diff --git a/python/paddle/fluid/contrib/slim/quantization/quant2_int8_mkldnn_pass.py b/python/paddle/fluid/contrib/slim/quantization/quant2_int8_mkldnn_pass.py
index 0251dd693f66f..92a335a73dc85 100644
--- a/python/paddle/fluid/contrib/slim/quantization/quant2_int8_mkldnn_pass.py
+++ b/python/paddle/fluid/contrib/slim/quantization/quant2_int8_mkldnn_pass.py
@@ -397,6 +397,7 @@ def _remove_ctrl_vars(self, graph):
     def _optimize_fp32_graph(self, graph):
         graph = self._update_activations(graph)
         graph = self._remove_ctrl_vars(graph)
+        graph = self._apply_pass(graph, 'layer_norm_fuse_pass')
         graph = self._apply_pass(graph, 'attention_lstm_fuse_pass')
         graph = self._apply_pass(graph, 'seqconv_eltadd_relu_fuse_pass')
         #  graph = self._apply_pass(graph, 'seqpool_concat_fuse_pass')
@@ -409,24 +410,39 @@ def _optimize_fp32_graph(self, graph):
         graph = self._apply_pass(graph, 'multi_gru_fuse_pass')
         graph = self._apply_pass(graph, 'multi_gru_seq_fuse_pass')
         graph = self._apply_pass(graph, 'seq_concat_fc_fuse_pass')
+        graph = self._apply_pass(graph, 'squeeze2_matmul_fuse_pass')
+        graph = self._apply_pass(graph, 'reshape2_matmul_fuse_pass')
+        graph = self._apply_pass(graph, 'flatten2_matmul_fuse_pass')
+        graph = self._apply_pass(graph, 'matmul_v2_scale_fuse_pass')
         graph = self._apply_pass(graph, 'squared_mat_sub_fuse_pass')
         graph = self._apply_pass(graph, 'is_test_pass')
         graph = self._apply_pass(graph, 'map_matmul_v2_to_mul_pass')
         graph = self._apply_pass(graph, 'map_matmul_v2_to_matmul_pass')
+        graph = self._apply_pass(graph, 'matmul_scale_fuse_pass')
         graph = self._apply_pass(graph, 'map_matmul_to_mul_pass')
+        graph = self._apply_pass(graph, 'repeated_fc_relu_fuse_pass')
         graph = self._apply_pass(graph, 'mkldnn_placement_pass',
                                  ['mkldnn_enabled_op_types'], [set()])
         graph = self._apply_pass(graph, 'depthwise_conv_mkldnn_pass')
         graph = self._apply_pass(graph, 'conv_bn_fuse_pass')
         graph = self._apply_pass(graph, 'conv_eltwiseadd_bn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_affine_channel_fuse_pass')
+        graph = self._apply_pass(graph,
+                                 'conv_eltwiseadd_affine_channel_fuse_pass')
         graph = self._apply_pass(graph, 'conv_transpose_bn_fuse_pass')
         graph = self._apply_pass(graph,
                                  'conv_transpose_eltwiseadd_bn_fuse_pass')
         graph = self._apply_pass(graph, 'conv_bias_mkldnn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_transpose_bias_mkldnn_fuse_pass')
         graph = self._apply_pass(graph, 'conv_elementwise_add_mkldnn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_concat_relu_mkldnn_fuse_pass')
         graph = self._apply_pass(graph, 'conv_relu_mkldnn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_leaky_relu_mkldnn_fuse_pass')
         graph = self._apply_pass(graph, 'conv_relu6_mkldnn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_swish_mkldnn_fuse_pass')
         graph = self._apply_pass(graph, 'conv_hard_swish_mkldnn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_hard_sigmoid_mkldnn_fuse_pass')
+        graph = self._apply_pass(graph, 'conv_gelu_mkldnn_fuse_pass')
         graph = self._apply_pass(graph, 'fc_fuse_pass',
                                  ['use_gpu', 'use_fc_padding'], [False, False])
         graph = self._apply_pass(graph, 'repeated_fc_relu_fuse_pass')
@@ -436,6 +452,8 @@ def _optimize_fp32_graph(self, graph):
             graph = self._apply_pass(graph, 'fc_act_mkldnn_fuse_pass')
         graph = self._apply_pass(graph, 'matmul_transpose_reshape_fuse_pass')
         graph = self._apply_pass(graph, 'matmul_v2_transpose_reshape_fuse_pass')
+        graph = self._apply_pass(graph, 'batch_norm_act_fuse_pass')
+        graph = self._apply_pass(graph, 'softplus_activation_mkldnn_fuse_pass')
         # the following pass should be the last one since it will work on all fused ops.
         graph = self._apply_pass(graph, 'runtime_context_cache_pass')
         return graph
@@ -638,15 +656,15 @@ def _get_data_layout(self, graph):
         return 'NHWC' if self._is_conv_quantized(graph) else 'NCHW'
 
     def _quantize_fp32_graph(self, graph):
-        graph = self._apply_pass(
-            graph, 'cpu_quantize_placement_pass',
-            ['quantize_enabled_op_types', 'quantize_excluded_op_ids'],
-            [self._ops_to_quantize, self._find_avg_pooling_ids(graph)])
         graph = self._apply_pass(graph, 'scale_matmul_fuse_pass')
         graph = self._apply_pass(graph,
                                  'reshape_transpose_matmul_mkldnn_fuse_pass')
         graph = self._apply_pass(graph,
                                  'reshape_transpose_matmul_v2_mkldnn_fuse_pass')
+        graph = self._apply_pass(
+            graph, 'cpu_quantize_placement_pass',
+            ['quantize_enabled_op_types', 'quantize_excluded_op_ids'],
+            [self._ops_to_quantize, self._find_avg_pooling_ids(graph)])
         graph = self._apply_pass(
             graph, 'cpu_quantize_pass', ['quant_var_scales', 'data_layout'],
             [self._var_quant_scales, self._get_data_layout(graph)])