this is the shape of numpy array, (35628, 1, 16000)


i train/test split it
from sklearn.model_selection import train_test_split
x_train, x_test ,y_train, y_test = train_test_split(datan, label, test_size=0.2,  shuffle=True, random_state=40)
(this works fine)


make dataset from split arrays
import torch.utils.data as utils


tensor_x = torch.stack([torch.Tensor(i) for i in list(x_train)])
tensor_y = torch.Tensor(y_train)
my_dataset = utils.TensorDataset(tensor_x, tensor_y)
trainloader = utils.DataLoader(my_dataset, batch_size = 1)
tensor_xte = torch.stack([torch.Tensor(i) for i in list(x_test)])
tensor_yte = torch.Tensor(y_test)
my_datasette = utils.TensorDataset(tensor_xte, tensor_yte)
testloader = utils.DataLoader(my_datasette, batch_size = 1)
ERROR HERE!!! (session crashes in google colab)
This works well for all other dataset, but its not working only for this dataset.
is it becoz the data is large?? if yes, how do i do it.