Introduction

When working with TensorFlow's high-level Estimator API, performance and efficiency are crucial. TensorFlow provides different utilities to facilitate and optimize various tasks during model training and evaluation. Among these utilities are `Validation Monitors` and `tf.train.SessionRunHook`. Although `Validation Monitors` were popular in earlier TensorFlow versions for inserting validation checks during training, `tf.train.SessionRunHook` has become the recommended approach as it provides more flexibility and control.

Understanding Estimators

Before diving into the replacement, let's briefly discuss what Estimators are. Estimators simplify the task of creating and training models by encapsulating the complexities of model training, evaluation, and prediction. They are powerful tools for those who want to build robust machine learning workflows without getting bogged down by boilerplate code.

The Role of Validation Monitors

In earlier TensorFlow versions, `Validation Monitors` played an essential role in validating the training process using custom metrics on a different dataset. However, they came with limitations, such as reduced flexibility in customization, especially for complex workflows.

tf.train.SessionRunHook: A Better Alternative

With the advancement of TensorFlow, `tf.train.SessionRunHook` has emerged as a better alternative due to its capacity to perform a variety of actions at different points during training. `SessionRunHooks` can monitor performance, execute additional operations, and even terminate a session based on certain criteria.

Key Advantages

• Flexibility: Define custom actions at different points: before/after session starts, before/after each call to `session.run`.
• Better Integration: Fully compatible with TensorFlow Estimators and integrates seamlessly with the Estimator's training loop.
• Custom Logging and Saving: Adaptable to log information or save model checkpoints at custom intervals.
• Advanced Monitoring: Can easily be tailored to monitor and react to model performance.

Replacing Validation Monitors with SessionRunHooks

To replace `Validation Monitors` with `SessionRunHooks`, you can create custom hooks to be passed to the Estimator's `.train` or `.evaluate` methods. Here's a step-by-step guide, with code examples, showcasing the transition:

Example: Custom Logging Hook

Let's say we want to log loss every 100 steps during training: