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FIX: Update optimization_tutorial.py to expose batch_size in train_loop() #2920

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FIX: Update optimization_tutorial.py to expose batch_size in train_loop() #2920

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3855184
Update optimization_tutorial.py
loganthomas Jun 10, 2024
9f6ba07
Merge branch 'main' into fix-batch-size-optimization-tutorial
loganthomas Jun 12, 2024
af41b88
Merge branch 'main' into fix-batch-size-optimization-tutorial
loganthomas Jun 15, 2024
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4 changes: 2 additions & 2 deletions beginner_source/basics/optimization_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -147,7 +147,7 @@ def forward(self, x):
# We define ``train_loop`` that loops over our optimization code, and ``test_loop`` that
# evaluates the model's performance against our test data.

def train_loop(dataloader, model, loss_fn, optimizer):
def train_loop(dataloader, model, batch_size, loss_fn, optimizer):
size = len(dataloader.dataset)
# Set the model to training mode - important for batch normalization and dropout layers
# Unnecessary in this situation but added for best practices
Expand Down Expand Up @@ -198,7 +198,7 @@ def test_loop(dataloader, model, loss_fn):
epochs = 10
for t in range(epochs):
print(f"Epoch {t+1}\n-------------------------------")
train_loop(train_dataloader, model, loss_fn, optimizer)
train_loop(train_dataloader, model, batch_size, loss_fn, optimizer)
test_loop(test_dataloader, model, loss_fn)
print("Done!")

Expand Down