def _run_and_report_benchmark(self):
start_time_sec = time.time()
stats = imagenet_main.run_imagenet(flags.FLAGS)
wall_time_sec = time.time() - start_time_sec
self._report_benchmark(stats,
wall_time_sec,
top_1_min=0.762,
top_1_max=0.766)
def _run_and_report_benchmark(self):
start_time_sec = time.time()
stats = imagenet_main.run_imagenet(flags.FLAGS)
wall_time_sec = time.time() - start_time_sec
self._report_benchmark(stats,
wall_time_sec,
top_1_min=0.762,
top_1_max=0.766)
def _run_and_report_benchmark(self):
start_time_sec = time.time()
stats = imagenet_main.run_imagenet(FLAGS)
wall_time_sec = time.time() - start_time_sec
print(stats)
# Remove values to skip triggering accuracy check.
stats['eval_results'].pop('accuracy', None)
stats['eval_results'].pop('accuracy_top_5', None)
self._report_benchmark(stats, wall_time_sec)
def _run_and_report_benchmark(self):
start_time_sec = time.time()
stats = imagenet_main.run_imagenet(FLAGS)
wall_time_sec = time.time() - start_time_sec
print(stats)
# Remove values to skip triggering accuracy check.
del stats['eval_results']['accuracy']
del stats['eval_results']['accuracy_top_5']
self._report_benchmark(stats,
wall_time_sec)