rerouting paths

Author: garciadias

tests/apps/pathology/test_sliding_window_hovernet_inference.py

@@ -21,7 +21,7 @@
 from monai.data import MetaTensor
 from monai.inferers import sliding_window_inference
 from monai.utils import optional_import
-from tests.test_sliding_window_inference import TEST_CASES
+from tests.inferers.test_sliding_window_inference import TEST_CASES
 
 _, has_tqdm = optional_import("tqdm")
 
@@ -36,7 +36,6 @@
 
 
 class TestSlidingWindowHoVerNetInference(unittest.TestCase):
-
     @parameterized.expand(TEST_CASES_PADDING)
     def test_sliding_window_with_padding(
         self, key, image_shape, roi_shape, sw_batch_size, overlap, mode, device, extra_input_padding
@@ -122,21 +121,19 @@ def compute(self, data):
             sigma_scale=1.0,
         )
 
-        expected = np.array(
+        expected = np.array([
             [
                 [
-                    [
-                        [3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000],
-                        [3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000],
-                        [3.3333, 3.3333, 3.3333, 3.3333, 3.3333, 3.3333, 3.3333],
-                        [3.6667, 3.6667, 3.6667, 3.6667, 3.6667, 3.6667, 3.6667],
-                        [4.3333, 4.3333, 4.3333, 4.3333, 4.3333, 4.3333, 4.3333],
-                        [4.5000, 4.5000, 4.5000, 4.5000, 4.5000, 4.5000, 4.5000],
-                        [5.0000, 5.0000, 5.0000, 5.0000, 5.0000, 5.0000, 5.0000],
-                    ]
+                    [3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000],
+                    [3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000, 3.0000],
+                    [3.3333, 3.3333, 3.3333, 3.3333, 3.3333, 3.3333, 3.3333],
+                    [3.6667, 3.6667, 3.6667, 3.6667, 3.6667, 3.6667, 3.6667],
+                    [4.3333, 4.3333, 4.3333, 4.3333, 4.3333, 4.3333, 4.3333],
+                    [4.5000, 4.5000, 4.5000, 4.5000, 4.5000, 4.5000, 4.5000],
+                    [5.0000, 5.0000, 5.0000, 5.0000, 5.0000, 5.0000, 5.0000],
                 ]
             ]
-        )
+        ])
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
         result = sliding_window_inference(
             inputs,
@@ -150,31 +147,29 @@ def compute(self, data):
             sigma_scale=1.0,
             progress=has_tqdm,
         )
-        expected = np.array(
+        expected = np.array([
             [
                 [
-                    [
-                        [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0],
-                        [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0],
-                        [3.3271625, 3.3271623, 3.3271623, 3.3271623, 3.3271623, 3.3271623, 3.3271625],
-                        [3.6728377, 3.6728377, 3.6728377, 3.6728377, 3.6728377, 3.6728377, 3.6728377],
-                        [4.3271623, 4.3271623, 4.3271627, 4.3271627, 4.3271627, 4.3271623, 4.3271623],
-                        [4.513757, 4.513757, 4.513757, 4.513757, 4.513757, 4.513757, 4.513757],
-                        [4.9999995, 5.0, 5.0, 5.0, 5.0, 5.0, 4.9999995],
-                    ]
+                    [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0],
+                    [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0],
+                    [3.3271625, 3.3271623, 3.3271623, 3.3271623, 3.3271623, 3.3271623, 3.3271625],
+                    [3.6728377, 3.6728377, 3.6728377, 3.6728377, 3.6728377, 3.6728377, 3.6728377],
+                    [4.3271623, 4.3271623, 4.3271627, 4.3271627, 4.3271627, 4.3271623, 4.3271623],
+                    [4.513757, 4.513757, 4.513757, 4.513757, 4.513757, 4.513757, 4.513757],
+                    [4.9999995, 5.0, 5.0, 5.0, 5.0, 5.0, 4.9999995],
                 ]
             ]
-        )
+        ])
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
         result = SlidingWindowHoVerNetInferer(roi_shape, sw_batch_size, overlap=0.5, mode="gaussian", sigma_scale=1.0)(
             inputs, _Pred().compute
         )
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
-        result = SlidingWindowHoVerNetInferer(
-            roi_shape, sw_batch_size, overlap=0.5, mode="gaussian", sigma_scale=[1.0, 1.0]
-        )(inputs, _Pred().compute)
+        result = SlidingWindowHoVerNetInferer(roi_shape, sw_batch_size, overlap=0.5, mode="gaussian", sigma_scale=[1.0, 1.0])(
+            inputs, _Pred().compute
+        )
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
         result = SlidingWindowHoVerNetInferer(
@@ -205,9 +200,7 @@ def compute(data):
         expected = np.ones((1, 1, 3, 3)) * -6.0
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
-        result = SlidingWindowHoVerNetInferer(roi_shape, sw_batch_size, overlap=0.5, mode="constant", cval=-1)(
-            inputs, compute
-        )
+        result = SlidingWindowHoVerNetInferer(roi_shape, sw_batch_size, overlap=0.5, mode="constant", cval=-1)(inputs, compute)
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
     def test_args_kwargs(self):
@@ -245,9 +238,9 @@ def compute(data, test1, test2):
         expected = np.ones((1, 1, 3, 3)) + 2.0
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
-        result = SlidingWindowHoVerNetInferer(
-            roi_shape, sw_batch_size, overlap=0.5, mode="constant", cval=-1, progress=has_tqdm
-        )(inputs, compute, t1, test2=t2)
+        result = SlidingWindowHoVerNetInferer(roi_shape, sw_batch_size, overlap=0.5, mode="constant", cval=-1, progress=has_tqdm)(
+            inputs, compute, t1, test2=t2
+        )
         np.testing.assert_allclose(result.cpu().numpy(), expected, rtol=1e-4)
 
     @parameterized.expand(TEST_CASES_MULTIOUTPUT)
@@ -287,9 +280,9 @@ def compute_dict(data):
         for rr, _ in zip(result_dict, expected_dict):
             np.testing.assert_allclose(result_dict[rr].cpu().numpy(), expected_dict[rr], rtol=1e-4)
 
-        result = SlidingWindowHoVerNetInferer(
-            roi_shape, sw_batch_size, overlap=0.5, mode="constant", cval=-1, progress=has_tqdm
-        )(inputs, compute)
+        result = SlidingWindowHoVerNetInferer(roi_shape, sw_batch_size, overlap=0.5, mode="constant", cval=-1, progress=has_tqdm)(
+            inputs, compute
+        )
         for rr, ee in zip(result, expected):
             np.testing.assert_allclose(rr.cpu().numpy(), ee, rtol=1e-4)
 

tests/bundle/test_bundle_ckpt_export.py

@@ -15,6 +15,7 @@
 import os
 import tempfile
 import unittest
+from pathlib import Path
 
 from parameterized import parameterized
 
@@ -23,17 +24,9 @@
 from monai.networks import save_state
 from tests.utils import command_line_tests, skip_if_windows
 
-TEST_CASE_1 = [True, "", ""]
-
-TEST_CASE_2 = [True, "model", ""]
-
-TEST_CASE_3 = [True, "model", "True"]
-
-TEST_CASE_4 = [False, "", ""]
-
-TEST_CASE_5 = [False, "model", ""]
-
-TEST_CASE_6 = [False, "model", "True"]
+TEST_CASE_1 = ["", ""]
+TEST_CASE_2 = ["model", ""]
+TEST_CASE_3 = ["model", "True"]
 
 
 @skip_if_windows
@@ -42,8 +35,9 @@ def setUp(self):
         self.device = os.environ.get("CUDA_VISIBLE_DEVICES")
         if not self.device:
             os.environ["CUDA_VISIBLE_DEVICES"] = "0"  # default
-        self.meta_file = os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json")
-        self.config_file = os.path.join(os.path.dirname(__file__), "testing_data", "inference.json")
+        module_path = Path(__file__).resolve().parents[1].as_posix()
+        self.meta_file = os.path.join(module_path, "testing_data", "metadata.json")
+        self.config_file = os.path.join(module_path, "testing_data", "inference.json")
         self.tempdir_obj = tempfile.TemporaryDirectory()
         tempdir = self.tempdir_obj.name
         self.def_args = {"meta_file": "will be replaced by `meta_file` arg"}
@@ -81,9 +75,7 @@ def test_export(self, key_in_ckpt, use_trace):
         command_line_tests(full_cmd)
         self.assertTrue(os.path.exists(self.ts_file))
 
-        _, metadata, extra_files = load_net_with_metadata(
-            self.ts_file, more_extra_files=["inference.json", "def_args.json"]
-        )
+        _, metadata, extra_files = load_net_with_metadata(self.ts_file, more_extra_files=["inference.json", "def_args.json"])
         self.assertIn("schema", metadata)
         self.assertIn("meta_file", json.loads(extra_files["def_args.json"]))
         self.assertIn("network_def", json.loads(extra_files["inference.json"]))

tests/bundle/test_bundle_trt_export.py

@@ -15,6 +15,7 @@
 import os
 import tempfile
 import unittest
+from pathlib import Path
 
 from parameterized import parameterized
 
@@ -55,7 +56,6 @@
 @skip_if_quick
 @SkipIfBeforeComputeCapabilityVersion((7, 5))
 class TestTRTExport(unittest.TestCase):
-
     def setUp(self):
         self.device = os.environ.get("CUDA_VISIBLE_DEVICES")
         if not self.device:
@@ -70,8 +70,9 @@ def tearDown(self):
     @parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3, TEST_CASE_4])
     @unittest.skipUnless(has_torchtrt and has_tensorrt, "Torch-TensorRT is required for conversion!")
     def test_trt_export(self, convert_precision, input_shape, dynamic_batch):
-        meta_file = os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json")
-        config_file = os.path.join(os.path.dirname(__file__), "testing_data", "inference.json")
+        tests_dir = Path(__file__).resolve().parent
+        meta_file = os.path.join(tests_dir, "testing_data", "metadata.json")
+        config_file = os.path.join(tests_dir, "testing_data", "inference.json")
         with tempfile.TemporaryDirectory() as tempdir:
             def_args = {"meta_file": "will be replaced by `meta_file` arg"}
             def_args_file = os.path.join(tempdir, "def_args.yaml")
@@ -107,8 +108,9 @@ def test_trt_export(self, convert_precision, input_shape, dynamic_batch):
         has_onnx and has_torchtrt and has_tensorrt, "Onnx and TensorRT are required for onnx-trt conversion!"
     )
     def test_onnx_trt_export(self, convert_precision, input_shape, dynamic_batch):
-        meta_file = os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json")
-        config_file = os.path.join(os.path.dirname(__file__), "testing_data", "inference.json")
+        tests_dir = Path(__file__).resolve().parent
+        meta_file = os.path.join(tests_dir, "testing_data", "metadata.json")
+        config_file = os.path.join(tests_dir, "testing_data", "inference.json")
         with tempfile.TemporaryDirectory() as tempdir:
             def_args = {"meta_file": "will be replaced by `meta_file` arg"}
             def_args_file = os.path.join(tempdir, "def_args.yaml")

tests/bundle/test_bundle_verify_metadata.py

@@ -15,20 +15,21 @@
 import os
 import tempfile
 import unittest
+from pathlib import Path
 
 from parameterized import parameterized
 
 from monai.bundle import ConfigParser, verify_metadata
 from tests.utils import command_line_tests, download_url_or_skip_test, skip_if_windows, testing_data_config
 
-SCHEMA_FILE = os.path.join(os.path.dirname(__file__), "testing_data", "schema.json")
+TESTS_DIR = Path(__file__).parent.as_posix()
+SCHEMA_FILE = os.path.join(TESTS_DIR, "testing_data", "schema.json")
 
-TEST_CASE_1 = [os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json"), SCHEMA_FILE]
+TEST_CASE_1 = [os.path.join(TESTS_DIR, "testing_data", "metadata.json"), SCHEMA_FILE]
 
 
 @skip_if_windows
 class TestVerifyMetaData(unittest.TestCase):
-
     def setUp(self):
         self.config = testing_data_config("configs", "test_meta_file")
         download_url_or_skip_test(

tests/bundle/test_bundle_verify_net.py

@@ -14,21 +14,23 @@
 import os
 import tempfile
 import unittest
+from pathlib import Path
 
 from parameterized import parameterized
 
 from monai.bundle import ConfigParser, verify_net_in_out
 from tests.utils import command_line_tests, skip_if_no_cuda, skip_if_windows
 
+TESTS_PATH = Path(__file__).parent.as_posix()
+
 TEST_CASE_1 = [
-    os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json"),
-    os.path.join(os.path.dirname(__file__), "testing_data", "inference.json"),
+    os.path.join(TESTS_PATH, "testing_data", "metadata.json"),
+    os.path.join(TESTS_PATH, "testing_data", "inference.json"),
 ]
 
 
 @skip_if_windows
 class TestVerifyNetwork(unittest.TestCase):
-
     @parameterized.expand([TEST_CASE_1])
     def test_verify(self, meta_file, config_file):
         with tempfile.TemporaryDirectory() as tempdir:

tests/bundle/test_bundle_workflow.py

@@ -11,6 +11,7 @@
 
 from __future__ import annotations
 
+from pathlib import Path
 import os
 import shutil
 import sys
@@ -30,7 +31,7 @@
 from monai.transforms import Compose, LoadImage, LoadImaged, SaveImaged
 from tests.nonconfig_workflow import NonConfigWorkflow, PythonicWorkflowImpl
 
-MODULE_PATH = os.path.dirname(os.path.abspath(__file__).parents[2])
+MODULE_PATH = Path(__file__).resolve().parents[1]
 
 TEST_CASE_1 = [os.path.join(MODULE_PATH, "tests", "testing_data", "inference.json")]
 
@@ -106,7 +107,7 @@ def test_inference_config(self, config_file):
         inferer = ConfigWorkflow(
             workflow_type="infer",
             config_file=config_file,
-            logging_file=os.path.join(os.path.dirname(__file__), "testing_data", "logging.conf"),
+            logging_file=os.path.join(MODULE_PATH, "testing_data", "logging.conf"),
             **override,
         )
         self._test_inferer(inferer)
@@ -115,8 +116,8 @@ def test_inference_config(self, config_file):
         inferer = ConfigWorkflow(
             config_file=config_file,
             workflow_type="infer",
-            properties_path=os.path.join(os.path.dirname(__file__), "testing_data", "fl_infer_properties.json"),
-            logging_file=os.path.join(os.path.dirname(__file__), "testing_data", "logging.conf"),
+            properties_path=os.path.join(MODULE_PATH, "testing_data", "fl_infer_properties.json"),
+            logging_file=os.path.join(MODULE_PATH, "testing_data", "logging.conf"),
             **override,
         )
         self._test_inferer(inferer)
@@ -131,7 +132,7 @@ def test_responsive_inference_config(self, config_file):
         inferer = ConfigWorkflow(
             workflow_type="infer",
             config_file=config_file,
-            logging_file=os.path.join(os.path.dirname(__file__), "testing_data", "logging.conf"),
+            logging_file=os.path.join(MODULE_PATH, "testing_data", "logging.conf"),
         )
         # FIXME: temp add the property for test, we should add it to some formal realtime infer properties
         inferer.add_property(name="dataflow", required=True, config_id="dataflow")
@@ -157,7 +158,7 @@ def test_train_config(self, config_file):
         trainer = ConfigWorkflow(
             workflow_type="train",
             config_file=config_file,
-            logging_file=os.path.join(os.path.dirname(__file__), "testing_data", "logging.conf"),
+            logging_file=os.path.join(MODULE_PATH, "testing_data", "logging.conf"),
             init_id="initialize",
             run_id="run",
             final_id="finalize",
@@ -203,8 +204,8 @@ def test_non_config_wrong_log_cases(self, meta_file, logging_file, expected_erro
     def test_pythonic_workflow(self):
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         config_file = {"roi_size": (64, 64, 32)}
-        meta_file = os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json")
-        property_path = os.path.join(os.path.dirname(__file__), "testing_data", "python_workflow_properties.json")
+        meta_file = os.path.join(MODULE_PATH, "testing_data", "metadata.json")
+        property_path = os.path.join(MODULE_PATH, "testing_data", "python_workflow_properties.json")
         workflow = PythonicWorkflowImpl(
             workflow_type="infer", config_file=config_file, meta_file=meta_file, properties_path=property_path
         )
@@ -229,9 +230,9 @@ def test_pythonic_workflow(self):
     def test_create_pythonic_workflow(self):
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         config_file = {"roi_size": (64, 64, 32)}
-        meta_file = os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json")
-        property_path = os.path.join(os.path.dirname(__file__), "testing_data", "python_workflow_properties.json")
-        sys.path.append(os.path.dirname(__file__))
+        meta_file = os.path.join(MODULE_PATH, "testing_data", "metadata.json")
+        property_path = os.path.join(MODULE_PATH, "testing_data", "python_workflow_properties.json")
+        sys.path.append(MODULE_PATH)
         workflow = create_workflow(
             "nonconfig_workflow.PythonicWorkflowImpl",
             workflow_type="infer",

tests/clang_format_utils.py

@@ -18,14 +18,15 @@
 import platform
 import stat
 import sys
+from pathlib import Path
 
 from monai.apps.utils import download_url
 
 # String representing the host platform (e.g. Linux, Darwin).
 HOST_PLATFORM = platform.system()
 
 # MONAI directory root, derived from the location of this file.
-MONAI_ROOT = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+MONAI_ROOT = Path(__file__).resolve().parent.parent
 
 # This dictionary maps each platform to the S3 object URL for its clang-format binary.
 PLATFORM_TO_CF_URL = {