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#pragma once
#include <torch/custom_class.h>
namespace torch::jit {
// Interface for a JIT backend.
class TORCH_API PyTorchBackendInterface : public torch::CustomClassHolder {
public:
PyTorchBackendInterface() noexcept;
~PyTorchBackendInterface() override;
// Returns true if the backend is available to process delegation calls.
virtual bool is_available() = 0;
// Compile the module contained in \p processed using the details provided in
// \p method_compile_spec for each module method that should be compiled for
// the backend. \p method_compile_spec should be of type Dict<string, Any>.
// \returns a dictionary of type Dict<string, Any> that contains a backend
// handle each method that can run on the backend (i.e. each key in \p
// method_compile_spec).
virtual c10::impl::GenericDict compile(
c10::IValue processed,
c10::impl::GenericDict method_compile_spec) = 0;
// Execute the method specified by \p handle using \p inputs. \returns the
// outputs as a tuple.
virtual c10::impl::GenericList execute(
c10::IValue handle,
c10::impl::GenericList inputs) = 0;
};
} // namespace torch::jit
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