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Library tensorplay.library.custom_op tensorplay.library.define tensorplay.library.get_kernel tensorplay.library.impl tensorplay.library.impl_abstract tensorplay.library.infer_schema tensorplay.library.opcheck tensorplay.library.register_autocast tensorplay.library.register_autograd tensorplay.library.register_fake tensorplay.library.register_kernel tensorplay.library.register_vmap tensorplay.library.triton_op tensorplay.library.wrap_triton

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latest (dev)2026-09-08 v1.0.02026-09-06

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tensorplay.library.impl_abstract

tensorplay.library.impl_abstract(qualname: str, func: Callable[[...], Any] | None = None, /, *, lib: Any = None) → Callable[[Callable[[...], Any]], Callable[[...], Any]][source]

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tensorplay.library.impl

types accepts concrete devices ( "CPU" / "CUDA" ) or composite spellings ( CompositeExplicitAutograd → the device-agnostic slot).

tensorplay.library.infer_schema

Produces "ns::op(Tensor self, SymInt n, Tensor(a!) out) -> Tensor" alias-annotation (<type>(<letter>!)) marker. Parameters without annotations are treated as tensors; *args / **kwargs are skipped.

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