cleanup script

cleanup.py

@@ -0,0 +1,5 @@
+from util import cleanup
+
+cleanup_dir = '/Users/ryanzotti/Documents/repos/Self_Driving_RC_Car/tf_visual_data/runs/'
+cleanup(cleanup_dir)
+print("Cleanup completed successfully.")

train_glm.py

@@ -128,4 +128,7 @@ def max_pool_2x2(x):
 # Save the trained model to a file
 saver = tf.train.Saver()
 save_path = saver.save(sess, "/Users/ryanzotti/Documents/repos/Self-Driving-Car/trained_model/model.ckpt")
-#print("validation accuracy %g" % accuracy.eval(feed_dict={x: validation_predictors, y_: validation_targets, keep_prob: 1.0}))
+#print("validation accuracy %g" % accuracy.eval(feed_dict={x: validation_predictors, y_: validation_targets, keep_prob: 1.0}))
+
+# Marks unambiguous successful completion to prevent deletion by cleanup script
+shell_command('touch '+tfboard_run_dir+'/SUCCESS')

util.py

@@ -1,5 +1,6 @@
 import subprocess
-
+from os import listdir
+from os.path import isfile
 
 def dir_count(dir):
     shell_cmd = 'ls -ltr {dir} | wc -l'.format(dir=dir)
@@ -21,15 +22,24 @@ def mkdir_tfboard_run_dir(tf_basedir,):
     mkdir(new_run_dir)
     return new_run_dir
 
-
-def cp(a,b):
-    shell_cmd = 'cp {from_here} {to_there}'.format(from_here=a,to_there=b)
-    cmd_result = subprocess.check_output(shell_cmd, shell=True).strip()
-
 def shell_command(cmd):
     cmd_result = subprocess.check_output(cmd, shell=True).strip()
     return cmd_result
 
+
+def cleanup(dir):
+    if 'tf_visual_data/runs/' in dir:
+        sub_dirs = listdir(dir)
+        for sub_dir in sub_dirs:
+            if sub_dir is not isfile(sub_dir):
+                files = listdir(dir+'/'+sub_dir)
+                if "SUCCESS" not in files:
+                    shell_command('rm -rf ' + dir + sub_dir)
+    else:
+        pass # do not accidentally delete entire file system!
+
+
 if __name__ == '__main__':
     tensorboard_basedir = '/Users/ryanzotti/Documents/repos/Self_Driving_RC_Car/tf_visual_data/runs/'
+    cleanup(tensorboard_basedir)
     mkdir_tfboard_run_dir(tensorboard_basedir)