convert: prevent ndarray conversion in LazyChunkedTensor

gguf-py/gguf/gguf_writer.py

@@ -467,10 +467,15 @@ def write_tensors_to_file(self, *, progress: bool = False) -> None:
                     shard_bar.reset(total=(total if total > 0 else None))
 
                 # relying on the fact that Python dicts preserve insertion order (since 3.7)
-                for ti in tensors.values():
+                for name, ti in tensors.items():
                     assert ti.tensor is not None  # can only iterate once over the tensors
                     assert ti.tensor.nbytes == ti.nbytes
+                    start = fout.tell()
                     ti.tensor.tofile(fout)
+                    # a short write here would only surface as a corrupt file at load time
+                    if fout.tell() - start != ti.nbytes:
+                        raise ValueError(
+                            f"tensor {name!r} wrote {fout.tell() - start} bytes, expected {ti.nbytes}")
                     if shard_bar is not None:
                         shard_bar.update(ti.nbytes)
                     if bar is not None:

gguf-py/gguf/lazy.py

@@ -251,6 +251,10 @@ def nbytes(self) -> int:
     def numpy(self) -> LazyChunkedTensor:
         return self
 
+    def __array__(self, *args, **kwargs):
+        # numpy would otherwise make a 1-element object array of self, and write 8 bytes
+        raise TypeError("LazyChunkedTensor cannot become an ndarray, it is written in chunks")
+
     def quantize(self, qtype: Any) -> LazyChunkedTensor:
         from .constants import GGMLQuantizationType
         from .quants import QuantError, quant_shape_to_byte_shape