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@1pha
Created May 28, 2021 05:10
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Understanding collate_fn
import torch
from torch.utils.data import Dataset, DataLoader
import numpy as np
class MyDataset(Dataset):
def __init__(self):
x = np.random.randint(10, size=[1000, 3]) # 1000 3-dim samples
self.x = [x[i].tolist() for i in range(1000)]
y = np.random.randint(low=0, high=2, size=(1000,))
self.y = [y[i] for i in range(1000)]
def __len__(self):
return len(self.x)
def __getitem__(self, idx):
return self.x[idx], self.y[idx]
def collate_fn(batch):
print(f"batch: {batch}")
data_list, label_list = [], []
for _data, _label in batch:
data_list.append(_data)
label_list.append(_label)
return torch.Tensor(data_list), torch.LongTensor(label_list)
if __name__ == "__main__":
dataset = MyDataset()
print(len(dataset))
print(dataset[-1])
print(f"\nWITHOUT COLLATE_FN")
dataloader = DataLoader(dataset, batch_size=3, shuffle=False)
for data, label in dataloader:
print(data)
print(label)
break
print(f"\nWITH COLLATE_FN")
dataloader = DataLoader(dataset, batch_size=3, shuffle=False, collate_fn=collate_fn)
for data, label in dataloader:
print(data)
print(label)
break
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1pha commented May 28, 2021

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