Introduction

When working with machine learning models, especially using TensorFlow, thorough unit testing is crucial to ensure the robustness of your code. Nosetests is a popular testing framework in Python, and it's often used alongside TensorFlow to facilitate testing. However, due to TensorFlow's verbose nature, tests can produce an overwhelming amount of debugging output. Here, we'll discuss how to manage and minimize such verbosity and streamline your testing process.

Overview of Nosetests

Nosetests is a Python testing tool that extends unittest to make testing easier. It automatically finds tests, runs them, and reports the results, making it highly suitable for unit testing in TensorFlow projects.

Key Features

• Automatic Test Discovery: Nosetests automatically discovers tests within your project.
• Plug-in Support: Extensible through a variety of plug-ins.
• Simplifies Test Setup: Automatically handles setup and teardown.
• Highly Configurable: Can be customized to meet the needs of your projects.

Using Nosetests with TensorFlow

When using TensorFlow, the debugging and execution output can be large due to the numerous operations performed under the hood. By default, TensorFlow logs internal operations which can clutter your console when running tests. This section will explore methods to suppress or manage TensorFlow's verbosity using nosetests.

Suppressing Debug Output

The main source of extensive output in TensorFlow is its logging feature. By default, TensorFlow logs can include INFO and DEBUG level messages which are rarely needed unless diagnosing specific issues. To manage these logs, you can use environment variables or TensorFlow's built-in options.

1. Set TensorFlow Logging Level:
   TensorFlow's verbosity can be controlled through the TF_CPP_MIN_LOG_LEVEL environment variable:
   • 0 : ALL INFO, WARNINGS, ERRORS, or FATAL messages are displayed.
   • 1 : All INFO messages are not shown.
   • 2 : INFO and WARNINGS messages are not shown.
   • 3 : Only ERROR or FATAL messages are displayed (recommended for tests).

• --nologcapture : Disables log capture.
• --with-coverage : Measures code coverage during test execution.
• --cover-html : Generates an HTML report of the coverage.