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DNN Monitoring and Checkpointing on MNIST.ipynb


Monitoring and Checkpointing

This blog post covers how to change your code to allow for monitoring the validation accuracy and checkpointing the model weights to be used in later tasks.

  • Adjusted the code to checkpoint
  • Adjusted the code to monitor the validation accuracy
  • Showed how to use the tf.app.flags in the CLI

Running the Code

To run the code either follow the steps on the blog post or simply run:


Then run the following code or launch the jupyter notebook:

python model.py --num_steps=2500
python model.py --num_steps=2500