Patch release 0.5.1

CHANGELOG.md

@@ -4,16 +4,20 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
-## [Unreleased]
+## [v0.5.1] - 2023-05-24
 
 ### Added
 
 ### Changed
 
+- Rename `metadata_path` to `metadata` in `OpenvinoInferencer` in https://github.com/openvinotoolkit/anomalib/pull/1101
+
 ### Deprecated
 
 ###  Fixed
 
+- Fix `init_state_dict` bug in `wrap_nncf_model` in https://github.com/openvinotoolkit/anomalib/pull/1101
+
 ## [v0.5.0] - 2023-05-09
 
 ### Added

pyproject.toml

@@ -73,7 +73,7 @@ show_error_codes = true
 
 
 [[tool.mypy.overrides]]
-module = "torch.*"
+module = ["torch.*", "wandb.*"]
 follow_imports = "skip"
 follow_imports_for_stubs = true
 

src/anomalib/__init__.py

@@ -3,4 +3,4 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-__version__ = "1.0.0dev"
+__version__ = "0.5.1"

src/anomalib/deploy/inferencers/openvino_inferencer.py

@@ -19,31 +19,30 @@
 from .base_inferencer import Inferencer
 
 if find_spec("openvino") is not None:
-    from openvino.inference_engine import (  # type: ignore  # pylint: disable=no-name-in-module
-        IECore,
-    )
+    from openvino.inference_engine import IECore  # type: ignore  # pylint: disable=no-name-in-module
 
 
 class OpenVINOInferencer(Inferencer):
     """OpenVINO implementation for the inference.
 
     Args:
         path (str | Path): Path to the openvino onnx, xml or bin file.
-        metadata_path (str | Path, optional): Path to metadata file. Defaults to None.
+        metadata_path (str | Path | dict, optional): Path to metadata file or a dict object defining the
+            metadata. Defaults to None.
         device (str | None, optional): Device to run the inference on. Defaults to "CPU".
         task (TaskType | None, optional): Task type. Defaults to None.
     """
 
     def __init__(
         self,
         path: str | Path | tuple[bytes, bytes],
-        metadata_path: str | Path | None = None,
+        metadata: str | Path | dict | None = None,
         device: str | None = "CPU",
         task: str | None = None,
     ) -> None:
         self.device = device
         self.input_blob, self.output_blob, self.network = self.load_model(path)
-        self.metadata = super()._load_metadata(metadata_path)
+        self.metadata = metadata if isinstance(metadata, dict) else super()._load_metadata(metadata)
         self.task = TaskType(task) if task else TaskType(self.metadata["task"])
 
     def load_model(self, path: str | Path | tuple[bytes, bytes]):

src/anomalib/utils/callbacks/nncf/callback.py

@@ -52,7 +52,10 @@ def setup(self, trainer: pl.Trainer, pl_module: pl.LightningModule, stage: str |
         config = register_default_init_args(self.config, init_loader)
 
         self.nncf_ctrl, pl_module.model = wrap_nncf_model(
-            model=pl_module.model, config=config, dataloader=trainer.datamodule.train_dataloader()  # type: ignore
+            model=pl_module.model,
+            config=config,
+            dataloader=trainer.datamodule.train_dataloader(),  # type: ignore
+            init_state_dict=None,  # type: ignore
         )
 
     def on_train_batch_start(

src/anomalib/utils/sweep/helpers/inference.py

@@ -61,7 +61,7 @@ def get_openvino_throughput(model_path: str | Path, test_dataset: Dataset) -> fl
 
     inferencer = OpenVINOInferencer(
         path=model_path / "weights" / "openvino" / "model.xml",
-        metadata_path=model_path / "weights" / "openvino" / "metadata.json",
+        metadata=model_path / "weights" / "openvino" / "metadata.json",
     )
     start_time = time.time()
     for image_path in test_dataset.samples.image_path:

tools/inference/openvino_inference.py

@@ -71,7 +71,7 @@ def infer(args: Namespace) -> None:
         args (Namespace): The arguments from the command line.
     """
     # Get the inferencer.
-    inferencer = OpenVINOInferencer(path=args.weights, metadata_path=args.metadata, device=args.device)
+    inferencer = OpenVINOInferencer(path=args.weights, metadata=args.metadata, device=args.device)
     visualizer = Visualizer(mode=args.visualization_mode, task=args.task)
 
     filenames = get_image_filenames(path=args.input)