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dataloader.py
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dataloader.py
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import torch.utils.data
from torch.utils.data.dataloader import default_collate
from batch import BatchSubstructContext, BatchMasking, BatchAE
class DataLoaderSubstructContext(torch.utils.data.DataLoader):
r"""Data loader which merges data objects from a
:class:`torch_geometric.data.dataset` to a mini-batch.
Args:
dataset (Dataset): The dataset from which to load the data.
batch_size (int, optional): How may samples per batch to load.
(default: :obj:`1`)
shuffle (bool, optional): If set to :obj:`True`, the data will be
reshuffled at every epoch (default: :obj:`True`)
"""
def __init__(self, dataset, batch_size=1, shuffle=True, **kwargs):
super(DataLoaderSubstructContext, self).__init__(
dataset,
batch_size,
shuffle,
collate_fn=lambda data_list: BatchSubstructContext.from_data_list(data_list),
**kwargs)
class DataLoaderMasking(torch.utils.data.DataLoader):
r"""Data loader which merges data objects from a
:class:`torch_geometric.data.dataset` to a mini-batch.
Args:
dataset (Dataset): The dataset from which to load the data.
batch_size (int, optional): How may samples per batch to load.
(default: :obj:`1`)
shuffle (bool, optional): If set to :obj:`True`, the data will be
reshuffled at every epoch (default: :obj:`True`)
"""
def __init__(self, dataset, batch_size=1, shuffle=True, **kwargs):
super(DataLoaderMasking, self).__init__(
dataset,
batch_size,
shuffle,
collate_fn=lambda data_list: BatchMasking.from_data_list(data_list),