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']
