Post rebase

docs/source/format/CanonicalExtensions.rst

@@ -206,21 +206,6 @@ Variable shape tensor
     This allows for interpreting the tensor correctly without accounting for
     uniform dimensions while still permitting optional optimizations that
     take advantage of the uniformity.
-  * **uniform_dimensions** = indices of dimensions whose sizes are
-    guaranteed to remain constant. Indices are a subset of all possible
-    dimension indices ([0, 1, .., N-1]).
-    The uniform dimensions must still be represented in the `shape` field,
-    and must always be the same value for all tensors in the array -- this
-    allows code to interpret the tensor correctly without accounting for
-    uniform dimensions while still permitting optional optimizations that
-    take advantage of the uniformity. uniform_dimensions can be left out,
-    in which case it is assumed that all dimensions might be variable.
-
-  * **uniform_shape** = shape of the dimensions that are guaranteed to stay
-    constant over all tensors in the array, with the shape of the ragged dimensions
-    set to 0.
-    An array containing tensor with shape (2, 3, 4) and uniform dimensions
-    (0, 2) would have uniform shape (2, 0, 4).
 
 * Description of the serialization:
 
@@ -242,11 +227,6 @@ Variable shape tensor
 
     ``{ "dim_names": ["H", "W", "C"], "uniform_shape": [400, null, 3] }``
 
-  - Example with ``uniform_dimensions`` metadata for a set of color images
-    with variable width:
-
-    ``{ "dim_names": ["H", "W", "C"], "uniform_dimensions": [1] }``
-
   - Example of permuted 3-dimensional tensor:
 
     ``{ "permutation": [2, 0, 1] }``
@@ -271,9 +251,6 @@ Variable shape tensor
    Values inside each **data** tensor element are stored in row-major/C-contiguous
    order according to the corresponding **shape**.
 
-  Elements in a variable shape tensor extension array are stored
-  in row-major/C-contiguous order.
-
 =========================
 Community Extension Types
 =========================

python/pyarrow/tests/test_extension_type.py

@@ -1498,7 +1498,7 @@ def test_tensor_type_is_picklable(pickle_module):
         'fixed_shape_tensor[value_type=int64, shape=[2,2,3], dim_names=[C,H,W]]'
     )
 ])
-def test_tensor_type_str(tensor_type, text):
+def test_tensor_type_str(tensor_type, text, pickle_module):
     tensor_type_str = tensor_type.__str__()
     assert text in tensor_type_str