[oneDNN]Introducing oneDNN 1.6 (#27137)

* - introducing oneDNN 1.6

test=develop

* - Removed redundant code

test=develop

cmake/external/mkldnn.cmake

@@ -20,7 +20,7 @@ SET(MKLDNN_SOURCE_DIR     ${THIRD_PARTY_PATH}/mkldnn/src/extern_mkldnn)
 SET(MKLDNN_INSTALL_DIR    ${THIRD_PARTY_PATH}/install/mkldnn)
 SET(MKLDNN_INC_DIR        "${MKLDNN_INSTALL_DIR}/include" CACHE PATH "mkldnn include directory." FORCE)
 SET(MKLDNN_REPOSITORY     https://github.com/intel/mkl-dnn.git)
-SET(MKLDNN_TAG            1ea812f4f5aa1bd989372a23ab50d0f0f81ee677)
+SET(MKLDNN_TAG            4c05c181b40cf7132f8943411fb3fab1786df0f7)
 
 # Introduce variables:
 # * CMAKE_INSTALL_LIBDIR

paddle/fluid/operators/elementwise/elementwise_mul_op.h

@@ -33,22 +33,7 @@ class ElementwiseMulOp : public ElementwiseOp {
     auto input_data_type = OperatorWithKernel::IndicateVarDataType(ctx, "X");
 
 #ifdef PADDLE_WITH_MKLDNN
-    using mkldnn::memory;
-    auto CanMKLDNNElementwiseMulBeUsed = [&]() {
-      auto x_dims = ctx.Input<Tensor>("X")->dims();
-      auto y_dims = ctx.Input<Tensor>("Y")->dims();
-      int rankdiff = x_dims.size() - y_dims.size();
-      // TODO(jczaja): Remove this when oneDNN performance for scalar
-      // broadcasting
-      // is improved (Ernie large situation)
-      if (rankdiff != 0 && y_dims.size() == 1 && y_dims[0] == 1) {
-        return false;
-      }
-
-      return true;
-    };
-
-    if (platform::CanMKLDNNBeUsed(ctx) && CanMKLDNNElementwiseMulBeUsed()) {
+    if (platform::CanMKLDNNBeUsed(ctx)) {
       return framework::OpKernelType(input_data_type, ctx.GetPlace(),
                                      framework::DataLayout::kMKLDNN,
                                      framework::LibraryType::kMKLDNN);