jorisvandenbossche commented on code in PR #38008:
URL: https://github.com/apache/arrow/pull/38008#discussion_r1414433628
##########
python/pyarrow/array.pxi:
##########
@@ -3586,6 +3586,156 @@ class FixedShapeTensorArray(ExtensionArray):
)
+cdef class VariableShapeTensorArray(ExtensionArray):
+ """
+ Concrete class for variable shape tensor extension arrays.
+
+ Examples
+ --------
+ Define the extension type for tensor array
+
+ >>> import pyarrow as pa
+ >>> tensor_type = pa.variable_shape_tensor(pa.int32(), 2)
+
+ Create an extension array
+
+ >>> shapes = pa.array([[2, 3], [1, 2]], pa.list_(pa.uint32(), 2))
+ >>> values = pa.array([[1, 2, 3, 4, 5, 6], [7, 8]], pa.list_(pa.int32()))
+ >>> arr = pa.StructArray.from_arrays([shapes, values], names=["shape",
"data"])
+ >>> pa.ExtensionArray.from_storage(tensor_type, arr)
+ <pyarrow.lib.VariableShapeTensorArray object at ...>
+ -- is_valid: all not null
+ -- child 0 type: fixed_size_list<item: uint32>[2]
+ [
+ [
+ 2,
+ 3
+ ],
+ [
+ 1,
+ 2
+ ]
+ ]
+ -- child 1 type: list<item: int32>
+ [
+ [
+ 1,
+ 2,
+ 3,
+ 4,
+ 5,
+ 6
+ ],
+ [
+ 7,
+ 8
+ ]
+ ]
+ """
+
+ def to_numpy_ndarray(self):
Review Comment:
Is this actually needed as a method to start with?
My expectation is that `to_numpy()` should ideally return this, but just as
an object-dtype numpy array of numpy arrays, instead of a list of numpy arrays.
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