how to use wandb

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How to use Wandb

Introduction

Wandb is a tool that helps you track and visualize your machine learning experiments. It provides a clean and intuitive interface to log, analyze, and share your training and evaluation data. In this post, we will guide you through the process of using Wandb in your Python projects.

Installation

To install Wandb, you can use pip or conda package manager. Open your terminal and run the following command:

bash
pip install wandb

Setting up your project

  1. Import the wandb library in your Python script or notebook:

python
import wandb

  1. Initialize Wandb at the beginning of your script or notebook:

python
wandb.init(project='project-name', entity='username')
Replace 'project-name' with the name of your project and 'username' with your Wandb username.

Logging data

Wandb allows you to log various types of data during your experiments. Here are some examples:

  1. Logging scalar values:

python
wandb.log({'loss': 0.5, 'accuracy': 0.9})
You can log any number of scalar values in a single log call.

  1. Logging images:

python
wandb.log({'image': wandb.Image(image_array)})
Replace image_array with the NumPy array representing your image.

  1. Logging charts and plots:

python
wandb.log({'chart': wandb.plot.line(x=x_vals, y=y_vals)})
Replace x_vals and y_vals with the data for your chart.

  1. Logging text:

python
wandb.log({'text': wandb.Html('<h1>Heading</h1><p>Some text</p>')})
You can include any HTML content inside the wandb.Html() wrapper.

Experiment configuration

Wandb also allows you to track and compare different experiment configurations. You can use the wandb.config dictionary to store hyperparameters, dataset paths, model configurations, and any other important information.

“`python
wandb.config.lr = 0.001
wandb.config.batch_size = 32
wandb.config.dataset = ‘/path/to/dataset’

… Add more configurations as needed

“`

Running experiments

Once your script is set up for logging and configuration tracking, you can run your experiments as you normally would. Wandb will automatically collect and log the data specified in your code.

Analyzing results

You can view and analyze your experiment results on the Wandb dashboard. Log in to https://wandb.ai with your credentials and navigate to your project. Here, you can explore your logged data, compare multiple runs, and share your findings with others.

Conclusion

Wandb is a powerful tool that simplifies experiment tracking and visualization. By following the steps outlined in this post, you can easily integrate Wandb into your machine learning projects and gain valuable insights from your experiments. Happy logging!

Remember to check out the official Wandb documentation for more advanced features and options: https://docs.wandb.ai/