Implementations in tf.keras.backend have duplicates in pure tensorflow. For example: tf.keras.backend.ones vs tf.ones.
My question: Can I use tensorflow instead of tf.keras.backend, by just replacing it? Both are same API?
Implementations in tf.keras.backend have duplicates in pure tensorflow. For example: tf.keras.backend.ones vs tf.ones.
My question: Can I use tensorflow instead of tf.keras.backend, by just replacing it? Both are same API?
Yes, you can use tf but there might be minor difference in the results as both of them have different repo maintained.
For example the tf.keras.backend.binary_crossentropy and tf.keras.losses.binary_crossentropy have different code repo maintained but objective should remain the same.
Most of the time, yes. To learn of the difference, do:
tf.ones?
ortf.ones??
if your IDE supports it; this'll show docs + source code + file locationfrom inspect import getsource; print(getsource(tf.ones))
will show source codeI'd not replace
K
withtf
, though; stuff gets moved around between versions, and functionality may break. Each has its own list of imports:tensorflow/__init__.py
andtensorflow/python/keras/backend.py
.