I have a pandas dataset with a column of tensors of shape TensorShape([1, 512]) which are a result of tf.hub Bert embeddings. I know I can use an embedding layer directly in tensorflow, but is there a way to feed the data as it is in the Input layer?
I've tried with a (1, 512) shape input layer but I have an error: "Failed to convert a Numpy array to a Tensor". I've tried to feed it as a np.array instead of a series, but it's not working...
I would guess that it's a shape problem, but I don't see how to solve it!
Edits : I used USE from tf.hub : https://tfhub.dev/google/universal-sentence-encoder-large/5