mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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26 lines
795 B
26 lines
795 B
3 years ago
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from colossalai.tensor import ColoParameter, ColoTensor
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import torch
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from numpy import allclose
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from _utils import tensor_equal
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def test_multiinheritance():
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colo_param = ColoParameter()
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assert isinstance(colo_param, ColoTensor)
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assert isinstance(colo_param, torch.nn.Parameter)
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# __deepcopy__ overload
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import copy
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colo_param2 = copy.deepcopy(colo_param)
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assert isinstance(colo_param2, ColoParameter)
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assert tensor_equal(colo_param.data, colo_param2.data)
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assert colo_param.requires_grad == colo_param2.requires_grad
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# __repr__ overload
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assert 'ColoParameter' in str(colo_param)
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# __torch_function__
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clone_param = torch.clone(colo_param)
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assert isinstance(clone_param, ColoTensor)
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if __name__ == '__main__':
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test_multiinheritance()
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