Merge branch 'rebased_1.10_update' into 'release/1.0'

narendasan · narendasan · commit 87f1506114fa · 2021-11-08T15:11:29.000-08:00
refactor! : Update Pytorch version to 1.10

See merge request adlsa/TRTorch!18
diff --git a/.bazelversion b/.bazelversion
@@ -1 +1 @@
-4.0.0
+4.2.1
diff --git a/README.md b/README.md
@@ -96,7 +96,7 @@ torch.jit.save(trt_ts_module, "trt_torchscript_module.ts")
 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 4.0.0
-- Libtorch 1.9.1 (built with CUDA 11.1)
+- Libtorch 1.10.0 (built with CUDA 11.3)
 - CUDA 11.1 (10.2 on Jetson)
 - cuDNN 8.2
 - TensorRT 8.0.3.4 (TensorRT 8.0.1.6 on Jetson)
diff --git a/WORKSPACE b/WORKSPACE
@@ -41,7 +41,7 @@ local_repository(
 new_local_repository(
     name = "cuda",
     build_file = "@//third_party/cuda:BUILD",
-    path = "/usr/local/cuda-11.1/",
+    path = "/usr/local/cuda-11.3/",
 )
 
 new_local_repository(
@@ -56,17 +56,17 @@ new_local_repository(
 http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "db57b1023fb33768286a98ba22c44cfe03d6ed158bc2dc0ca1d4928ee5f19f60",
+    sha256 = "190e963e739d5f7c2dcf94b3994de8fcd335706a4ebb333812ea7d8c841beb06",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/cu111/libtorch-cxx11-abi-shared-with-deps-1.9.1%2Bcu111.zip"],
+    urls = ["https://download.pytorch.org/libtorch/cu113/libtorch-cxx11-abi-shared-with-deps-1.10.0%2Bcu113.zip"],
 )
 
 http_archive(
     name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "5563ca53b2b5342f1ab7eef9baf308f197673663ad5b1458a031c46dd802f413",
+    sha256 = "0996a6a4ea8bbc1137b4fb0476eeca25b5efd8ed38955218dec1b73929090053",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/cu111/libtorch-shared-with-deps-1.9.1%2Bcu111.zip"],
+    urls = ["https://download.pytorch.org/libtorch/cu113/libtorch-shared-with-deps-1.10.0%2Bcu113.zip"],
 )
 
 # Download these tarballs manually from the NVIDIA website
diff --git a/core/lowering/register_trt_placeholder_ops.cpp b/core/lowering/register_trt_placeholder_ops.cpp
@@ -12,7 +12,7 @@ RegisterOperators trt_placeholder_ops_reg({
     /// to a TRT constant Tensor
     Operator(
         "trt::const(Tensor val) -> Tensor",
-        [](Stack* stack) {},
+        [](Stack& stack) {/*noop*/},
         aliasAnalysisFromSchema()),
 });
 
diff --git a/docker/WORKSPACE.docs b/docker/WORKSPACE.docs
@@ -52,17 +52,17 @@ new_local_repository(
 http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "db57b1023fb33768286a98ba22c44cfe03d6ed158bc2dc0ca1d4928ee5f19f60",
+    sha256 = "190e963e739d5f7c2dcf94b3994de8fcd335706a4ebb333812ea7d8c841beb06",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/cu111/libtorch-cxx11-abi-shared-with-deps-1.9.1%2Bcu111.zip"],
+    urls = ["https://download.pytorch.org/libtorch/cu113/libtorch-cxx11-abi-shared-with-deps-1.10.0%2Bcu113.zip"],
 )
 
 http_archive(
     name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "5563ca53b2b5342f1ab7eef9baf308f197673663ad5b1458a031c46dd802f413",
+    sha256 = "0996a6a4ea8bbc1137b4fb0476eeca25b5efd8ed38955218dec1b73929090053",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/cu111/libtorch-shared-with-deps-1.9.1%2Bcu111.zip"],
+    urls = ["https://download.pytorch.org/libtorch/cu113/libtorch-shared-with-deps-1.10.0%2Bcu113.zip"],
 )
 
 ####################################################################################
@@ -99,4 +99,3 @@ pip3_import(
 
 load("@py_test_deps//:requirements.bzl", "pip_install")
 pip_install()
-
diff --git a/docsrc/tutorials/installation.rst b/docsrc/tutorials/installation.rst
@@ -52,7 +52,7 @@ Torch-TensorRT is built with Bazel, so begin by installing it.
 
     .. code-block:: shell
 
-        export BAZEL_VERSION=$(cat <PATH_TO_TRTORCH_ROOT>/.bazelversion)
+        export BAZEL_VERSION=$(cat <PATH_TO_TORCHTRT_ROOT>/.bazelversion)
         mkdir bazel
         cd bazel
         curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-dist.zip
@@ -66,7 +66,7 @@ the CUDA driver installed and the container must have CUDA)
 
 The correct LibTorch version will be pulled down for you by bazel.
 
-    NOTE: For best compatability with official PyTorch, use torch==1.9.1+cuda111, TensorRT 8.0 and cuDNN 8.2 for CUDA 11.1 however Torch-TensorRT itself supports
+    NOTE: For best compatability with official PyTorch, use torch==1.10.0+cuda113, TensorRT 8.0 and cuDNN 8.2 for CUDA 11.3 however Torch-TensorRT itself supports
     TensorRT and cuDNN for CUDA versions other than 11.1 for usecases such as using NVIDIA compiled distributions of PyTorch that use other versions of CUDA
     e.g. aarch64 or custom compiled version of PyTorch.
 
@@ -237,7 +237,7 @@ Install or compile a build of PyTorch/LibTorch for aarch64
 
 NVIDIA hosts builds the latest release branch for Jetson here:
 
-    https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-9-0-now-available/72048
+    https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-10-now-available/72048
 
 
 Enviorment Setup
diff --git a/examples/int8/training/vgg16/requirements.txt b/examples/int8/training/vgg16/requirements.txt
@@ -1,3 +1,3 @@
-torch>=1.9.1
+torch>=1.10.0
 tensorboard>=1.14.0
 pytorch-quantization --extra-index-url https://pypi.ngc.nvidia.com
diff --git a/py/Dockerfile b/py/Dockerfile
@@ -1,8 +1,8 @@
-FROM pytorch/manylinux-cuda111
+FROM pytorch/manylinux-cuda113
 
 RUN yum install -y ninja-build
 
-RUN wget https://copr.fedorainfracloud.org/coprs/vbatts/bazel/repo/epel-7/vbatts-bazel-epel-7.repo \
+RUN wget --no-check-certificate https://copr.fedorainfracloud.org/coprs/vbatts/bazel/repo/epel-7/vbatts-bazel-epel-7.repo \
     && mv vbatts-bazel-epel-7.repo /etc/yum.repos.d/
 
 RUN yum install -y bazel4 --nogpgcheck
diff --git a/py/build_whl.sh b/py/build_whl.sh
@@ -2,7 +2,7 @@
 
 # Example usage: docker run -it -v$(pwd)/..:/workspace/TRTorch build_trtorch_wheel /bin/bash /workspace/TRTorch/py/build_whl.sh
 
-cd /workspace/TRTorch/py
+cd /workspace/Torch-TensorRT/py
 
 export CXX=g++
 
diff --git a/py/requirements.txt b/py/requirements.txt
@@ -1,3 +1,3 @@
 -f https://download.pytorch.org/whl/torch_stable.html
-torch==1.9.1+cu111
-pybind11==2.6.2
+torch==1.10.0+cu113
+pybind11==2.6.2
diff --git a/py/setup.py b/py/setup.py
@@ -249,7 +249,7 @@ def run(self):
     long_description=long_description,
     ext_modules=ext_modules,
     install_requires=[
-        'torch>=1.9.0<1.11.0',
+        'torch>=1.10.0<1.11.0',
     ],
     setup_requires=[],
     cmdclass={
diff --git a/tests/core/conversion/converters/test_activation.cpp b/tests/core/conversion/converters/test_activation.cpp
@@ -200,13 +200,10 @@ TEST(Converters, ATenEluConvertsCorrectly) {
   ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0], 2e-6));
 }
 
-#ifndef DISABLE_TEST_IN_CI
-
 TEST(Converters, ATenGELUConvertsCorrectly) {
   const auto graph = R"IR(
       graph(%0 : Tensor):
-        %1 : bool = prim::Constant[value=0]()
-        %3 : Tensor = aten::gelu(%0, %1)
+        %3 : Tensor = aten::gelu(%0)
         return (%3))IR";
 
   auto g = std::make_shared<torch::jit::Graph>();
@@ -226,6 +223,5 @@ TEST(Converters, ATenGELUConvertsCorrectly) {
   // c10::cuda::compat::normcdf to compute Phi(x). So there's a difference here and therefore the threshold is slightly
   // higher than other ops. One in ten runs will give you an out of normal threshold result
 
-  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0], 5e-3));
+  ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0], 5e-2));
 }
-#endif
diff --git a/tests/modules/requirements.txt b/tests/modules/requirements.txt
@@ -1,3 +1,3 @@
 -f https://download.pytorch.org/whl/torch_stable.html
 timm==v0.4.12
-torch==1.9.1+cu111
+torch==1.10.0+cu113
diff --git a/tests/py/requirements.txt b/tests/py/requirements.txt
@@ -1,2 +1,2 @@
-torchvision==0.10.1+cu111
--f https://download.pytorch.org/whl/torch_stable.html
+torchvision==0.11.1+cu113
+-f https://download.pytorch.org/whl/torch_stable.html
