Microsoft Windows [版本 10.0.18363.1256]
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C:\Users\chenxuqi>conda activate ssd4pytorch1_2_0
(ssd4pytorch1_2_0) C:\Users\chenxuqi>python
Python 3.7.7 (default, May 6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.manual_seed(seed=20200910)
<torch._C.Generator object at 0x000001BA5FCFD330>
>>>
>>> a = torch.randn(3,5)
>>> a
tensor([[ 0.2824, -0.3715, 0.9088, -1.7601, -0.1806],
[ 2.0937, 1.0406, -1.7651, 1.1216, 0.8440],
[ 0.1783, 0.6859, -1.5942, -0.2006, -0.4050]])
>>> b = a + 1
>>> b
tensor([[ 1.2824, 0.6285, 1.9088, -0.7601, 0.8194],
[ 3.0937, 2.0406, -0.7651, 2.1216, 1.8440],
[ 1.1783, 1.6859, -0.5942, 0.7994, 0.5950]])
>>> print(b)
tensor([[ 1.2824, 0.6285, 1.9088, -0.7601, 0.8194],
[ 3.0937, 2.0406, -0.7651, 2.1216, 1.8440],
[ 1.1783, 1.6859, -0.5942, 0.7994, 0.5950]])
>>>
>>> a = torch.randn(3,5,requires_grad=True)
>>> a
tensor([[-0.5556, 0.9571, 0.7435, -0.2974, -2.2825],
[-0.6627, -1.1902, -0.1748, 1.2125, 0.6630],
[-0.5813, -0.1549, -0.4551, -0.4570, 0.4547]], requires_grad=True)
>>> b = a + 1
>>> b
tensor([[ 0.4444, 1.9571, 1.7435, 0.7026, -1.2825],
[ 0.3373, -0.1902, 0.8252, 2.2125, 1.6630],
[ 0.4187, 0.8451, 0.5449, 0.5430, 1.4547]], grad_fn=<AddBackward0>)
>>> c = a * 2
>>> c
tensor([[-1.1113, 1.9141, 1.4871, -0.5948, -4.5650],
[-1.3254, -2.3805, -0.3497, 2.4250, 1.3261],
[-1.1625, -0.3099, -0.9102, -0.9141, 0.9093]], grad_fn=<MulBackward0>)
>>> d = b / 2
>>> d
tensor([[ 0.2222, 0.9785, 0.8718, 0.3513, -0.6412],
[ 0.1686, -0.0951, 0.4126, 1.1063, 0.8315],
[ 0.2094, 0.4225, 0.2725, 0.2715, 0.7273]], grad_fn=<DivBackward0>)
>>>
>>>
>>> print(d)
tensor([[ 0.2222, 0.9785, 0.8718, 0.3513, -0.6412],
[ 0.1686, -0.0951, 0.4126, 1.1063, 0.8315],
[ 0.2094, 0.4225, 0.2725, 0.2715, 0.7273]], grad_fn=<DivBackward0>)
>>>
>>>
>>>
>>> a.is_leaf
True
>>> b.is_leaf
False
>>> c.is_leaf
False
>>> d.is_leaf
False
>>>
>>>
>>>
