🏷 Rename --model_config_path to config

README.md

@@ -75,15 +75,18 @@ file, [`config.yaml`](https://gitlab-icv.inn.intel.com/algo_rnd_team/anomaly/-/b
 category, the config file is to be provided:
 
 ```bash
-python tools/train.py --model_config_path <path/to/model/config.yaml>
+python tools/train.py --config <path/to/model/config.yaml>
 ```
 
 For example, to train [PADIM](anomalib/models/padim) you can use
 
 ```bash
-python tools/train.py --model_config_path anomalib/models/padim/config.yaml
+python tools/train.py --config anomalib/models/padim/config.yaml
 ```
 
+Note that `--model_config_path` will be deprecated in `v0.2.8` and removed
+in `v0.2.9`.
+
 Alternatively, a model name could also be provided as an argument, where the scripts automatically finds the corresponding config file.
 
 ```bash
@@ -138,7 +141,7 @@ The following command can be used to run inference from the command line:
 
 ```bash
 python tools/inference.py \
-    --model_config_path <path/to/model/config.yaml> \
+    --config <path/to/model/config.yaml> \
     --weight_path <path/to/weight/file> \
     --image_path <path/to/image>
 ```
@@ -147,7 +150,7 @@ As a quick example:
 
 ```bash
 python tools/inference.py \
-    --model_config_path anomalib/models/padim/config.yaml \
+    --config anomalib/models/padim/config.yaml \
     --weight_path results/padim/mvtec/bottle/weights/model.ckpt \
     --image_path datasets/MVTec/bottle/test/broken_large/000.png
 ```
@@ -164,7 +167,7 @@ Example OpenVINO Inference:
 
 ```bash
 python tools/inference.py \
-    --model_config_path  \
+    --config  \
     anomalib/models/padim/config.yaml  \
     --weight_path  \
     results/padim/mvtec/bottle/compressed/compressed_model.xml  \
@@ -200,7 +203,7 @@ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
 | DFM           | ResNet-18          |   0.894   |   0.864   |   0.558   |  0.945  |   0.984   |   0.946   |  0.994  |   0.913   |   0.871   |  0.979   |   0.941   |   0.838   |   0.761   |    0.95    |   0.911    |   0.949   |
 | DFKDE         | Wide ResNet-50     |   0.774   |   0.708   |   0.422   |  0.905  |   0.959   |   0.903   |  0.936  |   0.746   |   0.853   |  0.736   |   0.687   |   0.749   |   0.574   |   0.697    |   0.843    |   0.892   |
 | DFKDE         | ResNet-18          |   0.762   |   0.646   |   0.577   |  0.669  |   0.965   |   0.863   |  0.951  |   0.751   |   0.698   |  0.806   |   0.729   |   0.607   |   0.694   |   0.767    |   0.839    |   0.866   |
-| GANomaly   |                | 0.421 | 0.203  | 0.404 | 0.413   | 0.408 | 0.744 | 0.251  | 0.457 |  0.682  | 0.537    |  0.270    | 0.472 | 0.231 | 0.372      |  0.440     | 0.434  |
+| GANomaly      |                    |   0.421   |   0.203   |   0.404   |  0.413  |   0.408   |   0.744   |  0.251  |   0.457   |   0.682   |  0.537   |   0.270   |   0.472   |   0.231   |   0.372    |   0.440    |   0.434   |
 
 ### Pixel-Level AUC
 
@@ -229,7 +232,7 @@ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
 | DFM           | ResNet-18          |   0.919   |   0.895   |   0.844   |   0.926   |   0.971   |   0.948   |   0.977   |   0.874   |   0.935   |   0.957   |   0.958   |   0.921   |   0.874   |   0.933    |   0.833    |   0.943   |
 | DFKDE         | Wide ResNet-50     |   0.875   |   0.907   |   0.844   |   0.905   |   0.945   |   0.914   |   0.946   |   0.790   |   0.914   |   0.817   |   0.894   |   0.922   |   0.855   |   0.845    |   0.722    |   0.910   |
 | DFKDE         | ResNet-18          |   0.872   |   0.864   |   0.844   |   0.854   |   0.960   |   0.898   |   0.942   |   0.793   |   0.908   |   0.827   |   0.894   |   0.916   |   0.859   |   0.853    |   0.756    |   0.916   |
-| GANomaly |                | 0.834 | 0.864  | 0.844 | 0.852   | 0.836 | 0.863 | 0.863  | 0.760 | 0.905   | 0.777    |  0.894    | 0.916 | 0.853 |  0.833     |  0.571     |  0.881 |
+| GANomaly      |                    |   0.834   |   0.864   |   0.844   |   0.852   |   0.836   |   0.863   |   0.863   |   0.760   |   0.905   |   0.777   |   0.894   |   0.916   |   0.853   |   0.833    |   0.571    |   0.881   |
 
 ## Reference
 If you use this library and love it, use this to cite it 🤗

anomalib/config/config.py

@@ -113,7 +113,7 @@ def update_multi_gpu_training_config(config: Union[DictConfig, ListConfig]) -> U
 
 def get_configurable_parameters(
     model_name: Optional[str] = None,
-    model_config_path: Optional[Union[Path, str]] = None,
+    config_path: Optional[Union[Path, str]] = None,
     weight_file: Optional[str] = None,
     config_filename: Optional[str] = "config",
     config_file_extension: Optional[str] = "yaml",
@@ -122,24 +122,24 @@ def get_configurable_parameters(
 
     Args:
         model_name: Optional[str]:  (Default value = None)
-        model_config_path: Optional[Union[Path, str]]:  (Default value = None)
+        config_path: Optional[Union[Path, str]]:  (Default value = None)
         weight_file: Path to the weight file
         config_filename: Optional[str]:  (Default value = "config")
         config_file_extension: Optional[str]:  (Default value = "yaml")
 
     Returns:
         Union[DictConfig, ListConfig]: Configurable parameters in DictConfig object.
     """
-    if model_name is None and model_config_path is None:
+    if model_name is None and config_path is None:
         raise ValueError(
             "Both model_name and model config path cannot be None! "
             "Please provide a model name or path to a config file!"
         )
 
-    if model_config_path is None:
-        model_config_path = Path(f"anomalib/models/{model_name}/{config_filename}.{config_file_extension}")
+    if config_path is None:
+        config_path = Path(f"anomalib/models/{model_name}/{config_filename}.{config_file_extension}")
 
-    config = OmegaConf.load(model_config_path)
+    config = OmegaConf.load(config_path)
 
     # Dataset Configs
     if "format" not in config.dataset.keys():

anomalib/deploy/inferencers/openvino.py

@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions
 # and limitations under the License.
 
-import importlib
+from importlib.util import find_spec
 from pathlib import Path
 from typing import Dict, Optional, Tuple, Union
 
@@ -26,8 +26,10 @@
 
 from .base import Inferencer
 
-if importlib.util.find_spec("openvino") is not None:
-    from openvino.inference_engine import IECore  # pylint: disable=no-name-in-module
+if find_spec("openvino") is not None:
+    from openvino.inference_engine import (  # type: ignore  # pylint: disable=no-name-in-module
+        IECore,
+    )
 
 
 class OpenVINOInferencer(Inferencer):

docs/source/guides/getting_started.rst

@@ -47,7 +47,10 @@ file is to be provided:
 
 ::
 
-    python tools/train.py --model_config_path <path/to/model/config.yaml>
+    python tools/train.py --config <path/to/model/config.yaml>
+
+Note that `--model_config_path` will be deprecated in `v0.2.8` and removed
+in `v0.2.9`.
 
 Alternatively, a model name could also be provided as an argument, where
 the scripts automatically finds the corresponding config file.

tests/helpers/config.py

@@ -11,7 +11,7 @@
 def get_test_configurable_parameters(
     dataset_path: Optional[str] = None,
     model_name: Optional[str] = None,
-    model_config_path: Optional[Union[Path, str]] = None,
+    config_path: Optional[Union[Path, str]] = None,
     weight_file: Optional[str] = None,
     config_filename: Optional[str] = "config",
     config_file_extension: Optional[str] = "yaml",
@@ -21,7 +21,7 @@ def get_test_configurable_parameters(
     Args:
         datset_path: Optional[Path]: Path to dataset
         model_name: Optional[str]:  (Default value = None)
-        model_config_path: Optional[Union[Path, str]]:  (Default value = None)
+        config_path: Optional[Union[Path, str]]:  (Default value = None)
         weight_file: Path to the weight file
         config_filename: Optional[str]:  (Default value = "config")
         config_file_extension: Optional[str]:  (Default value = "yaml")
@@ -30,9 +30,7 @@ def get_test_configurable_parameters(
         Union[DictConfig, ListConfig]: Configurable parameters in DictConfig object.
     """
 
-    config = get_configurable_parameters(
-        model_name, model_config_path, weight_file, config_filename, config_file_extension
-    )
+    config = get_configurable_parameters(model_name, config_path, weight_file, config_filename, config_file_extension)
 
     # Update path to match the dataset path in the test image/runner
     config.dataset.path = get_dataset_path() if dataset_path is None else dataset_path

tests/pre_merge/utils/callbacks/normalization_callback/test_normalization_callback.py

@@ -20,7 +20,7 @@ def run_train_test(config):
 
 @TestDataset(num_train=200, num_test=30, path=get_dataset_path(), seed=42)
 def test_normalizer(path=get_dataset_path(), category="shapes"):
-    config = get_configurable_parameters(model_config_path="anomalib/models/padim/config.yaml")
+    config = get_configurable_parameters(config_path="anomalib/models/padim/config.yaml")
     config.dataset.path = path
     config.dataset.category = category
     config.model.threshold.adaptive = True

tests/pre_merge/utils/callbacks/openvino_callback/test_openvino.py

@@ -16,7 +16,7 @@ def test_openvino_model_callback():
     """Tests if an optimized model is created."""
 
     config = get_test_configurable_parameters(
-        model_config_path="tests/pre_merge/utils/callbacks/openvino_callback/dummy_config.yml"
+        config_path="tests/pre_merge/utils/callbacks/openvino_callback/dummy_config.yml"
     )
 
     with tempfile.TemporaryDirectory() as tmp_dir:

tests/pre_merge/utils/metrics/test_adaptive_threshold.py

@@ -48,7 +48,7 @@ def test_non_adaptive_threshold():
     Test if the non-adaptive threshold gets used in the F1 score computation when
     adaptive thresholding is disabled and no normalization is used.
     """
-    config = get_test_configurable_parameters(model_config_path="anomalib/models/padim/config.yaml")
+    config = get_test_configurable_parameters(config_path="anomalib/models/padim/config.yaml")
 
     config.model.normalization_method = "none"
     config.model.threshold.adaptive = False

tools/benchmarking/README.md

@@ -12,7 +12,7 @@ Note: To collect memory read/write numbers, run the script with sudo privileges.
 ```
 sudo -E ./train.sh    # Train STFPM on MVTec AD leather
 
-sudo -E ./train.sh --model_config_path <path/to/model/config.yaml>
+sudo -E ./train.sh --config <path/to/model/config.yaml>
 
 sudo -E ./train.sh --model stfpm
 ```

tools/hpo/wandb_sweep.py

@@ -16,9 +16,10 @@
 
 from argparse import ArgumentParser
 from pathlib import Path
+from typing import Union
 
 import pytorch_lightning as pl
-from omegaconf import DictConfig, OmegaConf
+from omegaconf import DictConfig, ListConfig, OmegaConf
 from pytorch_lightning import seed_everything
 from pytorch_lightning.loggers import WandbLogger
 from utils import flatten_hpo_params
@@ -38,12 +39,14 @@ class WandbSweep:
         sweep_config (DictConfig): Sweep configuration.
     """
 
-    def __init__(self, config: DictConfig, sweep_config: DictConfig) -> None:
+    def __init__(self, config: Union[DictConfig, ListConfig], sweep_config: Union[DictConfig, ListConfig]) -> None:
         self.config = config
         self.sweep_config = sweep_config
         self.observation_budget = sweep_config.observation_budget
         if "observation_budget" in self.sweep_config.keys():
-            self.sweep_config.pop("observation_budget")
+            # this instance check is to silence mypy.
+            if isinstance(self.sweep_config, DictConfig):
+                self.sweep_config.pop("observation_budget")
 
     def run(self):
         """Run the sweep."""
@@ -86,7 +89,7 @@ def get_args():
 
 if __name__ == "__main__":
     args = get_args()
-    model_config = get_configurable_parameters(model_name=args.model, model_config_path=args.model_config)
+    model_config = get_configurable_parameters(model_name=args.model, config_path=args.model_config)
     hpo_config = OmegaConf.load(args.sweep_config)
 
     if model_config.project.seed != 0:

tools/inference.py

@@ -37,7 +37,7 @@ def get_args() -> Namespace:
         Namespace: List of arguments.
     """
     parser = ArgumentParser()
-    parser.add_argument("--model_config_path", type=Path, required=True, help="Path to a model config file")
+    parser.add_argument("--config", type=Path, required=True, help="Path to a model config file")
     parser.add_argument("--weight_path", type=Path, required=True, help="Path to a model weights")
     parser.add_argument("--image_path", type=Path, required=True, help="Path to an image to infer.")
     parser.add_argument("--save_path", type=Path, required=False, help="Path to save the output image.")
@@ -75,7 +75,7 @@ def stream() -> None:
     # 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()
-    config = get_configurable_parameters(model_config_path=args.model_config_path)
+    config = get_configurable_parameters(config_path=args.config)
 
     # Get the inferencer. We use .ckpt extension for Torch models and (onnx, bin)
     # for the openvino models.

tools/test.py

@@ -14,6 +14,7 @@
 # See the License for the specific language governing permissions
 # and limitations under the License.
 
+import warnings
 from argparse import ArgumentParser, Namespace
 
 from pytorch_lightning import Trainer
@@ -32,11 +33,21 @@ def get_args() -> Namespace:
     """
     parser = ArgumentParser()
     parser.add_argument("--model", type=str, default="stfpm", help="Name of the algorithm to train/test")
+    # --model_config_path will be deprecated in 0.2.8 and removed in 0.2.9
     parser.add_argument("--model_config_path", type=str, required=False, help="Path to a model config file")
+    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")
-    parser.add_argument("--openvino", type=bool, default=False)
 
-    return parser.parse_args()
+    args = parser.parse_args()
+    if args.model_config_path is not None:
+        warnings.warn(
+            message="--model_config_path will be deprecated in v0.2.8 and removed in v0.2.9. Use --config instead.",
+            category=DeprecationWarning,
+            stacklevel=2,
+        )
+        args.config = args.model_config_path
+
+    return args
 
 
 def test():
@@ -47,9 +58,8 @@ def test():
     args = get_args()
     config = get_configurable_parameters(
         model_name=args.model,
-        model_config_path=args.model_config_path,
+        config_path=args.config,
         weight_file=args.weight_file,
-        openvino=args.openvino,
     )
 
     datamodule = get_datamodule(config)

tools/train.py

@@ -19,6 +19,7 @@
 # See the License for the specific language governing permissions
 # and limitations under the License.
 
+import warnings
 from argparse import ArgumentParser, Namespace
 
 from pytorch_lightning import Trainer, seed_everything
@@ -38,15 +39,26 @@ def get_args() -> Namespace:
     """
     parser = ArgumentParser()
     parser.add_argument("--model", type=str, default="padim", help="Name of the algorithm to train/test")
+    # --model_config_path will be deprecated in 0.2.8 and removed in 0.2.9
     parser.add_argument("--model_config_path", type=str, required=False, help="Path to a model config file")
+    parser.add_argument("--config", type=str, required=False, help="Path to a model config file")
 
-    return parser.parse_args()
+    args = parser.parse_args()
+    if args.model_config_path is not None:
+        warnings.warn(
+            message="--model_config_path will be deprecated in v0.2.8 and removed in v0.2.9. Use --config instead.",
+            category=DeprecationWarning,
+            stacklevel=2,
+        )
+        args.config = args.model_config_path
+
+    return args
 
 
 def train():
     """Train an anomaly classification or segmentation model based on a provided configuration file."""
     args = get_args()
-    config = get_configurable_parameters(model_name=args.model, model_config_path=args.model_config_path)
+    config = get_configurable_parameters(model_name=args.model, config_path=args.config)
 
     if config.project.seed != 0:
         seed_everything(config.project.seed)