change ComputeINT8 to template version to remove checking dst_datatype code (#18756)

* change INT8 to template so that checking dst_dt with if-else could be removed. CI will be enabled after fixing reviews

* reverse user_residual_memory_p and user_bias_memory_p declaration scope
test=develop

paddle/fluid/platform/mkldnn_helper.h

@@ -20,7 +20,6 @@ limitations under the License. */
 #include <vector>
 #include "paddle/fluid/framework/operator.h"
 #include "paddle/fluid/platform/place.h"
-
 namespace paddle {
 namespace platform {
 
@@ -82,22 +81,24 @@ inline bool CanMKLDNNBeUsed(const framework::ExecutionContext& ctx) {
 
 template <typename Type>
 mkldnn::memory::data_type MKLDNNGetDataType() {
-  return mkldnn::memory::data_undef;
+  return mkldnn::memory::data_type::data_undef;
 }
 
 template <>
 inline mkldnn::memory::data_type MKLDNNGetDataType<float>() {
-  return mkldnn::memory::f32;
+  return mkldnn::memory::data_type::f32;
+}
+template <>
+inline mkldnn::memory::data_type MKLDNNGetDataType<int32_t>() {
+  return mkldnn::memory::data_type::s32;
 }
-
 template <>
 inline mkldnn::memory::data_type MKLDNNGetDataType<int8_t>() {
-  return mkldnn::memory::s8;
+  return mkldnn::memory::data_type::s8;
 }
-
 template <>
 inline mkldnn::memory::data_type MKLDNNGetDataType<uint8_t>() {
-  return mkldnn::memory::u8;
+  return mkldnn::memory::data_type::u8;
 }
 
 inline void Reorder(const mkldnn::memory& src, const mkldnn::memory& dst) {

paddle/fluid/platform/mkldnn_reuse.h

@@ -1160,18 +1160,24 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
                                scale_data, mask);
   }
 
-  mkldnn::primitive_attr CreatePostOps(bool fuse_relu, bool fuse_residual_conn,
-                                       bool fuse_brelu,
-                                       float fuse_brelu_threshold) const {
+  mkldnn::primitive_attr CreatePostOps(
+      bool fuse_relu, bool fuse_residual_conn, bool fuse_brelu,
+      float fuse_brelu_threshold,
+      const std::vector<float> output_shift_scale = {},
+      float sum_scale = 1.0f) const {
     mkldnn::primitive_attr conv_attr;
     mkldnn::post_ops post_operations;
+    if (output_shift_scale.size() > 0) {
+      int mask = output_shift_scale.size() > 1 ? 1 << 1 : 0;
+      conv_attr.set_output_scales(mask, output_shift_scale);
+    }
     // Fusion with Elementwise layer relies on adding a sum post-operation with
     // the scale parameter. It is assumed that when fuse_residual_connection is
     // true, the output tensor contains the data coming from residual
     // connection. The result of this post_op is:
     // Output = scale * Output + Conv_Out.
     if (fuse_residual_conn) {
-      post_operations.append_sum(1.0f);
+      post_operations.append_sum(sum_scale);
     }
     // Fusion with ReLU layer is executed through the PostOps feature. Create a
     // PostOps object and configure it to execute an eltwise relu operation.
@@ -1202,7 +1208,9 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
       const std::vector<int>& paddings, const mkldnn::engine& engine,
       const bool fuse_relu, const bool fuse_residual_conn,
       const bool fuse_brelu, const float fuse_brelu_threshold,
-      mkldnn::prop_kind fwd_prop_kind) {
+      mkldnn::prop_kind fwd_prop_kind,
+      const std::vector<float> output_shift_scale = {},
+      const float sum_scale = 1.0f) {
     // Conv PD has to be passed to Grad op that
     // may be exxecuted by diffrent thread, hence
     // for that one we use key that does not contain TID
@@ -1232,8 +1240,9 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
                        src, weights, dst, stride_dims, padding_dims,
                        padding_dims, mkldnn::padding_kind::zero);
 
-        mkldnn::primitive_attr conv_attr = CreatePostOps(
-            fuse_relu, fuse_residual_conn, fuse_brelu, fuse_brelu_threshold);
+        mkldnn::primitive_attr conv_attr =
+            CreatePostOps(fuse_relu, fuse_residual_conn, fuse_brelu,
+                          fuse_brelu_threshold, output_shift_scale, sum_scale);
 
         conv_pd_.reset(new typename forward_t::primitive_desc(
             conv_desc, conv_attr, engine));
@@ -1393,10 +1402,10 @@ template <typename T>
 static void SetDstMemoryHandler(
     const framework::ExecutionContext& ctx, framework::Tensor* output,
     const std::shared_ptr<ConvMKLDNNHandler>& handler,
-    std::shared_ptr<mkldnn::memory>* dst_memory_p) {
+    std::shared_ptr<mkldnn::memory> dst_memory_p) {
   T* output_data =
       output->mutable_data<T>(ctx.GetPlace(), handler->GetDstMemorySize());
-  (*dst_memory_p)->set_data_handle(to_void_cast<T>(output_data));
+  dst_memory_p->set_data_handle(to_void_cast<T>(output_data));
 }
 
 template <typename T>