Add lag x eul loss tracking to tensorboard
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@ -297,9 +297,12 @@ def train(epoch, loader, model, lag2eul, criterion,
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eul_loss /= world_size
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if rank == 0:
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logger.add_scalar('loss/batch/train/lag', lag_loss.item(),
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global_step=batch)
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global_step=batch)
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logger.add_scalar('loss/batch/train/eul', eul_loss.item(),
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global_step=batch)
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global_step=batch)
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logger.add_scalar('loss/batch/train/lxe',
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lag_loss.item() * eul_loss.item(),
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global_step=batch)
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logger.add_scalar('grad/lag/first', lag_grads[0],
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global_step=batch)
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@ -314,9 +317,11 @@ def train(epoch, loader, model, lag2eul, criterion,
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epoch_loss /= len(loader) * world_size
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if rank == 0:
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logger.add_scalar('loss/epoch/train/lag', epoch_loss[0],
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global_step=epoch+1)
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global_step=epoch+1)
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logger.add_scalar('loss/epoch/train/eul', epoch_loss[1],
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global_step=epoch+1)
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global_step=epoch+1)
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logger.add_scalar('loss/epoch/train/lxe', epoch_loss.prod(),
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global_step=epoch+1)
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logger.add_figure('fig/epoch/train', plt_slices(
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input[-1], lag_out[-1], lag_tgt[-1], lag_out[-1] - lag_tgt[-1],
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@ -362,9 +367,11 @@ def validate(epoch, loader, model, lag2eul, criterion, logger, device, args):
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epoch_loss /= len(loader) * world_size
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if rank == 0:
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logger.add_scalar('loss/epoch/val/lag', epoch_loss[0],
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global_step=epoch+1)
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global_step=epoch+1)
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logger.add_scalar('loss/epoch/val/eul', epoch_loss[1],
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global_step=epoch+1)
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global_step=epoch+1)
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logger.add_scalar('loss/epoch/val/lxe', epoch_loss.prod(),
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global_step=epoch+1)
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logger.add_figure('fig/epoch/val', plt_slices(
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input[-1], lag_out[-1], lag_tgt[-1], lag_out[-1] - lag_tgt[-1],
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