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torch / include / torch / csrc / distributed / rpc / python_functions.h
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#pragma once

#include <torch/csrc/distributed/rpc/py_rref.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/jit/python/pybind_utils.h>
#include <torch/csrc/utils/pybind.h>

namespace torch {
namespace distributed {
namespace rpc {

// Converts an internal ivalue::Future of Message into a user-facing
// ivalue::Future of py::object type by creating a new ivalue::Future and call
// its  markCompleted as a callback in the given ivalue::Future.
// If hasValue is true, the Message will be converted into a py::object and then
// wrap it with an IValue. If hasValue is false, this ivalue::Future is only
// used for signaling and launching callbacks. In this case, the message will be
// discarded and then set the ivalue::Future using an empty IValue or the given
// FutureError if there is an error.
c10::intrusive_ptr<JitFuture> toPyJitFuture(
    const c10::intrusive_ptr<JitFuture>& messageJitFuture,
    bool hasValue = true);

c10::intrusive_ptr<JitFuture> pyRpcBuiltin(
    const WorkerInfo& dst,
    const std::string& opName,
    const py::args& args,
    const py::kwargs& kwargs,
    const float rpcTimeoutSeconds);

c10::intrusive_ptr<JitFuture> pyRpcPythonUdf(
    const WorkerInfo& dst,
    std::string& pickledPythonUDF,
    std::vector<torch::Tensor>& tensors,
    const float rpcTimeoutSeconds,
    const bool isAsyncExecution);

c10::intrusive_ptr<JitFuture> pyRpcTorchscript(
    const std::string& dstWorkerName,
    const std::string& qualifiedNameStr,
    const py::tuple& argsTuple,
    const py::dict& kwargsDict,
    const float rpcTimeoutSeconds,
    const bool isAsyncExecution);

PyRRef pyRemoteBuiltin(
    const WorkerInfo& dst,
    const std::string& opName,
    const float rpcTimeoutSeconds,
    const py::args& args,
    const py::kwargs& kwargs);

PyRRef pyRemotePythonUdf(
    const WorkerInfo& dst,
    std::string& pickledPythonUDF,
    std::vector<torch::Tensor>& tensors,
    const float rpcTimeoutSeconds,
    const bool isAsyncExecution);

PyRRef pyRemoteTorchscript(
    const std::string& dstWorkerName,
    const std::string& qualifiedNameStr,
    const float rpcTimeoutSeconds,
    const bool isAsyncExecution,
    const py::args& args,
    const py::kwargs& kwargs);

} // namespace rpc
} // namespace distributed
} // namespace torch