Starwhale Model SDK

model.build

model.build is a function that can build the Starwhale model, equivalent to the swcli model build command.

def build(
    modules: t.Optional[t.List[t.Any]] = None,
    workdir: t.Optional[_path_T] = None,
    name: t.Optional[str] = None,
    project_uri: str = "",
    desc: str = "",
    remote_project_uri: t.Optional[str] = None,
    add_all: bool = False,
    tags: t.List[str] | None = None,
) -> None:

Parameters

• modules: (List[str|object], optional)
  • The search modules supports object(function, class or module) or str(example: "to.path.module", "to.path.module:object").
  • If the argument is not specified, the search modules are the imported modules.
• name: (str, optional)
  • Starwhale Model name.
  • The default is the current work dir (cwd) name.
• workdir: (str, Pathlib.Path, optional)
  • The path of the rootdir. The default workdir is the current working dir.
  • All files in the workdir will be packaged. If you want to ignore some files, you can add .swignore file in the workdir.
• project_uri: (str, optional)
  • The project uri of the Starwhale Model.
  • If the argument is not specified, the project_uri is the config value of swcli project select command.
• desc: (str, optional)
  • The description of the Starwhale Model.
• remote_project_uri: (str, optional)
  • Project URI of another example instance. After the Starwhale model is built, it will be automatically copied to the remote instance.
• add_all: (bool, optional)
  • Add all files in the working directory to the model package(excludes python cache files and virtual environment files when disabled).The .swignore file still takes effect.
  • The default value is False.
• tags: (List[str], optional)
  • The tags for the model version.
  • latest and ^v\d+$ tags are reserved tags.

Examples

from starwhale import model

# class search handlers
from .user.code.evaluator import ExamplePipelineHandler
model.build([ExamplePipelineHandler])

# function search handlers
from .user.code.evaluator import predict_image
model.build([predict_image])

# module handlers, @handler decorates function in this module
from .user.code import evaluator
model.build([evaluator])

# str search handlers
model.build(["user.code.evaluator:ExamplePipelineHandler"])
model.build(["user.code1", "user.code2"])

# no search handlers, use imported modules
model.build()

# add user custom tags
model.build(tags=["t1", "t2"])