bert_max_doc_str_max_str_pos_clean_doc_noise_doc/run_doc_qa.py
def build_opt_op(self, learning_rate, num_train_steps, num_warmup_steps,
                     use_tpu=False):
        """Builds optimization operator for the model."""
        loss_to_opt = self._outputs['loss_to_opt']

        return optimization.create_optimizer(
            loss_to_opt, learning_rate, num_train_steps, num_warmup_steps,
            use_tpu
        )
Builds optimization operator for the model.
Builds optimization operator for the model.
Builds optimization operator for the model .
def build_opt_op(self, learning_rate, num_train_steps, num_warmup_steps,
                     use_tpu=False):
        loss_to_opt = self._outputs['loss_to_opt']
        return optimization.create_optimizer(
            loss_to_opt, learning_rate, num_train_steps, num_warmup_steps,
            use_tpu
        )
def build_opt_op ( self , learning_rate , num_train_steps , num_warmup_steps , use_tpu = False ) : loss_to_opt = self . _outputs [ 'loss_to_opt' ] return optimization . create_optimizer ( loss_to_opt , learning_rate , num_train_steps , num_warmup_steps , use_tpu )
Builds optimization operator for the model.
Builds optimization operator for the model .
"""Builds optimization operator for the model."""
self
learning_rate
num_train_steps
num_warmup_steps
use_tpu