Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

remove repeated ops #3

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
+17 −31
Open

remove repeated ops #3

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
20 changes: 3 additions & 17 deletions avocodo/lightning_module.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,6 @@
from avocodo.models.losses import feature_loss
from avocodo.models.losses import generator_loss
from avocodo.models.losses import discriminator_loss
from avocodo.pqmf import PQMF


class Avocodo(LightningModule):
Expand All @@ -22,11 +21,8 @@ def __init__(
super().__init__()
self.save_hyperparameters(h)

self.pqmf_lv2 = PQMF(*self.hparams.pqmf_config["lv2"])
self.pqmf_lv1 = PQMF(*self.hparams.pqmf_config["lv1"])

self.generator = Generator(self.hparams.generator)
self.combd = CoMBD(self.hparams.combd, [self.pqmf_lv2, self.pqmf_lv1])
self.combd = CoMBD(self.hparams.combd)
self.sbd = SBD(self.hparams.sbd)

def configure_optimizers(self):
Expand All @@ -43,22 +39,12 @@ def forward(self, z):
def training_step(self, batch, batch_idx, optimizer_idx):
x, y, _, y_mel = batch
y = y.unsqueeze(1)
ys = [
self.pqmf_lv2.analysis(
y
)[:, :self.hparams.generator.projection_filters[1]],
self.pqmf_lv1.analysis(
y
)[:, :self.hparams.generator.projection_filters[2]],
y
]

y_g_hats = self.generator(x)

# train generator
if optimizer_idx == 0:
y_du_hat_r, y_du_hat_g, fmap_u_r, fmap_u_g = self.combd(
ys, y_g_hats)
y, y_g_hats)
loss_fm_u, losses_fm_u = feature_loss(fmap_u_r, fmap_u_g)
loss_gen_u, losses_gen_u = generator_loss(y_du_hat_g)

Expand Down Expand Up @@ -91,7 +77,7 @@ def training_step(self, batch, batch_idx, optimizer_idx):
detached_y_g_hats = [x.detach() for x in y_g_hats]

y_du_hat_r, y_du_hat_g, _, _ = self.combd(
ys, detached_y_g_hats)
y, detached_y_g_hats)
loss_disc_u, losses_disc_u_r, losses_disc_u_g = discriminator_loss(
y_du_hat_r, y_du_hat_g)

Expand Down
28 changes: 14 additions & 14 deletions avocodo/models/CoMBD.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -65,16 +65,16 @@ def forward(self, x):


class CoMBD(torch.nn.Module):
def __init__(self, h, pqmf_list=None, use_spectral_norm=False):
def __init__(self, h, pqmf_list: List=None, use_spectral_norm=False):
super(CoMBD, self).__init__()
self.h = h
if pqmf_list is not None:
self.pqmf = pqmf_list
self.pqmf = nn.ModuleList(pqmf_list)
else:
self.pqmf = [
self.pqmf = nn.ModuleList([
PQMF(*h.pqmf_config["lv2"]),
PQMF(*h.pqmf_config["lv1"])
]
])

self.blocks = nn.ModuleList()
for _h_u, _d_k, _d_s, _d_d, _d_g, _d_p, _op_f, _op_k, _op_g in zip(
Expand Down Expand Up @@ -107,27 +107,27 @@ def _block_forward(self, input, blocks, outs, f_maps):
f_maps.append(f_map)
return outs, f_maps

def _pqmf_forward(self, ys, ys_hat):
def _pqmf_forward(self, y, ys_hat):
# preprocess for multi_scale forward
multi_scale_inputs = []
ys = []
multi_scale_inputs_hat = []
for pqmf in self.pqmf:
multi_scale_inputs.append(
pqmf.to(ys[-1]).analysis(ys[-1])[:, :1, :]
ys.append(
pqmf.analysis(y)[:, :1, :]
)
multi_scale_inputs_hat.append(
pqmf.to(ys[-1]).analysis(ys_hat[-1])[:, :1, :]
pqmf.analysis(ys_hat[-1])[:, :1, :]
)

ys.append(y)
outs_real = []
f_maps_real = []
# real
# for hierarchical forward
outs_real, f_maps_real = self._block_forward(
ys, self.blocks, outs_real, f_maps_real)
# for multi_scale forward
outs_real, f_maps_real = self._block_forward(
multi_scale_inputs, self.blocks[:-1], outs_real, f_maps_real)
outs_real.extend(outs_real[:-1])
f_maps_real.extend(f_maps_real[:-1])

outs_fake = []
f_maps_fake = []
Expand All @@ -141,7 +141,7 @@ def _pqmf_forward(self, ys, ys_hat):

return outs_real, outs_fake, f_maps_real, f_maps_fake

def forward(self, ys, ys_hat):
def forward(self, y, ys_hat):
outs_real, outs_fake, f_maps_real, f_maps_fake = self._pqmf_forward(
ys, ys_hat)
y, ys_hat)
return outs_real, outs_fake, f_maps_real, f_maps_fake