numba max reduction is 10x slower than sum on the same array #2367

import time

import numpy as np
import pytensor
import pytensor.tensor as pt

x_np = np.random.default_rng(0).normal(size=(200, 200, 200))
x = pt.tensor("x", shape=x_np.shape)


def bench(fn, *args):
    fn(*args)
    start = time.perf_counter()
    for _ in range(10):
        fn(*args)
    return (time.perf_counter() - start) / 10 * 1000


for name, op in (("max", pt.max), ("sum", pt.sum)):
    print(name, round(bench(pytensor.function([x], op(x), trust_input=True), x_np), 2), "ms")

print("numpy max", round(bench(x_np.max), 2), "ms")
print("numpy sum", round(bench(x_np.sum), 2), "ms")

# max 7.31 ms   sum 0.72 ms   numpy max 0.72 ms   numpy sum 0.96 ms