rok commented on code in PR #37533:
URL: https://github.com/apache/arrow/pull/37533#discussion_r1435214317
##########
python/pyarrow/array.pxi:
##########
@@ -3519,17 +3519,42 @@ class FixedShapeTensorArray(ExtensionArray):
def to_numpy_ndarray(self):
Review Comment:
`to_numpy`
```python
import pyarrow as pa
arrow_type = pa.int8()
tensor_type = pa.fixed_shape_tensor(arrow_type, [2, 3])
storage = pa.array([[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]],
pa.list_(arrow_type, 6))
arr = pa.ExtensionArray.from_storage(tensor_type, storage)
arr.to_numpy(zero_copy_only=False)
```
already returns storage arrays:
```
array([array([1, 2, 3, 4, 5, 6], dtype=int8),
array([ 7, 8, 9, 10, 11, 12], dtype=int8)], dtype=object)
```
We agreed (with @jorisvandenbossche and @AlenkaF ), in a thread I can't
find now, to use `to_numpy_ndarray` for getting tensors from
`FixedShapeTensorArray` into numpy. I'd use the same convention for
`from_numpy_ndarray` to go from `ndarray` into `FixedShapeTensorArray`
##########
python/pyarrow/scalar.pxi:
##########
@@ -1027,6 +1027,32 @@ cdef class ExtensionScalar(Scalar):
return pyarrow_wrap_scalar(<shared_ptr[CScalar]> sp_scalar)
+cdef class FixedShapeTensorScalar(ExtensionScalar):
+ """
+ Concrete class for fixed shape tensor extension scalar.
+ """
+
+ def to_numpy_ndarray(self):
Review Comment:
See above.
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