def imagetransformerpp_sep_channels_8l_8h():
  """separate rgb embeddings."""
  hparams = imagetransformer_base()
  hparams.likelihood = cia.DistributionType.DMOL
  hparams.num_channels = 1
  hparams.bottom["targets"] = modalities.image_channel_compress_targets_bottom
  hparams.top["targets"] = modalities.identity_top
  hparams.num_heads = 8
  hparams.batch_size = 4
  hparams.attention_key_channels = hparams.attention_value_channels = 0
  hparams.hidden_size = 512
  hparams.filter_size = 512
  hparams.num_hidden_layers = 8
  hparams.sampling_method = "random"
  hparams.layer_preprocess_sequence = "n"
  hparams.layer_postprocess_sequence = "da"
  hparams.summarize_grads = True
  hparams.learning_rate = 0.1
  return hparams