24
Jan
2020
/
Carey Phelps, Product Lead

Visualizing TensorFlow 2 models with Weights & Biases

It's easy to integrate your TensorFlow models with Weights & Biases. With this quick integration you can see your live metrics streaming in to our visualizations, and compare new results to your previous baselines.

Try the Colab → to train a CNN, or this one → to train a Perceptron.

In one minute you can train these TensorFlow 2 models and see live results → streaming into a Weights & Biases project.

Integrating with Weights & Biases

To visualize your own models, add a few lines of code to any TensorFlow script to start seeing results:

  1. import wandb at the top of your script
  2. wandb.init(config=param_dict) initialize a new run and pass in a dictionary of the model's hyperparameters
  3. wandb.log({"loss": loss, "val_acc": val_acc}) log output metrics to see them graphed over time


Next Steps

To see your live results in Weights & Biases:

  1. Get a free personal account. Sign up →
  2. Run the hosted notebook. Google Colab →
  3. See results appear in this W&B report →

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