Fix glow_tts imports

agrinh · Sep 10, 2021 · a89eb12 · a89eb12
1 parent 570d597
commit a89eb12
Showing 1 changed file with 14 additions and 7 deletions.
diff --git a/TTS/tts/models/glow_tts.py b/TTS/tts/models/glow_tts.py
@@ -7,9 +7,8 @@
 from TTS.tts.configs import GlowTTSConfig
 from TTS.tts.layers.glow_tts.decoder import Decoder
 from TTS.tts.layers.glow_tts.encoder import Encoder
-from TTS.tts.utils.helpers import generate_path, maximum_path
 from TTS.tts.models.base_tts import BaseTTS
-from TTS.tts.utils.helpers import sequence_mask
+from TTS.tts.utils.helpers import generate_path, maximum_path, sequence_mask
 from TTS.tts.utils.speakers import get_speaker_manager
 from TTS.tts.utils.synthesis import synthesis
 from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
@@ -133,7 +132,7 @@ def compute_outputs(attn, o_mean, o_log_scale, x_mask):
         return y_mean, y_log_scale, o_attn_dur
 
     def forward(
-        self, x, x_lengths, y, y_lengths=None, aux_input={"d_vectors": None, 'speaker_ids':None}
+        self, x, x_lengths, y, y_lengths=None, aux_input={"d_vectors": None, "speaker_ids": None}
     ):  # pylint: disable=dangerous-default-value
         """
         Shapes:
@@ -185,7 +184,7 @@ def forward(
 
     @torch.no_grad()
     def inference_with_MAS(
-        self, x, x_lengths, y=None, y_lengths=None, aux_input={"d_vectors": None, 'speaker_ids':None}
+        self, x, x_lengths, y=None, y_lengths=None, aux_input={"d_vectors": None, "speaker_ids": None}
     ):  # pylint: disable=dangerous-default-value
         """
         It's similar to the teacher forcing in Tacotron.
@@ -246,7 +245,7 @@ def inference_with_MAS(
 
     @torch.no_grad()
     def decoder_inference(
-        self, y, y_lengths=None, aux_input={"d_vectors": None, 'speaker_ids':None}
+        self, y, y_lengths=None, aux_input={"d_vectors": None, "speaker_ids": None}
     ):  # pylint: disable=dangerous-default-value
         """
         Shapes:
@@ -278,7 +277,9 @@ def decoder_inference(
         return outputs
 
     @torch.no_grad()
-    def inference(self, x, aux_input={"x_lengths": None, "d_vectors": None, "speaker_ids":None}):  # pylint: disable=dangerous-default-value
+    def inference(
+        self, x, aux_input={"x_lengths": None, "d_vectors": None, "speaker_ids": None}
+    ):  # pylint: disable=dangerous-default-value
         x_lengths = aux_input["x_lengths"]
         g = aux_input["d_vectors"] if aux_input is not None and "d_vectors" in aux_input else None
 
@@ -331,7 +332,13 @@ def train_step(self, batch: dict, criterion: nn.Module):
         d_vectors = batch["d_vectors"]
         speaker_ids = batch["speaker_ids"]
 
-        outputs = self.forward(text_input, text_lengths, mel_input, mel_lengths, aux_input={"d_vectors": d_vectors, "speaker_ids":speaker_ids})
+        outputs = self.forward(
+            text_input,
+            text_lengths,
+            mel_input,
+            mel_lengths,
+            aux_input={"d_vectors": d_vectors, "speaker_ids": speaker_ids},
+        )
 
         loss_dict = criterion(
             outputs["model_outputs"],