In Pytorch, is there any way of loading a specific single sample using the torch.utils.data.DataLoader
class? I'd like to do some testing with it.
The tutorial uses
trainloader = torch.utils.data.DataLoader(...)
images, labels = next(iter(trainloader))
to fetch a random batch of samples. Is there are way, using DataLoader
, to get a specific sample?
Cheers
shuffle
in DataLoader
batch_size
to calculate the batch in which the desired sample you are looking for falls inimport torch
import numpy as np
import itertools
X= np.arange(100)
batch_size = 2
dataloader = torch.utils.data.DataLoader(X, batch_size=batch_size, shuffle=False)
sample_at = 5
k = int(np.floor(sample_at/batch_size))
my_sample = next(itertools.islice(dataloader, k, None))
print (my_sample)
Output:
tensor([4, 5])
if you want to get a specific signle sample from your dataset you can
you should check Subset class.( https://pytorch.org/docs/stable/data.html#torch.utils.data.Subset ) something like this:
indices = [0,1,2] # select your indices here as a list
subset = torch.utils.data.Subset(train_set, indices)
trainloader = DataLoader(subset , batch_size = 16 , shuffle =False) #set shuffle to False
for image , label in trainloader:
print(image.size() , '\t' , label.size())
print(image[0], '\t' , label[0]) # index the specific sample
here is a useful link if you want to learn more about the Pytorch data loading utility ( https://pytorch.org/docs/stable/data.html )
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