feat!: TensorRT RTX 1.5 support (#105)

* fix: replace inline default destructors

* depds: add TRT RTX 1.5 headers

* feat!: add support for TRT RTX 1.5 and make it the default

* ci: test TRT RTX 1.5

Author: theHamsta

.github/workflows/ci.yml

@@ -74,7 +74,7 @@ jobs:
         shell: bash
         run: |
           # 1.3 is not on pip, only starting with 1.4
-          pip install tensorrt_rtx~=1.4
+          pip install tensorrt_rtx~=1.5
           RTX_LIB_DIR=$(python -c 'from os.path import dirname;print(dirname(__import__("tensorrt_rtx_libs").__file__))')
           echo "RTX_LIB_DIR=$RTX_LIB_DIR"
           echo "RTX_LIB_DIR=$RTX_LIB_DIR" >> $GITHUB_ENV
@@ -84,8 +84,8 @@ jobs:
         if: ${{ matrix.os == 'ubuntu-latest' }}
         shell: bash
         run: |
-          ln -s $RTX_LIB_DIR/libtensorrt_rtx.so.1{,.4.0}
-          ln -s $RTX_LIB_DIR/libtensorrt_onnxparser_rtx.so.1{,.4.0}
+          ln -s $RTX_LIB_DIR/libtensorrt_rtx.so.1{,.5.0}
+          ln -s $RTX_LIB_DIR/libtensorrt_onnxparser_rtx.so.1{,.5.0}
 
       - name: Check formatting
         run: cargo fmt --all -- --check
@@ -114,6 +114,10 @@ jobs:
 
       - name: Run tests (mock mode old TensorRT versions)
         run: |
+          # v_1_4
+          cargo test -F mock -F v_1_4 -F dlopen_tensorrt_rtx -F dlopen_tensorrt_onnxparser --no-default-features --verbose
+          cargo check -F v_1_4 -F dlopen_tensorrt_rtx -F dlopen_tensorrt_onnxparser --no-default-features --verbose
+          # v_1_3
           cargo test -F mock -F v_1_3 -F dlopen_tensorrt_rtx -F dlopen_tensorrt_onnxparser --no-default-features --verbose
           cargo check -F v_1_3 -F dlopen_tensorrt_rtx -F dlopen_tensorrt_onnxparser --no-default-features --verbose
           # onnxparser disabled

README.md

@@ -54,7 +54,7 @@ Use `TENSORRT_SDK_DIR` to point to the TensorRT SDK root directory (the path tha
 1. **NVIDIA TensorRT-RTX**: Download and install from [NVIDIA Developer](https://developer.nvidia.com/tensorrt)
      - The TensorRT libraries should be in a location where they can be dynamically loaded.
        (e.g. by setting PATH on Windows or LD_LIBRARY_PATH on Linux)
-     - This crate currently requires TensorRT RTX version 1.3 or 1.4 (see Cargo feature `v_1_3`, `v_1_4`).
+     - This crate currently requires TensorRT RTX version 1.3, 1.4 or 1.5 (see Cargo feature `v_1_3`, `v_1_4`, `v_1_5`).
        Use `default-features = false` plus version feature to select version.
        You will also have to either enable `dlopen_tensorrt_rtx` or `link_tensorrt_rtx`.
 
@@ -88,7 +88,7 @@ Mock mode provides stub implementations that allow you to:
 
 The `trtx` crate has the following Cargo features:
 
-- `default`: "dlopen_tensorrt_onnxparser", "dlopen_tensorrt_rtx", "onnxparser", "v_1_4"
+- `default`: "dlopen_tensorrt_onnxparser", "dlopen_tensorrt_rtx", "onnxparser", "v_1_5"
 - `mock`: use this library in mock mode. TensorRT libraries and a Nvidia GPU are no longer necessary for execution
 - `mock_runtime`: only mock runtime features of TensorRT. TensorRT libraries are required, but GPU execution is mocked (no GPU or CUDA required).
 - `dlopen_tensorrt_rtx`: enables dynamic loading of the TensorRT library via `trtx::dynamically_load_tensorrt`
@@ -99,6 +99,7 @@ The `trtx` crate has the following Cargo features:
   but using the builder library instead
 - `v_1_3` + `default-features = false` + (`dlopen_tensorrt_rtx` or `link_tensorrt_rtx`): Uses TensorRT RTX versions 1.3. At least one version feature has to be enabled
 - `v_1_4` + `default-features = false` + (`dlopen_tensorrt_rtx` or `link_tensorrt_rtx`): Uses TensorRT RTX versions 1.4. At least one version feature has to be enabled
+- `v_1_5` + `default-features = false` + (`dlopen_tensorrt_rtx` or `link_tensorrt_rtx`): Uses TensorRT RTX versions 1.5. At least one version feature has to be enabled
 
 ## Installation
 

trtx-sys/Cargo.toml

@@ -18,14 +18,15 @@ cc = "1.0"
 regex = "1.0"
 
 [features]
-default = ["v_1_4"]
+default = ["v_1_5"]
 onnxparser = []
 link_tensorrt_rtx = []
 link_tensorrt_onnxparser = ["onnxparser"]
 
 # versions
 v_1_3 = []
-v_1_4 = []
+v_1_4 = ["v_1_3"]
+v_1_5 = ["v_1_4"]
 # the non-RTX version of TensorRT (mainly for debugging/validating TensorRT RTX)
 enterprise = []