Visdom Tutorial

This is a simple tutorial to start using Visdom to plot graphs when using PyTorch.

Install

Install Visdom using pip

pip install visdom

or Anaconda

conda install -c conda-forge visdom

Start the server

To use vidsom, you need to start the visdom server first. Make sure the server is running before you run your algorithms!

Start the server with:

python -m visdom.server

Then, in your browser, you can go to:

http://localhost:8097

You will see the visdom interface:

Let's plot something!

This repository contains the code to train a simple image classifier (tutorial) and to produce some example plots with visdom.

VisdomLinePlotter

We first create a visdom object to make the calls for us. You can find this code in utils.py file:

from visdom import Visdom

class VisdomLinePlotter(object):
    """Plots to Visdom"""
    def __init__(self, env_name='main'):
        self.viz = Visdom()
        self.env = env_name
        self.plots = {}
    def plot(self, var_name, split_name, title_name, x, y):
        if var_name not in self.plots:
            self.plots[var_name] = self.viz.line(X=np.array([x,x]), Y=np.array([y,y]), env=self.env, opts=dict(
                legend=[split_name],
                title=title_name,
                xlabel='Epochs',
                ylabel=var_name
            ))
        else:
            self.viz.line(X=np.array([x]), Y=np.array([y]), env=self.env, win=self.plots[var_name], name=split_name, update = 'append')

To create a new plot or to add new data to an existing plot, we will call plot(var_name, split_name, title_name, x, y), with:

• var_name: variable name (e.g. loss, acc)
• split_name: split name (e.g. train, val)
• title_name: titles of the graph (e.g. Classification Accuracy)
• x: x axis value (e.g. epoch number)
• y: y axis value (e.g. epoch loss)

Main process

In train.py we create the visdom object as a global variable:

import utils

if __name__ == "__main__":
    
    global plotter
    plotter = utils.VisdomLinePlotter(env_name='Tutorial Plots')

Now we can use plotter in any function to add data to our graphs.

In the training function we add the loss value after every epoch as:

plotter.plot('loss', 'train', 'Class Loss', epoch, losses.avg)

In the validation function we add the loss and the accuracy values as:

plotter.plot('loss', 'val', 'Class Loss', epoch, losses.avg)
plotter.plot('acc', 'val', 'Class Accuracy', epoch, acc)

And that's it! Simple, isn't it?

Now we can check the graphs at any point by visiting the visdom interface at http://localhost:8097 as long as the visdom server is still running.