efficientnet_b0 tuning accuracy regression fix (#1140)

(cherry picked from commit c509883)

Author: lvliang-intel

neural_compressor/adaptor/tf_utils/graph_rewriter/generic/fuse_decomposed_bn.py

@@ -172,9 +172,12 @@ def do_transformation(self):
             # Workaround for model ava-person-vehicle-detection-stage2-2_0_0
             # FusedBatchNorm requires a 4D Tensor for input data, but MatMul only support 2D output.
             # Don't fuse the small ops to FusedBatchNorm when the upstream has MatMul.
-            ancestor_input_data_op = node_from_map(input_node_map, input_data_op.input[0])
-            if input_data_op.op == "MatMul" or ancestor_input_data_op.op == "MatMul":
+            if input_data_op.op == 'MatMul':
                 continue
+            if input_data_op.input:
+                ancestor_input_data_op = node_from_map(input_node_map, input_data_op.input[0])
+                if ancestor_input_data_op.op == "MatMul":
+                    continue
 
             scale_op = node_from_map(input_node_map, data_scale_mul_op.input[1])
 

neural_compressor/adaptor/tf_utils/graph_rewriter/generic/pre_optimize.py

@@ -111,12 +111,16 @@ def get_optimized_model(self, itex_mode=False):
         # Put FuseDecomposedBNOptimizer before GraphFoldConstantOptimizer
         # The 'Sub' op in the small decomposed ops of BN will be converted to const by GraphFoldConstantOptimizer.
         # Then the FuseDecomposedBNOptimizer can't fuse the small decomposed ops to BN.
-        self._tmp_graph_def = FuseDecomposedBNOptimizer(self._tmp_graph_def).do_transformation()
+        if self.new_api:
+            self._tmp_graph_def = FuseDecomposedBNOptimizer(self._tmp_graph_def).do_transformation()
 
         # disable fold constant for itex qdq mode
         if not itex_mode:
             self._tmp_graph_def = GraphFoldConstantOptimizer(self._tmp_graph_def).do_transformation()
 
+        if not self.new_api:
+            self._tmp_graph_def = FuseDecomposedBNOptimizer(self._tmp_graph_def).do_transformation()
+
         self._tmp_graph_def = FuseColumnWiseMulOptimizer(self._tmp_graph_def).do_transformation()
 
         self._tmp_graph_def = StripUnusedNodesOptimizer(self._tmp_graph_def,