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Changes to grad scale logging; increase grad scale more frequently if less than one.
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@ -845,14 +845,24 @@ def train_one_epoch(
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rank=rank,
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rank=rank,
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)
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)
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if batch_idx % 100 == 0 and params.use_fp16:
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# If the grad scale was less than 1, try increasing it. The _growth_interval
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# of the grad scaler is configurable, but we can't configure it to have different
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# behavior depending on the current grad scale.
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cur_grad_scale = scaler._scale.item()
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if cur_grad_scale < 1.0:
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scaler.update(cur_grad_scale * 2.0)
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if batch_idx % params.log_interval == 0:
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if batch_idx % params.log_interval == 0:
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cur_lr = scheduler.get_last_lr()[0]
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cur_lr = scheduler.get_last_lr()[0]
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cur_grad_scale = scaler._scale.item() if params.use_fp16 else 1.0
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logging.info(
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logging.info(
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f"Epoch {params.cur_epoch}, "
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f"Epoch {params.cur_epoch}, "
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f"batch {batch_idx}, loss[{loss_info}], "
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f"batch {batch_idx}, loss[{loss_info}], "
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f"tot_loss[{tot_loss}], batch size: {batch_size}, "
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f"tot_loss[{tot_loss}], batch size: {batch_size}, "
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f"lr: {cur_lr:.2e}, " +
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f"lr: {cur_lr:.2e}, " +
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(f"grad_scale: {scaler.scale}" if params.use_fp16 else "")
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(f"grad_scale: {scaler._scale.item()}" if params.use_fp16 else "")
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)
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)
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if tb_writer is not None:
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if tb_writer is not None:
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@ -868,7 +878,7 @@ def train_one_epoch(
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)
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)
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if params.use_fp16:
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if params.use_fp16:
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tb_writer.add_scalar(
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tb_writer.add_scalar(
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"train/grad_scale", scaler.scale, params.batch_idx_train
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"train/grad_scale", cur_grad_scale, params.batch_idx_train
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)
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)
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