fix a bug in calculating clarity loss as sample weight is specified; …

…update v0.5.6
ZebinYang · Oct 19, 2021 · 153bed4 · 153bed4
1 parent 8d99bc9
commit 153bed4
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Showing 2 changed files with 2 additions and 2 deletions.
diff --git a/dist/gaminet-0.5.6-py3-none-any.whl b/dist/gaminet-0.5.6-py3-none-any.whl
diff --git a/gaminet/gaminet.py b/gaminet/gaminet.py
@@ -159,8 +159,8 @@ def call(self, inputs, sample_weight=None, main_effect_training=False, interacti
                 a2 = tf.multiply(tf.gather(self.maineffect_outputs, [k2], axis=1), tf.gather(main_weights, [k2], axis=0))
                 b = tf.multiply(tf.gather(self.interact_outputs, [i], axis=1), tf.gather(interaction_weights, [i], axis=0))
                 if sample_weight is not None:
-                    self.clarity_loss += tf.abs(tf.reduce_mean(tf.multiply(tf.multiply(a1, b), sample_weight.reshape(-1, 1))))
-                    self.clarity_loss += tf.abs(tf.reduce_mean(tf.multiply(tf.multiply(a2, b), sample_weight.reshape(-1, 1))))
+                    self.clarity_loss += tf.abs(tf.reduce_mean(tf.multiply(tf.multiply(a1, b), tf.reshape(sample_weight, (-1, 1)))))
+                    self.clarity_loss += tf.abs(tf.reduce_mean(tf.multiply(tf.multiply(a2, b), tf.reshape(sample_weight, (-1, 1)))))
                 else:
                     self.clarity_loss += tf.abs(tf.reduce_mean(tf.multiply(a1, b)))
                     self.clarity_loss += tf.abs(tf.reduce_mean(tf.multiply(a2, b)))