[POT] Fix for measuring input shape when inference model with batch greater 1 in FBC (#10063)

* fix: diffrent batch shape in prediction and target in ac

* add calculate metric in engine True

* resolve conflicts

tools/pot/openvino/tools/pot/algorithms/quantization/fast_bias_correction/algorithm.py

@@ -212,7 +212,10 @@ class FastBiasCorrection(Algorithm):
             if input_node.type == 'FakeQuantize':
                 input_node = nu.get_node_input(input_node, 0)
             calculate_input_shape[input_node.fullname] = {'shape_node': lambda x: x.shape}
+        calculate_metrics = self._engine.calculate_metrics
+        self._engine.calculate_metrics = False
         _, inputs_shape = self._engine.predict(calculate_input_shape, sampler)
+        self._engine.calculate_metrics = calculate_metrics
         for node_name, shape_node in inputs_shape.items():
             inputs_shape[node_name] = shape_node['shape_node'][0]
             if len(inputs_shape[node_name]) > 1:

tools/pot/openvino/tools/pot/api/engine.py

@@ -24,6 +24,7 @@ class Engine(ABC):
         self._statistic_graph_builder = StatisticGraphBuilder()
         self._stat_requests_number = self.config.get('stat_requests_number', None)
         self._eval_requests_number = self.config.get('eval_requests_number', None)
+        self.calculate_metrics = True
 
     def set_model(self, model):
         """ Set/reset model to instance of engine class