Files
pytorch/test/test_opaque_obj.py
2025-09-22 20:02:29 +00:00

89 lines
2.7 KiB
Python

# Owner(s): ["module: custom-operators"]
import torch
from torch._dynamo.test_case import run_tests, TestCase
from torch._library.opaque_object import get_payload, make_opaque, set_payload
class OpaqueQueue:
def __init__(self, queue: list[torch.Tensor], init_tensor_: torch.Tensor) -> None:
super().__init__()
self.queue = queue
self.init_tensor_ = init_tensor_
def push(self, tensor: torch.Tensor) -> None:
self.queue.append(tensor)
def pop(self) -> torch.Tensor:
if len(self.queue) > 0:
return self.queue.pop(0)
return self.init_tensor_
def size(self) -> int:
return len(self.queue)
class TestOpaqueObject(TestCase):
def setUp(self):
self.lib = torch.library.Library("_TestOpaqueObject", "FRAGMENT") # noqa: TOR901
torch.library.define(
"_TestOpaqueObject::queue_push",
"(__torch__.torch.classes.aten.OpaqueObject a, Tensor b) -> ()",
tags=torch.Tag.pt2_compliant_tag,
lib=self.lib,
)
@torch.library.impl(
"_TestOpaqueObject::queue_push", "CompositeExplicitAutograd", lib=self.lib
)
def push_impl(q: torch._C.ScriptObject, b: torch.Tensor) -> None:
queue = get_payload(q)
assert isinstance(queue, OpaqueQueue)
queue.push(b)
self.lib.define(
"queue_pop(__torch__.torch.classes.aten.OpaqueObject a) -> Tensor",
)
def pop_impl(q: torch._C.ScriptObject) -> torch.Tensor:
queue = get_payload(q)
assert isinstance(queue, OpaqueQueue)
return queue.pop()
self.lib.impl("queue_pop", pop_impl, "CompositeExplicitAutograd")
super().setUp()
def tearDown(self):
self.lib._destroy()
super().tearDown()
def test_creation(self):
queue = OpaqueQueue([], torch.zeros(3))
obj = make_opaque(queue)
self.assertTrue(isinstance(obj, torch._C.ScriptObject))
self.assertEqual(str(obj._type()), "__torch__.torch.classes.aten.OpaqueObject")
# obj.payload stores a direct reference to this python queue object
payload = get_payload(obj)
self.assertEqual(payload, queue)
queue.push(torch.ones(3))
self.assertEqual(payload.size(), 1)
def test_ops(self):
queue = OpaqueQueue([], torch.zeros(3))
obj = make_opaque()
set_payload(obj, queue)
torch.ops._TestOpaqueObject.queue_push(obj, torch.ones(3) + 1)
self.assertEqual(queue.size(), 1)
popped = torch.ops._TestOpaqueObject.queue_pop(obj)
self.assertEqual(popped, torch.ones(3) + 1)
self.assertEqual(queue.size(), 0)
if __name__ == "__main__":
run_tests()