zoukankan      html  css  js  c++  java
  • Reduction operations

    Reuction operations

    Reduction operations

    A reduction operations on a tensor is an operation that reduces the number of elements contained within the tensor.

    Tensors give us the ability to manage out data. Reduction operations allow us to perform operations on elements within a single tensor.

    Suppose we have the following 3$ imes$3 rank-2 tensor.

    > t = torch.tensor([
        [0, 1, 0],
        [2, 0, 2],
        [0, 3, 0]
    ], dtype=torch.float32)
    

    Common tensor reduction operations

    > t.sum()
    tensor(8.)
    
    > t.numel()
    9
    
    > t.prod()
    tensor(0.)
    
    > t.mean()
    tensor(.8889)
    
    > t.std()
    tensor(1.1667)
    

    Reducing tensors by axes

    Suppose we have the following tensor:

    > t = torch.tensor([
        [1,1,1,1],
        [2,2,2,2],
        [3,3,3,3]
    ], dtype=torch.float32)
    

    This time , we will specify a dimension to reduce.

    > t.sum(dim=0)
    tensor([6., 6., 6., 6.])
    
    > t.sum(dim=1)
    tensor([4., 8., 12.])
    

    Argmax tensor reduction operation

    Argmax returns the index location of the maximum value inside a tensor.

    t = torch.tensor([
        [1,0,0,2],
        [0,3,3,0],
        [4,0,0,5]
    ], dtype=torch.float32)
    

    If we don't specific an axis to the argmax() method, it returns the index location of the max value from the flattened tensor, which in the case is indeed 11.

    > t.max()
    tensor(5.)
    
    > t.argmax()
    tensor(11)
    
    > t.flatten()
    tensor([1., 0., 0., 2., 0., 3., 3., 0., 4., 0., 0., 5.])
    

    Work with specific axis now:

    > t.max(dim=0)
    (tensor([4., 3., 3., 5.]), tensor([2, 1, 1, 2]))
    
    > t.argmax(dim=0)
    tensor([2, 1, 1, 2])
    
    > t.max(dim=1)
    (tensor([2., 3., 5.]), tensor([3, 1, 3]))
    
    > t.argmax(dim=1)
    tensor([3, 1, 3])
    

    In practice, we often use the argmax() function on a network's output prediction tensor, to determine which category has the highest prediction value.

  • 相关阅读:
    cookie和session
    图书馆里系统前端页面
    图书管理系统后端接口
    Vue组件
    axios前端登录
    django配置跨域并开发测试接口
    axios封装
    初始化vue项目
    model的基础操作
    Windows 系统版本介绍
  • 原文地址:https://www.cnblogs.com/xxxxxxxxx/p/11068461.html
Copyright © 2011-2022 走看看