blob: d0ab3e7e6b85bd2cbc31be47b99180e5693f635b [file] [log] [blame]
/*
* Copyright (c) 2018 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/graph2/mutators/NodeFusionMutator.h"
#include "arm_compute/graph2/Graph.h"
#include "arm_compute/graph2/Logger.h"
#include "arm_compute/graph2/nodes/Nodes.h"
#include "arm_compute/core/utils/misc/Cast.h"
namespace arm_compute
{
namespace graph2
{
namespace detail
{
void fuse_batch_norm_with_activation(Graph &g)
{
// Not interested in the order of nodes
for(auto &node : g.nodes())
{
// Check if the node is batch norm and not a branching node
if(node && node->type() == NodeType::BatchNormalizationLayer && node->output_edges().size() == 1)
{
auto output_edge_id = *node->output_edges().begin();
auto output_edge = g.edge(output_edge_id);
// Check if following node is an activation layer node
if((output_edge != nullptr) && (output_edge->consumer() != nullptr) && (output_edge->consumer()->type() == NodeType::ActivationLayer))
{
ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing Batch Normalization node with ID : " << output_edge->producer_id()
<< " with Activation Layer node with ID : " << output_edge->consumer_id() << std::endl);
auto *bn_node = arm_compute::utils::cast::polymorphic_downcast<BatchNormalizationLayerNode *>(output_edge->producer());
auto *act_node = arm_compute::utils::cast::polymorphic_downcast<ActivationLayerNode *>(output_edge->consumer());
// Get driving nodes of activation node
std::vector<NodeIdxPair> act_driving_nodes;
for(auto &act_output_edge_id : act_node->output_edges())
{
auto act_output_edge = g.edge(act_output_edge_id);
if(act_output_edge != nullptr)
{
ARM_COMPUTE_ERROR_ON(act_output_edge->consumer() == nullptr);
act_driving_nodes.push_back({ act_output_edge->consumer_id(), act_output_edge->consumer_idx() });
}
}
// Set activation info to batch normalization
bn_node->set_fused_activation(act_node->activation_info());
// Remove activation node
g.remove_node(act_node->id());
// Update batch normalization node outputs
for(auto &driving_node : act_driving_nodes)
{
g.add_connection(bn_node->id(), 0, driving_node.node_id, driving_node.index);
}
}
}
}
}
} // namespace detail
const char *NodeFusionMutator::name()
{
return "NodeFusionMutator";
}
void NodeFusionMutator::mutate(Graph &g)
{
detail::fuse_batch_norm_with_activation(g);
}
} // namespace graph2
} // namespace arm_compute