diff --git a/requirements/dev.txt b/requirements/dev.txt
index 98b81bbd28..4816a99c16 100644
--- a/requirements/dev.txt
+++ b/requirements/dev.txt
@@ -1,6 +1,7 @@
 pre-commit
 pytest
 pytest-cov
+pytest-order
 pytest-sugar
 pytest-xdist
 coverage[toml]
diff --git a/tests/pre_merge/tools/__init__.py b/tests/pre_merge/tools/__init__.py
new file mode 100644
index 0000000000..a35a271287
--- /dev/null
+++ b/tests/pre_merge/tools/__init__.py
@@ -0,0 +1,8 @@
+"""Test entry point scripts.
+
+
+Note: This might be removed when migration to CLI is complete.
+"""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
diff --git a/tests/pre_merge/tools/conftest.py b/tests/pre_merge/tools/conftest.py
new file mode 100644
index 0000000000..14bf1184e0
--- /dev/null
+++ b/tests/pre_merge/tools/conftest.py
@@ -0,0 +1,56 @@
+"""Fixtures for the tools tests."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
+
+from tempfile import TemporaryDirectory
+from typing import Generator
+
+import albumentations as A
+import cv2
+import numpy as np
+import pytest
+from albumentations.pytorch import ToTensorV2
+
+from anomalib.config import get_configurable_parameters
+
+
+@pytest.fixture(scope="package")
+def project_path() -> Generator[str, None, None]:
+    with TemporaryDirectory() as project_dir:
+        yield project_dir
+
+
+@pytest.fixture(scope="package")
+def get_config(project_path):
+    def get_config(
+        model_name: str | None = None,
+        config_path: str | None = None,
+        weight_file: str | None = None,
+    ):
+        """Gets config for testing."""
+        config = get_configurable_parameters(model_name, config_path, weight_file)
+        config.dataset.image_size = (100, 100)
+        config.model.input_size = (100, 100)
+        config.project.path = project_path
+        config.trainer.max_epochs = 1
+        config.trainer.check_val_every_n_epoch = 1
+        config.trainer.limit_train_batches = 1
+        config.trainer.limit_predict_batches = 1
+        return config
+
+    yield get_config
+
+
+@pytest.fixture(scope="package")
+def get_dummy_inference_image(project_path) -> Generator[str, None, None]:
+    image = np.zeros((100, 100, 3), dtype=np.uint8)
+    cv2.imwrite(project_path + "/dummy_image.png", image)
+    yield project_path + "/dummy_image.png"
+
+
+@pytest.fixture(scope="package")
+def transforms_config() -> dict:
+    """Note: this is computed using trainer.datamodule.test_data.transform.to_dict()"""
+    return A.Compose([A.ToFloat(max_value=255), ToTensorV2()]).to_dict()
diff --git a/tests/pre_merge/tools/test_gradio_entrypoint.py b/tests/pre_merge/tools/test_gradio_entrypoint.py
new file mode 100644
index 0000000000..d733bbb00f
--- /dev/null
+++ b/tests/pre_merge/tools/test_gradio_entrypoint.py
@@ -0,0 +1,93 @@
+"""Test Gradio inference entrypoint script."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+
+from __future__ import annotations
+
+import sys
+from importlib.util import find_spec
+
+import pytest
+
+from anomalib.data import TaskType
+from anomalib.deploy import ExportMode, OpenVINOInferencer, TorchInferencer, export
+from anomalib.models import get_model
+
+sys.path.append("tools/inference")
+
+
+@pytest.mark.order(5)
+class TestGradioInferenceEntrypoint:
+    """This tests whether the entrypoints run without errors without quantitative measure of the outputs.
+
+    Note: This does not launch the gradio server. It only checks if the right inferencer is called.
+    """
+
+    @pytest.fixture
+    def get_functions(self):
+        """Get functions from Gradio_inference.py"""
+        if find_spec("gradio_inference") is not None:
+            from tools.inference.gradio_inference import get_inferencer, get_parser
+        else:
+            raise Exception("Unable to import gradio_inference.py for testing")
+        return get_parser, get_inferencer
+
+    def test_torch_inference(self, get_functions, project_path, get_config, transforms_config):
+        """Test gradio_inference.py"""
+        parser, inferencer = get_functions
+        model = get_model(get_config("padim"))
+
+        # export torch model
+        export(
+            task=TaskType.SEGMENTATION,
+            transform=transforms_config,
+            input_size=(100, 100),
+            model=model,
+            export_mode=ExportMode.TORCH,
+            export_root=project_path,
+        )
+
+        arguments = parser().parse_args(
+            [
+                "--weights",
+                project_path + "/weights/torch/model.pt",
+            ]
+        )
+        assert isinstance(inferencer(arguments.weights, arguments.metadata), TorchInferencer)
+
+    def test_openvino_inference(self, get_functions, project_path, get_config, transforms_config):
+        """Test gradio_inference.py"""
+        parser, inferencer = get_functions
+        model = get_model(get_config("padim"))
+
+        # export OpenVINO model
+        export(
+            task=TaskType.SEGMENTATION,
+            transform=transforms_config,
+            input_size=(100, 100),
+            model=model,
+            export_mode=ExportMode.OPENVINO,
+            export_root=project_path,
+        )
+
+        arguments = parser().parse_args(
+            [
+                "--weights",
+                project_path + "/weights/openvino/model.bin",
+                "--metadata",
+                project_path + "/weights/openvino/metadata.json",
+            ]
+        )
+        assert isinstance(inferencer(arguments.weights, arguments.metadata), OpenVINOInferencer)
+
+        # test error is raised when metadata is not provided to openvino model
+        with pytest.raises(ValueError):
+            arguments = parser().parse_args(
+                [
+                    "--weights",
+                    project_path + "/weights/openvino/model.bin",
+                ]
+            )
+            inferencer(arguments.weights, arguments.metadata)
diff --git a/tests/pre_merge/tools/test_lightning_entrypoint.py b/tests/pre_merge/tools/test_lightning_entrypoint.py
new file mode 100644
index 0000000000..cf7e8d1129
--- /dev/null
+++ b/tests/pre_merge/tools/test_lightning_entrypoint.py
@@ -0,0 +1,47 @@
+"""Test lightning inference entrypoint script."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+
+from __future__ import annotations
+
+import sys
+from importlib.util import find_spec
+
+import pytest
+
+sys.path.append("tools/inference")
+from unittest.mock import patch
+
+
+@pytest.mark.order(3)
+class TestLightningInferenceEntrypoint:
+    """This tests whether the entrypoints run without errors without quantitative measure of the outputs."""
+
+    @pytest.fixture
+    def get_functions(self):
+        """Get functions from lightning_inference.py"""
+        if find_spec("lightning_inference") is not None:
+            from tools.inference.lightning_inference import get_parser, infer
+        else:
+            raise Exception("Unable to import lightning_inference.py for testing")
+        return get_parser, infer
+
+    def test_lightning_inference(self, get_functions, get_config, project_path, get_dummy_inference_image):
+        """Test lightning_inferenc.py"""
+        get_parser, infer = get_functions
+        with patch("tools.inference.lightning_inference.get_configurable_parameters", side_effect=get_config):
+            arguments = get_parser().parse_args(
+                [
+                    "--config",
+                    "src/anomalib/models/padim/config.yaml",
+                    "--weights",
+                    project_path + "/weights/lightning/model.ckpt",
+                    "--input",
+                    get_dummy_inference_image,
+                    "--output",
+                    project_path + "/output",
+                ]
+            )
+            infer(arguments)
diff --git a/tests/pre_merge/tools/test_openvino_entrypoint.py b/tests/pre_merge/tools/test_openvino_entrypoint.py
new file mode 100644
index 0000000000..ebf3f7d39e
--- /dev/null
+++ b/tests/pre_merge/tools/test_openvino_entrypoint.py
@@ -0,0 +1,66 @@
+"""Test OpenVINO inference entrypoint script."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+
+from __future__ import annotations
+
+import sys
+from importlib.util import find_spec
+
+import pytest
+
+from anomalib.data import TaskType
+from anomalib.deploy import ExportMode, export
+from anomalib.models import get_model
+
+sys.path.append("tools/inference")
+
+
+@pytest.mark.order(4)
+class TestOpenVINOInferenceEntrypoint:
+    """This tests whether the entrypoints run without errors without quantitative measure of the outputs."""
+
+    @pytest.fixture
+    def get_functions(self):
+        """Get functions from openvino_inference.py"""
+        if find_spec("openvino_inference") is not None:
+            from tools.inference.openvino_inference import get_parser, infer
+        else:
+            raise Exception("Unable to import openvino_inference.py for testing")
+        return get_parser, infer
+
+    def test_openvino_inference(
+        self, get_functions, get_config, project_path, get_dummy_inference_image, transforms_config
+    ):
+        """Test openvino_inference.py"""
+        get_parser, infer = get_functions
+
+        model = get_model(get_config("padim"))
+
+        # export OpenVINO model
+        export(
+            task=TaskType.SEGMENTATION,
+            transform=transforms_config,
+            input_size=(100, 100),
+            model=model,
+            export_mode=ExportMode.OPENVINO,
+            export_root=project_path,
+        )
+
+        arguments = get_parser().parse_args(
+            [
+                "--config",
+                "src/anomalib/models/padim/config.yaml",
+                "--weights",
+                project_path + "/weights/openvino/model.bin",
+                "--metadata",
+                project_path + "/weights/openvino/metadata.json",
+                "--input",
+                get_dummy_inference_image,
+                "--output",
+                project_path + "/output",
+            ]
+        )
+        infer(arguments)
diff --git a/tests/pre_merge/tools/test_test_entrypoint.py b/tests/pre_merge/tools/test_test_entrypoint.py
new file mode 100644
index 0000000000..a79db2eb29
--- /dev/null
+++ b/tests/pre_merge/tools/test_test_entrypoint.py
@@ -0,0 +1,54 @@
+"""Test test.py entrypoint script."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import sys
+from importlib.util import find_spec
+
+import pytest
+
+sys.path.append("tools")
+from unittest.mock import patch
+
+
+@pytest.mark.order(2)
+class TestTestEntrypoint:
+    """This tests whether the entrypoints run without errors without quantitative measure of the outputs."""
+
+    @pytest.fixture
+    def get_functions(self):
+        """Get functions from test.py"""
+        if find_spec("test") is not None:
+            from tools.test import get_parser, test
+        else:
+            raise Exception("Unable to import test.py for testing")
+        return get_parser, test
+
+    def test_test(self, get_functions, get_config, project_path):
+        """Test test.py"""
+        get_parser, test = get_functions
+        with patch("tools.test.get_configurable_parameters", side_effect=get_config):
+            # Test when model key is passed
+            arguments = get_parser().parse_args(
+                ["--model", "padim", "--weight_file", project_path + "/weights/lightning/model.ckpt"]
+            )
+            test(arguments)
+
+            # Test when weight file is incorrect
+            arguments = get_parser().parse_args(["--model", "padim"])
+            with pytest.raises(FileNotFoundError):
+                test(arguments)
+
+            # Test when config key is passed
+            arguments = get_parser().parse_args(
+                [
+                    "--config",
+                    "src/anomalib/models/padim/config.yaml",
+                    "--weight_file",
+                    project_path + "/weights/lightning/model.ckpt",
+                ]
+            )
+            test(arguments)
diff --git a/tests/pre_merge/tools/test_torch_entrypoint.py b/tests/pre_merge/tools/test_torch_entrypoint.py
new file mode 100644
index 0000000000..9917f5909e
--- /dev/null
+++ b/tests/pre_merge/tools/test_torch_entrypoint.py
@@ -0,0 +1,58 @@
+"""Test torch inference entrypoint script."""
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+
+from __future__ import annotations
+
+import sys
+from importlib.util import find_spec
+
+import pytest
+
+from anomalib.data import TaskType
+from anomalib.deploy import ExportMode, export
+from anomalib.models import get_model
+
+sys.path.append("tools/inference")
+
+
+@pytest.mark.order(4)
+class TestTorchInferenceEntrypoint:
+    """This tests whether the entrypoints run without errors without quantitative measure of the outputs."""
+
+    @pytest.fixture
+    def get_functions(self):
+        """Get functions from torch_inference.py"""
+        if find_spec("torch_inference") is not None:
+            from tools.inference.torch_inference import get_parser, infer
+        else:
+            raise Exception("Unable to import torch_inference.py for testing")
+        return get_parser, infer
+
+    def test_torch_inference(
+        self, get_functions, get_config, project_path, get_dummy_inference_image, transforms_config
+    ):
+        """Test torch_inference.py"""
+        get_parser, infer = get_functions
+        model = get_model(get_config("padim"))
+        export(
+            task=TaskType.SEGMENTATION,
+            transform=transforms_config,
+            input_size=(100, 100),
+            model=model,
+            export_mode=ExportMode.TORCH,
+            export_root=project_path,
+        )
+        arguments = get_parser().parse_args(
+            [
+                "--weights",
+                project_path + "/weights/torch/model.pt",
+                "--input",
+                get_dummy_inference_image,
+                "--output",
+                project_path + "/output",
+            ]
+        )
+        infer(arguments)
diff --git a/tests/pre_merge/tools/test_train_entrypoint.py b/tests/pre_merge/tools/test_train_entrypoint.py
new file mode 100644
index 0000000000..50aa951b8c
--- /dev/null
+++ b/tests/pre_merge/tools/test_train_entrypoint.py
@@ -0,0 +1,44 @@
+"""Test train entrypoint"""
+
+
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+import sys
+from importlib.util import find_spec
+from unittest.mock import patch
+
+import pytest
+
+sys.path.append("tools")  # This is the path to the tools folder as it is not part of the anomalib package
+
+
+@pytest.mark.order(1)
+class TestTrainEntrypoint:
+    """This tests whether the entrypoints run without errors without quantitative measure of the outputs."""
+
+    @pytest.fixture
+    def get_functions(self):
+        """Get functions from train.py"""
+        if find_spec("train") is not None:
+            from tools.train import get_parser, train
+        else:
+            raise Exception("Unable to import train.py for testing")
+        return get_parser, train
+
+    def test_train(self, get_functions, get_config):
+        """Test train.py."""
+        with patch("tools.train.get_configurable_parameters", side_effect=get_config):
+            get_parser, train = get_functions
+            # Test when model key is passed
+            args = get_parser().parse_args(["--model", "padim"])
+            train(args)
+
+            # Don't run fit and test the second time
+            with patch("tools.train.Trainer"):
+                # Test when config key is passed
+                args = get_parser().parse_args(["--config", "src/anomalib/models/padim/config.yaml"])
+
+                train(args)
+                # Test when log_level key is passed
+                args = get_parser().parse_args(["--log-level", "ERROR"])
+                train(args)
diff --git a/tools/inference/gradio_inference.py b/tools/inference/gradio_inference.py
index 048b0bbc5f..7d4e5f5ca7 100644
--- a/tools/inference/gradio_inference.py
+++ b/tools/inference/gradio_inference.py
@@ -8,7 +8,7 @@
 
 from __future__ import annotations
 
-from argparse import ArgumentParser, Namespace
+from argparse import ArgumentParser
 from importlib import import_module
 from pathlib import Path
 
@@ -20,8 +20,8 @@
 from anomalib.deploy import Inferencer
 
 
-def get_args() -> Namespace:
-    r"""Get command line arguments.
+def get_parser() -> ArgumentParser:
+    """Get command line arguments.
 
     Example:
 
@@ -30,14 +30,14 @@ def get_args() -> Namespace:
         ...     --weights ./results/padim/mvtec/bottle/weights/torch/model.pt
 
     Returns:
-        Namespace: List of arguments.
+        ArgumentParser: Argument parser for gradio inference.
     """
     parser = ArgumentParser()
     parser.add_argument("--weights", type=Path, required=True, help="Path to model weights")
     parser.add_argument("--metadata", type=Path, required=False, help="Path to a JSON file containing the metadata.")
     parser.add_argument("--share", type=bool, required=False, default=False, help="Share Gradio `share_url`")
 
-    return parser.parse_args()
+    return parser
 
 
 def get_inferencer(weight_path: Path, metadata_path: Path | None = None) -> Inferencer:
@@ -96,7 +96,7 @@ def infer(image: np.ndarray, inferencer: Inferencer) -> tuple[np.ndarray, np.nda
 
 
 if __name__ == "__main__":
-    args = get_args()
+    args = get_parser().parse_args()
     gradio_inferencer = get_inferencer(args.weights, args.metadata)
 
     interface = gr.Interface(
diff --git a/tools/inference/lightning_inference.py b/tools/inference/lightning_inference.py
index c00c0428d4..0474200154 100644
--- a/tools/inference/lightning_inference.py
+++ b/tools/inference/lightning_inference.py
@@ -16,11 +16,11 @@
 from anomalib.utils.callbacks import get_callbacks
 
 
-def get_args() -> Namespace:
-    """Get command line arguments.
+def get_parser() -> ArgumentParser:
+    """Get parser.
 
     Returns:
-        Namespace: List of arguments.
+        ArgumentParser: The parser object.
     """
     parser = ArgumentParser()
     parser.add_argument("--config", type=Path, required=True, help="Path to a config file")
@@ -42,13 +42,11 @@ def get_args() -> Namespace:
         help="Show the visualized predictions on the screen.",
     )
 
-    args = parser.parse_args()
-    return args
+    return parser
 
 
-def infer():
+def infer(args: Namespace):
     """Run inference."""
-    args = get_args()
     config = get_configurable_parameters(config_path=args.config)
     config.trainer.resume_from_checkpoint = str(args.weights)
     config.visualization.show_images = args.show
@@ -76,7 +74,9 @@ def infer():
     )
 
     # create the dataset
-    dataset = InferenceDataset(args.input, image_size=tuple(config.dataset.image_size), transform=transform)
+    dataset = InferenceDataset(
+        args.input, image_size=tuple(config.dataset.image_size), transform=transform  # type: ignore
+    )
     dataloader = DataLoader(dataset)
 
     # generate predictions
@@ -84,4 +84,5 @@ def infer():
 
 
 if __name__ == "__main__":
-    infer()
+    args = get_parser().parse_args()
+    infer(args)
diff --git a/tools/inference/openvino_inference.py b/tools/inference/openvino_inference.py
index ac0ce0c6f7..df1848fc3c 100644
--- a/tools/inference/openvino_inference.py
+++ b/tools/inference/openvino_inference.py
@@ -11,20 +11,16 @@
 from argparse import ArgumentParser, Namespace
 from pathlib import Path
 
-from anomalib.data.utils import (
-    generate_output_image_filename,
-    get_image_filenames,
-    read_image,
-)
+from anomalib.data.utils import generate_output_image_filename, get_image_filenames, read_image
 from anomalib.deploy import OpenVINOInferencer
 from anomalib.post_processing import Visualizer
 
 
-def get_args() -> Namespace:
-    """Get command line arguments.
+def get_parser() -> ArgumentParser:
+    """Get parser.
 
     Returns:
-        Namespace: List of arguments.
+        ArgumentParser: The parser object.
     """
     parser = ArgumentParser()
     parser.add_argument("--config", type=Path, required=True, help="Path to a config file")
@@ -63,21 +59,17 @@ def get_args() -> Namespace:
         help="Show the visualized predictions on the screen.",
     )
 
-    args = parser.parse_args()
+    return parser
 
-    return args
 
-
-def infer() -> None:
+def infer(args: Namespace) -> None:
     """Infer predictions.
 
     Show/save the output if path is to an image. If the path is a directory, go over each image in the directory.
-    """
-    # Get the command line arguments, and config from the config.yaml file.
-    # This config file is also used for training and contains all the relevant
-    # information regarding the data, model, train and inference details.
-    args = get_args()
 
+    Args:
+        args (Namespace): The arguments from the command line.
+    """
     # Get the inferencer.
     inferencer = OpenVINOInferencer(path=args.weights, metadata_path=args.metadata, device=args.device)
     visualizer = Visualizer(mode=args.visualization_mode, task=args.task)
@@ -103,4 +95,5 @@ def infer() -> None:
 
 
 if __name__ == "__main__":
-    infer()
+    args = get_parser().parse_args()
+    infer(args)
diff --git a/tools/inference/torch_inference.py b/tools/inference/torch_inference.py
index 3848408728..bc4f661b79 100644
--- a/tools/inference/torch_inference.py
+++ b/tools/inference/torch_inference.py
@@ -13,20 +13,16 @@
 
 import torch
 
-from anomalib.data.utils import (
-    generate_output_image_filename,
-    get_image_filenames,
-    read_image,
-)
+from anomalib.data.utils import generate_output_image_filename, get_image_filenames, read_image
 from anomalib.deploy import TorchInferencer
 from anomalib.post_processing import Visualizer
 
 
-def get_args() -> Namespace:
-    """Get command line arguments.
+def get_parser() -> ArgumentParser:
+    """Get parser.
 
     Returns:
-        Namespace: List of arguments.
+        ArgumentParser: The parser object.
     """
     parser = ArgumentParser()
     parser.add_argument("--weights", type=Path, required=True, help="Path to model weights")
@@ -63,18 +59,17 @@ def get_args() -> Namespace:
         help="Show the visualized predictions on the screen.",
     )
 
-    args = parser.parse_args()
+    return parser
 
-    return args
 
-
-def infer() -> None:
+def infer(args: Namespace) -> None:
     """Infer predictions.
 
     Show/save the output if path is to an image. If the path is a directory, go over each image in the directory.
+
+    Args:
+        args (Namespace): The arguments from the command line.
     """
-    # Get the command line arguments.
-    args = get_args()
 
     torch.set_grad_enabled(False)
 
@@ -103,4 +98,5 @@ def infer() -> None:
 
 
 if __name__ == "__main__":
-    infer()
+    args = get_parser().parse_args()
+    infer(args=args)
diff --git a/tools/test.py b/tools/test.py
index b2772aaf5d..6278d00017 100644
--- a/tools/test.py
+++ b/tools/test.py
@@ -13,27 +13,26 @@
 from anomalib.utils.callbacks import get_callbacks
 
 
-def get_args() -> Namespace:
-    """Get CLI arguments.
+def get_parser() -> ArgumentParser:
+    """Get parser.
 
     Returns:
-        Namespace: CLI arguments.
+        ArgumentParser: The parser object.
     """
     parser = ArgumentParser()
     parser.add_argument("--model", type=str, default="stfpm", help="Name of the algorithm to train/test")
     parser.add_argument("--config", type=str, required=False, help="Path to a model config file")
     parser.add_argument("--weight_file", type=str, default="weights/model.ckpt")
 
-    args = parser.parse_args()
-    return args
+    return parser
 
 
-def test():
-    """Test an anomaly classification and segmentation model that is initially trained via `tools/train.py`.
+def test(args: Namespace):
+    """Test an anomaly model.
 
-    The script is able to write the results into both filesystem and a logger such as Tensorboard.
+    Args:
+        args (Namespace): The arguments from the command line.
     """
-    args = get_args()
     config = get_configurable_parameters(
         model_name=args.model,
         config_path=args.config,
@@ -53,4 +52,5 @@ def test():
 
 
 if __name__ == "__main__":
-    test()
+    args = get_parser().parse_args()
+    test(args)
diff --git a/tools/train.py b/tools/train.py
index f5ffb8ef9b..3b0a1c88a0 100644
--- a/tools/train.py
+++ b/tools/train.py
@@ -24,24 +24,27 @@
 logger = logging.getLogger("anomalib")
 
 
-def get_args() -> Namespace:
-    """Get command line arguments.
+def get_parser() -> ArgumentParser:
+    """Get parser.
 
     Returns:
-        Namespace: List of arguments.
+        ArgumentParser: The parser object.
     """
     parser = ArgumentParser()
     parser.add_argument("--model", type=str, default="padim", help="Name of the algorithm to train/test")
     parser.add_argument("--config", type=str, required=False, help="Path to a model config file")
     parser.add_argument("--log-level", type=str, default="INFO", help="<DEBUG, INFO, WARNING, ERROR>")
 
-    args = parser.parse_args()
-    return args
+    return parser
 
 
-def train():
-    """Train an anomaly classification or segmentation model based on a provided configuration file."""
-    args = get_args()
+def train(args: Namespace):
+    """Train an anomaly model.
+
+    Args:
+        args (Namespace): The arguments from the command line.
+    """
+
     configure_logger(level=args.log_level)
 
     if args.log_level == "ERROR":
@@ -72,4 +75,5 @@ def train():
 
 
 if __name__ == "__main__":
-    train()
+    args = get_parser().parse_args()
+    train(args)
diff --git a/tox.ini b/tox.ini
index 34a0e381cc..0fdfe9e9c9 100644
--- a/tox.ini
+++ b/tox.ini
@@ -24,6 +24,7 @@ deps =
     coverage[toml]
     pytest
     pytest-cov
+    pytest-order
     flaky
     nbmake
     -r{toxinidir}/requirements/base.txt