Fix more URLs (#153277)

Or ignore them.
Found by running the lint_urls.sh script locally with https://github.com/pytorch/pytorch/pull/153246

Pull Request resolved: https://github.com/pytorch/pytorch/pull/153277
Approved by: https://github.com/malfet

.ci/caffe2/README.md

@@ -10,5 +10,3 @@ example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
 built on Jenkins and are used in triggered builds already have this
 environment variable set in their manifest. Also see
 `./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
-
-Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

.ci/docker/centos-rocm/Dockerfile

@@ -17,9 +17,8 @@ RUN bash ./install_base.sh && rm install_base.sh
 # Update CentOS git version
 RUN yum -y remove git
 RUN yum -y remove git-*
-RUN yum -y install https://packages.endpoint.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm || \
+RUN yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
-    (yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
+    sed -i 's/packages.endpoint/packages.endpointdev/' /etc/yum.repos.d/endpoint.repo
-    sed -i "s/packages.endpoint/packages.endpointdev/" /etc/yum.repos.d/endpoint.repo)
 RUN yum install -y git
 
 # Install devtoolset

.ci/docker/common/install_conda.sh

@@ -7,7 +7,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   BASE_URL="https://repo.anaconda.com/miniconda"
   CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
   if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
-    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
+    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"  # @lint-ignore
     CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
   fi
 

.ci/docker/common/install_cpython.sh

@@ -3,7 +3,7 @@
 set -uex -o pipefail
 
 PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python
-PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads
+PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads  # @lint-ignore
 GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
 
 # Python versions to be installed in /opt/$VERSION_NO

.ci/docker/manywheel/build_scripts/build.sh

@@ -97,7 +97,7 @@ find /opt/_internal -type f -print0 \
     | xargs -0 -n1 strip --strip-unneeded 2>/dev/null || true
 # We do not need the Python test suites, or indeed the precompiled .pyc and
 # .pyo files. Partially cribbed from:
-#    https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile
+#    https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile  # @lint-ignore
 find /opt/_internal \
      \( -type d -a -name test -o -name tests \) \
   -o \( -type f -a -name '*.pyc' -o -name '*.pyo' \) \

.ci/docker/manywheel/build_scripts/build_utils.sh

@@ -2,7 +2,7 @@
 # Helper utilities for build
 # Script used only in CD pipeline
 
-OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
+OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/  # @lint-ignore
 CURL_DOWNLOAD_URL=https://curl.se/download
 
 AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf

.ci/onnx/README.md

@@ -10,5 +10,3 @@ example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
 built on Jenkins and are used in triggered builds already have this
 environment variable set in their manifest. Also see
 `./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
-
-Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

.ci/pytorch/win-test-helpers/installation-helpers/install_magma.bat

@@ -24,7 +24,7 @@ if "%CUDA_SUFFIX%" == "" (
 
 if "%REBUILD%"=="" (
   if "%BUILD_ENVIRONMENT%"=="" (
-    curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --output %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z
+    curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --output %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z & REM @lint-ignore
   ) else (
     aws s3 cp s3://ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --quiet
   )

.ci/pytorch/windows/internal/7z_install.bat

@@ -1,6 +1,6 @@
 @echo off
 
-curl -k https://www.7-zip.org/a/7z1805-x64.exe -O
+curl -k -L "https://sourceforge.net/projects/sevenzip/files/7-Zip/18.05/7z1805-x64.exe/download" -o 7z1805-x64.exe
 if errorlevel 1 exit /b 1
 
 start /wait 7z1805-x64.exe /S

.ci/pytorch/windows/internal/clone.bat

@@ -8,7 +8,7 @@ goto submodule
 
 :clone_pytorch
 
-git clone https://github.com/%PYTORCH_REPO%/%MODULE_NAME%
+git clone https://github.com/%PYTORCH_REPO%/%MODULE_NAME% & REM @lint-ignore
 
 cd %MODULE_NAME%
 

.ci/pytorch/windows/internal/cuda_install.bat

@@ -35,7 +35,7 @@ exit /b 1
 
 set CUDA_INSTALL_EXE=cuda_11.8.0_522.06_windows.exe
 if not exist "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" (
-    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
+    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDA_SETUP_FILE=%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
     set "ARGS=cuda_profiler_api_11.8 thrust_11.8 nvcc_11.8 cuobjdump_11.8 nvprune_11.8 nvprof_11.8 cupti_11.8 cublas_11.8 cublas_dev_11.8 cudart_11.8 cufft_11.8 cufft_dev_11.8 curand_11.8 curand_dev_11.8 cusolver_11.8 cusolver_dev_11.8 cusparse_11.8 cusparse_dev_11.8 npp_11.8 npp_dev_11.8 nvrtc_11.8 nvrtc_dev_11.8 nvml_dev_11.8 nvtx_11.8"
@@ -45,7 +45,7 @@ set CUDNN_FOLDER=cudnn-windows-x86_64-9.5.0.50_cuda11-archive
 set CUDNN_LIB_FOLDER="lib"
 set "CUDNN_INSTALL_ZIP=%CUDNN_FOLDER%.zip"
 if not exist "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" (
-    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
+    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDNN_SETUP_FILE=%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
 )
@@ -62,7 +62,7 @@ goto cuda_common
 
 set CUDA_INSTALL_EXE=cuda_12.4.0_551.61_windows.exe
 if not exist "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" (
-    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
+    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDA_SETUP_FILE=%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
     set "ARGS=cuda_profiler_api_12.4 thrust_12.4 nvcc_12.4 cuobjdump_12.4 nvprune_12.4 nvprof_12.4 cupti_12.4 cublas_12.4 cublas_dev_12.4 cudart_12.4 cufft_12.4 cufft_dev_12.4 curand_12.4 curand_dev_12.4 cusolver_12.4 cusolver_dev_12.4 cusparse_12.4 cusparse_dev_12.4 npp_12.4 npp_dev_12.4 nvrtc_12.4 nvrtc_dev_12.4 nvml_dev_12.4 nvjitlink_12.4 nvtx_12.4"
@@ -72,7 +72,7 @@ set CUDNN_FOLDER=cudnn-windows-x86_64-9.5.0.50_cuda12-archive
 set CUDNN_LIB_FOLDER="lib"
 set "CUDNN_INSTALL_ZIP=%CUDNN_FOLDER%.zip"
 if not exist "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" (
-    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
+    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDNN_SETUP_FILE=%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
 )
@@ -89,7 +89,7 @@ goto cuda_common
 
 set CUDA_INSTALL_EXE=cuda_12.6.2_560.94_windows.exe
 if not exist "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" (
-    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
+    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDA_SETUP_FILE=%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
     set "ARGS=cuda_profiler_api_12.6 thrust_12.6 nvcc_12.6 cuobjdump_12.6 nvprune_12.6 nvprof_12.6 cupti_12.6 cublas_12.6 cublas_dev_12.6 cudart_12.6 cufft_12.6 cufft_dev_12.6 curand_12.6 curand_dev_12.6 cusolver_12.6 cusolver_dev_12.6 cusparse_12.6 cusparse_dev_12.6 npp_12.6 npp_dev_12.6 nvrtc_12.6 nvrtc_dev_12.6 nvml_dev_12.6 nvjitlink_12.6 nvtx_12.6"
@@ -99,7 +99,7 @@ set CUDNN_FOLDER=cudnn-windows-x86_64-9.5.0.50_cuda12-archive
 set CUDNN_LIB_FOLDER="lib"
 set "CUDNN_INSTALL_ZIP=%CUDNN_FOLDER%.zip"
 if not exist "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" (
-    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
+    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDNN_SETUP_FILE=%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
 )
@@ -116,7 +116,7 @@ goto cuda_common
 
 set CUDA_INSTALL_EXE=cuda_12.8.0_571.96_windows.exe
 if not exist "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" (
-    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
+    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDA_SETUP_FILE=%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
     set "ARGS=cuda_profiler_api_12.8 thrust_12.8 nvcc_12.8 cuobjdump_12.8 nvprune_12.8 nvprof_12.8 cupti_12.8 cublas_12.8 cublas_dev_12.8 cudart_12.8 cufft_12.8 cufft_dev_12.8 curand_12.8 curand_dev_12.8 cusolver_12.8 cusolver_dev_12.8 cusparse_12.8 cusparse_dev_12.8 npp_12.8 npp_dev_12.8 nvrtc_12.8 nvrtc_dev_12.8 nvml_dev_12.8 nvjitlink_12.8 nvtx_12.8"
@@ -126,7 +126,7 @@ set CUDNN_FOLDER=cudnn-windows-x86_64-9.7.0.66_cuda12-archive
 set CUDNN_LIB_FOLDER="lib"
 set "CUDNN_INSTALL_ZIP=%CUDNN_FOLDER%.zip"
 if not exist "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" (
-    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
+    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" & REM @lint-ignore
     if errorlevel 1 exit /b 1
     set "CUDNN_SETUP_FILE=%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
 )

.ci/pytorch/windows/internal/driver_update.bat

@@ -1,5 +1,5 @@
 set WIN_DRIVER_VN=528.89
-set "DRIVER_DOWNLOAD_LINK=https://ossci-windows.s3.amazonaws.com/%WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe"
+set "DRIVER_DOWNLOAD_LINK=https://ossci-windows.s3.amazonaws.com/%WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe" & REM @lint-ignore
 curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe
 if errorlevel 1 exit /b 1
 

.ci/pytorch/windows/internal/static_lib_test.bat

@@ -37,7 +37,7 @@ if "%DEBUG%" == "1" (
 if not "%CUDA_VERSION%" == "cpu" (
     rmdir /s /q magma_%CUDA_PREFIX%_%BUILD_TYPE%
     del magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z
-    curl -k https://s3.amazonaws.com/ossci-windows/magma_%MAGMA_VERSION%_%CUDA_PREFIX%_%BUILD_TYPE%.7z -o magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z
+    curl -k https://s3.amazonaws.com/ossci-windows/magma_%MAGMA_VERSION%_%CUDA_PREFIX%_%BUILD_TYPE%.7z -o magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z & REM @lint-ignore
     7z x -aoa magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z -omagma_%CUDA_PREFIX%_%BUILD_TYPE%
     set LIB=%CD%\magma_%CUDA_PREFIX%_%BUILD_TYPE%\lib;%LIB%
 )

.github/scripts/label_utils.py

@@ -45,7 +45,7 @@ def get_last_page_num_from_header(header: Any) -> int:
     # rel="next", <https://api.github.com/repositories/65600975/labels?per_page=100&page=3>; rel="last"
     link_info = header["link"]
     # Docs does not specify that it should be present for projects with just few labels
-    # And https://github.com/malfet/deleteme/actions/runs/7334565243/job/19971396887 it's not the case
+    # And https://github.com/malfet/deleteme/actions/runs/7334565243/job/19971396887 it's not the case  # @lint-ignore
     if link_info is None:
         return 1
     prefix = "&page="

.github/scripts/test_filter_test_configs.py

@@ -807,7 +807,7 @@ class TestConfigFilter(TestCase):
         # test bad things
         pr_body = (
             "fixes189 fixeshttps://github.com/pytorch/pytorch/issues/75123 "
-            "closedhttps://githubcom/pytorch/pytorch/issues/75123"
+            "closedhttps://githubcom/pytorch/pytorch/issues/75123"  # @lint-ignore
             "fix 234, fixes # 45, fixing #123, close 234, closes#45, closing #123 resolve 234, "
             "resolves  #45, resolving #123"
         )

.github/scripts/trymerge.py

@@ -2031,7 +2031,7 @@ def check_for_sev(org: str, project: str, skip_mandatory_checks: bool) -> None:
     response = cast(
         dict[str, Any],
         gh_fetch_json_list(
-            "https://api.github.com/search/issues",
+            "https://api.github.com/search/issues",  # @lint-ignore
             # Having two label: queries is an AND operation
             params={
                 "q": f'repo:{org}/{project} is:open is:issue label:"ci: sev" label:"merge blocking"'

.github/scripts/tryrebase.py

@@ -132,17 +132,17 @@ def rebase_ghstack_onto(
         # The contents of a successful push result should look like:
         # Summary of changes (ghstack 0.6.0)
 
-        #  - Updated https://github.com/clee2000/random-testing/pull/2
+        #  - Updated https://github.com/clee2000/random-testing-public/pull/2
-        #  - Updated https://github.com/clee2000/random-testing/pull/1
+        #  - Updated https://github.com/clee2000/random-testing-public/pull/1
 
         # Facebook employees can import your changes by running
         # (on a Facebook machine):
 
-        #     ghimport -s https://github.com/clee2000/random-testing/pull/2
+        #     ghimport -s https://github.com/clee2000/random-testing-public/pull/2
 
         # If you want to work on this diff stack on another machine:
 
-        #     ghstack checkout https://github.com/clee2000/random-testing/pull/2
+        #     ghstack checkout https://github.com/clee2000/random-testing-public/pull/2
         org, project = repo.gh_owner_and_name()
         for line in push_result.splitlines():
             if "Updated" in line:

.github/workflows/docker-builds.yml

@@ -128,7 +128,7 @@ jobs:
           docker-image: ${{ steps.build-docker-image.outputs.docker-image }}
 
       - uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0
-        name: Push to https://https://ghcr.io/
+        name: Push to https://ghcr.io/
         id: push-to-ghcr-io
         if: ${{ github.event_name == 'push' }}
         env:

CITATION.cff

@@ -113,4 +113,4 @@ preferred-citation:
   publisher:
     name: ACM
   doi: "10.1145/3620665.3640366"
-  url: "https://pytorch.org/assets/pytorch2-2.pdf"
+  url: "https://docs.pytorch.org/assets/pytorch2-2.pdf"

CONTRIBUTING.md

@@ -149,7 +149,7 @@ source venv/bin/activate  # or `& .\venv\Scripts\Activate.ps1` on Windows
 
   - If you encounter an error such as
     ```
-    fatal: unable to access 'https://github.com/pybind11/pybind11.git': could not load PEM client certificate ...
+    fatal: unable to access 'https://github.com/pybind/pybind11.git': could not load PEM client certificate ...
     ```
     this is likely that you are using HTTP proxying and the certificate expired. To check if the certificate is valid, run
     `git config --global --list` and search for config like `http.proxysslcert=<cert_file>`. Then check certificate valid date by running
@@ -434,7 +434,7 @@ PyTorch has two main types of documentation:
 These are the docs that you see over at [our docs website](https://pytorch.org/docs).
 - **Developer facing documentation**:
 Developer facing documentation is spread around our READMEs in our codebase and in
-the [PyTorch Developer Wiki](https://pytorch.org/wiki).
+the [PyTorch Developer Wiki](https://github.com/pytorch/pytorch/wiki).
 If you're interested in adding new developer docs, please read this [page on the wiki](https://github.com/pytorch/pytorch/wiki/Where-or-how-should-I-add-documentation) on our best practices for where to put it.
 
 The rest of this section is about user-facing documentation.
@@ -988,7 +988,7 @@ If you are working on the CUDA code, here are some useful CUDA debugging tips:
 3. CUDA supports a lot of C++11/14 features such as, `std::numeric_limits`, `std::nextafter`,
    `std::tuple` etc. in device code. Many of such features are possible because of the
    [--expt-relaxed-constexpr](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#constexpr-functions)
-   nvcc flag. There is a known [issue](https://github.com/ROCm-Developer-Tools/HIP/issues/374)
+   nvcc flag. There is a known [issue](https://github.com/ROCm/hip/issues/374)
    that ROCm errors out on device code, which uses such stl functions.
 4. A good performance metric for a CUDA kernel is the
    [Effective Memory Bandwidth](https://devblogs.nvidia.com/how-implement-performance-metrics-cuda-cc/).
@@ -1135,7 +1135,7 @@ CUDA, MSVC, and PyTorch versions are interdependent; please install matching ver
 | 10.2         | Visual Studio 2019 (16.X) (`_MSC_VER` < 1930)           |  1.5.0 ~ 1.7.0  |
 | 11.0         | Visual Studio 2019 (16.X) (`_MSC_VER` < 1930)           |      1.7.0      |
 
-Note: There's a [compilation issue](https://github.com/oneapi-src/oneDNN/issues/812) in several Visual Studio 2019 versions since 16.7.1, so please make sure your Visual Studio 2019 version is not in 16.7.1 ~ 16.7.5
+Note: There's a [compilation issue](https://github.com/uxlfoundation/oneDNN/issues/812) in several Visual Studio 2019 versions since 16.7.1, so please make sure your Visual Studio 2019 version is not in 16.7.1 ~ 16.7.5
 
 ## Pre-commit tidy/linting hook
 

README.md

@@ -502,7 +502,7 @@ To create the PDF:
 ### Previous Versions
 
 Installation instructions and binaries for previous PyTorch versions may be found
-on [our website](https://pytorch.org/previous-versions).
+on [our website](https://pytorch.org/get-started/previous-versions).
 
 
 ## Getting Started

cmake/Modules/FindNCCL.cmake

@@ -12,7 +12,7 @@
 #
 # The path hints include CUDA_TOOLKIT_ROOT_DIR seeing as some folks
 # install NCCL in the same location as the CUDA toolkit.
-# See https://github.com/caffe2/caffe2/issues/1601
+# See https://github.com/facebookarchive/caffe2/issues/1601
 
 set(NCCL_INCLUDE_DIR $ENV{NCCL_INCLUDE_DIR} CACHE PATH "Folder contains NVIDIA NCCL headers")
 set(NCCL_LIB_DIR $ENV{NCCL_LIB_DIR} CACHE PATH "Folder contains NVIDIA NCCL libraries")

docs/source/notes/autograd.rst

@@ -103,7 +103,7 @@ To try and reduce the impact of functions that are non-differentiable, we define
 #. If the function is not defined (``sqrt(-1)``, ``log(-1)`` or most functions when the input is ``NaN``, for example) then the value used as the gradient is arbitrary (we might also raise an error but that is not guaranteed). Most functions will use ``NaN`` as the gradient, but for performance reasons, some functions will use other values (``log(-1)``, for example).
 #. If the function is not a deterministic mapping (i.e. it is not a `mathematical function`_), it will be marked as non-differentiable. This will make it error out in the backward if used on tensors that require grad outside of a ``no_grad`` environment.
 
-.. _mathematical function: https://en.wikipedia.org/wiki/Function_(mathematics)
+.. _mathematical function: https://en.wikipedia.org/wiki/Function_%28mathematics%29
 
 .. _locally-disable-grad-doc:
 

test/functorch/test_eager_transforms.py

@@ -687,7 +687,7 @@ class TestGradTransform(TestCase):
         expected = (torch.zeros_like(x), torch.ones_like(x))
         self.assertEqual(result, expected)
 
-    # TODO: https://github.com/zou3519/functorch/issues/12
+    # TODO: https://github.com/pytorch/functorch/issues/12
     @onlyCPU
     def test_unrelated_hessian(self, device):
         N = 5

test/mobile/model_test/README.md

@@ -43,7 +43,7 @@ Python scripts in this folder are used to generate lite interpreter models for A
 
 The generated models are located at
 https://github.com/pytorch/pytorch/tree/master/android/pytorch_android/src/androidTest/assets (Android)
-https://github.com/pytorch/pytorch/tree/master/ios/TestApp/models/ (iOS)
+https://github.com/pytorch/pytorch/tree/master/ios/TestApp/models/ (iOS) <!-- @lint-ignore -->
 
 These test models will be executed in Android and iOS simulator tests. Note that we only check if there's error in model execution, but don't check the correctness of model output.
 

torch/ao/pruning/_experimental/data_sparsifier/benchmarks/README.md

@@ -8,7 +8,7 @@ The objective of this exercise is to use the data sparsifier to prune the embedd
 3. **Model forward time**: Can we speed up the model forward time by utilizing the sparsity? Specifically, can we introduce torch.sparse interim to reduce number of computations.
 
 ## Scope
-The [DataNormSparsifier](https://github.com/pytorch/pytorch/blob/master/torch/ao/sparsity/_experimental/data_sparsifier/data_norm_sparsifier.py) is used to sparsify the embeddings of the DLRM model. The model is sparsified for all the combinations of -
+The [DataNormSparsifier](https://github.com/pytorch/pytorch/blob/main/torch/ao/pruning/_experimental/data_sparsifier/data_norm_sparsifier.py) is used to sparsify the embeddings of the DLRM model. The model is sparsified for all the combinations of -
 1. Sparsity Levels: [0.0, 0.1, 0.2, ... 0.9, 0.91, 0.92, ... 0.99, 1.0]
 2. Sparse Block shapes: (1,1) and (1,4)
 3. Norm: L1 and L2

torch/utils/hipify/hipify_python.py

@@ -530,7 +530,7 @@ RE_EXTERN_SHARED = re.compile(r"extern\s+([\w\(\)]+)?\s*__shared__\s+([\w:<>\s]+
 
 def replace_extern_shared(input_string):
     """Match extern __shared__ type foo[]; syntax and use HIP_DYNAMIC_SHARED() MACRO instead.
-       https://github.com/ROCm-Developer-Tools/HIP/blob/master/docs/markdown/hip_kernel_language.md#__shared__
+       https://github.com/ROCm/hip/blob/master/docs/markdown/hip_kernel_language.md#__shared__
     Example:
         "extern __shared__ char smemChar[];" => "HIP_DYNAMIC_SHARED( char, smemChar)"
         "extern __shared__ unsigned char smem[];" => "HIP_DYNAMIC_SHARED( unsigned char, my_smem)"