How to build the tensorflow origin code fast when I modify the code

[YuMJie]

Issue type

Build/Install

Have you reproduced the bug with TensorFlow Nightly?

Yes

Source

source

TensorFlow version

2.16.1

Custom code

Yes

OS platform and distribution

Linux ubuntu 20.04

Mobile device

No response

Python version

3.9

Bazel version

No response

GCC/compiler version

No response

CUDA/cuDNN version

No response

GPU model and memory

No response

Current behavior?

I want to learn how TensorFlow is implemented and participate in the development of TensorFlow, but as far as I know, if you install it in the form of WHL through Build, you will spend a lot of time on Build, and there is any way to modify its code faster and verify that the modified code works

Standalone code to reproduce the issue

./configure  # answer prompts or use defaults

bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package

./bazel-bin/tensorflow/tools/pip_package/build_pip_package /mnt  # create package

chown $HOST_PERMS /mnt/tensorflow-version-tags.whl

Relevant log output

No response

[tilakrayal]

@YuMJie,
While WHL files offer faster installation, building from source gives the direct access to the code. If you choose this way, consider using a tool like Bazel which streamlines the build process for large projects like TensorFlow.

Also try to create a virtual environment to isolate your development dependencies and avoid conflicts with other projects. This allows you to quickly switch between different TensorFlow versions or experiment with custom libraries.

If you build the tensorflow from source, you can modify TensorFlow's behavior for specific use cases, Integrate the TensorFlow with custom libraries or frameworks and You can step through the code line by line using a debugger to identify the root cause of problems. Thank you!

[github-actions]

This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.

[github-actions]

This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further.

[google-ml-butler]

Are you satisfied with the resolution of your issue?
Yes
No