modify the conditions as PythonModuleVariable#116856
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jiayisunx wants to merge 17 commits intogh/jiayisunx/1/basefrom
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modify the conditions as PythonModuleVariable#116856jiayisunx wants to merge 17 commits intogh/jiayisunx/1/basefrom
jiayisunx wants to merge 17 commits intogh/jiayisunx/1/basefrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/116856
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit 706470a with merge base 5d2d21a ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
UNSTABLE - The following job failed but was likely due to flakiness present on trunk and has been marked as unstable:
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[ghstack-poisoned]
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@pytorchbot rebase |
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@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
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Successfully rebased |
cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
Skylion007
reviewed
Jan 9, 2024
| istype(value, (types.ModuleType, replay_record.DummyModule)) | ||
| # type(torch.backends.cudnn) -> <class 'torch.backends.cudnn.CudnnModule'> | ||
| # type(torch.ops) -> <class 'torch._ops._Ops'> | ||
| or value in [torch.backends.cudnn, torch.ops] |
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If this isn't working, wouldn't:
Suggested change
| or value in [torch.backends.cudnn, torch.ops] | |
| or any(value is obj for obj in (torch.backends.cudnn, torch.ops)) |
work?
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It works, thanks!
jansel
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Jan 9, 2024
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This seems like a semantic change. isinstance is not the same as ==.
I'd suggest replacing it with is instread as @Skylion007 suggests.
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
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## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
## Motivation The current code of `value in [torch.backends.cudnn, torch.ops]` requires `value` to have the implementation of `__eq__`. If the value is a custom object and does not implement `__eq__`, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error: **torch._dynamo.exc.InternalTorchDynamoError: '__eq__' is not implemented for __torch__.torch.classes.ipex_prepack.ConvolutionOpContext** I think this is a common issue, To avoid this issue, the PR replaces the current code `value in [torch.backends.cudnn, torch.ops]`with `isinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv chenyang78 aakhundov kadeng [ghstack-poisoned]
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@pytorchbot merge |
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Motivation
The current code of
value in [torch.backends.cudnn, torch.ops]requiresvalueto have the implementation of__eq__. If the value is a custom object and does not implement__eq__, dynamo will throw error. For example, ConvolutionOpContext, the custom 'torch._C.ScriptClass' object registered in IPEX, dynamo will throw the following error:torch._dynamo.exc.InternalTorchDynamoError: 'eq' is not implemented for torch.torch.classes.ipex_prepack.ConvolutionOpContext
I think this is a common issue, To avoid this issue, the PR replaces the current code
value in [torch.backends.cudnn, torch.ops]withisinstance(value, (torch.backends.cudnn.CudnnModule, torch._ops._Ops)Stack from ghstack (oldest at bottom):
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @chenyang78 @aakhundov @kadeng