feed_dict = {}
feed_dict[self._global_step] = i
for k in range(len(inputs)):
feed_dict[self._input_placeholders[k]] = inputs[k]
feed_dict[self._meta_placeholders[k]] = inputs[k]
self._session.run(self._add_gradients, feed_dict=feed_dict)
self._session.run(self._meta_train_op)
After Change
for j in range(self.meta_batch_size):
learner.select_task()
meta_loss, meta_gradients = self._compute_meta_loss(
learner.get_batch(), learner.get_batch(), variables)
if j == 0:
summed_gradients = meta_gradients
else:
