mirror of
https://github.com/zenlm/enso.git
synced 2026-07-26 22:30:28 +00:00
debug
This commit is contained in:
+7
-7
@@ -214,22 +214,22 @@ def main(args):
|
||||
|
||||
model_engine.backward(loss)
|
||||
|
||||
if (data_iter_step + 1) % args.accum_iter == 0:
|
||||
if (data_iter_step + 1) % args.accum_iter == 0:
|
||||
model_engine.step()
|
||||
log_steps += 1
|
||||
train_steps += 1
|
||||
|
||||
log_steps += 1
|
||||
train_steps += 1
|
||||
data_iter_step += 1
|
||||
# Log loss values:
|
||||
running_loss += loss.item()
|
||||
|
||||
if train_steps % args.log_every == 0 and train_steps > 0:
|
||||
if train_steps % args.log_every == 0:
|
||||
# Measure training speed:
|
||||
torch.cuda.synchronize()
|
||||
end_time = time()
|
||||
steps_per_sec = log_steps / (end_time - start_time)
|
||||
# Reduce loss history over all processes:
|
||||
avg_loss = torch.tensor(running_loss / data_iter_step, device=device)
|
||||
avg_loss = torch.tensor(running_loss / log_steps, device=device)
|
||||
dist.all_reduce(avg_loss, op=dist.ReduceOp.SUM)
|
||||
avg_loss = avg_loss.item() / dist.get_world_size()
|
||||
logger.info(f"(step={train_steps:07d}) Train Loss: {avg_loss:.4f}, Train Steps/Sec: {steps_per_sec:.2f}")
|
||||
@@ -239,7 +239,7 @@ def main(args):
|
||||
start_time = time()
|
||||
|
||||
# Save DiT checkpoint:
|
||||
if train_steps % args.ckpt_every == 0 and train_steps > 0:
|
||||
if train_steps % args.ckpt_every == 0 and train_steps > 0:
|
||||
try:
|
||||
checkpoint_path = f"{checkpoint_dir}/{train_steps:07d}"
|
||||
model_engine.save_checkpoint(checkpoint_path)
|
||||
@@ -267,7 +267,7 @@ if __name__ == "__main__":
|
||||
parser.add_argument("--global-seed", type=int, default=2023)
|
||||
parser.add_argument("--num-workers", type=int, default=4)
|
||||
parser.add_argument("--log-every", type=int, default=100)
|
||||
parser.add_argument('--accum_iter', default=8, type=int,)
|
||||
parser.add_argument('--accum_iter', default=4, type=int,)
|
||||
parser.add_argument('--num_experts', default=8, type=int,)
|
||||
parser.add_argument('--num_experts_per_tok', default=2, type=int,)
|
||||
parser.add_argument("--ckpt-every", type=int, default=10_000)
|
||||
|
||||
Reference in New Issue
Block a user