diff options
| -rw-r--r-- | models/model.py | 11 |
1 files changed, 2 insertions, 9 deletions
diff --git a/models/model.py b/models/model.py index c0adc41..da3eac3 100644 --- a/models/model.py +++ b/models/model.py @@ -137,7 +137,7 @@ class Model: sched_hp = self.hp.get('scheduler', {}) self.rgb_pn = RGBPartNet(self.train_size, self.in_channels, **model_hp) # Try to accelerate computation using CUDA or others - self.rgb_pn = self._accelerate(self.rgb_pn) + self.rgb_pn = self.rgb_pn.to(self.device) self.optimizer = optim.Adam(self.rgb_pn.parameters(), **optim_hp) self.scheduler = optim.lr_scheduler.StepLR(self.optimizer, **sched_hp) self.writer = SummaryWriter(self._log_name) @@ -196,13 +196,6 @@ class Model: self.writer.close() break - def _accelerate(self, model: nn.Module) -> nn.Module: - if not self.disable_acc: - if torch.cuda.device_count() > 1: - model = nn.DataParallel(model) - model = model.to(self.device) - return model - def predict_all( self, iter_: int, @@ -225,7 +218,7 @@ class Model: model_hp = self.hp.get('model', {}) self.rgb_pn = RGBPartNet(ae_in_channels=self.in_channels, **model_hp) # Try to accelerate computation using CUDA or others - self.rgb_pn = self._accelerate(self.rgb_pn) + self.rgb_pn = self.rgb_pn.to(self.device) self.rgb_pn.eval() gallery_samples, probe_samples = [], {} |