def _evaluate_squad(self, use_ds=True): """Runs BERT SQuAD evaluation.""" assert tf.version.VERSION.startswith('2.') input_meta_data = self._read_input_meta_data_from_file() strategy = self._get_distribution_strategy(use_ds) run_squad.predict_squad(strategy=strategy, input_meta_data=input_meta_data) dataset = self._read_predictions_dataset_from_file() predictions = self._read_predictions_from_file() eval_metrics = squad_evaluate_v1_1.evaluate(dataset, predictions) # Use F1 score as reported evaluation metric. self.eval_metrics = eval_metrics['f1']
def _evaluate_squad(self, use_ds=True): """Runs BERT SQuAD evaluation.""" tf.enable_v2_behavior() input_meta_data = self._read_input_meta_data_from_file() strategy = self._get_distribution_strategy(use_ds) run_squad.predict_squad(strategy=strategy, input_meta_data=input_meta_data) dataset = self._read_predictions_dataset_from_file() predictions = self._read_predictions_from_file() eval_metrics = squad_evaluate_v1_1.evaluate(dataset, predictions) # Use F1 score as reported evaluation metric. self.eval_metrics = eval_metrics['f1']
def _evaluate_squad(self, ds_type='mirrored'): """Runs BERT SQuAD evaluation. Uses mirrored strategy by default.""" assert tf.version.VERSION.startswith('2.') self._init_gpu_and_data_threads() input_meta_data = self._read_input_meta_data_from_file() strategy = self._get_distribution_strategy(ds_type) run_squad.predict_squad(strategy=strategy, input_meta_data=input_meta_data) dataset = self._read_predictions_dataset_from_file() predictions = self._read_predictions_from_file() eval_metrics = squad_evaluate_v1_1.evaluate(dataset, predictions) # Use F1 score as reported evaluation metric. self.eval_metrics = eval_metrics['f1']