pytorch_pfn_extras.onnx.symbolic_registry.Value#
- class pytorch_pfn_extras.onnx.symbolic_registry.Value#
Bases:
pybind11_object
Methods
__init__
(*args, **kwargs)copyMetadata
(self, arg0)debugName
(self)inferTypeFrom
(*args, **kwargs)Overloaded function.
isCompleteTensor
(self)node
(self)offset
(self)replaceAllUsesAfterNodeWith
(self, arg0, arg1)replaceAllUsesWith
(self, arg0)requiresGrad
(self)requires_grad
(self)setDebugName
(self, arg0)setType
(self, arg0)setTypeAs
(self, arg0)toIValue
(self)type
(*args, **kwargs)Overloaded function.
unique
(self)uses
(self)- __init__(*args, **kwargs)#
- copyMetadata(self: torch._C.Value, arg0: torch._C.Value) torch._C.Value #
- debugName(self: torch._C.Value) str #
- inferTypeFrom(*args, **kwargs)#
Overloaded function.
inferTypeFrom(self: torch._C.Value, arg0: torch.Tensor) -> None
inferTypeFrom(self: torch._C.Value, arg0: c10::ivalue::Object) -> None
- isCompleteTensor(self: torch._C.Value) bool #
- node(self: torch._C.Value) torch::jit::Node #
- offset(self: torch._C.Value) int #
- replaceAllUsesAfterNodeWith(self: torch._C.Value, arg0: torch::jit::Node, arg1: torch._C.Value) None #
- replaceAllUsesWith(self: torch._C.Value, arg0: torch._C.Value) None #
- requiresGrad(self: torch._C.Value) Optional[bool] #
- requires_grad(self: torch._C.Value) bool #
- setDebugName(self: torch._C.Value, arg0: str) torch._C.Value #
- setType(self: torch._C.Value, arg0: c10::Type) torch._C.Value #
- setTypeAs(self: torch._C.Value, arg0: torch._C.Value) torch._C.Value #
- toIValue(self: torch._C.Value) Optional[IValue] #
- type(*args, **kwargs)#
Overloaded function.
type(self: torch._C.Value) -> c10::Type
type(self: torch._C.Value) -> c10::Type
- unique(self: torch._C.Value) int #
- uses(self: torch._C.Value) List[torch::jit::Use] #