def convert_embedding(builder, layer, input_names, output_names, keras_layer):
    """Convert a dense layer from keras to coreml.

    Parameters
    keras_layer: layer
    ----------
        A keras layer object.

    builder: NeuralNetworkBuilder
        A neural network builder object.
    """
    # Get input and output names
    input_name, output_name = (input_names[0], output_names[0])

    # Get the weights from keras
    W = keras_layer.get_weights ()[0].T

    # assuming keras embedding layers don't have biases
    builder.add_embedding(name = layer,
                          W = W,
                          b = None,
                          input_dim = keras_layer.input_dim,
                          output_channels = keras_layer.output_dim,
                          has_bias = False,
                          input_name = input_name,
                          output_name = output_name)