[BUGFIX] Log loss in NG and GNG
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@ -99,9 +99,14 @@ class NeuralGas(UnsupervisedPrototypeModel):
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# TODO Check if the batch has labels
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x = train_batch[0]
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d = self.compute_distances(x)
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cost, _ = self.energy_layer(d)
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loss, _ = self.energy_layer(d)
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self.topology_layer(d)
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return cost
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self.log("loss", loss)
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return loss
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# def training_epoch_end(self, training_step_outputs):
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# print(f"{self.trainer.lr_schedulers}")
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# print(f"{self.trainer.lr_schedulers[0]['scheduler'].optimizer}")
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class GrowingNeuralGas(NeuralGas):
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@ -121,7 +126,7 @@ class GrowingNeuralGas(NeuralGas):
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# TODO Check if the batch has labels
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x = train_batch[0]
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d = self.compute_distances(x)
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cost, order = self.energy_layer(d)
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loss, order = self.energy_layer(d)
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winner = order[:, 0]
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mask = torch.zeros_like(d)
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mask[torch.arange(len(mask)), winner] = 1.0
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@ -131,7 +136,8 @@ class GrowingNeuralGas(NeuralGas):
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self.errors *= self.hparams.step_reduction
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self.topology_layer(d)
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return cost
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self.log("loss", loss)
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return loss
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def configure_callbacks(self):
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return [
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