fix per-dispatchkey-mode caching bug #98030
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[ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/98030
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 9f5c098: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Mar 30, 2023
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ezyang
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Apr 3, 2023
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I don't understand the comment about "indirect test" |
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
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(test added) |
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for **every** autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached). I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one. [ghstack-poisoned]
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The bug was that: if you want to move a mode to the autograd key, we need to use the "functionality" key for it (AutogradFunctionality). But when we do that, we need to clear any PythonDispatcher caches for every op for every autograd key (since you could run autograd ops with both cpu and cuda tensors underneath the mode, which both may have been cached).
I didn't add a test, since this ends up getting indirectly tests by export in the PR. If someone would prefer a direct test I can add one.
Stack from ghstack (oldest at bottom):