tensorrt_rtx try on

[lanluo-nvidia]

Description

Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.

Fixes # (issue)

Type of change

Please delete options that are not relevant and/or add your own.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Checklist:

• My code follows the style guidelines of this project (You can use the linters)
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas and hacks
• I have made corresponding changes to the documentation
• I have added tests to verify my fix or my feature
• New and existing unit tests pass locally with my changes
• I have added the relevant labels to my PR in so that relevant reviewers are notified

[github-actions]

There are some changes that do not conform to C++ style guidelines:

diff --git a/home/runner/work/TensorRT/TensorRT/cpp/bin/torchtrtc/main.cpp b/tmp/changes.txt
index 60c76da..63e4448 100644
--- a/home/runner/work/TensorRT/TensorRT/cpp/bin/torchtrtc/main.cpp
+++ b/tmp/changes.txt
@@ -374,7 +374,9 @@ int main(int argc, char** argv) {
        // } else {
        //   torchtrt::logging::log(
        //       torchtrt::logging::Level::kINFO,
-        //       "Int8 precision has been enabled but no calibrator provided. This assumes the network has Q/DQ nodes obtained from Quantization aware training. For more details, refer to https://docs.nvidia.com/deeplearning/tensorrt/developer-guide/index.html#work-with-qat-networks");
+        //       "Int8 precision has been enabled but no calibrator provided. This assumes the network has Q/DQ nodes
+        //       obtained from Quantization aware training. For more details, refer to
+        //       https://docs.nvidia.com/deeplearning/tensorrt/developer-guide/index.html#work-with-qat-networks");
        // }
      } else {
        std::stringstream ss;
diff --git a/home/runner/work/TensorRT/TensorRT/core/conversion/conversionctx/ConversionCtx.cpp b/tmp/changes.txt
index c821698..9fdcac7 100644
--- a/home/runner/work/TensorRT/TensorRT/core/conversion/conversionctx/ConversionCtx.cpp
+++ b/tmp/changes.txt
@@ -59,16 +59,16 @@ ConversionCtx::ConversionCtx(BuilderSettings build_settings)
  for (auto p = settings.enabled_precisions.begin(); p != settings.enabled_precisions.end(); ++p) {
    switch (*p) {
      case nvinfer1::DataType::kHALF:
-        // tensorrt_rtx is strong typed, cannot set fp16 by builder config, only do this for tensorrt build
-        #ifndef TRT_MAJOR_RTX
+// tensorrt_rtx is strong typed, cannot set fp16 by builder config, only do this for tensorrt build
+#ifndef TRT_MAJOR_RTX
        TORCHTRT_CHECK(
            builder->platformHasFastFp16(), "Requested inference in FP16 but platform does not support FP16");
        cfg->setFlag(nvinfer1::BuilderFlag::kFP16);
        break;
-        #endif
+#endif
      case nvinfer1::DataType::kINT8:
-        // tensorrt_rtx is strong typed, cannot set int8 by builder config, only do this for tensorrt build
-        #ifndef TRT_MAJOR_RTX
+// tensorrt_rtx is strong typed, cannot set int8 by builder config, only do this for tensorrt build
+#ifndef TRT_MAJOR_RTX
        TORCHTRT_CHECK(
            builder->platformHasFastInt8(), "Requested inference in INT8 but platform does not support INT8");
        cfg->setFlag(nvinfer1::BuilderFlag::kINT8);
@@ -81,7 +81,7 @@ ConversionCtx::ConversionCtx(BuilderSettings build_settings)
          cfg->setInt8Calibrator(settings.calibrator);
        }
        break;
-        #endif
+#endif
      case nvinfer1::DataType::kFLOAT:
        break;
      case nvinfer1::DataType::kINT32:
ERROR: Some files do not conform to style guidelines

[github-actions]

There are some changes that do not conform to Python style guidelines:

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/__init__.py	2025-07-11 22:54:04.884045+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/__init__.py	2025-07-11 22:54:29.748057+00:00
@@ -42,12 +42,13 @@

import torch

try:
    from . import trt_alias  # noqa: F401
- 
+
    import tensorrt  # noqa: F401
+
    print(f"You are using {tensorrt.__name__=} {tensorrt.__version__=}")
except ImportError:
    tensorrt_version = _parse_semver(__tensorrt_version__)
    tensorrt_rtx_version = _parse_semver(__tensorrt_rtx_version__)

--- /home/runner/work/TensorRT/TensorRT/setup.py	2025-07-11 22:54:04.902045+00:00
+++ /home/runner/work/TensorRT/TensorRT/setup.py	2025-07-11 22:54:34.510910+00:00
@@ -548,11 +548,17 @@
            tensorrt_linux_external_dir = tensorrt_x86_64_external_dir

    if USE_RTX:
        tensorrt_windows_external_dir = (
            lambda: subprocess.check_output(
-                [BAZEL_EXE, "query", "@tensorrt_rtx_win//:nvinfer", "--output", "location"]
+                [
+                    BAZEL_EXE,
+                    "query",
+                    "@tensorrt_rtx_win//:nvinfer",
+                    "--output",
+                    "location",
+                ]
            )
            .decode("ascii")
            .strip()
            .split("/BUILD.bazel")[0]
        )