www.yaml.org VS Keras

First of all, create a file in the root project directories called compose.yaml. YAML is a text format that uses indentation to specify dependencies between configuration options. Be aware that incorrect indentation will cause problems with executing commands properly.

Most commonly written in YAML, these files are large and complex to read and understand. And being written in YAML comes with its challenges (and quirks) since it is an additional programming language that devs need to learn.

YAML Ain't a Markup Language

Note, that this file is a Markdown and YAML file at the same time, and as such human- and machine-readable, if the fields are filled carefully.

Front matter is a bit of text at the start of a file (YAML to be exact) that is placed between two ---

Meanwhile, formats have been evolving (JSON5, YAML), config entry points are constantly changing. These fluctuations, fortunately, were covered by tools like the cosmiconfig.

Personally, I'd love to see them using a standard file format like TOML or YAML so that they're easy to parse and work with using already-existing tools.

Keras

As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development.

After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow.

All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467

You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/

I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?

Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.

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I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them.