train and test

+import tensorflow as tf
+from model import DTN
+from solver import Solver
+
+
+
+flags = tf.app.flags
+flags.DEFINE_boolean('is_train', False, 'True if train mode, False if test mode')
+
+FLAGS = flags.FLAGS
+
+def main(_):
+    
+    model = DTN(batch_size=100, learning_rate=0.001, image_size=32, output_size=32, 
+                 dim_color=3, dim_fout=100, dim_df=64, dim_gf=64, dim_ff=64)
+    
+    solver = Solver(model, num_epoch=10, mnist_path= 'mnist/', svhn_path='svhn/', model_save_path='model/', 
+                    log_path='log/', sample_path='sample/', test_model_path='model/dtn-2-1', sample_iter=100)
+    
+    
+    if FLAGS.is_train:
+        solver.train()
+    else:
+        solver.test()
+    
+
+
+if __name__ == '__main__':
+    tf.app.run()
+    
+    
+   
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