Reverse Dependencies of etils

The following projects have a declared dependency on etils:

• aironsuit — A model wrapper for automatic model design and visualization purposes.
• array-record — A file format that achieves a new frontier of IO efficiency
• bobbin — Tools for making training loops with flax.linen models.
• bojaxns — Bayesian Optimisation with JAXNS
• BookmarkParser — A Simple and clean way to explore Bookmarks Data.
• brax — A differentiable physics engine written in JAX.
• clu — Set of libraries for ML training loops in JAX.
• dataclass-array — Dataclasses that behave like numpy arrays (with indexing, slicing, vectorization).
• enformer-dna-diff — This is a package for that combines DeepMind Enformer model with DNA Diffusion project
• etils — Collection of common python utils
• fiddle — Fiddle: A Python-first configuration library
• grain — Grain: A library for loading and transforming data for neural network training.
• grain-nightly — Grain: A library for loading and transforming data for neural network training.
• graphite-datasets — tensorflow/datasets is a library of datasets ready to use with TensorFlow.
• jaxcam — no summary
• kauldron — Kauldron is a ML research library optimized for quick iteration and modularity.
• kubric-nightly — A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation, depth maps, and optical flow.
• mlcroissant — MLCommons datasets format.
• momaland — A standard API for Multi-Objective Multi-Agent Decision making and a diverse set of reference environments.
• mujoco — MuJoCo Physics Simulator
• mujoco-mjx — MuJoCo XLA (MJX)
• my_chrome_bookmarks — Utils to load local chrome bookmarks.
• neuralgcm — no summary
• neuroflex — An advanced neural network framework with interpretability, generalization, robustness, and fairness features
• optax — A gradient processing and optimization library in JAX.
• orbax — Orbax
• orbax-checkpoint — Orbax Checkpoint
• orbax-export — Orbax Export
• paxml — Framework to configure and run machine learning experiments on top of Jax.
• praxis — Functionalities such as a layers for building neural networks in Jax.
• protes — Method PROTES (PRobabilistic Optimizer with TEnsor Sampling) for derivative-free optimization of the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format
• rstojnic-tfds-nightly — tensorflow/datasets is a library of datasets ready to use with TensorFlow.
• sphinx-apitree — Sphinx extension to auto-generate API tree.
• sunds — Datasets for scene understanding and neural rendering.
• tensorflow-datasets — tensorflow/datasets is a library of datasets ready to use with TensorFlow.
• tfds-nightly — tensorflow/datasets is a library of datasets ready to use with TensorFlow.
• visu3d — 3d geometry made easy.
• xmanager — A framework for managing machine learning experiments