[Feature Request] use Onnxruntime TensorRT execution provider with lean tensorRT runtime

### Describe the feature request

I am doing an inference with Onnxruntime TensorRT Execution Provider by loading a tensorRT cached model that was generated previously with the libnvinfer_builder_resource.so from an original. onnx model
So I don't need anymore at runtime the huge 1GB+ libnvinfer_builder_resource.so and I can deply my onnxruntime environnement without it (tested).

Also I would like not to deploy 230MB libnvinfer.so either but 30MB libnvinfer_lean.so instead (NVDIA TensorRT says it is possible if we don't build _the tensorrt model anymore (quoting https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html :
We provide the possibility to install TensorRT in three different modes:
A full installation of TensorRT, including TensorRT plan file builder functionality. This mode is the same as the runtime provided before TensorRT 8.6.0.
A lean runtime installation is significantly smaller than the full installation. It allows you to load and run engines built with a version-compatible builder flag. However, this installation does not provide the functionality to build a TensorRT plan file.
A dispatch runtime installation. This installation allows for deployments with minimum memory consumption. It allows you to load and run engines built with a version compatible with the builder flag and includes the lean runtime. However, it does not provide the functionality to build a TensorRT plan file._

However , when I am redirecting libnvinfer.so to libnvinfer_lean.so as advised , then I am getting an error from Onnxruntime TensorRT Execution Provider
terminate called after throwing an instance of 'Ort::Exception'
what(): /tmp/onnxruntime/onnxruntime/core/session/provider_bridge_ort.cc:1419 onnxruntime::Provider& onnxruntime::ProviderLibrary::Get() [ONNXRuntimeError] : 1 : FAIL : Failed to load library libonnxruntime_providers_tensorrt.so with error: /usr/local/lib/libonnxruntime_providers_tensorrt.so: undefined symbol: createInferBuilder_INTERNAL

Am I making some error or is Onnxruntime TRT EP currently not capable of using libnvinfer_lean only instead of libnvinfer ?. In the last case adding this improvement in ORT would be nice when trying to reduce the Onnxrutime gpu image footprint

### Describe scenario use case

Build a trt cached model from an onnx model with libnvinfer_builder_resource.so deployed
then deploy the onnxrt and the TRT cached model in an environment where now lbvinfer.so points to lbvinfer_lean and without libnvinfer_builder_resource.so is removed
then load the cached model from onnxrt TRT EP : the model should be loaded and the infered with lbvinfer_lean.so only

ORT version 1.18.1 on Linux SLES15 compiled with GCC11 and flag --use_tensorrt_oss_parser as in build command
CC=gcc-11 CXX=g++-11 ./build.sh \
--skip_submodule_sync --nvcc_threads 2 \
--config $ORT_BUILD_MODE --use_cuda \
--cudnn_home /usr/local/cuda/lib64 \
--cuda_home /usr/local/cuda/ --use_tensorrt \
--use_tensorrt_oss_parser --tensorrt_home /usr/local/TensorRT \
--build_shared_lib --parallel --skip_tests \
--allow_running_as_root --cmake_extra_defines "CMAKE_CUDA_ARCHITECTURES=75" \
--cmake_extra_defines "CMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-11"

Cuda version 12.4
Cudnn 8.9.7.29
TRT 8.6.1

Review the TensorRT provider loading path at onnxruntime/core/session/provider_bridge_ort.cc:1419 and the TensorRT EP build configuration described in the issue. Reproduce the cached-engine deployment with TensorRT 8.6.1, then define completion as loading and running the cached model with libnvinfer_lean.so without libnvinfer_builder_resource.so.

Written by the indexing model from the issue text.