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remove unneeded iter()

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Eric Silberstein
2025-11-20 15:14:56 -05:00
parent 4a87a0d19f
commit f37d45c21f
1 changed files with 3 additions and 4 deletions
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7
scripts/chat_sft.py
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@@ -167,17 +167,16 @@ def get_lr_multiplier(it):
# Go! # Go!
step = 0 step = 0
train_iter = iter(train_loader)
for step in range(num_iterations): for step in range(num_iterations):
last_step = step == num_iterations - 1 last_step = step == num_iterations - 1
# evaluate the validation loss # evaluate the validation loss
if last_step or step % eval_every == 0: if last_step or step % eval_every == 0:
model.eval() model.eval()
val_iter = iter(build_val_loader()) val_loader = build_val_loader()
losses = [] losses = []
for _ in range(eval_steps): for _ in range(eval_steps):
val_inputs, val_targets = next(val_iter) val_inputs, val_targets = next(val_loader)
with torch.no_grad(), autocast_ctx: with torch.no_grad(), autocast_ctx:
loss = model(val_inputs, val_targets) loss = model(val_inputs, val_targets)
losses.append(loss) losses.append(loss)
@@ -214,7 +213,7 @@ for step in range(num_iterations):
# evaluate the gradient # evaluate the gradient
num_tokens = torch.tensor(0, device=device) # the number of "active" tokens of supervision seen num_tokens = torch.tensor(0, device=device) # the number of "active" tokens of supervision seen
for micro_step in range(grad_accum_steps): for micro_step in range(grad_accum_steps):
train_inputs, train_targets = next(train_iter) train_inputs, train_targets = next(train_loader)
with autocast_ctx: with autocast_ctx:
loss = model(train_inputs, train_targets) loss = model(train_inputs, train_targets)
train_loss = loss.detach() # for logging train_loss = loss.detach() # for logging