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reformatting and styling

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This commit is contained in:
Eren Gölge
2021-04-12 11:47:39 +02:00
parent 9011dddf77
commit f519012dea
159 changed files with 6589 additions and 6429 deletions
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tests/test_layers.py
+22 -27
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@@ -1,15 +1,16 @@
import unittest
import torch as T
from TTS.tts.layers.tacotron.tacotron import Prenet, CBHG, Decoder, Encoder
from TTS.tts.layers.losses import L1LossMasked, SSIMLoss
from TTS.tts.layers.tacotron.tacotron import CBHG, Decoder, Encoder, Prenet
from TTS.tts.utils.generic_utils import sequence_mask
# pylint: disable=unused-variable
class PrenetTests(unittest.TestCase):
def test_in_out(self): #pylint: disable=no-self-use
def test_in_out(self): # pylint: disable=no-self-use
layer = Prenet(128, out_features=[256, 128])
dummy_input = T.rand(4, 128)
@@ -21,7 +22,7 @@ class PrenetTests(unittest.TestCase):
class CBHGTests(unittest.TestCase):
def test_in_out(self):
#pylint: disable=attribute-defined-outside-init
# pylint: disable=attribute-defined-outside-init
layer = self.cbhg = CBHG(
128,
K=8,
@@ -29,7 +30,8 @@ class CBHGTests(unittest.TestCase):
conv_projections=[160, 128],
highway_features=80,
gru_features=80,
num_highways=4)
num_highways=4,
)
# B x D x T
dummy_input = T.rand(4, 128, 8)
@@ -52,26 +54,27 @@ class DecoderTests(unittest.TestCase):
attn_norm="sigmoid",
attn_K=5,
attn_type="original",
prenet_type='original',
prenet_type="original",
prenet_dropout=True,
forward_attn=True,
trans_agent=True,
forward_attn_mask=True,
location_attn=True,
separate_stopnet=True)
separate_stopnet=True,
)
dummy_input = T.rand(4, 8, 256)
dummy_memory = T.rand(4, 2, 80)
output, alignment, stop_tokens = layer(
dummy_input, dummy_memory, mask=None)
output, alignment, stop_tokens = layer(dummy_input, dummy_memory, mask=None)
assert output.shape[0] == 4
assert output.shape[1] == 80, "size not {}".format(output.shape[1])
assert output.shape[2] == 2, "size not {}".format(output.shape[2])
assert stop_tokens.shape[0] == 4
class EncoderTests(unittest.TestCase):
def test_in_out(self): #pylint: disable=no-self-use
def test_in_out(self): # pylint: disable=no-self-use
layer = Encoder(128)
dummy_input = T.rand(4, 8, 128)
@@ -84,7 +87,7 @@ class EncoderTests(unittest.TestCase):
class L1LossMaskedTests(unittest.TestCase):
def test_in_out(self): #pylint: disable=no-self-use
def test_in_out(self): # pylint: disable=no-self-use
# test input == target
layer = L1LossMasked(seq_len_norm=False)
dummy_input = T.ones(4, 8, 128).float()
@@ -104,16 +107,14 @@ class L1LossMaskedTests(unittest.TestCase):
dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.zeros(4, 8, 128).float()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 1.0, "1.0 vs {}".format(output.item())
dummy_input = T.rand(4, 8, 128).float()
dummy_target = dummy_input.detach()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 0, "0 vs {}".format(output.item())
@@ -137,22 +138,20 @@ class L1LossMaskedTests(unittest.TestCase):
dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.zeros(4, 8, 128).float()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert abs(output.item() - 1.0) < 1e-5, "1.0 vs {}".format(output.item())
dummy_input = T.rand(4, 8, 128).float()
dummy_target = dummy_input.detach()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 0, "0 vs {}".format(output.item())
class SSIMLossTests(unittest.TestCase):
def test_in_out(self): #pylint: disable=no-self-use
def test_in_out(self): # pylint: disable=no-self-use
# test input == target
layer = SSIMLoss()
dummy_input = T.ones(4, 8, 128).float()
@@ -172,16 +171,14 @@ class SSIMLossTests(unittest.TestCase):
dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.zeros(4, 8, 128).float()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert abs(output.item() - 1.0) < 1e-4, "1.0 vs {}".format(output.item())
dummy_input = T.rand(4, 8, 128).float()
dummy_target = dummy_input.detach()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 0, "0 vs {}".format(output.item())
@@ -205,15 +202,13 @@ class SSIMLossTests(unittest.TestCase):
dummy_input = T.ones(4, 8, 128).float()
dummy_target = T.zeros(4, 8, 128).float()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert abs(output.item() - 1.0) < 1e-5, "1.0 vs {}".format(output.item())
dummy_input = T.rand(4, 8, 128).float()
dummy_target = dummy_input.detach()
dummy_length = (T.arange(5, 9)).long()
mask = (
(sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
mask = ((sequence_mask(dummy_length).float() - 1.0) * 100.0).unsqueeze(2)
output = layer(dummy_input + mask, dummy_target, dummy_length)
assert output.item() == 0, "0 vs {}".format(output.item())