wehub-resource-sync
203 lines
7.1 KiB
Python
203 lines
7.1 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import ctypes
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import unittest
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from op_test import get_device, get_device_class, is_custom_device
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import paddle
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from paddle import base
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from paddle.base import core, framework
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class TestSetDeviceEagerSwitch(unittest.TestCase):
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"""Test that paddle.set_device immediately switches the underlying
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hardware device (e.g. cudaSetDevice) without creating any tensor."""
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def _get_cuda_runtime_device_id(self):
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"""Use ctypes to call cudaGetDevice directly from CUDA runtime."""
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try:
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lib_name = 'libcudart.so'
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cudart = ctypes.CDLL(lib_name)
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except:
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return None
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device = ctypes.c_int(-1)
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cudart.cudaGetDevice(ctypes.byref(device))
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return device.value
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def test_set_device_switches_cuda_device_immediately(self):
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"""After set_device('gpu:1'), cudaGetDevice should return 1
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immediately, even before creating any tensor."""
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if not core.is_compiled_with_cuda() or core.get_cuda_device_count() < 2:
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return
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paddle.disable_static()
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paddle.device.set_device('gpu:1')
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runtime_device = self._get_cuda_runtime_device_id()
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if runtime_device is None:
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return
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self.assertEqual(
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runtime_device,
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1,
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msg=f"Expected cudaGetDevice()=1 after set_device('gpu:1'), "
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f"but got {runtime_device}",
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)
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paddle.device.set_device('gpu:0')
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runtime_device = self._get_cuda_runtime_device_id()
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self.assertEqual(
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runtime_device,
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0,
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msg=f"Expected cudaGetDevice()=0 after set_device('gpu:0'), "
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f"but got {runtime_device}",
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)
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class TestStaticDeviceManage(unittest.TestCase):
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def _test_device(self, device_name, device_class):
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paddle.enable_static()
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paddle.set_device(device_name)
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out1 = paddle.zeros(shape=[1, 3], dtype='float32')
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out2 = paddle.ones(shape=[1, 3], dtype='float32')
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out3 = paddle.concat(x=[out1, out2], axis=0)
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exe = paddle.static.Executor()
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exe.run(paddle.base.default_startup_program())
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res = exe.run(fetch_list=[out3])
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device = paddle.get_device()
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self.assertEqual(isinstance(exe.place, device_class), True)
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self.assertEqual(device, device_name)
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paddle.disable_static()
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def test_cpu_device(self):
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self._test_device("cpu", core.CPUPlace)
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def test_gpu_device(self):
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if core.is_compiled_with_cuda():
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self._test_device("gpu:0", get_device_class())
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def test_xpu_device(self):
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if core.is_compiled_with_xpu():
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self._test_device("xpu:0", core.XPUPlace)
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def test_custom_device(self):
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if is_custom_device():
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self._test_device(get_device(True), get_device_class())
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class TestImperativeDeviceManage(unittest.TestCase):
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def test_cpu(self):
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with base.dygraph.guard():
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paddle.set_device('cpu')
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out1 = paddle.zeros(shape=[1, 3], dtype='float32')
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out2 = paddle.ones(shape=[1, 3], dtype='float32')
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out3 = paddle.concat(x=[out1, out2], axis=0)
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device = paddle.get_device()
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self.assertEqual(
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isinstance(framework._current_expected_place(), core.CPUPlace),
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True,
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)
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self.assertEqual(device, "cpu")
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def test_gpu(self):
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if core.is_compiled_with_cuda():
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with base.dygraph.guard():
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paddle.set_device('gpu:0')
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out1 = paddle.zeros(shape=[1, 3], dtype='float32')
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out2 = paddle.ones(shape=[1, 3], dtype='float32')
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out3 = paddle.concat(x=[out1, out2], axis=0)
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device = paddle.get_device()
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self.assertEqual(
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isinstance(
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framework._current_expected_place(), get_device_class()
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),
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True,
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)
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self.assertEqual(device, "gpu:0")
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def test_xpu(self):
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if core.is_compiled_with_xpu():
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with base.dygraph.guard():
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out = paddle.to_tensor([1, 2])
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device = paddle.get_device()
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self.assertEqual(
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isinstance(
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framework._current_expected_place(), core.XPUPlace
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),
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True,
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)
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self.assertTrue(out.place.is_xpu_place())
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self.assertEqual(device, "xpu:0")
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def test_custom_device(self):
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if is_custom_device():
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with base.dygraph.guard():
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paddle.set_device(get_device(True))
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out1 = paddle.zeros(shape=[1, 3], dtype='float32')
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out2 = paddle.ones(shape=[1, 3], dtype='float32')
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out3 = paddle.concat(x=[out1, out2], axis=0)
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device = paddle.get_device()
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self.assertEqual(
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isinstance(
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framework._current_expected_place(), get_device_class()
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),
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True,
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)
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self.assertEqual(device, get_device(True))
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class TestGetPaddlePlaceAdaptiveGPU(unittest.TestCase):
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"""Test that _get_paddle_place('gpu'/'cuda') respects the globally set device ID."""
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def setUp(self):
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paddle.disable_static()
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def test_empty_device_cuda_follows_set_device(self):
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"""paddle.empty(device='cuda') should be placed on the device
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selected by paddle.device.set_device('cuda:1'), not always GPU 0."""
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if not core.is_compiled_with_cuda():
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return
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if core.get_cuda_device_count() < 2:
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return
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paddle.device.set_device('cuda:1')
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a = paddle.empty(1, device='cuda')
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place_str = str(a.place)
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# restore default
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paddle.device.set_device('cuda:0')
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self.assertIn(
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'1',
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place_str,
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msg=f"Expected tensor on GPU 1 but got place: {place_str}",
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)
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def test_empty_device_gpu_follows_set_device_cpu(self):
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"""paddle.empty(device='gpu') should also respect set_device('gpu:0')."""
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if not core.is_compiled_with_cuda():
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return
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if core.get_cuda_device_count() < 1:
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return
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paddle.device.set_device('gpu:0')
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a = paddle.empty(1, device='gpu')
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self.assertTrue(a.place.is_gpu_place())
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paddle.device.set_device('cpu')
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a = paddle.empty(1, device='gpu')
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self.assertTrue(a.place.is_gpu_place())
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if __name__ == '__main__':
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unittest.main()
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