[jit] Polymorphic IValue::type() for DynamicType. #70120
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
CI Flow Status⚛️ CI FlowRuleset - Version:
You can add a comment to the PR and tag @pytorchbot with the following commands: # ciflow rerun, "ciflow/default" will always be added automatically
@pytorchbot ciflow rerun
# ciflow rerun with additional labels "-l <ciflow/label_name>", which is equivalent to adding these labels manually and trigger the rerun
@pytorchbot ciflow rerun -l ciflow/scheduled -l ciflow/slowFor more information, please take a look at the CI Flow Wiki. |
🔗 Helpful links
💊 CI failures summary and remediationsAs of commit 9553998 (more details on the Dr. CI page): 💚 💚 Looks good so far! There are no failures yet. 💚 💚 This comment was automatically generated by Dr. CI (expand for details).Please report bugs/suggestions to the (internal) Dr. CI Users group. |
facebook-github-bot
added
the
oncall: jit
This was referenced Dec 17, 2021
zhxchen17
requested review from
gmagogsfm and
suo
and removed request for
suo
gmagogsfm
approved these changes
Dec 18, 2021
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
This was referenced Dec 20, 2021
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Before the change: ``` c10::Type t = ivalue.type(); ``` After the change: ``` c10::Type t = ivalue.type(); c10::DynamicType d = ivalue.type<c10::DynamicType>(); // new path ``` The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced. Lite Interpreter should only use the `<DynamicType>` variant of the interfaces from aten, to reduce binary size. Differential Revision: [D33102276](https://our.internmc.facebook.com/intern/diff/D33102276/) [ghstack-poisoned]
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Stack from ghstack:
Before the change:
After the change:
The new path will be adopted in PyTorch Lite Interpreter to support lightweight type reflection. Note that type getters are selected at compile time so no performance overhead. The benefits of having a DynamicType will be elaborated in a separate document, but in short, DynamicType provides an isolated type system for controlling binary size bloat, and shrink down ~20 supported Type symbols into one so that the size taken by specializations and function name symbols are greatly reduced.
Lite Interpreter should only use the
<DynamicType>variant of the interfaces from aten, to reduce binary size.Differential Revision: D33102276