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Load python object saved by MLEM.
def load(
path: Union[str, os.PathLike],
project: Optional[str] = None,
rev: Optional[str] = None,
batch_size: Optional[int] = None,
follow_links: bool = True,
try_migrations: bool = False,
) -> Any
import os
from mlem.api import load
out_path = os.path.join(os.getcwd(), "saved-model")
loaded = load(out_path)
Loads a Python object from a given path. The path can belong to different file
systems (eg: S3
). The function returns the underlying Python object saved by
MLEM.
path
(required) - Path to the object. Could be local path or path inside
a git repo.project
(optional) - URL to project if object is located there.rev
(optional) - revision, could be git commit SHA, branch name or tag.follow_links
(optional) - If object we read is a MLEM link, whether to load
theactual object link points to. Defaults to True.Any
: Python object saved by MLEM
None
import os
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from mlem.api import load
path = os.path.join(os.getcwd(), "saved-model")
model = load(path)
assert isinstance(model, DecisionTreeClassifier)
train, _ = load_iris(return_X_y=True)
model.predict(train)