def test_moa_numba_reduce(benchmark):
n = 1000
m = 1000
expression = LazyArray(name='A', shape=('n', 'm')).reduce('+')
local_dict = {}
exec(expression.compile(backend='python', use_numba=True), globals(),
local_dict)
A = numpy.random.random((n, m))
benchmark(local_dict['f'], A)
def test_moa_numba_outer_product(benchmark):
n = 100
m = 100
expression = LazyArray(name='A', shape=('n', 'm')).outer(
'*', LazyArray(name='B', shape=('n', 'm')))
local_dict = {}
exec(expression.compile(backend='python', use_numba=True), globals(),
local_dict)
A = numpy.random.random((n, m))
B = numpy.random.random((n, m))
benchmark(local_dict['f'], A, B)
def test_moa_numba_double_addition(benchmark):
n = 1000
m = 1000
expression = LazyArray(name='A', shape=('n', 'm')) + LazyArray(
name='B', shape=('n', 'm')) + LazyArray(name='C', shape=('n', 'm'))
local_dict = {}
exec(expression.compile(backend='python', use_numba=True), globals(),
local_dict)
A = numpy.random.random((n, m))
B = numpy.random.random((n, m))
C = numpy.random.random((n, m))
benchmark(local_dict['f'], A=A, B=B, C=C)
