kernels.py 文件源码

def _slice(self, X, X2):
        """
        Slice the correct dimensions for use in the kernel, as indicated by
        `self.active_dims`.
        :param X: Input 1 (NxD).
        :param X2: Input 2 (MxD), may be None.
        :return: Sliced X, X2, (Nxself.input_dim).
        """
        if isinstance(self.active_dims, slice):
            X = X[:, self.active_dims]
            if X2 is not None:
                X2 = X2[:, self.active_dims]
        else:
            X = tf.transpose(tf.gather(tf.transpose(X), self.active_dims))
            if X2 is not None:
                X2 = tf.transpose(tf.gather(tf.transpose(X2), self.active_dims))
        input_dim_shape = tf.shape(X)[1]
        input_dim = tf.convert_to_tensor(self.input_dim, dtype=settings.tf_int)
        with tf.control_dependencies([tf.assert_equal(input_dim_shape, input_dim)]):
            X = tf.identity(X)

        return X, X2