Comments (4)
@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!
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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.
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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.
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