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.

1. inferTypeFrom(self: torch._C.Value, arg0: torch.Tensor) -> None

2. 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.

1. type(self: torch._C.Value) -> c10::Type

2. type(self: torch._C.Value) -> c10::Type

unique(self: torch._C.Value) → int

uses(self: torch._C.Value) → list[torch::jit::Use]