Create Data_loader.py

Data_loader.py

@@ -0,0 +1,20 @@
+# utils/data_loader.py
+import torch
+from torch.utils.data import Dataset, DataLoader
+
+class CustomDataset(Dataset):
+    def __init__(self, data):
+        self.data = data
+
+    def __len__(self):
+        return len(self.data)
+
+    def __getitem__(self, idx):
+        return self.data[idx]
+
+def load_data(batch_size=32):
+    # Dummy data
+    data = [torch.randn(10) for _ in range(1000)]
+    dataset = CustomDataset(data)
+    loader = DataLoader(dataset, batch_size=batch_size, shuffle=True)
+    return loader