Fix TorchRuntimeError

✅ Solution

TorchRuntimeError usually indicates an issue with tensor sizes, data types, or device placement conflicts within a PyTorch operation. Inspect the failing code for mismatched tensor shapes in operations like addition, matrix multiplication, or loss calculations, and explicitly move tensors to the same device (CPU or GPU) using `.to(device)` to ensure compatibility. Additionally, verify input data types are appropriate for the involved PyTorch functions, casting if necessary using `.float()` or `.long()`.