Error when forming a block matrix in CVXPY

I am trying to solve an optimization problem using CVXPY where I need to form a block matrix as a constraint. The block matrix is given by:

$$M = \begin{bmatrix} Q & \mathbf{b} \ \mathbf{b}^T & 1 \end{bmatrix}$$

where Q is a CVXPY variable representing a symmetric matrix, h is a NumPy array, and 1 is a scalar. I am trying to form this block matrix using the cp.bmat function in CVXPY as follows:

block_matrix = cp.bmat([[Q, h.reshape(-1, 1)], [h, 1]])

However, I am getting the following error:

All the input dimensions except for axis 0 must match exactly.

I have already reshaped h to a column vector using reshape(-1, 1) because CVXPY expects 2D arrays for matrix operations. I am not sure why I am getting this error and how to fix it. Any help would be greatly appreciated.

Here is the complete relevant code for reference:

import cvxpy as cp
import numpy as np

# Define the size of the matrix Q
n = 21

# Define the variables
Q = cp.Variable((n, n), symmetric=True)

# Define the h vector
h = np.array([0.01 * k**2 for k in range(-10, 11)])

# Form the block matrix
block_matrix = cp.bmat([[Q, h.reshape(-1, 1)], [h, 1]])

In case it wasn't obvious enough

# Form the block matrix
block_matrix = cp.bmat([[Q, h.reshape(-1, 1)], [h.reshape(1, -1), np.ones((1,1))]])