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All about the fundamental blocks of TF and JAX!

License: MIT License

Jupyter Notebook 100.00%

python deep-learning machine-learning tutorials tensorflow jax

tf_jax_tutorials's Introduction

TensorFlow-JAX Tutorials

Learn about TensorFlow and JAX but in a different way!

✅ Meant for everyone (from novice to advanced users)
✅ Deep dive into the fundamental building blocks of the frameworks
✅ Aim to improve your understanding and to some extent the mental model of the API
✅ Not a typical documentation-type tutorial
✅ Runnable notebooks available

❌ Not a replacement of the documentation

TensorFlow

Chapter No	Topic	Colab	Kaggle	Binder	GitHub
1.	Tensors
2.	Variables
3.	Automatic Differentiation

JAX

Chapter No	Topic	Colab	Kaggle	Binder	GitHub
1.	DeviceArray
2.	Pure Functions
3.	PRNG
4.	JIT
5.	Vmap and Pmap
6.	Automatic Differentiation
7.	Pytrees

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tf_jax_tutorials's Issues

Incorrect usage of PRNG

Hi,

I noticed that you are reusing the same key in e.g. cell 23 of main/src/notebooks/jax_tutorials/chapter_5_vmap_pmap.ipynb

key, subkey = random.split(key)
rotate = random.randint(key, shape=[batch_size], minval=0, maxval=2)

Looks like you shall be using the subkey in random.randint, not the original key. The way it is now subkey is never used.

Set seed

A neat way to setting seed is by using tf.keras.utils.set_random_seed(SEED). This API basically does away with all the redundant numpy, random, and tf random seed setting code.

Hope this will find its way into the tutorials. Thanks for the tutorial BTW.

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