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Version: 0.5.10

Python SDK Overview

Starwhale provides a series of Python SDKs to help manage datasets, models, evaluations etc. Using the Starwhale Python SDK can make it easier to complete your ML/DL development tasks.

Classes​

  • PipelineHandler: Provides default model evaluation process definition, requires implementation of predict and evaluate methods.
  • Context: Passes context information during model evaluation, including Project, Task ID etc.
  • class Dataset: Starwhale Dataset class.
  • class starwhale.api.service.Service: The base class of online evaluation.

Functions​

  • @multi_classification: Decorator for multi-class problems to simplify evaluate result calculation and storage for better evaluation presentation.
  • @handler: Decorator to define a running entity with resource attributes (mem/cpu/gpu). You can control replica count. Handlers can form DAGs through dependencies to control execution flow.
  • @evaluation.predict: Decorator to define inference process in model evaluation, similar to map phase in MapReduce.
  • @evaluation.evaluate: Decorator to define evaluation process in model evaluation, similar to reduce phase in MapReduce.
  • evaluation.log: Log evaluation metrics to the specific tables.
  • evaluation.log_summary: Log certain metrics to the summary table.
  • evaluation.iter: Iterate and read data from the certain tables.
  • model.build: Build Starwhale model.
  • @fine_tune: Decorator to define model fine-tuning process.
  • init_logger: Set log level, implement 5-level logging.
  • dataset: Get starwhale.Dataset object, by creating new datasets or loading existing datasets.
  • @starwhale.api.service.api: Decorator to provide a simple Web Handler input definition based on Gradio.
  • login: Log in to the server/cloud instance.
  • logout: Log out of the server/cloud instance.

Data Types​

  • COCOObjectAnnotation: Provides COCO format definitions.
  • BoundingBox: Bounding box type, currently in LTWH format - left_x, top_y, width and height.
  • ClassLabel: Describes the number and types of labels.
  • Image: Image type.
  • GrayscaleImage: Grayscale image type, e.g. MNIST digit images, a special case of Image type.
  • Audio: Audio type.
  • Video: Video type.
  • Text: Text type, default utf-8 encoding, for storing large texts.
  • Binary: Binary type, stored in bytes, for storing large binary content.
  • Line: Line type.
  • Point: Point type.
  • Polygon: Polygon type.
  • Link: Link type, for creating remote-link data.
  • S3LinkAuth: When data is stored in S3-based object storage, this type describes auth and key info.
  • MIMEType: Describes multimedia types supported by Starwhale, used in mime_type attribute of Image, Video etc for better Dataset Viewer.
  • LinkType: Describes remote link types supported by Starwhale, currently LocalFS and S3.

Other​

  • __version__: Version of Starwhale Python SDK and swcli, string constant.

Further reading​