Changing utils.py to test_utils.py

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):