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Added exp layer

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backport of commit: 6111935835
partial backport of commit: dd5976162b
This commit is contained in:
SamFC10
2021-02-20 22:16:00 +05:30
committed by Alexander Alekhin
parent 19f1bac18c
commit 96947c30c0
8 changed files with 173 additions and 2 deletions
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modules/dnn/src/layers/elementwise_layers.cpp
+113
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@@ -1202,6 +1202,105 @@ struct PowerFunctor : public BaseFunctor
int64 getFLOPSPerElement() const { return power == 1 ? 2 : 10; }
};
struct ExpFunctor : public BaseFunctor
{
typedef ExpLayer Layer;
float base, scale, shift;
float normScale, normShift;
ExpFunctor(float base_ = -1.f, float scale_ = 1.f, float shift_ = 0.f)
: base(base_), scale(scale_), shift(shift_)
{
// For base > 0 :
// y = base^(scale * input + shift)
// ln(y) = ln(base)*(scale * input + shift)
// y = exp((ln(base)*scale) * input + (ln(base)*shift))
// y = exp(normalized_scale * input + normalized_shift)
CV_Check(base, base == -1.f || base > 0.f, "Unsupported 'base' value");
const float ln_base = (base == -1.f) ? 1.f : log(base);
normScale = scale * ln_base;
normShift = shift * ln_base;
}
bool supportBackend(int backendId, int targetId)
{
return backendId == DNN_BACKEND_OPENCV ||
backendId == DNN_BACKEND_HALIDE || backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH;
}
void apply(const float* srcptr, float* dstptr, int len, size_t planeSize, int cn0, int cn1) const
{
float a = normScale, b = normShift;
for( int cn = cn0; cn < cn1; cn++, srcptr += planeSize, dstptr += planeSize )
{
for( int i = 0; i < len; i++ )
{
float x = srcptr[i];
dstptr[i] = exp(a*x + b);
}
}
}
#ifdef HAVE_OPENCL
bool applyOCL(InputArrayOfArrays inps, OutputArrayOfArrays outs, OutputArrayOfArrays internals)
{
std::vector<UMat> inputs;
std::vector<UMat> outputs;
inps.getUMatVector(inputs);
outs.getUMatVector(outputs);
String buildopt = oclGetTMacro(inputs[0]);
for (size_t i = 0; i < inputs.size(); i++)
{
UMat& src = inputs[i];
UMat& dst = outputs[i];
ocl::Kernel kernel("ExpForward", ocl::dnn::activations_oclsrc, buildopt);
kernel.set(0, (int)src.total());
kernel.set(1, ocl::KernelArg::PtrReadOnly(src));
kernel.set(2, ocl::KernelArg::PtrWriteOnly(dst));
kernel.set(3, (float)normScale);
kernel.set(4, (float)normShift);
size_t gSize = src.total();
CV_Assert(kernel.run(1, &gSize, NULL, false));
}
return true;
}
#endif
#ifdef HAVE_HALIDE
void attachHalide(const Halide::Expr& input, Halide::Func& top)
{
Halide::Var x("x"), y("y"), c("c"), n("n");
top(x, y, c, n) = exp(normScale * input + normShift);
}
#endif // HAVE_HALIDE
#ifdef HAVE_DNN_IE_NN_BUILDER_2019
InferenceEngine::Builder::Layer initInfEngineBuilderAPI()
{
CV_Error(Error::StsNotImplemented, "");
}
#endif // HAVE_DNN_IE_NN_BUILDER_2019
#ifdef HAVE_DNN_NGRAPH
std::shared_ptr<ngraph::Node> initNgraphAPI(const std::shared_ptr<ngraph::Node>& node)
{
auto scale_node = std::make_shared<ngraph::op::Constant>(ngraph::element::f32,
ngraph::Shape{1}, &normScale);
auto shift_node = std::make_shared<ngraph::op::Constant>(ngraph::element::f32,
ngraph::Shape{1}, &normShift);
auto mul = std::make_shared<ngraph::op::v1::Multiply>(scale_node, node, ngraph::op::AutoBroadcastType::NUMPY);
auto scale_shift = std::make_shared<ngraph::op::v1::Add>(mul, shift_node, ngraph::op::AutoBroadcastType::NUMPY);
return std::make_shared<ngraph::op::v0::Exp>(scale_shift);
}
#endif // HAVE_DNN_NGRAPH
int64 getFLOPSPerElement() const { return 3; }
};
struct ChannelsPReLUFunctor : public BaseFunctor
{
typedef ChannelsPReLULayer Layer;
@@ -1419,6 +1518,20 @@ Ptr<PowerLayer> PowerLayer::create(const LayerParams& params)
return l;
}
Ptr<ExpLayer> ExpLayer::create(const LayerParams& params)
{
float base = params.get<float>("base", -1.0f);
float scale = params.get<float>("scale", 1.0f);
float shift = params.get<float>("shift", 0.0f);
Ptr<ExpLayer> l(new ElementWiseLayer<ExpFunctor>(ExpFunctor(base, scale, shift)));
l->setParamsFrom(params);
l->base = base;
l->scale = scale;
l->shift = shift;
return l;
}
Ptr<Layer> ChannelsPReLULayer::create(const LayerParams& params)
{
CV_Assert(params.blobs.size() == 1);