Add seeds on Kernel Info and reduce randomness for Gaussian Blur (#6741)

* Add seeds on Kernel Info and reduce randomness for Gaussian Blur

* Fix linter

test/prototype_transforms_kernel_infos.py

@@ -49,12 +49,14 @@ class KernelInfo(InfoBase):
         test_marks=None,
         # See InfoBase
         closeness_kwargs=None,
+        seed=None,
     ):
         super().__init__(id=kernel_name or kernel.__name__, test_marks=test_marks, closeness_kwargs=closeness_kwargs)
         self.kernel = kernel
         self.sample_inputs_fn = sample_inputs_fn
         self.reference_fn = reference_fn
         self.reference_inputs_fn = reference_inputs_fn
+        self.seed = seed
 
 
 DEFAULT_IMAGE_CLOSENESS_KWARGS = dict(
@@ -1304,7 +1306,7 @@ KERNEL_INFOS.extend(
 
 def sample_inputs_gaussian_blur_image_tensor():
     make_gaussian_blur_image_loaders = functools.partial(
-        make_image_loaders, sizes=["random"], color_spaces=[features.ColorSpace.RGB]
+        make_image_loaders, sizes=[(7, 33)], color_spaces=[features.ColorSpace.RGB]
     )
 
     for image_loader, kernel_size in itertools.product(make_gaussian_blur_image_loaders(), [5, (3, 3), [3, 3]]):
@@ -1317,7 +1319,7 @@ def sample_inputs_gaussian_blur_image_tensor():
 
 
 def sample_inputs_gaussian_blur_video():
-    for video_loader in make_video_loaders(sizes=["random"], num_frames=["random"]):
+    for video_loader in make_video_loaders(sizes=[(7, 33)], num_frames=[5]):
         yield ArgsKwargs(video_loader, kernel_size=[3, 3])
 
 
@@ -1331,10 +1333,13 @@ KERNEL_INFOS.extend(
                 xfail_jit_python_scalar_arg("kernel_size"),
                 xfail_jit_python_scalar_arg("sigma"),
             ],
+            seed=0,
         ),
         KernelInfo(
             F.gaussian_blur_video,
             sample_inputs_fn=sample_inputs_gaussian_blur_video,
+            closeness_kwargs=DEFAULT_IMAGE_CLOSENESS_KWARGS,
+            seed=0,
         ),
     ]
 )

test/test_prototype_transforms_functional.py

@@ -6,7 +6,7 @@ import PIL.Image
 import pytest
 
 import torch
-from common_utils import cache, cpu_and_gpu, needs_cuda
+from common_utils import cache, cpu_and_gpu, needs_cuda, set_rng_seed
 from prototype_common_utils import assert_close, make_bounding_boxes, make_image
 from prototype_transforms_dispatcher_infos import DISPATCHER_INFOS
 from prototype_transforms_kernel_infos import KERNEL_INFOS
@@ -81,6 +81,8 @@ class TestKernels:
     @sample_inputs
     @pytest.mark.parametrize("device", cpu_and_gpu())
     def test_scripted_vs_eager(self, info, args_kwargs, device):
+        if info.seed is not None:
+            set_rng_seed(info.seed)
         kernel_eager = info.kernel
         kernel_scripted = script(kernel_eager)
 
@@ -111,6 +113,8 @@ class TestKernels:
     @sample_inputs
     @pytest.mark.parametrize("device", cpu_and_gpu())
     def test_batched_vs_single(self, info, args_kwargs, device):
+        if info.seed is not None:
+            set_rng_seed(info.seed)
         (batched_input, *other_args), kwargs = args_kwargs.load(device)
 
         feature_type = features.Image if features.is_simple_tensor(batched_input) else type(batched_input)
@@ -146,6 +150,8 @@ class TestKernels:
     @sample_inputs
     @pytest.mark.parametrize("device", cpu_and_gpu())
     def test_no_inplace(self, info, args_kwargs, device):
+        if info.seed is not None:
+            set_rng_seed(info.seed)
         (input, *other_args), kwargs = args_kwargs.load(device)
 
         if input.numel() == 0:
@@ -159,6 +165,8 @@ class TestKernels:
     @sample_inputs
     @needs_cuda
     def test_cuda_vs_cpu(self, info, args_kwargs):
+        if info.seed is not None:
+            set_rng_seed(info.seed)
         (input_cpu, *other_args), kwargs = args_kwargs.load("cpu")
         input_cuda = input_cpu.to("cuda")
 
@@ -170,6 +178,8 @@ class TestKernels:
     @sample_inputs
     @pytest.mark.parametrize("device", cpu_and_gpu())
     def test_dtype_and_device_consistency(self, info, args_kwargs, device):
+        if info.seed is not None:
+            set_rng_seed(info.seed)
         (input, *other_args), kwargs = args_kwargs.load(device)
 
         output = info.kernel(input, *other_args, **kwargs)
@@ -182,6 +192,8 @@ class TestKernels:
 
     @reference_inputs
     def test_against_reference(self, info, args_kwargs):
+        if info.seed is not None:
+            set_rng_seed(info.seed)
         args, kwargs = args_kwargs.load("cpu")
 
         actual = info.kernel(*args, **kwargs)