code: def plot_sequential_model():
      model = keras.Sequential(
          [
              keras.Input((3,)),
              keras.layers.Dense(4, activation="relu"),
              keras.layers.Dense(1, activation="sigmoid"),
          ]
      )
      plot_model(model, "sequential.png")
      plot_model(model, "sequential-show_shapes.png", show_shapes=True)
      plot_model(
          model,
          "sequential-show_shapes-show_dtype.png",
          show_shapes=True,
          show_dtype=True,
      )
      plot_model(
          model,
          "sequential-show_shapes-show_dtype-show_layer_names.png",
          show_shapes=True,
          show_dtype=True,
          show_layer_names=True,
      )
      plot_model(
          model,
          "sequential-show_shapes-show_dtype-show_layer_names-show_layer_activations.png",  # noqa: E501
          show_shapes=True,
          show_dtype=True,
          show_layer_names=True,
          show_layer_activations=True,
      )
      plot_model(
          model,
          "sequential-show_shapes-show_dtype-show_layer_names-show_layer_activations-show_trainable.png",  # noqa: E501
          show_shapes=True,
          show_dtype=True,
          show_layer_names=True,
          show_layer_activations=True,
          show_trainable=True,
      )
      plot_model(
          model,
          "sequential-show_shapes-show_dtype-show_layer_names-show_layer_activations-show_trainable-LR.png",  # noqa: E501
          show_shapes=True,
          show_dtype=True,
          show_layer_names=True,
          show_layer_activations=True,
          show_trainable=True,
          rankdir="LR",
      )
      plot_model(
          model,
          "sequential-show_layer_activations-show_trainable.png",
          show_layer_activations=True,
          show_trainable=True,
      )
  
imports: import keras
  from keras.utils import plot_model
label_desc: Use image node_id 1 for calling a global function with example usage: plot_sequential_model() without return types