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gat2
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@@ -118,10 +118,6 @@ class GAT(Model):
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)
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)
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)
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if loss not in {"mse", "binary"}:
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raise NotImplementedError("loss {} is not supported!".format(loss))
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self._scorer = mean_squared_error if loss == "mse" else roc_auc_score
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self.GAT_model = GATModel(
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self.GAT_model = GATModel(
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d_feat=self.d_feat,
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d_feat=self.d_feat,
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hidden_size=self.hidden_size,
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hidden_size=self.hidden_size,
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@@ -211,7 +207,6 @@ class GAT(Model):
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losses = []
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losses = []
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indices = np.arange(len(x_values))
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indices = np.arange(len(x_values))
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np.random.shuffle(indices)
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for i in range(len(indices))[:: self.batch_size]:
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for i in range(len(indices))[:: self.batch_size]:
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