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import torch from torch.utils.data import Dataset, DataLoader import pandas as pd class LargeCSVDataset(Dataset): def __init__(self, csv_file): self.csv_file = csv_file self.len = sum(1 for line in open(csv_file)) - 1 # number of data rows (minus 1 for the header) def __getitem__(self, index): # Skip rows until reaching the row with the requested index data = pd.read_csv(self.csv_file, skiprows=range(1, index + 1), nrows=1) # Assuming that the last column is the target and the rest are features target = torch.tensor(data.iloc[0, -1]) features = torch.tensor(data.iloc[0, :-1].values) return features, target def __len__(self): return self.len # Use the custom dataset dataset = LargeCSVDataset('large_dataset.csv') # Create a DataLoader dataloader = DataLoader(dataset, batch_size=32, shuffle=True)
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