#pragma once // @generated by torchgen/gen.py from Function.h #include #include #include #include #include #include #include #include #include #include #include #include #include namespace at { // aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor inline at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step); } namespace symint { template ::value>> at::Tensor unfold_backward(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step); } } // aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor inline at::Tensor unfold_backward_symint(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward::call(grad_in, input_sizes, dim, size, step); } namespace symint { template ::value>> at::Tensor unfold_backward(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward::call(grad_in, input_sizes, dim, size, step); } } // aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) inline at::Tensor & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out); } namespace symint { template ::value>> at::Tensor & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out); } } // aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) inline at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) { return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out); } namespace symint { template ::value>> at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, at::IntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) { return at::_ops::unfold_backward_out::call(grad_in, c10::fromIntArrayRefSlow(input_sizes), dim, size, step, out); } } // aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) inline at::Tensor & unfold_backward_symint_out(at::Tensor & out, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out); } namespace symint { template ::value>> at::Tensor & unfold_backward_out(at::Tensor & out, const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step) { return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out); } } // aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) inline at::Tensor & unfold_backward_symint_outf(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) { return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out); } namespace symint { template ::value>> at::Tensor & unfold_backward_outf(const at::Tensor & grad_in, c10::SymIntArrayRef input_sizes, int64_t dim, int64_t size, int64_t step, at::Tensor & out) { return at::_ops::unfold_backward_out::call(grad_in, input_sizes, dim, size, step, out); } } }