python - std::system_error after restoring model in Tensorflow -

i'm trying implement simple saver/restorer so: (copied tensorflow website)

saver:

import tensorflow tf  # create variables. v1 = tf.get_variable("v1", shape=[3], initializer = tf.zeros_initializer) v2 = tf.get_variable("v2", shape=[5], initializer = tf.zeros_initializer)  inc_v1 = v1.assign(v1+1) dec_v2 = v2.assign(v2-1)  # add op initialize variables. init_op = tf.global_variables_initializer()  # add ops save , restore variables. saver = tf.train.saver()  # later, launch model, initialize variables, work, , save # variables disk. tf.session() sess:   sess.run(init_op)   # work model.   inc_v1.op.run()   dec_v2.op.run()   # save variables disk.   save_path = saver.save(sess, "/tmp/model.ckpt")   print("model saved in file: %s" % save_path) 

restorer:

import tensorflow tf  tf.reset_default_graph()  # create variables. v1 = tf.get_variable("v1", shape=[3]) v2 = tf.get_variable("v2", shape=[5])  # add ops save , restore variables. saver = tf.train.saver()  # later, launch model, use saver restore variables disk, , # work model. tf.session() sess:   # restore variables disk.   saver.restore(sess, "/tmp/model.ckpt")   print("model restored.")   # check values of variables   print("v1 : %s" % v1.eval())   print("v2 : %s" % v2.eval()) 

it seems save model fine, when restoring gets stuck on line saver.restore(sess, "/tmp/model.ckpt") , end error message:

terminate called after throwing instance of 'std::system_error' what(): resource temporarily unavailable 

i don't see how can memory error running on work server has 100s of gb of memory.

python version 3.5, tensorflow version 1.2.1