Replace Relu with bounded Relu in MobileNetV2 quantization (#18988)

test=develop

paddle/fluid/framework/ir/mkldnn/cpu_quantize_pass.cc

@@ -208,6 +208,15 @@ void CPUQuantizePass::QuantizeConv(Graph* graph,
     DequantizeOutput(g, conv_op, conv_output, "Output", output_scale,
                      is_output_unsigned, "Scale_out");
 
+    // change threshold in bounded ReLu
+    if (conv_op->Op()->HasAttr("fuse_brelu") &&
+        boost::get<bool>(conv_op->Op()->GetAttr("fuse_brelu"))) {
+      float scale_out = boost::get<float>(conv_op->Op()->GetAttr("Scale_out"));
+      float threshold =
+          boost::get<float>(conv_op->Op()->GetAttr("fuse_brelu_threshold"));
+      conv_op->Op()->SetAttr("fuse_brelu_threshold", scale_out * threshold);
+    }
+
     ++quantize_conv_count;
   };
 

paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc

@@ -484,9 +484,6 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
       handler.reset(
           new platform::ConvMKLDNNHandler(dev_ctx, mkldnn_engine, key));
       // create a conv primitive descriptor and save it for usage in backward
-      // TODO(lidanqing): We use relu post-op instead of brelu post-op cause
-      // mkldnn v0.18 does not support INT8 brelu post-op. Use code in /**/ when
-      // v0.20 is enabled
       auto propagation = is_test ? mkldnn::prop_kind::forward_scoring
                                  : mkldnn::prop_kind::forward_training;
 
@@ -496,15 +493,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
                                                mkldnn::memory::format::x);
         conv_pd = handler->AcquireConvolutionPrimitiveDescriptor(
             src_md, weights_md, bias_md, dst_md, strides, paddings,
-            mkldnn_engine, fuse_relu || fuse_brelu /*fuse_relu*/,
-            fuse_residual_conn, false /*fuse_brelu*/, fuse_brelu_threshold,
-            propagation, output_shift_scale, sum_scale);
+            mkldnn_engine, fuse_relu, fuse_residual_conn, fuse_brelu,
+            fuse_brelu_threshold, propagation, output_shift_scale, sum_scale);
       } else {
         conv_pd = handler->AcquireConvolutionPrimitiveDescriptor(
             src_md, weights_md, boost::none, dst_md, strides, paddings,
-            mkldnn_engine, fuse_relu || fuse_brelu /*fuse_relu*/,
-            fuse_residual_conn, false /*fuse_brelu*/, fuse_brelu_threshold,
-            propagation, output_shift_scale, sum_scale);
+            mkldnn_engine, fuse_relu, fuse_residual_conn, fuse_brelu,
+            fuse_brelu_threshold, propagation, output_shift_scale, sum_scale);
       }
 
       // create mkldnn memory from input tensors (data/weights)