Move CELVQ to probabilistic.py
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"""Probabilistic GLVQ methods"""
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import torch
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from prototorch.functions.competitions import stratified_sum
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from prototorch.functions.competitions import stratified_min, stratified_sum
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from prototorch.functions.losses import log_likelihood_ratio_loss, robust_soft_loss
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from prototorch.functions.transforms import gaussian
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from .glvq import GLVQ
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class CELVQ(GLVQ):
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"""Cross-Entropy Learning Vector Quantization."""
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def __init__(self, hparams, **kwargs):
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super().__init__(hparams, **kwargs)
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self.loss = torch.nn.CrossEntropyLoss()
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def shared_step(self, batch, batch_idx, optimizer_idx=None):
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x, y = batch
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out = self._forward(x) # [None, num_protos]
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plabels = self.proto_layer.component_labels
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probs = -1.0 * stratified_min(out, plabels) # [None, num_classes]
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batch_loss = self.loss(probs, y.long())
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loss = batch_loss.sum(dim=0)
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return out, loss
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class ProbabilisticLVQ(GLVQ):
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def __init__(self, hparams, rejection_confidence=0.0, **kwargs):
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super().__init__(hparams, **kwargs)
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