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# Source code for torch.distributed.elastic.multiprocessing.api

    #!/usr/bin/env python3

    # Copyright (c) Facebook, Inc. and its affiliates.
    # All rights reserved.
    #
    # This source code is licensed under the BSD-style license found in the
    # LICENSE file in the root directory of this source tree.

    import abc
    import logging
    import os
    import re
    import signal
    import subprocess
    import sys
    import time
    from contextlib import nullcontext
    from dataclasses import dataclass, field
    from enum import IntFlag
    from multiprocessing import synchronize
    from types import FrameType
    from typing import Any, Callable, Dict, Optional, Set, Tuple, Union

    import torch.multiprocessing as mp
    from torch.distributed.elastic.multiprocessing.errors import ProcessFailure, record
    from torch.distributed.elastic.multiprocessing.redirects import (
        redirect_stderr,
        redirect_stdout,
    )
    from torch.distributed.elastic.multiprocessing.tail_log import TailLog

    IS_WINDOWS = sys.platform == "win32"
    IS_MACOS = sys.platform == "darwin"

    log = logging.getLogger(__name__)

    __all__ = ["SignalException", "Std", "to_map", "RunProcsResult", "PContext", "get_std_cm", "MultiprocessContext",
               "SubprocessHandler", "SubprocessContext"]

    class SignalException(Exception):
        """
        Exception is raised inside the torchelastic agent process by the termination handler
        if the death signal got received by the process.
        """

        def __init__(self, msg: str, sigval: signal.Signals) -> None:
            super().__init__(msg)
            self.sigval = sigval

    def _terminate_process_handler(signum: int, frame: Optional[FrameType]) -> None:
        """Termination handler that raises exceptions on the main process.

        When the process receives death signal(SIGTERM, SIGINT), this termination handler will
        be invoked. It raises the ``SignalException`` exception that should be processed by the
        user code. Python does not terminate process after the termination handler is finished,
        so the exception should not be silently ignored, otherwise the process will never
        be terminated.
        """
        sigval = signal.Signals(signum)
        raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)

    def _get_kill_signal() -> signal.Signals:
        """
        Get the kill signal. SIGKILL for unix, CTRL_C_EVENT for windows.
        """
        if IS_WINDOWS:
            return signal.CTRL_C_EVENT  # type: ignore[attr-defined] # noqa: F821
        else:
            return signal.SIGKILL

    def _get_default_signal() -> signal.Signals:
        """
        Get the default termination signal. SIGTERM for unix, CTRL_C_EVENT for windows.
        """
        if IS_WINDOWS:
            return signal.CTRL_C_EVENT  # type: ignore[attr-defined] # noqa: F821
        else:
            return signal.SIGTERM

    def _validate_full_rank(d: Dict[int, Any], nprocs: int, what: str):
        actual_keys = set(d.keys())
        expected_keys = set(range(nprocs))

        if actual_keys != expected_keys:
            raise RuntimeError(
                f"{what}, local rank mapping mismatch,"
                f" expected: {expected_keys}, actual: {actual_keys}"
            )

    _MAPPING_REGEX = r"^(\d:[0123],)*(\d:[0123])$"
    _VALUE_REGEX = r"^[0123]$"

    class Std(IntFlag):
        NONE = 0
        OUT = 1
        ERR = 2
        ALL = OUT | ERR

        @classmethod
        def from_str(cls, vm: str) -> Union["Std", Dict[int, "Std"]]:
            """
            Example:

            ::

             from_str("0") -> Std.NONE
             from_str("1") -> Std.OUT
             from_str("0:3,1:0,2:1,3:2") -> {0: Std.ALL, 1: Std.NONE, 2: Std.OUT, 3: Std.ERR}

            Any other input raises an exception
            """

            def to_std(v: str) -> Std:  # type: ignore[return]
                s = Std(int(v))
                if s in Std:
                    return s
                # return None -> should NEVER reach here since we regex check input

            if re.match(_VALUE_REGEX, vm):  # vm is a number (e.g. 0)
                return to_std(vm)
            elif re.match(_MAPPING_REGEX, vm):  # vm is a mapping (e.g. 0:1,1:2)
                d: Dict[int, Std] = {}
                for m in vm.split(","):
                    i, v = m.split(":")
                    d[int(i)] = to_std(v)
                return d
            else:
                raise ValueError(
                    f"{vm} does not match: <{_VALUE_REGEX}> or <{_MAPPING_REGEX}>"
                )

    def to_map(
        val_or_map: Union[Std, Dict[int, Std]], local_world_size: int
    ) -> Dict[int, Std]:
        """
        Certain APIs take redirect settings either as a single value (e.g. apply to all
        local ranks) or as an explicit user-provided mapping. This method is a convenience
        method that converts a value or mapping into a mapping.

        Example:

        ::

         to_map(Std.OUT, local_world_size=2) # returns: {0: Std.OUT, 1: Std.OUT}
         to_map({1: Std.OUT}, local_world_size=2) # returns: {0: Std.NONE, 1: Std.OUT}
         to_map({0: Std.OUT, 1: Std.OUT}, local_world_size=2) # returns: {0: Std.OUT, 1: Std.OUT}
        """
        if isinstance(val_or_map, Std):
            return {i: val_or_map for i in range(local_world_size)}
        else:
            map = {}
            for i in range(local_world_size):
                map[i] = val_or_map.get(i, Std.NONE)
            return map

    @dataclass
    class RunProcsResult:
        """
        Results of a completed run of processes started with ``start_processes()``.
        Returned by ``PContext``.

        Note the following:

        1. All fields are mapped by local rank
        2. ``return_values`` - only populated for functions (not the binaries).
        3. ``stdouts`` - path to stdout.log (empty string if no redirect)
        4. ``stderrs`` - path to stderr.log (empty string if no redirect)

        """

        return_values: Dict[int, Any] = field(default_factory=dict)
        failures: Dict[int, ProcessFailure] = field(default_factory=dict)
        stdouts: Dict[int, str] = field(default_factory=dict)
        stderrs: Dict[int, str] = field(default_factory=dict)

        def is_failed(self) -> bool:
            return len(self.failures) > 0

    class PContext(abc.ABC):
        """
        The base class that standardizes operations over a set of processes
        that are launched via different mechanisms. The name ``PContext``
        is intentional to disambiguate with ``torch.multiprocessing.ProcessContext``.

        .. warning:: stdouts and stderrs should ALWAYS be a superset of
                     tee_stdouts and tee_stderrs (respectively) this is b/c
                     tee is implemented as a redirect + tail -f <stdout/stderr.log>
        """

        def __init__(
            self,
            name: str,
            entrypoint: Union[Callable, str],
            args: Dict[int, Tuple],
            envs: Dict[int, Dict[str, str]],
            stdouts: Dict[int, str],
            stderrs: Dict[int, str],
            tee_stdouts: Dict[int, str],
            tee_stderrs: Dict[int, str],
            error_files: Dict[int, str],
        ):
            self.name = name
            # validate that all mappings have the same number of keys and
            # all local ranks are accounted for
            nprocs = len(args)
            _validate_full_rank(stdouts, nprocs, "stdouts")
            _validate_full_rank(stderrs, nprocs, "stderrs")

            self.entrypoint = entrypoint
            self.args = args
            self.envs = envs
            self.stdouts = stdouts
            self.stderrs = stderrs
            self.error_files = error_files
            self.nprocs = nprocs

            self._stdout_tail = TailLog(name, tee_stdouts, sys.stdout)
            self._stderr_tail = TailLog(name, tee_stderrs, sys.stderr)

        def start(self) -> None:
            """
            Start processes using parameters defined in the constructor.
            """
            signal.signal(signal.SIGTERM, _terminate_process_handler)
            signal.signal(signal.SIGINT, _terminate_process_handler)
            if not IS_WINDOWS:
                signal.signal(signal.SIGHUP, _terminate_process_handler)
                signal.signal(signal.SIGQUIT, _terminate_process_handler)
            self._start()
            self._stdout_tail.start()
            self._stderr_tail.start()

        @abc.abstractmethod
        def _start(self) -> None:
            """
            Start processes using strategy defined in a particular context.
            """
            raise NotImplementedError()

        @abc.abstractmethod
        def _poll(self) -> Optional[RunProcsResult]:
            """
            Polls the run status of the processes running under this context.
            This method follows an "all-or-nothing" policy and returns
            a ``RunProcessResults`` object if either all processes complete
            successfully or any process fails. Returns ``None`` if
            all processes are still running.
            """
            raise NotImplementedError()

        def wait(self, timeout: float = -1, period: float = 1) -> Optional[RunProcsResult]:
            """
            Waits for the specified ``timeout`` seconds, polling every ``period`` seconds
            for the processes to be done. Returns ``None`` if the processes are still running
            on timeout expiry. Negative timeout values are interpreted as "wait-forever".
            A timeout value of zero simply queries the status of the processes (e.g. equivalent
            to a poll).

            ..note: Multiprocessing library registers SIGTERM and SIGINT signal handlers that raise
                    ``SignalException`` when the signals received. It is up to the consumer of the code
                    to properly handle the exception. It is important not to swallow the exception otherwise
                    the process would not terminate. Example of the typical workflow can be:

            .. code-block:: python
                pc = start_processes(...)
                try:
                    pc.wait(1)
                    .. do some other work
                except SignalException as e:
                    pc.shutdown(e.sigval, timeout=30)

            If SIGTERM or SIGINT occurs, the code above will try to shutdown child processes by propagating
            received signal. If child processes will not terminate in the timeout time, the process will send
            the SIGKILL.
            """

            if timeout == 0:
                return self._poll()

            if timeout < 0:
                timeout = sys.maxsize

            expiry = time.time() + timeout
            while time.time() < expiry:
                pr = self._poll()
                if pr:
                    return pr
                time.sleep(period)

            return None

        @abc.abstractmethod
        def pids(self) -> Dict[int, int]:
            """
            Returns pids of processes mapped by their respective local_ranks
            """
            raise NotImplementedError()

        @abc.abstractmethod
        def _close(self, death_sig: signal.Signals, timeout: int = 30) -> None:
            r"""
            Terminates all processes managed by this context and cleans up any
            meta resources (e.g. redirect, error_file files).
            """
            raise NotImplementedError()

        def close(
            self, death_sig: Optional[signal.Signals] = None, timeout: int = 30
        ) -> None:
            r"""
            Terminates all processes managed by this context and cleans up any
            meta resources (e.g. redirect, error_file files).

            Args:
                death_sig: Death signal to terminate processes.
                timeout: Time to wait for processes to finish, if process is
                    still alive after this time, it will be terminated via SIGKILL.
            """
            if not death_sig:
                death_sig = _get_default_signal()
            self._close(death_sig=death_sig, timeout=timeout)
            if self._stdout_tail:
                self._stdout_tail.stop()
            if self._stderr_tail:
                self._stderr_tail.stop()

    def get_std_cm(std_rd: str, redirect_fn):
        if IS_WINDOWS or IS_MACOS or not std_rd:
            return nullcontext()
        else:
            return redirect_fn(std_rd)

    def _wrap(
        local_rank: int,
        fn: Callable,
        args: Dict[int, Tuple],
        envs: Dict[int, Dict[str, str]],
        stdout_redirects: Dict[int, str],  # redirect file for stdout (to console if None)
        stderr_redirects: Dict[int, str],  # redirect file for stderr (to console if None)
        ret_vals: Dict[int, mp.SimpleQueue],
        queue_finished_reading_event: synchronize.Event,
    ) -> None:
        # get the per-rank params up front so we fail fast if no mapping is found
        args_ = args[local_rank]
        env_ = envs[local_rank]
        ret_val_ = ret_vals[local_rank]

        stdout_rd = stdout_redirects[local_rank]
        stderr_rd = stderr_redirects[local_rank]

        stdout_cm = get_std_cm(stdout_rd, redirect_stdout)
        stderr_cm = get_std_cm(stderr_rd, redirect_stderr)

        for k, v in env_.items():
            os.environ[k] = v

        with stdout_cm, stderr_cm:
            ret = record(fn)(*args_)
        ret_val_.put(ret)
        queue_finished_reading_event.wait()

    class MultiprocessContext(PContext):
        """
        ``PContext`` holding worker processes invoked as a function.
        """

        def __init__(
            self,
            name: str,
            entrypoint: Callable,
            args: Dict[int, Tuple],
            envs: Dict[int, Dict[str, str]],
            stdouts: Dict[int, str],
            stderrs: Dict[int, str],
            tee_stdouts: Dict[int, str],
            tee_stderrs: Dict[int, str],
            error_files: Dict[int, str],
            start_method: str,
        ):
            super().__init__(
                name,
                entrypoint,
                args,
                envs,
                stdouts,
                stderrs,
                tee_stdouts,
                tee_stderrs,
                error_files,
            )

            self.start_method = start_method
            # each ret_val queue will always contain a single element.
            self._ret_vals = {
                local_rank: mp.get_context(self.start_method).SimpleQueue()
                for local_rank in range(self.nprocs)
            }

            # see comments in ``join()`` for what this is
            self._return_values: Dict[int, Any] = {}
            self._pc: Optional[mp.ProcessContext] = None
            # Note: set method should ONLY be invoked for the use case when all processes finished
            # successfully. If any process died on event.wait() calling set() method will deadlock.
            self._worker_finished_event = mp.get_context(self.start_method).Event()

        def _start(self):
            if self._pc:
                raise ValueError(
                    "The process context already initialized."
                    " Most likely the start method got called twice."
                )
            self._pc = mp.start_processes(
                fn=_wrap,
                args=(
                    self.entrypoint,
                    self.args,
                    self.envs,
                    self.stdouts,
                    self.stderrs,
                    self._ret_vals,
                    self._worker_finished_event,
                ),
                nprocs=self.nprocs,
                join=False,
                daemon=False,
                start_method=self.start_method,
            )

        def _is_done(self) -> bool:
            return len(self._return_values) == self.nprocs

        def _poll(self) -> Optional[RunProcsResult]:
            assert self._pc is not None  # assertion for mypy type checker

            try:
                # torch.mp.ProcessContext Throws an Exception if some/all of
                # worker processes failed
                # timeout < 0 checks worker status and return immediately
                # Join will never return success since we use synchronize.Event to wait
                # for all processes to finish.
                self._pc.join(-1)

                # IMPORTANT: we use multiprocessing.Queue to carry worker return values
                # back to the parent, the worker process will wait before terminating
                # until all the buffered items are fed by the feeder thread to the underlying
                # pipe. Hence to prevent deadlocks on large return values,
                # we opportunistically try queue.get on each join call
                # See: https://docs.python.org/2/library/multiprocessing.html#all-platforms
                for local_rank in range(0, self.nprocs):
                    return_queue = self._ret_vals[local_rank]
                    if not return_queue.empty():
                        # save the return values temporarily into a member var
                        self._return_values[local_rank] = return_queue.get()

                if self._is_done():
                    # we should ALWAYS have ALL the return values when all the processes are done
                    self._worker_finished_event.set()
                    # Wait untill all processes are finished. At this point workers finished executing
                    # user function
                    self._pc.join()
                    _validate_full_rank(
                        self._return_values, self.nprocs, "return_value queue"
                    )
                    self.close()
                    return RunProcsResult(
                        return_values=self._return_values,
                        stdouts=self.stdouts,
                        stderrs=self.stderrs,
                    )
                else:
                    return None
            except (mp.ProcessRaisedException, mp.ProcessExitedException) as e:
                failed_local_rank = e.error_index

                # entrypoint for MultiprocessContext will always be a Callable
                fn_name = self.entrypoint.__qualname__  # type: ignore[union-attr]
                failed_proc = self._pc.processes[failed_local_rank]
                error_filepath = self.error_files[failed_local_rank]

                log.error(
                    "failed (exitcode: %s)"
                    " local_rank: %s (pid: %s)"
                    " of fn: %s (start_method: %s)",
                    failed_proc.exitcode,
                    failed_local_rank, e.pid,
                    fn_name, self.start_method,
                    exc_info=True,
                )

                self.close()
                return RunProcsResult(
                    failures={
                        failed_local_rank: ProcessFailure(
                            local_rank=failed_local_rank,
                            pid=e.pid,
                            exitcode=failed_proc.exitcode,
                            error_file=error_filepath,
                        )
                    },
                    stdouts=self.stdouts,
                    stderrs=self.stderrs,
                )

        def pids(self) -> Dict[int, int]:
            assert self._pc is not None  # assertion for mypy type checking
            return dict(enumerate(self._pc.pids()))

        def _close(self, death_sig: signal.Signals, timeout: int = 30) -> None:
            if not self._pc:
                return
            for proc in self._pc.processes:
                if proc.is_alive():
                    log.warning("Closing process %s via signal %s", proc.pid, death_sig.name)
                    try:
                        os.kill(proc.pid, death_sig)
                    except ProcessLookupError:
                        # If the process exited because of some reason,
                        # `ProcessLookupError` will be raised, it is safe to ignore it.
                        pass
            end = time.monotonic() + timeout
            for proc in self._pc.processes:
                time_to_wait = end - time.monotonic()
                if time_to_wait <= 0:
                    break
                proc.join(time_to_wait)
            for proc in self._pc.processes:
                if proc.is_alive():
                    log.warning(
                        "Unable to shutdown process %s via %s, forcefully exiting via %s",
                        proc.pid, death_sig, _get_kill_signal()
                    )
                    try:
                        os.kill(proc.pid, _get_kill_signal())
                    except ProcessLookupError:
                        # If the process exited because of some reason,
                        # `ProcessLookupError` will be raised, it is safe to ignore it.
                        pass
                proc.join()

    class SubprocessHandler:
        """
        Convenience wrapper around python's ``subprocess.Popen``. Keeps track of
        meta-objects associated to the process (e.g. stdout and stderr redirect fds).
        """

        def __init__(
            self,
            entrypoint: str,
            args: Tuple,
            env: Dict[str, str],
            stdout: str,
            stderr: str,
        ):
            self._stdout = open(stdout, "w") if stdout else None
            self._stderr = open(stderr, "w") if stderr else None
            # inherit parent environment vars
            env_vars = os.environ.copy()
            env_vars.update(env)

            args_str = (entrypoint, *[str(e) for e in args])
            self.proc: subprocess.Popen = self._popen(args_str, env_vars)

        def _popen(self, args: Tuple, env: Dict[str, str]) -> subprocess.Popen:
            return subprocess.Popen(
                # pyre-fixme[6]: Expected `Union[typing.Sequence[Union[_PathLike[bytes],
                #  _PathLike[str], bytes, str]], bytes, str]` for 1st param but got
                #  `Tuple[str, *Tuple[Any, ...]]`.
                args=args,
                env=env,
                stdout=self._stdout,
                stderr=self._stderr,
            )

        def close(self, death_sig: Optional[signal.Signals] = None) -> None:
            if not death_sig:
                death_sig = _get_default_signal()
            self.proc.send_signal(death_sig)
            if self._stdout:
                self._stdout.close()
            if self._stderr:
                self._stderr.close()

    class SubprocessContext(PContext):
        """
        ``PContext`` holding worker processes invoked as a binary.
        """

        def __init__(
            self,
            name: str,
            entrypoint: str,
            args: Dict[int, Tuple],
            envs: Dict[int, Dict[str, str]],
            stdouts: Dict[int, str],
            stderrs: Dict[int, str],
            tee_stdouts: Dict[int, str],
            tee_stderrs: Dict[int, str],
            error_files: Dict[int, str],
        ):
            super().__init__(
                name,
                entrypoint,
                args,
                envs,
                stdouts,
                stderrs,
                tee_stdouts,
                tee_stderrs,
                error_files,
            )

            # state vector; _vdone[local_rank] -> is local_rank finished or not
            self._running_local_ranks: Set[int] = set(range(self.nprocs))
            self._failures: Dict[int, ProcessFailure] = {}
            self.subprocess_handlers: Dict[int, SubprocessHandler] = {}

        def _start(self):
            if self.subprocess_handlers:
                raise ValueError(
                    "The subprocess handlers already initialized. Most likely the start method got called twice."
                )
            self.subprocess_handlers = {
                local_rank: SubprocessHandler(
                    entrypoint=self.entrypoint,  # type: ignore[arg-type] # entrypoint is always a str
                    args=self.args[local_rank],
                    env=self.envs[local_rank],
                    stdout=self.stdouts[local_rank],
                    stderr=self.stderrs[local_rank],
                )
                for local_rank in range(self.nprocs)
            }

        def _poll(self) -> Optional[RunProcsResult]:
            done_local_ranks = set()
            for local_rank in self._running_local_ranks:
                handler = self.subprocess_handlers[local_rank]
                exitcode = handler.proc.poll()
                if exitcode is not None:
                    done_local_ranks.add(local_rank)
                    if exitcode != 0:  # failed or signaled
                        self._failures[local_rank] = ProcessFailure(
                            local_rank=local_rank,
                            pid=handler.proc.pid,
                            exitcode=exitcode,
                            error_file=self.error_files[local_rank],
                        )
                    # else: --> succeeded; nothing to do

            self._running_local_ranks.difference_update(done_local_ranks)

            # if ALL procs are finished or ANY have failed
            if not self._running_local_ranks or self._failures:
                self.close()  # terminate all running procs
                result = RunProcsResult(
                    failures=self._failures,
                    stdouts=self.stdouts,
                    stderrs=self.stderrs,
                )
                if result.is_failed():
                    first_failure = min(result.failures.values(), key=lambda f: f.timestamp)
                    log.error(
                        "failed (exitcode: %s)"
                        " local_rank: %s (pid: %s)"
                        " of binary: %s",
                        first_failure.exitcode, first_failure.local_rank, first_failure.pid, self.entrypoint
                    )
                else:
                    # Populate return with dummy values. This provides consistency with MultiprocessingHandler
                    result.return_values = {
                        local_rank: None for local_rank in range(self.nprocs)
                    }

                return result
            else:  # there are no failures and procs still running
                return None

        def pids(self) -> Dict[int, int]:
            return {
                local_rank: sh.proc.pid
                for local_rank, sh in self.subprocess_handlers.items()
            }

        def _close(self, death_sig: signal.Signals, timeout: int = 30) -> None:
            if not self.subprocess_handlers:
                return
            for handler in self.subprocess_handlers.values():
                if handler.proc.poll() is None:
                    log.warning(
                        "Sending process %s closing signal %s", handler.proc.pid, death_sig.name
                    )
                    handler.close(death_sig=death_sig)
            end = time.monotonic() + timeout
            for handler in self.subprocess_handlers.values():
                time_to_wait = end - time.monotonic()
                if time_to_wait <= 0:
                    break
                try:
                    handler.proc.wait(time_to_wait)
                except subprocess.TimeoutExpired:
                    # Ignore the timeout expired exception, since
                    # the child process will be forcefully terminated via SIGKILL
                    pass
            for handler in self.subprocess_handlers.values():
                if handler.proc.poll() is None:
                    log.warning(
                        "Unable to shutdown process %s via %s, forcefully exiting via %s",
                        handler.proc.pid, death_sig, _get_kill_signal()
                    )
                    handler.close(death_sig=_get_kill_signal())
                    handler.proc.wait()

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