How to Fix AttributeError: module ‘tensorflow’ has no attribute ‘logging’

Diagram

AttributeError: module ‘tensorflow’ has no attribute ‘logging’ error occurs when  you try to “use the TensorFlow logging module, but the system does not recognize it.”

The tensorflow.logging module has been removed in recent versions of TensorFlow (2.x).

Common reasons

Here are the common reasons for the error to occur:

1. You are using an “outdated version of TensorFlow” that doesn’t support the logging module.
   
2. The logging module has been removed from the version of TensorFlow you are using.
   
3. There is an issue with your Python environment, such as a missing dependency or an incompatible version of a library.

How to Fix the AttributeError: module ‘tensorflow’ has no attribute ‘logging’

Here are the ways to fix the AttributeError: module ‘tensorflow’ has no attribute ‘logging’ error:

1. Upgrade your TensorFlow version
2. Installing the logging module
3. Using tf.compat.v1.logging
4. Using the tf.get_logger()
5. Using Python’s built-in logging module

Solution 1: Upgrade your TensorFlow version

Check the version of TensorFlow you are using. If you are using an outdated version, upgrade to the latest version.

pip install --upgrade tensorflow

Solution 2: Installing the logging module

If you are using a version of TensorFlow that supports the logging module, but it’s still not available, you may need to install it separately.

!pip install tensorflow-logging

Solution 3: Using tf.compat.v1.logging

To use TensorFlow’s logging utilities but are working with TensorFlow 2.x, you can use the tf.compat.v1.logging module to access the old logging methods:

import tensorflow as tf

tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.INFO)

tf.compat.v1.logging.info("This is an info log.")

Output

INFO:tensorflow:This is an info log.

Solution 4: Using tf.get_logger()

TensorFlow 2.x provides a method to get the default logger, which is based on Python’s logging library.

import tensorflow as tf

logger = tf.get_logger()
logger.setLevel("INFO")
logger.info("This is an info log.")

Output

INFO:tensorflow:This is an info log.

Solution 5: Using Python’s built-in logging module

You can use Python’s standard logging module for logging messages. Here’s an example:

import logging

logging.basicConfig(level=logging.INFO)

logging.info("This is an info log.")

Output

INFO:root:This is an info log.

Krunal

Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.