PyTorch快速開始-Notebook with JupyterHub on K8s

時間 2019-12-23

標籤 pytorch 快速開始 notebook jupyterhub k8s 简体版

原文原文鏈接

在Kubernetes上的JupyterHub，經過Notebook快速運行PyTorch例程，測試鏡像是否可用。python

一、快速安裝

在個人鏡像中，已經將PyTorch、TorchVision打包到JupyterHub for K8s的Notebook鏡像中，能夠直接使用。git

或者，在notebook中進行安裝，以下：github

%%bash
pip install torch torchvision

注意：%%bash爲Notebook的魔法操做符，詳細使用參見：bash
- IPython 6/Jupyter的magic操做符框架
- IPython的Magics魔法操做符 dom
在Github的Databook項目獲取本Notebook的源文件：ide
- https://github.com/databooks/databook/deepml學習

二、導入引用庫

from __future__ import print_function, division
import os
import torch

三、運行例程

x = torch.rand(5, 3)
print(x)

輸出：
tensor([[0.4482, 0.9189, 0.2227],
        [0.3906, 0.4695, 0.1300],
        [0.5034, 0.7224, 0.0471],
        [0.5570, 0.4676, 0.8005],
        [0.0363, 0.2650, 0.1269]])

四、查看torchvision庫方法

查看torchvison的信息：測試

import torchvision
help(torchvision)

輸出信息：spa

Help on package torchvision:

NAME
    torchvision

PACKAGE CONTENTS
    _C
    datasets (package)
    models (package)
    ops (package)
    transforms (package)
    utils
    version

FUNCTIONS
    get_image_backend()
        Gets the name of the package used to load images
    
    set_image_backend(backend)
        Specifies the package used to load images.
        
        Args:
            backend (string): Name of the image backend. one of {'PIL', 'accimage'}.
                The :mod:`accimage` package uses the Intel IPP library. It is
                generally faster than PIL, but does not support as many operations.

VERSION
    0.3.0

FILE
    /opt/conda/lib/python3.6/site-packages/torchvision/__init__.py

五、查看torch庫方法

help(torch)

輸出信息：