Merge pull request #1102 from openvinotoolkit/releases/v0.2.0-sc1.1

Merge back OTE v0.2.0 release fixes

Author: Songki Choi

CHANGELOG.md

@@ -2,10 +2,29 @@
 
 All notable changes to this project will be documented in this file.
 
+## \[v0.2.0\]
+### Added
+* Model Preparation Algorithm (MPA), a newly introduced OTE Algorithm backend for advanced transfer learning
+  * Class-Incremental Learning support for OTE models
+    * Image Classification
+    * Object Detection
+    * Semantic Segmentation
+* Object counting & Rotated object detection are added to Object Detection backend
+* Increased support for NNCF / FP16 / HPO
+* Ignored label support
+* Stop training on NaN losses
+
+
+### Changed
+* Major refactoring
+  * Tasks & model templates had been moved to OTE repo from each OTE Algorithm backend
+
+
 ## \[v0.1.1\]
 ### Fixed
 * Some minor issues
 
+
 ## \[v0.1.0\]
 ### Added
 * OTE SDK, defines an interface which can be used by OTE CLI to access OTE Algorithms.
@@ -16,10 +35,3 @@ All notable changes to this project will be documented in this file.
   * Object Detection
   * Semantic Segmentation
 
-## \[v0.2.0\]
-### Added
-* Model Preparation Algorithm (MPA), a newly introduced OTE Algorithm backend for advanced transfer learning
-  * Class-Incremental Learning support for OTE models
-    * Image Classification
-    * Object Detection
-    * Semantic Segmentation

external/deep-object-reid/submodule

@@ -157,3 +157,4 @@
     dict(type='EarlyStoppingHook', patience=10, metric='mAP',
          interval=1, priority=75, iteration_patience=0),
 ]
+fp16 = dict(loss_scale=512.)

external/mmdetection/configs/custom-counting-instance-seg/efficientnetb2b_maskrcnn/model.py

@@ -34,6 +34,13 @@
     ote_eval_testing,
     ote_train_testing,
     ote_export_testing,
+    nncf_optimize_testing,
+    nncf_export_testing,
+    nncf_eval_testing,
+    ote_hpo_testing,
+    nncf_eval_openvino_testing,
+    pot_optimize_testing,
+    pot_eval_testing
 )
 
 
@@ -111,3 +118,45 @@ def test_ote_eval_deployment(self, template):
     @pytest.mark.parametrize("template", templates, ids=templates_ids)
     def test_ote_demo_deployment(self, template):
         ote_demo_deployment_testing(template, root, ote_dir, args)
+
+    @e2e_pytest_component
+    @pytest.mark.parametrize("template", templates, ids=templates_ids)
+    def test_nncf_optimize(self, template):
+        if template.entrypoints.nncf is None:
+            pytest.skip("nncf entrypoint is none")
+
+        nncf_optimize_testing(template, root, ote_dir, args)
+
+    @e2e_pytest_component
+    @pytest.mark.parametrize("template", templates, ids=templates_ids)
+    def test_nncf_export(self, template):
+        if template.entrypoints.nncf is None:
+            pytest.skip("nncf entrypoint is none")
+
+        nncf_export_testing(template, root)
+
+    @e2e_pytest_component
+    @pytest.mark.parametrize("template", templates, ids=templates_ids)
+    def test_nncf_eval(self, template):
+        if template.entrypoints.nncf is None:
+            pytest.skip("nncf entrypoint is none")
+
+        nncf_eval_testing(template, root, ote_dir, args, threshold=0.001)
+
+    @e2e_pytest_component
+    @pytest.mark.parametrize("template", templates, ids=templates_ids)
+    def test_nncf_eval_openvino(self, template):
+        if template.entrypoints.nncf is None:
+            pytest.skip("nncf entrypoint is none")
+
+        nncf_eval_openvino_testing(template, root, ote_dir, args)
+
+    @e2e_pytest_component
+    @pytest.mark.parametrize("template", templates, ids=templates_ids)
+    def test_pot_optimize(self, template):
+        pot_optimize_testing(template, root, ote_dir, args)
+
+    @e2e_pytest_component
+    @pytest.mark.parametrize("template", templates, ids=templates_ids)
+    def test_pot_eval(self, template):
+        pot_eval_testing(template, root, ote_dir, args)

external/mmdetection/submodule

@@ -83,7 +83,7 @@ def test_reading_classification_cls_incr_model_template(self):
                                    'mobilenet_v3_large_1_cls_incr', 'mobilenet_v3_large_075_cls_incr',
                                    'mobilenet_v3_small_cls_incr']
         for model_template in classification_template:
-            parse_model_template(osp.join('configs', 'classification', model_template, 'template.yaml'))
+            parse_model_template(osp.join('configs', 'classification', model_template, 'template_experimental.yaml'))
 
     @staticmethod
     def generate_label_schema(not_empty_labels, multilabel=False):
@@ -103,7 +103,7 @@ def generate_label_schema(not_empty_labels, multilabel=False):
 
     @staticmethod
     def setup_configurable_parameters(template_dir, num_iters=10):
-        model_template = parse_model_template(osp.join(template_dir, 'template.yaml'))
+        model_template = parse_model_template(osp.join(template_dir, 'template_experimental.yaml'))
         hyper_parameters = create(model_template.hyper_parameters.data)
         hyper_parameters.learning_parameters.num_iters = num_iters
         return hyper_parameters, model_template
@@ -240,7 +240,7 @@ class MPADetAPI(unittest.TestCase):
     def test_reading_detection_cls_incr_model_template(self):
         detection_template = ['mobilenetv2_atss_cls_incr', 'resnet50_vfnet_cls_incr']
         for model_template in detection_template:
-            parse_model_template(osp.join('configs', 'detection', model_template, 'template.yaml'))
+            parse_model_template(osp.join('configs', 'detection', model_template, 'template_experimental.yaml'))
 
     def init_environment(
             self,
@@ -455,7 +455,7 @@ class MPASegAPI(unittest.TestCase):
     def test_reading_segmentation_cls_incr_model_template(self):
         segmentation_template = ['ocr-lite-hrnet-18-cls-incr']
         for model_template in segmentation_template:
-            parse_model_template(osp.join('configs', 'segmentation', model_template, 'template.yaml'))
+            parse_model_template(osp.join('configs', 'segmentation', model_template, 'template_experimental.yaml'))
 
     @staticmethod
     def generate_label_schema(label_names):
@@ -537,7 +537,7 @@ def init_environment(self, params, model_template, number_of_images=10):
 
     @staticmethod
     def setup_configurable_parameters(template_dir, num_iters=10):
-        model_template = parse_model_template(osp.join(template_dir, 'template.yaml'))
+        model_template = parse_model_template(osp.join(template_dir, 'template_experimental.yaml'))
 
         hyper_parameters = create(model_template.hyper_parameters.data)
         hyper_parameters.learning_parameters.learning_rate_fixed_iters = 0