Is it possible to convert a keras model (h5 file of network architecture and weights) into a tensorflow model? Or is there an equivalent function to model.save of keras in tensorflow?
1 Answers
Yes, it is possible, because Keras, since it uses Tensorflow as backend, also builds computational graph. You just need to get this graph from your Keras model.
"Keras only uses one graph and one session. You can access the session via: K.get_session(). The graph associated with it would then be: K.get_session().graph."
(from fchollet: https://github.com/keras-team/keras/issues/3223#issuecomment-232745857)
Or you can save this graph in checkpoint format (https://www.tensorflow.org/api_docs/python/tf/train/Saver):
import tensorflow as tf
from keras import backend as K
saver = tf.train.Saver()
sess = K.get_session()
retval = saver.save(sess, ckpt_model_name)
By the way, since tensorflow 13 you can use keras right from it:
from tensorflow.python.keras import models, layers
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