Environment variables

Here are the environment variables that zea uses at runtime. Arguably the most important environment variable is the Keras backend selection via KERAS_BACKEND. See the Backend section for details on configuring the backend.

Variable	Description	Default	Options
KERAS_BACKEND	Select the Keras backend to use. This defines the ML framework that will be used for all tensor operations.	jax	tensorflow, torch, jax, numpy
ZEA_CACHE_DIR	Directory to use for caching downloaded files, e.g. model weights or datasets from Hugging Face Hub.	~/.cache/zea	str
ZEA_LOG_LEVEL	Logging level for zea.	DEBUG	DEBUG, INFO, WARNING, ERROR, CRITICAL
ZEA_DISABLE_CACHE	If set to 1 will write to a temporary cache directory that is deleted after the program exits.	0	0, 1
ZEA_NVIDIA_SMI_TIMEOUT	Timeout in seconds for calling nvidia-smi to get GPU information during zea.init_device().	30	Any positive integer, or <= 0 to disable timeout.
ZEA_DOWNLOAD_TIMEOUT	Timeout in seconds for downloading files, e.g. during dataset conversion.	60	Any positive integer, or <= 0 to disable timeout.
ZEA_FIND_H5_SHAPES_PARALLEL	If set to 1, will use parallel processing when searching for HDF5 file shapes.	1	0, 1
ZEA_TEST_DEVICE	Can be used to only run the tests with a particular device.	auto:1	Any valid device name as accepted by zea.init_device(). For example, cpu, cuda:0, auto:1, etc.
ZEA_CHUNK_CACHE	Cache chunks fetched while streaming (hf://) under ZEA_CACHE_DIR/chunks, so a repeated read is served from disk instead of re-downloaded. Keyed by content hash, so a re-uploaded file misses rather than serving stale bytes. Per-file: File(cache=False).	1	0, 1
ZEA_CHUNK_CACHE_SIZE	Byte budget for that cache; least-recently-used chunks are evicted once it is exceeded.	10737418240 (10 GiB)	Any positive integer (bytes).
BLOSC_NTHREADS	Threads Blosc uses within a single HDF5 chunk, which is most of the write throughput (~4x). Turn it down when writes are already parallel (several dataloader workers each saving a file will multiply with it); turning it far up backfires, as the blocks go memory-bound. Only affects writes: the read path (zea.data.chunk_reader) uses numcodecs, which has its own thread setting.	min(8, cpu_count)	Any positive integer.