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-rw-r--r--models/model.py18
1 files changed, 13 insertions, 5 deletions
diff --git a/models/model.py b/models/model.py
index 75e478e..75f243c 100644
--- a/models/model.py
+++ b/models/model.py
@@ -151,12 +151,13 @@ class Model:
self.rgb_pn = RGBPartNet(self.in_channels, self.in_size, **model_hp,
image_log_on=self.image_log_on)
# Try to accelerate computation using CUDA or others
+ self.rgb_pn = nn.DataParallel(self.rgb_pn)
self.rgb_pn = self.rgb_pn.to(self.device)
self.optimizer = optim.Adam([
- {'params': self.rgb_pn.ae.parameters(), **ae_optim_hp},
- {'params': self.rgb_pn.pn.parameters(), **pn_optim_hp},
- {'params': self.rgb_pn.hpm.parameters(), **hpm_optim_hp},
- {'params': self.rgb_pn.fc_mat, **fc_optim_hp}
+ {'params': self.rgb_pn.module.ae.parameters(), **ae_optim_hp},
+ {'params': self.rgb_pn.module.pn.parameters(), **pn_optim_hp},
+ {'params': self.rgb_pn.module.hpm.parameters(), **hpm_optim_hp},
+ {'params': self.rgb_pn.module.fc_mat, **fc_optim_hp}
], **optim_hp)
sched_gamma = sched_hp.get('gamma', 0.9)
sched_step_size = sched_hp.get('step_size', 500)
@@ -195,8 +196,14 @@ class Model:
x_c2 = batch_c2['clip'].to(self.device)
y = batch_c1['label'].to(self.device)
# Duplicate labels for each part
- y = y.unsqueeze(1).repeat(1, self.rgb_pn.num_total_parts)
+ y = y.unsqueeze(1).repeat(1, self.rgb_pn.module.num_total_parts)
losses, images = self.rgb_pn(x_c1, x_c2, y)
+ losses = torch.stack((
+ # xrecon cano_cons pose_sim
+ losses[0].sum(), losses[1].mean(), losses[2].mean(),
+ # hpm_ba_trip pn_ba_trip
+ losses[3].mean(), losses[4].mean()
+ ))
loss = losses.sum()
loss.backward()
self.optimizer.step()
@@ -302,6 +309,7 @@ class Model:
model_hp = self.hp.get('model', {})
self.rgb_pn = RGBPartNet(self.in_channels, self.in_size, **model_hp)
# Try to accelerate computation using CUDA or others
+ self.rgb_pn = nn.DataParallel(self.rgb_pn)
self.rgb_pn = self.rgb_pn.to(self.device)
self.rgb_pn.eval()