Enable type checks

.mypy.ini

@@ -0,0 +1,28 @@
+[mypy]
+python_version = 3.8
+ignore_missing_imports = True
+show_error_codes = True
+
+[mypy-mmdet.apis]
+ignore_errors = 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

.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"

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

@@ -25,20 +25,20 @@
 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,
-    set_values_as_default,
+    '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',
+    'set_values_as_default',
     ]

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

@@ -205,7 +205,8 @@ def hook(module, input, output):
 
     @staticmethod
     def _infer_detector(model: torch.nn.Module, config: Config, dataset: DatasetEntity,
-                        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)
@@ -224,7 +225,7 @@ def _infer_detector(model: torch.nn.Module, config: Config, dataset: DatasetEnti
         # Use a single gpu for testing. Set in both mm_val_dataloader and eval_model
         eval_predictions = single_gpu_test(eval_model, mm_val_dataloader, show=False)
 
-        metric = None
+        metric = 0.0
         if eval:
             metric = mm_val_dataset.evaluate(eval_predictions, metric=metric_name)[metric_name]
         return eval_predictions, metric

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
@@ -143,7 +143,7 @@ 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)
 
@@ -183,7 +183,7 @@ 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
@@ -46,7 +47,7 @@
 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'
@@ -57,7 +58,8 @@ 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)
@@ -106,7 +108,7 @@ def __init__(
         self.confidence_threshold = float(hparams.postprocessing.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

@@ -16,7 +16,7 @@
 import logging
 import os
 from collections import defaultdict
-from typing import List, Optional
+from typing import DefaultDict, Dict, List, Optional
 
 import torch
 from ote_sdk.entities.datasets import DatasetEntity
@@ -40,7 +40,7 @@
 
 class OTEDetectionTrainingTask(OTEDetectionInferenceTask, ITrainingTask):
 
-    def _generate_training_metrics_group(self, learning_curves) -> Optional[List[MetricsGroup]]:
+    def _generate_training_metrics_group(self, learning_curves: Dict[str, OTELoggerHook.Curve]) -> List[MetricsGroup]:
         """
         Parses the mmdetection logs to get metrics from the latest training run
 
@@ -77,7 +77,7 @@ def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_paramet
         old_model = copy.deepcopy(self._model)
 
         # Evaluate model performance before training.
-        _, initial_performance = self._infer_detector(self._model, config, val_dataset, True)
+        initial_performance = self._infer_detector(self._model, config, val_dataset, True)[1]
         logger.info(f'initial_performance = {initial_performance}')
 
         # Check for stop signal between pre-eval and training. If training is cancelled at this point,
@@ -96,7 +96,7 @@ def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_paramet
         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)
         self._training_work_dir = training_config.work_dir
         mm_train_dataset = build_dataset(training_config.data.train)
@@ -120,7 +120,7 @@ def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_paramet
         self._model.load_state_dict(best_checkpoint['state_dict'])
 
         # Evaluate model performance after training.
-        _, final_performance = self._infer_detector(self._model, config, val_dataset, True)
+        final_performance = self._infer_detector(self._model, config, val_dataset, True)[1]
         improved = final_performance > initial_performance
 
         # Return a new model if model has improved, or there is no model yet.

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/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

@@ -20,7 +20,7 @@
 from collections import namedtuple, OrderedDict
 from copy import deepcopy
 from pprint import pformat
-from typing import Optional, Union
+from typing import Optional, Tuple, Union
 
 import pytest
 import yaml
@@ -43,7 +43,7 @@
 
 logger = logging.getLogger(__name__)
 
-def DATASET_PARAMETERS_FIELDS():
+def DATASET_PARAMETERS_FIELDS() -> Tuple[str, ...]:
     return ('annotations_train',
             'images_train_dir',
             'annotations_val',
@@ -53,7 +53,7 @@ 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):