TensorFlow Debugger Command-Line-Interface Tutorial: MNIST

TensorFlow Debugger (tfdbg) Command-Line-Interface Tutorial: MNIST

(Experimental)

TensorFlow debugger (tfdbg) is a specialized debugger for TensorFlow. It provides visibility into the internal structure and states of running TensorFlow graphs. The insight gained from this visibility should facilitate debugging of various types of model bugs during training and inference.

This tutorial showcases the features of tfdbg command-line interface (CLI), by focusing on how to debug a type of frequently-encountered bug in TensorFlow model development: bad numerical values (nans and infs) causing training to fail.

To observe such an issue, run the following code without the debugger:

python -m tensorflow.python.debug.examples.debug_mnist

This code trains a simple NN for M