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27c7158166
Summary: There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports: ```2to3 -f future -w caffe2``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033 Reviewed By: seemethere Differential Revision: D23808648 Pulled By: bugra fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
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import unittest
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import torch
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from caffe2.python import core, workspace
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# This is a standalone test that doesn't use test_util as we're testing
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# initialization and thus we should be the ones calling GlobalInit
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@unittest.skipIf(not workspace.has_cuda_support,
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"THC pool testing is obscure and doesn't work on HIP yet")
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class TestGPUInit(unittest.TestCase):
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def testTHCAllocator(self):
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cuda_or_hip = 'hip' if workspace.has_hip_support else 'cuda'
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flag = '--caffe2_{}_memory_pool=thc'.format(cuda_or_hip)
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core.GlobalInit(['caffe2', flag])
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# just run one operator
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# it's importantant to not call anything here from Torch API
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# even torch.cuda.memory_allocated would initialize CUDA context
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workspace.RunOperatorOnce(core.CreateOperator(
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'ConstantFill', [], ["x"], shape=[5, 5], value=1.0,
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device_option=core.DeviceOption(workspace.GpuDeviceType)
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))
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# make sure we actually used THC allocator
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self.assertGreater(torch.cuda.memory_allocated(), 0)
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if __name__ == '__main__':
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unittest.main()
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