feat(//core/conversion/converters/impl): added support for aten::stack

Signed-off-by: Abhiram Iyer <abhirami@nvidia.com>

Signed-off-by: Abhiram Iyer <abhi.iyer.ai@gmail.com>

core/conversion/converters/BUILD

@@ -29,7 +29,8 @@ cc_library(
         "impl/softmax.cpp",
         "impl/unary.cpp",
         "impl/interpolate.cpp",
-        "impl/select.cpp"
+        "impl/select.cpp",
+        "impl/stack.cpp"
     ],
     deps = [
         "@tensorrt//:nvinfer",

core/conversion/converters/impl/stack.cpp

@@ -0,0 +1,64 @@
+#include "torch/torch.h"
+#include "core/util/prelude.h"
+#include "core/conversion/converters/converters.h"
+#include "core/conversion/tensorcontainer/TensorContainer.h"
+#include "NvInfer.h"
+
+#include <ATen/ATen.h>
+#include <vector>
+
+namespace trtorch {
+namespace core {
+namespace conversion {
+namespace converters {
+namespace impl {
+namespace {
+
+auto stack_registrations TRTORCH_UNUSED = RegisterNodeConversionPatterns()
+    .pattern({
+        "aten::stack(Tensor[] tensors, int dim=0) -> (Tensor)",
+        [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
+            auto in = args[0].IValue()->toListRef();
+            auto dim = args[1].unwrapToInt();
+
+            std::vector<nvinfer1::ITensor*> tensors; 
+
+            for (auto t : in) {
+                nvinfer1::ITensor* itensor;
+
+                if (t.isTensor()) {
+                    auto weight = Weights(ctx, t.toTensor());
+
+                    auto const_layer = ctx->net->addConstant(weight.shape, weight.data);
+                    TRTORCH_CHECK(const_layer, "Unable to create constant layer from node: " << *n);
+
+                    itensor = const_layer->getOutput(0);
+                } else {
+                    auto cont = t.toCustomClass<TensorContainer>();
+                    itensor = cont->tensor();
+                }
+
+                auto shuffle_layer = ctx->net->addShuffle(*itensor);
+                TRTORCH_CHECK(shuffle_layer, "Unable to create shuffle layer from node: " << *n);
+                shuffle_layer->setReshapeDimensions(util::unsqueezeDims(itensor->getDimensions(), dim));
+
+                tensors.push_back(shuffle_layer->getOutput(0));
+            }
+
+            auto concat_layer = ctx->net->addConcatenation(tensors.data(), tensors.size());
+            TRTORCH_CHECK(concat_layer, "Unable to create concatenation layer from node: " << *n);
+            concat_layer->setAxis(static_cast<int>(dim));
+            auto out = ctx->AssociateValueAndTensor(n->outputs()[0], concat_layer->getOutput(0));
+
+            LOG_DEBUG("Output tensor shape: " << out->getDimensions());
+
+            return true;
+        }
+    });
+
+} // namespace
+} // namespace impl
+} // namespace converters
+} // namespace conversion
+} // namespace core
+} // namespace trtorch