pvardanis opened a new issue, #36890: URL: https://github.com/apache/arrow/issues/36890
### Describe the usage question you have. Please include as many useful details as possible. I'm following from the official [docs](https://arrow.apache.org/docs/python/extending_types.html#fixed-size-tensor) on how to create a fixed size tensor and store it in a `pyarrow.Table`: ```python data = [ pa.array([1, 2, 3]), pa.array(['foo', 'bar', None]), pa.array([True, None, True]), tensor_array, tensor_array_2 ] my_schema = pa.schema([('f0', pa.int8()), ('f1', pa.string()), ('f2', pa.bool_()), ('tensors_int', tensor_type), ('tensors_float', tensor_type_2)]) table = pa.Table.from_arrays(data, schema=my_schema) table ``` While it's possible to do: ```python numpy_tensor = tensor_array_2.to_numpy_ndarray() ``` I cannot achieve the same if I retrieve `tensor_array_2` from the table like this: ```python table.column("tensors_float").to_numpy_ndarray() ``` I get the following error: ``` Traceback (most recent call last): File "<string>", line 1, in <module> AttributeError: 'pyarrow.lib.ChunkedArray' object has no attribute 'to_numpy_ndarray' ``` ### Component(s) Python -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
