'Gate values corresponding to the examples in the per-expert `Tensor`s.
Returns:
a list of `num_experts` one-dimensional `Tensor`s with type `tf.float32`
and shapes `[expert_batch_size_i]`'

def ExpertToGates(self):

    return tf.split(self._nonzero_gates, self._part_sizes_tensor, 0)
