Support Python 3.11

Support Python 3.11

(required to change hydra-core to 1.3)

.github/workflows/tests.yaml

@@ -14,7 +14,7 @@ jobs:
     if: github.event_name == 'pull_request'
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
     steps:
     - name: Checkout
       uses: actions/checkout@v3
@@ -36,7 +36,7 @@ jobs:
     if: github.event_name == 'push'
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
     steps:
     - name: Checkout
       uses: actions/checkout@v3

.gitignore

@@ -14,6 +14,8 @@ docs/build
 tmp.py
 tmp.ipynb
 *outputs*
+*.hydra*
+*predictions.json*
 
 # __________________________________
 

Makefile

@@ -59,15 +59,13 @@ wandb_login:
 
 .PHONY: run_all_tests
 run_all_tests: download_mock_dataset wandb_login
-	export PYTORCH_ENABLE_MPS_FALLBACK=1
-	pytest --disable-warnings -sv tests
+	export PYTORCH_ENABLE_MPS_FALLBACK=1; pytest --disable-warnings -sv tests
 	pytest --disable-warnings --doctest-modules --doctest-continue-on-failure -sv oml
 	$(JUPYTER_CMD) --execute pipelines/features_extraction/visualization.ipynb
 
 .PHONY: run_short_tests
 run_short_tests: download_mock_dataset
-	export PYTORCH_ENABLE_MPS_FALLBACK=1
-	pytest --disable-warnings -sv -m "not long" tests
+	export PYTORCH_ENABLE_MPS_FALLBACK=1; pytest --disable-warnings -sv -m "not long" tests
 	pytest --disable-warnings --doctest-modules --doctest-continue-on-failure -sv oml
 
 .PHONY: test_converters

README.md

@@ -8,6 +8,7 @@
 [![python](https://img.shields.io/badge/python_3.8-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
 [![python](https://img.shields.io/badge/python_3.9-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
 [![python](https://img.shields.io/badge/python_3.10-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
+[![python](https://img.shields.io/badge/python_3.11-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
 
 
 OML is a PyTorch-based framework to train and validate the models producing high-quality embeddings.

ci/requirements.txt

@@ -7,7 +7,7 @@ pillow>=8.2
 pandas>=1.0, <=1.5.2
 matplotlib>3.5.2, <3.6.2
 omegaconf>=2.0.5, <2.3.0
-hydra-core>=1.2.0, <1.3.0
+hydra-core==1.3.0
 python-dotenv>=0.17.0
 validators>=0.18.0
 gdown>=4.0

docs/readme/header.md

@@ -8,6 +8,7 @@
 [![python](https://img.shields.io/badge/python_3.8-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
 [![python](https://img.shields.io/badge/python_3.9-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
 [![python](https://img.shields.io/badge/python_3.10-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
+[![python](https://img.shields.io/badge/python_3.11-passing-success)](https://github.com/OML-Team/open-metric-learning/actions/workflows/tests.yaml/badge.svg?)
 
 
 OML is a PyTorch-based framework to train and validate the models producing high-quality embeddings.

oml/const.py

@@ -101,4 +101,6 @@ def get_cache_folder() -> Path:
 
 IMAGE_EXTENSIONS = ["jpg", "jpeg", "JPG", "JPEG", "png"]
 
-HYDRA_VERSION = "1.1"
+# hydra provides ability to set its behaviour for convinient backwards compatibility
+# no matter what the current version is
+HYDRA_BEHAVIOUR = "1.1"

pipelines/features_extraction/extractor_cars/predict_cars.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.predict import extractor_prediction_pipeline
 
 
-@hydra.main(config_path=".", config_name="predict_cars.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="predict_cars.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_prediction_pipeline(cfg)
 

pipelines/features_extraction/extractor_cars/train_cars.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.train import extractor_training_pipeline
 
 
-@hydra.main(config_path=".", config_name="train_cars.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="train_cars.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_training_pipeline(cfg)
 

pipelines/features_extraction/extractor_cars/validate_cars.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.validate import extractor_validation_pipeline
 
 
-@hydra.main(config_path=".", config_name="val_cars.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="val_cars.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_validation_pipeline(cfg)
 

pipelines/features_extraction/extractor_cub/predict_cub.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.predict import extractor_prediction_pipeline
 
 
-@hydra.main(config_path=".", config_name="predict_cub.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="predict_cub.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_prediction_pipeline(cfg)
 

pipelines/features_extraction/extractor_cub/train_cub.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.train import extractor_training_pipeline
 
 
-@hydra.main(config_path=".", config_name="train_cub.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="train_cub.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     print("Training model on SOP dataset.")
     extractor_training_pipeline(cfg)

pipelines/features_extraction/extractor_cub/validate_cub.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.validate import extractor_validation_pipeline
 
 
-@hydra.main(config_path=".", config_name="val_cub.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="val_cub.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_validation_pipeline(cfg)
 

pipelines/features_extraction/extractor_inshop/predict_inshop.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.predict import extractor_prediction_pipeline
 
 
-@hydra.main(config_path=".", config_name="predict_inshop.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="predict_inshop.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_prediction_pipeline(cfg)
 

pipelines/features_extraction/extractor_inshop/train_inshop.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.train import extractor_training_pipeline
 
 
-@hydra.main(config_path=".", config_name="train_inshop.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="train_inshop.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_training_pipeline(cfg)
 

pipelines/features_extraction/extractor_inshop/validate_inshop.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.validate import extractor_validation_pipeline
 
 
-@hydra.main(config_path=".", config_name="val_inshop.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="val_inshop.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_validation_pipeline(cfg)
 

pipelines/features_extraction/extractor_sop/predict_sop.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.predict import extractor_prediction_pipeline
 
 
-@hydra.main(config_path=".", config_name="predict_sop.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="predict_sop.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_prediction_pipeline(cfg)
 

pipelines/features_extraction/extractor_sop/train_sop.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.train import extractor_training_pipeline
 
 
-@hydra.main(config_path=".", config_name="train_sop.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="train_sop.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     print("Training model on SOP dataset.")
     extractor_training_pipeline(cfg)

pipelines/features_extraction/extractor_sop/validate_sop.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.validate import extractor_validation_pipeline
 
 
-@hydra.main(config_path=".", config_name="val_sop.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="val_sop.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_validation_pipeline(cfg)
 

pipelines/postprocessing/pairwise_postprocessing/train_extractor.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.train import extractor_training_pipeline
 
 
-@hydra.main(config_path=".", config_name="extractor_train.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="extractor_train.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_training_pipeline(cfg)
 

pipelines/postprocessing/pairwise_postprocessing/train_postprocessor.py

@@ -1,13 +1,13 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.train_postprocessor import (
     postprocessor_training_pipeline,  # type: ignore
 )
 
 
-@hydra.main(config_path=".", config_name="postprocessor_train.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="postprocessor_train.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     postprocessor_training_pipeline(cfg)
 

pipelines/postprocessing/pairwise_postprocessing/validate_extractor.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.validate import extractor_validation_pipeline
 
 
-@hydra.main(config_path=".", config_name="extractor_validate.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="extractor_validate.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_validation_pipeline(cfg)
 

pipelines/postprocessing/pairwise_postprocessing/validate_postprocessor.py

@@ -1,11 +1,11 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION
+from oml.const import HYDRA_BEHAVIOUR
 from oml.lightning.pipelines.validate import extractor_validation_pipeline
 
 
-@hydra.main(config_path=".", config_name="postprocessor_validate.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path=".", config_name="postprocessor_validate.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     extractor_validation_pipeline(cfg)
 

setup.py

@@ -55,6 +55,7 @@ def load_version() -> str:
         "Programming Language :: Python :: 3.8",
         "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.10",
+        "Programming Language :: Python :: 3.11",
         "Programming Language :: Python :: Implementation :: CPython",
     ],
     project_urls={

tests/test_oml/test_functional/test_metrics/synthetic.py

@@ -76,7 +76,7 @@ def generate_retrieval_case(
             # we guarantee that for each query there is at least one gallery which is not equal to query
             if sum(is_query_for_label) == 1:
                 # set another available idx as gallery
-                guaranted_galleries = random.sample(set(range(num_samples_for_label)) - {guaranted_query}, k=1)
+                guaranted_galleries = random.sample(list(set(range(num_samples_for_label)) - {guaranted_query}), k=1)
             else:
                 # We have at least 2 queries in this section
                 # To calculate metric for each query it's necessary to have minimum 1 gallery with another idx.

tests/test_runs/test_pipelines/predict.py

@@ -1,13 +1,13 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION, MOCK_DATASET_PATH
+from oml.const import HYDRA_BEHAVIOUR, MOCK_DATASET_PATH
 from oml.lightning.pipelines.predict import extractor_prediction_pipeline
 from oml.utils.download_mock_dataset import download_mock_dataset
 from oml.utils.misc import dictconfig_to_dict
 
 
-@hydra.main(config_path="configs", config_name="predict.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path="configs", config_name="predict.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     cfg = dictconfig_to_dict(cfg)
     download_mock_dataset(MOCK_DATASET_PATH)

tests/test_runs/test_pipelines/train.py

@@ -1,13 +1,13 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION, MOCK_DATASET_PATH
+from oml.const import HYDRA_BEHAVIOUR, MOCK_DATASET_PATH
 from oml.lightning.pipelines.train import extractor_training_pipeline
 from oml.utils.download_mock_dataset import download_mock_dataset
 from oml.utils.misc import dictconfig_to_dict
 
 
-@hydra.main(config_path="configs", config_name="train.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path="configs", config_name="train.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     cfg = dictconfig_to_dict(cfg)
     download_mock_dataset(MOCK_DATASET_PATH)

tests/test_runs/test_pipelines/train_arcface_with_categories.py

@@ -1,13 +1,13 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION, MOCK_DATASET_PATH
+from oml.const import HYDRA_BEHAVIOUR, MOCK_DATASET_PATH
 from oml.lightning.pipelines.train import extractor_training_pipeline
 from oml.utils.download_mock_dataset import download_mock_dataset
 from oml.utils.misc import dictconfig_to_dict
 
 
-@hydra.main(config_path="configs", config_name="train_arcface_with_categories.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path="configs", config_name="train_arcface_with_categories.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     cfg = dictconfig_to_dict(cfg)
     download_mock_dataset(MOCK_DATASET_PATH)

tests/test_runs/test_pipelines/train_postprocessor.py

@@ -1,13 +1,13 @@
 import hydra
 from omegaconf import DictConfig
 
-from oml.const import HYDRA_VERSION, MOCK_DATASET_PATH
+from oml.const import HYDRA_BEHAVIOUR, MOCK_DATASET_PATH
 from oml.lightning.pipelines.train_postprocessor import postprocessor_training_pipeline
 from oml.utils.download_mock_dataset import download_mock_dataset
 from oml.utils.misc import dictconfig_to_dict
 
 
-@hydra.main(config_path="configs", config_name="train_postprocessor.yaml", version_base=HYDRA_VERSION)
+@hydra.main(config_path="configs", config_name="train_postprocessor.yaml", version_base=HYDRA_BEHAVIOUR)
 def main_hydra(cfg: DictConfig) -> None:
     cfg = dictconfig_to_dict(cfg)
     download_mock_dataset(MOCK_DATASET_PATH)