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)