def predict(self, data, *args):
if self.preprocessing:
data = self.preprocessing(data, *args)
with tf.Graph().as_default() as _:
variables_test, sampler_test = machine_reading_sampler(data, batch_size=None, shuffling=False)
ops = embedding_updater_model(variables_test, rank=self.rank, n_ents=self.n_ents, n_slots=self.n_slots,
init_params=self.params)
nll, pred, y = tf_eval(ops)
return pred, y, nll
import tensorflow as tf from naga.shared.tf_addons import tf_eval a = tf.Variable([[1, 2], [3, 4], [5, 6]]) b = tf.constant(3) print(tf_eval(tf.minimum(a, 2)))
