diff -ruN mkl-dnn-1.2/include/dnnl.hpp mkl-dnn-1.2-patch/include/dnnl.hpp
--- mkl-dnn-1.2/include/dnnl.hpp	2020-01-25 06:54:36.000000000 +0900
+++ mkl-dnn-1.2-patch/include/dnnl.hpp	2020-02-03 12:04:59.085778234 +0900
@@ -106,6 +106,8 @@
     static void wrap_c_api(dnnl_status_t status, const char *message) {
         if (status != dnnl_success) DNNL_THROW_ERROR(status, message);
     }
+
+    const std::string& toStdString() { return std::string(message).append(": status = ").append(std::to_string(status)); }
 };
 
 /// A class that provides the destructor for a DNNL C API handle.
diff -ruN mkl-dnn-1.2/src/CMakeLists.txt mkl-dnn-1.2-patch/src/CMakeLists.txt
--- mkl-dnn-1.2/src/CMakeLists.txt	2020-01-25 06:54:36.000000000 +0900
+++ mkl-dnn-1.2-patch/src/CMakeLists.txt	2020-02-03 12:05:40.463770968 +0900
@@ -136,48 +136,6 @@
     -DDIR=${CMAKE_INSTALL_PREFIX}/${CMAKE_INSTALL_LIBDIR}/cmake
     -P ${PROJECT_SOURCE_DIR}/cmake/gen_mkldnn_compat_cmakes.cmake)")
 
-# MKL-DNN compat libraries
-if (WIN32)
-    if (NOT MINGW)
-        set(prefix "")
-        set(ext "lib")
-    else()
-        set(prefix "lib")
-        if (DNNL_LIBRARY_TYPE STREQUAL "SHARED")
-            set(ext "dll.a")
-        else()
-            set(ext "a")
-        endif()
-    endif()
-    add_custom_target(compat_libs ALL
-        ${CMAKE_COMMAND} -E copy
-        $<TARGET_FILE_DIR:${LIB_NAME}>/${prefix}dnnl.${ext}
-        $<TARGET_FILE_DIR:${LIB_NAME}>/${prefix}mkldnn.${ext}
-        DEPENDS ${LIB_NAME})
-    install(FILES $<TARGET_FILE_DIR:${LIB_NAME}>/${prefix}mkldnn.${ext}
-        DESTINATION ${CMAKE_INSTALL_PREFIX}/${CMAKE_INSTALL_LIBDIR})
-else()
-    if(DNNL_LIBRARY_TYPE STREQUAL "SHARED")
-        set_ternary(ext APPLE ".dylib" ".so")
-        set(vers ".${DNNL_VERSION_MAJOR};.${DNNL_VERSION_MAJOR}.${DNNL_VERSION_MINOR}")
-    else()
-        set(ext ".a")
-        set(vers "")
-    endif()
-    foreach(ver "" ${vers})
-        set_ternary(ext_and_ver APPLE "${ver}${ext}" "${ext}${ver}")
-        add_custom_command(OUTPUT libmkldnn${ext_and_ver}
-            # to make the next command work fine
-            COMMAND ${CMAKE_COMMAND} -E remove -f libmkldnn${ext_and_ver}
-            COMMAND ${CMAKE_COMMAND} -E create_symlink libdnnl${ext_and_ver} libmkldnn${ext_and_ver}
-            DEPENDS ${LIB_NAME})
-        add_custom_target(compat_libs${ver} ALL
-                DEPENDS libmkldnn${ext_and_ver})
-        install(FILES ${CMAKE_CURRENT_BINARY_DIR}/libmkldnn${ext_and_ver}
-            DESTINATION ${CMAKE_INSTALL_PREFIX}/${CMAKE_INSTALL_LIBDIR})
-    endforeach()
-endif()
-
 # Install custom find modules for transitive dependencies
 set(LIB_CONFIG_INSTALL_DIR_COMPAT "${CMAKE_INSTALL_LIBDIR}/cmake/mkldnn")
 if(DNNL_CPU_RUNTIME STREQUAL "TBB")
diff -ruN mkl-dnn-1.2/src/cpu/cpu_engine.cpp mkl-dnn-1.2-patch/src/cpu/cpu_engine.cpp
--- mkl-dnn-1.2/src/cpu/cpu_engine.cpp	2020-01-25 06:54:36.000000000 +0900
+++ mkl-dnn-1.2-patch/src/cpu/cpu_engine.cpp	2020-02-03 12:18:10.721768939 +0900
@@ -23,10 +23,29 @@
 #include "cpu_stream.hpp"
 #include "memory.hpp"
 
+#include "jit_uni_dw_conv_kernel_utils.hpp"
+
 namespace dnnl {
 namespace impl {
 namespace cpu {
 
+template struct jit_uni_dw_conv_fwd_kernel<avx512_core, data_type::bf16>;
+template struct jit_uni_dw_conv_fwd_kernel<avx512_common, data_type::f32>;
+template struct jit_uni_dw_conv_fwd_kernel<avx2, data_type::f32>;
+template struct jit_uni_dw_conv_fwd_kernel<sse41, data_type::f32>;
+
+template struct jit_uni_dw_conv_bwd_data_kernel<avx512_core, data_type::bf16>;
+template struct jit_uni_dw_conv_bwd_data_kernel<avx512_common, data_type::f32>;
+template struct jit_uni_dw_conv_bwd_data_kernel<avx2, data_type::f32>;
+template struct jit_uni_dw_conv_bwd_data_kernel<sse41, data_type::f32>;
+
+template struct jit_uni_dw_conv_bwd_weights_kernel<avx512_core,
+        data_type::bf16>;
+template struct jit_uni_dw_conv_bwd_weights_kernel<avx512_common,
+        data_type::f32>;
+template struct jit_uni_dw_conv_bwd_weights_kernel<avx2, data_type::f32>;
+template struct jit_uni_dw_conv_bwd_weights_kernel<sse41, data_type::f32>;
+
 status_t cpu_engine_t::create_memory_storage(
         memory_storage_t **storage, unsigned flags, size_t size, void *handle) {
     auto _storage = new cpu_memory_storage_t(this);
diff -ruN mkl-dnn-1.2/src/cpu/jit_uni_dw_conv_kernel_utils.hpp mkl-dnn-1.2-patch/src/cpu/jit_uni_dw_conv_kernel_utils.hpp
--- mkl-dnn-1.2/src/cpu/jit_uni_dw_conv_kernel_utils.hpp	2020-01-25 06:54:36.000000000 +0900
+++ mkl-dnn-1.2-patch/src/cpu/jit_uni_dw_conv_kernel_utils.hpp	2020-02-03 12:05:04.333777313 +0900
@@ -192,11 +192,6 @@
         scratchpad.book(key_conv_padded_bias, sizeof(float) * jcp.oc);
 }
 
-template struct jit_uni_dw_conv_fwd_kernel<avx512_core, data_type::bf16>;
-template struct jit_uni_dw_conv_fwd_kernel<avx512_common, data_type::f32>;
-template struct jit_uni_dw_conv_fwd_kernel<avx2, data_type::f32>;
-template struct jit_uni_dw_conv_fwd_kernel<sse41, data_type::f32>;
-
 template <cpu_isa_t isa, data_type_t kernel_dt>
 struct jit_uni_dw_conv_bwd_data_kernel {
 
@@ -326,11 +321,6 @@
     UNUSED(jcp);
 }
 
-template struct jit_uni_dw_conv_bwd_data_kernel<avx512_core, data_type::bf16>;
-template struct jit_uni_dw_conv_bwd_data_kernel<avx512_common, data_type::f32>;
-template struct jit_uni_dw_conv_bwd_data_kernel<avx2, data_type::f32>;
-template struct jit_uni_dw_conv_bwd_data_kernel<sse41, data_type::f32>;
-
 template <cpu_isa_t isa, data_type_t kernel_dt>
 struct jit_uni_dw_conv_bwd_weights_kernel {
 
@@ -507,12 +497,6 @@
     jcp.nthr = jcp.nthr_g * jcp.nthr_mb;
 }
 
-template struct jit_uni_dw_conv_bwd_weights_kernel<avx512_core,
-        data_type::bf16>;
-template struct jit_uni_dw_conv_bwd_weights_kernel<avx512_common,
-        data_type::f32>;
-template struct jit_uni_dw_conv_bwd_weights_kernel<avx2, data_type::f32>;
-template struct jit_uni_dw_conv_bwd_weights_kernel<sse41, data_type::f32>;
 } // namespace cpu
 } // namespace impl
 } // namespace dnnl