code: def image_channel_embeddings_bottom(x, model_hparams, vocab_size):
    
    del vocab_size  # unused arg
    inputs = tf.to_int32(x)
    io_depth = model_hparams.num_channels
    tshape = common_layers.shape_list(inputs)
    hidden_size = model_hparams.hidden_size
    target_embeddings = cia.get_channel_embeddings(
        io_depth, inputs, hidden_size, "input_bottom")
    return tf.reshape(target_embeddings,
                      [tshape[0], tshape[1], tshape[2] * io_depth, hidden_size])
docs: Bottom transformation for image targets.