@@ -209,7 +209,7 @@ class SwapResult:
209209 score_change : float
210210
211211
212- SwapFucntion : TypeAlias = Callable [[npt .NDArray [np .bool_ ], bool ], SwapResult ]
212+ SwapFunction : TypeAlias = Callable [[npt .NDArray [np .bool_ ], bool ], SwapResult ]
213213
214214
215215def make_swaps_2 (actmat : npt .NDArray [np .bool_ ], use_cupy : bool = True ) -> SwapResult :
@@ -229,7 +229,7 @@ def make_swaps_2(actmat: npt.NDArray[np.bool_], use_cupy: bool = True) -> SwapRe
229229 # Sum score_change[i, j] + score_change[j, i] to get the cumulative impact of the swap.
230230 score_change = score_change + score_change .T
231231
232- def all_indices_in_same_block (i : int ) -> list [int ]:
232+ def all_indices_in_same_block (i : np . int_ ) -> list [int ]:
233233 """Returns a list of indices of all neurons in the same block as the i-th neuron."""
234234 # Floor to the start of the block.
235235 base = i // ZERO_BLOCK_SIZE * ZERO_BLOCK_SIZE
@@ -373,7 +373,7 @@ def find_perm_impl(
373373 total_score_change = 0
374374 perm = np .arange (L1 // 2 )
375375
376- stages : list [SwapFucntion ] = [make_swaps_2 , make_swaps_3 ]
376+ stages : list [SwapFunction ] = [make_swaps_2 , make_swaps_3 ]
377377 # The optimization routines are deterministic, so no need to retry.
378378 stages_max_fails = [0 , 0 ]
379379 stage_id = 0
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