code: def prepare_model1_weights_file():
      tf.reset_default_graph()
      m1 = Model1()
      m1.train(X, Y, testX, testY, 2)
      m1.model.save("model1.tfl")
  
imports: from __future__ import division, print_function, absolute_import
  import re
  import tflearn
  import tensorflow.compat.v1
  import tflearn.datasets.mnist
  from tflearn.layers.core import input_data, dropout, fully_connected
  from tflearn.layers.conv import conv_2d, max_pool_2d
  from tflearn.layers.normalization import local_response_normalization
  from tflearn.layers.estimator import regression
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_model1_weights_file() without return types