Address even more lint problems

This commit is contained in:
Reuben Morais 2019-07-19 11:48:12 +02:00
parent 057a50a889
commit e3f841742d
5 changed files with 10 additions and 3 deletions

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@ -88,8 +88,8 @@ class Tacotron2(nn.Module):
def _add_speaker_embedding(self, encoder_outputs, speaker_ids):
if hasattr(self, "speaker_embedding") and speaker_ids is None:
raise RuntimeError(" [!] Model has speaker embedding layer but speaker_id is not provided")
elif hasattr(self, "speaker_embedding") and speaker_ids is not None:
raise RuntimeError(" [!] Model has speaker embedding layer but speaker_id is not provided")
if hasattr(self, "speaker_embedding") and speaker_ids is not None:
speaker_embeddings = self.speaker_embedding(speaker_ids)
speaker_embeddings.unsqueeze_(1)

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@ -5,6 +5,7 @@ from layers.tacotron import Prenet, CBHG, Decoder, Encoder
from layers.losses import L1LossMasked
from utils.generic_utils import sequence_mask
#pylint: disable=unused-variable
class PrenetTests(unittest.TestCase):
def test_in_out(self):

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@ -8,6 +8,8 @@ from utils.audio import AudioProcessor
from datasets import TTSDataset
from datasets.preprocess import ljspeech
#pylint: disable=unused-variable
file_path = os.path.dirname(os.path.realpath(__file__))
OUTPATH = os.path.join(file_path, "outputs/loader_tests/")
os.makedirs(OUTPATH, exist_ok=True)

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@ -10,6 +10,8 @@ from utils.generic_utils import load_config
from layers.losses import MSELossMasked
from models.tacotron2 import Tacotron2
#pylint: disable=unused-variable
torch.manual_seed(1)
use_cuda = torch.cuda.is_available()
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

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@ -9,6 +9,8 @@ from utils.generic_utils import load_config
from layers.losses import L1LossMasked
from models.tacotron import Tacotron
#pylint: disable=unused-variable
torch.manual_seed(1)
use_cuda = torch.cuda.is_available()
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
@ -45,7 +47,7 @@ class TacotronTrainTest(unittest.TestCase):
criterion_st = nn.BCEWithLogitsLoss().to(device)
model = Tacotron(
32,
5,
5,
linear_dim=c.audio['num_freq'],
mel_dim=c.audio['num_mels'],
r=c.r,