wehub-resource-sync
58 lines
2.0 KiB
Python
58 lines
2.0 KiB
Python
# -*- coding:utf-8 -*-
|
|
# Author: hankcs
|
|
# Date: 2019-06-13 18:05
|
|
import hanlp.common
|
|
import hanlp.components
|
|
import hanlp.pretrained
|
|
import hanlp.utils
|
|
from hanlp.version import __version__
|
|
|
|
hanlp.utils.ls_resource_in_module(hanlp.pretrained)
|
|
|
|
|
|
def load(save_dir: str, verbose=None, **kwargs) -> hanlp.common.component.Component:
|
|
"""Load a pretrained component from an identifier.
|
|
|
|
Args:
|
|
save_dir (str): The identifier to the saved component. It could be a remote URL or a local path.
|
|
verbose: ``True`` to print loading progress.
|
|
**kwargs: Arguments passed to :func:`hanlp.common.torch_component.TorchComponent.load`, e.g.,
|
|
``devices`` is a useful argument to specify which GPU devices a PyTorch component will use.
|
|
|
|
Examples::
|
|
|
|
import hanlp
|
|
# Load component onto the 0-th GPU.
|
|
hanlp.load(..., devices=0)
|
|
# Load component onto the 0-th and 1-st GPUs using data parallelization.
|
|
hanlp.load(..., devices=[0, 1])
|
|
|
|
.. Note::
|
|
A component can have dependencies on other components or resources, which will be recursively loaded. So it's
|
|
common to see multiple downloading messages per single load.
|
|
|
|
Returns:
|
|
hanlp.common.component.Component: A pretrained component.
|
|
|
|
"""
|
|
save_dir = hanlp.pretrained.ALL.get(save_dir, save_dir)
|
|
from hanlp.utils.component_util import load_from_meta_file
|
|
if verbose is None:
|
|
from hanlp_common.constant import HANLP_VERBOSE
|
|
verbose = HANLP_VERBOSE
|
|
return load_from_meta_file(save_dir, 'meta.json', verbose=verbose, **kwargs)
|
|
|
|
|
|
def pipeline(*pipes) -> hanlp.components.pipeline.Pipeline:
|
|
"""Creates a pipeline of components. It's made for bundling `KerasComponents`. For `TorchComponent`, use
|
|
:class:`~hanlp.components.mtl.multi_task_learning.MultiTaskLearning` instead.
|
|
|
|
Args:
|
|
*pipes: Components if pre-defined any.
|
|
|
|
Returns:
|
|
hanlp.components.pipeline.Pipeline: A pipeline, which is a list of components in order.
|
|
|
|
"""
|
|
return hanlp.components.pipeline.Pipeline(*pipes)
|