def _train_squad(self):
"""Runs BERT SQuAD training."""
input_meta_data = self._read_input_meta_data_from_file()
strategy = self._get_distribution_strategy()
run_squad.train_squad(strategy=strategy,
input_meta_data=input_meta_data,
custom_callbacks=[self.timer_callback])
def _train_squad(self, use_ds=True, run_eagerly=False):
"""Runs BERT SQuAD training."""
input_meta_data = self._read_input_meta_data_from_file()
strategy = self._get_distribution_strategy(use_ds)
run_squad.train_squad(strategy=strategy,
input_meta_data=input_meta_data,
run_eagerly=run_eagerly,
custom_callbacks=[self.timer_callback])
def _run_bert_squad(self):
"""Starts BERT SQuAD task."""
with tf.io.gfile.GFile(FLAGS.input_meta_data_path, 'rb') as reader:
input_meta_data = json.loads(reader.read().decode('utf-8'))
strategy = distribution_utils.get_distribution_strategy(
distribution_strategy='mirrored', num_gpus=self.num_gpus)
run_squad.train_squad(
strategy=strategy,
input_meta_data=input_meta_data,
custom_callbacks=[self.timer_callback])
def _run_bert_squad(self):
"""Starts BERT SQuAD training and evaluation tasks."""
with tf.io.gfile.GFile(FLAGS.input_meta_data_path, 'rb') as reader:
input_meta_data = json.loads(reader.read().decode('utf-8'))
strategy = distribution_utils.get_distribution_strategy(
distribution_strategy='mirrored', num_gpus=self.num_gpus)
run_squad.train_squad(strategy=strategy,
input_meta_data=input_meta_data,
custom_callbacks=[self.timer_callback])
run_squad.predict_squad(strategy=strategy,
input_meta_data=input_meta_data)
predictions_file = os.path.join(FLAGS.model_dir, 'predictions.json')
eval_metrics = self._evaluate_squad(predictions_file)
# Use F1 score as reported evaluation metric.
self.eval_metrics = eval_metrics['f1']