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fix missing 'mean loss' for tensorboard integration

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AngelBottomless 2023-01-16 02:08:47 +09:00 committed by GitHub
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modules/hypernetworks/hypernetwork.py
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@ -644,7 +644,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
if shared.opts.training_enable_tensorboard: if shared.opts.training_enable_tensorboard:
epoch_num = hypernetwork.step // len(ds) epoch_num = hypernetwork.step // len(ds)
epoch_step = hypernetwork.step - (epoch_num * len(ds)) + 1 epoch_step = hypernetwork.step - (epoch_num * len(ds)) + 1
mean_loss = sum(sum(x) for x in loss_dict.values()) / sum(len(x) for x in loss_dict.values())
textual_inversion.tensorboard_add(tensorboard_writer, loss=mean_loss, global_step=hypernetwork.step, step=epoch_step, learn_rate=scheduler.learn_rate, epoch_num=epoch_num) textual_inversion.tensorboard_add(tensorboard_writer, loss=mean_loss, global_step=hypernetwork.step, step=epoch_step, learn_rate=scheduler.learn_rate, epoch_num=epoch_num)
textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, steps_per_epoch, { textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, steps_per_epoch, {