Small optimizations for conv2d kernel subroutines. (#29188)

- Make sure that oneDNN memory descriptors are created only once at
first iteration.

paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc

@@ -290,13 +290,25 @@ class ConvMKLDNNHandlerT
   std::shared_ptr<mkldnn::memory> AcquireSrcMemoryWithReorder(
       const framework::Tensor* input) {
     const T* input_data = input->data<T>();
+    const std::string user_key_suffix{"@src_mem_p_user"};
+    auto user_src_mem_p = this->AcquireMemory(user_key_suffix);
+
+    if (!user_src_mem_p) {
       auto user_src_md = platform::MKLDNNMemDesc(
           framework::vectorize(input->dims()), platform::MKLDNNGetDataType<T>(),
           input->format());
-
       return this->AcquireMemoryWithReorder(
           user_src_md, this->fwd_pd_->src_desc(), to_void_cast<T>(input_data),
           "@src_mem_p");
+    } else {
+      const std::string target_key_suffix{"@src_mem_p_target"};
+      const auto target_src_mem_p = this->AcquireMemory(target_key_suffix);
+      user_src_mem_p->set_data_handle(to_void_cast<T>(input_data));
+      if (user_src_mem_p != target_src_mem_p) {
+        this->AcquireReorder(user_src_mem_p, target_src_mem_p, "@src_mem_p");
+      }
+      return target_src_mem_p;
+    }
   }
 
   std::shared_ptr<mkldnn::memory> AcquireWeightsMemoryWithReorder(
@@ -324,6 +336,10 @@ class ConvMKLDNNHandlerT
 
   std::shared_ptr<mkldnn::memory> AcquireBiasMemoryWithReorder(
       const framework::Tensor* bias, const bool is_test) {
+    auto bias_mem_p = this->AcquireMemory("@bias_mem_p_target");
+    if (is_test && bias_mem_p) {
+      return bias_mem_p;
+    } else {
       const K* bias_data = bias->data<K>();
       auto user_bias_md = platform::MKLDNNMemDesc(
           framework::vectorize(bias->dims()), platform::MKLDNNGetDataType<K>(),
@@ -333,6 +349,7 @@ class ConvMKLDNNHandlerT
           user_bias_md, this->fwd_pd_->bias_desc(), to_void_cast<K>(bias_data),
           "@bias_mem_p", is_test);
     }
+  }
 
   std::shared_ptr<mkldnn::memory> AcquireResidualMemory(
       const framework::Tensor* residual_param) {
@@ -340,6 +357,11 @@ class ConvMKLDNNHandlerT
         residual_param->type() == framework::DataTypeTrait<T_out>::DataType()
             ? to_void_cast<T_out>(residual_param->data<T_out>())
             : to_void_cast<T>(residual_param->data<T>());
+    auto residual_mem_p = this->AcquireMemory("@user_residual_data_mem_p");
+    if (residual_mem_p) {
+      residual_mem_p->set_data_handle(residual_data);
+      return residual_mem_p;
+    } else {
       auto user_residual_md = platform::MKLDNNMemDesc(
           framework::vectorize(residual_param->dims()),
           framework::ToMKLDNNDataType(residual_param->type()),
@@ -348,6 +370,7 @@ class ConvMKLDNNHandlerT
       return this->AcquireMemoryFromPrimitive(user_residual_md, residual_data,
                                               "@user_residual_data_mem_p");
     }
+  }
 
   std::shared_ptr<mkldnn::memory> AcquireDstMemoryWithResidual(
       framework::Tensor* output, const framework::Tensor* residual_param) {