test_distributed.py 6.7 KB
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# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
import multiprocessing as mp
import platform
import queue

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import numpy as np
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import pytest

import megengine as mge
import megengine.distributed as dist
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from megengine.core.ops.builtin import CollectiveComm, ParamPackConcat, ParamPackSplit
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from megengine.distributed.helper import (
    get_device_count_by_fork,
    param_pack_concat,
    param_pack_split,
)
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def _assert_q_empty(q):
    try:
        res = q.get(timeout=1)
    except Exception as e:
        assert isinstance(e, queue.Empty)
    else:
        assert False, "queue is not empty"


def _assert_q_val(q, val):
    ret = q.get()
    assert ret == val


@pytest.mark.skipif(
    platform.system() == "Darwin", reason="do not imp GPU mode at macos now"
)
@pytest.mark.skipif(
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    platform.system() == "Windows", reason="windows disable MGB_ENABLE_OPR_MM"
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)
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@pytest.mark.skipif(get_device_count_by_fork("gpu") < 2, reason="need more gpu device")
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@pytest.mark.isolated_distributed
def test_init_process_group():
    world_size = 2
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    server = dist.Server()
    port = server.py_server_port
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    def worker(rank, backend):
        dist.init_process_group("localhost", port, world_size, rank, rank, backend)
        assert dist.is_distributed() == True
        assert dist.get_rank() == rank
        assert dist.get_world_size() == world_size
        assert dist.get_backend() == backend

        py_server_addr = dist.get_py_server_addr()
        assert py_server_addr[0] == "localhost"
        assert py_server_addr[1] == port

        mm_server_addr = dist.get_mm_server_addr()
        assert mm_server_addr[0] == "localhost"
        assert mm_server_addr[1] > 0

        assert isinstance(dist.get_client(), dist.Client)

    def check(backend):
        procs = []
        for rank in range(world_size):
            p = mp.Process(target=worker, args=(rank, backend))
            p.start()
            procs.append(p)

        for p in procs:
            p.join(20)
            assert p.exitcode == 0

    check("nccl")


@pytest.mark.skipif(
    platform.system() == "Darwin", reason="do not imp GPU mode at macos now"
)
@pytest.mark.skipif(
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    platform.system() == "Windows", reason="windows disable MGB_ENABLE_OPR_MM"
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)
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@pytest.mark.skipif(get_device_count_by_fork("gpu") < 2, reason="need more gpu device")
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@pytest.mark.isolated_distributed
def test_new_group():
    world_size = 3
    ranks = [2, 0]

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    @dist.launcher
    def worker():
        rank = dist.get_rank()
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        if rank in ranks:
            group = dist.new_group(ranks)
            assert group.size == 2
            assert group.key == "2,0"
            assert group.rank == ranks.index(rank)
            assert group.comp_node == "gpu{}:2".format(rank)

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    worker()
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@pytest.mark.skipif(
    platform.system() == "Darwin", reason="do not imp GPU mode at macos now"
)
@pytest.mark.skipif(
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    platform.system() == "Windows", reason="windows disable MGB_ENABLE_OPR_MM"
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)
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@pytest.mark.skipif(get_device_count_by_fork("gpu") < 2, reason="need more gpu device")
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@pytest.mark.isolated_distributed
def test_group_barrier():
    world_size = 2
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    server = dist.Server()
    port = server.py_server_port
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    def worker(rank, q):
        dist.init_process_group("localhost", port, world_size, rank, rank)
        dist.group_barrier()
        if rank == 0:
            dist.group_barrier()
            q.put(0)  # to be observed in rank 1
        else:
            _assert_q_empty(q)  # q.put(0) is not executed in rank 0
            dist.group_barrier()
            _assert_q_val(q, 0)  # q.put(0) executed in rank 0

    Q = mp.Queue()
    procs = []
    for rank in range(world_size):
        p = mp.Process(target=worker, args=(rank, Q))
        p.start()
        procs.append(p)

    for p in procs:
        p.join(20)
        assert p.exitcode == 0


@pytest.mark.skipif(
    platform.system() == "Darwin", reason="do not imp GPU mode at macos now"
)
@pytest.mark.skipif(
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    platform.system() == "Windows", reason="windows disable MGB_ENABLE_OPR_MM"
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)
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@pytest.mark.skipif(get_device_count_by_fork("gpu") < 2, reason="need more gpu device")
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@pytest.mark.isolated_distributed
def test_synchronized():
    world_size = 2
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    server = dist.Server()
    port = server.py_server_port
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    @dist.synchronized
    def func(rank, q):
        q.put(rank)

    def worker(rank, q):
        dist.init_process_group("localhost", port, world_size, rank, rank)
        dist.group_barrier()
        if rank == 0:
            func(0, q)  # q.put(0)
            q.put(2)
        else:
            _assert_q_val(q, 0)  # func executed in rank 0
            _assert_q_empty(q)  # q.put(2) is not executed
            func(1, q)
            _assert_q_val(
                q, 1
            )  # func in rank 1 executed earlier than q.put(2) in rank 0
            _assert_q_val(q, 2)  # q.put(2) executed in rank 0

    Q = mp.Queue()
    procs = []
    for rank in range(world_size):
        p = mp.Process(target=worker, args=(rank, Q))
        p.start()
        procs.append(p)

    for p in procs:
        p.join(20)
        assert p.exitcode == 0
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@pytest.mark.skipif(
    platform.system() == "Darwin", reason="do not imp GPU mode at macos now"
)
@pytest.mark.skipif(
    platform.system() == "Windows", reason="windows disable MGB_ENABLE_OPR_MM"
)
@pytest.mark.skipif(get_device_count_by_fork("gpu") < 2, reason="need more gpu device")
@pytest.mark.isolated_distributed
def test_user_set_get():
    world_size = 2

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    @dist.launcher
    def worker():
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        # set in race condition
        dist.get_client().user_set("foo", 1)
        # get in race condition
        ret = dist.get_client().user_get("foo")
        assert ret == 1

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    worker()
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def test_oprmm_hashable():
    lhs = (CollectiveComm(), ParamPackConcat(), ParamPackSplit())
    rhs = (CollectiveComm(), ParamPackConcat(), ParamPackSplit())
    assert lhs == rhs
    assert hash(lhs) == hash(rhs)
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def test_param_pack_split():
    a = mge.Tensor(np.ones((10,), np.int32))
    b, c = param_pack_split(a, [0, 1, 1, 10], [(1,), (3, 3)])
    assert np.allclose(b.numpy(), a.numpy()[1])
    assert np.allclose(c.numpy(), a.numpy()[1:].reshape(3, 3))


def test_param_pack_concat():
    a = mge.Tensor(np.ones((1,), np.int32))
    b = mge.Tensor(np.ones((3, 3), np.int32))
    offsets_val = [0, 1, 1, 10]
    offsets = mge.Tensor(offsets_val, np.int32)
    c = param_pack_concat([a, b], offsets, offsets_val)
    assert np.allclose(np.concatenate([a.numpy(), b.numpy().flatten()]), c.numpy())