fix: use inverse func in p method in Label class
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@@ -103,7 +103,7 @@ class ClassicalAutoencoder(AAutoencoder):
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self.losses = [self.loss(data_set)]
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epoch = 0
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no_improv = 0
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prev_error = self.losses[0]
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prev_error = self.losses[-1]
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with tqdm(bar_format="{desc} {elapsed} {rate_fmt}") as lbar:
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while True:
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lbar.set_description(
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@@ -198,7 +198,7 @@ class VariationalAutoencoder(AAutoencoder):
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self.KL_losses = [kl_0]
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epoch = 0
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no_improv = 0
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prev_loss = self.recon_losses[0] + self.KL_losses[0]
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prev_loss = self.recon_losses[-1] + self.KL_losses[-1]
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with tqdm(bar_format="{desc} {elapsed} {rate_fmt}") as lbar:
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while True:
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lbar.set_description(
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@@ -265,9 +265,7 @@ class Label:
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self.history[idx] = (self.history[idx] + code) / 2
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def p(self, x: np.ndarray):
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return np.mean(
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np.exp(-np.abs(self.history - x))
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)
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return 1 / (1e-4 + np.mean(np.abs(self.history - x)))
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class LabelingVAE(VariationalAutoencoder):
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