format code

deepspeech/exps/deepspeech2/model.py

@@ -189,7 +189,6 @@ class DeepSpeech2Trainer(Trainer):
         self.lr_scheduler = lr_scheduler
         logger.info("Setup optimizer/lr_scheduler!")
 
-
     def setup_dataloader(self):
         config = self.config.clone()
         config.defrost()

parakeet/data/batch.py

@@ -53,8 +53,8 @@ def batch_text_id(minibatch, pad_id=0, dtype=np.int64):
     peek_example = minibatch[0]
     assert len(peek_example.shape) == 1, "text example is an 1D tensor"
 
-    lengths = [example.shape[0] for example in minibatch
+    lengths = [example.shape[0] for example in
-               ]  # assume (channel, n_samples) or (n_samples, )
+               minibatch]  # assume (channel, n_samples) or (n_samples, )
     max_len = np.max(lengths)
 
     batch = []

parakeet/exps/tacotron2/ljspeech.py

@@ -67,19 +67,16 @@ class LJSpeechCollector(object):
 
         # Sort by text_len in descending order
         texts = [
-            i
+            i for i, _ in sorted(
-            for i, _ in sorted(
                 zip(texts, text_lens), key=lambda x: x[1], reverse=True)
         ]
         mels = [
-            i
+            i for i, _ in sorted(
-            for i, _ in sorted(
                 zip(mels, text_lens), key=lambda x: x[1], reverse=True)
         ]
 
         mel_lens = [
-            i
+            i for i, _ in sorted(
-            for i, _ in sorted(
                 zip(mel_lens, text_lens), key=lambda x: x[1], reverse=True)
         ]