Merge branch 'main' into swin_unet

Author: peri044

.bazelrc

@@ -22,7 +22,7 @@
 # +------------------------------------------------------------+
 # Enable colorful output of GCC
 build --cxxopt="-fdiagnostics-color=always"
-build --cxxopt='-std=c++14'
+build --cxxopt='-std=c++17'
 #build --linkopt="-Wl,--no-as-needed"
 
 

.circleci/config.yml

@@ -269,10 +269,10 @@ commands:
     parameters:
       torch-build:
         type: string
-        default: "2.1.0.dev20230419+cu118"
+        default: "2.1.0.dev20230605+cu118"
       torchvision-build:
         type: string
-        default: "0.16.0.dev20230419+cu118"
+        default: "0.16.0.dev20230605+cu118"
       torch-build-index:
         type: string
         default: "https://download.pytorch.org/whl/nightly/cu118"
@@ -1352,10 +1352,10 @@ parameters:
   # Nightly platform config
   torch-build:
     type: string
-    default: "2.1.0.dev20230419+cu118"
+    default: "2.1.0.dev20230605+cu118"
   torchvision-build:
     type: string
-    default: "0.16.0.dev20230419+cu118"
+    default: "0.16.0.dev20230605+cu118"
   torch-build-index:
     type: string
     default: "https://download.pytorch.org/whl/nightly/cu118"

CMakeLists.txt

@@ -2,8 +2,8 @@
 cmake_minimum_required(VERSION 3.17)
 project(Torch-TensorRT LANGUAGES CXX)
 
-# use c++14 like PyTorch
-set(CMAKE_CXX_STANDARD 14)
+# use c++17 like PyTorch
+set(CMAKE_CXX_STANDARD 17)
 
 # Build the libraries with -fPIC
 set(CMAKE_POSITION_INDEPENDENT_CODE ON)

README.md

@@ -116,7 +116,7 @@ torch.jit.save(trt_ts_module, "trt_torchscript_module.ts") # save the TRT embedd
 These are the following dependencies used to verify the testcases. Torch-TensorRT can work with other versions, but the tests are not guaranteed to pass.
 
 - Bazel 5.2.0
-- Libtorch 2.1.0.dev20230419 (built with CUDA 11.8)
+- Libtorch 2.1.0.dev20230605 (built with CUDA 11.8)
 - CUDA 11.8
 - cuDNN 8.8.0
 - TensorRT 8.6.1

WORKSPACE

@@ -51,17 +51,17 @@ new_local_repository(
 http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "1a526a9cd19c1015674d26921dbb94bcd2d632a6f9c431a21c43f4e24768d834",
+    sha256 = "999becce82b73e566d0ffe010cd21fea8cf3a33f90f09dcc6b01150b820ae063",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu118/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230419%2Bcu118.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu118/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230605%2Bcu118.zip"],
 )
 
 http_archive(
     name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "60c5912a5085a6a7073b3804b10d41d6cc054693bbeb7a45e0247050c2837bac",
+    sha256 = "786cc728c63ea69c40bd8fb535cf8e5e1dfff1d43eaad3eb5256b9ed89c1b268",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu118/libtorch-shared-with-deps-2.1.0.dev20230419%2Bcu118.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu118/libtorch-shared-with-deps-2.1.0.dev20230605%2Bcu118.zip"],
 )
 
 # Download these tarballs manually from the NVIDIA website

core/runtime/TRTEngine.cpp

@@ -111,7 +111,7 @@ TRTEngine::TRTEngine(
     for (size_t pyt_idx = 0; pyt_idx < inputs_size; pyt_idx++) {
       auto binding_name = _in_binding_names[pyt_idx];
       auto trt_idx = cuda_engine->getBindingIndex(binding_name.c_str());
-      std::string engine_binded_name = cuda_engine->getIOTensorName(pyt_idx);
+      std::string engine_binded_name = cuda_engine->getIOTensorName(trt_idx);
       TORCHTRT_CHECK(
           (binding_name == engine_binded_name),
           "Could not find a TensorRT engine binding for input named " << binding_name);