small
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@@ -260,9 +260,9 @@ def train_step(batch):
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kl = kl_loss(mean, logvar)
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if config['use_extra_losses']:
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (e_loss + l2_loss + l2_mesh_loss)
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (l2_loss + l2_mesh_loss)
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if not config['is_cape']:
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (c_loss) * config['reg_loss_coeff']
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (e_loss + c_loss) * config['reg_loss_coeff']
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else:
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (l2_loss)
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@@ -345,9 +345,9 @@ def valid_step(batch):
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kl = kl_loss(mean, logvar)
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if config['use_extra_losses']:
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (e_loss + l2_loss + l2_mesh_loss)
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (l2_loss + l2_mesh_loss)
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if not config['is_cape']:
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (c_loss) * config['reg_loss_coeff']
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (e_loss + c_loss) * config['reg_loss_coeff']
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else:
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reconstr_loss_total = reconstr_loss_total + config['pyramid']['loss_weights'][i] * (l2_loss)
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