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linter fixes

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This commit is contained in:
erogol
2020-09-22 03:54:16 +02:00
parent a6df617eb1
commit 10258724d1
14 changed files with 164 additions and 154 deletions
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tests/test_glow_tts.py
+54 -58
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@@ -4,7 +4,7 @@ import unittest
import torch
from tests import get_tests_input_path
from torch import nn, optim
from torch import optim
from TTS.tts.layers.losses import GlowTTSLoss
from TTS.tts.models.glow_tts import GlowTts
@@ -42,64 +42,60 @@ class GlowTTSTrainTest(unittest.TestCase):
criterion = criterion = GlowTTSLoss()
# model to train
model = GlowTts(
num_chars=32,
hidden_channels=128,
filter_channels=32,
filter_channels_dp=32,
out_channels=80,
kernel_size=3,
num_heads=2,
num_layers_enc=6,
dropout_p=0.1,
num_flow_blocks_dec=12,
kernel_size_dec=5,
dilation_rate=5,
num_block_layers=4,
dropout_p_dec=0.,
num_speakers=0,
c_in_channels=0,
num_splits=4,
num_sqz=1,
sigmoid_scale=False,
rel_attn_window_size=None,
input_length=None,
mean_only=False,
hidden_channels_enc=None,
hidden_channels_dec=None,
use_encoder_prenet=False,
encoder_type="transformer"
).to(device)
model = GlowTts(num_chars=32,
hidden_channels=128,
filter_channels=32,
filter_channels_dp=32,
out_channels=80,
kernel_size=3,
num_heads=2,
num_layers_enc=6,
dropout_p=0.1,
num_flow_blocks_dec=12,
kernel_size_dec=5,
dilation_rate=5,
num_block_layers=4,
dropout_p_dec=0.,
num_speakers=0,
c_in_channels=0,
num_splits=4,
num_sqz=1,
sigmoid_scale=False,
rel_attn_window_size=None,
input_length=None,
mean_only=False,
hidden_channels_enc=None,
hidden_channels_dec=None,
use_encoder_prenet=False,
encoder_type="transformer").to(device)
# reference model to compare model weights
model_ref = GlowTts(
num_chars=32,
hidden_channels=128,
filter_channels=32,
filter_channels_dp=32,
out_channels=80,
kernel_size=3,
num_heads=2,
num_layers_enc=6,
dropout_p=0.1,
num_flow_blocks_dec=12,
kernel_size_dec=5,
dilation_rate=5,
num_block_layers=4,
dropout_p_dec=0.,
num_speakers=0,
c_in_channels=0,
num_splits=4,
num_sqz=1,
sigmoid_scale=False,
rel_attn_window_size=None,
input_length=None,
mean_only=False,
hidden_channels_enc=None,
hidden_channels_dec=None,
use_encoder_prenet=False,
encoder_type="transformer"
).to(device)
model_ref = GlowTts(num_chars=32,
hidden_channels=128,
filter_channels=32,
filter_channels_dp=32,
out_channels=80,
kernel_size=3,
num_heads=2,
num_layers_enc=6,
dropout_p=0.1,
num_flow_blocks_dec=12,
kernel_size_dec=5,
dilation_rate=5,
num_block_layers=4,
dropout_p_dec=0.,
num_speakers=0,
c_in_channels=0,
num_splits=4,
num_sqz=1,
sigmoid_scale=False,
rel_attn_window_size=None,
input_length=None,
mean_only=False,
hidden_channels_enc=None,
hidden_channels_dec=None,
use_encoder_prenet=False,
encoder_type="transformer").to(device)
model.train()
print(" > Num parameters for GlowTTS model:%s" %
@@ -120,7 +116,7 @@ class GlowTTSTrainTest(unittest.TestCase):
input_dummy, input_lengths, mel_spec, mel_lengths, None)
optimizer.zero_grad()
loss_dict = criterion(z, y_mean, y_log_scale, logdet, mel_lengths,
o_dur_log, o_total_dur, input_lengths)
o_dur_log, o_total_dur, input_lengths)
loss = loss_dict['loss']
loss.backward()
optimizer.step()