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-rw-r--r--src/graph/mutators/NodeFusionMutator.cpp169
1 files changed, 91 insertions, 78 deletions
diff --git a/src/graph/mutators/NodeFusionMutator.cpp b/src/graph/mutators/NodeFusionMutator.cpp
index 38284b93cf..998a4a05c7 100644
--- a/src/graph/mutators/NodeFusionMutator.cpp
+++ b/src/graph/mutators/NodeFusionMutator.cpp
@@ -24,15 +24,14 @@
#include "arm_compute/graph/mutators/NodeFusionMutator.h"
#include "arm_compute/core/utils/DataTypeUtils.h"
+#include "arm_compute/graph/backends/BackendRegistry.h"
#include "arm_compute/graph/GraphBuilder.h"
#include "arm_compute/graph/Logger.h"
-#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/Nodes.h"
+#include "arm_compute/graph/Utils.h"
#include "src/graph/mutators/MutatorUtils.h"
-
#include "support/Cast.h"
#include <list>
@@ -46,7 +45,7 @@ namespace detail
{
void transfer_driving_nodes_and_remove_old_node(Graph &g, INode *new_node, INode *old_node, bool add_output_tensor)
{
- if(new_node == nullptr || old_node == nullptr)
+ if (new_node == nullptr || old_node == nullptr)
{
return;
}
@@ -55,7 +54,7 @@ void transfer_driving_nodes_and_remove_old_node(Graph &g, INode *new_node, INode
std::vector<NodeIdxPair> last_driving_nodes = get_driving_nodes(*old_node);
// Extract last fusable node accessor if any
- if(old_node->output(0) == nullptr)
+ if (old_node->output(0) == nullptr)
{
return;
}
@@ -65,10 +64,10 @@ void transfer_driving_nodes_and_remove_old_node(Graph &g, INode *new_node, INode
g.remove_node(old_node->id());
// Update fused node outputs
- for(auto &driving_node : last_driving_nodes)
+ for (auto &driving_node : last_driving_nodes)
{
g.add_connection(new_node->id(), 0, driving_node.node_id, driving_node.index);
- if(add_output_tensor)
+ if (add_output_tensor)
{
configure_tensor(new_node->output(0));
}
@@ -83,19 +82,21 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge
ARM_COMPUTE_ERROR_ON(output_edge == nullptr);
auto *conv_node = arm_compute::utils::cast::polymorphic_downcast<ConvolutionLayerNode *>(output_edge->producer());
- auto *bn_node = arm_compute::utils::cast::polymorphic_downcast<BatchNormalizationLayerNode *>(output_edge->consumer());
+ auto *bn_node =
+ arm_compute::utils::cast::polymorphic_downcast<BatchNormalizationLayerNode *>(output_edge->consumer());
// Not fusing if number of groups is greater than 1
- if(conv_node->num_groups() > 1)
+ if (conv_node->num_groups() > 1)
{
return;
}
- ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing convolution node with ID : " << output_edge->producer_id()
- << " with BatchNormalization Layer node with ID : " << output_edge->consumer_id() << std::endl);
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing convolution node with ID : "
+ << output_edge->producer_id() << " with BatchNormalization Layer node with ID : "
+ << output_edge->consumer_id() << std::endl);
// Prevent fusion if fused node has an output accessor
- if(conv_node->output(0)->accessor() == nullptr)
+ if (conv_node->output(0)->accessor() == nullptr)
{
const Target assigned_target = conv_node->assigned_target();
@@ -115,9 +116,10 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge
const auto epsilon = bn_node->epsilon();
// Create the fused node
- const NodeID fused_id = g.add_node<FusedConvolutionBatchNormalizationNode>(epsilon, conv_info, num_groups, conv_method, fast_math_hint, act_info);
+ const NodeID fused_id = g.add_node<FusedConvolutionBatchNormalizationNode>(
+ epsilon, conv_info, num_groups, conv_method, fast_math_hint, act_info);
- if(conv_node->input_edge(2) != nullptr)
+ 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);
@@ -129,13 +131,13 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge
g.add_connection(bn_mean_id, 0, fused_id, 3);
g.add_connection(bn_var_id, 0, fused_id, 4);
- if(bn_node->input_edge(3) != nullptr)
+ if (bn_node->input_edge(3) != nullptr)
{
const auto bn_beta_id = bn_node->input_edge(3)->producer_id();
g.add_connection(bn_beta_id, 0, fused_id, 5);
}
- if(bn_node->input_edge(4) != nullptr)
+ if (bn_node->input_edge(4) != nullptr)
{
const auto bn_gamma_id = bn_node->input_edge(4)->producer_id();
g.add_connection(bn_gamma_id, 0, fused_id, 6);
@@ -147,14 +149,15 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge
transfer_driving_nodes_and_remove_old_node(g, fused_node, bn_node, true);
fused_node->set_assigned_target(assigned_target);
- fused_node->set_common_node_parameters(NodeParams{ conv_node->name() + "+" + bn_node_name, assigned_target });
+ fused_node->set_common_node_parameters(NodeParams{conv_node->name() + "+" + bn_node_name, assigned_target});
// Remove convolution node
g.remove_node(conv_node->id());
}
else
{
- ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution with batch normalization due to the presence of an output accessor\n");
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE(
+ "Prevented fusion of convolution with batch normalization due to the presence of an output accessor\n");
}
}
@@ -162,14 +165,17 @@ void fuse_depthwise_convolution_with_batch_normalization(Graph &g, const Edge *o
{
ARM_COMPUTE_ERROR_ON(output_edge == nullptr);
- auto *depth_conv_node = arm_compute::utils::cast::polymorphic_downcast<DepthwiseConvolutionLayerNode *>(output_edge->producer());
- auto *bn_node = arm_compute::utils::cast::polymorphic_downcast<BatchNormalizationLayerNode *>(output_edge->consumer());
+ auto *depth_conv_node =
+ arm_compute::utils::cast::polymorphic_downcast<DepthwiseConvolutionLayerNode *>(output_edge->producer());
+ auto *bn_node =
+ arm_compute::utils::cast::polymorphic_downcast<BatchNormalizationLayerNode *>(output_edge->consumer());
- ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing depthwise convolution node with ID : " << output_edge->producer_id()
- << " with BatchNormalization Layer node with ID : " << output_edge->consumer_id() << std::endl);
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing depthwise convolution node with ID : "
+ << output_edge->producer_id() << " with BatchNormalization Layer node with ID : "
+ << output_edge->consumer_id() << std::endl);
// Prevent fusion if fused node has an output accessor
- if(depth_conv_node->output(0)->accessor() == nullptr)
+ if (depth_conv_node->output(0)->accessor() == nullptr)
{
const Target assigned_target = depth_conv_node->assigned_target();
@@ -189,9 +195,10 @@ void fuse_depthwise_convolution_with_batch_normalization(Graph &g, const Edge *o
const auto epsilon = bn_node->epsilon();
// Create the fused node
- const NodeID fused_id = g.add_node<FusedDepthwiseConvolutionBatchNormalizationNode>(epsilon, conv_info, depth_multiplier, depth_conv_method, act_info);
+ const NodeID fused_id = g.add_node<FusedDepthwiseConvolutionBatchNormalizationNode>(
+ epsilon, conv_info, depth_multiplier, depth_conv_method, act_info);
- if(depth_conv_node->input_edge(2) != nullptr)
+ if (depth_conv_node->input_edge(2) != nullptr)
{
const auto conv_bias_id = depth_conv_node->input_edge(2)->producer_id();
g.add_connection(conv_bias_id, 0, fused_id, 2);
@@ -211,19 +218,23 @@ void fuse_depthwise_convolution_with_batch_normalization(Graph &g, const Edge *o
transfer_driving_nodes_and_remove_old_node(g, fused_node, bn_node, true);
fused_node->set_assigned_target(assigned_target);
- fused_node->set_common_node_parameters(NodeParams{ depth_conv_node->name() + "+" + bn_node_name, assigned_target });
+ fused_node->set_common_node_parameters(
+ NodeParams{depth_conv_node->name() + "+" + bn_node_name, assigned_target});
// Remove convolution node
g.remove_node(depth_conv_node->id());
}
else
{
- ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of depthwise convolution with batch normalization due to the presence of an output accessor\n");
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of depthwise convolution with batch normalization due to the "
+ "presence of an output accessor\n");
}
}
template <typename N>
-void fuse_node_with_activation(Graph &g, const Edge *output_edge, const std::set<Activation> &supported_fused_activations)
+void fuse_node_with_activation(Graph &g,
+ const Edge *output_edge,
+ const std::set<Activation> &supported_fused_activations)
{
ARM_COMPUTE_ERROR_ON(output_edge == nullptr);
@@ -233,22 +244,23 @@ void fuse_node_with_activation(Graph &g, const Edge *output_edge, const std::set
ARM_COMPUTE_ERROR_ON(act_node->output(0) == nullptr || n_node->output(0) == nullptr);
// Check if activation is supported for fusion
- if(supported_fused_activations.count(act_node->activation_info().activation()) == 0)
+ if (supported_fused_activations.count(act_node->activation_info().activation()) == 0)
{
return;
}
// EltwiseLayerNode can only be fused when dataype is float
- if(n_node->type() == NodeType::EltwiseLayer && !is_data_type_float(n_node->output(0)->desc().data_type))
+ if (n_node->type() == NodeType::EltwiseLayer && !is_data_type_float(n_node->output(0)->desc().data_type))
{
return;
}
ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing node with ID : " << output_edge->producer_id()
- << " with Activation Layer node with ID : " << output_edge->consumer_id() << std::endl);
+ << " with Activation Layer node with ID : "
+ << output_edge->consumer_id() << std::endl);
// Prevent fusion if fused node has an output accessor
- if(n_node->output(0)->accessor() == nullptr)
+ if (n_node->output(0)->accessor() == nullptr)
{
// Set activation info to fused node
n_node->set_fused_activation(act_node->activation_info());
@@ -257,7 +269,8 @@ void fuse_node_with_activation(Graph &g, const Edge *output_edge, const std::set
}
else
{
- ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of node with activation due to the presence of an output accessor\n");
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE(
+ "Prevented fusion of node with activation due to the presence of an output accessor\n");
}
}
@@ -268,8 +281,8 @@ void fuse_pad_with_convolution(Graph &g, const Edge *output_edge)
auto *conv_node = arm_compute::utils::cast::polymorphic_downcast<N *>(output_edge->consumer());
const Edge *input_edge = pad_node->input_edge(0);
- if(input_edge != nullptr && input_edge->tensor() != nullptr && pad_node->output(0)->accessor() == nullptr
- && pad_node->pad_value().get<float>() == 0.0)
+ if (input_edge != nullptr && input_edge->tensor() != nullptr && pad_node->output(0)->accessor() == nullptr &&
+ pad_node->pad_value().get<float>() == 0.0)
{
const DataLayout layout = input_edge->tensor()->desc().layout;
const PaddingList padding_list = pad_node->padding();
@@ -280,18 +293,14 @@ void fuse_pad_with_convolution(Graph &g, const Edge *output_edge)
const PaddingInfo pad_w = width_index < padding_list.size() ? padding_list[width_index] : PaddingInfo(0, 0);
const PaddingInfo pad_h = height_index < padding_list.size() ? padding_list[height_index] : PaddingInfo(0, 0);
- if(is_padding_in_height_or_width(layout, padding_list))
+ if (is_padding_in_height_or_width(layout, padding_list))
{
// Add paddings to the convolution node
const PadStrideInfo conv_info = conv_node->convolution_info();
- const PadStrideInfo new_conv_info(
- conv_info.stride().first,
- conv_info.stride().second,
- conv_info.pad_left() + pad_w.first,
- conv_info.pad_right() + pad_w.second,
- conv_info.pad_top() + pad_h.first,
- conv_info.pad_bottom() + pad_h.second,
- conv_info.round());
+ const PadStrideInfo new_conv_info(conv_info.stride().first, conv_info.stride().second,
+ conv_info.pad_left() + pad_w.first, conv_info.pad_right() + pad_w.second,
+ conv_info.pad_top() + pad_h.first, conv_info.pad_bottom() + pad_h.second,
+ conv_info.round());
conv_node->set_convolution_info(new_conv_info);
// Update drivers of the convolution node
@@ -299,7 +308,7 @@ void fuse_pad_with_convolution(Graph &g, const Edge *output_edge)
g.remove_node(pad_node->id());
// Update fused node inputs
- for(auto &driver_node : pad_driver_nodes)
+ for (auto &driver_node : pad_driver_nodes)
{
g.add_connection(driver_node.node_id, driver_node.index, conv_node->id(), 0);
}
@@ -308,22 +317,23 @@ void fuse_pad_with_convolution(Graph &g, const Edge *output_edge)
}
template <typename N1, typename N2, typename F, typename... Args>
-void fuse_layer(Graph &g, std::function<bool(INode &)> const &prec, const F fuse_fcn, Args &&... optional_arguments)
+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)
+ 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)
+ 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 a type N2 node
- if((output_edge != nullptr) && (output_edge->consumer() != nullptr) && (output_edge->consumer()->type() == N2::node_type) && prec(*output_edge->producer()))
+ 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...);
}
@@ -332,22 +342,22 @@ void fuse_layer(Graph &g, std::function<bool(INode &)> const &prec, const F fuse
}
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)
+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)
+ 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)
+ 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()))
+ if ((output_edge != nullptr) && (output_edge->consumer() != nullptr) && prec(*output_edge->producer()))
{
fuse_fcn(g, output_edge, i, optional_arguments...);
}
@@ -369,30 +379,24 @@ IGraphMutator::MutationType NodeFusionMutator::type() const
void NodeFusionMutator::mutate(Graph &g)
{
// Supported activations when fusing
- const std::set<Activation> supported_fused_activations = { Activation::ABS, Activation::BOUNDED_RELU, Activation::ELU,
- Activation::HARD_SWISH, Activation::IDENTITY, Activation::LEAKY_RELU,
- Activation::LINEAR, Activation::LOGISTIC, Activation::LU_BOUNDED_RELU,
- Activation::RELU, Activation::SOFT_RELU, Activation::SQRT,
- Activation::SQUARE, Activation::TANH
- };
+ const std::set<Activation> supported_fused_activations = {
+ Activation::ABS, Activation::BOUNDED_RELU, Activation::ELU,
+ Activation::HARD_SWISH, Activation::IDENTITY, Activation::LEAKY_RELU,
+ Activation::LINEAR, Activation::LOGISTIC, Activation::LU_BOUNDED_RELU,
+ Activation::RELU, Activation::SOFT_RELU, Activation::SQRT,
+ Activation::SQUARE, Activation::TANH};
// Preconditions
- auto empty_prec = [](INode &)
- {
- return true;
- };
- auto cl_target_prec = [](INode & n)
- {
- return n.assigned_target() == Target::CL;
- };
- auto qs8_prec = [&g](INode & n)
+ auto empty_prec = [](INode &) { return true; };
+ auto cl_target_prec = [](INode &n) { return n.assigned_target() == Target::CL; };
+ auto qs8_prec = [&g](INode &n)
{
ARM_COMPUTE_ERROR_ON(n.output(0) == nullptr);
const auto output_edge_id = *n.output_edges().begin();
const auto output_edge = g.edge(output_edge_id);
// To perform fusion the two nodes must have same output quantization information
- const bool same_qinfo = n.output(0)->desc().quant_info == output_edge->producer()->output(0)->desc().quant_info;
+ const bool same_qinfo = n.output(0)->desc().quant_info == output_edge->producer()->output(0)->desc().quant_info;
const bool output_qasymm8 = n.output(0)->desc().data_type == DataType::QASYMM8;
return (output_qasymm8 && same_qinfo) || !output_qasymm8;
@@ -400,16 +404,25 @@ void NodeFusionMutator::mutate(Graph &g)
// Fusion mutations
- 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<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<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<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);
// The fusion of BatchNormalizationLayer must occur after the fusion of ActivationLayer. Because FusedConvolutionBatchNormalizationNode assumes the BatchNormalization is already fused with activation, if any
- 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);
+ 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
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-19 22:36:38 +0000