def make_nat_value(prelude, n):
"""The inverse of count(): Given a non-negative Python integer,
constructs a ConstructorValue representing that value as a nat.
"""
if n == 0:
return ConstructorValue(prelude.z, [], [])
return ConstructorValue(prelude.s, [make_nat_value(prelude, n - 1)], [])
def make_nat_value(prelude, n):
"""The inverse of count(): Given a non-negative Python integer,
constructs a ConstructorValue representing that value as a nat.
"""
_, z, s = prelude.mod.get_type("nat")
if n == 0:
return ConstructorValue(z.tag, [], z)
return ConstructorValue(s.tag, [make_nat_value(prelude, n - 1)], s)
def test_function_taking_adt_ref_tuple():
mod = tvm.IRModule()
prelude = relay.prelude.Prelude(mod)
intrp = create_executor("debug", mod)
_, cons, nil = prelude.mod.get_type("List")
nil_value = ConstructorValue(nil.tag, [], nil)
cons_value = ConstructorValue(
cons.tag,
[nd.array(np.random.rand(1, 10).astype("float32")), nil_value],
cons,
)
ref_value = RefValue(nd.array(np.random.rand(1, 10).astype("float32")))
tuple_value = container.tuple_object(
[nd.array(np.random.rand(1, 10).astype("float32")) for _ in range(10)])
id_func = intrp.evaluate(prelude.id)
res_nil = id_func(nil_value)
assert res_nil.tag == nil_value.tag
assert len(res_nil.fields) == 0
res_cons = id_func(cons_value)
assert res_cons.tag == cons_value.tag
assert len(res_cons.fields) == len(cons_value.fields)
tvm.testing.assert_allclose(res_cons.fields[0].asnumpy(),
cons_value.fields[0].asnumpy())
assert isinstance(res_cons.fields[1], ConstructorValue)
assert res_cons.fields[1].tag == nil.tag
assert len(res_cons.fields[1].fields) == 0
res_ref = id_func(ref_value)
tvm.testing.assert_allclose(res_ref.value.asnumpy(),
ref_value.value.asnumpy())
res_tuple = id_func(tuple_value)
for i in range(10):
tvm.testing.assert_allclose(res_tuple[i].asnumpy(),
tuple_value[i].asnumpy())
def test_function_taking_adt_ref_tuple():
mod = relay.Module()
prelude = relay.prelude.Prelude(mod)
intrp = create_executor("debug", mod)
nil_value = ConstructorValue(prelude.nil.tag, [], prelude.nil, [])
cons_value = ConstructorValue(
prelude.cons.tag,
[TensorValue(np.random.rand(1, 10).astype('float32')), nil_value],
prelude.cons, [relay.TensorType((1, 10), 'float32')])
ref_value = RefValue(TensorValue(np.random.rand(1, 10).astype('float32')))
tuple_value = TupleValue(*[
TensorValue(np.random.rand(1, 10).astype('float32')) for _ in range(10)
])
id_func = intrp.evaluate(prelude.id)
res_nil = id_func(nil_value)
assert res_nil.tag == nil_value.tag
assert len(res_nil.fields) == 0
res_cons = id_func(cons_value)
assert res_cons.tag == cons_value.tag
assert len(res_cons.fields) == len(cons_value.fields)
tvm.testing.assert_allclose(res_cons.fields[0].asnumpy(),
cons_value.fields[0].asnumpy())
assert isinstance(res_cons.fields[1], ConstructorValue)
assert res_cons.fields[1].tag == prelude.nil.tag
assert len(res_cons.fields[1].fields) == 0
res_ref = id_func(ref_value)
tvm.testing.assert_allclose(res_ref.value.asnumpy(),
ref_value.value.asnumpy())
res_tuple = id_func(tuple_value)
for i in range(10):
tvm.testing.assert_allclose(res_tuple.fields[i].asnumpy(),
tuple_value.fields[i].asnumpy())
def make_nat(n):
if n != 0:
return ConstructorValue(s, [make_nat(n - 1)])
else:
return ConstructorValue(z, [])
def from_tree(p, rt, t):
return ConstructorValue(
p.rose.tag,
[rt.head,
from_list(p, [from_tree(p, x, t) for x in rt.children], t)], None)
def from_list(p, l, t):
if len(l) == 0:
return ConstructorValue(p.nil.tag, [], None)
else:
return ConstructorValue(p.cons.tag,
[l[0], from_list(p, l[1:], t)], None)
def make_nat(p, n):
if n != 0:
return ConstructorValue(p.s.tag, [make_nat(n - 1)], None)
else:
return ConstructorValue(p.z.tag, [], None)
