pytorch
99349def - remove unnecessary Node* ops (#32760)
Commit
4 years agoremove unnecessary Node* ops (#32760)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32760
Minor changes to the way ops are implemented to remove incidental use of Node*
in the operator implementation.
Current state for operators that previously took Node:
```
TBD:
USES NODE: prim::DifferentiableGraph(...) -> (...)
USES NODE: prim::profile(...) -> (...)
USES NODE: prim::FusionGroup(...) -> (...)
USES NODE: prim::PythonOp(...) -> (...)
USES NODE: prim::ImplicitTensorToNum(Tensor a) -> Scalar # next PR
Should be made interpreter primitives:
USES NODE: prim::TupleUnpack(...) -> (...)
USES NODE: prim::TupleSlice(...) -> (...)
USES NODE: prim::TupleConstruct(...) -> (...)
USES NODE: prim::ListUnpack(...) -> (...)
USES NODE: prim::ListConstruct(...) -> (...)
USES NODE: prim::DictConstruct(...) -> (...)
USES NODE: prim::Constant() -> (...)
USES NODE: prim::isinstance(...) -> (...)
USES NODE: prim::CreateObject(...) -> (...)
USES NODE: prim::fork(...) -> (...)
USES NODE: aten::warn(str message, *, int stacklevel=2) -> () # need stack level information, so ideally in interpreter so it can look at the stack
Should be made into vararg operators, i.e. the operators last argument should be an IValue
that contains the number of arguments.
USES NODE: prim::FusedConcat(...) -> (...)
USES NODE: prim::MMTreeReduce(...) -> (...)
USES NODE: prim::MMBatchSide(...) -> (...)
USES NODE: prim::ConstantChunk(...) -> (...)
USES NODE: prim::AutogradAnyNonZero(...) -> bool
USES NODE: prim::BroadcastSizes(...) -> (...)
USES NODE: prim::ChunkSizes(...) -> (...)
USES NODE: aten::format(str self, ...) -> str
USES NODE: prim::Print(...) -> (...)
fixed:
USES NODE: aten::extend(Tensor[](a!) self, Tensor [] other) -> ()
USES NODE: aten::copy(Tensor[](a) self) -> Tensor[]
USES NODE: aten::extend(int[](a!) self, int [] other) -> ()
USES NODE: aten::copy(int[](a) self) -> int[]
USES NODE: aten::extend(float[](a!) self, float [] other) -> ()
USES NODE: aten::copy(float[](a) self) -> float[]
USES NODE: aten::extend(bool[](a!) self, bool [] other) -> ()
USES NODE: aten::copy(bool[](a) self) -> bool[]
USES NODE: aten::extend(t[](a!) self, t [] other) -> ()
USES NODE: aten::copy(t[](a) self) -> t[]
USES NODE: aten::keys(Dict(str, t) self) -> str[](*)
USES NODE: aten::values(Dict(str, t) self) -> t[](*)
USES NODE: aten::dict((str, tVal)[] inputs) -> Dict(str, tVal)
USES NODE: aten::keys(Dict(int, t) self) -> int[](*)
USES NODE: aten::values(Dict(int, t) self) -> t[](*)
USES NODE: aten::dict((int, tVal)[] inputs) -> Dict(int, tVal)
USES NODE: aten::keys(Dict(float, t) self) -> float[](*)
USES NODE: aten::values(Dict(float, t) self) -> t[](*)
USES NODE: aten::dict((float, tVal)[] inputs) -> Dict(float, tVal)
USES NODE: aten::keys(Dict(Tensor, t) self) -> Tensor[](*)
USES NODE: aten::values(Dict(Tensor, t) self) -> t[](*)
USES NODE: aten::dict((Tensor, tVal)[] inputs) -> Dict(Tensor, tVal)
USES NODE: aten::test_vartype2(t a, t[] b) -> (t[])
USES NODE: aten::_ncf_unsqueeze(Tensor self, int ndim) -> Tensor
USES NODE: aten::_ncf_view(Tensor self, int[] input_shape, int normalized_ndim) -> Tensor
USES NODE: prim::is_none(int? a) -> bool
USES NODE: aten::__interpolate(Tensor input, int? size = None, float[]? scale_factor = None, str mode = 'nearest', bool? align_corners = None, bool? recompute_scale_factor = None) -> Tensor
USES NODE: aten::__interpolate(Tensor input, int[]? size = None, float[]? scale_factor = None, str mode = 'nearest', bool? align_corners = None, bool? recompute_scale_factor = None) -> Tensor
USES NODE: aten::__interpolate(Tensor input, int? size = None, float? scale_factor = None, str mode = 'nearest', bool? align_corners = None, bool? recompute_scale_factor = None) -> Tensor
USES NODE: aten::__interpolate(Tensor input, int[]? size = None, float? scale_factor = None, str mode = 'nearest', bool? align_corners = None, bool? recompute_scale_factor = None) -> Tensor
USES NODE: aten::sorted(t[](a) self) -> (t[])
USES NODE: aten::sort(t[](a!) self, bool reverse=False) -> ()
USES NODE: aten::test_vartype(t[] a, t b) -> (t)
USES NODE: prim::unchecked_unwrap_optional(t(a)? optional) -> t(a)
USES NODE: prim::unchecked_cast(...) -> (...)
USES NODE: aten::dict() -> Dict(str, Tensor)
USES NODE: prim::Load(...) -> (...)
USES NODE: prim::Store(...) -> (...)
USES NODE: prim::Drop(...) -> (...)
USES NODE: aten::tensor(t[] data, *, ScalarType? dtype=None, Device? device=None, bool requires_grad=False) -> Tensor
USES NODE: aten::as_tensor(t[] data, *, ScalarType? dtype=None, Device? device=None) -> Tensor
```
Test Plan: Imported from OSS
Differential Revision: D19615387
Pulled By: zdevito
fbshipit-source-id: 95298c3c4249b9f812c332d13f0fb79daeecb662
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