32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
import torch
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from . import ConditionInterface
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from ..label_tensor import LabelTensor
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from ..graph import Graph
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from ..utils import check_consistency
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class DataConditionInterface(ConditionInterface):
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"""
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Condition for data. This condition must be used every
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time a Unsupervised Loss is needed in the Solver. The conditionalvariable
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can be passed as extra-input when the model learns a conditional
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distribution
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"""
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__slots__ = ["input_points", "conditional_variables"]
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def __init__(self, input_points, conditional_variables=None):
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"""
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TODO
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"""
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super().__init__()
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self.input_points = input_points
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self.conditional_variables = conditional_variables
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self.condition_type = 'unsupervised'
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def __setattr__(self, key, value):
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if (key == 'input_points') or (key == 'conditional_variables'):
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check_consistency(value, (LabelTensor, Graph, torch.Tensor))
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DataConditionInterface.__dict__[key].__set__(self, value)
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elif key in ('problem', 'condition_type'):
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super().__setattr__(key, value) |