未验证 提交 831a3e62 编写于 作者: J Jiabin Yang 提交者: GitHub

Add install check for multigpu (#18323)

* test=develop, add_install_check_for_multigpu

* test=develop, refine code to use cuda_devices
上级 f88e07a0
......@@ -12,7 +12,8 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from .framework import Program, program_guard, unique_name, default_startup_program
import os
from .framework import Program, program_guard, unique_name, cuda_places, cpu_places
from .param_attr import ParamAttr
from .initializer import Constant
from . import layers
......@@ -24,7 +25,6 @@ from . import core
from . import compiler
import logging
import numpy as np
import os
__all__ = ['run_check']
......@@ -48,39 +48,43 @@ def run_check():
This func should not be called only if you need to verify installation
'''
print("Running Verify Fluid Program ... ")
use_cuda = False if not core.is_compiled_with_cuda() else True
place = core.CPUPlace() if not core.is_compiled_with_cuda(
) else core.CUDAPlace(0)
np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
if use_cuda:
if core.get_cuda_device_count() > 1:
os.environ['CUDA_VISIBLE_DEVICES'] = "0,1"
device_list = []
if core.is_compiled_with_cuda():
try:
core.get_cuda_device_count()
except Exception as e:
logging.warning(
"You are using GPU version Paddle Fluid, But Your CUDA Device is not set properly"
"\n Original Error is {}".format(e))
return 0
device_list = cuda_places()
else:
os.environ['CUDA_VISIBLE_DEVICES'] = "0"
device_list = [core.CPUPlace(), core.CPUPlace()]
np_inp_single = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
inp = []
for i in range(len(device_list)):
inp.append(np_inp_single)
np_inp_muti = np.array(inp)
np_inp_muti = np_inp_muti.reshape(len(device_list), 2, 2)
def test_parallerl_exe():
train_prog = Program()
startup_prog = Program()
scope = core.Scope()
if not use_cuda:
os.environ['CPU_NUM'] = "2"
with executor.scope_guard(scope):
with program_guard(train_prog, startup_prog):
with unique_name.guard():
places = []
build_strategy = compiler.BuildStrategy()
build_strategy.enable_inplace = True
build_strategy.memory_optimize = True
inp = layers.data(
name="inp", shape=[2, 2], append_batch_size=False)
inp = layers.data(name="inp", shape=[2, 2])
simple_layer = SimpleLayer("simple_layer")
out = simple_layer(inp)
exe = executor.Executor(place)
if use_cuda:
places = [core.CUDAPlace(0), core.CUDAPlace(1)]
else:
places = [core.CPUPlace(), core.CPUPlace()]
exe = executor.Executor(
core.CUDAPlace(0) if core.is_compiled_with_cuda() and
(core.get_cuda_device_count() > 0) else core.CPUPlace())
loss = layers.mean(out)
loss.persistable = True
optimizer.SGD(learning_rate=0.01).minimize(loss)
......@@ -89,19 +93,17 @@ def run_check():
train_prog).with_data_parallel(
build_strategy=build_strategy,
loss_name=loss.name,
places=places)
places=device_list)
exe.run(startup_prog)
exe.run(compiled_prog,
feed={inp.name: np_inp},
feed={inp.name: np_inp_muti},
fetch_list=[loss.name])
def test_simple_exe():
train_prog = Program()
startup_prog = Program()
scope = core.Scope()
if not use_cuda:
os.environ['CPU_NUM'] = "1"
with executor.scope_guard(scope):
with program_guard(train_prog, startup_prog):
with unique_name.guard():
......@@ -111,11 +113,11 @@ def run_check():
out0 = simple_layer0(inp0)
param_grads = backward.append_backward(
out0, parameter_list=[simple_layer0._fc1._w.name])[0]
exe0 = executor.Executor(core.CPUPlace()
if not core.is_compiled_with_cuda()
else core.CUDAPlace(0))
exe0 = executor.Executor(
core.CUDAPlace(0) if core.is_compiled_with_cuda() and
(core.get_cuda_device_count() > 0) else core.CPUPlace())
exe0.run(startup_prog)
exe0.run(feed={inp0.name: np_inp},
exe0.run(feed={inp0.name: np_inp_single},
fetch_list=[out0.name, param_grads[1].name])
test_simple_exe()
......@@ -130,7 +132,7 @@ def run_check():
except Exception as e:
logging.warning(
"Your Paddle Fluid has some problem with multiple GPU. This may be caused by:"
"\n 1. There is only 1 GPU visible on your Device;"
"\n 1. There is only 1 or 0 GPU visible on your Device;"
"\n 2. No.1 or No.2 GPU or both of them are occupied now"
"\n 3. Wrong installation of NVIDIA-NCCL2, please follow instruction on https://github.com/NVIDIA/nccl-tests "
"\n to test your NCCL, or reinstall it following https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html"
......@@ -139,4 +141,4 @@ def run_check():
print("\n Original Error is: {}".format(e))
print(
"Your Paddle Fluid is installed successfully ONLY for SINGLE GPU or CPU! "
"\n Let's start deep Learning with Paddle Fluid now!")
"\n Let's start deep Learning with Paddle Fluid now")
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