9cae9a438f
* Enable DDP training with batch_size=None and add validity check for split sizes * Refactoring SolverInterfaces (#435) * Solver update + weighting * Updating PINN for 0.2 * Modify GAROM + tests * Adding more versatile loggers * Disable compilation when running on Windows * Fix tests --------- Co-authored-by: giovanni <giovanni.canali98@yahoo.it> Co-authored-by: FilippoOlivo <filippo@filippoolivo.com>
37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
""" Module for Loss Interface """
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from .weighting_interface import WeightingInterface
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from ..utils import check_consistency
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class _NoWeighting(WeightingInterface):
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def aggregate(self, losses):
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return sum(losses.values())
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class ScalarWeighting(WeightingInterface):
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"""
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TODO
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"""
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def __init__(self, weights):
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super().__init__()
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check_consistency([weights], (float, dict, int))
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if isinstance(weights, (float, int)):
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self.default_value_weights = weights
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self.weights = {}
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else:
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self.default_value_weights = 1
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self.weights = weights
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def aggregate(self, losses):
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"""
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Aggregate the losses.
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:param dict(torch.Tensor) losses: The dictionary of losses.
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:return: The losses aggregation. It should be a scalar Tensor.
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:rtype: torch.Tensor
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"""
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return sum(
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self.weights.get(condition, self.default_value_weights) * loss for
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condition, loss in losses.items()
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)
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