def test_constant_variable():
def before(x):
return Q(15) + Q(x)
def after(x):
return P(15) + Q(x)
Qct_to_P = psub((Q, V), (P, V), name='Qct_to_P')
_check_opt(before, after, Qct_to_P)
specialize = scalar_pipeline \
.configure({
'resources.convert.object_map': Merge({
operations.getitem: prim.tuple_getitem
})
}) \
.select('resources', 'parse', 'resolve', 'infer', 'specialize')
# We will optimize patterns of these fake primitives
P = Primitive('P')
Q = Primitive('Q')
R = Primitive('R')
idempotent_P = psub((P, (P, X)), (P, X), name='idempotent_P')
elim_R = psub((R, X), X, name='elim_R')
Q0_to_R = psub((Q, 0), (R, 0), name='Q0_to_R')
QP_to_QR = psub((Q, (P, X)), (Q, (R, X)), name='QP_to_QR')
multiply_by_zero_l = psub((prim.scalar_mul, 0, X),
0,
name='multiply_by_zero_l')
multiply_by_zero_r = psub((prim.scalar_mul, X, 0),
0,
name='multiply_by_zero_r')
specialize = scalar_pipeline.configure(
{"convert.object_map": Merge({operations.getitem: prim.tuple_getitem})}
).with_steps(steps.step_parse, steps.step_infer, steps.step_specialize)
# We will optimize patterns of these fake primitives
P = Primitive("P")
Q = Primitive("Q")
R = Primitive("R")
idempotent_P = psub((P, (P, X)), (P, X), name="idempotent_P")
elim_R = psub((R, X), X, name="elim_R")
Q0_to_R = psub((Q, 0), (R, 0), name="Q0_to_R")
QP_to_QR = psub((Q, (P, X)), (Q, (R, X)), name="QP_to_QR")
multiply_by_zero_l = psub((prim.scalar_mul, 0, X), 0, name="multiply_by_zero_l")
multiply_by_zero_r = psub((prim.scalar_mul, X, 0), 0, name="multiply_by_zero_r")
add_zero_l = psub((prim.scalar_add, 0, X), X, name="add_zero_l")
add_zero_r = psub((prim.scalar_add, X, 0), X, name="add_zero_r")