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add torch.script tests to convert_image_dtype #2313

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add torch.script tests to convert_image_dtype #2313

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fba59a1
add torch.script tests to convert_image_dtype
pmeier Jun 11, 2020
074e8ce
lint
pmeier Jun 11, 2020
7100a6e
lint
pmeier Jun 11, 2020
06393e4
bug fix
pmeier Jun 12, 2020
df58a27
remove lambda
pmeier Jun 12, 2020
d789cb9
try remove torch.dtype.is_floating_point
pmeier Jun 12, 2020
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23 changes: 23 additions & 0 deletions test/test_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -532,7 +532,13 @@ def test_convert_image_dtype_float_to_float(self):
for output_dtype in output_dtypes:
with self.subTest(input_dtype=input_dtype, output_dtype=output_dtype):
transform = transforms.ConvertImageDtype(output_dtype)
transform_script = torch.jit.script(F.convert_image_dtype)

output_image = transform(input_image)
output_image_script = transform_script(input_image, output_dtype)

script_diff = output_image_script - output_image
self.assertTrue(script_diff.abs().max() < 1e-6)

actual_min, actual_max = output_image.tolist()
desired_min, desired_max = 0.0, 1.0
Expand All @@ -546,6 +552,7 @@ def test_convert_image_dtype_float_to_int(self):
for output_dtype in int_dtypes():
with self.subTest(input_dtype=input_dtype, output_dtype=output_dtype):
transform = transforms.ConvertImageDtype(output_dtype)
transform_script = torch.jit.script(F.convert_image_dtype)

if (input_dtype == torch.float32 and output_dtype in (torch.int32, torch.int64)) or (
input_dtype == torch.float64 and output_dtype == torch.int64
Expand All @@ -554,6 +561,10 @@ def test_convert_image_dtype_float_to_int(self):
transform(input_image)
else:
output_image = transform(input_image)
output_image_script = transform_script(input_image, output_dtype)

script_diff = output_image_script - output_image
self.assertTrue(script_diff.abs().max() < 1e-6)

actual_min, actual_max = output_image.tolist()
desired_min, desired_max = 0, torch.iinfo(output_dtype).max
Expand All @@ -567,7 +578,13 @@ def test_convert_image_dtype_int_to_float(self):
for output_dtype in float_dtypes():
with self.subTest(input_dtype=input_dtype, output_dtype=output_dtype):
transform = transforms.ConvertImageDtype(output_dtype)
transform_script = torch.jit.script(F.convert_image_dtype)

output_image = transform(input_image)
output_image_script = transform_script(input_image, output_dtype)

script_diff = output_image_script - output_image
self.assertTrue(script_diff.abs().max() < 1e-6)

actual_min, actual_max = output_image.tolist()
desired_min, desired_max = 0.0, 1.0
Expand All @@ -586,7 +603,13 @@ def test_convert_image_dtype_int_to_int(self):

with self.subTest(input_dtype=input_dtype, output_dtype=output_dtype):
transform = transforms.ConvertImageDtype(output_dtype)
transform_script = torch.jit.script(F.convert_image_dtype)

output_image = transform(input_image)
output_image_script = transform_script(input_image, output_dtype)

script_diff = output_image_script - output_image
self.assertTrue(script_diff.abs().max() < 1e-6)

actual_min, actual_max = output_image.tolist()
desired_min, desired_max = 0, output_max
Expand Down
14 changes: 11 additions & 3 deletions torchvision/transforms/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,6 +113,11 @@ def pil_to_tensor(pic):
return img


def _is_floating_point(dtype: torch.dtype) -> bool:
# helper function since torch.dtype.is_floating_point is not scriptable
return isinstance(dtype, (torch.float32, torch.float, torch.float64, torch.double))


def convert_image_dtype(image: torch.Tensor, dtype: torch.dtype = torch.float) -> torch.Tensor:
"""Convert a tensor image to the given ``dtype`` and scale the values accordingly

Expand All @@ -137,9 +142,12 @@ def convert_image_dtype(image: torch.Tensor, dtype: torch.dtype = torch.float) -
if image.dtype == dtype:
return image

if image.dtype.is_floating_point:
input_is_float = _is_floating_point(image.dtype)
output_is_float = _is_floating_point(dtype)

if input_is_float:
# float to float
if dtype.is_floating_point:
if output_is_float:
return image.to(dtype)

# float to int
Expand All @@ -153,7 +161,7 @@ def convert_image_dtype(image: torch.Tensor, dtype: torch.dtype = torch.float) -
return image.mul(torch.iinfo(dtype).max + 1 - eps).to(dtype)
else:
# int to float
if dtype.is_floating_point:
if output_is_float:
max = torch.iinfo(image.dtype).max
image = image.to(dtype)
return image / max
Expand Down