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Merged
pmeier merged 13 commits into from
Sep 28, 2022
+151 −36
Merged

diversify parameter types for a couple of prototype kernels #6635

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f550c4f
add more size types for prototype resize sample inputs
pmeier Sep 23, 2022
13c3753
add skip for dispatcher
pmeier Sep 23, 2022
a0a0fe8
Merge branch 'main' into resize-test
pmeier Sep 26, 2022
484f907
add more sizes to resize kernel info
pmeier Sep 26, 2022
5989320
add more skips
pmeier Sep 26, 2022
65317ed
add more diversity to gaussian_blur parameters
pmeier Sep 27, 2022
d905da2
diversify affine parameters and fix bounding box kernel
pmeier Sep 27, 2022
fe8e1bf
fix center_crop dispatcher info
pmeier Sep 27, 2022
0dafca0
Merge branch 'main' into resize-test
pmeier Sep 28, 2022
6dfc965
revert kernel fixes
pmeier Sep 28, 2022
27f5c23
add skips for scalar shears in affine_bounding_box
pmeier Sep 28, 2022
fde75e2
Merge branch 'main' into resize-test
pmeier Sep 28, 2022
69ffbc9
Merge branch 'resize-test' of https://github.com/pmeier/vision into r…
pmeier Sep 28, 2022
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55 changes: 39 additions & 16 deletions test/prototype_transforms_dispatcher_infos.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import dataclasses
from typing import Callable, Dict, Sequence, Type
from collections import defaultdict
from typing import Callable, Dict, List, Sequence, Type

import pytest
import torchvision.prototype.transforms.functional as F
Expand All @@ -11,15 +12,30 @@
KERNEL_SAMPLE_INPUTS_FN_MAP = {info.kernel: info.sample_inputs_fn for info in KERNEL_INFOS}


def skip_python_scalar_arg_jit(name, *, reason="Python scalar int or float is not supported when scripting"):
return Skip(
"test_scripted_smoke",
condition=lambda args_kwargs, device: isinstance(args_kwargs.kwargs[name], (int, float)),
reason=reason,
)


def skip_integer_size_jit(name="size"):
return skip_python_scalar_arg_jit(name, reason="Integer size is not supported when scripting.")


@dataclasses.dataclass
class DispatcherInfo:
dispatcher: Callable
kernels: Dict[Type, Callable]
skips: Sequence[Skip] = dataclasses.field(default_factory=list)
_skips_map: Dict[str, Skip] = dataclasses.field(default=None, init=False)
_skips_map: Dict[str, List[Skip]] = dataclasses.field(default=None, init=False)

def __post_init__(self):
self._skips_map = {skip.test_name: skip for skip in self.skips}
skips_map = defaultdict(list)
for skip in self.skips:
skips_map[skip.test_name].append(skip)
self._skips_map = dict(skips_map)

def sample_inputs(self, *types):
for type in types or self.kernels.keys():
Expand All @@ -29,9 +45,13 @@ def sample_inputs(self, *types):
yield from KERNEL_SAMPLE_INPUTS_FN_MAP[self.kernels[type]]()

def maybe_skip(self, *, test_name, args_kwargs, device):
skip = self._skips_map.get(test_name)
if skip and skip.condition(args_kwargs, device):
pytest.skip(skip.reason)
skips = self._skips_map.get(test_name)
if not skips:
return

for skip in skips:
if skip.condition(args_kwargs, device):
pytest.skip(skip.reason)


DISPATCHER_INFOS = [
Expand All @@ -50,6 +70,9 @@ def maybe_skip(self, *, test_name, args_kwargs, device):
features.BoundingBox: F.resize_bounding_box,
features.Mask: F.resize_mask,
},
skips=[
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@pmeier pmeier Sep 23, 2022

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These skips currently don't do anything since we don't have integer sizes, but will be necessary as soon that happens.

skip_integer_size_jit(),
],
),
DispatcherInfo(
F.affine,
Expand All @@ -58,6 +81,7 @@ def maybe_skip(self, *, test_name, args_kwargs, device):
features.BoundingBox: F.affine_bounding_box,
features.Mask: F.affine_mask,
},
skips=[skip_python_scalar_arg_jit("shear", reason="Scalar shear is not supported by JIT")],
),
DispatcherInfo(
F.vertical_flip,
Expand Down Expand Up @@ -122,12 +146,19 @@ def maybe_skip(self, *, test_name, args_kwargs, device):
features.BoundingBox: F.center_crop_bounding_box,
features.Mask: F.center_crop_mask,
},
skips=[
skip_integer_size_jit("output_size"),
],
),
DispatcherInfo(
F.gaussian_blur,
kernels={
features.Image: F.gaussian_blur_image_tensor,
},
skips=[
skip_python_scalar_arg_jit("kernel_size"),
skip_python_scalar_arg_jit("sigma"),
],
),
DispatcherInfo(
F.equalize,
Expand Down Expand Up @@ -207,11 +238,7 @@ def maybe_skip(self, *, test_name, args_kwargs, device):
features.Image: F.five_crop_image_tensor,
},
skips=[
Skip(
"test_scripted_smoke",
condition=lambda args_kwargs, device: isinstance(args_kwargs.kwargs["size"], int),
reason="Integer size is not supported when scripting five_crop_image_tensor.",
),
skip_integer_size_jit(),
],
),
DispatcherInfo(
Expand All @@ -220,11 +247,7 @@ def maybe_skip(self, *, test_name, args_kwargs, device):
features.Image: F.ten_crop_image_tensor,
},
skips=[
Skip(
"test_scripted_smoke",
condition=lambda args_kwargs, device: isinstance(args_kwargs.kwargs["size"], int),
reason="Integer size is not supported when scripting ten_crop_image_tensor.",
),
skip_integer_size_jit(),
],
),
DispatcherInfo(
Expand Down
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