Excessively slow evaluation?

Questions
3

Here is the performance with the compiled only once func:

import theano
import theano.tensor as tt

import pymc3 as pm
import numpy as np
import matplotlib.pyplot as plt
import time

def my_func(x, θ):
    return pm.math.exp(-θ * x)

def compile_my_func():
    x = tt.vector()
    θ = tt.scalar()
    result = my_func(x, θ)
    return theano.function([x, θ], result)

# faux posterior samples
n_samples = 1000
θ = np.random.randn(n_samples)

xi = np.linspace(-1, 2, 100)

# how long to evaluate the function 100 times? ----------------------
start = time.time()
for i in np.random.choice(n_samples, 100, replace=False):
    my_func(xi, θ[i]).eval()
end = time.time()
print(end - start)  # 5 seconds on Colab

# how long to evaluate the function 100 times? ----------------------
start = time.time()
my_func_compiled = compile_my_func()
for i in np.random.choice(n_samples, 100, replace=False):
    my_func_compiled(xi, θ[i])
end = time.time()
print(end - start)  # 0.03 seconds on Colab
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