Optimize fetching of tensorflow header files

[isZumpo]

Rather than cloning the whole tensorflow repository, which is rather large, clone only the header files. Accomplished by utilizing sparse checkout feature.

During testing, cloning tensorflow like this was over 5 times faster than the old approach. It can be optimized further by limiting which folders to grab header files from too. However, currently I am not too familiar with how the header files are dependent on each-other, so I decided not to go for the extreme "tensorflow/lite/**/*.h" pattern which I was able to build and run the application with, since some of the headers there had dependencies to tensorflow/core.

Summary by CodeRabbit

• Chores
  • Improved the download and retrieval processes for TensorFlow headers by configuring sparse checkout in the Dockerfile and Makefile.

[coderabbitai]

Walkthrough

The recent modifications involve integrating additional Git commands into both the Dockerfile and Makefile. These commands are specially designed to set up a sparse checkout process for TensorFlow headers. This adjustment aims to streamline the download and retrieval stages, making them more efficient and less resource-intensive by focusing only on the necessary parts of the TensorFlow repository.

Changes

Files	Change Summary
Dockerfile, Makefile	Added Git commands for sparse checkout of TensorFlow headers

🌟✨
In the land of code and byte,
Where Docker sails and Makefiles fight,
A rabbit hopped with glee tonight,
For TensorFlow's load grew light.
Sparse checkout, the wizards' might,
Made our builds both swift and right.
🚀🐰💫

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[coderabbitai]

Actionable comments posted: 0

Review Status

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between 4c839a3 and 2e10fa7.

Files selected for processing (2)

• Dockerfile (1 hunks)
• Makefile (1 hunks)

Additional comments not posted (2)

Dockerfile (1)

34-37: Consider refining the sparse checkout pattern to be more specific to the required TensorFlow header files, if a thorough analysis of dependencies allows for it. This could further optimize the fetching process by reducing the amount of data cloned even more. However, ensure that all necessary dependencies are included to avoid build issues.

Makefile (1)

36-39: Consider refining the sparse checkout pattern in the Makefile to be more specific to the required TensorFlow header files, if a thorough analysis of dependencies allows for it. This could further optimize the fetching process by reducing the amount of data cloned even more. However, ensure that all necessary dependencies are included to avoid build issues.