Fix optimization feature backward compatibility issue (#2141)

Temporary disable quantization for 2 models due to Geti project upgrade issue

Signed-off-by: Songki Choi <[email protected]>

Author: Songki Choi

otx/algorithms/common/tasks/nncf_task.py

@@ -112,7 +112,12 @@ def _set_attributes_by_hyperparams(self):
             self._optimization_methods = [OptimizationMethod.FILTER_PRUNING]
             self._precision = [ModelPrecision.FP32]
             return
-        raise RuntimeError("Not selected optimization algorithm")
+        # FIXEME: Error rasing should be re-enabled after Geti issue resolved
+        # raise RuntimeError("Not selected optimization algorithm")
+        logger.warning("Not selected optimization algorithm. Defaults to quantization")
+        self._nncf_preset = "nncf_quantization"
+        self._optimization_methods = [OptimizationMethod.QUANTIZATION]
+        self._precision = [ModelPrecision.INT8]
 
     def _init_train_data_cfg(self, dataset: DatasetEntity):
         logger.info("init data cfg.")

otx/algorithms/detection/configs/instance_segmentation/efficientnetb2b_maskrcnn/template.yaml

@@ -40,7 +40,7 @@ hyper_parameters:
         default_value: 1
     nncf_optimization:
       enable_quantization:
-        default_value: true
+        default_value: false
       enable_pruning:
         default_value: false
       pruning_supported:

otx/algorithms/segmentation/configs/ocr_lite_hrnet_x_mod3/template.yaml

@@ -39,7 +39,7 @@ hyper_parameters:
         default_value: 300
     nncf_optimization:
       enable_quantization:
-        default_value: true
+        default_value: false
       enable_pruning:
         default_value: false
       pruning_supported: