I have the following code:
import torch
import numpy as np
import pandas as pd
from torch.utils.data import TensorDataset, DataLoader
# Load dataset
df = pd.read_csv(r'../iris.csv')
# Extract features and target
data = df.drop('target',axis=1).values
labels = df['target'].values
# Create tensor dataset
iris = TensorDataset(torch.FloatTensor(data),torch.LongTensor(labels))
# Create random batches
iris_loader = DataLoader(iris, batch_size=105, shuffle=True)
next(iter(iris_loader))
What does next()
and iter()
do in the above code? I have went through PyTorch's documentation and still can't quite understand what is next()
and iter()
doing here. Can anyone help in explaining this? Many thanks in advance.