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-rw-r--r--models/model.py13
1 files changed, 8 insertions, 5 deletions
diff --git a/models/model.py b/models/model.py
index 497a0ea..2eeaf5e 100644
--- a/models/model.py
+++ b/models/model.py
@@ -175,13 +175,15 @@ class Model:
num_pos_pairs = (self.k*(self.k-1)//2) * self.pr
# 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.triplet_loss = nn.DataParallel(self.triplet_loss)
self.triplet_loss = self.triplet_loss.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_final_gamma = sched_hp.get('final_gamma', 0.001)
sched_start_step = sched_hp.get('start_step', 15_000)
@@ -227,7 +229,7 @@ class Model:
y = y.repeat(self.rgb_pn.num_total_parts, 1)
trip_loss, dist, num_non_zero = self.triplet_loss(embedding, y)
losses = torch.cat((
- ae_losses,
+ ae_losses.mean(0),
torch.stack((
trip_loss[:self.rgb_pn.hpm_num_parts].mean(),
trip_loss[self.rgb_pn.hpm_num_parts:].mean()
@@ -389,6 +391,7 @@ class Model:
model_hp.pop('triplet_margins', None)
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()