I have a dataset that looks like below. That is the first item is the user id followed by the set of items which is clicked by the user.
0 24104 27359 6684
0 24104 27359
1 16742 31529 31485
1 16742 31529
2 6579 19316 13091 7181 6579 19316 13091
2 6579 19316 13091 7181 6579 19316
2 6579 19316 13091 7181 6579 19316 13091 6579
2 6579 19316 13091 7181 6579
4 19577 21608
4 19577 21608
4 19577 21608 18373
5 3541 9529
5 3541 9529
6 6832 19218 14144
6 6832 19218
7 9751 23424 25067 12606 26245 23083 12606
I define a custom dataset to handle my click log data.
import torch.utils.data as data
class ClickLogDataset(data.Dataset):
def __init__(self, data_path):
self.data_path = data_path
self.uids = []
self.streams = []
with open(self.data_path, 'r') as fdata:
for row in fdata:
row = row.strip('\n').split('\t')
self.uids.append(int(row[0]))
self.streams.append(list(map(int, row[1:])))
def __len__(self):
return len(self.uids)
def __getitem__(self, idx):
uid, stream = self.uids[idx], self.streams[idx]
return uid, stream
Then I use a DataLoader to retrieve mini batches from the data for training.
from torch.utils.data.dataloader import DataLoader
clicklog_dataset = ClickLogDataset(data_path)
clicklog_data_loader = DataLoader(dataset=clicklog_dataset, batch_size=16)
for uid_batch, stream_batch in stream_data_loader:
print(uid_batch)
print(stream_batch)
The code above returns differently from what I expected, I want stream_batch
to be a 2D tensor of type integer of length 16
. However, what I get is a list of 1D tensor of length 16, and the list has only one element, like below. Why is that ?
#stream_batch
[tensor([24104, 24104, 16742, 16742, 6579, 6579, 6579, 6579, 19577, 19577,
19577, 3541, 3541, 6832, 6832, 9751])]
So how do you handle the fact that your samples are of different length? torch.utils.data.DataLoader
has a collate_fn
parameter which is used to transform a list of samples into a batch. By default it does this to lists. You can write your own collate_fn
, which for instance 0
-pads the input, truncates it to some predefined length or applies any other operation of your choice.