ONE - On-device Neural Engine
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luci::XpSepActFromTransposeConvPass Struct Referencefinal

Experimental Class to separate activation functions from TransposeConv. More...

#include <XpSepActFromTransposeConvPass.h>

Collaboration diagram for luci::XpSepActFromTransposeConvPass:

Public Member Functions

const char * name (void) const final
 
bool run (loco::Graph *g) final
 Run the pass.
 
- Public Member Functions inherited from logo::Pass
virtual ~Pass ()=default
 

Detailed Description

Experimental Class to separate activation functions from TransposeConv.

Definition at line 28 of file XpSepActFromTransposeConvPass.h.

Member Function Documentation

◆ name()

const char * luci::XpSepActFromTransposeConvPass::name ( void  ) const
inlinefinalvirtual

Reimplemented from logo::Pass.

Definition at line 30 of file XpSepActFromTransposeConvPass.h.

30{ return "luci::XpSepActFromTransposeConvPass"; }

◆ run()

bool luci::XpSepActFromTransposeConvPass::run ( loco::Graph graph)
finalvirtual

Run the pass.

Returns
false if there was nothing changed

Implements logo::Pass.

Definition at line 111 of file XpSepActFromTransposeConvPass.cpp.

112{
113 bool changed = false;
114 for (auto node : loco::active_nodes(loco::output_nodes(g)))
115 {
116 auto trconv = dynamic_cast<luci::CircleTransposeConv *>(node);
117 if (trconv != nullptr)
118 {
119 if (separate_activation_fuction(trconv))
120 changed = true;
121 }
122 }
123
124 return changed;
125}
TRANSPOSE_CONV in Circle.
std::set< loco::Node * > active_nodes(const std::vector< loco::Node * > &roots)
Enumerate all the nodes required to compute "roots".
std::vector< Node * > output_nodes(Graph *)
Definition Graph.cpp:101

References loco::active_nodes(), and loco::output_nodes().

Referenced by package.infer.session::inference().


The documentation for this struct was generated from the following files: