Optimize batching

1 files changed, 8 insertions, 10 deletions

diff --git a/simclr/main.py b/simclr/main.py
index 93a2d83..b170355 100644
--- a/simclr/main.py
+++ b/simclr/main.py
@@ -294,12 +294,11 @@ class SimCLRTrainer(Trainer):
         train_loader = iter(self.train_loader)
         model.train()
         for iter_ in range(self.restore_iter, num_iters):
-            (input1, input2), _ = next(train_loader)
-            input1, input2 = input1.to(device), input2.to(device)
+            input_, _ = next(train_loader)
+            input_ = torch.cat(input_).to(device)
             model.zero_grad()
-            output1 = model(input1)
-            output2 = model(input2)
-            train_loss, train_accuracy = loss_fn(output1, output2)
+            output = model(input_)
+            train_loss, train_accuracy = loss_fn(output)
             train_loss.backward()
             optim.step()
             self.log(logger, self.BatchLogRecord(
@@ -327,11 +326,10 @@ class SimCLRTrainer(Trainer):
         model = self.models['model']
         model.eval()
         with torch.no_grad():
-            for (input1, input2), _ in self.test_loader:
-                input1, input2 = input1.to(device), input2.to(device)
-                output1 = model(input1)
-                output2 = model(input2)
-                loss, accuracy = loss_fn(output1, output2)
+            for input_, _ in self.test_loader:
+                input_ = torch.cat(input_).to(device)
+                output = model(input_)
+                loss, accuracy = loss_fn(output)
                 yield loss.item(), accuracy.item()