[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

nemo/collections/asr/parts/utils/online_clustering.py

@@ -350,9 +350,7 @@ def merge_vectors(selected_inds: torch.Tensor, emb_ndx: torch.Tensor, pre_cluste
 
 
 @torch.jit.script
-def get_closest_embeddings(
-    affinity_mat: torch.Tensor, n_closest: int
-) -> Tuple[torch.Tensor, torch.Tensor]:
+def get_closest_embeddings(affinity_mat: torch.Tensor, n_closest: int) -> Tuple[torch.Tensor, torch.Tensor]:
     """
     Get the indices of the embedding vectors we want to merge.
 
@@ -387,9 +385,7 @@ def get_closest_embeddings(
     """
     comb_limit = int(affinity_mat.shape[0] - 1)
     if n_closest > comb_limit:
-        raise ValueError(
-            f"Got n_closest of {n_closest}: {n_closest} is bigger than comb_limit {comb_limit}"
-        )
+        raise ValueError(f"Got n_closest of {n_closest}: {n_closest} is bigger than comb_limit {comb_limit}")
 
     # Take summed values over one axis
     sum_cmat = affinity_mat.sum(0)
@@ -1046,7 +1042,9 @@ def match_labels(self, Y_new: torch.Tensor, add_new: bool) -> torch.Tensor:
                 try:
                     Y_out = torch.hstack((self.Y_fullhist[: self.history_buffer_seg_end], Y_matched[self.history_n :]))
                 except:
-                    import ipdb; ipdb.set_trace()
+                    import ipdb
+
+                    ipdb.set_trace()
                 self.Y_fullhist = Y_out
             else:
                 # Do not update cumulative labels since there are no new segments.
@@ -1058,11 +1056,7 @@ def match_labels(self, Y_new: torch.Tensor, add_new: bool) -> torch.Tensor:
         return Y_out
 
     def forward_infer(
-        self,
-        emb: torch.Tensor,
-        frame_index: int,
-        enhanced_count_thres: int = 40,
-        cuda: bool = False,
+        self, emb: torch.Tensor, frame_index: int, enhanced_count_thres: int = 40, cuda: bool = False,
     ) -> torch.Tensor:
         """
         Perform speaker clustering in online mode. Embedding vector set `emb` is expected to be containing

tests/collections/asr/test_diar_utils.py

@@ -582,7 +582,7 @@ def test_online_speaker_clustering(self, n_spks, total_sec, buffer_size, sigma,
         assert add_new
         cumul_label_acc = sum(evaluation_list) / len(evaluation_list)
         assert cumul_label_acc > 0.9
-    
+
     @pytest.mark.run_only_on('CPU')
     @pytest.mark.unit
     @pytest.mark.parametrize("n_spks", [4])
@@ -592,4 +592,3 @@ def test_online_speaker_clustering(self, n_spks, total_sec, buffer_size, sigma,
     @pytest.mark.parametrize("seed", [0])
     def test_online_speaker_clustering_cpu(self, n_spks, total_sec, buffer_size, sigma, seed):
         self.test_online_speaker_clustering(n_spks, total_sec, buffer_size, sigma, seed)
-