try unflake CI

Author: pmeier

test/test_transforms_v2_consistency.py

@@ -354,24 +354,34 @@ def __init__(
             v2_transforms.ElasticTransform,
             legacy_transforms.ElasticTransform,
             [
-                ArgsKwargs(),
                 ArgsKwargs(alpha=20.0),
                 ArgsKwargs(alpha=(15.3, 27.2)),
                 ArgsKwargs(sigma=3.0),
                 ArgsKwargs(sigma=(2.5, 3.9)),
                 ArgsKwargs(interpolation=v2_transforms.InterpolationMode.NEAREST),
-                ArgsKwargs(interpolation=v2_transforms.InterpolationMode.BICUBIC),
                 ArgsKwargs(interpolation=PIL.Image.NEAREST),
-                ArgsKwargs(interpolation=PIL.Image.BICUBIC),
                 ArgsKwargs(fill=1),
+                *extra_args_kwargs,
             ],
             # ElasticTransform needs larger images to avoid the needed internal padding being larger than the actual image
             make_images_kwargs=dict(DEFAULT_MAKE_IMAGES_KWARGS, sizes=[(163, 163), (72, 333), (313, 95)], dtypes=[dt]),
             # We updated gaussian blur kernel generation with a faster and numerically more stable version
             # This brings float32 accumulation visible in elastic transform -> we need to relax consistency tolerance
             closeness_kwargs=ckw,
         )
-        for dt, ckw in [(torch.uint8, {"rtol": 1e-1, "atol": 1}), (torch.float32, {"rtol": 1e-2, "atol": 1e-3})]
+        for dt, ckw, extra_args_kwargs in [
+            (torch.uint8, {"rtol": 1e-1, "atol": 1}, []),
+            (
+                torch.float32,
+                {"rtol": 1e-2, "atol": 1e-3},
+                [
+                    # These proved to be flaky on uint8 inputs so we only run them on float32
+                    ArgsKwargs(),
+                    ArgsKwargs(interpolation=v2_transforms.InterpolationMode.BICUBIC),
+                    ArgsKwargs(interpolation=PIL.Image.BICUBIC),
+                ],
+            ),
+        ]
     ],
     ConsistencyConfig(
         v2_transforms.GaussianBlur,

test/transforms_v2_kernel_infos.py

@@ -635,6 +635,9 @@ def sample_inputs_affine_video():
             sample_inputs_fn=sample_inputs_affine_bounding_box,
             reference_fn=reference_affine_bounding_box,
             reference_inputs_fn=reference_inputs_affine_bounding_box,
+            closeness_kwargs={
+                (("TestKernels", "test_against_reference"), torch.int64, "cpu"): {"atol": 1, "rtol": 0},
+            },
             test_marks=[
                 xfail_jit_python_scalar_arg("shear"),
             ],
@@ -1946,13 +1949,15 @@ def sample_inputs_adjust_contrast_video():
                 **float32_vs_uint8_pixel_difference(2),
                 **cuda_vs_cpu_pixel_difference(),
                 (("TestKernels", "test_against_reference"), torch.uint8, "cpu"): pixel_difference_closeness_kwargs(1),
+                (("TestKernels", "test_scripted_vs_eager"), torch.uint8, "cuda"): pixel_difference_closeness_kwargs(1),
             },
         ),
         KernelInfo(
             F.adjust_contrast_video,
             sample_inputs_fn=sample_inputs_adjust_contrast_video,
             closeness_kwargs={
                 **cuda_vs_cpu_pixel_difference(),
+                (("TestKernels", "test_scripted_vs_eager"), torch.uint8, "cuda"): pixel_difference_closeness_kwargs(1),
                 (("TestKernels", "test_against_reference"), torch.uint8, "cpu"): pixel_difference_closeness_kwargs(1),
             },
         ),