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This commit is contained in:
Eren G??lge
2022-07-12 14:12:57 +02:00
parent a6f73a18cb
commit 2cf89b88c9
3 changed files with 119 additions and 65 deletions
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tests/tts_tests/test_losses.py
+9 -7
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@@ -1,9 +1,10 @@
import unittest
import torch as T
from torch.nn import functional
from TTS.tts.layers.losses import BCELossMasked, L1LossMasked, MSELossMasked, SSIMLoss
from TTS.tts.utils.helpers import sequence_mask
from TTS.tts.layers.losses import L1LossMasked, SSIMLoss, MSELossMasked, BCELossMasked
class L1LossMaskedTests(unittest.TestCase):
@@ -134,7 +135,6 @@ class MSELossMaskedTests(unittest.TestCase):
assert output.item() == 0, "0 vs {}".format(output.item())
class SSIMLossTests(unittest.TestCase):
def test_in_out(self): # pylint: disable=no-self-use
# test input == target
@@ -150,7 +150,7 @@ class SSIMLossTests(unittest.TestCase):
dummy_input = dummy_input.reshape(4, 57, 128).float()
dummy_target = T.arange(-4 * 57 * 128, 0)
dummy_target = dummy_target.reshape(4, 57, 128).float()
dummy_target = (-dummy_target)
dummy_target = -dummy_target
dummy_length = (T.ones(4) * 58).long()
output = layer(dummy_input, dummy_target, dummy_length)
@@ -210,11 +210,13 @@ class BCELossTest(unittest.TestCase):
length = T.tensor([95])
mask = sequence_mask(length, 100)
pos_weight = T.tensor([5.0])
target = 1. - sequence_mask(length - 1, 100).float() # [0, 0, .... 1, 1] where the first 1 is the last mel frame
target = (
1.0 - sequence_mask(length - 1, 100).float()
) # [0, 0, .... 1, 1] where the first 1 is the last mel frame
true_x = target * 200 - 100 # creates logits of [-100, -100, ... 100, 100] corresponding to target
zero_x = T.zeros(target.shape) - 100. # simulate logits if it never stops decoding
early_x = -200. * sequence_mask(length - 3, 100).float() + 100. # simulate logits on early stopping
late_x = -200. * sequence_mask(length + 1, 100).float() + 100. # simulate logits on late stopping
zero_x = T.zeros(target.shape) - 100.0 # simulate logits if it never stops decoding
early_x = -200.0 * sequence_mask(length - 3, 100).float() + 100.0 # simulate logits on early stopping
late_x = -200.0 * sequence_mask(length + 1, 100).float() + 100.0 # simulate logits on late stopping
loss = layer(true_x, target, length)
self.assertEqual(loss.item(), 0.0)