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cuda 11 problems with test_normal_consistency

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Summary:
One test hits problems with CUDA 11.1 and pytorch 1.8. This seems to be a known bug, so we just run that test on the cpu in the problematic cases.

Note - the full test run is much slower with cuda 11.1 than 10.2, but this is known.

Reviewed By: patricklabatut

Differential Revision: D28938933

fbshipit-source-id: cf8ed84cd10a0b52d8f4292edbef7bd4844fea65
This commit is contained in:
Jeremy Reizenstein 2021-06-08 02:51:12 -07:00 committed by Facebook GitHub Bot
parent c710d8c101
commit 7204a4ca64
1 changed files with 15 additions and 1 deletions
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16
tests/test_mesh_normal_consistency.py
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@ -9,6 +9,17 @@ from pytorch3d.structures.meshes import Meshes
from pytorch3d.utils.ico_sphere import ico_sphere
IS_TORCH_1_8 = torch.__version__.startswith("1.8.")
PROBLEMATIC_CUDA = torch.version.cuda in ("11.0", "11.1")
# TODO: There are problems with cuda 11.0 and 11.1 here.
# The symptom can be
# RuntimeError: radix_sort: failed on 1st step: cudaErrorInvalidDevice: invalid device ordinal
# or something like
# operator(): block: [0,0,0], thread: [96,0,0]
# Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
AVOID_LARGE_MESH_CUDA = PROBLEMATIC_CUDA and IS_TORCH_1_8
class TestMeshNormalConsistency(unittest.TestCase):
def setUp(self) -> None:
torch.manual_seed(42)
@ -37,7 +48,10 @@ class TestMeshNormalConsistency(unittest.TestCase):
@staticmethod
def init_meshes(num_meshes: int = 10, num_verts: int = 1000, num_faces: int = 3000):
device = torch.device("cuda:0")
if AVOID_LARGE_MESH_CUDA:
device = torch.device("cpu")
else:
device = torch.device("cuda:0")
valid_faces = TestMeshNormalConsistency.init_faces(num_verts).to(device)
verts_list = []
faces_list = []