NotImplemented Error while running ImbalancedDatasetSampler

[aryamansriram]

I followed the steps exactly according to the readme file. Yet I am getting a notimplemented error. There's no explanation for the error as well.

Here's my code:
`from torchvision import transforms
from torchsampler import ImbalancedDatasetSampler

batch_size = 128
val_split = 0.2
shuffle_dataset=True
random_seed=42

dataset_size = len(melanoma_dataset)
indices = list(range(dataset_size))
split = int(np.floor(val_split * dataset_size))
if shuffle_dataset :
np.random.seed(random_seed)
np.random.shuffle(indices)
train_indices, test_indices = indices[split:], indices[:split]

train_loader = torch.utils.data.DataLoader(melanoma_dataset,batch_size=batch_size,sampler=ImbalancedDatasetSampler(melanoma_dataset))
test_loader = torch.utils.data.DataLoader(melanoma_dataset,batch_size=batch_size,sampler=test_sampler)`

[polm]

Having the same issue - no detailed error message, just a NotImplementedError.

It looks like the code only supports MNIST, Subsets, or an ImageFolder out of the box. If you have a custom dataset you need to implement callback_get_label.

[SorenJ89]

If anyone reads this, this worked for me:

def callback_get_label(dataset, idx):
    #callback function used in imbalanced dataset loader.
    input, target = dataset[idx]
    return np.argwhere(target.numpy()).item()

Edit: I suspect it would be faster to not cast the tensor to numpy, so the following change should do the same within the tensor framework:

def callback_get_label(dataset, idx):
    #callback function used in imbalanced dataset loader.
    input, target = dataset[idx]
    return target.nonzero().item()

[PaleNeutron]

If you have an int label, try use this:

def callback_get_label(dataset, idx):
    #callback function used in imbalanced dataset loader.
    i, target = dataset[idx]
    return int(target)

[robinzhaorr]

If you have an int label, try use this:

def callback_get_label(dataset, idx):
    #callback function used in imbalanced dataset loader.
    i, target = dataset[idx]
    return int(target)

For those who are new to Python like me: define the 'callback_get_label' function before you initialize the train_loader, and make your function like:
train_loader = DataLoader(dataset, ImbalancedDatasetSampler(dataset,callback_get_label = callback_get_label),batch_size = batch_size)

[Borda]

@ufoym this is solved, can be closed 🐰

[ufoym]

@Borda Thanks pretty much for your contribution!

[Andybrizt]

If you have an int label, try use this:

def callback_get_label(dataset, idx):
    #callback function used in imbalanced dataset loader.
    i, target = dataset[idx]
    return int(target)

For those who are new to Python like me: define the 'callback_get_label' function before you initialize the train_loader, and make your function like: train_loader = DataLoader(dataset, ImbalancedDatasetSampler(dataset,callback_get_label = callback_get_label),batch_size = batch_size)

I got this error:
TypeError: callback_get_label() missing 1 required positional argument: 'idx'

could you tell where to define the callback_get_label() function?

[robinzhaorr]

This? def callback_get_label(dataset, idx): #callback function used in imbalanced dataset loader. i, target = dataset[idx] return int(target)

…

On Thu, May 19, 2022 at 2:18 AM xong ***@***.***> wrote: If you have an int label, try use this: def callback_get_label(dataset, idx): #callback function used in imbalanced dataset loader. i, target = dataset[idx] return int(target) For those who are new to Python like me: define the 'callback_get_label' function before you initialize the train_loader, and make your function like: train_loader = DataLoader(dataset, ImbalancedDatasetSampler(dataset,callback_get_label = callback_get_label),batch_size = batch_size) I got this error: TypeError: callback_get_label() missing 1 required positional argument: 'idx' could you tell where to define the callback_get_label() function? — Reply to this email directly, view it on GitHub <#18 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/APLVASGMETIEKAM4C7LO7YTVKUX6DANCNFSM4OBNKJSQ> . You are receiving this because you commented.Message ID: ***@***.***>