Changing utils.py to test_utils.py (Project-MONAI#8335)

Related to Project-MONAI#8185.

### Description

This changes the name of `tests/utils.py` to `tests/test_utils.py` to
conform to the changes introduced with the daily CICD tests. This is
done in Project-MONAI#8231 but the change is being pre-merged now to get tests
working again while issues are sorted out there. This also includes
changes this PR made to that file, and changes anywhere else to
correctly import the module.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: Eric Kerfoot <eric.kerfoot@kcl.ac.uk>
Signed-off-by: Can-Zhao <volcanofly@gmail.com>

Author: ericspod

tests/croppers.py

@@ -20,7 +20,7 @@
 from monai.transforms import Randomizable
 from monai.transforms.lazy.functional import apply_pending
 from monai.transforms.transform import MapTransform
-from tests.utils import TEST_NDARRAYS_ALL, assert_allclose
+from tests.test_utils import TEST_NDARRAYS_ALL, assert_allclose
 
 
 class CropTest(unittest.TestCase):

tests/hvd_evenly_divisible_all_gather.py

@@ -15,7 +15,7 @@
 
 from monai.utils import evenly_divisible_all_gather
 from monai.utils.module import optional_import
-from tests.utils import assert_allclose
+from tests.test_utils import assert_allclose
 
 hvd, has_hvd = optional_import("horovod", name="torch")
 

tests/lazy_transforms_utils.py

@@ -16,7 +16,7 @@
 from monai.data import MetaTensor, set_track_meta
 from monai.transforms import InvertibleTransform, MapTransform, Randomizable
 from monai.transforms.lazy.functional import apply_pending
-from tests.utils import assert_allclose
+from tests.test_utils import assert_allclose
 
 apply_transforms_kwargs = ("pending", "mode", "padding_mode", "dtype", "align_corners")
 

tests/ngc_bundle_download.py

@@ -24,7 +24,7 @@
 from monai.bundle import download, load
 from monai.config import print_debug_info
 from monai.networks.utils import copy_model_state
-from tests.utils import assert_allclose, skip_if_downloading_fails, skip_if_quick, skip_if_windows
+from tests.test_utils import assert_allclose, skip_if_downloading_fails, skip_if_quick, skip_if_windows
 
 TEST_CASE_NGC_1 = [
     "spleen_ct_segmentation",

tests/padders.py

@@ -21,7 +21,7 @@
 from monai.transforms.lazy.functional import apply_pending
 from monai.transforms.transform import MapTransform
 from monai.utils.enums import NumpyPadMode, PytorchPadMode
-from tests.utils import TEST_NDARRAYS_ALL, assert_allclose
+from tests.test_utils import TEST_NDARRAYS_ALL, assert_allclose
 
 MODES = []
 # Test modes

tests/test_activations.py

@@ -18,7 +18,7 @@
 
 from monai.networks.layers.factories import Act
 from monai.transforms import Activations
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 TEST_CASES = []
 for p in TEST_NDARRAYS:

tests/test_activationsd.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import Activationsd
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 TEST_CASES = []
 for p in TEST_NDARRAYS:

tests/test_add_coordinate_channels.py

@@ -18,7 +18,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AddCoordinateChannels
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 TESTS, TEST_CASES_ERROR_1, TEST_CASES_ERROR_2 = [], [], []
 for p in TEST_NDARRAYS:

tests/test_add_coordinate_channelsd.py

@@ -18,7 +18,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AddCoordinateChannelsd
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 TESTS, TEST_CASES_ERROR_1, TEST_CASES_ERROR_2 = [], [], []
 for p in TEST_NDARRAYS:

tests/test_add_extreme_points_channel.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AddExtremePointsChannel
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 IMG_CHANNEL = 3
 TESTS = []

tests/test_add_extreme_points_channeld.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AddExtremePointsChanneld
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 IMG_CHANNEL = 3
 

tests/test_adjust_contrast.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AdjustContrast
-from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
 
 TESTS = []
 for invert_image in (True, False):

tests/test_adjust_contrastd.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AdjustContrastd
-from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
 
 TESTS = []
 for invert_image in (True, False):

tests/test_adn.py

@@ -16,7 +16,7 @@
 from parameterized import parameterized
 
 from monai.networks.blocks import ADN
-from tests.utils import TorchImageTestCase2D, TorchImageTestCase3D
+from tests.test_utils import TorchImageTestCase2D, TorchImageTestCase3D
 
 TEST_CASES_2D = [
     [{"act": None}],

tests/test_affine.py

@@ -23,7 +23,7 @@
 from monai.transforms.lazy.functional import apply_pending
 from monai.utils import optional_import
 from tests.lazy_transforms_utils import test_resampler_lazy
-from tests.utils import TEST_NDARRAYS_ALL, assert_allclose, test_local_inversion
+from tests.test_utils import TEST_NDARRAYS_ALL, assert_allclose, test_local_inversion
 
 TESTS = []
 for p in TEST_NDARRAYS_ALL:

tests/test_affine_grid.py

@@ -19,7 +19,7 @@
 
 from monai.data import MetaTensor, set_track_meta
 from monai.transforms import AffineGrid
-from tests.utils import TEST_NDARRAYS_ALL, assert_allclose, is_tf32_env
+from tests.test_utils import TEST_NDARRAYS_ALL, assert_allclose, is_tf32_env
 
 TESTS = []
 for p in TEST_NDARRAYS_ALL:

tests/test_affine_transform.py

@@ -19,7 +19,7 @@
 
 from monai.networks import normalize_transform, to_norm_affine
 from monai.networks.layers import AffineTransform
-from tests.utils import is_tf32_env
+from tests.test_utils import is_tf32_env
 
 _rtol = 1e-4 if not is_tf32_env() else 5e-3
 

tests/test_affined.py

@@ -20,7 +20,7 @@
 
 from monai.transforms import Affined
 from tests.lazy_transforms_utils import test_resampler_lazy
-from tests.utils import TEST_NDARRAYS_ALL, assert_allclose, test_local_inversion
+from tests.test_utils import TEST_NDARRAYS_ALL, assert_allclose, test_local_inversion
 
 TESTS = []
 for p in TEST_NDARRAYS_ALL:

tests/test_ahnet.py

@@ -19,7 +19,7 @@
 from monai.networks import eval_mode
 from monai.networks.blocks import FCN, MCFCN
 from monai.networks.nets import AHNet
-from tests.utils import skip_if_quick, test_pretrained_networks, test_script_save
+from tests.test_utils import skip_if_quick, test_pretrained_networks, test_script_save
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 

tests/test_anchor_box.py

@@ -18,7 +18,7 @@
 
 from monai.apps.detection.utils.anchor_utils import AnchorGenerator, AnchorGeneratorWithAnchorShape
 from monai.utils import optional_import
-from tests.utils import SkipIfBeforePyTorchVersion, assert_allclose, test_script_save
+from tests.test_utils import SkipIfBeforePyTorchVersion, assert_allclose, test_script_save
 
 _, has_torchvision = optional_import("torchvision")
 

tests/test_apply.py

@@ -19,7 +19,7 @@
 from monai.transforms.lazy.functional import apply_pending
 from monai.transforms.utils import create_rotate
 from monai.utils import LazyAttr, convert_to_tensor
-from tests.utils import get_arange_img
+from tests.test_utils import get_arange_img
 
 
 def single_2d_transform_cases():

tests/test_as_channel_last.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AsChannelLast
-from tests.utils import TEST_NDARRAYS
+from tests.test_utils import TEST_NDARRAYS
 
 TESTS = []
 for p in TEST_NDARRAYS:

tests/test_as_channel_lastd.py

@@ -17,7 +17,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AsChannelLastd
-from tests.utils import TEST_NDARRAYS
+from tests.test_utils import TEST_NDARRAYS
 
 TESTS = []
 for p in TEST_NDARRAYS:

tests/test_as_discrete.py

@@ -16,7 +16,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AsDiscrete
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 TEST_CASES = []
 for p in TEST_NDARRAYS:

tests/test_as_discreted.py

@@ -16,7 +16,7 @@
 from parameterized import parameterized
 
 from monai.transforms import AsDiscreted
-from tests.utils import TEST_NDARRAYS, assert_allclose
+from tests.test_utils import TEST_NDARRAYS, assert_allclose
 
 TEST_CASES = []
 for p in TEST_NDARRAYS:

tests/test_atss_box_matcher.py

@@ -18,7 +18,7 @@
 
 from monai.apps.detection.utils.ATSS_matcher import ATSSMatcher
 from monai.data.box_utils import box_iou
-from tests.utils import assert_allclose
+from tests.test_utils import assert_allclose
 
 TEST_CASES = [
     [

tests/test_attentionunet.py

@@ -17,7 +17,7 @@
 import torch.nn as nn
 
 import monai.networks.nets.attentionunet as att
-from tests.utils import skip_if_no_cuda, skip_if_quick
+from tests.test_utils import skip_if_no_cuda, skip_if_quick
 
 
 def get_net_parameters(net: nn.Module) -> int:

tests/test_auto3dseg.py

@@ -54,7 +54,7 @@
     ToDeviced,
 )
 from monai.utils.enums import DataStatsKeys
-from tests.utils import skip_if_no_cuda
+from tests.test_utils import skip_if_no_cuda
 
 device = "cpu"
 n_workers = 2

tests/test_auto3dseg_bundlegen.py

@@ -26,7 +26,7 @@
 from monai.bundle.config_parser import ConfigParser
 from monai.data import create_test_image_3d
 from monai.utils import set_determinism
-from tests.utils import (
+from tests.test_utils import (
     SkipIfBeforePyTorchVersion,
     get_testing_algo_template_path,
     skip_if_downloading_fails,

tests/test_auto3dseg_ensemble.py

@@ -32,7 +32,7 @@
 from monai.transforms import SaveImage
 from monai.utils import check_parent_dir, optional_import, set_determinism
 from monai.utils.enums import AlgoKeys
-from tests.utils import (
+from tests.test_utils import (
     SkipIfBeforePyTorchVersion,
     get_testing_algo_template_path,
     skip_if_downloading_fails,

tests/test_auto3dseg_hpo.py

@@ -25,7 +25,7 @@
 from monai.data import create_test_image_3d
 from monai.utils import optional_import
 from monai.utils.enums import AlgoKeys
-from tests.utils import (
+from tests.test_utils import (
     SkipIfBeforePyTorchVersion,
     get_testing_algo_template_path,
     skip_if_downloading_fails,

tests/test_autoencoder.py

@@ -19,7 +19,7 @@
 from monai.networks import eval_mode
 from monai.networks.layers import Act
 from monai.networks.nets import AutoEncoder
-from tests.utils import test_script_save
+from tests.test_utils import test_script_save
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 

tests/test_autoencoderkl.py

@@ -23,7 +23,7 @@
 from monai.networks import eval_mode
 from monai.networks.nets import AutoencoderKL
 from monai.utils import optional_import
-from tests.utils import SkipIfBeforePyTorchVersion, skip_if_downloading_fails, testing_data_config
+from tests.test_utils import SkipIfBeforePyTorchVersion, skip_if_downloading_fails, testing_data_config
 
 tqdm, has_tqdm = optional_import("tqdm", name="tqdm")
 _, has_einops = optional_import("einops")

tests/test_autoencoderkl_maisi.py

@@ -19,7 +19,7 @@
 from monai.apps.generation.maisi.networks.autoencoderkl_maisi import AutoencoderKlMaisi
 from monai.networks import eval_mode
 from monai.utils import optional_import
-from tests.utils import SkipIfBeforePyTorchVersion
+from tests.test_utils import SkipIfBeforePyTorchVersion
 
 tqdm, has_tqdm = optional_import("tqdm", name="tqdm")
 _, has_einops = optional_import("einops")

tests/test_avg_merger.py

@@ -18,7 +18,7 @@
 from torch.nn.functional import pad
 
 from monai.inferers import AvgMerger
-from tests.utils import assert_allclose
+from tests.test_utils import assert_allclose
 
 TENSOR_4x4 = torch.randint(low=0, high=255, size=(2, 3, 4, 4), dtype=torch.float32)
 TENSOR_4x4_WITH_NAN = TENSOR_4x4.clone()

tests/test_basic_unet.py

@@ -18,7 +18,7 @@
 
 from monai.networks import eval_mode
 from monai.networks.nets import BasicUNet
-from tests.utils import test_script_save
+from tests.test_utils import test_script_save
 
 CASES_1D = []
 for mode in ["pixelshuffle", "nontrainable", "deconv", None]:

tests/test_basic_unetplusplus.py

@@ -18,7 +18,7 @@
 
 from monai.networks import eval_mode
 from monai.networks.nets import BasicUNetPlusPlus
-from tests.utils import test_script_save
+from tests.test_utils import test_script_save
 
 CASES_1D = []
 for mode in ["pixelshuffle", "nontrainable", "deconv", None]:

tests/test_bilateral_approx_cpu.py

@@ -19,7 +19,7 @@
 from torch.autograd import gradcheck
 
 from monai.networks.layers.filtering import BilateralFilter
-from tests.utils import skip_if_no_cpp_extension
+from tests.test_utils import skip_if_no_cpp_extension
 
 TEST_CASES = [
     [

tests/test_bilateral_approx_cuda.py

@@ -19,7 +19,7 @@
 from torch.autograd import gradcheck
 
 from monai.networks.layers.filtering import BilateralFilter
-from tests.utils import skip_if_no_cpp_extension, skip_if_no_cuda
+from tests.test_utils import skip_if_no_cpp_extension, skip_if_no_cuda
 
 TEST_CASES = [
     [

tests/test_bilateral_precise.py

@@ -19,7 +19,7 @@
 from torch.autograd import gradcheck
 
 from monai.networks.layers.filtering import BilateralFilter
-from tests.utils import skip_if_no_cpp_extension, skip_if_no_cuda, skip_if_quick
+from tests.test_utils import skip_if_no_cpp_extension, skip_if_no_cuda, skip_if_quick
 
 TEST_CASES = [
     [

tests/test_blend_images.py

@@ -22,7 +22,7 @@
 from monai.transforms.utils_pytorch_numpy_unification import moveaxis
 from monai.utils.module import optional_import
 from monai.visualize.utils import blend_images
-from tests.utils import TEST_NDARRAYS
+from tests.test_utils import TEST_NDARRAYS
 
 plt, has_matplotlib = optional_import("matplotlib.pyplot")
 

tests/test_bounding_rect.py

@@ -18,7 +18,7 @@
 
 import monai
 from monai.transforms import BoundingRect
-from tests.utils import TEST_NDARRAYS
+from tests.test_utils import TEST_NDARRAYS
 
 TEST_CASE_1 = [(2, 3), [[0, 0], [1, 2]]]
 

tests/test_bounding_rectd.py

@@ -18,7 +18,7 @@
 
 import monai
 from monai.transforms import BoundingRectD
-from tests.utils import TEST_NDARRAYS
+from tests.test_utils import TEST_NDARRAYS
 
 TEST_CASE_1 = [(2, 3), [[0, 0], [1, 2]]]
 

tests/test_box_coder.py

@@ -17,7 +17,7 @@
 
 from monai.apps.detection.utils.box_coder import BoxCoder
 from monai.transforms import CastToType
-from tests.utils import assert_allclose
+from tests.test_utils import assert_allclose
 
 
 class TestBoxTransform(unittest.TestCase):