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readability changes to f-string, remove extra .item()
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parent
3c43ef370c
commit
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@ -274,7 +274,7 @@ for step in range(num_iterations + 1):
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# gradient clipping (TODO possibly experiment with)
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if grad_clip > 0.0:
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grad_norm = torch.nn.utils.clip_grad_norm_(orig_model.parameters(), grad_clip)
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grad_norm = grad_norm.item()
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grad_norm = grad_norm.item() # takes cpu and gpu sync, call it once and use everywhere
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# step the optimizers
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lrm = get_lr_multiplier(step)
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for opt in optimizers:
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@ -301,14 +301,10 @@ for step in range(num_iterations + 1):
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mfu = 100 * flops_per_sec / promised_flops_per_sec_h100 # in %
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if step > 10:
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total_training_time += dt # only count the time after the first 10 steps
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print0(
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f"step {step:05d}/{num_iterations:05d} ({pct_done:.2f}%) | "
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f"loss: {debiased_smooth_loss:.6f} | "
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+ (f"grad_norm: {grad_norm.item():.5f} | " if grad_clip > 0.0 else "")
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+ f"lrm: {lrm:.2f} | dt: {dt * 1000:.2f}ms | "
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f"tok/sec: {tok_per_sec:,} | mfu: {mfu:.2f} | "
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f"total time: {total_training_time/60:.2f}m"
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)
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print_grad_norm = ""
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if grad_clip > 0.0:
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print_grad_norm = f" grad_norm: {grad_norm:.5f} |"
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print0(f"step {step:05d}/{num_iterations:05d} ({pct_done:.2f}%) | loss: {debiased_smooth_loss:.6f} |{print_grad_norm} lrm: {lrm:.2f} | dt: {dt * 1000:.2f}ms | tok/sec: {tok_per_sec:,} | mfu: {mfu:.2f} | total time: {total_training_time/60:.2f}m")
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if step % 100 == 0:
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log_data = {
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"step": step,
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