Enable type checks

.mypy.ini

@@ -0,0 +1,51 @@
+[mypy]
+python_version = 3.8
+ignore_missing_imports = True
+show_error_codes = True
+check_untyped_defs = True
+strict = True
+
+[mypy-mmdet.core.*]
+ignore_errors = True
+
+[mypy-mmdet.datasets.*]
+ignore_errors = True
+
+[mypy-mmdet.integration.*]
+ignore_errors = True
+
+[mypy-mmdet.models.*]
+ignore_errors = True
+
+[mypy-mmdet.ops.*]
+ignore_errors = True
+
+[mypy-mmdet.parallel.*]
+ignore_errors = True
+
+[mypy-mmdet.utils.*]
+ignore_errors = True
+
+[mypy-mmdet]
+ignore_errors = True
+
+[mypy-mmdet.version]
+ignore_errors = True
+
+[mypy-mmdet.apis]
+ignore_errors = True
+
+[mypy-mmdet.apis.train]
+ignore_errors = True
+
+[mypy-mmdet.apis.test]
+ignore_errors = True
+
+[mypy-mmdet.apis.export]
+ignore_errors = True
+
+[mypy-mmdet.apis.inference]
+ignore_errors = True
+
+[mypy-mmdet.apis.fake_input]
+ignore_errors = True

.pre-commit-config.yaml

@@ -1,40 +1,47 @@
 repos:
-  - repo: https://gitlab.com/pycqa/flake8.git
-    rev: 3.8.3
+  # - repo: https://gitlab.com/pycqa/flake8.git
+  #   rev: 3.8.3
+  #   hooks:
+  #     - id: flake8
+  # - repo: https://github.com/asottile/seed-isort-config
+  #   rev: v2.2.0
+  #   hooks:
+  #     - id: seed-isort-config
+  # - repo: https://github.com/timothycrosley/isort
+  #   rev: 4.3.21
+  #   hooks:
+  #     - id: isort
+  # - repo: https://github.com/pre-commit/mirrors-yapf
+  #   rev: v0.30.0
+  #   hooks:
+  #     - id: yapf
+  # - repo: https://github.com/pre-commit/pre-commit-hooks
+  #   rev: v3.1.0
+  #   hooks:
+  #     - id: trailing-whitespace
+  #     - id: check-yaml
+  #     - id: end-of-file-fixer
+  #     - id: requirements-txt-fixer
+  #     - id: double-quote-string-fixer
+  #     - id: check-merge-conflict
+  #     - id: fix-encoding-pragma
+  #       args: ["--remove"]
+  #     - id: mixed-line-ending
+  #       args: ["--fix=lf"]
+  # - repo: https://github.com/jumanjihouse/pre-commit-hooks
+  #   rev: 2.1.4
+  #   hooks:
+  #     - id: markdownlint
+  #       args: ["-r", "~MD002,~MD013,~MD024,~MD029,~MD033,~MD034,~MD036"]
+  # - repo: https://github.com/myint/docformatter
+  #   rev: v1.3.1
+  #   hooks:
+  #     - id: docformatter
+  #       args: ["--in-place", "--wrap-descriptions", "79"]
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: 'v0.812'
     hooks:
-      - id: flake8
-  - repo: https://github.com/asottile/seed-isort-config
-    rev: v2.2.0
-    hooks:
-      - id: seed-isort-config
-  - repo: https://github.com/timothycrosley/isort
-    rev: 4.3.21
-    hooks:
-      - id: isort
-  - repo: https://github.com/pre-commit/mirrors-yapf
-    rev: v0.30.0
-    hooks:
-      - id: yapf
-  - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.1.0
-    hooks:
-      - id: trailing-whitespace
-      - id: check-yaml
-      - id: end-of-file-fixer
-      - id: requirements-txt-fixer
-      - id: double-quote-string-fixer
-      - id: check-merge-conflict
-      - id: fix-encoding-pragma
-        args: ["--remove"]
-      - id: mixed-line-ending
-        args: ["--fix=lf"]
-  - repo: https://github.com/jumanjihouse/pre-commit-hooks
-    rev: 2.1.4
-    hooks:
-      - id: markdownlint
-        args: ["-r", "~MD002,~MD013,~MD024,~MD029,~MD033,~MD034,~MD036"]
-  - repo: https://github.com/myint/docformatter
-    rev: v1.3.1
-    hooks:
-      - id: docformatter
-        args: ["--in-place", "--wrap-descriptions", "79"]
+      - id: mypy
+        args: ["--config-file=.mypy.ini"]
+        additional_dependencies: [numpy==1.19.5, types-PyYAML, attrs==21.2.*, types-requests, types-Deprecated, types-docutils, types_futures, types-python-dateutil]
+        exclude: "ci|configs|data|demo|docker|docs|experiments|resources|tools|.dev_scripts|tests|setup.py"

mmdet/apis/ote/apis/detection/__init__.py

@@ -24,19 +24,19 @@
 from .train_task import OTEDetectionTrainingTask
 
 __all__ = [
-    config_from_string,
-    config_to_string,
-    generate_label_schema,
-    get_task_class,
-    load_template,
-    OpenVINODetectionTask,
-    OTEDetectionConfig,
-    OTEDetectionInferenceTask,
-    OTEDetectionNNCFTask,
-    OTEDetectionTrainingTask,
-    patch_config,
-    prepare_for_testing,
-    prepare_for_training,
-    save_config_to_file,
-    set_hyperparams,
-    ]
+    'config_from_string',
+    'config_to_string',
+    'generate_label_schema',
+    'get_task_class',
+    'load_template',
+    'OpenVINODetectionTask',
+    'OTEDetectionConfig',
+    'OTEDetectionInferenceTask',
+    'OTEDetectionNNCFTask',
+    'OTEDetectionTrainingTask',
+    'patch_config',
+    'prepare_for_testing',
+    'prepare_for_training',
+    'save_config_to_file',
+    'set_hyperparams',
+]

mmdet/apis/ote/apis/detection/inference_task.py

@@ -221,7 +221,7 @@ def hook(module, input, output):
 
     @staticmethod
     def _infer_detector(model: torch.nn.Module, config: Config, dataset: DatasetEntity, dump_features: bool = False,
-                        eval: Optional[bool] = False, metric_name: Optional[str] = 'mAP') -> Tuple[List, float]:
+                        eval: bool = False, metric_name: str = 'mAP') -> Tuple[List, float]:
         model.eval()
         test_config = prepare_for_testing(config, dataset)
         mm_val_dataset = build_dataset(test_config.data.test)
@@ -256,7 +256,7 @@ def dummy_dump_features_hook(mod, inp, out):
                     result = eval_model(return_loss=False, rescale=True, **data)
                 eval_predictions.extend(result)
 
-        metric = None
+        metric = 0.0
         if eval:
             metric = mm_val_dataset.evaluate(eval_predictions, metric=metric_name)[metric_name]
 

mmdet/apis/ote/apis/detection/nncf_task.py

@@ -17,7 +17,7 @@
 import logging
 import os
 from collections import defaultdict
-from typing import Optional
+from typing import DefaultDict, Optional
 
 import torch
 from ote_sdk.configuration import cfg_helper
@@ -189,7 +189,7 @@ def optimize(
         else:
             update_progress_callback = default_progress_callback
         time_monitor = TrainingProgressCallback(update_progress_callback)
-        learning_curves = defaultdict(OTELoggerHook.Curve)
+        learning_curves: DefaultDict[str, OTELoggerHook.Curve] = defaultdict(OTELoggerHook.Curve)
         training_config = prepare_for_training(config, train_dataset, val_dataset, time_monitor, learning_curves)
         mm_train_dataset = build_dataset(training_config.data.train)
 
@@ -235,7 +235,7 @@ def save_model(self, output_model: ModelEntity):
         hyperparams_str = ids_to_strings(cfg_helper.convert(hyperparams, dict, enum_to_str=True))
         labels = {label.name: label.color.rgb_tuple for label in self._labels}
         modelinfo = {
-            'compression_state': self._compression_ctrl.get_compression_state(),
+            'compression_state': self._compression_ctrl.get_compression_state(),  # type: ignore  # FIXME.
             'meta': {
                 'config': self._config,
                 'nncf_enable_compression': True,

mmdet/apis/ote/apis/detection/openvino_task.py

@@ -25,6 +25,7 @@
 from compression.graph import load_model, save_model
 from compression.graph.model_utils import compress_model_weights, get_nodes_by_type
 from compression.pipeline.initializer import create_pipeline
+from openvino.inference_engine import ExecutableNetwork
 from ote_sdk.entities.annotation import Annotation, AnnotationSceneEntity, AnnotationSceneKind
 from ote_sdk.entities.datasets import DatasetEntity
 from ote_sdk.entities.inference_parameters import InferenceParameters, default_progress_callback
@@ -52,7 +53,7 @@
 logger = logging.getLogger(__name__)
 
 
-def get_output(net, outputs, name):
+def get_output(net: ExecutableNetwork, outputs: Dict[str, np.ndarray], name: str) -> np.ndarray:
     try:
         key = net.get_ov_name_for_tensor(name)
         assert key in outputs, f'"{key}" is not a valid output identifier'
@@ -63,7 +64,8 @@ def get_output(net, outputs, name):
     return outputs[key]
 
 
-def extract_detections(output, net, input_size):
+def extract_detections(output: Dict[str, np.ndarray], net: ExecutableNetwork,
+                       input_size: Tuple[int, int]) -> Dict[str, np.ndarray]:
     if 'detection_out' in output:
         detection_out = output['detection_out']
         output['labels'] = detection_out[0, 0, :, 1].astype(np.int32)
@@ -114,7 +116,7 @@ def __init__(
         self.confidence_threshold = confidence_threshold
 
     @staticmethod
-    def resize_image(image: np.ndarray, size: Tuple[int], keep_aspect_ratio: bool = False) -> np.ndarray:
+    def resize_image(image: np.ndarray, size: Tuple[int, int], keep_aspect_ratio: bool = False) -> np.ndarray:
         if not keep_aspect_ratio:
             resized_frame = cv2.resize(image, size)
         else:

mmdet/apis/ote/apis/detection/train_task.py

@@ -18,7 +18,7 @@
 import os
 from collections import defaultdict
 from glob import glob
-from typing import List, Optional
+from typing import DefaultDict, Dict, List, Optional
 
 import torch
 from ote_sdk.configuration import cfg_helper
@@ -45,7 +45,7 @@
 
 class OTEDetectionTrainingTask(OTEDetectionInferenceTask, ITrainingTask):
 
-    def _generate_training_metrics(self, learning_curves, map) -> Optional[List[MetricsGroup]]:
+    def _generate_training_metrics(self, learning_curves: Dict[str, OTELoggerHook.Curve], map: float) -> List[MetricsGroup]:
         """
         Parses the mmdetection logs to get metrics from the latest training run
 
@@ -97,7 +97,7 @@ def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_paramet
         if train_parameters is not None:
             update_progress_callback = train_parameters.update_progress
         time_monitor = TrainingProgressCallback(update_progress_callback)
-        learning_curves = defaultdict(OTELoggerHook.Curve)
+        learning_curves: DefaultDict[str, OTELoggerHook.Curve] = defaultdict(OTELoggerHook.Curve)
         training_config = prepare_for_training(config, train_dataset, val_dataset, time_monitor, learning_curves)
         self._training_work_dir = training_config.work_dir
         mm_train_dataset = build_dataset(training_config.data.train)

mmdet/apis/ote/extension/datasets/__init__.py

@@ -14,4 +14,4 @@
 
 from .mmdataset import OTEDataset, get_annotation_mmdet_format
 
-__all__ = [OTEDataset, get_annotation_mmdet_format]
+__all__ = ['OTEDataset', 'get_annotation_mmdet_format']

mmdet/apis/ote/extension/datasets/mmdataset.py

@@ -13,7 +13,7 @@
 # and limitations under the License.
 
 from copy import deepcopy
-from typing import List
+from typing import List, Sequence, Optional
 
 import numpy as np
 from ote_sdk.entities.dataset_item import DatasetItemEntity
@@ -88,7 +88,7 @@ class _DataInfoProxy:
         forwards data access operations to ote_dataset and converts the dataset items to the view
         convenient for mmdetection.
         """
-        def __init__(self, ote_dataset, classes):
+        def __init__(self, ote_dataset: DatasetEntity, classes: Optional[Sequence[str]]):
             self.ote_dataset = ote_dataset
             self.CLASSES = classes
 
@@ -113,7 +113,7 @@ def __getitem__(self, index):
             return data_info
 
     def __init__(self, ote_dataset: DatasetEntity, pipeline, classes=None, test_mode: bool = False):
-        self.ote_dataset = ote_dataset
+        self.ote_dataset: DatasetEntity = ote_dataset
         self.test_mode = test_mode
         self.CLASSES = self.get_classes(classes)
 

mmdet/apis/ote/extension/utils/__init__.py

@@ -17,6 +17,6 @@
 from .pipelines import LoadImageFromOTEDataset, LoadAnnotationFromOTEDataset
 from .runner import EpochRunnerWithCancel
 
-__all__ = [CancelTrainingHook, FixedMomentumUpdaterHook, LoadImageFromOTEDataset, EpochRunnerWithCancel,
-           LoadAnnotationFromOTEDataset, OTELoggerHook, OTEProgressHook, EarlyStoppingHook,
-           ReduceLROnPlateauLrUpdaterHook]
+__all__ = ['CancelTrainingHook', 'FixedMomentumUpdaterHook', 'LoadImageFromOTEDataset', 'EpochRunnerWithCancel',
+           'LoadAnnotationFromOTEDataset', 'OTELoggerHook', 'OTEProgressHook', 'EarlyStoppingHook',
+           'ReduceLROnPlateauLrUpdaterHook']

tests/conftest.py

@@ -10,7 +10,7 @@
     _e2e_pytest_addoption = None
     pass
 
-import config
+import e2e_config
 
 def pytest_addoption(parser):
     if _e2e_pytest_addoption:

tests/test_ote_training.py

@@ -21,7 +21,7 @@
 from collections import namedtuple, OrderedDict
 from copy import deepcopy
 from pprint import pformat
-from typing import List, Optional, Union
+from typing import List, Optional, Tuple, Union
 
 import pytest
 import yaml
@@ -34,10 +34,8 @@
 from ote_sdk.entities.model import (
     ModelEntity,
     ModelFormat,
-    ModelPrecision,
     ModelStatus,
     ModelOptimizationType,
-    OptimizationMethod,
 )
 from ote_sdk.entities.model_template import parse_model_template, TargetDevice
 from ote_sdk.entities.optimization_parameters import OptimizationParameters
@@ -53,7 +51,7 @@
 
 logger = logging.getLogger(__name__)
 
-def DATASET_PARAMETERS_FIELDS():
+def DATASET_PARAMETERS_FIELDS() -> Tuple[str, ...]:
     return ('annotations_train',
             'images_train_dir',
             'annotations_val',
@@ -63,7 +61,7 @@ def DATASET_PARAMETERS_FIELDS():
             )
 
 ROOT_PATH_KEY = '_root_path'
-DatasetParameters = namedtuple('DatasetParameters', DATASET_PARAMETERS_FIELDS())
+DatasetParameters = namedtuple('DatasetParameters', DATASET_PARAMETERS_FIELDS())  # type: ignore
 
 @pytest.fixture
 def dataset_definitions_fx(request):
@@ -659,7 +657,7 @@ class OTETestStage:
             time the stage is called the exception is re-raised.
     """
     def __init__(self, action: BaseOTETestAction,
-                 depends_stages: Optional[List['OTETestStage']]=None):
+                 depends_stages: Optional[List['OTETestStage']] = None):
         self.was_processed = False
         self.stored_exception = None
         self.action = action