Renamed the private Objective cost function iterator to _get_iterator().

theseus/core/objective.py

@@ -489,7 +489,7 @@ def update_vectorization(self):
     def __iter__(self):
         return iter([cf for cf in self.cost_functions.values()])
 
-    def _vectorized_iter(self):
+    def _get_iterator(self):
         if self._cost_functions_iterable is None:
             return iter([cf for cf in self.cost_functions.values()])
         return iter([cf for cf in self._cost_functions_iterable])

theseus/core/tests/test_vectorizer.py

@@ -48,7 +48,7 @@ def _check_attr(cf, var):
         # Check that the vectorizer's cost functions have the right variables and error
         saw_cf1 = False
         saw_cf2 = False
-        for cf in objective._vectorized_iter():
+        for cf in objective._get_iterator():
             assert isinstance(cf, _CostFunctionWrapper)
             optim_vars = [v for v in cf.optim_vars]
             aux_vars = [v for v in cf.aux_vars]

theseus/optimizer/dense_linearization.py

@@ -38,7 +38,7 @@ def _linearize_jacobian_impl(self):
             device=self.objective.device,
             dtype=self.objective.dtype,
         )
-        for cost_function in self.objective._vectorized_iter():
+        for cost_function in self.objective._get_iterator():
             jacobians, error = cost_function.weighted_jacobians_error()
             num_rows = cost_function.dim()
             for var_idx_in_cost_function, var_jacobian in enumerate(jacobians):

theseus/optimizer/sparse_linearization.py

@@ -38,7 +38,7 @@ def __init__(
         cost_function_row_block_starts = []  # where data start for this row block
         cost_function_stride = []  # total jacobian cols
 
-        for _, cost_function in enumerate(self.objective._vectorized_iter()):
+        for _, cost_function in enumerate(self.objective._get_iterator()):
             num_rows = cost_function.dim()
             col_slices_indices = []
             for var_idx_in_cost_function, variable in enumerate(
@@ -101,7 +101,7 @@ def _linearize_jacobian_impl(self):
         )
 
         err_row_idx = 0
-        for f_idx, cost_function in enumerate(self.objective._vectorized_iter()):
+        for f_idx, cost_function in enumerate(self.objective._get_iterator()):
             jacobians, error = cost_function.weighted_jacobians_error()
             num_rows = cost_function.dim()
             row_slice = slice(err_row_idx, err_row_idx + num_rows)