提交 207a3463 编写于 作者: M Megvii Engine Team

chore(mge): run get_device_count("gpu") in subprocess

GitOrigin-RevId: 0f0dc001cfc45fc0d04de1a86c27f8bba8185d6b
上级 869a0327
......@@ -181,11 +181,6 @@ def synchronized(func: Callable):
return wrapper
def _get_device_count_worker(queue, device_type):
num = get_device_count(device_type)
queue.put(num)
def _check_device_initialized(device_type: str, rank: int):
try:
test = Tensor(1, device=(device_type + str(rank)))
......@@ -198,19 +193,6 @@ def _check_device_initialized(device_type: str, rank: int):
raise RuntimeError(errmsg)
def get_device_count_by_fork(device_type: str):
"""
Get device count in fork thread.
See https://stackoverflow.com/questions/22950047/cuda-initialization-error-after-fork
for more information.
"""
q = mp.Queue()
p = mp.Process(target=_get_device_count_worker, args=(q, device_type))
p.start()
p.join()
return q.get()
def bcast_list_(inps: list, group: Group = WORLD):
"""
Broadcast tensors between given group.
......
......@@ -13,9 +13,10 @@ import queue
from .. import _exit
from ..core._imperative_rt.core2 import full_sync
from ..device import get_device_count
from ..logger import get_logger
from .group import _set_machine_ranks, group_barrier, init_process_group
from .helper import _check_device_initialized, get_device_count_by_fork
from .helper import _check_device_initialized
from .server import Client, Server
WARN_SUBPROCESS_EXIT_WITHOUT_RETURN = (
......@@ -91,9 +92,7 @@ class launcher:
backend="auto",
):
self.func = func
self.n_gpus = (
n_gpus if n_gpus is not None else get_device_count_by_fork(device_type)
)
self.n_gpus = n_gpus if n_gpus is not None else get_device_count(device_type)
self.world_size = world_size if world_size is not None else self.n_gpus
self.rank_start = rank_start
self.master_ip = master_ip
......
......@@ -1188,11 +1188,11 @@ def copy(inp, device=None):
import numpy as np
import platform
from megengine import tensor
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
import megengine.functional as F
x = tensor([1, 2, 3], np.int32)
if 1 == get_device_count_by_fork("gpu"):
if 1 == get_device_count("gpu"):
y = F.copy(x, "cpu1")
print(y.numpy())
else:
......
......@@ -15,7 +15,7 @@ import megengine.functional
import megengine.module
from megengine import Parameter
from megengine.core._imperative_rt.core2 import sync
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
from megengine.experimental.autograd import (
disable_higher_order_directive,
enable_higher_order_directive,
......@@ -25,7 +25,7 @@ from megengine.module import Linear, Module
sys.path.append(os.path.join(os.path.dirname(__file__), "helpers"))
_ngpu = get_device_count_by_fork("gpu")
_ngpu = get_device_count("gpu")
@pytest.fixture(autouse=True)
......
......@@ -16,7 +16,6 @@ import megengine.autodiff as ad
import megengine.distributed as dist
import megengine.optimizer as optimizer
from megengine import Parameter, tensor
from megengine.distributed.helper import get_device_count_by_fork
from megengine.module import Module
from megengine.optimizer import SGD
......
......@@ -18,7 +18,6 @@ import megengine.functional as F
import megengine.module as M
import megengine.optimizer as optim
from megengine.autodiff import GradManager
from megengine.distributed.helper import get_device_count_by_fork
from megengine.jit import trace
......
......@@ -20,7 +20,6 @@ from megengine.core._imperative_rt import CompNode, TensorAttr, imperative
from megengine.core._imperative_rt.core2 import TensorWeakRef, apply, sync
from megengine.core.autodiff.grad import Grad
from megengine.core.ops.builtin import Elemwise, Identity
from megengine.distributed.helper import get_device_count_by_fork
from megengine.functional.distributed import remote_recv, remote_send
......
......@@ -31,7 +31,7 @@ from megengine.core.tensor.dtype import (
quint4,
quint8,
)
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
from megengine.tensor import Tensor
......@@ -184,8 +184,7 @@ def test_dtype_int4_ffi_handle():
@pytest.mark.skipif(
get_device_count_by_fork("gpu") != 0,
reason="TypeCvt to quint4 is not supported on GPU",
get_device_count("gpu") != 0, reason="TypeCvt to quint4 is not supported on GPU",
)
def test_quint4_typecvt():
device = "xpux"
......
......@@ -17,11 +17,7 @@ import megengine as mge
import megengine.distributed as dist
from megengine.core.ops.builtin import CollectiveComm, ParamPackConcat, ParamPackSplit
from megengine.device import get_default_device
from megengine.distributed.helper import (
get_device_count_by_fork,
param_pack_concat,
param_pack_split,
)
from megengine.distributed.helper import param_pack_concat, param_pack_split
def _assert_q_empty(q):
......
......@@ -22,8 +22,7 @@ from megengine import Parameter, Tensor, is_cuda_available, tensor
from megengine.core._trace_option import use_symbolic_shape
from megengine.core.autodiff.grad import Grad
from megengine.core.tensor.utils import make_shape_tuple
from megengine.distributed.helper import get_device_count_by_fork
from megengine.jit import trace
from megengine.device import get_device_count
def test_where():
......@@ -613,7 +612,7 @@ def test_nms():
@pytest.mark.skipif(
get_device_count_by_fork("gpu") > 0, reason="cuda does not support nchw int8"
get_device_count("gpu") > 0, reason="cuda does not support nchw int8"
)
def test_conv_bias():
inp_scale = 1.5
......@@ -715,9 +714,7 @@ def test_conv_bias():
run(10, 36, 8, 46, 26, 2, 2, 2, 1, 1, 2, True, "relu")
@pytest.mark.skipif(
get_device_count_by_fork("gpu") > 0, reason="no int8 algorithm on cuda"
)
@pytest.mark.skipif(get_device_count("gpu") > 0, reason="no int8 algorithm on cuda")
def test_batch_conv_bias():
inp_scale = 1.5
w_scale = 2.5
......
......@@ -16,7 +16,6 @@ import megengine.distributed as dist
from megengine import Parameter, tensor
from megengine.core._imperative_rt.core2 import sync
from megengine.device import get_default_device, set_default_device
from megengine.distributed.helper import get_device_count_by_fork
from megengine.functional.distributed import (
all_gather,
all_reduce_max,
......
......@@ -18,7 +18,6 @@ from megengine import tensor
from megengine.core._trace_option import use_symbolic_shape
from megengine.core.tensor import megbrain_graph as G
from megengine.core.tensor.utils import astensor1d
from megengine.distributed.helper import get_device_count_by_fork
from megengine.jit import trace
from megengine.utils.network import Network, set_symbolic_shape
from megengine.utils.network_node import VarNode
......
......@@ -16,7 +16,6 @@ import megengine as mge
import megengine.distributed as dist
from megengine import Tensor
from megengine.core._trace_option import use_symbolic_shape
from megengine.distributed.helper import get_device_count_by_fork
from megengine.module import BatchNorm1d, BatchNorm2d, SyncBatchNorm
_assert_allclose = functools.partial(np.testing.assert_allclose, atol=5e-6, rtol=5e-6)
......
......@@ -6,7 +6,7 @@ import pytest
import megengine.utils.comp_graph_tools as cgtools
from megengine import jit, tensor
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
from megengine.functional import expand_dims
from megengine.module import (
BatchMatMulActivation,
......@@ -101,9 +101,7 @@ def test_qat_conv():
np.testing.assert_allclose(normal_outputs.numpy(), qat_outputs.numpy())
@pytest.mark.skipif(
get_device_count_by_fork("gpu") > 0, reason="no int8 algorithm on cuda"
)
@pytest.mark.skipif(get_device_count("gpu") > 0, reason="no int8 algorithm on cuda")
def test_qat_batchmatmul_activation():
batch = 4
in_features = 8
......
......@@ -13,7 +13,7 @@ import pytest
import megengine as mge
import megengine.distributed as dist
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
from megengine.quantization import QuantMode, create_qparams
from megengine.quantization.observer import (
ExponentialMovingAverageObserver,
......@@ -78,7 +78,7 @@ def test_passive_observer():
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_sync_min_max_observer():
word_size = get_device_count_by_fork("gpu")
word_size = get_device_count("gpu")
x = np.random.rand(3 * word_size, 3, 3, 3).astype("float32")
np_min, np_max = x.min(), x.max()
......@@ -96,7 +96,7 @@ def test_sync_min_max_observer():
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_sync_exponential_moving_average_observer():
word_size = get_device_count_by_fork("gpu")
word_size = get_device_count("gpu")
t = np.random.rand()
x1 = np.random.rand(3 * word_size, 3, 3, 3).astype("float32")
x2 = np.random.rand(3 * word_size, 3, 3, 3).astype("float32")
......
......@@ -12,7 +12,7 @@ import pytest
import megengine as mge
import megengine.functional as F
from megengine.core.tensor import dtype
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
from megengine.functional.elemwise import _elemwise_multi_type, _elwise
from megengine.quantization import QuantMode, create_qparams
......@@ -68,7 +68,7 @@ def test_elemwise(kind):
@pytest.mark.skipif(
get_device_count_by_fork("gpu") > 0, reason="cuda does not support nchw int8"
get_device_count("gpu") > 0, reason="cuda does not support nchw int8"
)
def test_conv_bias():
inp_scale = np.float32(np.random.rand() + 1)
......
......@@ -26,12 +26,12 @@ from megengine.core.ops.builtin import (
PoissonRNG,
UniformRNG,
)
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count
from megengine.random import RNG, seed, uniform
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 2, reason="xpu counts need > 2",
get_device_count("xpu") <= 2, reason="xpu counts need > 2",
)
def test_gaussian_op():
shape = (
......@@ -61,7 +61,7 @@ def test_gaussian_op():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 2, reason="xpu counts need > 2",
get_device_count("xpu") <= 2, reason="xpu counts need > 2",
)
def test_uniform_op():
shape = (
......@@ -89,7 +89,7 @@ def test_uniform_op():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 2, reason="xpu counts need > 2",
get_device_count("xpu") <= 2, reason="xpu counts need > 2",
)
def test_gamma_op():
_shape, _scale = 2, 0.8
......@@ -117,7 +117,7 @@ def test_gamma_op():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 2, reason="xpu counts need > 2",
get_device_count("xpu") <= 2, reason="xpu counts need > 2",
)
def test_beta_op():
_alpha, _beta = 2, 0.8
......@@ -148,7 +148,7 @@ def test_beta_op():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 2, reason="xpu counts need > 2",
get_device_count("xpu") <= 2, reason="xpu counts need > 2",
)
def test_poisson_op():
lam = F.full([8, 9, 11, 12], value=2, dtype="float32")
......@@ -171,7 +171,7 @@ def test_poisson_op():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 2, reason="xpu counts need > 2",
get_device_count("xpu") <= 2, reason="xpu counts need > 2",
)
def test_permutation_op():
n = 1000
......@@ -205,7 +205,7 @@ def test_permutation_op():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 1, reason="xpu counts need > 1",
get_device_count("xpu") <= 1, reason="xpu counts need > 1",
)
def test_UniformRNG():
m1 = RNG(seed=111, device="xpu0")
......@@ -233,7 +233,7 @@ def test_UniformRNG():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 1, reason="xpu counts need > 1",
get_device_count("xpu") <= 1, reason="xpu counts need > 1",
)
def test_NormalRNG():
m1 = RNG(seed=111, device="xpu0")
......@@ -262,7 +262,7 @@ def test_NormalRNG():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 1, reason="xpu counts need > 1",
get_device_count("xpu") <= 1, reason="xpu counts need > 1",
)
def test_GammaRNG():
m1 = RNG(seed=111, device="xpu0")
......@@ -295,7 +295,7 @@ def test_GammaRNG():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 1, reason="xpu counts need > 1",
get_device_count("xpu") <= 1, reason="xpu counts need > 1",
)
def test_BetaRNG():
m1 = RNG(seed=111, device="xpu0")
......@@ -330,7 +330,7 @@ def test_BetaRNG():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 1, reason="xpu counts need > 1",
get_device_count("xpu") <= 1, reason="xpu counts need > 1",
)
def test_PoissonRNG():
m1 = RNG(seed=111, device="xpu0")
......@@ -359,7 +359,7 @@ def test_PoissonRNG():
@pytest.mark.skipif(
get_device_count_by_fork("xpu") <= 1, reason="xpu counts need > 1",
get_device_count("xpu") <= 1, reason="xpu counts need > 1",
)
def test_PermutationRNG():
m1 = RNG(seed=111, device="xpu0")
......
......@@ -13,8 +13,7 @@ import megengine.random as rand
from megengine.core._imperative_rt.core2 import apply
from megengine.core._wrap import Device
from megengine.core.ops import builtin
from megengine.device import is_cuda_available
from megengine.distributed.helper import get_device_count_by_fork
from megengine.device import get_device_count, is_cuda_available
from megengine.functional.external import tensorrt_runtime_opr
from megengine.jit.tracing import trace
from megengine.tensor import Tensor
......@@ -273,7 +272,7 @@ def test_deformable_ps_roi_pooling():
@pytest.mark.skipif(
get_device_count_by_fork("gpu") > 0,
get_device_count("gpu") > 0,
reason="does not support int8 when gpu compute capability less than 6.1",
)
def test_convbias():
......
......@@ -27,8 +27,14 @@ using namespace mgb;
#include <thread>
#include <cuda.h>
#include <cuda_runtime.h>
#ifdef __unix__
#include <unistd.h>
#include <sys/wait.h>
#endif
using CudaCompNodeImpl = CudaCompNode::CompNodeImpl;
namespace {
......@@ -700,19 +706,90 @@ void CudaCompNode::EventImpl::do_device_wait_by(Impl* cn_impl) {
/* ===================== CudaCompNode static methods ===================== */
namespace {
#ifndef __unix__
CUresult get_device_count_forksafe(int* pcnt) {
cuInit(0);
return cuDeviceGetCount(pcnt);
}
#else
struct RAIICloseFD : NonCopyableObj {
int m_fd = -1;
RAIICloseFD(int fd) : m_fd(fd) {}
~RAIICloseFD() {close();}
void close() {
if (m_fd != -1) {
::close(m_fd);
m_fd = -1;
}
}
};
// an implementation that does not call cuInit
CUresult get_device_count_forksafe(int* pcnt) {
auto err = cuDeviceGetCount(pcnt);
if (err != CUDA_ERROR_NOT_INITIALIZED) return err;
// cuInit not called, call it in child process
int fd[2];
mgb_assert(pipe(fd) == 0, "pipe() failed");
int fdr = fd[0], fdw = fd[1];
RAIICloseFD fdr_guard(fdr);
RAIICloseFD fdw_guard(fdw);
auto cpid = fork();
mgb_assert(cpid != -1, "fork() failed");
if (cpid == 0) {
fdr_guard.close();
do {
err = cuInit(0);
if (err != CUDA_SUCCESS) break;
err = cuDeviceGetCount(pcnt);
} while (0);
auto sz = write(fdw, &err, sizeof(err));
if (sz == sizeof(err) && err == CUDA_SUCCESS) {
sz = write(fdw, pcnt, sizeof(*pcnt));
}
fdw_guard.close();
std::quick_exit(0);
}
fdw_guard.close();
auto sz = read(fdr, &err, sizeof(err));
mgb_assert(sz == sizeof(err), "failed to read error code from child");
if (err == CUDA_SUCCESS) {
sz = read(fdr, pcnt, sizeof(*pcnt));
mgb_assert(sz == sizeof(*pcnt), "failed to read device count from child");
return err;
}
// try again, maybe another thread called cuInit while we fork
auto err2 = cuDeviceGetCount(pcnt);
if (err2 == CUDA_SUCCESS) return err2;
if (err2 == CUDA_ERROR_NOT_INITIALIZED) return err;
return err2;
}
#endif
const char* cu_get_error_string(CUresult err) {
const char* ret = nullptr;
cuGetErrorString(err, &ret);
if (!ret) ret = "unknown cuda error";
return ret;
}
} // namespace
bool CudaCompNode::available() {
static int result = -1;
static Spinlock mtx;
MGB_LOCK_GUARD(mtx);
if (result == -1) {
int ndev = -1;
auto err = cudaGetDeviceCount(&ndev);
result = err == cudaSuccess && ndev > 0;
auto err = get_device_count_forksafe(&ndev);
result = err == CUDA_SUCCESS && ndev > 0;
if (!result) {
mgb_log_warn("cuda unavailable: %s(%d) ndev=%d",
cudaGetErrorString(err), static_cast<int>(err), ndev);
cu_get_error_string(err), static_cast<int>(err), ndev);
}
if (err == cudaErrorInitializationError) {
if (err == CUDA_ERROR_NOT_INITIALIZED) {
mgb_throw(std::runtime_error, "cuda initialization error.");
}
}
......@@ -857,11 +934,11 @@ size_t CudaCompNode::get_device_count(bool warn) {
static Spinlock mtx;
MGB_LOCK_GUARD(mtx);
if (cnt == -1) {
auto err = cudaGetDeviceCount(&cnt);
if (err != cudaSuccess) {
auto err = get_device_count_forksafe(&cnt);
if (err != CUDA_SUCCESS) {
if (warn)
mgb_log_error("cudaGetDeviceCount failed: %s (err %d)",
cudaGetErrorString(err), int(err));
cu_get_error_string(err), int(err));
cnt = 0;
}
mgb_assert(cnt >= 0);
......
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