filter test, since librispeech will cause OOM, but all test wer will be worse, since mismatch train with test

deepspeech/exps/deepspeech2/model.py

@@ -323,12 +323,12 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
         config.data.manifest = config.data.test_manifest
         config.data.keep_transcription_text = True
         config.data.augmentation_config = ""
-        config.data.min_input_len = 0.0  # second
+        # config.data.min_input_len = 0.0  # second
-        config.data.max_input_len = float('inf')  # second
+        # config.data.max_input_len = float('inf')  # second
-        config.data.min_output_len = 0.0  # tokens
+        # config.data.min_output_len = 0.0  # tokens
-        config.data.max_output_len = float('inf')  # tokens
+        # config.data.max_output_len = float('inf')  # tokens
-        config.data.min_output_input_ratio = 0.00
+        # config.data.min_output_input_ratio = 0.00
-        config.data.max_output_input_ratio = float('inf')
+        # config.data.max_output_input_ratio = float('inf')
         test_dataset = ManifestDataset.from_config(config)
 
         # return text ord id

deepspeech/exps/u2/model.py

@@ -254,12 +254,12 @@ class U2Trainer(Trainer):
         config.data.manifest = config.data.test_manifest
         config.data.keep_transcription_text = True
         config.data.augmentation_config = ""
-        config.data.min_input_len = 0.0  # second
+        # config.data.min_input_len = 0.0  # second
-        config.data.max_input_len = float('inf')  # second
+        # config.data.max_input_len = float('inf')  # second
-        config.data.min_output_len = 0.0  # tokens
+        # config.data.min_output_len = 0.0  # tokens
-        config.data.max_output_len = float('inf')  # tokens
+        # config.data.max_output_len = float('inf')  # tokens
-        config.data.min_output_input_ratio = 0.00
+        # config.data.min_output_input_ratio = 0.00
-        config.data.max_output_input_ratio = float('inf')
+        # config.data.max_output_input_ratio = float('inf')
         test_dataset = ManifestDataset.from_config(config)
         # return text ord id
         self.test_loader = DataLoader(

deepspeech/training/trainer.py

@@ -264,6 +264,7 @@ class Trainer():
 
     @mp_tools.rank_zero_only
     def destory(self):
+        """Close visualizer to avoid hanging after training"""
         # https://github.com/pytorch/fairseq/issues/2357
         if self.visualizer:
             self.visualizer.close()