def discriminate(x):
        """Run a dioscriminator depending on the hparams."""
        if hparams.discriminator == "default":
          return common_layers.deep_discriminator(
              x, hparams.discriminator_batchnorm, is_training)
        elif hparams.discriminator == "patched":
          return common_layers.patch_discriminator(x)
        elif hparams.discriminator == "single":
          return common_layers.single_discriminator(
              x,
              hparams.discriminator_size,
              hparams.discriminator_kernel_size,
              hparams.discriminator_strides,
              pure_mean=hparams.discriminator_pure_mean)
        elif hparams.discriminator == "double":
          return common_layers.double_discriminator(
              x,
              hparams.discriminator_size,
              hparams.discriminator_kernel_size,
              hparams.discriminator_strides,
              pure_mean=hparams.discriminator_pure_mean)
        else:
          raise Exception("Unknown discriminator %s" % hparams.discriminator)
Run a dioscriminator depending on the hparams.
tensor2tensor/models/research/autoencoders.py