I am learning TensorFlow 2.0, whose layer functions are based on Keras. What is the difference between the
Keras has two basic organizational modes: "Sequential" and "Functional".
concatenate is the functional version, and really just wraps the
def concatenate(inputs, axis=-1, **kwargs): """...snip documentation...""" return Concatenate(axis=axis, **kwargs)(inputs)
Keras provides 2 kinds of API i.e. Sequential and Functional. And because of this 2 kind of API, the difference is there in them.
- Concatenate is used when you are using Sequential API
- concatenate is used when you are using Functional API
Just look into the following documentation: https://keras.io/layers/merge/