Merge pull request #549 from NVIDIA/cat_neg_dim

fix(aten::cat): support neg dim for cat

Author: narendasan

core/conversion/converters/impl/concat.cpp

@@ -20,15 +20,17 @@ auto cat_registrations TRTORCH_UNUSED = RegisterNodeConversionPatterns()
               for (auto t : ts) {
                 if (t.isTensor()) {
                   auto torch_tensor = t.toTensor();
-                  auto t_weights = Weights(ctx, torch_tensor);
-                  auto const_layer = ctx->net->addConstant(t_weights.shape, t_weights.data);
-                  tensors.push_back(const_layer->getOutput(0));
+                  tensors.push_back(tensor_to_const(ctx, torch_tensor));
                 } else {
                   auto cont = t.toCustomClass<TensorContainer>();
                   tensors.push_back(cont->tensor());
                 }
               }
 
+              if (dim < 0) {
+                dim = tensors[0]->getDimensions().nbDims + dim;
+              }
+
               auto cat_layer = ctx->net->addConcatenation(tensors.data(), tensors.size());
               cat_layer->setAxis(static_cast<int>(dim));
               auto cat_out = ctx->AssociateValueAndTensor(n->outputs()[0], cat_layer->getOutput(0));

tests/core/conversion/converters/test_concat.cpp

@@ -49,5 +49,52 @@ TEST(Converters, ATenCatDiffTensorConvertsCorrectly) {
   params = trtorch::core::conversion::get_named_params(g->inputs(), {in2});
   auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {in1});
 
+  ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
+}
+TEST(Converters, ATenCatPureTensorNegDimConvertsCorrectly) {
+  const auto graph = R"IR(
+      graph(%0 : Tensor,
+            %1 : Tensor):
+        %2 : Tensor[] = prim::ListConstruct(%0, %1)
+        %3 : int = prim::Constant[value=-1]()
+        %4 : Tensor = aten::cat(%2, %3)
+        return (%4))IR";
+
+  auto g = std::make_shared<torch::jit::Graph>();
+  torch::jit::parseIR(graph, g.get());
+
+  auto in1 = at::randint(1, 10, {5, 5}, {at::kCUDA});
+  auto in2 = at::randint(1, 10, {5, 5}, {at::kCUDA});
+
+  auto params = trtorch::core::conversion::get_named_params(g->inputs(), {});
+  auto jit_results = trtorch::tests::util::RunGraph(g, params, {in1, in2});
+
+  params = trtorch::core::conversion::get_named_params(g->inputs(), {});
+  auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {in1, in2});
+
+  ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
+}
+
+TEST(Converters, ATenCatDiffTensorNegDimConvertsCorrectly) {
+  const auto graph = R"IR(
+      graph(%0 : Tensor,
+            %1 : Float(5)):
+        %2 : Tensor[] = prim::ListConstruct(%0, %1)
+        %3 : int = prim::Constant[value=-1]()
+        %4 : Tensor = aten::cat(%2, %3)
+        return (%4))IR";
+
+  auto g = std::make_shared<torch::jit::Graph>();
+  torch::jit::parseIR(graph, g.get());
+
+  auto in1 = at::randint(1, 10, {5, 5}, {at::kCUDA});
+  auto in2 = at::randint(1, 10, {5, 5}, {at::kCUDA});
+
+  auto params = trtorch::core::conversion::get_named_params(g->inputs(), {in2});
+  auto jit_results = trtorch::tests::util::RunGraph(g, params, {in1});
+
+  params = trtorch::core::conversion::get_named_params(g->inputs(), {in2});
+  auto trt_results = trtorch::tests::util::RunGraphEngine(g, params, {in1});
+
   ASSERT_TRUE(trtorch::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
 }