Remove phantom initializations from base_custom_evaluator.py

tools/accuracy_checker/accuracy_checker/adapters/reidentification.py

@@ -113,7 +113,7 @@ class BertEmbeddingsAdapter(ReidAdapter):
 
     @classmethod
     def parameters(cls):
-        parameters = super(ReidAdapter, cls).parameters()
+        parameters = super().parameters()
         parameters.update({
             'target_out': StringField(optional=True, description='Target output layer name')
         })
@@ -123,5 +123,7 @@ def configure(self):
         self.joining_method = 'sum'
         self.target_out = self.get_value_from_config('target_out')
         self.keep_shape = True
-        self.mean_pooling = False # use 'sentence_similarity_pooling' postprocessor for proper mean pooling with attention to the input_mask
-        self.grn_workaround = False
+        # use 'sentence_similarity_pooling' postprocessor for proper mean pooling
+        # with attention to the input_mask
+        self.mean_pooling = False
+        self.grn_workaround = False

tools/accuracy_checker/accuracy_checker/dataset.py

@@ -599,7 +599,8 @@ def ibl_subset(pairs_set, subsample_set, ids):
 
         return list(subsample_set)
 
-    def store_first_annotation(self, annotation, identifier, dump_infer_data_path):
+    @staticmethod
+    def store_first_annotation(annotation, identifier, dump_infer_data_path):
         plain_annotation = {
             'class_name': annotation.__class__.__name__,
             **{

tools/accuracy_checker/accuracy_checker/evaluators/custom_evaluators/base_custom_evaluator.py

@@ -27,8 +27,6 @@ def __init__(self, dataset_config, launcher, orig_config,
                  preprocessor=None, postprocessor=None):
         self.dataset_config = dataset_config
         self.dataset = None
-        self.input_feeder = None
-        self.adapter = None
         self.preprocessing_executor = None
         self.preprocessor = preprocessor
         self.postprocessor = postprocessor

tools/accuracy_checker/accuracy_checker/evaluators/custom_evaluators/base_models.py

@@ -15,8 +15,8 @@
 """
 from pathlib import Path
 from collections import OrderedDict
-import numpy as np
 import pickle  # nosec B403  # disable import-pickle check
+import numpy as np
 from ...config import ConfigError
 from ...utils import get_path, parse_partial_shape, contains_any
 from ...logging import print_info

tools/accuracy_checker/accuracy_checker/evaluators/model_evaluator.py

@@ -343,8 +343,7 @@ def completion_callback(status_code, request_id):
         if progress_reporter:
             progress_reporter.finish()
 
-        if stored_predictions:
-            print_info("prediction objects are save to {}".format(stored_predictions))
+        self.stored_prediction_info(stored_predictions)
 
     def process_dataset_async_infer_queue(
         self, dataset_iterator, metric_config, progress_reporter, stored_predictions, **kwargs):
@@ -386,8 +385,7 @@ def completion_callback(request, user_data):
         if progress_reporter:
             progress_reporter.finish()
 
-        if stored_predictions:
-            print_info("prediction objects are save to {}".format(stored_predictions))
+        self.stored_prediction_info(stored_predictions)
 
     def process_dataset_sync(self, stored_predictions, progress_reporter, *args, **kwargs):
         if self.dataset is None:
@@ -434,8 +432,7 @@ def process_dataset_sync(self, stored_predictions, progress_reporter, *args, **k
         if progress_reporter:
             progress_reporter.finish()
 
-        if stored_predictions:
-            print_info("prediction objects are save to {}".format(stored_predictions))
+        self.stored_prediction_info(stored_predictions)
         return self._annotations, self._predictions
 
     def _process_batch_results(
@@ -633,9 +630,14 @@ def prepare_prediction_to_store(self, batch_predictions, batch_identifiers, batc
         prediction_to_store = StoredPredictionBatch(batch_predictions, batch_identifiers, batch_meta)
         self.store_predictions(stored_predictions, prediction_to_store)
 
+    @staticmethod
+    def stored_prediction_info(stored_predictions):
+        if stored_predictions:
+            print_info("prediction objects are save to {}".format(stored_predictions))
+
     @property
     def metrics_results(self):
-        if not self.metrics_results:
+        if not self._metrics_results:
             self.compute_metrics(print_results=False)
         computed_metrics = copy.deepcopy(self._metrics_results)
         return computed_metrics

tools/accuracy_checker/accuracy_checker/launcher/openvino_launcher.py

@@ -20,8 +20,8 @@
 import multiprocessing
 from pathlib import Path
 import re
-import numpy as np
 import pickle  # nosec B403  # disable import-pickle check
+import numpy as np
 from openvino import Core, AsyncInferQueue, get_version, PartialShape, Type, Dimension
 from openvino.preprocess import PrePostProcessor
 from .dlsdk_launcher_config import (
@@ -1051,4 +1051,3 @@ def _dump_first_inference(self, input_data, output_data):
         with open(self._dump_first_infer_data, 'wb') as file:
             pickle.dump(dump_inf_data, file)
         self._dump_first_infer_data = None
-