AC: port some important fixes for api2.0 (#3050)

Author: eaidova

tools/accuracy_checker/openvino/tools/accuracy_checker/adapters/image_processing.py

@@ -72,7 +72,7 @@ def configure(self):
         self.output_verified = False
 
     def select_output_blob(self, outputs):
-        self.outputs_checked = True
+        self.outputs_verified = True
         if not self.target_out:
             super().select_output_blob(outputs)
             self.target_out = self.output_blob
@@ -114,7 +114,7 @@ class SuperResolutionAdapter(ImageProcessingAdapter):
     def process(self, raw, identifiers=None, frame_meta=None):
         result = []
         raw_outputs = self._extract_predictions(raw, frame_meta)
-        if not self.target_out:
+        if not self.outputs_verified:
             self.select_output_blob(raw_outputs)
             self.target_out = self.output_blob
 

tools/accuracy_checker/openvino/tools/accuracy_checker/evaluators/custom_evaluators/lpcnet_evaluator.py

@@ -150,7 +150,7 @@ def infer(self, input_data):
         if self.feature_input in self.dynamic_inputs or feature_layer_shape != input_data[self.feature_input].shape:
             input_shapes = {in_name: value.shape for in_name, value in input_data.items()}
             self._reshape_input(input_shapes)
-        return self.infer(input_data)
+        return super().infer(input_data)
 
 
 class EncoderONNXModel(BaseONNXModel, EncoderModel):

tools/accuracy_checker/openvino/tools/accuracy_checker/evaluators/custom_evaluators/tacotron2_evaluator.py

@@ -481,7 +481,7 @@ def prepare_inputs(self, feed_dict):
         if len(feed_dict) != len(self.inputs):
             extra_inputs = set(self.inputs).difference(set(feed_dict))
             for input_layer in extra_inputs:
-                shape = self.inputs[input_layer].input_data.shape
+                shape = parse_partial_shape(self.inputs[input_layer].get_partial_shape())
                 if self.additional_inputs_filling == 'zeros':
                     feed_dict[input_layer] = np.zeros(shape, dtype=np.float32)
                 else: