TensorFlow saves variables in binary checkpoint files that map variable names to
tensor values. vai_p_tensorflow takes a checkpoint
file as input to load trained weights. tf.train.Saver
provides methods to specify paths for the checkpoint files to write to or read from.
The following code snippet calls the tf.train.Saver.save method to save variables to checkpoint files:
with tf.Session() as sess:
# your graph building codes here
# ……
sess.run(train_op)
# Save the variables to disk.
save_path = saver.save(sess, "/tmp/model.ckpt")
print("Model saved in path: %s" % save_path)
The saved checkpoint files look like this:
model.ckpt.data-00000-of-00001
model.ckpt.index
model.ckpt.meta