Check whether the buffer is empty (#468)

Apparently, PyTorch does not handle CUDA array interface well if the
tensor is empty.

Instead of saying 'failed to convert', it is better to warn users that
the buffer is empty, because it is likely not what users intend.

Author: mthrok

src/spdl/io/_convert.py

@@ -51,12 +51,15 @@ def to_torch(buffer: CPUBuffer | CUDABuffer):
     Returns:
         (torch.Tensor): A PyTorch Tensor.
     """
-    if hasattr(buffer, "__cuda_array_interface__"):
+    if (interface := getattr(buffer, "__cuda_array_interface__", None)) is not None:
         # Note: this is to silence pyre errors.
         # Usually, it should be asserting that `buffer` is a CUDABuffer,
         # but CUDABuffer class is a stub, so it would fail.
         assert not isinstance(buffer, CPUBuffer)
-        data_ptr = buffer.__cuda_array_interface__["data"][0]
+        if any(s == 0 for s in interface.get("shape", [])):
+            raise ValueError("0-element array is not supported.")
+
+        data_ptr = interface["data"][0]
         tensor = torch.as_tensor(buffer, device=f"cuda:{buffer.device_index}")
         if tensor.data_ptr() == 0:
             raise RuntimeError(