mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-21 05:34:18 +08:00
806010b75e
Summary: Relate to https://github.com/pytorch/pytorch/issues/50483. Everything except ONNX, detectron and release notes tests are moved to use common_utils.run_tests() to ensure CI reports XML correctly. Pull Request resolved: https://github.com/pytorch/pytorch/pull/50923 Reviewed By: samestep Differential Revision: D26027621 Pulled By: walterddr fbshipit-source-id: b04c03f10d1fe96181b720c4c3868e86e4c6281a
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
import os.path
|
|
import tempfile
|
|
|
|
import torch
|
|
from torch import ops
|
|
|
|
from model import Model, get_custom_op_library_path
|
|
from torch.testing._internal.common_utils import TestCase, run_tests
|
|
|
|
|
|
class TestCustomOperators(TestCase):
|
|
def setUp(self):
|
|
self.library_path = get_custom_op_library_path()
|
|
ops.load_library(self.library_path)
|
|
|
|
def test_custom_library_is_loaded(self):
|
|
self.assertIn(self.library_path, ops.loaded_libraries)
|
|
|
|
def test_calling_custom_op_string(self):
|
|
output = ops.custom.op2("abc", "def")
|
|
self.assertLess(output, 0)
|
|
output = ops.custom.op2("abc", "abc")
|
|
self.assertEqual(output, 0)
|
|
|
|
def test_calling_custom_op(self):
|
|
output = ops.custom.op(torch.ones(5), 2.0, 3)
|
|
self.assertEqual(type(output), list)
|
|
self.assertEqual(len(output), 3)
|
|
for tensor in output:
|
|
self.assertTrue(tensor.allclose(torch.ones(5) * 2))
|
|
|
|
output = ops.custom.op_with_defaults(torch.ones(5))
|
|
self.assertEqual(type(output), list)
|
|
self.assertEqual(len(output), 1)
|
|
self.assertTrue(output[0].allclose(torch.ones(5)))
|
|
|
|
def test_calling_custom_op_with_autograd(self):
|
|
x = torch.randn((5, 5), requires_grad=True)
|
|
y = torch.randn((5, 5), requires_grad=True)
|
|
output = ops.custom.op_with_autograd(x, 2, y)
|
|
self.assertTrue(output.allclose(x + 2 * y + x * y))
|
|
|
|
go = torch.ones((), requires_grad=True)
|
|
output.sum().backward(go, False, True)
|
|
grad = torch.ones(5, 5)
|
|
|
|
self.assertTrue(torch.allclose(x.grad, y + grad))
|
|
self.assertTrue(torch.allclose(y.grad, x + grad * 2))
|
|
|
|
# Test with optional arg.
|
|
x.grad.zero_()
|
|
y.grad.zero_()
|
|
z = torch.randn((5, 5), requires_grad=True)
|
|
output = ops.custom.op_with_autograd(x, 2, y, z)
|
|
self.assertTrue(output.allclose(x + 2 * y + x * y + z))
|
|
|
|
go = torch.ones((), requires_grad=True)
|
|
output.sum().backward(go, False, True)
|
|
self.assertTrue(torch.allclose(x.grad, y + grad))
|
|
self.assertTrue(torch.allclose(y.grad, x + grad * 2))
|
|
self.assertTrue(torch.allclose(z.grad, grad))
|
|
|
|
def test_calling_custom_op_with_autograd_in_nograd_mode(self):
|
|
with torch.no_grad():
|
|
x = torch.randn((5, 5), requires_grad=True)
|
|
y = torch.randn((5, 5), requires_grad=True)
|
|
output = ops.custom.op_with_autograd(x, 2, y)
|
|
self.assertTrue(output.allclose(x + 2 * y + x * y))
|
|
|
|
def test_calling_custom_op_inside_script_module(self):
|
|
model = Model()
|
|
output = model.forward(torch.ones(5))
|
|
self.assertTrue(output.allclose(torch.ones(5) + 1))
|
|
|
|
def test_saving_and_loading_script_module_with_custom_op(self):
|
|
model = Model()
|
|
# Ideally we would like to not have to manually delete the file, but NamedTemporaryFile
|
|
# opens the file, and it cannot be opened multiple times in Windows. To support Windows,
|
|
# close the file after creation and try to remove it manually.
|
|
file = tempfile.NamedTemporaryFile(delete=False)
|
|
try:
|
|
file.close()
|
|
model.save(file.name)
|
|
loaded = torch.jit.load(file.name)
|
|
finally:
|
|
os.unlink(file.name)
|
|
|
|
output = loaded.forward(torch.ones(5))
|
|
self.assertTrue(output.allclose(torch.ones(5) + 1))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
run_tests()
|