Adding to @Dmitry Kabanov, they are similar yet they aren’t exactly the same thing. If you care about performance, need to look in to critical differences between them.
model.predict | model(x) |
---|---|
loops over the data in batches which means means that predict() calls can scale to very large arrays. | happens in-memory and doesn’t scale |
not differentiable | differentiable |
use this if you just need the output value | use this when you need to retrieve the gradients |
Output is NumPy value | Output is a Tensor |
use this if you have batches of data to be predicted | use this for small dataset |
relatively slower for small data | relatively faster for small data |
Please check more detailed explanation in Keras FAQs