text: from build_model import model_tools
  import tensorflow as tf
  model=model_tools()
  
  def generate_model(images_ph,number_of_classes):
      #MODEL ARCHITECTURE:
      #level 1 convolution
      network=model.conv_layer(images_ph,5,3,16,1)
      network=model.pooling_layer(network,5,2)
      network=model.activation_layer(network)
      print(network)
  
      #level 2 convolution
      network=model.conv_layer(network,4,16,32,1)
      network=model.pooling_layer(network,4,2)
      network=model.activation_layer(network)
      print(network)
  
      #level 3 convolution
      network=model.conv_layer(network,3,32,64,1)
      network=model.pooling_layer(network,3,2)
      network=model.activation_layer(network)
      print(network)
  
      #flattening layer
      network,features=model.flattening_layer(network)
      print(network)
  
      #fully connected layer
      network=model.fully_connected_layer(network,features,1024)
      network=model.activation_layer(network)
      print(network)
  
      #output layer
      network=model.fully_connected_layer(network,1024,number_of_classes)
      print(network)
      return network
  
  
  if __name__== "__main__":
      images_ph = tf.placeholder(tf.float32, shape=[None, 100,100,3])
      generate_model(images_ph,2)