Exemple #1
0
class StatefulPool(object):
    def __init__(self):
        self.n_parallel = 1
        self.pool = None
        self.queue = None
        self.worker_queue = None
        self.G = SharedGlobal()

    def initialize(self, n_parallel):
        self.n_parallel = n_parallel
        if self.pool is not None:
            print("Warning: terminating existing pool")
            self.pool.terminate()
            self.queue.close()
            self.worker_queue.close()
            self.G = SharedGlobal()
        if n_parallel > 1:
            self.queue = mp.Queue()
            self.worker_queue = mp.Queue()
            self.pool = MemmapingPool(
                self.n_parallel,
                temp_folder="/tmp",
            )

    def run_each(self, runner, args_list=None):
        """
        Run the method on each worker process, and collect the result of execution.
        The runner method will receive 'G' as its first argument, followed by the arguments
        in the args_list, if any
        :return:
        """
        if args_list is None:
            args_list = [tuple()] * self.n_parallel
        assert len(args_list) == self.n_parallel
        if self.n_parallel > 1:
            #return [runner(self.G, *args_list[i]) for i in range(self.n_parallel)]
            results = self.pool.map_async(
                _worker_run_each, [(runner, args) for args in args_list]
            )
            for i in range(self.n_parallel):
                self.worker_queue.get()
            for i in range(self.n_parallel):
                self.queue.put(None)
            return results.get()
        return [runner(self.G, *args_list[0])]

    def run_map(self, runner, args_list):
        if self.n_parallel > 1:
            return self.pool.map(_worker_run_map, [(runner, args) for args in args_list])
        else:
            ret = []
            for args in args_list:
                ret.append(runner(self.G, *args))
            return ret

    def run_imap_unordered(self, runner, args_list):
        if self.n_parallel > 1:
            for x in self.pool.imap_unordered(_worker_run_map, [(runner, args) for args in args_list]):
                yield x
        else:
            for args in args_list:
                yield runner(self.G, *args)

    def run_collect(self, collect_once, threshold, args=None, show_prog_bar=True, multi_task=False):
        """
        Run the collector method using the worker pool. The collect_once method will receive 'G' as
        its first argument, followed by the provided args, if any. The method should return a pair of values.
        The first should be the object to be collected, and the second is the increment to be added.
        This will continue until the total increment reaches or exceeds the given threshold.

        Sample script:

        def collect_once(G):
            return 'a', 1

        stateful_pool.run_collect(collect_once, threshold=3) # => ['a', 'a', 'a']

        :param collector:
        :param threshold:
        :return:
        """
        if args is None:
            args = tuple()
        if self.pool and multi_task:
            manager = mp.Manager()
            counter = manager.Value('i', 0)
            lock = manager.RLock()

            inputs = [(collect_once, counter, lock, threshold, arg) for arg in args]
            results = self.pool.map_async(
                _worker_run_collect,
                inputs,
            )
            if show_prog_bar:
                pbar = ProgBarCounter(threshold)
            last_value = 0
            while True:
                time.sleep(0.1)
                with lock:
                    if counter.value >= threshold:
                        if show_prog_bar:
                            pbar.stop()
                        break
                    if show_prog_bar:
                        pbar.inc(counter.value - last_value)
                    last_value = counter.value
            finished_results = results.get()
            # TODO - for some reason this is buggy.
            return {i:finished_results[i] for i in range(len(finished_results))}
        elif multi_task:
            assert False # not supported
        elif self.pool:
            manager = mp.Manager()
            counter = manager.Value('i', 0)
            lock = manager.RLock()
            results = self.pool.map_async(
                _worker_run_collect,
                [(collect_once, counter, lock, threshold, args)] * self.n_parallel
            )
            if show_prog_bar:
                pbar = ProgBarCounter(threshold)
            last_value = 0
            while True:
                time.sleep(0.1)
                with lock:
                    if counter.value >= threshold:
                        if show_prog_bar:
                            pbar.stop()
                        break
                    if show_prog_bar:
                        pbar.inc(counter.value - last_value)
                    last_value = counter.value
            return sum(results.get(), [])
        else:
            count = 0
            results = []
            if show_prog_bar:
                pbar = ProgBarCounter(threshold)
            while count < threshold:
                result, inc = collect_once(self.G, *args)
                results.append(result)
                count += inc
                if show_prog_bar:
                    pbar.inc(inc)
            if show_prog_bar:
                pbar.stop()
            return results
class StatefulPool:
    def __init__(self):
        self.n_parallel = 1
        self.pool = None
        self.queue = None
        self.worker_queue = None
        self.G = SharedGlobal()

    def initialize(self, n_parallel):
        self.n_parallel = n_parallel
        if self.pool is not None:
            print("Warning: terminating existing pool")
            self.pool.terminate()
            self.queue.close()
            self.worker_queue.close()
            self.G = SharedGlobal()
        if n_parallel > 1:
            self.queue = mp.Queue()
            self.worker_queue = mp.Queue()
            self.pool = MemmapingPool(
                self.n_parallel,
                temp_folder="/tmp",
            )

    def terminate(self):
        if self.pool:
            self.pool.terminate()

    def run_each(self, runner, args_list=None):
        """
        Run the method on each worker process, and collect the result of
        execution.

        The runner method will receive 'g' as its first argument, followed
        by the arguments in the args_list, if any
        :return:
        """
        assert not inspect.ismethod(runner), (
            "run_each() cannot run a class method. Please ensure that runner "
            "is a function with the prototype def foo(g, ...), where g is an "
            "object of type garage.sampler.stateful_pool.SharedGlobal")

        if args_list is None:
            args_list = [tuple()] * self.n_parallel
        assert len(args_list) == self.n_parallel
        if self.n_parallel > 1:
            results = self.pool.map_async(_worker_run_each,
                                          [(runner, args)
                                           for args in args_list])
            for i in range(self.n_parallel):
                self.worker_queue.get()
            for i in range(self.n_parallel):
                self.queue.put(None)
            return results.get()
        return [runner(self.G, *args_list[0])]

    def run_map(self, runner, args_list):
        assert not inspect.ismethod(runner), (
            "run_map() cannot run a class method. Please ensure that runner "
            "is a function with the prototype 'def foo(g, ...)', where g is "
            "an object of type garage.sampler.stateful_pool.SharedGlobal")

        if self.n_parallel > 1:
            return self.pool.map(_worker_run_map,
                                 [(runner, args) for args in args_list])
        else:
            ret = []
            for args in args_list:
                ret.append(runner(self.G, *args))
            return ret

    def run_imap_unordered(self, runner, args_list):
        assert not inspect.ismethod(runner), (
            "run_imap_unordered() cannot run a class method. Please ensure "
            "that runner is a function with the prototype 'def foo(g, ...)', "
            "where g is an object of type "
            "garage.sampler.stateful_pool.SharedGlobal")

        if self.n_parallel > 1:
            for x in self.pool.imap_unordered(_worker_run_map,
                                              [(runner, args)
                                               for args in args_list]):
                yield x
        else:
            for args in args_list:
                yield runner(self.G, *args)

    def run_collect(self,
                    collect_once,
                    threshold,
                    args=None,
                    show_prog_bar=True):
        """
        Run the collector method using the worker pool. The collect_once method
        will receive 'g' as its first argument, followed by the provided args,
        if any. The method should return a pair of values. The first should be
        the object to be collected, and the second is the increment to be
        added.
        This will continue until the total increment reaches or exceeds the
        given threshold.

        Sample script:

        def collect_once(g):
            return 'a', 1

        stateful_pool.run_collect(collect_once, threshold=3)
        # should return ['a', 'a', 'a']

        :param collector:
        :param threshold:
        :return:
        """
        assert not inspect.ismethod(collect_once), (
            "run_collect() cannot run a class method. Please ensure that "
            "collect_once is a function with the prototype 'def foo(g, ...)', "
            "where g is an object of type "
            "garage.sampler.stateful_pool.SharedGlobal")

        if args is None:
            args = tuple()
        if self.pool:
            manager = mp.Manager()
            counter = manager.Value('i', 0)
            lock = manager.RLock()
            results = self.pool.map_async(
                _worker_run_collect,
                [(collect_once, counter, lock, threshold, args)] *
                self.n_parallel)
            if show_prog_bar:
                pbar = ProgBarCounter(threshold)
            last_value = 0
            while True:
                time.sleep(0.1)
                with lock:
                    if counter.value >= threshold:
                        if show_prog_bar:
                            pbar.stop()
                        break
                    if show_prog_bar:
                        pbar.inc(counter.value - last_value)
                    last_value = counter.value
            return sum(results.get(), [])
        else:
            count = 0
            results = []
            if show_prog_bar:
                pbar = ProgBarCounter(threshold)
            while count < threshold:
                result, inc = collect_once(self.G, *args)
                results.append(result)
                count += inc
                if show_prog_bar:
                    pbar.inc(inc)
            if show_prog_bar:
                pbar.stop()
            return results
        return []