《深度学习框架PyTorch入门与实践》——Tensor基本操作

《深度学习框架PyTorch入门与实践》——Tensor基本操作(1) 一.PyTorch入门第一步

1.构建53矩阵*

import torch as tx = t.Tensor(5,3)print(x)

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2.使用【0，1】均匀分布随机初始化二维数组

import torch as tx = t.Tensor(5,3)x= t.rand(5,3)print(x)

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3.查看x形状和列的个数

import torch as tx = t.rand(5,3)print(x.size())print(x.size()[0])print(x.size(1))

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4.加法的三种写法

import torch as tx = t.rand(5,3)y = t.rand(5,3)print("最初y，x")print(y)print(x)print("第一种加法,y的结果")print(x+y)print("第二种加法，y的结果")print(t.add(x,y))print("第三种加法，y的结果")result=t.Tensor(5,3)t.add(x,y,out=result)print(result)

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5.对y的两种加法对比

import torch as tx = t.rand(5,3)y = t.rand(5,3)print("最初y，x")print(y)print(x)print("第一种加法,y的结果")print(y.add(x))print("第二种加法，y的结果")print(y.add_(x))

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6.Tensor的选取操作

import torch as tx = t.rand(5,3)print(x)print(x[:, 1])

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7.Tensor与numpy之间的互操作

import torch as timport numpy as npa=t.ones(5)print(a)b=a.numpy()print(b)a=np.ones(5)b=t.from_numpy(a)print(a)print(b)

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8.Tensor与numpy共同改变

import torch as timport numpy as npa=np.ones(5)b=t.from_numpy(a)b.add_(1)print(a)print(b)

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二.Tensor和autograd

1.创建tensor

import torch as ta=t.Tensor(2,3)print(a)b=t.Tensor([[1,2,3],[4,5,6]])print(b)b.tolist()print(b)b_size=b.size()print(b_size)print(b.numel())c=t.Tensor(b_size)d=t.Tensor((2,3))print(c)print(d)

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2、查看形状

import torch as tc=t.Tensor(b_size)print(c.shape)print(c.size)

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3、其他创建方法

import torch as tprint(t.ones(2,3))print(t.zeros(2,3))print(t.arange(1,6,2))print(t.linspace(1,10,3))print(t.randn(2,3))print(t.randperm(5))print(t.eye(2,3))

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4.常用的tensor操作

import torch as ta=t.arange(0,6)a.view(2,3)print(a)b=a.view(-1,3)print(b)print(b.unsqueeze(1))print(b.unsqueeze(-2))c=b.view(1,1,1,2,3)c.squeeze(0)print(c)c.squeeze()a[1]=100print(b)b.resize_(1,3)print(b)b.resize_(3,3)print(b)

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5.索引操作

import torch as ta=t.randn(3,4)print(a)print(a[0])print(a[:0])print(a[0][2])print(a[0,-1])print(a[:2])print(a[:2,0:2])print(a[0:1,:2])print(a[0,:2])print(a>1)print(a[a>1])print(a[t.LongTensor([0,1])])

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6.gather，scatter_操作

import torch as ta=t.arange(0,16).view(4,4)print(a)index=t.LongTensor([[0,1,2,3]])print(a.gather(0,index))index=t.LongTensor([[3,2,1,0]]).t()print(a.gather(1,index))index=t.LongTensor([[0,1,2,3]])print(a.gather(0,index))index=t.LongTensor([[0,1,2,3],[3,2,1,0]]).t()b=a.gather(1,index)print(b)#scatterc=t.zeros(4,4,dtype=t.int64)c.scatter_(1,index,b).float()print(c)

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7.高级索引

import torch as tx=t.arange(0,27).view(3,3,3)print(x)print(x[[1,2],[1,2],[2,0]])print(x[[2,1,0],[0],[1]])print(x[[0,2],...])

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8.tensor类型

import torch as tt.set_default_tensor_type('torch.DoubleTensor')a=t.Tensor(2,3)print(a)b=a.float()print(b)c=a.type_as(b)print(c)d=a.new(2,3)print(d)print(a.new)t.set_default_tensor_type('torch.FloatTensor')

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9.逐元素操作

import torch as ta=t.arange(0,6).view(2,3)print(t.cos(a))print(a%3)print(a**2)print(a)print(t.clamp(a,min=3))

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