[jit] add dynamic isinstance#26269
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suo
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ngnt. I kind of hate the "list", "tuple" thing but I guess that means I kind of hate Python.
| Operator( | ||
| "prim::BailOut(...) -> Tensor(a)", | ||
| [](const Node* /* node */) -> Operation { | ||
| [](const Node * /* node */) -> Operation { |
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nit: looks like some random formatting changes got through
This was referenced Sep 25, 2019
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
[jit] add dynamic isinstance previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support.it gh-metadata: pytorch pytorch 26269 gh/zdevito/109/head
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Summary: Pull Request resolved: pytorch/pytorch#26269 previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support. Test Plan: Imported from OSS Differential Revision: D17412853 Pulled By: zdevito fbshipit-source-id: e2c37040f25f6b94ee1676854fceecd22de190ef
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pdlive215
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Nov 27, 2019
Summary: Pull Request resolved: pytorch#26269 previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support. Test Plan: Imported from OSS Differential Revision: D17412853 Pulled By: zdevito fbshipit-source-id: e2c37040f25f6b94ee1676854fceecd22de190ef
thiagocrepaldi
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Feb 4, 2020
Summary: Pull Request resolved: pytorch#26269 previously isinstance only worked when we could statically determine if it were true/false. Now we actually can issue an isinstance check in case where it is dependent on the runtime type, e.g. Optional[int] being an instance of int. This is not very useful on its own yet, but with type refinement and allowing Any as an argument type this will allow for python-style "overloaded" functions such that we can remove our __overload__ support. Test Plan: Imported from OSS Differential Revision: D17412853 Pulled By: zdevito fbshipit-source-id: e2c37040f25f6b94ee1676854fceecd22de190ef
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Stack from ghstack:
previously isinstance only worked when we could statically determine
if it were true/false. Now we actually can issue an isinstance check
in case where it is dependent on the runtime type, e.g. Optional[int]
being an instance of int. This is not very useful on its own yet,
but with type refinement and allowing Any as an argument type this will
allow for python-style "overloaded" functions such that we do not rely
on overload support for all instances of polymorphic arguments.
Differential Revision: D17412853