Use transpose parameter of matmul
@@ -546,7 +546,7 @@ class ArcCosine(Kern):
if X2 is None:
return tf.reduce_sum(self.weight_variances * tf.square(X), axis=1) + self.bias_variance
else:
- return tf.matmul((self.weight_variances * X), tf.transpose(X2)) + self.bias_variance
+ return tf.matmul((self.weight_variances * X), X2, transpose_b=True) + self.bias_variance
def _J(self, theta):
"""
