Verify Tensorboard Installation

Oct 13, 2025 by sorusgentrification.com 116 views

Introduction

Profiling JAX code is an essential step in optimizing performance and identifying bottlenecks. However, when trying to use the example provided in the JAX documentation, Tensorboard crashes when loading the profile. In this article, we will explore the issue and provide a step-by-step guide to troubleshoot and resolve the problem.

Description of the Issue

The issue arises when trying to load the profile using Tensorboard. The error message indicates that Tensorboard is unable to load the profile, resulting in a crash. The example script used in the JAX documentation is as follows:

import jax

with jax.profiler.trace("/tmp/tensorboard"):
  key = jax.random.key(0)
  x = jax.random.normal(key, (5000, 5000))
  y = x @ x
  y.block_until_ready()

This script is designed to profile the JAX code and generate a profile that can be loaded into Tensorboard. However, when running this script and attempting to load the profile using Tensorboard, the program crashes with an error message.

System Information

To troubleshoot the issue, it is essential to gather system information, including the Python version, JAXlib version, and accelerator being used. The system information is as follows:

Python version: 3.11
JAXlib version: 0.5.2
Accelerator: CUDA 12

Installation Steps

To replicate the issue, the following installation steps were taken:

mamba create jax2 python=3.11  -c conda-forge 
mamba jax2

pip install "jax[cuda12]"==0.5.2 tensorflow tensorboard-plugin-profile
mamba install flax=0.10.2

Note: For some reason, it was necessary to install Flax 0.10.2 to get JAX to work. The difference in jax.print_environment_info() was that JAXlib was 0.5.2 when Flax was installed. Without it, JAX could not locate the CUDA drivers.

Troubleshooting Steps

To troubleshoot the issue, the following steps were taken:

Verify Tensorboard Installation: Ensure that Tensorboard is installed correctly by running tensorboard --version.
Check Log Directory: Verify that the log directory is correct and that the profile is being generated correctly.
Check JAX Version: Ensure that the JAX version is compatible with the Tensorboard version.
Check CUDA Drivers: Verify that the CUDA drivers are installed correctly and that JAX can locate them.

Conclusion

In conclusion, the JAX Tensorboard profiling example not working is a complex issue that requires a thorough troubleshooting process. By following the steps outlined in this article, you should be able to identify and resolve the issue. If the issue persists, it may be worth transferring the issue to the Tensorboard repository for further assistance.

Additional Resources

For further assistance, please refer to the following resources:

JAX Documentation: https://docs.jax.dev/en/latest/profiling.html
Tensorboard Documentation: https://www.tensorflow.org/tensorboard
JAX GitHub Repository: https://github.com/google/jax

System Requirements

To replicate the issue, the following system requirements are necessary:

Python 3.11
JAX 0.5.2
CUDA 12
Tensorboard 2.10.0
Flax 0.10.2

Troubleshooting Tips

Ensure that the log directory is correct and that the profile is being generated correctly.
Verify that the JAX version is compatible with the Tensorboard version.
Check the CUDA drivers to ensure that they are installed correctly and that JAX can locate them.

Error Message

The error message received when attempting to load the profile using Tensorboard is as follows:

System Information (Python Version, JAXlib Version, Accelerator, etc.)

The system information is as follows:

Python version: 3.11
JAXlib version: 0.5.2
Accelerator: CUDA 12

Installation Steps (Mamba, Pip, Mamba Install)

The installation steps are as follows:

mamba create jax2 python=3.11  -c conda-forge 
mamba jax2

pip install "jax[cuda12]"==0.5.2 tensorflow tensorboard-plugin-profile
mamba install flax=0.10.2

Q: What is the issue with the JAX Tensorboard profiling example?

A: The issue arises when trying to load the profile using Tensorboard. The error message indicates that Tensorboard is unable to load the profile, resulting in a crash.

Q: What are the system requirements to replicate the issue?

A: To replicate the issue, the following system requirements are necessary:

Python 3.11
JAX 0.5.2
CUDA 12
Tensorboard 2.10.0
Flax 0.10.2

Q: What are the installation steps to replicate the issue?

A: The installation steps are as follows:

mamba create jax2 python=3.11  -c conda-forge 
mamba jax2

pip install "jax[cuda12]"==0.5.2 tensorflow tensorboard-plugin-profile
mamba install flax=0.10.2

Q: Why was it necessary to install Flax 0.10.2 to get JAX to work?

A: For some reason, it was necessary to install Flax 0.10.2 to get JAX to work. The difference in jax.print_environment_info() was that JAXlib was 0.5.2 when Flax was installed. Without it, JAX could not locate the CUDA drivers.

Q: What are the troubleshooting steps to resolve the issue?

A: To troubleshoot the issue, the following steps were taken:

Verify Tensorboard Installation: Ensure that Tensorboard is installed correctly by running tensorboard --version.
Check Log Directory: Verify that the log directory is correct and that the profile is being generated correctly.
Check JAX Version: Ensure that the JAX version is compatible with the Tensorboard version.
Check CUDA Drivers: Verify that the CUDA drivers are installed correctly and that JAX can locate them.

Q: What are the additional resources available to resolve the issue?

A: For further assistance, please refer to the following resources:

JAX Documentation: https://docs.jax.dev/en/latest/profiling.html
Tensorboard Documentation: https://www.tensorflow.org/tensorboard
JAX GitHub Repository: https://github.com/google/jax

Q: What is the error message received when attempting to load the profile using Tensorboard?

A: The error message received when attempting to load the profile using Tensorboard is as follows:

Q: What are the system information (Python version, JAXlib version, accelerator, etc.)?

A: The system information is as follows:

Python version: 3.11
JAXlib version: 0.5.2
Accelerator: CUDA 12

Q: What are the installation steps (Mamba, Pip, Mamba Install) to replicate the issue?

A: The installation steps are as follows:

mamba create jax2 python=3.11  -c conda-forge 
mamba jax2

pip install "jax[cuda12]"==0.5.2 tensorflow tensorboard-plugin-profile
mamba install flax=0.10.2

Q: Why was it necessary to install Flax 0.10.2 to get JAX to work?

Q: What are the troubleshooting tips to resolve the issue?

A: To troubleshoot the issue, ensure that the log directory is correct and that the profile is being generated correctly. Verify that the JAX version is compatible with the Tensorboard version and that the CUDA drivers are installed correctly and that JAX can locate them.