Using Matrix operation within pm_Model not working

Questions v5
3

This code should show the issue.

import numpy as np
import pymc as pm
import matplotlib.pyplot as plt
import arviz as az

n_changepoints = 2

t = np.arange(50) / 50
s = np.linspace(0,max(t),n_changepoints+2)[1:-1]

#indicator matrix 
A = (t[:, None] > s) *1.0

k_det = 1
m_det = 0
delta_det = [-2.0, 1.]
gamma_det = delta_det * -s

g_det = (k_det + A@delta_det)
o_det = (m_det + A@gamma_det)


trend_det = g_det*t+o_det
trend_rnd = trend_det +  np.random.normal(0, 0.02, trend_det.size)
trend_rnd = (trend_rnd - np.mean(trend_rnd))/np.std(trend_rnd)
plt.plot(trend_rnd)

with pm.Model() as ts_model:
    #the initial growth and innteresection is k and m respectively  
    k = pm.Normal('k', mu=0, sigma=1)
    m = pm.Normal('m', mu=0, sigma=1)
    # after each change point  the growth rate  may change with delta 
    delta = pm.Laplace('delta', mu=0, b=0.01, shape=n_changepoints)
    # reflect the slope with new intersections
    gamma = delta * -s

    growth = k + pm.math.dot(A, delta)
    offset = m + pm.math.dot(A, gamma)
    
    trend = growth * t + offset

    error = pm.HalfCauchy('sigma', beta=0.5)
    pm.Normal('observation', mu=trend, sigma=error, observed=trend_rnd)
    idata = pm.sample(tune=1000)

az.plot_trace(idata,combined=True)
az.plot_forest(idata,combined=True)