def test_no_args():
adobj = AD(lambda x: x)
with pytest.raises(TypeError):
adobj._forward()
def test_self_m():
adobj = AD(lambda x, y: x**2 + y + y)
adobj._forward(0, 0)
assert adobj.m == 1
def test_set_seed_wrong_dim():
adobj = AD(lambda x: x + 5)
adobj.set_seed([2, 1])
with pytest.raises(ValueError):
adobj._forward(3)
def test_self_n():
adobj = AD(lambda x, y: x + y)
adobj._forward(1, 2)
assert adobj.n == 2
def my_sum(a):
return a.sum()
ad_object = AD(my_sum)
# showcase reverse better than forward when inputs increase
fwd_times = []
rev_times = []
ninputs = range(1, 10000, 100)
for n in range(1, 10000, 100):
inp = np.array([i for i in range(n)])
start_time = time.time()
ad_object._forward(inp)
runtime = time.time() - start_time
fwd_times.append(runtime)
start_time = time.time()
ad_object._reverse(inp)
runtime = time.time() - start_time
rev_times.append(runtime)
# plot results
plt.plot(ninputs, fwd_times, label='forward')
plt.plot(ninputs, rev_times, label='backward')
plt.legend()
plt.title('Comparing times under different AD modes')
plt.xlabel('Number of inputs')
plt.ylabel('Elapsed time in seconds')