diff --git a/include/aidge/operator/MetaOperatorDefs.hpp b/include/aidge/operator/MetaOperatorDefs.hpp
index 5bb184b808e0a9d685879e53554ff3be500f5717..1214f918624fe02940ba6c6476a1940d09556510 100644
--- a/include/aidge/operator/MetaOperatorDefs.hpp
+++ b/include/aidge/operator/MetaOperatorDefs.hpp
@@ -200,6 +200,48 @@ PaddedAvgPooling(DimSize_t const (&kernel_dims)[DIM],
////////////////////////////////////////////////////////////////////////////////
+template <std::array<DimSize_t, 1>::size_type DIM>
+extern std::shared_ptr<Node> PaddedConvTranspose(
+ const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
+ const std::array<DimSize_t, DIM> &kernelDims,
+ const std::array<DimSize_t, DIM> &strideDims =
+ create_array<DimSize_t,DIM>(1),
+ const std::array<DimSize_t, DIM> &dilationDims =
+ create_array<DimSize_t,DIM>(1),
+ const bool noBias = false,
+ const std::array<DimSize_t, 2*DIM> &paddingDims =
+ create_array<DimSize_t,2*DIM>(0),
+ const std::string& name = "");
+
+template <std::array<DimSize_t, 1>::size_type DIM>
+extern std::shared_ptr<Node> PaddedConvTranspose(const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
+ DimSize_t const (&kernel_dims)[DIM],
+ const std::array<DimSize_t, DIM> &strideDims =
+ create_array<DimSize_t,DIM>(1),
+ const std::array<DimSize_t, DIM> &dilationDims =
+ create_array<DimSize_t,DIM>(1),
+ const bool noBias = false,
+ const std::array<DimSize_t, 2*DIM> &paddingDims =
+ create_array<DimSize_t,2*DIM>(0),
+ const std::string& name = "");
+
+template <std::array<DimSize_t, 1>::size_type DIM>
+extern std::shared_ptr<MetaOperator_Op> PaddedConvTranspose_Op(const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
+ const std::array<DimSize_t, DIM> &kernelDims,
+ const std::array<DimSize_t, DIM> &strideDims =
+ create_array<DimSize_t,DIM>(1),
+ const std::array<DimSize_t, DIM> &dilationDims =
+ create_array<DimSize_t,DIM>(1),
+ const bool noBias = false,
+ const std::array<DimSize_t, 2*DIM> &paddingDims =
+ create_array<DimSize_t,2*DIM>(0),
+ const std::string& name = "");
+
+////////////////////////////////////////////////////////////////////////////////
+
/**
* @brief Creates a padded max pooling operation.
*
diff --git a/python_binding/operator/pybind_MetaOperatorDefs.cpp b/python_binding/operator/pybind_MetaOperatorDefs.cpp
index b2811fbaab2b6cd33dc2b105f0044cd8a5edbbc7..9ad80dd6d2b2b8396796833f978a066c6b1503c8 100644
--- a/python_binding/operator/pybind_MetaOperatorDefs.cpp
+++ b/python_binding/operator/pybind_MetaOperatorDefs.cpp
@@ -14,9 +14,7 @@
#include <string>
#include <vector>
-#include <array>
-#include "aidge/backend/OperatorImpl.hpp"
#include "aidge/operator/MetaOperatorDefs.hpp"
#include "aidge/utils/Types.h"
@@ -106,6 +104,71 @@ template <DimIdx_t DIM> void declare_PaddedConvDepthWiseOp(py::module &m) {
}
+template <DimIdx_t DIM> void declare_PaddedConvTransposeOp(py::module &m) {
+ m.def(("PaddedConvTranspose" + std::to_string(DIM) + "D").c_str(), [](const DimSize_t &in_channels,
+ const DimSize_t &out_channels,
+ const std::vector<DimSize_t>& kernel_dims,
+ const std::vector<DimSize_t> &stride_dims,
+ const std::vector<DimSize_t> &dilation_dims,
+ const bool no_bias,
+ const std::vector<DimSize_t> &padding_dims,
+ const std::string& name)
+ {
+ AIDGE_ASSERT(kernel_dims.size() == DIM, "kernel_dims size [{}] does not match DIM [{}]", kernel_dims.size(), DIM);
+ AIDGE_ASSERT(stride_dims.size() == DIM, "stride_dims size [{}] does not match DIM [{}]", stride_dims.size(), DIM);
+ AIDGE_ASSERT(dilation_dims.size() == DIM, "dilation_dims size [{}] does not match DIM [{}]", dilation_dims.size(), DIM);
+ AIDGE_ASSERT(padding_dims.size() == 2*DIM, "padding_dims size [{}] does not match DIM [{}]", padding_dims.size(), 2*DIM);
+
+ return PaddedConvTranspose<DIM>(in_channels,
+ out_channels,
+ to_array<DIM>(kernel_dims.begin()),
+ to_array<DIM>(stride_dims.begin()),
+ to_array<DIM>(dilation_dims.begin()),
+ no_bias,
+ to_array<2*DIM>(padding_dims.begin()),
+ name);
+ }, py::arg("in_channels"),
+ py::arg("out_channels"),
+ py::arg("kernel_dims"),
+ py::arg("stride_dims") = std::vector<DimSize_t>(DIM,1),
+ py::arg("dilation_dims") = std::vector<DimSize_t>(DIM,1),
+ py::arg("no_bias")= false,
+ py::arg("padding_dims") = std::vector<DimSize_t>(2*DIM,0),
+ py::arg("name") = "");
+ m.def(("PaddedConvTranspose" + std::to_string(DIM) + "DOp").c_str(), [](
+ const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
+ const std::vector<DimSize_t>& kernel_dims,
+ const std::vector<DimSize_t> &stride_dims,
+ const std::vector<DimSize_t> &dilation_dims,
+ const bool no_bias,
+ const std::vector<DimSize_t> &padding_dims,
+ const std::string &name)
+ {
+ AIDGE_ASSERT(kernel_dims.size() == DIM, "kernel_dims size [{}] does not match DIM [{}]", kernel_dims.size(), DIM);
+ AIDGE_ASSERT(stride_dims.size() == DIM, "stride_dims size [{}] does not match DIM [{}]", stride_dims.size(), DIM);
+ AIDGE_ASSERT(dilation_dims.size() == DIM, "dilation_dims size [{}] does not match DIM [{}]", dilation_dims.size(), DIM);
+ AIDGE_ASSERT(padding_dims.size() == 2*DIM, "padding_dims size [{}] does not match DIM [{}]", padding_dims.size(), 2*DIM);
+
+ return PaddedConvTranspose_Op<DIM>(inChannels,
+ outChannels,
+ to_array<DIM>(kernel_dims.begin()),
+ to_array<DIM>(stride_dims.begin()),
+ to_array<DIM>(dilation_dims.begin()),
+ no_bias,
+ to_array<2*DIM>(padding_dims.begin()),
+ name);
+ }, py::arg("in_channels"),
+ py::arg("out_channels"),
+ py::arg("kernel_dims"),
+ py::arg("stride_dims") = std::vector<DimSize_t>(DIM,1),
+ py::arg("dilation_dims") = std::vector<DimSize_t>(DIM,1),
+ py::arg("no_bias") = false,
+ py::arg("padding_dims") = std::vector<DimSize_t>(2*DIM,0),
+ py::arg("name") = "");
+}
+
+
template <DimIdx_t DIM> void declare_PaddedAvgPoolingOp(py::module &m) {
m.def(("PaddedAvgPooling" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& kernel_dims,
const std::string& name,
@@ -194,6 +257,8 @@ void init_MetaOperatorDefs(py::module &m) {
declare_PaddedConvDepthWiseOp<1>(m);
declare_PaddedConvDepthWiseOp<2>(m);
// declare_PaddedConvDepthWiseOp<3>(m);
+ declare_PaddedConvTransposeOp<1>(m);
+ declare_PaddedConvTransposeOp<2>(m);
// declare_PaddedAvgPoolingOp<1>(m);
declare_PaddedAvgPoolingOp<2>(m);
// declare_PaddedAvgPoolingOp<3>(m);
diff --git a/src/operator/MetaOperatorDefs/PaddedConvTranspose.cpp b/src/operator/MetaOperatorDefs/PaddedConvTranspose.cpp
index 7a9142c82ff28f075c80bc16afc4cdbd99526ac8..1d43e891ac73f53f2bad565584b805711b4d80d1 100644
--- a/src/operator/MetaOperatorDefs/PaddedConvTranspose.cpp
+++ b/src/operator/MetaOperatorDefs/PaddedConvTranspose.cpp
@@ -25,30 +25,29 @@
namespace Aidge {
-template <std::array<DimSize_t, 1>::size_type DIM>
+//////////////////////////////////
+// Node functions
+//////////////////////////////////
+
+template <std::array<DimIdx_t, 1>::size_type DIM>
std::shared_ptr<Node>
-PaddedConvTranspose(DimSize_t inChannels,
- DimSize_t outChannels,
+PaddedConvTranspose(const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
const std::array<DimSize_t, DIM> &kernelDims,
- const std::string &name,
const std::array<DimSize_t, DIM> &strideDims,
- const std::array<DimSize_t, 2 * DIM> &paddingDims,
const std::array<DimSize_t, DIM> &dilationDims,
- bool noBias) {
- // auto metaOp = PaddedConvTranspose_Op<DIM>(kernel_dims, stride_dims,
- // padding_dims, dilation_dims); if (!name.empty()) {
- // metaOp->getMicroGraph()->setName(name);
- // metaOp->getMicroGraph()->setNodesName();
- // }
- // auto metaOpNode = std::make_shared<Node>(metaOp, name);
+ const bool noBias,
+ const std::array<DimSize_t, 2 * DIM> &paddingDims,
+ const std::string &name) {
auto graph = Sequential(
{Pad<DIM>(paddingDims, (!name.empty()) ? name + "_pad" : ""),
- std::make_shared<Node>(
- std::make_shared<ConvTranspose_Op<static_cast<DimIdx_t>(DIM)>>(
- kernelDims,
- strideDims,
- dilationDims),
- (!name.empty()) ? name + "_conv" : "")});
+ ConvTranspose(inChannels,
+ outChannels,
+ kernelDims,
+ strideDims,
+ dilationDims,
+ noBias,
+ !name.empty() ? name + "_convTranspose" : "")});
auto metaOpNode = MetaOperator(
("PaddedConvTranspose" + std::to_string(DIM) + "D").c_str(),
graph,
@@ -63,95 +62,116 @@ PaddedConvTranspose(DimSize_t inChannels,
}
return metaOpNode;
}
+
template std::shared_ptr<Node>
-PaddedConvTranspose<1>(const DimSize_t,
- const DimSize_t,
+PaddedConvTranspose<1>(const DimSize_t &,
+ const DimSize_t &,
const std::array<DimSize_t, 1> &,
- const std::string &,
const std::array<DimSize_t, 1> &,
- const std::array<DimSize_t, 2> &,
const std::array<DimSize_t, 1> &,
- bool);
+ const bool,
+ const std::array<DimSize_t, 2> &,
+ const std::string &);
template std::shared_ptr<Node>
-PaddedConvTranspose<2>(const DimSize_t,
- const DimSize_t,
+PaddedConvTranspose<2>(const DimSize_t &,
+ const DimSize_t &,
const std::array<DimSize_t, 2> &,
- const std::string &,
const std::array<DimSize_t, 2> &,
+ const std::array<DimSize_t, 2> &,
+ const bool,
const std::array<DimSize_t, 4> &,
+ const std::string &);
+
+template <std::array<DimIdx_t, 1>::size_type DIM>
+extern std::shared_ptr<Node>
+PaddedConvTranspose(const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
+ DimSize_t const (&kernelDims)[DIM],
+ const std::array<DimSize_t, DIM> &strideDims,
+ const std::array<DimSize_t, DIM> &dilationDims,
+ const bool noBias,
+ const std::array<DimSize_t, 2 * DIM> &paddingDims,
+ const std::string &name) {
+ return PaddedConvTranspose<DIM>(inChannels,
+ outChannels,
+ to_array(kernelDims),
+ strideDims,
+ dilationDims,
+ noBias,
+ paddingDims,
+ name);
+}
+
+template std::shared_ptr<Node>
+PaddedConvTranspose<1>(const DimSize_t &,
+ const DimSize_t &,
+ DimSize_t const (&)[1],
+ const std::array<DimSize_t, 1> &,
+ const std::array<DimSize_t, 1> &,
+ const bool,
+ const std::array<DimSize_t, 2> &,
+ const std::string &);
+template std::shared_ptr<Node>
+PaddedConvTranspose<2>(const DimSize_t &,
+ const DimSize_t &,
+ const DimSize_t (&)[2],
+ const std::array<DimSize_t, 2> &,
const std::array<DimSize_t, 2> &,
- bool);
+ const bool,
+ const std::array<DimSize_t, 4> &,
+ const std::string &);
+
+//////////////////////////////////
+// Operator functions
+//////////////////////////////////
-template <std::array<DimSize_t, 1>::size_type DIM>
+template <std::array<DimIdx_t, 1>::size_type DIM>
std::shared_ptr<MetaOperator_Op>
-PaddedConvTranspose_Op(const std::array<DimSize_t, DIM> &kernelDims,
+PaddedConvTranspose_Op(const DimSize_t &inChannels,
+ const DimSize_t &outChannels,
+ const std::array<DimSize_t, DIM> &kernelDims,
const std::array<DimSize_t, DIM> &strideDims,
+ const std::array<DimSize_t, DIM> &dilationDims,
+ const bool noBias,
const std::array<DimSize_t, 2 * DIM> &paddingDims,
- const std::array<DimSize_t, DIM> &dilationDims) {
- auto pad = Pad<DIM>(paddingDims, "", PadBorderType::Constant, 0.0);
- auto conv = std::make_shared<Node>(
- std::make_shared<ConvTranspose_Op<static_cast<DimIdx_t>(DIM)>>(
- kernelDims,
- strideDims,
- dilationDims),
- "");
+ const std::string &name) {
+ auto pad = Pad<DIM>(paddingDims,
+ !name.empty() ? name + "_pad" : "pad",
+ PadBorderType::Constant,
+ 0.0);
+
+ auto convTranspose = ConvTranspose(
+ inChannels,
+ outChannels,
+ kernelDims,
+ strideDims,
+ dilationDims,
+ noBias,
+ !name.empty() ? name + "_convtranspose" : "convTranspose");
return std::make_shared<MetaOperator_Op>(
("PaddedConvTranspose" + std::to_string(DIM) + "D").c_str(),
- Sequential({pad, conv}));
+ Sequential({pad, convTranspose}));
}
template std::shared_ptr<MetaOperator_Op>
-PaddedConvTranspose_Op<1>(const std::array<DimSize_t, 1> &,
+PaddedConvTranspose_Op<1>(const DimSize_t &,
+ const DimSize_t &,
const std::array<DimSize_t, 1> &,
+ const std::array<DimSize_t, 1> &,
+ const std::array<DimSize_t, 1> &,
+ const bool,
const std::array<DimSize_t, 2> &,
- const std::array<DimSize_t, 1> &);
+ const std::string &);
+
template std::shared_ptr<MetaOperator_Op>
-PaddedConvTranspose_Op<2>(const std::array<DimSize_t, 2> &,
+PaddedConvTranspose_Op<2>(const DimSize_t &,
+ const DimSize_t &,
const std::array<DimSize_t, 2> &,
+ const std::array<DimSize_t, 2> &,
+ const std::array<DimSize_t, 2> &,
+ const bool,
const std::array<DimSize_t, 4> &,
- const std::array<DimSize_t, 2> &);
-
-// helper with C-style array instead of std::array for kernel_dims to allow
-// automatic template DIM deduction
-template <DimSize_t DIM>
-std::shared_ptr<Node>
-PaddedConvTranspose(DimSize_t inChannels,
- DimSize_t outChannels,
- DimSize_t const (&kernelDims)[DIM],
- const std::string &name,
- const std::array<DimSize_t, DIM> &strideDims,
- const std::array<DimSize_t, 2 * DIM> &paddingDims,
- const std::array<DimSize_t, DIM> &dilationDims,
- bool noBias) {
- return PaddedConvTranspose(inChannels,
- outChannels,
- to_array(kernelDims),
- name,
- strideDims,
- paddingDims,
- dilationDims,
- noBias);
-}
-
-template std::shared_ptr<Node>
-PaddedConvTranspose<1>(const DimSize_t,
- const DimSize_t,
- const DimSize_t (&)[1],
- const std::string &,
- const std::array<DimSize_t, 1> &,
- const std::array<DimSize_t, 2> &,
- const std::array<DimSize_t, 1> &,
- bool);
-
-template std::shared_ptr<Node>
-PaddedConvTranspose<2>(const DimSize_t,
- const DimSize_t,
- const DimSize_t (&)[2],
- const std::string &,
- const std::array<DimSize_t, 2> &,
- const std::array<DimSize_t, 4> &,
- const std::array<DimSize_t, 2> &,
- bool);
+ const std::string &);
} // namespace Aidge