rechunk padded values, handle 1 sized datasets

xarray/core/computation.py

@@ -1507,8 +1507,9 @@ def cross(a, b, dim):
     for i, arr in enumerate(arrays):
         if isinstance(arr, Dataset):
             is_dataset = True
-            # TODO: How make sure this temporary dimension is matches
-            # the orther dataset?
+            # Turn the dataset to a stacked dataarray to follow the
+            # normal code path. Then at the end turn it back to a
+            # dataset.
             arrays[i] = arr = arr.to_stacked_array(
                 variable_dim=dim, new_dim="variable", sample_dims=arr.dims
             ).unstack("variable")
@@ -1546,6 +1547,8 @@ def cross(a, b, dim):
             # If the array doesn't have coords we can can only infer
             # that it is composite values if the size is 2:
             arrays[i] = arrays[i].pad({dim: (0, 1)}, constant_values=0)
+            if is_duck_dask_array(arrays[i].data):
+                arrays[i] = arrays[i].chunk({dim: -1})
         else:
             # Size is 1, then we do not know if the array is a constant or
             # composite value:
@@ -1565,6 +1568,9 @@ def cross(a, b, dim):
     c = c.transpose(*[d for d in all_dims if d in c.dims])
     if is_dataset:
         c = c.stack(variable=[dim]).to_unstacked_dataset("variable")
+        c = c.expand_dims(
+            [dim for ds in arrays for dim, size in ds.sizes.items() if size == 1]
+        )
 
     return c