Optimize INT8 DeQuantize Op with primitive reuse.

test=develop

paddle/fluid/operators/mkldnn/dequantize_mkldnn_op.cc

@@ -17,6 +17,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/tensor.h"
 #include "paddle/fluid/operators/dequantize_op.h"
 #include "paddle/fluid/platform/mkldnn_helper.h"
+#include "paddle/fluid/platform/mkldnn_reuse.h"
 
 namespace paddle {
 namespace operators {
@@ -30,6 +31,18 @@ using framework::DataLayout;
 using mkldnn::stream;
 using platform::GetMKLDNNFormat;
 
+std::string CreateKey(const paddle::framework::ExecutionContext& ctx,
+                      const mkldnn::memory::data_type& src_dt,
+                      const std::vector<int>& src_tz, const float scale_data) {
+  std::string key;
+  key.reserve(platform::MKLDNNHandler::MaxKeyLength);
+  platform::MKLDNNHandler::AppendKey(&key, std::to_string(src_dt));
+  platform::MKLDNNHandler::AppendKeyDims(&key, src_tz);
+  platform::MKLDNNHandler::AppendKey(&key, std::to_string(scale_data));
+  platform::MKLDNNHandler::AppendKey(&key, ctx.op().Output("Output"));
+  return key;
+}
+
 template <typename T>
 class DeQuantOpKernel : public framework::OpKernel<T> {
  public:
@@ -51,14 +64,24 @@ class DeQuantOpKernel : public framework::OpKernel<T> {
     mkldnn::memory::data_type src_dt =
         paddle::framework::ToMKLDNNDataType(input->type());
     mkldnn::memory::format src_fmt = input->format();
+    std::string key = CreateKey(ctx, src_dt, src_tz, reorder_scale[0]);
+    const std::string key_prim = key + "@reorder_p";
+    const std::string key_src_mem = key + "@src_mem";
+    const std::string key_dst_mem = key + "@dst_mem";
+
+    std::shared_ptr<mkldnn::memory> src_memory;
+    std::shared_ptr<mkldnn::memory> dst_memory;
+    std::shared_ptr<reorder> reorder_p;
+    reorder_p = std::static_pointer_cast<reorder>(dev_ctx.GetBlob(key_prim));
 
+    if (reorder_p == nullptr) {
       mkldnn::primitive_attr attri;
       int mask = 0;
       attri.set_output_scales(mask, reorder_scale);
 
       auto src_md = platform::MKLDNNMemDesc({src_tz}, src_dt, src_fmt);
       auto src_pd = mkldnn::memory::primitive_desc(src_md, engine);
-    auto src_memory =
+      src_memory =
           std::make_shared<mkldnn::memory>(src_pd, to_void_cast<T>(input_data));
       std::shared_ptr<primitive::at> src_memory_p =
           std::shared_ptr<primitive::at>(new primitive::at(*src_memory));
@@ -66,16 +89,30 @@ class DeQuantOpKernel : public framework::OpKernel<T> {
       auto dst_md = platform::MKLDNNMemDesc({dst_tz}, memory::data_type::f32,
                                             memory::format::nchw);
       auto dst_pd = mkldnn::memory::primitive_desc(dst_md, engine);
-    auto dst_memory = mkldnn::memory(dst_pd, to_void_cast<float>(output_data));
+      dst_memory = std::make_shared<mkldnn::memory>(
+          dst_pd, to_void_cast<float>(output_data));
 
       auto reorder_pd = std::shared_ptr<reorder::primitive_desc>(
           new reorder::primitive_desc(src_pd, dst_pd, attri));
-    auto reorder_p = std::shared_ptr<reorder>(
-        new reorder(*reorder_pd, *src_memory_p, dst_memory));
+      reorder_p = std::shared_ptr<reorder>(
+          new reorder(*reorder_pd, *src_memory_p, *dst_memory));
+      dev_ctx.SetBlob(key_prim, reorder_p);
+      dev_ctx.SetBlob(key_src_mem, src_memory);
+      dev_ctx.SetBlob(key_dst_mem, dst_memory);
+    } else {
+      src_memory = std::static_pointer_cast<mkldnn::memory>(
+          dev_ctx.GetBlob(key_src_mem));
+      src_memory->set_data_handle(to_void_cast<T>(input_data));
+
+      dst_memory = std::static_pointer_cast<mkldnn::memory>(
+          dev_ctx.GetBlob(key_dst_mem));
+      dst_memory->set_data_handle(output->mutable_data<float>(ctx.GetPlace()));
+    }
+
     pipeline.push_back(*reorder_p);
     stream(stream::kind::eager).submit(pipeline).wait();
 
-    output->set_format(GetMKLDNNFormat(dst_memory));
+    output->set_format(GetMKLDNNFormat(*dst_memory));
   }
 };