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- #pragma once
- // @generated by torchgen/gen.py from DispatchKeyFunction.h
- // NB: The implementing C++ file is RegisterDispatchKey.cpp
- // The only #includes we need are for custom classes that have defaults in the C++ API
- #include <c10/core/MemoryFormat.h>
- #include <c10/core/Scalar.h>
- #include <ATen/core/Reduction.h>
- // Forward declarations of any types needed in the operator signatures.
- // We can't directly include these classes because it will cause circular include dependencies.
- // This file is included by TensorBody.h, which defines the Tensor class.
- #include <ATen/core/ATen_fwd.h>
- namespace at {
- namespace compositeimplicitautograd {
- TORCH_API at::Tensor nanquantile(const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false, c10::string_view interpolation="linear");
- TORCH_API at::Tensor & nanquantile_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false, c10::string_view interpolation="linear");
- TORCH_API at::Tensor & nanquantile_outf(const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation, at::Tensor & out);
- TORCH_API at::Tensor nanquantile(const at::Tensor & self, double q, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false, c10::string_view interpolation="linear");
- TORCH_API at::Tensor & nanquantile_out(at::Tensor & out, const at::Tensor & self, double q, c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false, c10::string_view interpolation="linear");
- TORCH_API at::Tensor & nanquantile_outf(const at::Tensor & self, double q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation, at::Tensor & out);
- } // namespace compositeimplicitautograd
- } // namespace at
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