test fixes

Summary: Some random seed changes. Skip multigpu tests when there's only one gpu. This is a better fix for what AI is doing in D80600882.

Reviewed By: MichaelRamamonjisoa

Differential Revision: D80625966

fbshipit-source-id: ac3952e7144125fd3a05ad6e4e6e5976ae10a8ef

Author: bottler

dev/linter.sh

@@ -10,7 +10,7 @@
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
 DIR=$(dirname "${DIR}")
 
-if [[ -f "${DIR}/TARGETS" ]]
+if [[ -f "${DIR}/BUCK" ]]
 then
   pyfmt "${DIR}"
 else

setup.py

@@ -134,7 +134,7 @@ def get_extensions():
 
     class BuildExtension(torch.utils.cpp_extension.BuildExtension):
         def __init__(self, *args, **kwargs):
-            super().__init__(use_ninja=False, *args, **kwargs)
+            super().__init__(*args, use_ninja=False, **kwargs)
 
 else:
     BuildExtension = torch.utils.cpp_extension.BuildExtension

tests/common_testing.py

@@ -31,6 +31,13 @@ def skip_opengl_requested() -> bool:
 usesOpengl = unittest.skipIf(skip_opengl_requested(), "uses opengl")
 
 
+def have_multiple_gpus() -> bool:
+    return torch.cuda.device_count() > 1
+
+
+needs_multigpu = unittest.skipIf(not have_multiple_gpus(), "needs multiple GPUs")
+
+
 def get_tests_dir() -> Path:
     """
     Returns Path for the directory containing this file.

tests/test_knn.py

@@ -72,6 +72,7 @@ def _knn_vs_python_square_helper(self, device, return_sorted):
         factors = [Ns, Ds, P1s, P2s, Ks, norms]
         for N, D, P1, P2, K, norm in product(*factors):
             for version in versions:
+                torch.manual_seed(2)
                 if version == 3 and K > 4:
                     continue
                 x = torch.randn(N, P1, D, device=device, requires_grad=True)

tests/test_pointclouds.py

@@ -17,7 +17,7 @@
     Pointclouds,
 )
 
-from .common_testing import TestCaseMixin
+from .common_testing import needs_multigpu, TestCaseMixin
 
 
 class TestPointclouds(TestCaseMixin, unittest.TestCase):
@@ -703,6 +703,7 @@ def test_to(self):
         self.assertEqual(cuda_device, cloud.device)
         self.assertIsNot(cloud, converted_cloud)
 
+    @needs_multigpu
     def test_to_list(self):
         cloud = self.init_cloud(5, 100, 10)
         device = torch.device("cuda:1")
@@ -740,6 +741,7 @@ def test_to_list(self):
         self.assertTrue(cloud._P == new_cloud._P)
         self.assertTrue(cloud._C == new_cloud._C)
 
+    @needs_multigpu
     def test_to_tensor(self):
         cloud = self.init_cloud(5, 100, 10, lists_to_tensors=True)
         device = torch.device("cuda:1")

tests/test_points_alignment.py

@@ -165,7 +165,7 @@ def test_heterogeneous_inputs(self, batch_size=7):
         a set of randomly-sized Pointclouds and on their padded versions.
         """
 
-        torch.manual_seed(4)
+        torch.manual_seed(14)
         device = torch.device("cuda:0")
 
         for estimate_scale in (True, False):

tests/test_render_multigpu.py

@@ -29,7 +29,7 @@
 from pytorch3d.structures import Meshes, Pointclouds
 from pytorch3d.utils.ico_sphere import ico_sphere
 
-from .common_testing import TestCaseMixin, usesOpengl
+from .common_testing import needs_multigpu, TestCaseMixin, usesOpengl
 
 
 # Set the number of GPUS you want to test with
@@ -116,6 +116,7 @@ def _mesh_renderer_to(self, rasterizer_class, shader_class):
         output_images = renderer(mesh)
         self.assertEqual(output_images.device, device2)
 
+    @needs_multigpu
     def test_mesh_renderer_to(self):
         self._mesh_renderer_to(MeshRasterizer, SoftPhongShader)
 
@@ -173,6 +174,7 @@ def forward(self, verts, texs):
         for _ in range(100):
             model(verts, texs)
 
+    @needs_multigpu
     def test_render_meshes(self):
         self._render_meshes(MeshRasterizer, HardGouraudShader)
 

tests/test_rendering_utils.py

@@ -63,9 +63,6 @@ def test_to(self):
         self.assertEqual(example_gpu.device.type, "cuda")
         self.assertIsNotNone(example_gpu.device.index)
 
-        example_gpu1 = example.cuda(1)
-        self.assertEqual(example_gpu1.device, torch.device("cuda:1"))
-
     def test_clone(self):
         # Check clone method
         example = TensorPropertiesTestClass(x=10.0, y=(100.0, 200.0))