# saver.restore(sess, ckpt_path)
# sess.graph.as_default()
# import numpy as np
# in_m = sess.run(terminals['in_matr'])
# np.savetxt("in_m.txt", in_m, delimiter="\t")
# out_m = sess.run(terminals['out_matr'])
# np.savetxt("out_m.txt", out_m, delimiter="\t")
# sys.exit()
for e in range(epochs):
# batch = reader.next_batch()
# first_batch = batch
for ind, batch in enumerate(reader.batches()):
in_words, out_words, labels = batch
_, batch_count = sess.run([train_, adder_], {
in_words_: in_words,
out_words_: out_words,
labels_: labels
})
if batch_count % 1000 == 0:
# in_words, out_words, labels = first_batch
loss_val, summary, _ = sess.run([loss_, saveloss_, final_], {
in_words_: in_words,
out_words_: out_words,
labels_: labels
