Definition of the base Training Backend
: Base class for all local Training ZenML backends.
Every ZenML pipeline runs in backends. A training backend can be used to efficiently train a machine learning model on large amounts of data. Since most common machine learning models leverage mainly linear algebra operations under the hood, they can potentially benefit a lot from dedicated training hardware like Graphics Processing Units (GPUs) or application-specific integrated circuits (ASICs). ### Ancestors (in MRO) * zenml.core.backends.base_backend.BaseBackend ### Class variables `BACKEND_KEY` : `BACKEND_TYPE` : ### Methods `get_custom_config(self)` : Return a dict to be passed as a custom_config to the Trainer. `get_executor_spec(self)` : Return a TFX Executor spec for the Trainer Component.