code: def build_model():
      inp = Input(shape=(FRAME_H, FRAME_W, 3))
      x = Conv2D(filters=8, kernel_size=(5, 5), activation="relu")(inp)
      x = MaxPooling2D((2, 2))(x)
  
      x = Conv2D(filters=16, kernel_size=(5, 5), activation="relu")(x)
      x = MaxPooling2D((2, 2))(x)
  
      x = Conv2D(filters=32, kernel_size=(5, 5), activation="relu")(x)
      x = MaxPooling2D((2, 2))(x)
  
      x = Flatten()(x)
      x = Dropout(0.5)(x)
      x = Dense(128, activation="relu")(x)
      x = Dropout(0.5)(x)
      x = Dense(1, activation="tanh")(x)
      return Model(inputs=[inp], outputs=[x])
  
imports: from keras.layers.core import Dropout, Flatten
  from keras.layers.convolutional import MaxPooling2D, Conv2D
  from keras.models import Model
  from keras.layers import Input, Dense
label_desc: Use image node_id 1 for calling a global function with example usage: build_model() and returns: Model