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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def image_channel_embeddings_bottom(x, model_hparams, vocab_size):
 """Bottom transformation for image targets."""

  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])