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Force requires setting device to `env.DEVICE` or `cpu` explictly for functions like `torch.tensor`, `torch.zeros`, `torch.ones`, `torch.rand`, `torch.eye`, and dataloader. This ensures that no OPs that should be run on GPUs run on CPUs.
The trick here is `torch.set_default_device("cuda:9999999")` in the tests, so errors will be thrown if no device is set.
Tips:
(1) Avoid `torch.zeros(...).to(device=...)`. This firstly initlizes memory on CPUs and copy it to GPUs.
(2) Use `with torch.device(...)` for third-party modules.
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## devel #3307 +/- ##
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Coverage 75.29% 75.29%
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Files 398 398
Lines 33684 33694 +10
Branches 1604 1604
=======================================
+ Hits 25361 25371 +10
Misses 7462 7462
Partials 861 861 ☔ View full report in Codecov by Sentry. |
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
wanghan-iapcm
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Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
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Forcely requires setting the device to
env.DEVICEorcpuexplicitly for functions liketorch.tensor,torch.zeros,torch.ones,torch.rand,torch.eye,LayerNorm, and data loader.This ensures that no OP runs on the wrong device. The trick here is
torch.set_default_device("cuda:9999999")in the tests, so errors will be thrown if the default device is used.Tips:
(1) Avoid
torch.zeros(...).to(device=...). This first initializes memory on CPUs and copies it to GPUs.(2) Use
with torch.device(...)for a module that cannot set a device (i.e., the data loader).