code: def convert_dense(builder, layer, input_names, output_names, keras_layer):
      
      # Get input and output names
      input_name, output_name = (input_names[0], output_names[0])
  
      has_bias = keras_layer.bias
      # Get the weights from keras
      W = keras_layer.get_weights ()[0].T
      Wb = keras_layer.get_weights ()[1].T if has_bias else None
  
      builder.add_inner_product(name = layer,
              W = W,
              b = Wb,
              input_channels = keras_layer.input_dim,
              output_channels = keras_layer.output_dim,
              has_bias = has_bias,
              input_name = input_name,
              output_name = output_name)
docs: Convert a dense layer from keras to coreml.
  
      Parameters
      keras_layer: layer
      ----------
          A keras layer object.
  
      builder: NeuralNetworkBuilder
          A neural network builder object.