def testTrainWithNoneAsLogdirWhenUsingSummariesRaisesError(self):
with tf.Graph().as_default():
tf.set_random_seed(0)
tf_inputs = tf.constant(self._inputs, dtype=tf.float32)
tf_labels = tf.constant(self._labels, dtype=tf.float32)
tf_predictions = LogisticClassifier(tf_inputs)
slim.losses.log_loss(tf_predictions, tf_labels)
total_loss = slim.losses.get_total_loss()
tf.scalar_summary('total_loss', total_loss)
optimizer = tf.train.GradientDescentOptimizer(learning_rate=1.0)
train_op = slim.learning.create_train_op(total_loss, optimizer)
summary_op = tf.merge_all_summaries()
with self.assertRaises(ValueError):
slim.learning.train(
train_op, None, number_of_steps=300, summary_op=summary_op)
评论列表
文章目录