code: def prepare_model1_weights_file_in_scopeQ():
      tf.reset_default_graph()
      with tf.variable_scope("scopeQ") as scope:
          m1 = Model1()
      m1.model.fit(
          {"scopeQ/input": X},
          {"scopeQ/target": Y},
          n_epoch=1,
          validation_set=0.1,
          show_metric=True,
          run_id="model1_scopeQ",
      )
      m1.model.save("model1_scopeQ.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 2 for calling a global function with example usage: prepare_model1_weights_file_in_scopeQ() without return types