I am trying Tensorflow 2.0 alpha preview and was testing the Eager execution . My doubt is that if you have a numpy array of variable size in middle like
in
This was happening to me in eager as well. Looking at the docs here , I ended up trying
tf.convert_to_tensor(input, dtype=tf.float32)
And that worked for me.
It seems that the only way to work with this is to use lists of lists and then convert them to ragged tensors, since numpy doesnt support ragged arrays very well. Will Update if I find anything new