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Summary: Fix recent flake complaints

Reviewed By: MichaelRamamonjisoa

Differential Revision: D51811912

fbshipit-source-id: 65183f5bc7058da910e4d5a63b2250ce8637f1cc
This commit is contained in:
Jeremy Reizenstein
2023-12-04 13:43:34 -08:00
committed by Facebook GitHub Bot
parent f74fc450e8
commit 83bacda8fb
20 changed files with 73 additions and 85 deletions
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11
tests/implicitron/models/test_utils.py
View File

@@ -15,15 +15,14 @@ from pytorch3d.implicitron.models.utils import preprocess_input, weighted_sum_lo
class TestUtils(unittest.TestCase):
def test_prepare_inputs_wrong_num_dim(self):
img = torch.randn(3, 3, 3)
with self.assertRaises(ValueError) as context:
text = (
"Model received unbatched inputs. "
+ "Perhaps they came from a FrameData which had not been collated."
)
with self.assertRaisesRegex(ValueError, text):
img, fg_prob, depth_map = preprocess_input(
img, None, None, True, True, 0.5, (0.0, 0.0, 0.0)
)
self.assertEqual(
"Model received unbatched inputs. "
+ "Perhaps they came from a FrameData which had not been collated.",
context.exception,
)
def test_prepare_inputs_mask_image_true(self):
batch, channels, height, width = 2, 3, 10, 10

5
tests/implicitron/test_frame_data_builder.py
View File

@@ -224,6 +224,7 @@ class TestFrameDataBuilder(TestCaseMixin, unittest.TestCase):
def test_load_mask(self):
path = os.path.join(self.dataset_root, self.frame_annotation.mask.path)
path = self.path_manager.get_local_path(path)
mask = load_mask(path)
self.assertEqual(mask.dtype, np.float32)
self.assertLessEqual(np.max(mask), 1.0)
@@ -231,12 +232,14 @@ class TestFrameDataBuilder(TestCaseMixin, unittest.TestCase):
def test_load_depth(self):
path = os.path.join(self.dataset_root, self.frame_annotation.depth.path)
path = self.path_manager.get_local_path(path)
depth_map = load_depth(path, self.frame_annotation.depth.scale_adjustment)
self.assertEqual(depth_map.dtype, np.float32)
self.assertEqual(len(depth_map.shape), 3)
def test_load_16big_png_depth(self):
path = os.path.join(self.dataset_root, self.frame_annotation.depth.path)
path = self.path_manager.get_local_path(path)
depth_map = load_16big_png_depth(path)
self.assertEqual(depth_map.dtype, np.float32)
self.assertEqual(len(depth_map.shape), 2)
@@ -245,6 +248,7 @@ class TestFrameDataBuilder(TestCaseMixin, unittest.TestCase):
mask_path = os.path.join(
self.dataset_root, self.frame_annotation.depth.mask_path
)
mask_path = self.path_manager.get_local_path(mask_path)
mask = load_1bit_png_mask(mask_path)
self.assertEqual(mask.dtype, np.float32)
self.assertEqual(len(mask.shape), 2)
@@ -253,6 +257,7 @@ class TestFrameDataBuilder(TestCaseMixin, unittest.TestCase):
mask_path = os.path.join(
self.dataset_root, self.frame_annotation.depth.mask_path
)
mask_path = self.path_manager.get_local_path(mask_path)
mask = load_depth_mask(mask_path)
self.assertEqual(mask.dtype, np.float32)
self.assertEqual(len(mask.shape), 3)

45
tests/implicitron/test_models_renderer_base.py
View File

@@ -38,22 +38,23 @@ class TestRendererBase(TestCaseMixin, unittest.TestCase):
def test_implicitron_raise_value_error_bins_is_set_and_try_to_set_lengths(
self,
) -> None:
with self.assertRaises(ValueError) as context:
ray_bundle = ImplicitronRayBundle(
origins=torch.rand(2, 3, 4, 3),
directions=torch.rand(2, 3, 4, 3),
lengths=None,
xys=torch.rand(2, 3, 4, 2),
bins=torch.rand(2, 3, 4, 1),
)
ray_bundle = ImplicitronRayBundle(
origins=torch.rand(2, 3, 4, 3),
directions=torch.rand(2, 3, 4, 3),
lengths=None,
xys=torch.rand(2, 3, 4, 2),
bins=torch.rand(2, 3, 4, 14),
)
with self.assertRaisesRegex(
ValueError,
"If the bins attribute is not None you cannot set the lengths attribute.",
):
ray_bundle.lengths = torch.empty(2)
self.assertEqual(
str(context.exception),
"If the bins attribute is not None you cannot set the lengths attribute.",
)
def test_implicitron_raise_value_error_if_bins_dim_equal_1(self) -> None:
with self.assertRaises(ValueError) as context:
with self.assertRaisesRegex(
ValueError, "The last dim of bins must be at least superior or equal to 2."
):
ImplicitronRayBundle(
origins=torch.rand(2, 3, 4, 3),
directions=torch.rand(2, 3, 4, 3),
@@ -61,15 +62,14 @@ class TestRendererBase(TestCaseMixin, unittest.TestCase):
xys=torch.rand(2, 3, 4, 2),
bins=torch.rand(2, 3, 4, 1),
)
self.assertEqual(
str(context.exception),
"The last dim of bins must be at least superior or equal to 2.",
)
def test_implicitron_raise_value_error_if_neither_bins_or_lengths_provided(
self,
) -> None:
with self.assertRaises(ValueError) as context:
with self.assertRaisesRegex(
ValueError,
"Please set either bins or lengths to initialize an ImplicitronRayBundle.",
):
ImplicitronRayBundle(
origins=torch.rand(2, 3, 4, 3),
directions=torch.rand(2, 3, 4, 3),
@@ -77,10 +77,6 @@ class TestRendererBase(TestCaseMixin, unittest.TestCase):
xys=torch.rand(2, 3, 4, 2),
bins=None,
)
self.assertEqual(
str(context.exception),
"Please set either bins or lengths to initialize an ImplicitronRayBundle.",
)
def test_conical_frustum_to_gaussian(self) -> None:
origins = torch.zeros(3, 3, 3)
@@ -266,8 +262,6 @@ class TestRendererBase(TestCaseMixin, unittest.TestCase):
ray = ImplicitronRayBundle(
origins=origins, directions=directions, lengths=lengths, xys=None
)
with self.assertRaises(ValueError) as context:
_ = conical_frustum_to_gaussian(ray)
expected_error_message = (
"RayBundle pixel_radii_2d or bins have not been provided."
@@ -276,7 +270,8 @@ class TestRendererBase(TestCaseMixin, unittest.TestCase):
"`cast_ray_bundle_as_cone` to True?"
)
self.assertEqual(expected_error_message, str(context.exception))
with self.assertRaisesRegex(ValueError, expected_error_message):
_ = conical_frustum_to_gaussian(ray)
# Ensure message is coherent with AbstractMaskRaySampler
class FakeRaySampler(AbstractMaskRaySampler):