refix linter

TTS/trainer.py

@@ -22,7 +22,6 @@ from torch.utils.data import DataLoader
 from TTS.config import load_config, register_config
 from TTS.tts.datasets import load_meta_data
 from TTS.tts.models import setup_model as setup_tts_model
-from TTS.vocoder.models.wavegrad import Wavegrad
 from TTS.tts.utils.text.symbols import parse_symbols
 from TTS.utils.audio import AudioProcessor
 from TTS.utils.callbacks import TrainerCallback
@@ -41,6 +40,7 @@ from TTS.utils.logging import ConsoleLogger, TensorboardLogger
 from TTS.utils.trainer_utils import get_optimizer, get_scheduler, is_apex_available, setup_torch_training_env
 from TTS.vocoder.datasets.preprocess import load_wav_data, load_wav_feat_data
 from TTS.vocoder.models import setup_model as setup_vocoder_model
+from TTS.vocoder.models.wavegrad import Wavegrad
 
 if platform.system() != "Windows":
     # https://github.com/pytorch/pytorch/issues/973
@@ -766,14 +766,15 @@ class Trainer:
         Model must return figures and audios to be logged by the Tensorboard."""
         if hasattr(self.model, "test_run"):
             if isinstance(self.model, Wavegrad):
-                return None # TODO: Fix inference on WaveGrad
-            elif hasattr(self.eval_loader.dataset, "load_test_samples"):
+                return None  # TODO: Fix inference on WaveGrad
+            if hasattr(self.eval_loader.dataset, "load_test_samples"):
                 samples = self.eval_loader.dataset.load_test_samples(1)
                 figures, audios = self.model.test_run(self.ap, samples, None, self.use_cuda)
             else:
                 figures, audios = self.model.test_run(self.ap, self.use_cuda)
             self.tb_logger.tb_test_audios(self.total_steps_done, audios, self.config.audio["sample_rate"])
             self.tb_logger.tb_test_figures(self.total_steps_done, figures)
+        return None
 
     def _fit(self) -> None:
         """🏃 train -> evaluate -> test for the number of epochs."""

TTS/tts/models/glow_tts.py

@@ -113,7 +113,7 @@ class GlowTTS(BaseTTS):
 
     @staticmethod
     def compute_outputs(attn, o_mean, o_log_scale, x_mask):
-        """ Compute and format the mode outputs with the given alignment map"""
+        """Compute and format the mode outputs with the given alignment map"""
         y_mean = torch.matmul(attn.squeeze(1).transpose(1, 2), o_mean.transpose(1, 2)).transpose(
             1, 2
         )  # [b, t', t], [b, t, d] -> [b, d, t']

TTS/vocoder/models/__init__.py

@@ -31,7 +31,7 @@ def setup_model(config: Coqpit):
 
 
 def setup_generator(c):
-    """ TODO: use config object as arguments"""
+    """TODO: use config object as arguments"""
     print(" > Generator Model: {}".format(c.generator_model))
     MyModel = importlib.import_module("TTS.vocoder.models." + c.generator_model.lower())
     MyModel = getattr(MyModel, to_camel(c.generator_model))
@@ -94,7 +94,7 @@ def setup_generator(c):
 
 
 def setup_discriminator(c):
-    """ TODO: use config objekt as arguments"""
+    """TODO: use config objekt as arguments"""
     print(" > Discriminator Model: {}".format(c.discriminator_model))
     if "parallel_wavegan" in c.discriminator_model:
         MyModel = importlib.import_module("TTS.vocoder.models.parallel_wavegan_discriminator")

TTS/vocoder/models/wavegrad.py

@@ -261,7 +261,9 @@ class Wavegrad(BaseModel):
     def eval_log(self, ap: AudioProcessor, batch: Dict, outputs: Dict) -> Tuple[Dict, np.ndarray]:
         return None, None
 
-    def test_run(self, ap: AudioProcessor, samples: List[Dict], ouputs: Dict, use_cuda):  # pylint: disable=unused-argument
+    def test_run(
+        self, ap: AudioProcessor, samples: List[Dict], ouputs: Dict, use_cuda
+    ):  # pylint: disable=unused-argument
         # setup noise schedule and inference
         noise_schedule = self.config["test_noise_schedule"]
         betas = np.linspace(noise_schedule["min_val"], noise_schedule["max_val"], noise_schedule["num_steps"])

TTS/vocoder/models/wavernn.py

@@ -571,7 +571,7 @@ class Wavernn(BaseVocoder):
 
     @torch.no_grad()
     def test_run(
-        self, ap: AudioProcessor, samples: List[Dict], output: Dict, use_cuda # pylint: disable=unused-argument
+        self, ap: AudioProcessor, samples: List[Dict], output: Dict, use_cuda  # pylint: disable=unused-argument
     ) -> Tuple[Dict, Dict]:
         figures = {}
         audios = {}

tests/test_speaker_encoder_train.py

@@ -6,6 +6,7 @@ from tests import get_device_id, get_tests_output_path, run_cli
 from TTS.config.shared_configs import BaseAudioConfig
 from TTS.speaker_encoder.speaker_encoder_config import SpeakerEncoderConfig
 
+
 def run_test_train():
     command = (
         f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_encoder.py --config_path {config_path} "
@@ -17,6 +18,7 @@ def run_test_train():
     )
     run_cli(command)
 
+
 config_path = os.path.join(get_tests_output_path(), "test_speaker_encoder_config.json")
 output_path = os.path.join(get_tests_output_path(), "train_outputs")