Mean of likelihood function for Bayesian regression

Questions
2

Something along these lines maybe?

import pymc3 as pm
import theano.tensor as tt

my_data = [1,2,3,4,5]

with pm.Model() as model:
    s1 = pm.Normal('summand1', mu=0, sigma=1)
    s2 = pm.Normal('summand2', mu=0, sigma=1)
    s3 = pm.Normal('summand3', mu=0, sigma=1)
    s4 = pm.Normal('summand4', mu=0, sigma=1)
    s5 = pm.Normal('summand5', mu=0, sigma=1)
    my_sum = pm.Deterministic('my_sum', s1+s2+s3+s4+s5)
    likelihood = pm.Normal('likelihood',
                           mu=my_sum,
                           sigma=1,
                           observed=my_data)
    trace = pm.sample()

Or, more compactly:

with pm.Model() as model:
    summands = pm.Normal('summands', mu=0, sigma=1, shape=5)
    my_sum = pm.Deterministic('my_sum', tt.sum(summands))
    likelihood = pm.Normal('likelihood',
                           mu=my_sum,
                           sigma=1,
                           observed=my_data
    trace = pm.sample()
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