_connected_layer<CLFullyConnectedLayer, CLTargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx);
         case NodeType::FusedConvolutionBatchNormalizationLayer:
             return detail::create_fused_convolution_batch_normalization_layer<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedConvolutionBatchNormalizationNode *>(node), ctx);
+        case NodeType::FusedConvolutionWithPostOp:
+            return detail::create_fused_convolution_with_post_op<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedConvolutionWithPostOpNode *>(node), ctx);
         case NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer:
             return detail::create_fused_depthwise_convolution_batch_normalization_layer<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node), ctx);
         case NodeType::GenerateProposalsLayer:
diff --git a/src/graph/backends/CL/CLNodeValidator.cpp b/src/graph/backends/CL/CLNodeValidator.cpp
index 8e3b4c8705..c50782db48 100644
--- a/src/graph/backends/CL/CLNodeValidator.cpp
+++ b/src/graph/backends/CL/CLNodeValidator.cpp
@@ -76,6 +76,8 @@ Status CLNodeValidator::validate(INode *node)
                    CLDirectConvolutionLayer,
                    CLGEMMConvolutionLayer,
                    CLWinogradConvolutionLayer>(*polymorphic_downcast<ConvolutionLayerNode *>(node));
+        case NodeType::FusedConvolutionWithPostOp:
+            return detail::validate_fused_convolution_with_post_op<CLGEMMConvolutionLayer>(*polymorphic_downcast<FusedConvolutionWithPostOpNode *>(node));
         case NodeType::DepthToSpaceLayer:
             return detail::validate_depth_to_space_layer<CLDepthToSpaceLayer>(*polymorphic_downcast<DepthToSpaceLayerNode *>(node));
         case NodeType::DepthwiseConvolutionLayer:
diff --git a/src/graph/mutators/NodeFusionMutator.cpp b/src/graph/mutators/NodeFusionMutator.cpp
index e37164c60c..463d1cd8f6 100644
--- a/src/graph/mutators/NodeFusionMutator.cpp
+++ b/src/graph/mutators/NodeFusionMutator.cpp
@@ -28,12 +28,14 @@
 #include "arm_compute/graph/Utils.h"
 #include "arm_compute/graph/backends/BackendRegistry.h"
 #include "arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h"
+#include "arm_compute/graph/nodes/FusedConvolutionWithPostOpNode.h"
 #include "arm_compute/graph/nodes/Nodes.h"
 
 #include "src/graph/mutators/MutatorUtils.h"
 
 #include "support/Cast.h"
 
+#include <list>
 #include <set>
 
 namespace arm_compute
@@ -322,13 +324,13 @@ void fuse_layer(Graph &g, std::function<bool(INode &)> const &prec, const F fuse
     for(unsigned int i = 0; i < g.nodes().size(); ++i)
     {
         auto node = g.node(i);
-        // Check if the node is of type N and not a branching node
+        // Check if the node is of type N1 and not a branching node
         if(node && node->type() == N1::node_type && node->output_edges().size() == 1)
         {
             const auto output_edge_id = *node->output_edges().begin();
             const auto output_edge    = g.edge(output_edge_id);
 
-            // Check if following node is an activation layer node
+            // Check if following node is a type N2 node
             if((output_edge != nullptr) && (output_edge->consumer() != nullptr) && (output_edge->consumer()->type() == N2::node_type) && prec(*output_edge->producer()))
             {
                 fuse_fcn(g, output_edge, optional_arguments...);
@@ -336,6 +338,266 @@ void fuse_layer(Graph &g, std::function<bool(INode &)> const &prec, const F fuse
         }
     }
 }
+
+/** Fuse below operators:
+ *
+ * | Main operator | Post operators             |
+ * |:--------------|:---------------------------|
+ * |conv           | add                        |
+ * |conv           | act + add                  |
+ * |conv           | add + act                  |
+ * |conv           | act + add + act            |
+ *
+ * Notes: currently, only GEMM supports fusion with post operator
+*/
+template <typename N>
+void fuse_convolution(Graph &g, const Edge *output_edge, int conv_node_id, const std::set<Activation> &supported_fused_activations)
+{
+    ARM_COMPUTE_ERROR_ON(output_edge == nullptr);
+
+    auto *conv_node = arm_compute::utils::cast::polymorphic_downcast<N *>(output_edge->producer());
+    ARM_COMPUTE_ERROR_ON(conv_node->output(0) == nullptr);
+    // Prevent fusion if fused node has an output accessor
+    if(conv_node->output(0)->accessor() == nullptr)
+    {
+        // If data type is FP32/FP16, data layout is NHWC, and filter size if 1x1, fuse convolution with post op, as Conv1x1 always leads to GEMM.
+        const Edge *input_edge = conv_node->input_edge(1);
+        if(input_edge != nullptr && input_edge->tensor() != nullptr)
+        {
+            const DataLayout  data_layout  = input_edge->tensor()->desc().layout;
+            const DataType    data_type    = input_edge->tensor()->desc().data_type;
+            const TensorShape tensor_shape = input_edge->tensor()->desc().shape;
+            if(data_layout != DataLayout::NHWC || is_data_type_float(data_type) == false || tensor_shape.y() != 1 || tensor_shape.z() != 1)
+            {
+                ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to non GEMM convolution\n");
+                return;
+            }
+        }
+        else
+        {
+            return;
+        }
+
+        std::list<INode *> post_op_node_list      = {};
+        int                eltwise_adden_input_id = 0;
+        int                prev_op_dst_pos        = 0; // Previous operator dst's postion in current operator
+        NodeID             prev_op_dst_id         = conv_node->id();
+        for(unsigned int i = conv_node_id + 1; i < g.nodes().size(); ++i)
+        {
+            auto post_op_node    = g.node(i);
+            bool fusable_post_op = false;
+            if(post_op_node != nullptr && post_op_node->output_edges().size() > 0)
+            {
+                const auto post_op_output_edge_id = *post_op_node->output_edges().begin();
+                const auto post_op_output_edge    = g.edge(post_op_output_edge_id);
+
+                if(post_op_output_edge != nullptr)
+                {
+                    switch(post_op_output_edge->producer()->type())
+                    {
+                        case EltwiseLayerNode::node_type:
+                        {
+                            auto *eltwise_node = arm_compute::utils::cast::polymorphic_downcast<EltwiseLayerNode *>(post_op_output_edge->producer());
+                            ARM_COMPUTE_ERROR_ON(eltwise_node->output(0) == nullptr);
+                            if(eltwise_node->output(0)->accessor() == nullptr)
+                            {
+                                post_op_node_list.push_back(post_op_output_edge->producer());
+                                fusable_post_op = true;
+
+                                // Extract elementwise inputs
+                                const auto eltwise_input_id_0 = eltwise_node->input_edge(0)->producer_id();
+                                const auto eltwise_input_id_1 = eltwise_node->input_edge(1)->producer_id();
+                                if(eltwise_input_id_0 == prev_op_dst_id)
+                                {
+                                    eltwise_adden_input_id = eltwise_input_id_1;
+                                    prev_op_dst_pos        = 0;
+                                }
+                                else if(eltwise_input_id_1 == prev_op_dst_id)
+                                {
+                                    eltwise_adden_input_id = eltwise_input_id_0;
+                                    prev_op_dst_pos        = 1;
+                                }
+                            }
+                            else
+                            {
+                                ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with elementwise due to the presence of an output accessor\n");
+                            }
+                            break;
+                        }
+                        case ActivationLayerNode::node_type:
+                        {
+                            auto *act_node = arm_compute::utils::cast::polymorphic_downcast<ActivationLayerNode *>(post_op_output_edge->producer());
+                            ARM_COMPUTE_ERROR_ON(act_node->output(0) == nullptr);
+                            // Check if activation is supported for fusion
+                            if(supported_fused_activations.count(act_node->activation_info().activation()) == 0)
+                            {
+                                break;
+                            }
+                            if(act_node->output(0)->accessor() == nullptr)
+                            {
+                                post_op_node_list.push_back(post_op_output_edge->producer());
+                                fusable_post_op = true;
+                                prev_op_dst_id  = act_node->id();
+                            }
+                            else
+                            {
+                                ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with activation due to the presence of an output accessor\n");
+                            }
+                            break;
+                        }
+                        default:
+                            break;
+                    }
+                }
+
+                // Check if the node is not a branching node and current node is fusable
+                if(post_op_node->output_edges().size() == 1 && fusable_post_op == true)
+                {
+                    continue;
+                }
+                else
+                {
+                    break;
+                }
+            }
+        }
+
+        if(post_op_node_list.size() == 0)
+        {
+            return;
+        }
+        else if(post_op_node_list.size() == 1) // Use fusion without post op if post op only contains one activation operator
+        {
+            for(const auto &post_op : post_op_node_list)
+            {
+                if(post_op->type() == ActivationLayerNode::node_type)
+                {
+                    post_op_node_list.clear();
+                    return;
+                }
+            }
+        }
+        else // Use fusion with post op if there're two or more operators
+        {
+            const Target assigned_target = conv_node->assigned_target();
+
+            // Extract conv inputs
+            const auto   conv_input_id   = conv_node->input_edge(0)->producer_id();
+            const auto   conv_weights_id = conv_node->input_edge(1)->producer_id();
+            const auto   conv_info       = conv_node->convolution_info();
+            const auto   conv_method     = conv_node->convolution_method();
+            const auto   num_groups      = conv_node->num_groups();
+            FastMathHint fast_math_hint  = conv_node->fast_math_hint();
+
+            // Create the fused node
+            const NodeID fused_id = g.add_node<FusedConvolutionWithPostOpNode>(conv_info, num_groups, conv_method, fast_math_hint);
+            ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing convolution node with ID : " << conv_node->id());
+
+            // Add connections from the conv inputs to the fused node
+            g.add_connection(conv_input_id, 0, fused_id, 0);
+            g.add_connection(conv_weights_id, 0, fused_id, 1);
+            if(conv_node->input_edge(2) != nullptr)
+            {
+                auto conv_bias_id = conv_node->input_edge(2)->producer_id();
+                g.add_connection(conv_bias_id, 0, fused_id, 2);
+            }
+            g.add_connection(eltwise_adden_input_id, 0, fused_id, 3);
+            g.remove_node(conv_node->id());
+
+            // Update fused node outputs
+            auto  fused_node      = g.node(fused_id);
+            auto *fused_conv_node = arm_compute::utils::cast::polymorphic_downcast<FusedConvolutionWithPostOpNode *>(fused_node);
+            fused_node->set_assigned_target(assigned_target);
+
+            unsigned int op_idx = 0;
+            // Fuse post operators with conv
+            for(const auto &post_op : post_op_node_list)
+            {
+                switch(post_op->type())
+                {
+                    case EltwiseLayerNode::node_type:
+                    {
+                        auto *eltwise_node = arm_compute::utils::cast::polymorphic_downcast<EltwiseLayerNode *>(post_op);
+                        ARM_COMPUTE_ERROR_ON(eltwise_node->output(0) == nullptr);
+
+                        fused_conv_node->post_op_info_list().push_back(std::make_unique<ConvPostOpInfoEltwiseAdd>(prev_op_dst_pos, eltwise_node->convert_policy()));
+                        ARM_COMPUTE_LOG_GRAPH_VERBOSE(" with Elementwise Layer node with ID : " << post_op->id());
+                        break;
+                    }
+                    case ActivationLayerNode::node_type:
+                    {
+                        auto *act_node = arm_compute::utils::cast::polymorphic_downcast<ActivationLayerNode *>(post_op);
+                        ARM_COMPUTE_ERROR_ON(act_node->output(0) == nullptr);
+
+                        fused_conv_node->post_op_info_list().push_back(std::make_unique<ConvPostOpInfoActivation>(act_node->activation_info()));
+                        ARM_COMPUTE_LOG_GRAPH_VERBOSE(" with Activation Layer node with ID : " << post_op->id());
+                        break;
+                    }
+                    default:
+                        break;
+                }
+
+                if(op_idx == post_op_node_list.size() - 1) // last fusable node
+                {
+                    // Get driving nodes of last fusable node
+                    std::vector<NodeIdxPair> last_driving_nodes = get_driving_nodes(*post_op);
+
+                    // Extract last fusable node accessor if any
+                    auto last_node_accessor = post_op->output(0)->extract_accessor();
+
+                    // Remove node
+                    g.remove_node(post_op->id());
+
+                    // Update fused node outputs
+                    for(auto &driving_node : last_driving_nodes)
+                    {
+                        g.add_connection(fused_id, 0, driving_node.node_id, driving_node.index);
+                        configure_tensor(fused_node->output(0));
+                    }
+
+                    // Update accessor to fused node
+                    fused_node->output(0)->set_accessor(std::move(last_node_accessor));
+                }
+                else
+                {
+                    // Remove node
+                    g.remove_node(post_op->id());
+                }
+                op_idx++;
+            }
+            post_op_node_list.clear();
+            ARM_COMPUTE_LOG_GRAPH_VERBOSE(std::endl);
+        }
+    }
+    else
+    {
+        ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to the presence of an output accessor\n");
+    }
+}
+
+template <typename N1, typename F, typename... Args>
+void fuse_layer(Graph &g, std::function<bool(INode &)> const &prec, const F fuse_fcn, Args &&... optional_arguments)
+{
+    // Note that fused nodes may be added to the end of the node list.
+    // Instead of only looping over the original list of nodes, we loop over the current node list which could be growing.
+    // This is intentional as it probes the newly added fused nodes for further fusing opportunities.
+    for(unsigned int i = 0; i < g.nodes().size(); ++i)
+    {
+        auto node = g.node(i);
+        // Check if the node is of type N1 and not a branching node
+        if(node && node->type() == N1::node_type && node->output_edges().size() == 1)
+        {
+            const auto output_edge_id = *node->output_edges().begin();
+            const auto output_edge    = g.edge(output_edge_id);
+
+            // Check if it's the correct target
+            if((output_edge != nullptr) && (output_edge->consumer() != nullptr) && prec(*output_edge->producer()))
+            {
+                fuse_fcn(g, output_edge, i, optional_arguments...);
+            }
+        }
+    }
+}
 } // namespace detail
 
 const char *NodeFusionMutator::name()
@@ -381,15 +643,17 @@ void NodeFusionMutator::mutate(Graph &g)
     };
 
     // Fusion mutations
+
+    detail::fuse_layer<ConvolutionLayerNode>(g, cl_target_prec, detail::fuse_convolution<ConvolutionLayerNode>, supported_fused_activations);
+    detail::fuse_layer<ConvolutionLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<ConvolutionLayerNode>, supported_fused_activations);
+    detail::fuse_layer<ConvolutionLayerNode, BatchNormalizationLayerNode>(g, empty_prec, detail::fuse_convolution_with_batch_normalization);
     detail::fuse_layer<PadLayerNode, ConvolutionLayerNode>(g, empty_prec, detail::fuse_pad_with_convolution<ConvolutionLayerNode>);
     detail::fuse_layer<PadLayerNode, DepthwiseConvolutionLayerNode>(g, empty_prec, detail::fuse_pad_with_convolution<DepthwiseConvolutionLayerNode>);
     detail::fuse_layer<BatchNormalizationLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<BatchNormalizationLayerNode>, supported_fused_activations);
-    detail::fuse_layer<ConvolutionLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<ConvolutionLayerNode>, supported_fused_activations);
     detail::fuse_layer<DepthwiseConvolutionLayerNode, ActivationLayerNode>(g, qs8_prec, detail::fuse_node_with_activation<DepthwiseConvolutionLayerNode>, supported_fused_activations);
+    detail::fuse_layer<DepthwiseConvolutionLayerNode, BatchNormalizationLayerNode>(g, empty_prec, detail::fuse_depthwise_convolution_with_batch_normalization);
     detail::fuse_layer<FullyConnectedLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<FullyConnectedLayerNode>, supported_fused_activations);
     detail::fuse_layer<EltwiseLayerNode, ActivationLayerNode>(g, cl_target_prec, detail::fuse_node_with_activation<EltwiseLayerNode>, supported_fused_activations);
-    detail::fuse_layer<ConvolutionLayerNode, BatchNormalizationLayerNode>(g, empty_prec, detail::fuse_convolution_with_batch_normalization);
-    detail::fuse_layer<DepthwiseConvolutionLayerNode, BatchNormalizationLayerNode>(g, empty_prec, detail::fuse_depthwise_convolution_with_batch_normalization);
 }
 } // namespace graph
 } // namespace arm_compute
diff --git a/src/graph/nodes/FusedConvolutionWithPostOpNode.cpp b/src/graph/nodes/FusedConvolutionWithPostOpNode.cpp
new file mode 100644
index 0000000000..c7ca59d863
--- /dev/null
+++ b/src/graph/nodes/FusedConvolutionWithPostOpNode.cpp
@@ -0,0 +1,164 @@
+/*
+ * Copyright (c) 2021 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.
+ */
+#include "arm_compute/graph/nodes/FusedConvolutionWithPostOpNode.h"
+
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/graph/Graph.h"
+#include "arm_compute/graph/INodeVisitor.h"
+#include "arm_compute/graph/Utils.h"
+
+namespace arm_compute
+{
+namespace graph
+{
+FusedConvolutionWithPostOpNode::FusedConvolutionWithPostOpNode(PadStrideInfo     info,
+                                                               unsigned int      num_groups,
+                                                               ConvolutionMethod method,
+                                                               FastMathHint      fast_math_hint,
+                                                               QuantizationInfo  out_quant_info)
+    : _info(std::move(info)), _num_groups(num_groups), _method(method), _fast_math_hint(fast_math_hint), _out_quant_info(std::move(out_quant_info)), _fused_activation(),
+      _post_op_info_list(std::list<std::unique_ptr<ConvPostOpInfo>> {})
+{
+    _input_edges.resize(4, EmptyEdgeID);
+    _outputs.resize(1, NullTensorID);
+}
+
+void FusedConvolutionWithPostOpNode::set_convolution_method(ConvolutionMethod method)
+{
+    _method = method;
+}
+
+ConvolutionMethod FusedConvolutionWithPostOpNode::convolution_method() const
+{
+    return _method;
+}
+
+void FusedConvolutionWithPostOpNode::set_fast_math_hint(FastMathHint hint)
+{
+    _fast_math_hint = hint;
+}
+
+FastMathHint FusedConvolutionWithPostOpNode::fast_math_hint() const
+{
+    return _fast_math_hint;
+}
+
+const std::list<std::unique_ptr<ConvPostOpInfo>> &FusedConvolutionWithPostOpNode::post_op_info_list() const
+{
+    return _post_op_info_list;
+}
+
+std::list<std::unique_ptr<ConvPostOpInfo>> &FusedConvolutionWithPostOpNode::post_op_info_list()
+{
+    return _post_op_info_list;
+}
+
+PadStrideInfo FusedConvolutionWithPostOpNode::convolution_info() const
+{
+    return _info;
+}
+
+unsigned int FusedConvolutionWithPostOpNode::num_groups() const
+{
+    return _num_groups;
+}
+
+ActivationLayerInfo FusedConvolutionWithPostOpNode::fused_activation() const
+{
+    return _fused_activation;
+}
+
+void FusedConvolutionWithPostOpNode::set_fused_activation(ActivationLayerInfo fused_activation)
+{
+    _fused_activation = fused_activation;
+}
+
+void FusedConvolutionWithPostOpNode::set_convolution_info(PadStrideInfo info)
+{
+    _info = info;
+}
+
+TensorDescriptor FusedConvolutionWithPostOpNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
+                                                                           const TensorDescriptor &weights_descriptor,
+                                                                           const PadStrideInfo    &info)
+{
+    unsigned int output_width  = 0;
+    unsigned int output_height = 0;
+
+    const unsigned int input_width   = get_dimension_size(input_descriptor, DataLayoutDimension::WIDTH);
+    const unsigned int input_height  = get_dimension_size(input_descriptor, DataLayoutDimension::HEIGHT);
+    const unsigned int kernel_width  = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH);
+    const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT);
+
+    std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
+
+    const DataLayout data_layout       = input_descriptor.layout;
+    TensorDescriptor output_descriptor = input_descriptor;
+    output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width);
+    output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height);
+    output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
+
+    return output_descriptor;
+}
+
+bool FusedConvolutionWithPostOpNode::forward_descriptors()
+{
+    if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID))
+    {
+        Tensor *dst = output(0);
+        ARM_COMPUTE_ERROR_ON(dst == nullptr);
+        dst->desc() = configure_output(0);
+        return true;
+    }
+    return false;
+}
+
+TensorDescriptor FusedConvolutionWithPostOpNode::configure_output(size_t idx) const
+{
+    ARM_COMPUTE_UNUSED(idx);
+    const Tensor *src     = input(0);
+    const Tensor *weights = input(1);
+
+    ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr);
+
+    TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info);
+    if(!_out_quant_info.empty())
+    {
+        output_info.quant_info = _out_quant_info;
+    }
+
+    return output_info;
+}
+
+NodeType FusedConvolutionWithPostOpNode::type() const
+{
+    return FusedConvolutionWithPostOpNode::node_type;
+}
+
+void FusedConvolutionWithPostOpNode::accept(INodeVisitor &v)
+{
+    v.visit(*this);
+}
+} // namespace graph
+} // namespace arm_compute
diff --git a/src/graph/printers/DotGraphPrinter.cpp b/src/graph/printers/DotGraphPrinter.cpp
index 08f7f25ee5..47371e34d5 100644
--- a/src/graph/printers/DotGraphPrinter.cpp
+++ b/src/graph/printers/DotGraphPrinter.cpp
@@ -85,6 +85,14 @@ void DotGraphVisitor::visit(FusedConvolutionBatchNormalizationNode &n)
     _info = ss.str();
 }
 
+void DotGraphVisitor::visit(FusedConvolutionWithPostOpNode &n)
+{
+    ARM_COMPUTE_UNUSED(n);
+    std::stringstream ss;
+    ss << "FusedConvolutionWithPostOpNode";
+    _info = ss.str();
+}
+
 void DotGraphVisitor::visit(FusedDepthwiseConvolutionBatchNormalizationNode &n)
 {
     ARM_COMPUTE_UNUSED(n);