Are you tired of trying to build Tensorflow Lite on Windows, only to be met with the infuriating error message ” Symlink creation failed”? Fear not, dear developer, for we’re about to embark on a thrilling adventure to vanquish this pesky issue and get your TF Lite project up and running in no time!
The Culprit: Windows and Symlinks
Before we dive into the solutions, it’s essential to understand the root cause of the problem. Windows, unlike its Unix-based counterparts, doesn’t natively support symlinks (symbolic links). Symlinks are a fundamental concept in Linux, allowing multiple names to point to the same file or directory. TensorFlow Lite relies heavily on symlinks during the build process, which is where the trouble begins.
Why Does TensorFlow Lite Need Symlinks?
In a nutshell, symlinks enable TensorFlow Lite to:
- Create a unified build environment across different operating systems.
- Allow for more efficient use of disk space by avoiding duplicated files.
- Facilitate easier maintenance and updates of the TF Lite codebase.
The Fix: Enable Symlink Creation on Windows
Now that we understand the root cause, let’s explore the solutions to this symlink conundrum. We’ll cover two methods to enable symlink creation on Windows, ensuring a successful TensorFlow Lite build.
Method 1: Windows 10’s Developer Mode
Starting with Windows 10, Microsoft introduced the Developer Mode, which allows enabling symlinks creation. To activate this feature:
- Press the Windows key + S to open the Search bar.
- Type “Developer settings” and select “For developers” from the results.
- Toggle the switch to “On” under the “Developer mode” section.
- Restart your system to apply the changes.
Method 2: Using the Command Prompt as Administrator
If you’re not on Windows 10 or prefer a more manual approach, you can use the Command Prompt to enable symlinks creation. Follow these steps:
- Press the Windows key + R to open the Run dialog box.
- Type “cmd” and press Enter to open the Command Prompt.
- Right-click on the Command Prompt icon in the taskbar and select “Run as administrator”.
- Type the following command and press Enter:
fsutil behavior set symlinkevaluation 1 - Verify that the command has been executed successfully by typing:
fsutil behavior query symlinkevaluation
This method will enable symlinks creation for the current user account.
Building TensorFlow Lite with Symlink Support
Now that we’ve overcome the symlink hurdle, it’s time to build TensorFlow Lite. You can use either the TensorFlow Lite build tools or Bazel to compile the project.
Building with TensorFlow Lite Build Tools
To build TensorFlow Lite using the official build tools, follow these steps:
- Download the TensorFlow Lite build tools from the official GitHub repository.
- Extract the downloaded archive to a directory of your choice.
- Open a Command Prompt or terminal in the extracted directory.
- Run the following command to build TensorFlow Lite:
python ./build.py
Building with Bazel
To build TensorFlow Lite using Bazel, you’ll need to:
- Download and install Bazel from the official website.
- Create a new directory for your TensorFlow Lite project and navigate to it.
- Run the following command to build TensorFlow Lite:
bazel build -c opt //tensorflow/lite:tensorflow_lite
| Build Tool | Command |
|---|---|
| TensorFlow Lite Build Tools | python ./build.py |
| Bazel | bazel build -c opt //tensorflow/lite:tensorflow_lite |
Troubleshooting and Common Issues
During the build process, you might encounter some common issues. Don’t worry; we’ve got you covered!
Symlink Creation Fails with Error Code 1314
If you encounter an error code 1314 while creating symlinks, try:
- Disabling Windows Defender or antivirus software temporarily.
- Running the Command Prompt as administrator (as described in Method 2).
TensorFlow Lite Build Fails with “File Not Found” Errors
If you encounter “File Not Found” errors during the build process, ensure that:
- You have installed all required dependencies, such as Visual Studio and the Windows SDK.
- You have correctly extracted the TensorFlow Lite build tools or Bazel.
By following these instructions and troubleshooting tips, you should be able to successfully build TensorFlow Lite on Windows, despite the symlink challenge. Remember to stay calm, patient, and persistent – and don’t hesitate to seek help from the TensorFlow community if needed!
Happy building, and may the TensorFlow Lite force be with you!
Frequently Asked Question
Are you stuck with Tensorflow Lite build failures on Windows because of symlink issues? Don’t worry, we’ve got you covered! Here are the top 5 questions and answers to help you troubleshoot and resolve the problem.
Q1: Why does Tensorflow Lite build fail on Windows due to symlink?
The Tensorflow Lite build fails on Windows because symlink (symbolic link) support is not enabled by default. Windows has limited support for symlinks, and when you try to build Tensorflow Lite, it uses symlinks to link libraries, which causes the build to fail.
Q2: How can I enable symlink support on Windows?
You can enable symlink support on Windows by running the Command Prompt or PowerShell as an administrator and executing the command `fsutil_behavior querying Syslawdll 1` or `fsutil behavior set SymlinkEvaluation L2L:1`. This will enable symlink support for the current user session. To make it persistent, you can add the registry key `HKEY_LOCAL_MACHINE\System\CurrentControlSet\Control\FileSystem\SymlinkEvaluation` and set its value to `1`.
Q3: Can I use the ‘–allow_boost’ flag to fix the symlink issue?
Yes, you can use the `–allow_boost` flag when building Tensorflow Lite to bypass the symlink issue. This flag tells the build system to use the Boost library instead of symlinks. However, keep in mind that this might cause other issues or limitations in your build.
Q4: Is there a way to build Tensorflow Lite without symlink support?
Yes, you can build Tensorflow Lite without symlink support by using the `–no_default_deps` flag and specifying the dependencies manually. This requires more expertise and configuration, but it’s a viable solution if you’re stuck with the symlink issue.
Q5: What are some alternative solutions for building Tensorflow Lite on Windows?
If you’re struggling with the symlink issue, consider using alternative solutions like Docker or a Linux virtual machine to build Tensorflow Lite. You can also use pre-built binaries or repositories like the Tensorflow Lite SDK, which might save you from building from source.
