Python numpy with cvxpy incompatibility issue

Question

I'm trying to run the following code in order to achieve from two vectors A = (N,1) and B = (M,1) a matrix with dimension (N, M). A matrix multiplication should allow to achieve this: AxB. However, my code below throws a strange incompatibility issue:

import pandas as pd
import numpy as np
import cvxpy as cvx
        
df = pd.DataFrame([
        [1,3,1],
        [2,0,4],
        [0,5,4],
        [3,4,3],
        [5,2,5]],  
    columns = ["Metric1","Metric2","Metric3"]
)    
        
mat_bin = df.copy().to_numpy()
v_cvxvar = cvx.Variable(mat_bin.shape[1], nonneg=True)
        
temp_vect = np.ones(v_cvxvar .shape[0])
eval('(  1.0 / (1.0 - (mat_bin @  v_cvxvar  ))) @ temp_vect.T')

• mat_bin is a matrix with dimension (5,3).
• v_cvxvar is a vector with dimension (3,1) (not clear to me if it's a column or row vector)
• mat_bin @ v_cvxvar is a new vector (5,1)
• ( 1.0 / (1.0 - (mat_bin @ v_cvxvar ))) is still a (5,1) vector
• temp_vect.T should be a (1,3) vector

What am I missing? Thank you