0.3.6
0.3.6
0.3.6 is a more inwards-facing release as part of a bigger effort to create a more flexible ZenML. As a first step, ZenML now supports arbitrary splits for all components natively, freeing us from the train/eval
split paradigm. Here is an overview of changes:
New Features
-
The inner-workings of the
BaseTrainerStep
,BaseEvaluatorStep
and theBasePreprocesserStep
have been modified along with their respective components to work with the new split_mapping. Now, users can define arbitrary splits (not just train/eval). E.g. Doing atrain/eval/test
split is possible. -
Within the instance of a
TrainerStep
, the user has access toinput_patterns
andoutput_patterns
which provide the required uris with respect to their splits for the input and output(test_results) examples. -
The built-in trainers are modified to work with the new changes.
Bug Fixes + Refactor
A big thanks to our new super supporter @zyfzjsc988 for most of the feedback that led to bug fixes and enhancements for this release:
- #63: Now one can specify which ports ZenML opens its add-on applications.
- #64 Now there is a way to list integrations with the following code:
from zenml.utils.requirements_utils import list_integrations.
list_integrations()
- Fixed #61:
view_anomalies()
breaking in the quickstart. - Analytics is now
opt-in
by default, to get rid of the unnecessary prompt atzenml init
. Users can still freelyopt-out
by using the CLI:
zenml config analytics opt-out
Again, the telemetry data is fully anonymized and just used to improve the product. Read more here