AC: fix lpcnet quantization (#3175)

Author: eaidova

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

@@ -63,7 +63,8 @@ def __init__(self, network_info, launcher, models_args, adapter_info, is_blob=No
         self.decoder = create_model(network_info['decoder'], launcher, self._decoder_mapping, 'decoder',
                                     delayed_model_loading)
         self.adapter = create_adapter(adapter_info)
-        self.update_inputs_outputs_info()
+        if not delayed_model_loading:
+            self.update_inputs_outputs_info()
         self.adapter.output_blob = 'audio'
 
         self.with_prefix = False
@@ -123,6 +124,10 @@ def update_inputs_outputs_info(self, with_prefix):
         self.periods_input = generate_layer_name(self.periods_input, self.default_model_suffix+'_', with_prefix)
         if hasattr(self, 'outputs'):
             self.output = postprocess_output_name(self.output, self.outputs, raise_error=False)
+            if self.output not in self.outputs:
+                self.output = postprocess_output_name(
+                    generate_layer_name(self.output, self.default_model_suffix+'_', with_prefix),
+                    self.outputs, raise_error=False)
 
 
 class EncoderDLSDKModel(EncoderModel, TTSDLSDKModel):
@@ -240,8 +245,20 @@ def update_inputs_outputs_info(self, with_prefix):
         self.rnn_input2 = generate_layer_name(self.rnn_input2, prefix, with_prefix)
         if hasattr(self, 'outputs'):
             self.output = postprocess_output_name(self.output, self.outputs, raise_error=False)
+            if self.output not in self.outputs:
+                self.output = postprocess_output_name(
+                    generate_layer_name(self.output, self.default_model_suffix + '_', with_prefix),
+                    self.outputs, raise_error=False)
             self.rnn_output1 = postprocess_output_name(self.rnn_output1, self.outputs, raise_error=False)
+            if self.rnn_output1 not in self.outputs:
+                self.rnn_output1 = postprocess_output_name(
+                    generate_layer_name(self.rnn_output1, self.default_model_suffix + '_', with_prefix),
+                    self.outputs, raise_error=False)
             self.rnn_output2 = postprocess_output_name(self.rnn_output2, self.outputs, raise_error=False)
+            if self.rnn_output2 not in self.outputs:
+                self.rnn_output2 = postprocess_output_name(
+                    generate_layer_name(self.rnn_output2, self.default_model_suffix + '_', with_prefix),
+                    self.outputs, raise_error=False)
 
 
 class DecoderONNXModel(BaseONNXModel, DecoderModel):