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.. _guide-data-pipeline-savenload:
4.4 Save and load data
----------------------
:ref:`(中文版) <guide_cn-data-pipeline-savenload>`
DGL recommends implementing saving and loading functions to cache the
processed data in local disk. This saves a lot of data processing time
in most cases. DGL provides four functions to make things simple:
- :func:`dgl.save_graphs` and :func:`dgl.load_graphs`: save/load DGLGraph objects and labels to/from local disk.
- :func:`dgl.data.utils.save_info` and :func:`dgl.data.utils.load_info`: save/load useful information of the dataset (python ``dict`` object) to/from local disk.
The following example shows how to save and load a list of graphs and
dataset information.
.. code::
import os
from dgl import save_graphs, load_graphs
from dgl.data.utils import makedirs, save_info, load_info
def save(self):
# save graphs and labels
graph_path = os.path.join(self.save_path, self.mode + '_dgl_graph.bin')
save_graphs(graph_path, self.graphs, {'labels': self.labels})
# save other information in python dict
info_path = os.path.join(self.save_path, self.mode + '_info.pkl')
save_info(info_path, {'num_classes': self.num_classes})
def load(self):
# load processed data from directory `self.save_path`
graph_path = os.path.join(self.save_path, self.mode + '_dgl_graph.bin')
self.graphs, label_dict = load_graphs(graph_path)
self.labels = label_dict['labels']
info_path = os.path.join(self.save_path, self.mode + '_info.pkl')
self.num_classes = load_info(info_path)['num_classes']
def has_cache(self):
# check whether there are processed data in `self.save_path`
graph_path = os.path.join(self.save_path, self.mode + '_dgl_graph.bin')
info_path = os.path.join(self.save_path, self.mode + '_info.pkl')
return os.path.exists(graph_path) and os.path.exists(info_path)
Note that there are cases not suitable to save processed data. For
example, in the builtin dataset :class:`~dgl.data.GDELTDataset`,
the processed data is quite large, so it’s more effective to process
each data example in ``__getitem__(idx)``.