break
// build variables to run
vars_to_run = dict()
vars_to_run[NETWORK_OUTPUT], vars_to_run[CONSOLE] = \
self.outputs_collector.variables(NETWORK_OUTPUT), \
self.outputs_collector.variables(CONSOLE)
// evaluate the graph variables
graph_output = sess.run(vars_to_run)
// process the graph outputs
if not self.app.interpret_output(graph_output[NETWORK_OUTPUT]):
tf.logging.info("processed all batches.")
After Change
iter_msg = IterationMessage()
loop_status["all_saved_flag"] = False
iter_i = 0
while True:
if self._coord.should_stop():
break
if iter_msg.should_stop:
break
iter_msg.current_iter, iter_msg.phase = iter_i, INFER
// run variables provided in `iter_msg` and set values of
// variables to iter_msg.current_iter_output
self.app.set_iteration_update(iter_msg)
self.run_vars(sess, iter_msg)
self.app.set_iteration_update(iter_msg)
iter_i = iter_i + 1
// process the graph outputs
if not self.app.interpret_output(
iter_msg.current_iter_output[NETWORK_OUTPUT]):
