60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
"""Module for the Scalar Weighting."""
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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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"""
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Weighting scheme that does not apply any weighting to the losses.
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"""
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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 losses: The dictionary of losses.
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:return: The aggregated losses.
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:rtype: torch.Tensor
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"""
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return sum(losses.values())
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class ScalarWeighting(WeightingInterface):
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"""
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Weighting scheme that assigns a scalar weight to each loss term.
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"""
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def __init__(self, weights):
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"""
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Initialization of the :class:`ScalarWeighting` class.
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:param weights: The weights to be assigned to each loss term.
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If a single scalar value is provided, it is assigned to all loss
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terms. If a dictionary is provided, the keys are the conditions and
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the values are the weights. If a condition is not present in the
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dictionary, the default value is used.
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:type weights: float | int | dict
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"""
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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 losses: The dictionary of losses.
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:return: The aggregated losses.
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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
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for condition, loss in losses.items()
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)
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