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

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

nemo/collections/asr/models/label_models.py

@@ -502,4 +502,4 @@ def get_batch_embeddings(speaker_model, manifest_filepath, batch_size=32, sample
 
         all_logits, true_labels, all_embs = np.asarray(all_logits), np.asarray(all_labels), np.asarray(all_embs)
 
-        return all_embs, all_logits, true_labels, dataset.id2label
+        return all_embs, all_logits, true_labels, dataset.id2label

nemo/collections/nlp/models/language_modeling/megatron_gpt_prompt_learning_model.py

@@ -1013,4 +1013,4 @@ def get_pseudo_tokens(num_virtual_tokens):
         for i in range(num_virtual_tokens)
     ]
 
-    return pseudo_tokens
+    return pseudo_tokens

nemo/collections/nlp/modules/common/__init__.py

@@ -39,4 +39,4 @@
 from nemo.collections.nlp.modules.common.sequence_regression import SequenceRegression
 from nemo.collections.nlp.modules.common.sequence_token_classifier import SequenceTokenClassifier
 from nemo.collections.nlp.modules.common.token_classifier import BertPretrainingTokenClassifier, TokenClassifier
-from nemo.collections.nlp.modules.common.tokenizer_utils import get_tokenizer, get_tokenizer_list
+from nemo.collections.nlp.modules.common.tokenizer_utils import get_tokenizer, get_tokenizer_list

nemo/collections/nlp/modules/common/prompt_encoder.py

@@ -295,4 +295,4 @@ def forward(self, taskname_embeddings) -> torch.Tensor:
         else:
             raise ValueError("Prompt encoder type not recognized. Please use one of MLP (recommended) or LSTM.")
 
-        return output_embeds
+        return output_embeds

nemo_text_processing/text_normalization/zh/data/char/__init__.py

@@ -10,4 +10,4 @@
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
-# limitations under the License.
+# limitations under the License.

tests/core/test_exp_manager.py

@@ -571,4 +571,4 @@ class CustomLoop(TrainingEpochLoop):
         loop.trainer = trainer
         trainer.fit_loop.epoch_loop = loop
         with pytest.warns(UserWarning, match="Detected custom epoch loop"):
-            exp_manager(trainer, {"explicit_log_dir": str(tmp_path)})
+            exp_manager(trainer, {"explicit_log_dir": str(tmp_path)})