torch.mul()函数的使用

参考链接: mul(value) → Tensor

参考链接: torch.mul()

使用说明:

对两个张量进行逐元素乘法
           

Microsoft Windows [版本 10.0.18363.1256]
(c) 2019 Microsoft Corporation。保留所有权利。

C:\Users\chenxuqi>conda activate ssd4pytorch1_2_0

(ssd4pytorch1_2_0) C:\Users\chenxuqi>
(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 0x000002DDA5E6D330>
>>>
>>>
>>> a = torch.randn(3)
>>> a
tensor([ 0.2824, -0.3715,  0.9088])
>>> torch.mul(a, 2020.0910)
tensor([ 570.4512, -750.4310, 1835.8087])
>>>
>>>
>>>
>>> torch.manual_seed(seed=20200910)
<torch._C.Generator object at 0x000002DDA5E6D330>
>>>
>>> a = torch.randn(4, 1)
>>> b = torch.randn(1, 4)
>>> a
tensor([[ 0.2824],
        [-0.3715],
        [ 0.9088],
        [-1.7601]])
>>> b
tensor([[-0.1806,  2.0937,  1.0406, -1.7651]])
>>> torch.mul(a, b)
tensor([[-0.0510,  0.5912,  0.2939, -0.4985],
        [ 0.0671, -0.7778, -0.3866,  0.6557],
        [-0.1641,  1.9027,  0.9457, -1.6041],
        [ 0.3179, -3.6851, -1.8316,  3.1069]])
>>>
>>> torch.mul(b, a)
tensor([[-0.0510,  0.5912,  0.2939, -0.4985],
        [ 0.0671, -0.7778, -0.3866,  0.6557],
        [-0.1641,  1.9027,  0.9457, -1.6041],
        [ 0.3179, -3.6851, -1.8316,  3.1069]])
>>>
>>>
>>>