Docs: add spatial shape constraints to SegResNetDS docstring

monai/networks/nets/segresnet_ds.py

@@ -254,6 +254,20 @@ class SegResNetDS(nn.Module):
                     image spacing into an approximately isotropic space.
                     Otherwise, by default, the kernel size and downsampling is always isotropic.
 
+                    **Spatial shape constraints**: If ``resolution`` is ``None`` (isotropic mode),
+                    each spatial dimension must be divisible by ``2 ** (len(blocks_down) - 1)``.
+                    With the default ``blocks_down=(1, 2, 2, 4)``, each dimension must be
+                    divisible by 8. If ``resolution`` is provided (anisotropic mode),
+                    divisibility can differ per dimension; use :py:meth:`shape_factor` for
+                    the exact required factors and :py:meth:`is_valid_shape` to verify a shape.
+
+                    Example::
+
+                        model = SegResNetDS(spatial_dims=3, blocks_down=(1, 2, 2, 4))
+                        print(model.shape_factor())  # [8, 8, 8]
+                        print(model.is_valid_shape((1, 1, 128, 128, 128)))  # True
+                        print(model.is_valid_shape((1, 1, 100, 100, 100)))  # False
+
     """
 
     def __init__(