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Zero-grad more aggressively to save memory

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Clive Chan 2023-01-19 22:10:44 -08:00 committed by GitHub
parent 2c7806db6e
commit 67166079c9
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train.py
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@ -259,7 +259,6 @@ while True:
break break
# forward backward update, with optional gradient accumulation to simulate larger batch size # forward backward update, with optional gradient accumulation to simulate larger batch size
optimizer.zero_grad(set_to_none=True)
for micro_step in range(gradient_accumulation_steps): for micro_step in range(gradient_accumulation_steps):
X, Y = get_batch('train') X, Y = get_batch('train')
if ddp: if ddp:
@ -272,6 +271,7 @@ while True:
logits, loss = model(X, Y) logits, loss = model(X, Y)
loss.backward() loss.backward()
optimizer.step() optimizer.step()
optimizer.zero_grad(set_to_none=True)
# timing and logging # timing and logging
t1 = time.time() t1 = time.time()