Created
May 11, 2019 15:13
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import torch | |
from torch_geometric.data import InMemoryDataset | |
class MyOwnDataset(InMemoryDataset): | |
def __init__(self, root, transform=None, pre_transform=None): | |
super(MyOwnDataset, self).__init__(root, transform, pre_transform) | |
self.data, self.slices = torch.load(self.processed_paths[0]) | |
@property | |
def raw_file_names(self): | |
return ['some_file_1', 'some_file_2', ...] | |
@property | |
def processed_file_names(self): | |
return ['data.pt'] | |
def download(self): | |
# Download to `self.raw_dir`. | |
def process(self): | |
# Read data into huge `Data` list. | |
data_list = [...] | |
if self.pre_filter is not None: | |
data_list [data for data in data_list if self.pre_filter(data)] | |
if self.pre_transform is not None: | |
data_list = [self.pre_transform(data) for data in data_list] | |
data, slices = self.collate(data_list) | |
torch.save((data, slices), self.processed_paths[0]) |
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