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Use cu132 binaries in the nightly build to test 2.15 - #3986
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Follow-up to #3983: install torch==2.15.0 from the test channel with cu132 instead of cu130 on the USE_NIGHTLY path and the commented reference line in .jenkins/build.sh. AI assistance (Claude) was used for this change.
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/tutorials/3986
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Follow-up to #3983: switch the 2.15 nightly/test build from cu130 to cu132.
.jenkins/build.sh:--index-url https://download.pytorch.org/whl/test/cu130->.../test/cu132on theUSE_NIGHTLYpath and the commented reference line.torch==2.15.0+cu132is published for cp312 on x86_64 and aarch64 on thetest/cu132index (it is also on the stablecu132index). The channel staystest; only the CUDA suffix changes.bash -n .jenkins/build.shpasses. The nightly job itself has not been run against cu132 yet, so the runner driver compatibility with CUDA 13.2 is unverified.AI assistance (Claude) was used for this change.