filter test, since librispeech will cause OOM, but all test wer will be worse,...

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.max_input_len = float('inf')  # second
-        config.data.min_output_len = 0.0  # tokens
-        config.data.max_output_len = float('inf')  # tokens
-        config.data.min_output_input_ratio = 0.00
-        config.data.max_output_input_ratio = float('inf')
+        # config.data.min_input_len = 0.0  # second
+        # config.data.max_input_len = float('inf')  # second
+        # config.data.min_output_len = 0.0  # tokens
+        # config.data.max_output_len = float('inf')  # tokens
+        # config.data.min_output_input_ratio = 0.00
+        # 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.max_input_len = float('inf')  # second
-        config.data.min_output_len = 0.0  # tokens
-        config.data.max_output_len = float('inf')  # tokens
-        config.data.min_output_input_ratio = 0.00
-        config.data.max_output_input_ratio = float('inf')
+        # config.data.min_input_len = 0.0  # second
+        # config.data.max_input_len = float('inf')  # second
+        # config.data.min_output_len = 0.0  # tokens
+        # config.data.max_output_len = float('inf')  # tokens
+        # config.data.min_output_input_ratio = 0.00
+        # 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()