fix ptl_bugs in slu_models.py

examples/slu/speech_intent_slot/configs/conformer_transformer_large_bpe.yaml

@@ -174,7 +174,7 @@ trainer:
   max_steps: -1 # computed at runtime if not set
   val_check_interval: 1.0 # Set to 0.25 to check 4 times per epoch, or an int for number of iterations
   accelerator: auto
-  strategy: ddp
+  strategy: ddp_find_unused_parameters_true
   accumulate_grad_batches: 1
   gradient_clip_val: 0.0
   precision: 32 # Should be set to 16 for O1 and O2 to enable the AMP.

nemo/collections/asr/models/slu_models.py

@@ -285,7 +285,7 @@ def predict(
         predictions = self.sequence_generator.decode_semantics_from_tokens(pred_tokens)
         return predictions
 
-    def validation_step(self, batch, batch_idx, dataloader_idx=0):
+    def validation_pass(self, batch, batch_idx, dataloader_idx=0):
         if len(batch) == 4:
             signal, signal_len, semantics, semantics_len = batch
         else:
@@ -327,19 +327,29 @@ def validation_step(self, batch, batch_idx, dataloader_idx=0):
             'val_wer': wer,
         }
 
+    def validation_step(self, batch, batch_idx, dataloader_idx=0):
+        metrics = self.validation_pass(batch, batch_idx, dataloader_idx)
+        if type(self.trainer.val_dataloaders) == list and len(self.trainer.val_dataloaders) > 1:
+            self.validation_step_outputs[dataloader_idx].append(metrics)
+        else:
+            self.validation_step_outputs.append(metrics)
+        return metrics
+
     def test_step(self, batch, batch_idx, dataloader_idx=0):
-        logs = self.validation_step(batch, batch_idx, dataloader_idx=dataloader_idx)
-        test_logs = {
-            'test_loss': logs['val_loss'],
-            'test_wer_num': logs['val_wer_num'],
-            'test_wer_denom': logs['val_wer_denom'],
-            'test_wer': logs['val_wer'],
-        }
+        logs = self.validation_pass(batch, batch_idx, dataloader_idx=dataloader_idx)
+        test_logs = {name.replace("val_", "test_"): value for name, value in logs.items()}
+        if type(self.trainer.test_dataloaders) == list and len(self.trainer.test_dataloaders) > 1:
+            self.test_step_outputs[dataloader_idx].append(test_logs)
+        else:
+            self.test_step_outputs.append(test_logs)
         return test_logs
 
     def test_dataloader(self):
-        if self._test_dl is not None:
-            return self._test_dl
+        if self._test_dl is None:
+            # None dataloader no longer supported in PTL2.0
+            self._test_dl = []
+
+        return self._test_dl
 
     def _setup_dataloader_from_config(self, config: Optional[Dict]):
         if 'augmentor' in config: