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fix(tests): correct TensorRT-RTX deconv version gate and guard plugin-backed converter tests #4467

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fix(tests): correct TensorRT-RTX deconv version gate and guard plugin-backed converter tests #4467

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5d8493d
fix(conversion): allow grouped and dilated deconv on TensorRT-RTX
tp5uiuc Aug 7, 2026
9375394
test: guard plugin-backed converter tests on TensorRT-RTX
tp5uiuc Aug 7, 2026
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4 changes: 3 additions & 1 deletion core/conversion/converters/impl/conv_deconv.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -294,7 +294,9 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
deconv->setStrideNd(stride);
deconv->setPrePadding(begPadding);
deconv->setPostPadding(padding);
#if NV_TENSORRT_MAJOR > 7 || (NV_TENSORRT_MAJOR == 7 && NV_TENSORRT_MINOR >= 1)
// TensorRT-RTX reports NV_TENSORRT_MAJOR == 1, so the plain version comparison below would
// select the pre-7.1 fallback and reject grouped or dilated deconvolutions that RTX supports.
#if defined(TRT_MAJOR_RTX) || NV_TENSORRT_MAJOR > 7 || (NV_TENSORRT_MAJOR == 7 && NV_TENSORRT_MINOR >= 1)
deconv->setDilationNd(dilation);
deconv->setNbGroups(groups);
#else
Expand Down
9 changes: 9 additions & 0 deletions tests/core/conversion/converters/test_instance_norm.cpp
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Expand Up @@ -28,6 +28,13 @@ constexpr auto graph = R"IR(
return (%4)
)IR";

// The aten::instance_norm converter is implemented with a TensorRT plugin, which TensorRT-RTX
// does not provide, so aten::instance_norm is left unregistered for RTX builds (see
// core/conversion/converters/impl/batch_norm.cpp). All three tests below share the same
// aten::instance_norm graph, so all three are guarded -- the first two additionally carry an
// unconditional GTEST_SKIP() that is unrelated to RTX.
#ifndef TRT_MAJOR_RTX

TEST(Converters, ATenInstanceNormConvertsCorrectly) {
GTEST_SKIP();
auto g = std::make_shared<torch::jit::Graph>();
Expand Down Expand Up @@ -103,3 +110,5 @@ TEST(Converters, ATenInstanceNormRunningStatsConvertsCorrectly) {
auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {trt_in});
ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0])));
}

#endif // TRT_MAJOR_RTX
6 changes: 6 additions & 0 deletions tests/core/conversion/converters/test_normalize.cpp
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Expand Up @@ -43,6 +43,11 @@
ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt)); \
}

// The aten::norm converter is implemented with a TensorRT plugin, which TensorRT-RTX does not
// provide, so it is compiled out for RTX builds (see
// core/conversion/converters/impl/normalize.cpp). The aten::frobenius_norm and
// aten::linalg_norm tests below do not use that converter and are left enabled.
#ifndef TRT_MAJOR_RTX
ATEN_INTERPOLATE_TESTS(
ATenNormOrder1RemoveDims,
R"IR(
Expand Down Expand Up @@ -75,6 +80,7 @@ ATEN_INTERPOLATE_TESTS(
%5 : Tensor = aten::norm(%x.1, %3, %2, %4)
return (%5))IR",
std::vector<int64_t>({3, 4, 3}));
#endif // TRT_MAJOR_RTX

TEST(Converters, ATenFrobeniusNorm) {
const auto graph = R"IR(
Expand Down
8 changes: 8 additions & 0 deletions tests/core/conversion/converters/test_pooling.cpp
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Expand Up @@ -410,6 +410,12 @@ TEST(Converters, ATenAvgPool3DNoCountPadConvertsCorrectly) {
ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0]));
}

// The adaptive pooling converters are implemented with TensorRT plugins, which TensorRT-RTX
// does not provide, so they are compiled out for RTX builds (see
// core/conversion/converters/impl/pooling.cpp). Without this guard every test below fails
// conversion with "Expected converter to be true but got false".
#ifndef TRT_MAJOR_RTX

TEST(Converters, ATenAdaptiveAvgPool2DConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor):
Expand Down Expand Up @@ -781,3 +787,5 @@ TEST(Converters, ATenAdaptiveMaxPool3DUsingPluginConvertsCorrectly) {

ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0]));
}

#endif // TRT_MAJOR_RTX
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