Installation | Quickstart | Reference docs
Grain is a Python library for reading and processing data for training and evaluating JAX models. It is flexible, fast and deterministic.
Grain allows to define data processing steps in a simple declarative way:
import grain
dataset = (
grain.MapDataset.source([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
.shuffle(seed=42) # Shuffles elements globally.
.map(lambda x: x+1) # Maps each element.
.batch(batch_size=2) # Batches consecutive elements.
)
for batch in dataset:
# Training step.Grain is designed to work with JAX models but it does not require JAX to run and can be used with other frameworks as well.
Grain is available on PyPI and can be
installed with pip install grain.
Grain does not directly use GPU or TPU in its transformations, the processing within Grain will be done on the CPU by default.
| Linux | Mac | Windows | |
|---|---|---|---|
| x86_64 | yes | no | no |
| aarch64 | yes | yes | n/a |
Grain is used by MaxText, kauldron and multiple internal Google projects.
