refactor! : Update Pytorch version to 1.10

BREAKING CHANGE: This commit updates the pytorch version to 1.10. To use python API of torch_tensorrt, please upgrade your local pytorch to 1.10 to avoid ABI incompatibility errors. WORKSPACE and requirements files are updated accordingly Signed-off-by: Dheeraj Peri <peri.dheeraj@gmail.com> Signed-off-by: Dheeraj Peri <peri.dheeraj@gmail.com>
pytorch · Nov 3, 2021 · cc7d0b7 · cc7d0b7
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Showing 9 changed files with 17 additions and 18 deletions.
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
@@ -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/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
@@ -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.
 

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/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/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