def parametrized_bottleneck(x, hparams):
  """Meta-function calling all the above bottlenecks with hparams."""
  if hparams.bottleneck_kind == "tanh_discrete":
    d, _ = tanh_discrete_bottleneck(
        x, hparams.bottleneck_bits, hparams.bottleneck_noise * 0.5,
        hparams.discretize_warmup_steps, hparams.mode)
    return d, 0.0
  if hparams.bottleneck_kind == "isemhash":
    return isemhash_bottleneck(
        x, hparams.bottleneck_bits, hparams.bottleneck_noise * 0.5,
        hparams.discretize_warmup_steps, hparams.mode,
        hparams.isemhash_noise_dev, hparams.isemhash_mix_prob)
  if hparams.bottleneck_kind == "vq":
    return vq_discrete_bottleneck(x, hparams.bottleneck_bits, hparams.vq_beta,
                                  hparams.vq_decay, hparams.vq_epsilon)
  if hparams.bottleneck_kind == "em":
    return vq_discrete_bottleneck(
        x,
        hparams.bottleneck_bits,
        hparams.vq_beta,
        hparams.vq_decay,
        hparams.vq_epsilon,
        soft_em=True,
        num_samples=hparams.vq_num_samples)
  if hparams.bottleneck_kind == "gumbel_softmax":
    return gumbel_softmax_discrete_bottleneck(
        x,
        hparams.bottleneck_bits,
        hparams.vq_beta,
        hparams.vq_decay,
        hparams.vq_epsilon,
        hparams.temperature_warmup_steps,
        hard=False,
        summary=True)

  raise ValueError(
      "Unsupported hparams.bottleneck_kind %s" % hparams.bottleneck_kind)
Meta-function calling all the above bottlenecks with hparams.