#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::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor inline at::Tensor _pack_padded_sequence_backward(const at::Tensor & grad, at::IntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first) { return at::_ops::_pack_padded_sequence_backward::call(grad, c10::fromIntArrayRefSlow(input_size), batch_sizes, batch_first); } namespace symint { template ::value>> at::Tensor _pack_padded_sequence_backward(const at::Tensor & grad, at::IntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first) { return at::_ops::_pack_padded_sequence_backward::call(grad, c10::fromIntArrayRefSlow(input_size), batch_sizes, batch_first); } } // aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor inline at::Tensor _pack_padded_sequence_backward_symint(const at::Tensor & grad, c10::SymIntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first) { return at::_ops::_pack_padded_sequence_backward::call(grad, input_size, batch_sizes, batch_first); } namespace symint { template ::value>> at::Tensor _pack_padded_sequence_backward(const at::Tensor & grad, c10::SymIntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first) { return at::_ops::_pack_padded_sequence_backward::call(grad, input_size, batch_sizes, batch_first); } } }