def _run_and_report_benchmark(self):
start_time_sec = time.time()
stats = ncf_keras_main.run_ncf(FLAGS)
wall_time_sec = time.time() - start_time_sec
metrics = self._extract_benchmark_report_extras(stats)
self.report_benchmark(iters=-1, wall_time=wall_time_sec, metrics=metrics)
def _run_and_report_benchmark(self):
start_time_sec = time.time()
stats = ncf_keras_main.run_ncf(FLAGS)
wall_time_sec = time.time() - start_time_sec
extras = self._extract_benchmark_report_extras(stats)
self.report_benchmark(iters=-1, wall_time=wall_time_sec, extras=extras)
def _run_and_report_benchmark(self, hr_at_10_min=0, hr_at_10_max=0):
start_time_sec = time.time()
stats = ncf_keras_main.run_ncf(FLAGS)
wall_time_sec = time.time() - start_time_sec
metrics = []
metrics.append({'name': 'exp_per_second',
'value': stats['avg_exp_per_second']})
if hr_at_10_min > 0:
metrics.append({'name': 'hr_at_10',
'value': stats['eval_hit_rate'],
'min_value': hr_at_10_min,
'max_value': hr_at_10_max})
metrics.append({'name': 'train_loss',
'value': stats['loss']})
self.report_benchmark(iters=-1, wall_time=wall_time_sec, metrics=metrics)
