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6033 keep the gradient in sliding window utility when possible #6034

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Merged
wyli merged 3 commits into from
Feb 21, 2023
Merged

6033 keep the gradient in sliding window utility when possible #6034

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c35ad20
differentiable sliding window utility
wyli Feb 21, 2023
59aef40
skip quick tests
wyli Feb 21, 2023
2bbf3a2
skip warp if quick tests
wyli Feb 21, 2023
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2 changes: 1 addition & 1 deletion monai/inferers/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -262,7 +262,7 @@ def sliding_window_inference(

# account for any overlapping sections
for ss in range(len(output_image_list)):
output_image_list[ss] = output_image_list[ss].detach()
output_image_list[ss] = output_image_list[ss]
_map = count_map_list.pop(0)
for _i in range(output_image_list[ss].shape[1]):
output_image_list[ss][:, _i : _i + 1, ...] /= _map
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4 changes: 3 additions & 1 deletion tests/test_sliding_window_inference.py
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Expand Up @@ -83,10 +83,12 @@ def test_default_device(self, data_type):
def compute(data):
return data + 1

inputs.requires_grad = True
result = sliding_window_inference(inputs, roi_shape, sw_batch_size, compute)
self.assertTrue(result.requires_grad)
np.testing.assert_string_equal(inputs.device.type, result.device.type)
expected_val = np.ones((1, 3, 16, 15, 7), dtype=np.float32) + 1
np.testing.assert_allclose(result.cpu().numpy(), expected_val)
np.testing.assert_allclose(result.detach().cpu().numpy(), expected_val)

@parameterized.expand(list(itertools.product(TEST_TORCH_AND_META_TENSORS, ("cpu", "cuda"), ("cpu", "cuda", None))))
@skip_if_no_cuda
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3 changes: 2 additions & 1 deletion tests/test_vit.py
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Expand Up @@ -18,7 +18,7 @@

from monai.networks import eval_mode
from monai.networks.nets.vit import ViT
from tests.utils import SkipIfBeforePyTorchVersion, test_script_save
from tests.utils import SkipIfBeforePyTorchVersion, skip_if_quick, test_script_save

TEST_CASE_Vit = []
for dropout_rate in [0.6]:
Expand Down Expand Up @@ -59,6 +59,7 @@
TEST_CASE_Vit.append(test_case)


@skip_if_quick
class TestViT(unittest.TestCase):
@parameterized.expand(TEST_CASE_Vit)
def test_shape(self, input_param, input_shape, expected_shape):
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9 changes: 8 additions & 1 deletion tests/test_warp.py
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Expand Up @@ -22,7 +22,13 @@
from monai.networks.blocks.warp import Warp
from monai.transforms import LoadImaged
from monai.utils import GridSampleMode, GridSamplePadMode
from tests.utils import SkipIfBeforePyTorchVersion, SkipIfNoModule, download_url_or_skip_test, testing_data_config
from tests.utils import (
SkipIfBeforePyTorchVersion,
SkipIfNoModule,
download_url_or_skip_test,
skip_if_quick,
testing_data_config,
)

LOW_POWER_TEST_CASES = [ # run with BUILD_MONAI=1 to test csrc/resample, BUILD_MONAI=0 to test native grid_sample
[
Expand Down Expand Up @@ -98,6 +104,7 @@
TEST_CASES += CPP_TEST_CASES


@skip_if_quick
class TestWarp(unittest.TestCase):
def setUp(self):
config = testing_data_config("images", "Prostate_T2W_AX_1")
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