Reference

Encyclopedia MAITEanica.

COMING SOON! All reference documentation includes detailed Examples sections. Please scroll to the bottom of any given reference page to see the examples.

Protocols

Data, Datasets, & DataLoaders

protocols.ArrayLike
protocols.image_classification.Dataset(...)	A dataset protocol for image classification ML subproblem providing datum-level data access.
protocols.image_classification.DataLoader(...)	A dataloader protocol for the image classification ML subproblem providing batch-level data access.
protocols.object_detection.ObjectDetectionTarget(...)	An object-detection target protocol.
protocols.object_detection.Dataset(*args, ...)	A dataset protocol for object detection ML subproblem providing datum-level data access.
protocols.object_detection.DataLoader(*args, ...)	A dataloader protocol for the object detection ML subproblem providing batch-level data access.

Models

protocols.image_classification.Model(*args, ...)	A model protocol for the image classification ML subproblem.
protocols.object_detection.Model(*args, **kwargs)	A model protocol for the object detection ML subproblem.

Augmentations

protocols.image_classification.Augmentation(...)	An augmentation protocol for the image classification subproblem.
protocols.object_detection.Augmentation(...)	An augmentation protocol for the object detection subproblem.

Metrics

protocols.image_classification.Metric(*args, ...)	A metric protocol for the image classification ML subproblem.
protocols.object_detection.Metric(*args, ...)	A metric protocol for the object detection ML subproblem.

Workflows

workflows.evaluate(*, model[, metric, ...])	Evaluate a model's performance on data according to some metric with optional augmentation.
workflows.predict(*, model[, dataloader, ...])	Make predictions for a given model & data source with optional augmentation.

Validation and Error Handling

check_type(name, arg, type_, *[, optional])	Check that an argument is an instance of one or more types.
check_domain(name, arg, *[, lower, upper, ...])	Check that an argument falls within [lower <=] arg [<= upper].
check_one_of(name, arg, collection, *vals[, ...])	Check that arg is a member of collection or of vals.
chain_validators(*validators)	Enable validators to be chained together.

MaiteException	Base exception thrown by the MAITE.
InvalidArgument	A MAITE interface was passed a bad value or type.

Testing Tools

validate_docstring(obj[, ignore, ...])	Validate an object's docstring against the NumPy docstring standard [Rf5befd11ff4f-1].
NumpyDocErrorCode
NumPyDocResults

pyright_analyze(*code_objs_and_or_paths[, ...])	Scan a Python object, docstring, or file with pyright.
PyrightOutput	The schema for the JSON output of a pyright scan
list_error_messages(results)	A convenience function that returns a list of error messages reported by pyright.

cleandir()

A pytest fixture that runs a test in a temporary directory as the current working directory.

ModuleScan()	Uses pyright's type completeness scan to summarize a module's contents.
get_public_symbols(scan[, submodule, ...])	Return all public symbols (functions, classes, etc.) from a module's API.