1bd3f40f54
* Modify domain by adding sample_mode, variables as property * Small change concatenate -> cat in lno/avno * Create different factory classes for conditions
30 lines
978 B
Python
30 lines
978 B
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__ = ["data", "conditionalvariable"]
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def __init__(self, data, conditionalvariable=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.data = data
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self.conditionalvariable = conditionalvariable
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self.condition_type = 'unsupervised'
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def __setattr__(self, key, value):
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if (key == 'data') or (key == 'conditionalvariable'):
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check_consistency(value, (LabelTensor, Graph, torch.Tensor))
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DataConditionInterface.__dict__[key].__set__(self, value) |