Discrepancy between pybamm inner and numpy inner

General
1

I was wondering the reasoning for this discrepancy between the Pybamm Inner product and the numpy inner product

import pybamm
import numpy as np

a = np.array([1,2,3,4,5])
b = np.array([5,4,3,2,1])

c_pb = pybamm.Inner(a,b)
c_np = np.inner(a,b)
print(f"pybamm inner: {c_pb.evaluate()} \n numpy inner: {c_np}")

returns:

pybamm inner: [[5.]
 [8.]
 [9.]
 [8.]
 [5.]] 
 numpy inner: 35

I am attempting to apply the inner product as a part of a custom parameter model evaluation which would utilize custom Input Parameters representing the GP model, it would be very helpful if these models are able to be solved in parallel. Any help is appreciated thank you!