Google Colab Tutorial
A free GPU testing environment
Date: Dec. 8th, 2019
Lecturer: Chia
Outline
- Introduction To Google Colab
- Setting for using GPU
- Connect Google Colab with Google Drive
- Running with Google Colab
- Sharing my Colab notebook
Introduction To Google Colab
- Google Colab (Colaboratory)
- 雲端的 Jupyter Notebook 開發環境
- 特點:提供免費的GPU (型號為Tesla K80 GPU)
- 限制:每次開啟有12小時的連續使用時間限制
Setting for using GPU
- Open your Google Drive
Setting for using GPU
import tensorflow as tf
tf.test.gpu_device_name()
#Output: ''
- Check if CPU is working or not!
Setting for using GPU
- Change Hardware accelerator to GPU
Setting for using GPU
import tensorflow as tf
tf.test.gpu_device_name()
#Output: '/device:GPU:0'
- Check if GPU is working or not!
from tensorflow.python.client import device_lib
device_lib.list_local_devices()
- Which GPU Am I Using?
Connect Google Colab with Google Drive
from google.colab import drive
drive.mount('/content/drive/')
- Enable authorization to link with Google Drive.
!ls "/content/drive/My Drive/"
- Now, you can reach your Google Drive.
Running with Google Colab
!python3 "/content/drive/My Drive/Colab Notebooks/print_abc.py"
- Upload print_abc.py to Google Drive & Run with Google Colab
from google.colab import files
files.download('/content/drive/My Drive/Colab Notebooks/print_abc.py')
- Run with Google Colab to Download print_abc.py from Google Drive
Running with Google Colab
import os
os.chdir("/content/drive/My Drive/Colab Notebooks")
!ls
from google.colab import files
uploaded = files.upload()
for fn in uploaded.keys():
print('User uploaded file "{name}" with length {length} bytes'.format(name=fn, length=len(uploaded[fn])))
- Select the print_xyz.py from computer and upload it to the Google Colab virtual machine.
Running with Google Colab
# -P => 指定存放路徑
!wget https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/datasets/Titanic.csv \
-P "/content/drive/My Drive/Colab Notebooks"
- Download Titanic Dataset (.csv File)
- Display First 5 Rows
import pandas as pd
titanic = pd.read_csv("/content/drive/My Drive/Colab Notebooks/Titanic.csv")
titanic.head(5)
Running with Google Colab
!git clone https://github.com/wxs/keras-mnist-tutorial.git
- Changing Working Directory
import os
os.chdir("/content/drive/My Drive/Colab Notebooks")
!ls
# 到上一層目錄
#os.chdir("../")
#!ls
- Cloning Github Repo to Google Colab
Running with Google Colab
%%bash
pip freeze
- List all packages had already been installed.
- The virtual machine you’re using, including any custom files and libraries that you’ve setup, will not be shared.
- So it’s a good idea to include cells which install and load any custom libraries or files that your notebook needs.
Running with Google Colab
- Install Keras
# -q, --quiet => Give less output.
!pip install -q keras
import keras
Running with Google Colab
%%bash
# For a specific version:
pip install -q tensorflow==1.2
# To determine which version you're using:
pip show tensorflow
- Install / Show package
%%bash
# For the current version:
pip install --upgrade -q tensorflow
# To determine which version you're using:
pip show tensorflow
Sharing my Colab notebook
Sharing my Colab notebook
Sharing my Colab notebook
Thanks for listening.
Google Colab Tutorial
By BessyHuang
Google Colab Tutorial
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