text: from framework import Framework
  import tensorflow as tf
  
  FLAGS = tf.app.flags.FLAGS
  
  def pcnn_att(is_training, is_dev=False):
  	if is_training:
  		framework = Framework(is_training=True)
  	else:
  		framework = Framework(is_training=False, use_bag=False)
  
  	word_embedding = framework.embedding.word_embedding()
  	pos_embedding = framework.embedding.pos_embedding()
  	embedding = framework.embedding.concat_embedding(word_embedding, pos_embedding)
  	x = framework.encoder.pcnn(embedding, FLAGS.hidden_size, framework.mask, activation=tf.nn.relu)
  
  	if is_training:
  		logit, repre = framework.selector.attention(x, framework.scope, framework.label_for_select)
  		loss = framework.classifier.softmax_cross_entropy(logit)
  		output = framework.classifier.output(logit)
  		framework.init_train_model(loss, output, optimizer=tf.train.GradientDescentOptimizer)
  		framework.load_train_data()
  		framework.train()
  	else:
  		logit, repre = framework.selector.no_bag(x)
  		framework.init_test_model(logit) # TODO
  		if is_dev:
  			framework.load_dev_data()
  			framework.test()
  		else:
  			framework.load_test_data()
  			framework.test()
  
  