merge develop

CMakeLists.txt

@@ -63,7 +63,28 @@ if(WIN32)
         set(CMAKE_C_FLAGS_RELEASE  "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
         set(CMAKE_CXX_FLAGS_DEBUG  "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
         set(CMAKE_CXX_FLAGS_RELEASE   "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
+        foreach(flag_var
+            CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
+            CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO
+            CMAKE_C_FLAGS CMAKE_C_FLAGS_DEBUG CMAKE_C_FLAGS_RELEASE
+            CMAKE_C_FLAGS_MINSIZEREL CMAKE_C_FLAGS_RELWITHDEBINFO)
+            if(${flag_var} MATCHES "/MD")
+                string(REGEX REPLACE "/MD" "/MT" ${flag_var} "${${flag_var}}")
             endif()
+        endforeach(flag_var)
+    endif()
+
+    # windows build turn off warnings.
+    foreach(flag_var
+        CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
+        CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO
+        CMAKE_C_FLAGS CMAKE_C_FLAGS_DEBUG CMAKE_C_FLAGS_RELEASE
+        CMAKE_C_FLAGS_MINSIZEREL CMAKE_C_FLAGS_RELWITHDEBINFO)
+        string(REGEX REPLACE "/W[1-4]" " /W0 " ${flag_var} "${${flag_var}}")
+    endforeach(flag_var)
+    foreach(flag_var CMAKE_CXX_FLAGS CMAKE_C_FLAGS)
+        set(${flag_var} "${${flag_var}} /w")
+    endforeach(flag_var)
 
     set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /wd4068 /wd4129 /wd4244 /wd4267 /wd4297 /wd4530 /wd4577 /wd4819 /wd4838 /MP")
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4068 /wd4129 /wd4244 /wd4267 /wd4297 /wd4530 /wd4577 /wd4819 /wd4838 /MP")

cmake/cuda.cmake

@@ -16,6 +16,7 @@ else()
   set(paddle_known_gpu_archs8 "30 35 50 52 60 61")
   set(paddle_known_gpu_archs9 "30 35 50 52 60 61 70")
   set(paddle_known_gpu_archs10 "30 35 50 52 60 61 70 75")
+  set(paddle_known_gpu_archs11 "52 60 61 70 75 80")
 endif()
 
 ######################################################################################
@@ -106,6 +107,9 @@ function(select_nvcc_arch_flags out_variable)
   elseif(${CUDA_ARCH_NAME} STREQUAL "Maxwell")
     set(cuda_arch_bin "50")
   elseif(${CUDA_ARCH_NAME} STREQUAL "Pascal")
+    if (NOT ${CMAKE_CUDA_COMPILER_VERSION} LESS 10.0)
+      add_definitions("-DSUPPORTS_CUDA_FP16")
+    endif()
     set(cuda_arch_bin "60 61")
   elseif(${CUDA_ARCH_NAME} STREQUAL "Volta")
     if (NOT ${CMAKE_CUDA_COMPILER_VERSION} LESS 10.0)
@@ -188,6 +192,10 @@ elseif (${CMAKE_CUDA_COMPILER_VERSION} LESS 11.0) # CUDA 10.x
   set(paddle_known_gpu_archs ${paddle_known_gpu_archs10})
   set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -D_MWAITXINTRIN_H_INCLUDED")
   set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -D__STRICT_ANSI__")
+elseif (${CMAKE_CUDA_COMPILER_VERSION} LESS 12.0) # CUDA 11.x
+  set(paddle_known_gpu_archs ${paddle_known_gpu_archs11})
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -D_MWAITXINTRIN_H_INCLUDED")
+  set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -D__STRICT_ANSI__")
 endif()
 
 add_definitions("-DPADDLE_CUDA_BINVER=\"${CUDA_VERSION_MAJOR}${CUDA_VERSION_MINOR}\"")

cmake/external/cryptopp.cmake

@@ -22,23 +22,8 @@ SET(CRYPTOPP_TAG        CRYPTOPP_8_2_0)
 
 IF(WIN32)
   SET(CRYPTOPP_LIBRARIES "${CRYPTOPP_INSTALL_DIR}/lib/cryptopp-static.lib" CACHE FILEPATH "cryptopp library." FORCE)
-  SET(CRYPTOPP_CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-  set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /MT")
-  set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /MTd")
-  set(CompilerFlags
-        CMAKE_CXX_FLAGS
-        CMAKE_CXX_FLAGS_DEBUG
-        CMAKE_CXX_FLAGS_RELEASE
-        CMAKE_C_FLAGS
-        CMAKE_C_FLAGS_DEBUG
-        CMAKE_C_FLAGS_RELEASE
-        )
-  foreach(CompilerFlag ${CompilerFlags})
-    string(REPLACE "/MD" "/MT" ${CompilerFlag} "${${CompilerFlag}}")
-  endforeach()
 ELSE(WIN32)
   SET(CRYPTOPP_LIBRARIES "${CRYPTOPP_INSTALL_DIR}/lib/libcryptopp.a" CACHE FILEPATH "cryptopp library." FORCE)
-  SET(CRYPTOPP_CMAKE_CXX_FLAGS ${CMAKE_CXX_FLAGS})
 ENDIF(WIN32)
 
 set(CRYPTOPP_CMAKE_ARGS ${COMMON_CMAKE_ARGS}
@@ -48,7 +33,7 @@ set(CRYPTOPP_CMAKE_ARGS ${COMMON_CMAKE_ARGS}
                         -DCMAKE_INSTALL_LIBDIR=${CRYPTOPP_INSTALL_DIR}/lib
                         -DCMAKE_INSTALL_PREFIX=${CRYPTOPP_INSTALL_DIR}
                         -DCMAKE_BUILD_TYPE=${THIRD_PARTY_BUILD_TYPE}
-                        -DCMAKE_CXX_FLAGS=${CRYPTOPP_CMAKE_CXX_FLAGS}
+                        -DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}
                         -DCMAKE_CXX_FLAGS_RELEASE=${CMAKE_CXX_FLAGS_RELEASE}
                         -DCMAKE_C_COMPILER=${CMAKE_C_COMPILER}
                         -DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}

cmake/external/dgc.cmake

@@ -19,7 +19,7 @@ SET(DGC_SOURCES_DIR "${THIRD_PARTY_PATH}/dgc/src/extern_dgc")
 SET(DGC_INSTALL_DIR "${THIRD_PARTY_PATH}/install/dgc")
 SET(DGC_INCLUDE_DIR "${DGC_INSTALL_DIR}/include" CACHE PATH "dgc include directory." FORCE)
 SET(DGC_LIBRARIES   "${DGC_INSTALL_DIR}/lib/libdgc.a" CACHE FILEPATH "dgc library." FORCE)
-SET(DGC_URL         "http://fleet.bj.bcebos.com/collective_ef2216a.tgz")
+SET(DGC_URL         "https://fleet.bj.bcebos.com/dgc/collective_f66ef73.tgz")
 INCLUDE_DIRECTORIES(${DGC_INCLUDE_DIR})
 
 cache_third_party(extern_dgc
@@ -30,7 +30,7 @@ ExternalProject_Add(
     extern_dgc
     ${EXTERNAL_PROJECT_LOG_ARGS}
     "${DGC_DOWNLOAD_CMD}"
-    URL_MD5         "2f67549fd5f1262383d83289abc4f88f"
+    URL_MD5         "94e6fa1bc97169d0e1aad44570fe3251"
     PREFIX          "${DGC_PREFIX_DIR}"
     SOURCE_DIR      "${DGC_SOURCES_DIR}"
     CONFIGURE_COMMAND ""

cmake/external/lite.cmake

@@ -34,7 +34,7 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
   set(LITE_INSTALL_DIR ${THIRD_PARTY_PATH}/install/lite)
 
   if(NOT LITE_GIT_TAG)
-    set(LITE_GIT_TAG dfdfa6440c83bf0b415f9f5a9ff84842ce0bb0fa)
+    set(LITE_GIT_TAG 6d2b2a4028a58715b01887b04eb9bff8432eb184)
   endif()
 
   if(NOT CUDA_ARCH_NAME)

cmake/external/mkldnn.cmake

@@ -19,8 +19,8 @@ SET(MKLDNN_PREFIX_DIR     ${THIRD_PARTY_PATH}/mkldnn)
 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_REPOSITORY     https://github.com/oneapi-src/oneDNN.git)
+SET(MKLDNN_TAG            64a48f9565aa72f6359917b3406328075a409939)
 
 # Introduce variables:
 # * CMAKE_INSTALL_LIBDIR

cmake/external/warpctc.cmake

@@ -18,7 +18,7 @@ SET(WARPCTC_PREFIX_DIR  ${THIRD_PARTY_PATH}/warpctc)
 SET(WARPCTC_SOURCE_DIR  ${THIRD_PARTY_PATH}/warpctc/src/extern_warpctc)
 SET(WARPCTC_INSTALL_DIR ${THIRD_PARTY_PATH}/install/warpctc)
 set(WARPCTC_REPOSITORY  https://github.com/baidu-research/warp-ctc.git)
-set(WARPCTC_TAG         bc29dcfff07ced1c7a19a4ecee48e5ad583cef8e)
+set(WARPCTC_TAG         fc7f226b93758216a03b1be9d24593a12819b984)
 
 SET(WARPCTC_INCLUDE_DIR "${WARPCTC_INSTALL_DIR}/include"
     CACHE PATH "Warp-ctc Directory" FORCE)

cmake/flags.cmake

@@ -28,7 +28,15 @@ function(CheckCompilerCXX11Flag)
 endfunction()
 
 CheckCompilerCXX11Flag()
-set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
+if (WITH_GPU)
+    if (${CMAKE_CUDA_COMPILER_VERSION} GREATER_EQUAL 11.0)
+       set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14")
+    else()
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
+    endif()
+else()
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
+endif()
 # safe_set_flag
 #
 # Set a compile flag only if compiler is support
@@ -82,20 +90,6 @@ macro(safe_set_nvflag flag_name)
     endif()
 endmacro()
 
-macro(safe_set_static_flag) # set c_flags and cxx_flags to static or shared
-    if (BUILD_SHARED_LIBS) 
-        return() # if build shared libs, the flags keep same with '/MD'
-    endif(BUILD_SHARED_LIBS)
-    foreach(flag_var
-        CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
-        CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO
-        CMAKE_C_FLAGS CMAKE_C_FLAGS_DEBUG CMAKE_C_FLAGS_RELEASE
-        CMAKE_C_FLAGS_MINSIZEREL CMAKE_C_FLAGS_RELWITHDEBINFO)
-      if(${flag_var} MATCHES "/MD")
-        string(REGEX REPLACE "/MD" "/MT" ${flag_var} "${${flag_var}}")
-      endif(${flag_var} MATCHES "/MD")
-    endforeach(flag_var)
-endmacro()
 
 CHECK_CXX_SYMBOL_EXISTS(UINT64_MAX "stdint.h" UINT64_MAX_EXISTS)
 if(NOT UINT64_MAX_EXISTS)
@@ -221,20 +215,3 @@ endforeach()
 
 set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} ${SAFE_GPU_COMMON_FLAGS}")
 
-
-if(WIN32)
-    # windows build turn off warnings.
-    if(MSVC_STATIC_CRT)
-        safe_set_static_flag()
-    endif()
-    foreach(flag_var
-        CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
-        CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO
-        CMAKE_C_FLAGS CMAKE_C_FLAGS_DEBUG CMAKE_C_FLAGS_RELEASE
-        CMAKE_C_FLAGS_MINSIZEREL CMAKE_C_FLAGS_RELWITHDEBINFO)
-        string(REGEX REPLACE "/W[1-4]" " /W0 " ${flag_var} "${${flag_var}}")
-    endforeach(flag_var)
-    foreach(flag_var CMAKE_CXX_FLAGS CMAKE_C_FLAGS)
-        set(${flag_var} "${${flag_var}} /w")
-    endforeach(flag_var)
-endif()

cmake/generic.cmake

@@ -386,7 +386,7 @@ function(cc_test_run TARGET_NAME)
     set_property(TEST ${TARGET_NAME} PROPERTY ENVIRONMENT FLAGS_cudnn_deterministic=true)
     # No unit test should exceed 2 minutes.
     if (APPLE OR WIN32)
-        set_tests_properties(${TARGET_NAME} PROPERTIES TIMEOUT 600)
+        set_tests_properties(${TARGET_NAME} PROPERTIES TIMEOUT 150)
     else()
         set_tests_properties(${TARGET_NAME} PROPERTIES TIMEOUT 120)
     endif()
@@ -748,7 +748,7 @@ function(py_test TARGET_NAME)
     endif()
     
     if (APPLE OR WIN32)
-        set_tests_properties(${TARGET_NAME} PROPERTIES TIMEOUT 600)
+        set_tests_properties(${TARGET_NAME} PROPERTIES TIMEOUT 150)
     else()
         # No unit test should exceed 2 minutes in Linux.
         set_tests_properties(${TARGET_NAME} PROPERTIES TIMEOUT 120)

cmake/inference_lib.cmake

@@ -13,18 +13,18 @@
 # limitations under the License.
 
 # make package for paddle fluid shared and static library
-set(FLUID_INSTALL_DIR "${CMAKE_BINARY_DIR}/fluid_install_dir" CACHE STRING
-  "A path setting fluid shared and static libraries")
+set(PADDLE_INSTALL_DIR "${CMAKE_BINARY_DIR}/paddle_install_dir" CACHE STRING
+  "A path setting paddle shared and static libraries")
 
-set(FLUID_INFERENCE_INSTALL_DIR "${CMAKE_BINARY_DIR}/fluid_inference_install_dir" CACHE STRING
-  "A path setting fluid inference shared and static libraries")
+set(PADDLE_INFERENCE_INSTALL_DIR "${CMAKE_BINARY_DIR}/paddle_inference_install_dir" CACHE STRING
+  "A path setting paddle inference shared and static libraries")
   
 # TODO(zhaolong)
 # At present, the size of static lib in Windows exceeds the system limit,
 # so the generation of static lib is temporarily turned off.
 if(WIN32)
     #todo: remove the option 
-    option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static."   OFF)
+    option(WITH_STATIC_LIB "Compile demo with static/shared library, default use dynamic."   OFF)
     if(NOT PYTHON_EXECUTABLE)
         FIND_PACKAGE(PythonInterp REQUIRED)
     endif()
@@ -142,14 +142,14 @@ set(inference_lib_deps third_party paddle_fluid paddle_fluid_c paddle_fluid_shar
 add_custom_target(inference_lib_dist DEPENDS ${inference_lib_deps})
 
 
-set(dst_dir "${FLUID_INFERENCE_INSTALL_DIR}/third_party/threadpool")
+set(dst_dir "${PADDLE_INFERENCE_INSTALL_DIR}/third_party/threadpool")
 copy(inference_lib_dist
         SRCS ${THREADPOOL_INCLUDE_DIR}/ThreadPool.h
         DSTS ${dst_dir})
 
 # Only GPU need cudaErrorMessage.pb
 IF(WITH_GPU)
-        set(dst_dir "${FLUID_INFERENCE_INSTALL_DIR}/third_party/cudaerror/data")
+        set(dst_dir "${PADDLE_INFERENCE_INSTALL_DIR}/third_party/cudaerror/data")
         copy(inference_lib_dist
                 SRCS ${cudaerror_INCLUDE_DIR}
                 DSTS ${dst_dir})
@@ -158,65 +158,62 @@ ENDIF()
 # CMakeCache Info
 copy(inference_lib_dist
         SRCS ${CMAKE_CURRENT_BINARY_DIR}/CMakeCache.txt
-        DSTS ${FLUID_INFERENCE_INSTALL_DIR})
+        DSTS ${PADDLE_INFERENCE_INSTALL_DIR})
 
-copy_part_of_thrid_party(inference_lib_dist ${FLUID_INFERENCE_INSTALL_DIR})
+copy_part_of_thrid_party(inference_lib_dist ${PADDLE_INFERENCE_INSTALL_DIR})
 
 set(src_dir "${PADDLE_SOURCE_DIR}/paddle/fluid")
 if(WIN32)
     if(WITH_STATIC_LIB)
-        set(paddle_fluid_lib ${PADDLE_BINARY_DIR}/paddle/fluid/inference/${CMAKE_BUILD_TYPE}/libpaddle_fluid.lib)
+        set(paddle_fluid_lib ${PADDLE_BINARY_DIR}/paddle/fluid/inference/${CMAKE_BUILD_TYPE}/libpaddle_fluid.lib
+                             ${PADDLE_BINARY_DIR}/paddle/fluid/inference/${CMAKE_BUILD_TYPE}/paddle_fluid.*)
     else()
         set(paddle_fluid_lib ${PADDLE_BINARY_DIR}/paddle/fluid/inference/${CMAKE_BUILD_TYPE}/paddle_fluid.dll
                              ${PADDLE_BINARY_DIR}/paddle/fluid/inference/${CMAKE_BUILD_TYPE}/paddle_fluid.lib)
     endif()
-else(WIN32)
-    set(paddle_fluid_lib ${PADDLE_BINARY_DIR}/paddle/fluid/inference/libpaddle_fluid.*)
-endif(WIN32)
-
-if(WIN32 AND NOT WITH_STATIC_LIB)
     copy(inference_lib_dist
             SRCS  ${src_dir}/inference/api/paddle_*.h ${paddle_fluid_lib}
-                DSTS  ${FLUID_INFERENCE_INSTALL_DIR}/paddle/include ${FLUID_INFERENCE_INSTALL_DIR}/paddle/lib
-                      ${FLUID_INFERENCE_INSTALL_DIR}/paddle/lib)
-else()
+            DSTS  ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/include ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/lib
+            ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/lib)
+else(WIN32)
+    set(paddle_fluid_lib ${PADDLE_BINARY_DIR}/paddle/fluid/inference/libpaddle_fluid.*)
     copy(inference_lib_dist
                 SRCS  ${src_dir}/inference/api/paddle_*.h ${paddle_fluid_lib}
-                DSTS  ${FLUID_INFERENCE_INSTALL_DIR}/paddle/include ${FLUID_INFERENCE_INSTALL_DIR}/paddle/lib)
-endif()
+                DSTS  ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/include ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/lib)
+endif(WIN32)
 
 copy(inference_lib_dist
         SRCS  ${CMAKE_BINARY_DIR}/paddle/fluid/framework/framework.pb.h
-        DSTS  ${FLUID_INFERENCE_INSTALL_DIR}/paddle/include/internal)
+        DSTS  ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/include/internal)
 copy(inference_lib_dist
         SRCS  ${PADDLE_SOURCE_DIR}/paddle/fluid/framework/io/crypto/cipher.h
-        DSTS  ${FLUID_INFERENCE_INSTALL_DIR}/paddle/include/crypto/)
+        DSTS  ${PADDLE_INFERENCE_INSTALL_DIR}/paddle/include/crypto/)
 include_directories(${CMAKE_BINARY_DIR}/../paddle/fluid/framework/io)
 
 # CAPI inference library for only inference
-set(FLUID_INFERENCE_C_INSTALL_DIR "${CMAKE_BINARY_DIR}/fluid_inference_c_install_dir" CACHE STRING
-"A path setting CAPI fluid inference shared")
-copy_part_of_thrid_party(inference_lib_dist ${FLUID_INFERENCE_C_INSTALL_DIR})
+set(PADDLE_INFERENCE_C_INSTALL_DIR "${CMAKE_BINARY_DIR}/paddle_inference_c_install_dir" CACHE STRING
+"A path setting CAPI paddle inference shared")
+copy_part_of_thrid_party(inference_lib_dist ${PADDLE_INFERENCE_C_INSTALL_DIR})
 
 set(src_dir "${PADDLE_SOURCE_DIR}/paddle/fluid")
 set(paddle_fluid_c_lib ${PADDLE_BINARY_DIR}/paddle/fluid/inference/capi/libpaddle_fluid_c.*)
 
 copy(inference_lib_dist
       SRCS  ${src_dir}/inference/capi/paddle_c_api.h  ${paddle_fluid_c_lib}
-      DSTS  ${FLUID_INFERENCE_C_INSTALL_DIR}/paddle/include ${FLUID_INFERENCE_C_INSTALL_DIR}/paddle/lib)
+      DSTS  ${PADDLE_INFERENCE_C_INSTALL_DIR}/paddle/include ${PADDLE_INFERENCE_C_INSTALL_DIR}/paddle/lib)
 
 # fluid library for both train and inference
 set(fluid_lib_deps inference_lib_dist)
 add_custom_target(fluid_lib_dist ALL DEPENDS ${fluid_lib_deps})
 
-set(dst_dir "${FLUID_INSTALL_DIR}/paddle/fluid")
+set(dst_dir "${PADDLE_INSTALL_DIR}/paddle/fluid")
 set(module "inference")
-if(WIN32 AND NOT WITH_STATIC_LIB)
+if(WIN32)
         copy(fluid_lib_dist
                 SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/api/paddle_*.h ${paddle_fluid_lib}
                 DSTS ${dst_dir}/${module} ${dst_dir}/${module} ${dst_dir}/${module} ${dst_dir}/${module}
                 )
-else()
+        else()
         copy(fluid_lib_dist
                 SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/api/paddle_*.h ${paddle_fluid_lib}
                 DSTS ${dst_dir}/${module} ${dst_dir}/${module} ${dst_dir}/${module} 
@@ -273,22 +270,22 @@ copy(fluid_lib_dist
         DSTS ${dst_dir}/${module}
         )
 
-set(dst_dir "${FLUID_INSTALL_DIR}/third_party/eigen3")
+set(dst_dir "${PADDLE_INSTALL_DIR}/third_party/eigen3")
 copy(inference_lib_dist
         SRCS ${EIGEN_INCLUDE_DIR}/Eigen/Core ${EIGEN_INCLUDE_DIR}/Eigen/src ${EIGEN_INCLUDE_DIR}/unsupported/Eigen
         DSTS ${dst_dir}/Eigen ${dst_dir}/Eigen ${dst_dir}/unsupported)
 
-set(dst_dir "${FLUID_INSTALL_DIR}/third_party/boost")
+set(dst_dir "${PADDLE_INSTALL_DIR}/third_party/boost")
 copy(inference_lib_dist
         SRCS ${BOOST_INCLUDE_DIR}/boost
         DSTS ${dst_dir})
 
-set(dst_dir "${FLUID_INSTALL_DIR}/third_party/dlpack")
+set(dst_dir "${PADDLE_INSTALL_DIR}/third_party/dlpack")
 copy(inference_lib_dist
         SRCS ${DLPACK_INCLUDE_DIR}/dlpack
         DSTS ${dst_dir})
 
-set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/zlib")
+set(dst_dir "${PADDLE_INSTALL_DIR}/third_party/install/zlib")
 copy(inference_lib_dist
         SRCS ${ZLIB_INCLUDE_DIR} ${ZLIB_LIBRARIES}
         DSTS ${dst_dir} ${dst_dir}/lib)
@@ -296,8 +293,8 @@ copy(inference_lib_dist
 
 # CMakeCache Info
 copy(fluid_lib_dist
-        SRCS ${FLUID_INFERENCE_INSTALL_DIR}/third_party ${CMAKE_CURRENT_BINARY_DIR}/CMakeCache.txt
-        DSTS ${FLUID_INSTALL_DIR} ${FLUID_INSTALL_DIR}
+        SRCS ${PADDLE_INFERENCE_INSTALL_DIR}/third_party ${CMAKE_CURRENT_BINARY_DIR}/CMakeCache.txt
+        DSTS ${PADDLE_INSTALL_DIR} ${PADDLE_INSTALL_DIR}
         )
 
 # paddle fluid version
@@ -323,6 +320,6 @@ function(version version_file)
     endif()
     
 endfunction()
-version(${FLUID_INSTALL_DIR}/version.txt)
-version(${FLUID_INFERENCE_INSTALL_DIR}/version.txt)
-version(${FLUID_INFERENCE_C_INSTALL_DIR}/version.txt)
+version(${PADDLE_INSTALL_DIR}/version.txt)
+version(${PADDLE_INFERENCE_INSTALL_DIR}/version.txt)
+version(${PADDLE_INFERENCE_C_INSTALL_DIR}/version.txt)

cmake/operators.cmake

@@ -127,7 +127,8 @@ function(op_library TARGET)
 "tensor_array_read_write_op" "tensorrt_engine_op" "conv_fusion_op"
 "fusion_transpose_flatten_concat_op" "fusion_conv_inception_op"
 "sync_batch_norm_op" "dgc_op" "fused_fc_elementwise_layernorm_op"
-"multihead_matmul_op" "fusion_group_op" "fused_bn_activation_op" "fused_embedding_eltwise_layernorm_op" "fusion_gru_op")
+"multihead_matmul_op" "fusion_group_op" "fused_bn_activation_op" "fused_embedding_eltwise_layernorm_op" "fusion_gru_op"
+"fused_bn_add_activation_op")
         if ("${TARGET}" STREQUAL "${manual_pybind_op}")
             set(pybind_flag 1)
         endif()
@@ -138,12 +139,17 @@ function(op_library TARGET)
     # And for detail pybind information, please see generated paddle/pybind/pybind.h.
     file(READ ${TARGET}.cc TARGET_CONTENT)
     string(REGEX MATCH "REGISTER_OPERATOR\\(.*REGISTER_OPERATOR\\(" multi_register "${TARGET_CONTENT}")
-    string(REGEX MATCH "REGISTER_OPERATOR\\([a-z0-9_]*," one_register "${multi_register}")
+    # [ \t\r\n]* is used for blank characters
+    string(REGEX MATCH "REGISTER_OPERATOR\\([ \t\r\n]*[a-z0-9_]*," one_register "${multi_register}")
+
     if (one_register STREQUAL "")
         string(REPLACE "_op" "" TARGET "${TARGET}")
     else ()
         string(REPLACE "REGISTER_OPERATOR(" "" TARGET "${one_register}")
         string(REPLACE "," "" TARGET "${TARGET}")
+        # [ \t\r\n]+ is used for blank characters.
+        # Here we use '+' instead of '*' since it is a REPLACE operation.
+        string(REGEX REPLACE "[ \t\r\n]+" "" TARGET "${TARGET}")
     endif()
 
     # pybind USE_NO_KERNEL_OP

cmake/third_party.cmake

@@ -243,9 +243,10 @@ IF(WITH_TESTING OR (WITH_DISTRIBUTE AND NOT WITH_GRPC))
 ENDIF()
 
 if(WITH_GPU)
+    if (${CMAKE_CUDA_COMPILER_VERSION} LESS 11.0)
         include(external/cub)       # download cub
         list(APPEND third_party_deps extern_cub)
-  
+    endif()
     set(CUDAERROR_URL  "http://paddlepaddledeps.bj.bcebos.com/cudaErrorMessage.tar.gz" CACHE STRING "" FORCE)
     file_download_and_uncompress(${CUDAERROR_URL} "cudaerror") # download file cudaErrorMessage
 endif(WITH_GPU)

go/README_cn.md

 # Paddle 预测golang API
 
 ## 安装
-首先cmake编译时打开`-DON_INFER=ON`,在编译目录下得到``fluid_inference_c_install_dir``,将该目录移动到当前目录中并重命名为`paddle_c`
+首先cmake编译时打开`-DON_INFER=ON`,在编译目录下得到``paddle_inference_c_install_dir``,将该目录移动到当前目录中并重命名为`paddle_c`
 
 ## 在Go中使用Paddle预测
 首先创建预测配置

go/paddle/config.go

@@ -154,10 +154,17 @@ func (config *AnalysisConfig) EnableMkldnnQuantizer() {
 	C.PD_EnableMkldnnQuantizer(config.c)
 }
 
+func (config *AnalysisConfig) EnableMkldnnBfloat16() {
+	C.PD_EnableMkldnnBfloat16(config.c)
+}
+
 func (config *AnalysisConfig) MkldnnQuantizerEnabled() bool {
 	return ConvertCBooleanToGo(C.PD_MkldnnQuantizerEnabled(config.c))
 }
 
+func (config *AnalysisConfig) MkldnnBfloat16Enabled() bool {
+	return ConvertCBooleanToGo(C.PD_MkldnnBfloat16Enabled(config.c))
+}
 // SetModelBuffer
 // ModelFromMemory
 

paddle/fluid/framework/CMakeLists.txt

@@ -272,7 +272,7 @@ cc_test(op_compatible_info_test SRCS op_compatible_info_test.cc DEPS op_compatib
 
 cc_library(save_load_util SRCS save_load_util DEPS tensor scope layer)
 cc_test(save_load_util_test SRCS save_load_util_test.cc DEPS save_load_util tensor scope layer)
-cc_library(generator SRCS generator.cc)
+cc_library(generator SRCS generator.cc DEPS enforce place)
 
 # Get the current working branch
 execute_process(

paddle/fluid/framework/c/c_api.cc

@@ -49,7 +49,8 @@ std::vector<std::string> PD_GetGradOpDescStrs(
     for (size_t i = 0; i < op_num; ++i) {
       PADDLE_ENFORCE_EQ(
           grad_op_descs[i]->Proto()->SerializePartialToString(&ret[i]), true,
-          "Cannot serialize message.");
+          paddle::platform::errors::Unavailable(
+              "Cannot serialize operator desc message."));
     }
   }
   return ret;

paddle/fluid/framework/data_feed.cc

@@ -527,6 +527,8 @@ bool MultiSlotDataFeed::CheckFile(const char* filename) {
         VLOG(0) << "error: the number of ids is a negative number: " << num;
         VLOG(0) << "please check line<" << instance_cout << "> in file<"
                 << filename << ">";
+        VLOG(0) << "Error occured when parsing " << i
+                << " th slot with total slots number: " << all_slots_.size();
         return false;
       } else if (num == 0) {
         VLOG(0)
@@ -536,42 +538,66 @@ bool MultiSlotDataFeed::CheckFile(const char* filename) {
                "characters.";
         VLOG(0) << "please check line<" << instance_cout << "> in file<"
                 << filename << ">";
+        VLOG(0) << "Error occured when parsing " << i
+                << " th slot with total slots number: " << all_slots_.size();
         return false;
       } else if (errno == ERANGE || num > INT_MAX) {
         VLOG(0) << "error: the number of ids greater than INT_MAX";
         VLOG(0) << "please check line<" << instance_cout << "> in file<"
                 << filename << ">";
+        VLOG(0) << "Error occured when parsing " << i
+                << " th slot with total slots number: " << all_slots_.size();
         return false;
       }
       if (all_slots_type_[i] == "float") {
-        for (int i = 0; i < num; ++i) {
+        for (int j = 0; j < num; ++j) {
           strtof(endptr, &endptr);
           if (errno == ERANGE) {
             VLOG(0) << "error: the value is out of the range of "
                        "representable values for float";
             VLOG(0) << "please check line<" << instance_cout << "> in file<"
                     << filename << ">";
+            VLOG(0) << "Error occured when parsing " << i
+                    << " th slot with total slots number: "
+                    << all_slots_.size();
+            VLOG(0) << "and in this slot: " << j
+                    << " th id with total id number: " << num;
             return false;
           }
-          if (i + 1 != num && endptr - str == len) {
+          if (j + 1 != num && endptr - str == len) {
             VLOG(0) << "error: there is a wrong with the number of ids.";
+            VLOG(0) << "Error occured when parsing " << i
+                    << " th slot with total slots number: "
+                    << all_slots_.size();
+            VLOG(0) << "and in this slot: " << j
+                    << " th id with total id number: " << num;
             VLOG(0) << "please check line<" << instance_cout << "> in file<"
                     << filename << ">";
             return false;
           }
         }
       } else if (all_slots_type_[i] == "uint64") {
-        for (int i = 0; i < num; ++i) {
+        for (int j = 0; j < num; ++j) {
           strtoull(endptr, &endptr, 10);
           if (errno == ERANGE) {
             VLOG(0) << "error: the value is out of the range of "
                        "representable values for uint64_t";
+            VLOG(0) << "Error occured when parsing " << i
+                    << " th slot with total slots number: "
+                    << all_slots_.size();
+            VLOG(0) << "and in this slot: " << j
+                    << " th id with total id number: " << num;
             VLOG(0) << "please check line<" << instance_cout << "> in file<"
                     << filename << ">";
             return false;
           }
-          if (i + 1 != num && endptr - str == len) {
+          if (j + 1 != num && endptr - str == len) {
             VLOG(0) << "error: there is a wrong with the number of ids.";
+            VLOG(0) << "Error occured when parsing " << i
+                    << " th slot with total slots number: "
+                    << all_slots_.size();
+            VLOG(0) << "and in this slot: " << j
+                    << " th id with total id number: " << num;
             VLOG(0) << "please check line<" << instance_cout << "> in file<"
                     << filename << ">";
             return false;
@@ -632,8 +658,13 @@ bool MultiSlotDataFeed::ParseOneInstanceFromPipe(
               "The number of ids can not be zero, you need padding "
               "it in data generator; or if there is something wrong with "
               "the data, please check if the data contains unresolvable "
-              "characters.\nplease check this error line: %s",
-              str));
+              "characters.\nplease check this error line: %s, \n Specifically, "
+              "something wrong happened(the length of this slot's feasign is 0)"
+              "when we parse the %d th slots."
+              "Maybe something wrong around this slot",
+              "\nWe detect the feasign number of this slot is %d, "
+              "which is illegal.",
+              str, i, num));
       if (idx != -1) {
         (*instance)[idx].Init(all_slots_type_[i]);
         if ((*instance)[idx].GetType()[0] == 'f') {  // float
@@ -683,8 +714,13 @@ bool MultiSlotDataFeed::ParseOneInstance(std::vector<MultiSlotType>* instance) {
               "The number of ids can not be zero, you need padding "
               "it in data generator; or if there is something wrong with "
               "the data, please check if the data contains unresolvable "
-              "characters.\nplease check this error line: %s.",
-              str));
+              "characters.\nplease check this error line: %s, \n Specifically, "
+              "something wrong happened(the length of this slot's feasign is 0)"
+              "when we parse the %d th slots."
+              "Maybe something wrong around this slot",
+              "\nWe detect the feasign number of this slot is %d, "
+              "which is illegal.",
+              str, i, num));
 
       if (idx != -1) {
         (*instance)[idx].Init(all_slots_type_[i]);
@@ -916,8 +952,13 @@ bool MultiSlotInMemoryDataFeed::ParseOneInstanceFromPipe(Record* instance) {
               "The number of ids can not be zero, you need padding "
               "it in data generator; or if there is something wrong with "
               "the data, please check if the data contains unresolvable "
-              "characters.\nplease check this error line: %s.",
-              str));
+              "characters.\nplease check this error line: %s, \n Specifically, "
+              "something wrong happened(the length of this slot's feasign is 0)"
+              "when we parse the %d th slots."
+              "Maybe something wrong around this slot",
+              "\nWe detect the feasign number of this slot is %d, "
+              "which is illegal.",
+              str, i, num));
       if (idx != -1) {
         if (all_slots_type_[i][0] == 'f') {  // float
           for (int j = 0; j < num; ++j) {
@@ -982,8 +1023,13 @@ bool MultiSlotInMemoryDataFeed::ParseOneInstance(Record* instance) {
               "The number of ids can not be zero, you need padding "
               "it in data generator; or if there is something wrong with "
               "the data, please check if the data contains unresolvable "
-              "characters.\nplease check this error line: %s.",
-              str));
+              "characters.\nplease check this error line: %s, \n Specifically, "
+              "something wrong happened(the length of this slot's feasign is 0)"
+              "when we parse the %d th slots."
+              "Maybe something wrong around this slot",
+              "\nWe detect the feasign number of this slot is %d, "
+              "which is illegal.",
+              str, i, num));
 
       if (idx != -1) {
         if (all_slots_type_[i][0] == 'f') {  // float

paddle/fluid/framework/data_layout_transform.cc

@@ -116,6 +116,8 @@ void* GetDataFromTensor(const Tensor& tensor, mkldnn::memory::data_type type) {
       return platform::to_void_cast(tensor.data<unsigned char>());
     case mkldnn::memory::data_type::s32:
       return platform::to_void_cast(tensor.data<int32_t>());
+    case mkldnn::memory::data_type::bf16:
+      return platform::to_void_cast(tensor.data<paddle::platform::bfloat16>());
     default:
       PADDLE_THROW(
           platform::errors::InvalidArgument("Wrong mkldnn type provided."));

paddle/fluid/framework/data_layout_transform.h

@@ -61,7 +61,8 @@ inline MKLDNNDataType ToMKLDNNDataType(proto::VarType::Type type) {
       {DataTypeTrait<float>::DataType(), MKLDNNDataType::f32},
       {DataTypeTrait<int8_t>::DataType(), MKLDNNDataType::s8},
       {DataTypeTrait<uint8_t>::DataType(), MKLDNNDataType::u8},
-      {DataTypeTrait<int32_t>::DataType(), MKLDNNDataType::s32}};
+      {DataTypeTrait<int32_t>::DataType(), MKLDNNDataType::s32},
+      {DataTypeTrait<platform::bfloat16>::DataType(), MKLDNNDataType::bf16}};
   auto iter = dict.find(static_cast<int>(type));
   if (iter != dict.end()) return iter->second;
   return MKLDNNDataType::undef;
@@ -74,6 +75,9 @@ void innerTransDataLayoutFromMKLDNN(DataLayout in_layout, DataLayout out_layout,
 void TransDataLayoutFromMKLDNN(const OpKernelType& kernel_type_for_var,
                                const OpKernelType& expected_kernel_type,
                                const Tensor& in, Tensor* out);
+
+void* GetDataFromTensor(const Tensor& tensor, MKLDNNDataType type);
+
 #endif
 
 std::vector<int> GetAxis(const DataLayout& from, const DataLayout& to);

paddle/fluid/framework/data_layout_transform_test.cc

@@ -43,3 +43,17 @@ TEST(DataTransform, DataLayoutFunction) {
   EXPECT_TRUE(in.layout() == paddle::framework::DataLayout::kNHWC);
   EXPECT_TRUE(in.dims() == paddle::framework::make_ddim({2, 3, 1, 2}));
 }
+
+#ifdef PADDLE_WITH_MKLDNN
+TEST(DataTransform, GetDataFromTensorDNNL) {
+  auto place = paddle::platform::CPUPlace();
+  paddle::framework::Tensor in = paddle::framework::Tensor();
+  in.mutable_data<paddle::platform::bfloat16>(
+      paddle::framework::make_ddim({2, 3, 1, 2}), place);
+
+  void* in_data =
+      paddle::framework::GetDataFromTensor(in, dnnl::memory::data_type::bf16);
+  EXPECT_EQ(in_data, paddle::platform::to_void_cast(
+                         in.data<paddle::platform::bfloat16>()));
+}
+#endif

paddle/fluid/framework/data_type.cc

@@ -18,6 +18,7 @@
 #include <unordered_map>
 
 using float16 = paddle::platform::float16;
+using bfloat16 = paddle::platform::bfloat16;
 
 namespace paddle {
 namespace framework {

paddle/fluid/framework/data_type.h

@@ -17,6 +17,8 @@ limitations under the License. */
 #include <typeindex>
 #include "paddle/fluid/framework/framework.pb.h"
 #include "paddle/fluid/platform/enforce.h"
+
+#include "paddle/fluid/platform/bfloat16.h"
 #include "paddle/fluid/platform/float16.h"
 
 namespace paddle {
@@ -39,6 +41,7 @@ struct DataTypeTrait<void> {
 #define _ForEachDataType_(callback)                                      \
   _ForEachDataTypeHelper_(callback, float, FP32);                        \
   _ForEachDataTypeHelper_(callback, ::paddle::platform::float16, FP16);  \
+  _ForEachDataTypeHelper_(callback, ::paddle::platform::bfloat16, BF16); \
   _ForEachDataTypeHelper_(callback, double, FP64);                       \
   _ForEachDataTypeHelper_(callback, int, INT32);                         \
   _ForEachDataTypeHelper_(callback, int64_t, INT64);                     \

paddle/fluid/framework/data_type_test.cc

@@ -38,3 +38,25 @@ TEST(DataType, float16) {
   std::string type = "::paddle::platform::float16";
   EXPECT_STREQ(f::DataTypeToString(dtype).c_str(), type.c_str());
 }
+
+TEST(DataType, bfloat16) {
+  using paddle::framework::Tensor;
+  using paddle::platform::CPUPlace;
+  using paddle::platform::bfloat16;
+  namespace f = paddle::framework;
+  f::proto::VarType::Type dtype = f::proto::VarType::BF16;
+
+  Tensor tensor;
+  CPUPlace cpu;
+  tensor.mutable_data(cpu, dtype);
+
+  // test bf16 tensor
+  EXPECT_EQ(tensor.type(), f::ToDataType(typeid(bfloat16)));
+
+  // test bf16 size
+  EXPECT_EQ(f::SizeOfType(dtype), 2u);
+
+  // test debug info
+  std::string type = "::paddle::platform::bfloat16";
+  EXPECT_STREQ(f::DataTypeToString(dtype).c_str(), type.c_str());
+}

paddle/fluid/framework/data_type_transform.cc

@@ -77,6 +77,10 @@ void TransDataType(const OpKernelType& kernel_type_for_var,
       framework::VisitDataType(dst_type,
                                CastDataType<platform::float16>(in, out, ctx));
       break;
+    case proto::VarType::BF16:
+      framework::VisitDataType(dst_type,
+                               CastDataType<platform::bfloat16>(in, out, ctx));
+      break;
     case proto::VarType::FP32:
       framework::VisitDataType(dst_type, CastDataType<float>(in, out, ctx));
       break;

paddle/fluid/framework/data_type_transform_test.cc

@@ -24,6 +24,11 @@ TEST(DataTypeTransform, CPUTransform) {
       paddle::framework::DataLayout::kAnyLayout,
       paddle::framework::LibraryType::kPlain);
 
+  auto kernel_bf16 = paddle::framework::OpKernelType(
+      paddle::framework::proto::VarType::BF16, place,
+      paddle::framework::DataLayout::kAnyLayout,
+      paddle::framework::LibraryType::kPlain);
+
   auto kernel_fp32 = paddle::framework::OpKernelType(
       paddle::framework::proto::VarType::FP32, place,
       paddle::framework::DataLayout::kAnyLayout,
@@ -189,4 +194,120 @@ TEST(DataTypeTransform, CPUTransform) {
                 static_cast<paddle::platform::float16>(in_data_bool[i]).x);
     }
   }
+
+  // data type transform from/to bfloat16
+  {
+    paddle::framework::Tensor in;
+    paddle::framework::Tensor out;
+
+    paddle::platform::bfloat16* ptr =
+        in.mutable_data<paddle::platform::bfloat16>(
+            paddle::framework::make_ddim({2, 3}), place);
+    int data_number = 2 * 3;
+
+    for (int i = 0; i < data_number; ++i) {
+      ptr[i] = i;
+    }
+
+    // transform from bfloat16 to other data types
+    paddle::framework::TransDataType(kernel_bf16, kernel_fp32, in, &out);
+    float* out_data_float = out.data<float>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(out_data_float[i], static_cast<float>(ptr[i]));
+    }
+
+    paddle::framework::TransDataType(kernel_bf16, kernel_fp64, in, &out);
+    double* out_data_double = out.data<double>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(out_data_double[i], static_cast<double>(ptr[i]));
+    }
+
+    paddle::framework::TransDataType(kernel_bf16, kernel_int32, in, &out);
+    int* out_data_int = out.data<int>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(out_data_int[i], static_cast<int>(ptr[i]));
+    }
+
+    paddle::framework::TransDataType(kernel_bf16, kernel_int64, in, &out);
+    int64_t* out_data_int64 = out.data<int64_t>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(out_data_int64[i], static_cast<int64_t>(ptr[i]));
+    }
+
+    paddle::framework::TransDataType(kernel_bf16, kernel_bool, in, &out);
+    bool* out_data_bool = out.data<bool>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(out_data_bool[i], static_cast<bool>(ptr[i]));
+    }
+
+    // transform float to bfloat16
+    float* in_data_float =
+        in.mutable_data<float>(paddle::framework::make_ddim({2, 3}), place);
+    for (int i = 0; i < data_number; ++i) {
+      in_data_float[i] = i;
+    }
+
+    paddle::framework::TransDataType(kernel_fp32, kernel_bf16, in, &out);
+    ptr = out.data<paddle::platform::bfloat16>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(ptr[i].x,
+                static_cast<paddle::platform::bfloat16>(in_data_float[i]).x);
+    }
+
+    // transform double to bfloat16
+    double* in_data_double =
+        in.mutable_data<double>(paddle::framework::make_ddim({2, 3}), place);
+    for (int i = 0; i < data_number; ++i) {
+      in_data_double[i] = i;
+    }
+
+    paddle::framework::TransDataType(kernel_fp64, kernel_bf16, in, &out);
+    ptr = out.data<paddle::platform::bfloat16>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(ptr[i].x,
+                static_cast<paddle::platform::bfloat16>(in_data_double[i]).x);
+    }
+
+    // transform int to bfloat16
+    int* in_data_int =
+        in.mutable_data<int>(paddle::framework::make_ddim({2, 3}), place);
+    for (int i = 0; i < data_number; ++i) {
+      in_data_int[i] = i;
+    }
+
+    paddle::framework::TransDataType(kernel_int32, kernel_bf16, in, &out);
+    ptr = out.data<paddle::platform::bfloat16>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(ptr[i].x,
+                static_cast<paddle::platform::bfloat16>(in_data_int[i]).x);
+    }
+
+    // transform int64 to bfloat16
+    int64_t* in_data_int64 =
+        in.mutable_data<int64_t>(paddle::framework::make_ddim({2, 3}), place);
+    for (int i = 0; i < data_number; ++i) {
+      in_data_int64[i] = i;
+    }
+
+    paddle::framework::TransDataType(kernel_int64, kernel_bf16, in, &out);
+    ptr = out.data<paddle::platform::bfloat16>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(ptr[i].x,
+                static_cast<paddle::platform::bfloat16>(in_data_int64[i]).x);
+    }
+
+    // transform bool to bfloat16
+    bool* in_data_bool =
+        in.mutable_data<bool>(paddle::framework::make_ddim({2, 3}), place);
+    for (int i = 0; i < data_number; ++i) {
+      in_data_bool[i] = i;
+    }
+
+    paddle::framework::TransDataType(kernel_bool, kernel_bf16, in, &out);
+    ptr = out.data<paddle::platform::bfloat16>();
+    for (int i = 0; i < data_number; ++i) {
+      EXPECT_EQ(ptr[i].x,
+                static_cast<paddle::platform::bfloat16>(in_data_bool[i]).x);
+    }
+  }
 }

paddle/fluid/framework/details/CMakeLists.txt

@@ -74,6 +74,7 @@ set(SSA_GRAPH_EXECUTOR_DEPS graph framework_proto
     eager_deletion_pass
     buffer_shared_inplace_op_pass
     buffer_shared_cross_op_memory_reuse_pass
+    inplace_addto_op_pass
     set_reader_device_info_utils
     add_reader_dependency_pass)
 cc_library(ssa_graph_executor SRCS ssa_graph_executor.cc DEPS ${SSA_GRAPH_EXECUTOR_DEPS})

paddle/fluid/framework/details/all_reduce_op_handle.cc

@@ -12,7 +12,9 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/all_reduce_op_handle.h"
+
 #include <algorithm>
+
 #include "paddle/fluid/framework/details/container_cast.h"
 #include "paddle/fluid/framework/details/reduce_and_gather.h"
 #include "paddle/fluid/framework/details/variable_visitor.h"
@@ -34,14 +36,24 @@ AllReduceOpHandle::AllReduceOpHandle(ir::Node *node,
                                      const std::vector<platform::Place> &places,
                                      const platform::NCCLCommunicator *ctxs)
     : NCCLOpHandleBase(node, places, ctxs), local_scopes_(local_scopes) {
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
 }
 #else
 AllReduceOpHandle::AllReduceOpHandle(ir::Node *node,
                                      const std::vector<Scope *> &local_scopes,
                                      const std::vector<platform::Place> &places)
     : OpHandleBase(node), local_scopes_(local_scopes), places_(places) {
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
 }
 #endif
 
@@ -60,13 +72,25 @@ void AllReduceOpHandle::AllReduceImpl(
     const std::vector<VarHandle *> &in_var_handles,
     const std::vector<VarHandle *> &out_var_handles) {
   size_t num_places = places_.size();
-  PADDLE_ENFORCE_EQ(
-      in_var_handles.size(), num_places,
-      "The NoDummyInputSize should be equal to the number of places.");
+  PADDLE_ENFORCE_EQ(in_var_handles.size(), num_places,
+                    platform::errors::InvalidArgument(
+                        "The NoDummyInputSize should be equal "
+                        "to the number of places, but got NoDummyInputSize is "
+                        "%d and the number of place is %d.",
+                        in_var_handles.size(), num_places));
   PADDLE_ENFORCE_EQ(
       in_var_handles.size(), out_var_handles.size(),
-      "The NoDummyInputSize and NoDummyOutputSize should be equal.");
-  PADDLE_ENFORCE_EQ(local_exec_scopes_.size(), num_places);
+      platform::errors::InvalidArgument(
+          "The NoDummyInputSize and NoDummyOutputSize should be "
+          "equal, but got NoDummyInputSize is %d and NoDummyOutputSize is %d.",
+          in_var_handles.size(), out_var_handles.size()));
+  PADDLE_ENFORCE_EQ(
+      local_exec_scopes_.size(), num_places,
+      platform::errors::InvalidArgument(
+          "The number of local scopes should be equal "
+          "to the number of places, but got the number of local scopes is "
+          "%d and the number of place is %d.",
+          in_var_handles.size(), num_places));
 
   std::vector<const void *> lod_tensor_data;
   std::vector<platform::Place> places;
@@ -78,23 +102,36 @@ void AllReduceOpHandle::AllReduceImpl(
   for (size_t i = 0; i < local_exec_scopes_.size(); ++i) {
     auto &local_scope = local_exec_scopes_[i];
     auto var = local_scope->FindVar(in_var_handles[i]->name());
-    PADDLE_ENFORCE_NOT_NULL(var, "%s is not found int scope.",
-                            in_var_handles[i]->name());
+    PADDLE_ENFORCE_NOT_NULL(var, platform::errors::NotFound(
+                                     "Variable %s is not found in local scope.",
+                                     in_var_handles[i]->name()));
     auto &lod_tensor = var->Get<LoDTensor>();
 
     if (i == 0) {
       numel = static_cast<int64_t>(lod_tensor.numel());
       // only enforce place0, we will enforce other palce numel == place0 numel
       PADDLE_ENFORCE_GT(
-          numel, 0, platform::errors::InvalidArgument(
-                        "The numel of tensos=[%s] must > 0. But now numel=[%d]",
+          numel, 0,
+          platform::errors::PreconditionNotMet(
+              "The numel of tensor %s should be > 0, but got numel is %d.",
               in_var_handles[i]->name(), numel));
       dtype = lod_tensor.type();
       is_gpu_place = platform::is_gpu_place(lod_tensor.place());
     }
-    PADDLE_ENFORCE_EQ(numel, static_cast<int64_t>(lod_tensor.numel()));
-    PADDLE_ENFORCE_EQ(dtype, lod_tensor.type());
-    PADDLE_ENFORCE_EQ(is_gpu_place, platform::is_gpu_place(lod_tensor.place()));
+    PADDLE_ENFORCE_EQ(
+        numel, static_cast<int64_t>(lod_tensor.numel()),
+        platform::errors::PreconditionNotMet(
+            "The size of tensors of the same variable in different local "
+            "scopes should be equal."));
+    PADDLE_ENFORCE_EQ(
+        dtype, lod_tensor.type(),
+        platform::errors::PreconditionNotMet(
+            "The dtype of tensors of the same variable in different local "
+            "scopes should be equal."));
+    PADDLE_ENFORCE_EQ(is_gpu_place, platform::is_gpu_place(lod_tensor.place()),
+                      platform::errors::PreconditionNotMet(
+                          "The place type of tensors of the same variable "
+                          "in different local scopes should be equal."));
 
     lod_tensor_data.emplace_back(lod_tensor.data<void>());
     places.emplace_back(lod_tensor.place());
@@ -102,8 +139,12 @@ void AllReduceOpHandle::AllReduceImpl(
     VLOG(10) << "place:" << i << ", input_name:" << in_var_handles[i]->name()
              << ", out_name:" << out_var_handles[i]->name();
 
-    PADDLE_ENFORCE_EQ(in_var_handles[i]->name(), out_var_handles[i]->name(),
-                      "The name of input and output should be equal.");
+    PADDLE_ENFORCE_EQ(
+        in_var_handles[i]->name(), out_var_handles[i]->name(),
+        platform::errors::InvalidArgument(
+            "The name of input and output of all_reduce op should be equal, "
+            "but got input is %s and output is %s.",
+            in_var_handles[i]->name(), out_var_handles[i]->name()));
   }
 
   std::vector<std::string> grad_var_names;
@@ -122,7 +163,9 @@ void AllReduceOpHandle::AllReduceFunc(
     const std::vector<std::string> &out_var_names) {
   if (is_gpu_place(places[0])) {
 #if defined(PADDLE_WITH_NCCL)
-    PADDLE_ENFORCE_NOT_NULL(nccl_ctxs_, "nccl_ctxs should not be nullptr.");
+    PADDLE_ENFORCE_NOT_NULL(nccl_ctxs_,
+                            platform::errors::InvalidArgument(
+                                "The nccl context should not be NULL."));
     ncclDataType_t nccl_dtype = platform::ToNCCLDataType(dtype);
     std::vector<std::function<void()>> all_reduce_calls;
     for (size_t i = 0; i < local_exec_scopes_.size(); ++i) {
@@ -134,7 +177,8 @@ void AllReduceOpHandle::AllReduceFunc(
     }
     NCCLAllReduceFunc(all_reduce_calls);
 #else
-    PADDLE_THROW("Not compiled with CUDA.");
+    PADDLE_THROW(
+        platform::errors::PreconditionNotMet("Not compiled with CUDA."));
 #endif
   } else {  // Special handle CPU only Operator's gradient. Like CRF
     auto &trg = *local_exec_scopes_[0]

paddle/fluid/framework/details/async_ssa_graph_executor.cc

@@ -89,8 +89,19 @@ AsyncSSAGraphExecutor::AsyncSSAGraphExecutor(
       places_(std::move(places)),
       graphs_(std::move(graphs)) {
   VLOG(3) << "build AsyncSSAGraphExecutor";
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
-  PADDLE_ENFORCE_EQ(local_scopes_.size(), local_exec_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
+  PADDLE_ENFORCE_EQ(
+      local_scopes_.size(), local_exec_scopes_.size(),
+      platform::errors::InvalidArgument(
+          "The number of local scopes and the number of local execution scopes "
+          "should be equal, but got number of local scopes is %d and "
+          "number of local execution scopes is %d.",
+          local_scopes_.size(), local_exec_scopes_.size()));
 
   // set the correct size of thread pool to each device.
   strategy_.num_threads_ = strategy_.num_threads_ < places_.size()

paddle/fluid/framework/details/build_strategy.h

@@ -19,6 +19,7 @@
 #include <unordered_set>
 #include <utility>
 #include <vector>
+
 #include "boost/optional.hpp"
 #include "paddle/fluid/framework/ir/pass_builder.h"
 #include "paddle/fluid/framework/program_desc.h"
@@ -119,6 +120,9 @@ struct BuildStrategy {
   // Turn on inplace by default.
   bool enable_inplace_{true};
 
+  // Turn off inplace addto by default.
+  bool enable_addto_{false};
+
   // FIXME(zcd): is_distribution_ is a temporary field, because in pserver mode,
   // num_trainers is 1, so the current fields of build_strategy doesn't tell if
   // it's distributed model.

paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.cc

@@ -12,12 +12,14 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.h"
+
 #include <deque>
 #include <memory>
 #include <string>
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
+
 #include "paddle/fluid/framework/details/computation_op_handle.h"
 #include "paddle/fluid/framework/details/fetch_async_op_handle.h"
 #include "paddle/fluid/framework/details/multi_devices_helper.h"
@@ -48,7 +50,9 @@ FastThreadedSSAGraphExecutor::FastThreadedSSAGraphExecutor(
       bootstrap_ops_.emplace_back(op);
     }
   }
-  PADDLE_ENFORCE_GT(op_deps_.size(), 0, "The graph doesn't have operators.");
+  PADDLE_ENFORCE_GT(op_deps_.size(), 0,
+                    platform::errors::PreconditionNotMet(
+                        "The graph doesn't have operators."));
   PrepareAtomicOpDeps();
 }
 

paddle/fluid/framework/details/fetch_op_handle.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/fetch_op_handle.h"
+
 #include <string>
 #include <utility>
 #include <vector>
+
 #include "paddle/fluid/platform/profiler.h"
 
 namespace paddle {
@@ -138,8 +140,10 @@ void FetchOpHandle::RunImpl() {
     auto *var_handle = static_cast<VarHandle *>(inputs_[i]);
     auto &scope = scopes.at(var_handle->scope_idx());
     auto *var = scope->FindVar(var_handle->name());
-    PADDLE_ENFORCE_NOT_NULL(var, "Cannot find variable %s in execution scope",
-                            var_handle->name());
+    PADDLE_ENFORCE_NOT_NULL(
+        var,
+        platform::errors::NotFound(
+            "Cannot find variable %s in execution scope.", var_handle->name()));
 
     if (var->IsType<LoDTensor>()) {
       auto &t = var->Get<framework::LoDTensor>();

paddle/fluid/framework/details/nan_inf_utils_detail.cc

@@ -167,6 +167,8 @@ static void PrintNanInf(const T* value, const size_t numel, int print_num,
 // more detail see: 180 page of
 // https://www.openmp.org/wp-content/uploads/OpenMP4.0.0.pdf
 #pragma omp declare reduction(+ : paddle::platform::float16 : omp_out += omp_in)
+#pragma omp declare reduction(+ : paddle::platform::bfloat16 : omp_out += \
+                              omp_in)
 #endif
 
 template <typename T>
@@ -205,6 +207,21 @@ void CheckNanInf<paddle::platform::float16>(
     PrintNanInf(value, numel, print_num, op_type, var_name);
   }
 }
+
+template <>
+void CheckNanInf<paddle::platform::bfloat16>(
+    const paddle::platform::bfloat16* value, const size_t numel, int print_num,
+    const std::string& op_type, const std::string& var_name) {
+  float sum = 0.0f;
+#pragma omp parallel for reduction(+ : sum)
+  for (size_t i = 0; i < numel; ++i) {
+    sum += static_cast<float>(value[i] - value[i]);
+  }
+
+  if (std::isnan(sum) || std::isinf(sum)) {
+    PrintNanInf(value, numel, print_num, op_type, var_name);
+  }
+}
 #endif
 
 template <>

paddle/fluid/framework/details/op_handle_base.cc

@@ -12,6 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 #include "paddle/fluid/framework/details/op_handle_base.h"
+
 #include <map>
 #include <unordered_set>
 
@@ -88,6 +89,12 @@ void OpHandleBase::Run(bool use_cuda) {
   PADDLE_ENFORCE(!use_cuda);
 #endif
 
+  // skip running current op, used with inplace_addto_op_pass
+  if (skip_running_) {
+    VLOG(4) << "skip running: " << Name();
+    return;
+  }
+
   RunImpl();
 }
 

paddle/fluid/framework/details/op_handle_base.h

@@ -18,6 +18,7 @@
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
+
 #include "paddle/fluid/framework/details/var_handle.h"
 #include "paddle/fluid/framework/ir/node.h"
 #include "paddle/fluid/platform/device_context.h"
@@ -52,6 +53,10 @@ class OpHandleBase {
 
   virtual Priority GetPriority() const { return kNormal; }
 
+  virtual bool GetSkipRunning() const { return skip_running_; }
+
+  virtual void SetSkipRunning(bool skip_runing) { skip_running_ = skip_runing; }
+
   virtual std::string Name() const = 0;
 
   void Run(bool use_cuda);
@@ -131,6 +136,7 @@ class OpHandleBase {
   std::map<platform::Place, platform::DeviceContext *> dev_ctxes_;
 
   std::vector<Scope *> local_exec_scopes_;
+  bool skip_running_ = false;
 
 #ifdef PADDLE_WITH_CUDA
   std::unordered_map<int, cudaEvent_t> events_;

paddle/fluid/framework/details/parallel_ssa_graph_executor.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/parallel_ssa_graph_executor.h"
+
 #include <algorithm>
 #include <memory>
 #include <utility>
+
 #include "paddle/fluid/framework/ir/graph_helper.h"
 
 namespace paddle {
@@ -104,7 +106,12 @@ ParallelSSAGraphExecutor::ParallelSSAGraphExecutor(
       places_(places),
       graphs_(std::move(graphs)),
       feed_status_(places.size(), FeedStatus::kNone) {
-  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
+  PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size(),
+                    platform::errors::InvalidArgument(
+                        "The number of places and the number of local scopes "
+                        "should be equal, but got number of places is %d and "
+                        "number of local scopes is %d.",
+                        places_.size(), local_scopes_.size()));
 
   PADDLE_ENFORCE_EQ(places_.size(), graphs_.size(),
                     platform::errors::InvalidArgument(

paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc

@@ -13,10 +13,12 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.h"
+
 #include <stdexcept>
 #include <string>
 #include <utility>
 #include <vector>
+
 #include "paddle/fluid/framework/details/multi_devices_helper.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/variable_helper.h"
@@ -37,7 +39,13 @@ ScopeBufferedSSAGraphExecutor::ScopeBufferedSSAGraphExecutor(
       var_infos_(std::move(var_infos)),
       places_(std::move(places)),
       scope_monitor_(places_, local_exec_scopes_) {
-  PADDLE_ENFORCE_EQ(local_scopes_.size(), local_exec_scopes_.size());
+  PADDLE_ENFORCE_EQ(
+      local_scopes_.size(), local_exec_scopes_.size(),
+      platform::errors::InvalidArgument(
+          "The number of local scopes and the number of local execution scopes "
+          "should be equal, but got number of local scopes is %d and "
+          "number of local execution scopes is %d.",
+          local_scopes_.size(), local_exec_scopes_.size()));
   PrepareLocalExeScopes();
 }
 

paddle/fluid/framework/details/share_tensor_buffer_functor.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/share_tensor_buffer_functor.h"
+
 #include <string>
 #include <unordered_map>
 #include <unordered_set>
+
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/selected_rows.h"
 #include "paddle/fluid/platform/enforce.h"
@@ -29,7 +31,8 @@ static inline const Tensor &GetTensorFromVar(const Variable *var) {
   if (var->IsType<LoDTensor>()) {
     return var->Get<LoDTensor>();
   } else {
-    PADDLE_THROW("Variable must be type of LoDTensor");
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "Variable must be type of LoDTensor."));
   }
 }
 
@@ -37,20 +40,27 @@ static inline Tensor *GetMutableTensorFromVar(Variable *var) {
   if (var->IsType<LoDTensor>()) {
     return var->GetMutable<LoDTensor>();
   } else {
-    PADDLE_THROW("Variable must be type of LoDTensor");
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "Variable must be type of LoDTensor."));
   }
 }
 
 ShareTensorBufferFunctor::ShareTensorBufferFunctor(
     Scope *scope, size_t scope_idx, const std::string &op_type,
     const std::vector<const ir::MemOptVarInfo *> &in_var_infos,
-    const std::vector<std::string> &out_var_names)
+    const std::vector<std::string> &out_var_names, bool share_dims)
     : scope_(scope),
       scope_idx_(scope_idx),
       op_type_(op_type),
       in_var_infos_(in_var_infos),
-      out_var_names_(out_var_names) {
-  PADDLE_ENFORCE_EQ(in_var_infos_.size(), out_var_names_.size());
+      out_var_names_(out_var_names),
+      share_dims_(share_dims) {
+  PADDLE_ENFORCE_EQ(in_var_infos_.size(), out_var_names_.size(),
+                    platform::errors::PreconditionNotMet(
+                        "The number of input variables and output variables "
+                        "should be equal, but got number of input variables is "
+                        "%d and number of output variables is %d.",
+                        in_var_infos_.size(), out_var_names_.size()));
   for (size_t i = 0; i < in_var_infos_.size(); ++i) {
     AddReuseVarPair(in_var_infos_[i], out_var_names_[i]);
   }
@@ -67,32 +77,59 @@ ShareTensorBufferFunctor::ReusedVars() const {
 
 void ShareTensorBufferFunctor::AddReuseVarPair(
     const ir::MemOptVarInfo *in_var_info, const std::string &out_var_name) {
-  PADDLE_ENFORCE_NOT_NULL(in_var_info, "in_var_info cannot be nullptr");
+  PADDLE_ENFORCE_NOT_NULL(
+      in_var_info,
+      platform::errors::InvalidArgument(
+          "The input variables to be inplaced should not be NULL."));
   PADDLE_ENFORCE_NE(in_var_info->Name(), out_var_name,
-                    "in/out cannot have same name: %s", out_var_name);
+                    platform::errors::InvalidArgument(
+                        "The input variable and output variable to be inplaced "
+                        "cannot have the same name: %s.",
+                        out_var_name));
   in_var_infos_.emplace_back(in_var_info);
   out_var_names_.emplace_back(out_var_name);
 }
 
 void ShareTensorBufferFunctor::CallOnce() {
-  PADDLE_ENFORCE(in_out_vars_.empty(), "in_out_vars_ must be initialized here");
+  PADDLE_ENFORCE(in_out_vars_.empty(),
+                 platform::errors::InvalidArgument(
+                     "The input-output variable pairs to be "
+                     "inplaced should be initialized here."));
   for (size_t i = 0; i < in_var_infos_.size(); ++i) {
     auto *in_var = exec_scope_->FindVar(in_var_infos_[i]->Name());
     auto *out_var = exec_scope_->FindVar(out_var_names_[i]);
-    PADDLE_ENFORCE_NOT_NULL(in_var);
-    PADDLE_ENFORCE_NOT_NULL(out_var);
-    PADDLE_ENFORCE_NE(in_var, out_var);
+    PADDLE_ENFORCE_NOT_NULL(
+        in_var, platform::errors::NotFound(
+                    "The input variable(%s)to be inplaced should not be NULL.",
+                    in_var_infos_[i]->Name()));
+    PADDLE_ENFORCE_NOT_NULL(
+        out_var,
+        platform::errors::NotFound(
+            "The output variable(%s) to be inplaced should not be NULL.",
+            out_var_names_[i]));
+    PADDLE_ENFORCE_NE(
+        in_var, out_var,
+        platform::errors::PreconditionNotMet(
+            "The input variable and output variable to be inplaced "
+            "cannot be the same variable(%s).",
+            out_var_names_[i]));
     in_out_vars_.emplace_back(in_var, out_var);
   }
 }
 
 void ShareTensorBufferFunctor::operator()(Scope *exec_scope) {
   if (!exec_scope_) {
-    PADDLE_ENFORCE_NOT_NULL(exec_scope);
+    PADDLE_ENFORCE_NOT_NULL(exec_scope,
+                            platform::errors::InvalidArgument(
+                                "The given execution scope should not be NULL "
+                                "if the cached scope is NULL."));
     exec_scope_ = exec_scope;
     CallOnce();
   } else {
-    PADDLE_ENFORCE(exec_scope_ == exec_scope, "Scope must be the same");
+    PADDLE_ENFORCE_EQ(exec_scope_, exec_scope,
+                      platform::errors::InvalidArgument(
+                          "The given execution scope and the cached execution "
+                          "scope should be the same."));
   }
 
   for (size_t i = 0; i < in_var_infos_.size(); ++i) {
@@ -115,6 +152,13 @@ void ShareTensorBufferFunctor::operator()(Scope *exec_scope) {
     } else {
       out_tensor->ShareBufferWith(in_tensor);
 
+      // NOTE(zhiqiu): In the case of inplace addto, if the operator of
+      // the in_out_vars is skipped during running, we should set the dims of
+      // output as the same as input.
+      if (share_dims_) {
+        out_tensor->Resize(in_tensor.dims());
+      }
+
       VLOG(2) << "Share tensor buffer when running " << op_type_ << " : "
               << in_var_info->Name() << " -> " << out_var_names_[i];
     }

paddle/fluid/framework/details/share_tensor_buffer_functor.h

@@ -19,6 +19,7 @@
 #include <unordered_set>
 #include <utility>
 #include <vector>
+
 #include "paddle/fluid/framework/details/op_handle_base.h"
 #include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
 #include "paddle/fluid/framework/scope.h"
@@ -40,11 +41,13 @@ class ShareTensorBufferFunctor {
   ShareTensorBufferFunctor(
       Scope *scope, size_t scope_idx, const std::string &op_type,
       const std::vector<const ir::MemOptVarInfo *> &in_var_infos,
-      const std::vector<std::string> &out_var_names);
+      const std::vector<std::string> &out_var_names, bool share_dims = false);
 
   void AddReuseVarPair(const ir::MemOptVarInfo *in_var_info,
                        const std::string &out_var_name);
 
+  void SetShareDims(bool share_dims) { share_dims_ = share_dims; }
+
   void operator()(Scope *exec_scope);
 
   std::unordered_map<std::string, std::string> ReusedVars() const;
@@ -66,6 +69,11 @@ class ShareTensorBufferFunctor {
   std::vector<std::string> out_var_names_;
 
   std::vector<std::pair<const Variable *, Variable *>> in_out_vars_;
+
+  // NOTE(zhiqiu): In the case of inplace addto, if the operator of
+  // the in_out_vars is skipped during running, we should set the dims of output
+  // as the same as input.
+  bool share_dims_{false};
 };
 
 }  // namespace details

paddle/fluid/framework/details/share_tensor_buffer_op_handle.cc

@@ -13,8 +13,10 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/share_tensor_buffer_op_handle.h"
+
 #include <string>
 #include <unordered_set>
+
 #include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
 #include "paddle/fluid/framework/lod_tensor.h"
 #include "paddle/fluid/framework/scope.h"
@@ -32,26 +34,35 @@ ComputationOpHandle *GetUniquePendingComputationOpHandle(
     for (ir::Node *pending_op : out_var->outputs) {
       auto &op = pending_op->Wrapper<OpHandleBase>();
       auto *compute_op = dynamic_cast<ComputationOpHandle *>(&op);
-      PADDLE_ENFORCE_NOT_NULL(compute_op);
+      PADDLE_ENFORCE_NOT_NULL(
+          compute_op,
+          platform::errors::PreconditionNotMet(
+              "The pending OpHandle should be ComputationOpHandle."));
 
       if (result_op == nullptr) {
         result_op = compute_op;
       } else {
-        PADDLE_ENFORCE_EQ(result_op, compute_op);
+        PADDLE_ENFORCE_EQ(
+            result_op, compute_op,
+            platform::errors::PreconditionNotMet(
+                "The pending OpHandle should be the unique one."));
       }
     }
   }
 
-  PADDLE_ENFORCE_NOT_NULL(result_op);
+  PADDLE_ENFORCE_NOT_NULL(result_op,
+                          platform::errors::PreconditionNotMet(
+                              "The pending OpHandle should not be NULL."));
   return result_op;
 }
 
 ShareTensorBufferOpHandle::ShareTensorBufferOpHandle(
     ir::Node *node, Scope *scope, size_t scope_idx, const std::string &op_type,
     const std::vector<const ir::MemOptVarInfo *> &in_var_infos,
-    const std::vector<std::string> &out_var_names)
+    const std::vector<std::string> &out_var_names, bool share_dims)
     : OpHandleBase(node),
-      functor_(scope, scope_idx, op_type, in_var_infos, out_var_names) {}
+      functor_(scope, scope_idx, op_type, in_var_infos, out_var_names,
+               share_dims) {}
 
 std::unordered_map<std::string, std::string>
 ShareTensorBufferOpHandle::ReusedVars() const {
@@ -63,6 +74,10 @@ void ShareTensorBufferOpHandle::AddReuseVarPair(
   functor_.AddReuseVarPair(in_var_info, out_var_name);
 }
 
+void ShareTensorBufferOpHandle::SetShareDims(bool share_dims) {
+  functor_.SetShareDims(share_dims);
+}
+
 void ShareTensorBufferOpHandle::InitCUDA() {
 #ifdef PADDLE_WITH_CUDA
   int dev_id =

paddle/fluid/framework/details/share_tensor_buffer_op_handle.h

@@ -17,6 +17,7 @@
 #include <unordered_map>
 #include <utility>
 #include <vector>
+
 #include "paddle/fluid/framework/details/computation_op_handle.h"
 #include "paddle/fluid/framework/details/op_handle_base.h"
 #include "paddle/fluid/framework/details/share_tensor_buffer_functor.h"
@@ -31,7 +32,7 @@ class ShareTensorBufferOpHandle : public OpHandleBase {
       ir::Node *node, Scope *scope, size_t scope_idx,
       const std::string &op_type,
       const std::vector<const ir::MemOptVarInfo *> &in_vars_infos,
-      const std::vector<std::string> &out_var_names);
+      const std::vector<std::string> &out_var_names, bool share_dims = false);
 
   std::unordered_map<std::string, std::string> ReusedVars() const;
 
@@ -42,6 +43,8 @@ class ShareTensorBufferOpHandle : public OpHandleBase {
   void AddReuseVarPair(const ir::MemOptVarInfo *in_var_info,
                        const std::string &out_var_name);
 
+  void SetShareDims(bool share_dims);
+
   const ShareTensorBufferFunctor &Functor() const { return functor_; }
 
  protected:

paddle/fluid/framework/details/ssa_graph_executor.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/ssa_graph_executor.h"
+
 #include "paddle/fluid/framework/details/fetch_async_op_handle.h"
 
 namespace paddle {
@@ -27,8 +28,9 @@ void ClearFetchOp(ir::Graph* graph, std::vector<OpHandleBase*>* fetch_ops) {
     PADDLE_ENFORCE_EQ(dynamic_cast<FetchOpHandle*>(op) != nullptr ||
                           dynamic_cast<FetchAsyncOpHandle*>(op) != nullptr,
                       true,
+                      platform::errors::PreconditionNotMet(
                           "The input ops of ClearFetchOp function should be "
-                      "FetchOpHandle or FetchAsyncOpHandle.");
+                          "FetchOpHandle or FetchAsyncOpHandle."));
     for (auto& out_var : op->Node()->outputs) {
       graph->RemoveNode(out_var);
     }

paddle/fluid/framework/details/threaded_ssa_graph_executor.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
+
 #include "paddle/fluid/framework/ir/graph_helper.h"
 #include "paddle/fluid/platform/profiler.h"
 
@@ -138,7 +139,10 @@ inline FetchResultType ThreadedSSAGraphExecutor::RunImpl(
         }
       }
     }
-    PADDLE_ENFORCE(ready_ops.empty());
+    PADDLE_ENFORCE_EQ(
+        ready_ops.empty(), true,
+        platform::errors::Fatal("After the execution of computation graph, "
+                                "there are unexecuted operators left."));
   }
 
   // Wait FetchOps.
@@ -165,9 +169,8 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
     FetchResultType *fetch_data, bool return_merged) {
   std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
   std::unordered_set<VarHandleBase *> local_ready_vars;
-  std::unordered_set<std::string> fetch_tensor_set(fetch_tensors.begin(),
-                                                   fetch_tensors.end());
-  for (auto &fetch_var_name : fetch_tensor_set) {
+
+  for (auto &fetch_var_name : fetch_tensors) {
     for (auto &var_map : graph_->Get<details::GraphVars>(details::kGraphVars)) {
       auto it = var_map.find(fetch_var_name);
       if (it != var_map.end()) {
@@ -231,7 +234,11 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
       ready_ops->insert(static_cast<OpHandleBase *>(op));
     }
   }
-  PADDLE_ENFORCE_EQ(local_ready_vars.size(), 0);
+  PADDLE_ENFORCE_EQ(
+      local_ready_vars.size(), 0,
+      platform::errors::Fatal(
+          "The number of ready variables should be 0, but got %d.",
+          local_ready_vars.size()));
 }
 
 void ThreadedSSAGraphExecutor::InsertPendingOp(
@@ -277,7 +284,9 @@ void ThreadedSSAGraphExecutor::PrepareOpDeps() {
     }
   }
   op_deps_->num_ops_ = ready_ops.size() + pending_ops.size();
-  PADDLE_ENFORCE_GT(op_deps_->num_ops_, 0, "The graph doesn't have operators.");
+  PADDLE_ENFORCE_GT(
+      op_deps_->num_ops_, 0,
+      platform::errors::InvalidArgument("The graph doesn't have operators."));
 
   for (auto ready_var : ready_vars) {
     pending_vars.erase(ready_var);

paddle/fluid/framework/details/threaded_ssa_graph_executor.h

@@ -14,6 +14,8 @@
 
 #pragma once
 
+#include <ThreadPool.h>  // ThreadPool in thrird party
+
 #include <deque>
 #include <functional>
 #include <list>
@@ -24,8 +26,6 @@
 #include <utility>
 #include <vector>
 
-#include <ThreadPool.h>  // ThreadPool in thrird party
-
 #include "paddle/fluid/framework/blocking_queue.h"
 #include "paddle/fluid/framework/details/exception_holder.h"
 #include "paddle/fluid/framework/details/execution_strategy.h"

paddle/fluid/framework/details/var_handle.h

@@ -54,8 +54,10 @@ struct VarHandleBase {
 
   void AddOutput(OpHandleBase* out, ir::Node* node) {
     if (pending_ops_.find(out) == pending_ops_.end()) {
-      PADDLE_ENFORCE(out != nullptr, "The output of %s should not be nullptr",
-                     this->Node()->Name());
+      PADDLE_ENFORCE_NOT_NULL(out,
+                              platform::errors::InvalidArgument(
+                                  "The output added to VarHandle %s is NULL.",
+                                  this->Node()->Name()));
       pending_ops_.insert(out);
       node_->outputs.push_back(node);
     }
@@ -120,7 +122,10 @@ struct VarHandle : public VarHandleBase {
   bool HasEvent() { return has_event_; }
 
   const cudaEvent_t& GetEvent() {
-    PADDLE_ENFORCE(HasEvent(), "The event is not set.");
+    PADDLE_ENFORCE_EQ(
+        HasEvent(), true,
+        platform::errors::PreconditionNotMet(
+            "The cuda event is not set, maybe InitCUDA() is not called."));
     return event_;
   }
 

paddle/fluid/framework/details/variable_visitor.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/variable_visitor.h"
+
 #include "paddle/fluid/framework/selected_rows.h"
 namespace paddle {
 namespace framework {
@@ -24,7 +25,9 @@ static void VisitVariable(Variable* var, Func* func) {
   } else if (var->IsType<SelectedRows>()) {
     (*func)(var->GetMutable<SelectedRows>());
   } else {
-    PADDLE_THROW("Not supported type %s", ToTypeName(var->Type()));
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "VisitVariable is not supported for type %s.",
+        ToTypeName(var->Type())));
   }
 }
 
@@ -35,7 +38,8 @@ static void VisitVariable(const Variable& var, Func* func) {
   } else if (var.IsType<SelectedRows>()) {
     (*func)(var.Get<SelectedRows>());
   } else {
-    PADDLE_THROW("Not supported type %s", ToTypeName(var.Type()));
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "VisitVariable is not supported for type %s.", ToTypeName(var.Type())));
   }
 }
 
@@ -50,7 +54,8 @@ struct TensorVisitor {
 
   template <typename T>
   void operator()() {
-    PADDLE_THROW("Not Support to get LoDTensor from %s", typeid(T).name());
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "Getting tensor from type %s is not supported.", typeid(T).name()));
   }
 };
 
@@ -78,8 +83,8 @@ struct ShareDimsAndLoDVisitor {
 
   template <typename T>
   void operator()(const T&) {
-    PADDLE_ENFORCE("ShareDimsAndLoD is not supported by type %s",
-                   typeid(T).name());
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "ShareDimsAndLoD is not supported for type %s.", typeid(T).name()));
   }
 };
 
@@ -89,42 +94,54 @@ void VariableVisitor::ShareDimsAndLoD(const Variable& src, Variable* trg) {
 }
 
 struct EnforceShapeAndDTypeEQVisitor {
-  const Variable* trg_;
+  const Variable* dst_;
 
   void operator()(const LoDTensor& src) {
-    auto& tensor = trg_->Get<LoDTensor>();
-    PADDLE_ENFORCE_EQ(
-        src.place().which(), tensor.place().which(),
-        "The Places of the two Variable must be all on CPU or all on GPU.");
+    auto& tensor = dst_->Get<LoDTensor>();
+    PADDLE_ENFORCE_EQ(src.place().which(), tensor.place().which(),
+                      platform::errors::PreconditionNotMet(
+                          "The place type of the two variables is not equal."));
     PADDLE_ENFORCE_EQ(src.type(), tensor.type(),
-                      "The dtype of the two Variable is not equal.");
-    PADDLE_ENFORCE_EQ(src.dims(), tensor.dims(),
-                      "The dims of the two Variable is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The dtype of the two variables is not equal."));
+    PADDLE_ENFORCE_EQ(
+        src.dims(), tensor.dims(),
+        platform::errors::PreconditionNotMet(
+            "The layout of the two variables' tensors is not equal."));
     PADDLE_ENFORCE_EQ(src.lod(), tensor.lod(),
-                      "The lod of the two Variable is not equal.");
-    PADDLE_ENFORCE_EQ(src.layout(), tensor.layout(),
-                      "The layout of the two Variable's tensor is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The lod of the two variable is not equal."));
+    PADDLE_ENFORCE_EQ(
+        src.layout(), tensor.layout(),
+        platform::errors::PreconditionNotMet(
+            "The layout of the two variables' tensors tensor is not equal."));
   }
 
   void operator()(const SelectedRows& src) {
-    auto& selected_rows = trg_->Get<SelectedRows>();
-    PADDLE_ENFORCE_EQ(
-        src.place().which(), selected_rows.place().which(),
-        "The Places of the two Variable must be all on CPU or all on GPU.");
+    auto& selected_rows = dst_->Get<SelectedRows>();
+    PADDLE_ENFORCE_EQ(src.place().which(), selected_rows.place().which(),
+                      platform::errors::PreconditionNotMet(
+                          "The place type of the two variables is not equal."));
     PADDLE_ENFORCE_EQ(src.value().type(), selected_rows.value().type(),
-                      "The dtype of the two Variable is not equal.");
-    PADDLE_ENFORCE_EQ(src.value().layout(), selected_rows.value().layout(),
-                      "The layout of the two Variable's tensor is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The dtype of the two variables is not equal."));
+    PADDLE_ENFORCE_EQ(
+        src.value().layout(), selected_rows.value().layout(),
+        platform::errors::PreconditionNotMet(
+            "The layout of the two variables' tensors is not equal."));
     PADDLE_ENFORCE_EQ(src.height(), selected_rows.height(),
-                      "The height of the two Variable is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The height of the two variables is not equal."));
     PADDLE_ENFORCE_EQ(src.GetCompleteDims(), selected_rows.GetCompleteDims(),
-                      "The dims of the two Variable is not equal.");
+                      platform::errors::PreconditionNotMet(
+                          "The dims of the two variables is not equal."));
   }
 
   template <typename T>
   void operator()(const T&) {
-    PADDLE_ENFORCE("EnforceShapeAndDTypeEQ is not supported by type %s",
-                   typeid(T).name());
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "EnforceShapeAndDTypeEQ is not supported for type %s.",
+        typeid(T).name()));
   }
 };
 

paddle/fluid/framework/device_worker.h

@@ -441,6 +441,7 @@ class SectionWorker : public DeviceWorker {
     skip_vars_ = skip_vars;
   }
   static void ResetBatchId() { batch_id_ = 0; }
+  static void ResetThreadCompletedFlag() { threads_completed = false; }
 
   static std::atomic<int> cpu_id_;
 

paddle/fluid/framework/distributed_strategy.proto

@@ -36,7 +36,15 @@ message AMPConfig {
   repeated string custom_black_varnames = 9;
 }
 
-message LocalSGDConfig { optional int32 k_steps = 1 [ default = 4 ]; }
+message LocalSGDConfig {
+  optional int32 k_steps = 1 [ default = 1 ];
+  optional int32 begin_step = 2 [ default = 1 ];
+}
+
+message AdaptiveLocalSGDConfig {
+  optional int32 init_k_steps = 1 [ default = 1 ];
+  optional int32 begin_step = 2 [ default = 1 ];
+}
 
 message GradientMergeConfig {
   optional int32 k_steps = 1 [ default = 1 ];
@@ -52,6 +60,8 @@ message DGCConfig {
 message LarsConfig {
   optional float lars_coeff = 1 [ default = 0.001 ];
   optional float lars_weight_decay = 2 [ default = 0.0005 ];
+  optional float epsilon = 3 [ default = 0.0 ];
+  repeated string exclude_from_weight_decay = 4;
 }
 
 message LambConfig {
@@ -116,6 +126,7 @@ message DistributedStrategy {
   optional bool cudnn_exhaustive_search = 21 [ default = true ];
   optional int32 conv_workspace_size_limit = 22 [ default = 4000 ];
   optional bool cudnn_batchnorm_spatial_persistent = 23 [ default = true ];
+  optional bool adaptive_localsgd = 24 [ default = false ];
 
   optional RecomputeConfig recompute_configs = 101;
   optional AMPConfig amp_configs = 102;
@@ -126,6 +137,7 @@ message DistributedStrategy {
   optional AsyncConfig a_sync_configs = 107;
   optional LarsConfig lars_configs = 108;
   optional LambConfig lamb_configs = 109;
+  optional AdaptiveLocalSGDConfig adaptive_localsgd_configs = 110;
   optional BuildStrategy build_strategy = 201;
   optional ExecutionStrategy execution_strategy = 202;
 }

paddle/fluid/framework/dlpack_tensor.cc

@@ -23,6 +23,7 @@ template <typename T>
 static ::DLDataType GetDLDataTypeCode() {
   ::DLDataType dtype;
   if (std::is_same<T, platform::float16>::value ||
+      std::is_same<T, platform::bfloat16>::value ||
       std::is_floating_point<T>::value) {
     dtype.code = kDLFloat;
   } else if (std::is_unsigned<T>::value) {

paddle/fluid/framework/fleet/gloo_wrapper.cc

@@ -19,6 +19,8 @@ limitations under the License. */
 namespace gloo {
 namespace rendezvous {
 
+constexpr int kNodeSize = 136;
+
 HdfsStore::HdfsStore(const std::string& path) {
   path_ = path;
   wait_sleep_ms_ = 10000;
@@ -213,12 +215,14 @@ void ParallelConnectContext::connectFullMesh(
   storeKey << rank;
   store.set(storeKey.str(), allBytes);
 
+  auto total_add_size = kNodeSize * (size - 1);
+
   std::vector<std::shared_ptr<std::thread>> connect_threads(thread_num_);
   // Connect every pair
   for (uint32_t i = 0; i < connect_threads.size(); ++i) {
     connect_threads[i].reset(new std::thread(
-        [&store, &transportContext, this](size_t thread_idx,
-                                          size_t thread_num) -> void {
+        [&store, &transportContext, total_add_size, this](
+            size_t thread_idx, size_t thread_num) -> void {
           for (int i = thread_idx; i < size; i += thread_num) {
             if (i == rank) {
               continue;
@@ -226,8 +230,23 @@ void ParallelConnectContext::connectFullMesh(
             // Wait for address of other side of this pair to become available
             std::string key = std::to_string(i);
             store.wait({key}, getTimeout());
+
+            std::vector<char> allAddrs;
+            auto max_retry_times = 5;
             // Connect to other side of this pair
-            auto allAddrs = store.get(key);
+
+            while (max_retry_times > 0) {
+              allAddrs = store.get(key);
+
+              VLOG(3) << "store get all address size: " << allAddrs.size()
+                      << " except: " << total_add_size;
+              if (allAddrs.size() == static_cast<size_t>(total_add_size)) {
+                break;
+              }
+
+              --max_retry_times;
+            }
+
             auto addr = extractAddress(allAddrs, i);
             transportContext->getPair(i)->connect(addr);
           }

paddle/fluid/framework/fleet/nccl_wrapper.cc

@@ -25,7 +25,7 @@ bool NCCLWrapper::is_initialized_ = false;
 
 void NCCLWrapper::InitNCCL() {
 #if defined(PADDLE_WITH_NCCL)
-  PADDLE_ENFORCE(platform::dynload::ncclCommInitRank(
+  PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclCommInitRank(
       &(nccl_info_.comm_), nccl_info_.global_ranks_, nccl_info_.nccl_id_,
       nccl_info_.my_global_rank_));
 #endif
@@ -41,7 +41,8 @@ void NCCLWrapper::SetNCCLId(const NCCLInfo& nccl_info) {
 
 NCCLInfo NCCLWrapper::GetNCCLId() {
 #if defined(PADDLE_WITH_NCCL)
-  PADDLE_ENFORCE(platform::dynload::ncclGetUniqueId(&(nccl_info_.nccl_id_)));
+  PADDLE_ENFORCE_CUDA_SUCCESS(
+      platform::dynload::ncclGetUniqueId(&(nccl_info_.nccl_id_)));
 #endif
   return nccl_info_;
 }
@@ -52,8 +53,8 @@ void NCCLWrapper::SetRankInfo(const int local_rank, const int global_rank,
   nccl_info_.local_rank_ = local_rank;
   nccl_info_.my_global_rank_ = global_rank;
   nccl_info_.global_ranks_ = ranks;
-  PADDLE_ENFORCE(cudaSetDevice(local_rank));
-  PADDLE_ENFORCE(cudaStreamCreate(&(nccl_info_.stream_)));
+  PADDLE_ENFORCE_CUDA_SUCCESS(cudaSetDevice(local_rank));
+  PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&(nccl_info_.stream_)));
 #endif
   return;
 }
@@ -65,7 +66,7 @@ void NCCLWrapper::SyncVar(const int root_rank, const Scope& scope,
     auto var = scope.FindVar(name);
     LoDTensor* tensor = var->GetMutable<LoDTensor>();
     int32_t total_size = tensor->numel();
-    PADDLE_ENFORCE(platform::dynload::ncclBcast(
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
         reinterpret_cast<void*>(tensor->data<float>()), total_size, ncclFloat,
         root_rank, nccl_info_.comm_, nccl_info_.stream_));
     cudaStreamSynchronize(nccl_info_.stream_);

paddle/fluid/framework/generator.cc

@@ -21,10 +21,46 @@ limitations under the License. */
 #include <unordered_map>
 #include <unordered_set>
 #include <utility>
+#include <vector>
+
+#include "paddle/fluid/platform/enforce.h"
+#include "paddle/fluid/platform/gpu_info.h"
+#include "paddle/fluid/platform/place.h"
 
 namespace paddle {
 namespace framework {
 
+const std::shared_ptr<Generator>& GetDefaultCUDAGenerator(int64_t device_id) {
+#ifdef PADDLE_WITH_CUDA
+
+  static int64_t num_cuda_devices = -1;
+  static std::once_flag num_devices_init_flag;
+  static std::deque<std::once_flag> cuda_device_flags;
+  static std::vector<std::shared_ptr<Generator>> default_cuda_generators;
+
+  std::call_once(num_devices_init_flag, []() {
+    num_cuda_devices = paddle::platform::GetCUDADeviceCount();
+    cuda_device_flags.resize(num_cuda_devices);
+    default_cuda_generators.resize(num_cuda_devices);
+  });
+  if (device_id < 0) {
+    PADDLE_THROW(platform::errors::InvalidArgument(
+        "cuda device id shoule be greater than 0"));
+  }
+
+  std::call_once(cuda_device_flags[device_id], [device_id]() {
+    default_cuda_generators[device_id] =
+        std::make_shared<Generator>(GetRandomSeed(), device_id);
+    VLOG(4) << "initial seed: "
+            << default_cuda_generators[device_id]->GetCurrentSeed();
+  });
+  return default_cuda_generators[device_id];
+#else
+  PADDLE_THROW(platform::errors::PermissionDenied(
+      "getDefaultCUDAGenerator only support in CUDA place"));
+#endif
+}
+
 const std::shared_ptr<Generator>& DefaultCPUGenerator() {
   static auto default_cpu_generator =
       std::make_shared<Generator>(GetRandomSeed());
@@ -103,6 +139,7 @@ uint64_t Generator::Seed() {
 void Generator::SetCurrentSeed(uint64_t seed) {
   std::lock_guard<std::mutex> lock(this->mu_);
   this->state_.current_seed = seed;
+  this->state_.thread_offset = 0;
   std::seed_seq seq({seed});
   this->engine_->seed(seq);
 }
@@ -123,6 +160,22 @@ uint64_t Generator::Random64() {
   return (*engine)();
 }
 
+std::pair<uint64_t, uint64_t> Generator::IncrementOffset(
+    uint64_t increament_offset) {
+  uint64_t cur_offset = this->state_.thread_offset;
+#ifdef PADDLE_WITH_CUDA
+  std::lock_guard<std::mutex> lock(this->mu_);
+
+  this->state_.thread_offset += increament_offset;
+
+#else
+  PADDLE_THROW(platform::errors::PermissionDenied(
+      "Increment Offset only support in CUDA place"));
+#endif
+  return std::make_pair(static_cast<int>(this->state_.current_seed),
+                        cur_offset);
+}
+
 void Generator::SetIsInitPy(bool is_init_py) {
   this->is_init_py_ = is_init_py;
   VLOG(4) << "SetIsInitPy:" << this->is_init_py_;

paddle/fluid/framework/generator.h

@@ -38,6 +38,7 @@ static uint64_t GetRandomSeed() {
 struct GeneratorState {
   int64_t device = -1;
   uint64_t current_seed = 34342423252;
+  uint64_t thread_offset = 0;
   std::mt19937_64 cpu_engine;
 };
 
@@ -49,6 +50,7 @@ struct Generator {
     this->state_.cpu_engine = *engine;
     this->state_.device = -1;
     this->state_.current_seed = seed;
+    this->state_.thread_offset = 0;
     this->engine_ = engine;
     VLOG(4) << "initial seed: " << this->state_.current_seed
             << ", cpu engine: " << &this->state_.cpu_engine;
@@ -59,11 +61,25 @@ struct Generator {
     this->state_.cpu_engine = *engine;
     this->state_.device = -1;
     this->state_.current_seed = seed;
+    this->state_.thread_offset = 0;
     this->engine_ = engine;
     VLOG(4) << "initial seed: " << this->state_.current_seed
             << ", cpu engine: " << &this->state_.cpu_engine;
     this->is_init_py_ = true;  // TODO(zhiqiu): remove it in future
   }
+  Generator(uint64_t seed, uint64_t device_id) {
+    std::seed_seq seq({seed});
+    auto engine = std::make_shared<std::mt19937_64>(seq);
+    this->state_.cpu_engine = *engine;
+    this->state_.device = device_id;
+    this->state_.current_seed = seed;
+    this->state_.thread_offset = 0;
+    this->engine_ = engine;
+    VLOG(4) << "initial seed: " << this->state_.current_seed
+            << ", cpu engine: " << &this->state_.cpu_engine;
+    this->is_init_py_ = false;  // TODO(zhiqiu): remove it in future
+  }
+
   Generator(const Generator& other) = delete;
 
   // get random state
@@ -83,8 +99,11 @@ struct Generator {
 
   uint64_t Random64();
 
+  std::pair<uint64_t, uint64_t> IncrementOffset(uint64_t increament_offset);
+
   void SetIsInitPy(bool);
   bool GetIsInitPy() const;
+  uint64_t get_device_id() { return this->state_.device; }
 
  private:
   GeneratorState state_;
@@ -105,5 +124,8 @@ std::shared_ptr<std::mt19937_64> OpDefaultCPUEngine();
 
 std::shared_ptr<std::mt19937_64> GetCPURandomEngine(uint64_t);
 
+const std::shared_ptr<Generator>& GetDefaultCUDAGenerator(
+    int64_t device_id = -1);
+
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/CMakeLists.txt

@@ -102,6 +102,8 @@ if(WITH_MKLDNN)
     pass_library(conv_concat_relu_mkldnn_fuse_pass inference DIR mkldnn)
     pass_library(conv_elementwise_add_mkldnn_fuse_pass inference DIR mkldnn)
     pass_library(scale_matmul_fuse_pass inference DIR mkldnn)
+    pass_library(cpu_bfloat16_placement_pass inference DIR mkldnn)
+    pass_library(cpu_bfloat16_pass inference DIR mkldnn)
     pass_library(fc_mkldnn_pass inference DIR mkldnn)
     pass_library(cpu_quantize_placement_pass base DIR mkldnn)
     pass_library(cpu_quantize_pass inference DIR mkldnn)
@@ -162,4 +164,6 @@ endif()
     cc_test(test_cpu_quantize_squash_pass SRCS mkldnn/cpu_quantize_squash_pass_tester.cc DEPS cpu_quantize_squash_pass naive_executor)
     cc_test(test_reshape_transpose_matmul_mkldnn_fuse_pass SRCS mkldnn/reshape_transpose_matmul_mkldnn_fuse_pass_tester.cc DEPS reshape_transpose_matmul_mkldnn_fuse_pass)
     cc_test(test_matmul_transpose_reshape_fuse_pass SRCS mkldnn/matmul_transpose_reshape_fuse_pass_tester.cc DEPS matmul_transpose_reshape_fuse_pass)
+    cc_test(test_cpu_bfloat16_placement_pass SRCS mkldnn/cpu_bfloat16_placement_pass_tester.cc DEPS cpu_bfloat16_placement_pass)
+    cc_test(test_cpu_bfloat16_pass SRCS mkldnn/cpu_bfloat16_pass_tester.cc DEPS cpu_bfloat16_pass)
 endif ()

paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.cc

@@ -18,6 +18,7 @@
 #include <string>
 #include <vector>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 #include "paddle/fluid/operators/math/cpu_vec.h"
 #include "paddle/fluid/platform/enforce.h"
 
@@ -225,3 +226,14 @@ REGISTER_PASS(conv_affine_channel_fuse_pass,
               paddle::framework::ir::ConvAffineChannelFusePass);
 REGISTER_PASS(conv_eltwiseadd_affine_channel_fuse_pass,
               paddle::framework::ir::ConvEltwiseAddAffineChannelFusePass);
+REGISTER_PASS_CAPABILITY(conv_affine_channel_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("affine_channel", 0));
+REGISTER_PASS_CAPABILITY(conv_eltwiseadd_affine_channel_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("affine_channel", 0));

paddle/fluid/framework/ir/conv_bn_fuse_pass.cc

@@ -18,6 +18,7 @@
 #include <string>
 #include <vector>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 #include "paddle/fluid/operators/math/cpu_vec.h"
 #include "paddle/fluid/platform/enforce.h"
 
@@ -372,3 +373,14 @@ REGISTER_PASS(depthwise_conv_bn_fuse_pass,
               paddle::framework::ir::DepthwiseConvBNFusePass);
 REGISTER_PASS(depthwise_conv_eltwiseadd_bn_fuse_pass,
               paddle::framework::ir::DepthwiseConvEltwiseAddBNFusePass);
+REGISTER_PASS_CAPABILITY(conv_bn_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("batch_norm", 0));
+REGISTER_PASS_CAPABILITY(conv_eltwiseadd_bn_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("batch_norm", 0));

paddle/fluid/framework/ir/conv_elementwise_add2_act_fuse_pass.cc

@@ -11,9 +11,9 @@
 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 // See the License for the specific language governing permissions and
 // limitations under the License.
-
 #include "paddle/fluid/framework/ir/conv_elementwise_add2_act_fuse_pass.h"
 #include <string>
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -116,3 +116,10 @@ void ConvElementwiseAdd2ActFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(conv_elementwise_add2_act_fuse_pass,
               paddle::framework::ir::ConvElementwiseAdd2ActFusePass);
+REGISTER_PASS_CAPABILITY(conv_elementwise_add2_act_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("relu", 0)
+            .EQ("identity", 0));

paddle/fluid/framework/ir/conv_elementwise_add_act_fuse_pass.cc

@@ -15,6 +15,7 @@
 #include "paddle/fluid/framework/ir/conv_elementwise_add_act_fuse_pass.h"
 #include <string>
 #include "paddle/fluid/framework/ir/graph_viz_pass.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -102,3 +103,10 @@ void ConvElementwiseAddActFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(conv_elementwise_add_act_fuse_pass,
               paddle::framework::ir::ConvElementwiseAddActFusePass);
+REGISTER_PASS_CAPABILITY(conv_elementwise_add_act_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("relu", 0)
+            .EQ("identity", 0));

paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.cc

@@ -12,10 +12,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include <string>
-
 #include "paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h"
+#include <string>
 #include "paddle/fluid/framework/ir/graph_viz_pass.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -89,3 +89,8 @@ void ConvElementwiseAddFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(conv_elementwise_add_fuse_pass,
               paddle::framework::ir::ConvElementwiseAddFusePass);
+REGISTER_PASS_CAPABILITY(conv_elementwise_add_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0));

paddle/fluid/framework/ir/embedding_eltwise_layernorm_fuse_pass.cc

@@ -19,6 +19,7 @@
 #include <vector>
 #include "paddle/fluid/framework/ddim.h"
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -334,3 +335,8 @@ void EmbeddingEltwiseLayerNormFusePass::ApplyImpl(Graph* graph) const {
 
 REGISTER_PASS(embedding_eltwise_layernorm_fuse_pass,
               paddle::framework::ir::EmbeddingEltwiseLayerNormFusePass);
+REGISTER_PASS_CAPABILITY(embedding_eltwise_layernorm_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("lookup_table", 0)
+            .EQ("elementweise_add", 0));

paddle/fluid/framework/ir/embedding_eltwise_layernorm_fuse_pass_tester.cc

@@ -16,12 +16,13 @@ limitations under the License. */
 
 #include <gtest/gtest.h>
 #include "paddle/fluid/framework/ir/pass_tester_helper.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
 namespace ir {
 
-TEST(SkipLayerNormFusePass, basic) {
+TEST(EmbeddingElewiseLayernormFusePass, basic) {
   // inputs                           operator            output
   // --------------------------------------------------------------------
   // (x, y)                       elementwise_add    -> elementwise_out
@@ -91,6 +92,12 @@ TEST(SkipLayerNormFusePass, basic) {
           "The number of fusion nodes does not meet expectations after fuse"));
 }
 
+TEST(EmbeddingElewiseLayernormFusePass, pass_op_version_check) {
+  ASSERT_TRUE(
+      paddle::framework::compatible::PassVersionCheckerRegistrar::GetInstance()
+          .IsPassCompatible("embedding_eltwise_layernorm_fuse_pass"));
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/embedding_fc_lstm_fuse_pass.cc

@@ -23,6 +23,8 @@
 #include "paddle/fluid/operators/math/cpu_vec.h"
 #include "paddle/fluid/platform/cpu_info.h"
 
+#include "paddle/fluid/framework/op_version_registry.h"
+
 namespace paddle {
 namespace framework {
 namespace ir {
@@ -34,7 +36,7 @@ static int BuildFusion(Graph* graph, const std::string& name_scope,
 
   // Build pattern
   PDNode* x = pattern->NewNode(patterns::PDNodeName(name_scope, "x"))
-                  ->assert_is_op_input("lookup_table")
+                  ->assert_is_op_input("lookup_table_v2")
                   ->assert_var_not_persistable();
   patterns::Embedding embedding_pattern(pattern, name_scope);
   // TODO(jczaja): Intermediate can only be for val that are not used anywhere
@@ -256,3 +258,11 @@ void EmbeddingFCLSTMFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(embedding_fc_lstm_fuse_pass,
               paddle::framework::ir::EmbeddingFCLSTMFusePass);
+REGISTER_PASS_CAPABILITY(embedding_fc_lstm_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("lookup_table_v2", 0)
+            .EQ("mul", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("lstm", 0)
+            .EQ("fused_embedding_fc_lstm", 0));

paddle/fluid/framework/ir/fc_fuse_pass.cc

@@ -18,6 +18,7 @@
 #include <unordered_set>
 #include <vector>
 #include "paddle/fluid/framework/ir/graph_helper.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 #include "paddle/fluid/platform/enforce.h"
 
 namespace paddle {
@@ -182,3 +183,10 @@ int FCFusePass::ApplyFCPattern(Graph* graph, bool with_relu) const {
 
 REGISTER_PASS(fc_fuse_pass, paddle::framework::ir::FCFusePass)
     .RequirePassAttr("use_gpu");
+REGISTER_PASS_CAPABILITY(fc_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("mul", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("relu", 0)
+            .EQ("fc", 0));

paddle/fluid/framework/ir/fc_gru_fuse_pass.cc

@@ -16,6 +16,7 @@
 #include <string>
 #include <unordered_set>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -125,7 +126,6 @@ static int BuildFusion(Graph* graph, const std::string& name_scope,
     auto* x_n = subgraph.at(x);
     GET_IR_NODE_FROM_SUBGRAPH(w, w, fc_pattern);
     GET_IR_NODE_FROM_SUBGRAPH(mul, mul, fc_pattern);
-    GET_IR_NODE_FROM_SUBGRAPH(fc_out, elementwise_add_out, fc_pattern);
     GET_IR_NODE_FROM_SUBGRAPH(Weight, Weight, gru_pattern);
     GET_IR_NODE_FROM_SUBGRAPH(gru, gru, gru_pattern);
     GET_IR_NODE_FROM_SUBGRAPH(Bias, Bias, gru_pattern);
@@ -136,10 +136,17 @@ static int BuildFusion(Graph* graph, const std::string& name_scope,
                               gru_pattern);
     GET_IR_NODE_FROM_SUBGRAPH(BatchHidden, BatchHidden, gru_pattern);
 
+    // TODO(wilber): Support origin_mode=True.
+    if (gru->Op()->GetAttrIfExists<bool>("origin_mode") == true) {
+      LOG(INFO) << "fc_gru_fuse_pass not supported when origin_mode=True.";
+      return;
+    }
+
     if (with_fc_bias) {
       GET_IR_NODE_FROM_SUBGRAPH(mul_out, mul_out, fc_pattern);
       GET_IR_NODE_FROM_SUBGRAPH(fc_bias, bias, fc_pattern);
       GET_IR_NODE_FROM_SUBGRAPH(elementwise_add, elementwise_add, fc_pattern);
+      GET_IR_NODE_FROM_SUBGRAPH(fc_out, elementwise_add_out, fc_pattern);
 
       gru_creater(gru, x_n, w, Weight, Bias, Hidden, fc_bias);
       // Remove unneeded nodes.
@@ -188,3 +195,16 @@ void FCGRUFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(mul_gru_fuse_pass, paddle::framework::ir::MulGRUFusePass);
 REGISTER_PASS(fc_gru_fuse_pass, paddle::framework::ir::FCGRUFusePass);
+REGISTER_PASS_CAPABILITY(mul_gru_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("mul", 0)
+            .EQ("gru", 0)
+            .EQ("fusion_gru", 0));
+REGISTER_PASS_CAPABILITY(fc_gru_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("mul", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("gru", 0)
+            .EQ("fusion_gru", 0));

paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc

@@ -16,6 +16,7 @@
 #include <string>
 #include <unordered_set>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -196,3 +197,17 @@ void FCLstmFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(mul_lstm_fuse_pass, paddle::framework::ir::MulLstmFusePass);
 REGISTER_PASS(fc_lstm_fuse_pass, paddle::framework::ir::FCLstmFusePass);
+
+REGISTER_PASS_CAPABILITY(fc_lstm_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("mul", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("lstm", 0)
+            .EQ("fusion_lstm", 0));
+REGISTER_PASS_CAPABILITY(mul_lstm_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("mul", 0)
+            .EQ("lstm", 0)
+            .EQ("fusion_lstm", 0));

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -1892,6 +1892,82 @@ PDNode *patterns::QuantizePlacement::operator()(
   return op;
 }
 
+PDNode *patterns::Bfloat16Placement::operator()(
+    const std::unordered_set<std::string> &bfloat16_enabled_op_types) {
+  std::unordered_set<std::string> supported_op_types =
+      std::unordered_set<std::string>();
+  if (!bfloat16_enabled_op_types.empty()) {
+    supported_op_types = bfloat16_enabled_op_types;
+  }
+  auto *op = pattern->NewNode(op_repr())->assert_is_ops(supported_op_types);
+  return op;
+}
+
+PDNode *patterns::OrphanedBfloat16::operator()() {
+  auto *prev_op = pattern->NewNode(prev_op_repr())->assert_is_op();
+  prev_op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") ==
+           "float32";
+  });
+  auto *prev_out = pattern->NewNode(prev_out_repr())->AsOutput();
+
+  auto *op = pattern->NewNode(op_repr())->assert_is_op();
+  op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") ==
+           "bfloat16";
+  });
+  auto *op_out = pattern->NewNode(op_out_repr())->AsOutput();
+
+  auto *next_op = pattern->NewNode(next_op_repr())->assert_is_op();
+  next_op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") ==
+           "float32";
+  });
+
+  prev_op->LinksTo({prev_out});
+  op->LinksFrom({prev_out}).LinksTo({op_out});
+  next_op->LinksFrom({op_out});
+  return next_op;
+}
+
+PDNode *patterns::LastBfloat16Ops::operator()() {
+  auto *op = pattern->NewNode(op_repr())->assert_is_op();
+  op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") ==
+           "bfloat16";
+  });
+  auto *op_out = pattern->NewNode(op_out_repr())->AsOutput();
+
+  auto *next_op = pattern->NewNode(next_op_repr())->assert_is_op();
+  next_op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") !=
+           "bfloat16";
+  });
+
+  op->LinksTo({op_out});
+  next_op->LinksFrom({op_out});
+  return next_op;
+}
+
+PDNode *patterns::FirstBfloat16Ops::operator()() {
+  auto *prev_op = pattern->NewNode(prev_op_repr())->assert_is_op();
+  prev_op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") !=
+           "bfloat16";
+  });
+  auto *op_in = pattern->NewNode(op_in_repr())->AsOutput();
+
+  auto *op = pattern->NewNode(op_repr())->assert_is_op();
+  op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") ==
+           "bfloat16";
+  });
+
+  prev_op->LinksTo({op_in});
+  op->LinksFrom({op_in});
+  return op;
+}
+
 PDNode *patterns::MKLDNNInPlace::operator()() {
   const std::unordered_set<std::string> &supported_op_types = {
       "abs",

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -1129,6 +1129,47 @@ struct QuantizePlacement : public PatternBase {
   PATTERN_DECL_NODE(op);
 };
 
+struct Bfloat16Placement : public PatternBase {
+  Bfloat16Placement(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "bfloat16_placement") {}
+  PDNode* operator()(
+      const std::unordered_set<std::string>& bfloat16_enabled_op_types);
+
+  PATTERN_DECL_NODE(op);
+};
+
+struct OrphanedBfloat16 : public PatternBase {
+  OrphanedBfloat16(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "orphaned_bfloat16") {}
+  PDNode* operator()();
+
+  PATTERN_DECL_NODE(prev_op);
+  PATTERN_DECL_NODE(prev_out);
+  PATTERN_DECL_NODE(op);
+  PATTERN_DECL_NODE(op_out);
+  PATTERN_DECL_NODE(next_op);
+};
+
+struct LastBfloat16Ops : public PatternBase {
+  LastBfloat16Ops(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "last_bfloat16_ops") {}
+  PDNode* operator()();
+
+  PATTERN_DECL_NODE(op);
+  PATTERN_DECL_NODE(op_out);
+  PATTERN_DECL_NODE(next_op);
+};
+
+struct FirstBfloat16Ops : public PatternBase {
+  FirstBfloat16Ops(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "first_bfloat16_ops") {}
+  PDNode* operator()();
+
+  PATTERN_DECL_NODE(prev_op);
+  PATTERN_DECL_NODE(op_in);
+  PATTERN_DECL_NODE(op);
+};
+
 // Pattern used for enforcing inplace computation for in-place computation
 // supporting DNNL ops. softmax, batch_norm and layer_norm
 struct MKLDNNInPlace : public PatternBase {

paddle/fluid/framework/ir/memory_optimize_pass/CMakeLists.txt

@@ -13,4 +13,6 @@ cc_library(memory_reuse_pass SRCS memory_reuse_pass.cc DEPS computation_op_handl
 cc_library(buffer_shared_inplace_op_pass SRCS buffer_shared_inplace_op_pass.cc DEPS memory_reuse_pass)
 cc_library(buffer_shared_cross_op_memory_reuse_pass SRCS buffer_shared_cross_op_memory_reuse_pass.cc DEPS memory_reuse_pass) 
 
+cc_library(inplace_addto_op_pass SRCS inplace_addto_op_pass.cc DEPS memory_reuse_pass)
+
 cc_test(test_reference_count_pass_last_lived_ops SRCS test_reference_count_pass_last_lived_ops.cc DEPS parallel_executor elementwise_mul_op elementwise_add_op scale_op)

paddle/fluid/framework/ir/memory_optimize_pass/buffer_shared_inplace_op_pass.cc

@@ -16,6 +16,7 @@
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
+
 #include "paddle/fluid/framework/details/computation_op_handle.h"
 #include "paddle/fluid/framework/details/multi_devices_helper.h"
 #include "paddle/fluid/framework/details/share_tensor_buffer_op_handle.h"
@@ -141,11 +142,12 @@ void BufferSharedInplaceOpPass::Run(Graph *graph) const {
         VLOG(4) << "Inplace performed in op " << op_type << ": "
                 << in_var_handle_ptr->Name() << " -> "
                 << out_var_handle_ptr->Name()
-                << ". Debug String is: " << op->GetOp()->DebugString();
+                << ". Debug String is: " << op->GetOp()->DebugString()
+                << ". ReuseType: " << ReuseType();
       } else {
         VLOG(3) << "Inplace failed in op " << op_type << ": "
                 << in_var_handle_ptr->Name() << " -> "
-                << out_var_handle_ptr->Name();
+                << out_var_handle_ptr->Name() << ". ReuseType: " << ReuseType();
       }
     }
   }

paddle/fluid/framework/ir/memory_optimize_pass/inplace_addto_op_pass.cc

+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <string>
+#include <unordered_map>
+#include <unordered_set>
+#include <vector>
+
+#include "paddle/fluid/framework/details/computation_op_handle.h"
+#include "paddle/fluid/framework/details/multi_devices_helper.h"
+#include "paddle/fluid/framework/details/share_tensor_buffer_op_handle.h"
+#include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
+#include "paddle/fluid/framework/ir/memory_optimize_pass/memory_reuse_pass.h"
+#include "paddle/fluid/framework/ir/memory_optimize_pass/reference_count_pass_helper.h"
+#include "paddle/fluid/framework/ir/pass.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+class InplaceAddToOpPass : public MemoryReusePass {
+ protected:
+  std::string ReuseType() const override { return "inplace_addto"; }
+
+  void Run(Graph *graph) const override;
+
+ private:
+  // 1. Add last living op of in_var, add any last living op of out_var
+  // 2. Set reference count of in_var to be 2
+  void UpdateLastLiveOpOfVar(details::ComputationOpHandle *op,
+                             details::VarHandle *in_var,
+                             details::VarHandle *out_var) const override {
+    size_t scope_idx = op->GetScopeIdx();
+    auto *last_live_ops_of_vars_ =
+        &Get<std::vector<LastLiveOpsOfVars>>(kLastLiveOpsOfVars);
+    auto *var_infos_ = &(Get<MemOptVarInfoMapList>(kMemOptVarInfoMapList));
+    auto out_var_op_iter =
+        (*last_live_ops_of_vars_)[scope_idx].find(out_var->Name());
+
+    // In Reduce mode, some output variable(gradient of parameter) does not have
+    // last live ops
+    details::ComputationOpHandle *last_live_op_of_in_var = nullptr;
+    if (out_var_op_iter == (*last_live_ops_of_vars_)[scope_idx].end()) {
+      last_live_op_of_in_var = op;
+    } else {
+      PADDLE_ENFORCE_EQ(
+          out_var_op_iter->second.ops().empty(), false,
+          platform::errors::InvalidArgument(
+              "Var(%s)'s last live op should not empty.", out_var->Name()));
+      last_live_op_of_in_var = *(out_var_op_iter->second.ops().begin());
+    }
+
+    auto *last_live_ops_of_in_var =
+        (*last_live_ops_of_vars_)[scope_idx][in_var->Name()].mutable_ops();
+    // last_live_ops_of_in_var->clear();
+    last_live_ops_of_in_var->insert(last_live_op_of_in_var);
+
+    auto in_var_info_iter = (*var_infos_)[scope_idx].find(in_var->Name());
+    PADDLE_ENFORCE_NE(
+        in_var_info_iter, (*var_infos_)[scope_idx].end(),
+        platform::errors::NotFound("Cannot find variable %s.", in_var->Name()));
+
+    in_var_info_iter->second->SetRefCnt(2);  // before inplace, it is 1
+  }
+};
+
+void InplaceAddToOpPass::Run(Graph *graph) const {
+  const auto &last_live_ops =
+      Get<std::vector<LastLiveOpsOfVars>>(kLastLiveOpsOfVars);
+
+  bool use_cuda = Get<bool>(kUseCuda);
+
+  // Currently, only perform InplaceAddToOpPass on cuda place
+  if (!use_cuda) {
+    return;
+  }
+
+  // Step 1: Build a reverse map of last_live_ops
+  // i.e.: op -> vars
+  std::unordered_map<details::ComputationOpHandle *,
+                     std::unordered_map<std::string, ir::Node *>>
+      candidate_ops;
+  for (auto &each_scope_ops : last_live_ops) {
+    for (auto &pair : each_scope_ops) {
+      // If variable has more than 1 last lived ops, this variable cannot
+      // be inplaced.
+      if (pair.second.ops().size() != 1) {
+        continue;
+      }
+
+      auto *op = *(pair.second.ops().begin());
+      const std::string &op_type = op->GetOp()->Type();
+      const framework::OpDesc *op_desc = op->Node()->Op();
+      PADDLE_ENFORCE_NOT_NULL(
+          op_desc, platform::errors::NotFound("Op(%s) can not find opdesc.",
+                                              op->Name()));
+
+      // only grad op should be processed.
+      if (op_type != "grad_add") {
+        continue;
+      }
+
+      const std::string &var_name = pair.first;
+      auto in_nodes = this->FindNodesByName(var_name, op->Node()->inputs);
+      if (in_nodes.size() == 1) {
+        candidate_ops[op][var_name] = *in_nodes.begin();
+      }
+      VLOG(4) << "Find op " << op_type << " with input(" << var_name
+              << ") that can do inplace add to";
+    }
+  }
+
+  // Step 2: Check which vars can be inplaced indeed
+  for (auto &op_vars_pair : candidate_ops) {
+    auto *op = op_vars_pair.first;
+
+    // The original gradient accumulation is g = sum(g_0, g_1,..., g_n), and it
+    // could be changed as follws if inplace addto is enabled:
+    // g_sum_0 = g_0
+    // g_sum_1 = grad_add(g_sum_0, g_1)
+    // g_sum_2 = grad_add(g_sum_1, g_2)
+    // ...
+    // g_sum_n = grad_add(g_sum_n-1, g_n)
+
+    // here we will add inplace for each grad_add, for example, for the first
+    // grad_add, g_sum_0 -> g1, g_sum_1 -> g1, and set grad_add as skipped.
+
+    const std::string &op_type = op->GetOp()->Type();
+
+    PADDLE_ENFORCE_EQ(op->Node()->inputs.size(), 2,
+                      platform::errors::InvalidArgument(
+                          "The size of inputs of %s should be 2, but got %d",
+                          op_type, op->Node()->inputs.size()));
+
+    PADDLE_ENFORCE_EQ(op->Node()->outputs.size(), 1,
+                      platform::errors::InvalidArgument(
+                          "The size of outputs of %s should be 1, but got %d",
+                          op_type, op->Node()->outputs.size()));
+
+    auto *left_var_ptr = dynamic_cast<details::VarHandle *>(
+        &(op->Node()->inputs[0]->Wrapper<details::VarHandleBase>()));
+    auto *right_var_ptr = dynamic_cast<details::VarHandle *>(
+        &(op->Node()->inputs[1]->Wrapper<details::VarHandleBase>()));
+    auto *out_var_ptr = dynamic_cast<details::VarHandle *>(
+        &(op->Node()->outputs[0]->Wrapper<details::VarHandleBase>()));
+
+    if (left_var_ptr == nullptr || right_var_ptr == nullptr ||
+        out_var_ptr == nullptr) {
+      continue;
+    }
+
+    // auto *left_generated_op = dynamic_cast<details::ComputationOpHandle *>(
+    //     left_var_ptr->GeneratedOp());
+
+    auto *right_generated_op = dynamic_cast<details::ComputationOpHandle *>(
+        right_var_ptr->GeneratedOp());
+
+    auto *out_generated_op = dynamic_cast<details::ComputationOpHandle *>(
+        out_var_ptr->GeneratedOp());
+
+    // NOTE(zhiqiu): currently, only conv2d_grad supports addto strategy
+    if (right_generated_op->Name() != "conv2d_grad") {
+      continue;
+    }
+
+    // NOTE(zhiqiu): Normally, if we inplace a->b, we should let a generated
+    // before b. However, in the situation of inplace addto, we do not care
+    // the order, since a+b is equal to b+a. Is there any exception for that?
+
+    // AddDependencyVar(right_generated_op, left_generated_op);
+    // no need, as discussed above.
+
+    // step (a): inplace right_var->left_var of grad_add
+
+    this->AddReuseVar(right_generated_op, left_var_ptr, right_var_ptr);
+    UpdateLastLiveOpOfVar(right_generated_op, left_var_ptr, right_var_ptr);
+    VLOG(4) << "Inplace performed in op " << right_generated_op->GetOp()->Type()
+            << ": " << left_var_ptr->Name() << " -> " << right_var_ptr->Name()
+            << ". Debug String is: "
+            << right_generated_op->GetOp()->DebugString()
+            << ". ReuseType: " << ReuseType();
+
+    // step (b): inplace out -> right_var of grad_add
+
+    this->AddReuseVar(out_generated_op, right_var_ptr, out_var_ptr, true);
+
+    VLOG(4) << "Inplace performed in op " << op_type << ": "
+            << left_var_ptr->Name() << " -> " << out_var_ptr->Name()
+            << ". Debug String is: " << op->GetOp()->DebugString()
+            << ". ReuseType: " << ReuseType();
+
+    // step (c): make right_var cannot inplace afterwards. canbe done
+    // aotomatically since CollectReusedVars is called before any reuse.
+
+    // step (d): make right_var's generated op use addto
+    right_generated_op->GetOp()->SetAttr("use_addto", true);
+
+    // step (e): make grad_add skip running
+    op->SetSkipRunning(true);
+  }
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(inplace_addto_op_pass, paddle::framework::ir::InplaceAddToOpPass)
+    .RequirePassAttr(paddle::framework::ir::kMemOptVarInfoMapList)
+    .RequirePassAttr(paddle::framework::ir::kLastLiveOpsOfVars)
+    .RequirePassAttr(paddle::framework::ir::kUseCuda);

paddle/fluid/framework/ir/memory_optimize_pass/memory_reuse_pass.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/ir/memory_optimize_pass/memory_reuse_pass.h"
+
 #include <functional>
 #include <map>
 #include <string>
@@ -73,6 +74,7 @@ bool MemoryReusePass::TryReuseVar(details::VarHandle *in_var,
           out_var->Name()));
   if (IsVarPairReusable(*in_var, *out_var)) {
     AddReuseVar(op, in_var, out_var);
+    UpdateLastLiveOpOfVar(op, in_var, out_var);
     return true;
   } else {
     return false;
@@ -324,7 +326,8 @@ bool MemoryReusePass::IsVarPairReusable(
 
 void MemoryReusePass::AddReuseVar(details::ComputationOpHandle *op,
                                   details::VarHandle *in_var,
-                                  details::VarHandle *out_var) const {
+                                  details::VarHandle *out_var,
+                                  bool share_dims) const {
   PADDLE_ENFORCE_GT(
       (*var_infos_)[op->GetScopeIdx()].count(in_var->Name()), 0,
       platform::errors::NotFound("Var(%s) does not in mem opt var infos.",
@@ -344,13 +347,15 @@ void MemoryReusePass::AddReuseVar(details::ComputationOpHandle *op,
     share_buffer_op->AddInput(in_var);
   }
 
+  if (share_dims) {
+    share_buffer_op->SetShareDims(true);
+  }
+
   share_buffer_op->AddReuseVarPair(
       (*var_infos_)[op->GetScopeIdx()].at(in_var->Name()).get(),
       out_var->Name());
   reused_in_var_names_[op->GetScopeIdx()].insert(in_var->Name());
   reused_out_var_names_[op->GetScopeIdx()].insert(out_var->Name());
-
-  UpdateLastLiveOpOfVar(op, in_var, out_var);
 }
 
 // 1. Set last living op of in_var to be any last living op of out_var

paddle/fluid/framework/ir/memory_optimize_pass/memory_reuse_pass.h

@@ -18,6 +18,7 @@
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
+
 #include "paddle/fluid/framework/details/computation_op_handle.h"
 #include "paddle/fluid/framework/details/multi_devices_helper.h"
 #include "paddle/fluid/framework/details/share_tensor_buffer_op_handle.h"
@@ -92,6 +93,12 @@ class MemoryReusePass : public Pass {
 
   int64_t GetMemorySize(const details::VarHandle &var) const;
 
+  void AddReuseVar(details::ComputationOpHandle *op, details::VarHandle *in_var,
+                   details::VarHandle *out_var, bool share_dims = false) const;
+  virtual void UpdateLastLiveOpOfVar(details::ComputationOpHandle *op,
+                                     details::VarHandle *in_var,
+                                     details::VarHandle *out_var) const;
+
  private:
   VarDesc *GetVarDesc(const details::VarHandle &var) const;
 
@@ -109,13 +116,6 @@ class MemoryReusePass : public Pass {
 
   void CollectReusedVars() const;
 
-  void AddReuseVar(details::ComputationOpHandle *op, details::VarHandle *in_var,
-                   details::VarHandle *out_var) const;
-
-  void UpdateLastLiveOpOfVar(details::ComputationOpHandle *op,
-                             details::VarHandle *in_var,
-                             details::VarHandle *out_var) const;
-
  private:
   mutable Graph *graph_;
   mutable bool use_cuda_;

paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.cc

@@ -17,6 +17,7 @@
 #include <string>
 #include <vector>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 #include "paddle/fluid/platform/enforce.h"
 
 namespace paddle {
@@ -84,6 +85,19 @@ void ConvBiasFusePass::ApplyImpl(ir::Graph* graph) const {
       VLOG(3) << "do not perform " + type() + "+bias fuse";
       return;
     }
+    if (conv->Op()->HasAttr("dilations")) {
+      auto dilations =
+          BOOST_GET_CONST(std::vector<int>, conv->Op()->GetAttr("dilations"));
+      for (const auto& d : dilations) {
+        if (d != 1) {
+          LOG(WARNING)
+              << "dilation conv not supported in MKLDNN, fuse not apply "
+              << "and set conv attribute use_mkldnn = false";
+          conv->Op()->SetAttr("use_mkldnn", false);
+          return;
+        }
+      }
+    }
 
     auto* eltwise_bias_tensor =
         scope->FindVar(eltwise_bias->Name())->GetMutable<LoDTensor>();
@@ -151,3 +165,8 @@ REGISTER_PASS(conv_transpose_bias_mkldnn_fuse_pass,
               paddle::framework::ir::Conv2DTransposeBiasFusePass);
 REGISTER_PASS(conv3d_bias_mkldnn_fuse_pass,
               paddle::framework::ir::Conv3DBiasFusePass);
+REGISTER_PASS_CAPABILITY(conv_bias_mkldnn_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0));

paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc

@@ -18,6 +18,7 @@
 #include "paddle/fluid/platform/place.h"
 
 #include "paddle/fluid/framework/op_proto_maker.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 #include "paddle/fluid/imperative/type_defs.h"
 
 namespace paddle {
@@ -149,6 +150,12 @@ TEST(ConvBiasFusePass, conv2d_transpose) {
   ASSERT_EQ(pass.type(), std::string("conv2d_transpose"));
 }
 
+TEST(ConvBiasFusePass, pass_op_version_check) {
+  ASSERT_TRUE(
+      paddle::framework::compatible::PassVersionCheckerRegistrar::GetInstance()
+          .IsPassCompatible("conv_bias_mkldnn_fuse_pass"));
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/mkldnn/conv_elementwise_add_mkldnn_fuse_pass.cc

@@ -19,6 +19,7 @@
 #include <memory>
 #include <tuple>
 #include "paddle/fluid/framework/ir/graph_traits.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -341,3 +342,8 @@ void ResidualConnectionMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
 
 REGISTER_PASS(conv_elementwise_add_mkldnn_fuse_pass,
               paddle::framework::ir::ResidualConnectionMKLDNNFusePass);
+REGISTER_PASS_CAPABILITY(conv_elementwise_add_mkldnn_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("conv2d", 0)
+            .EQ("elementwise_add", 0));

paddle/fluid/framework/ir/mkldnn/conv_elementwise_add_mkldnn_fuse_pass_tester.cc

@@ -17,6 +17,7 @@
 
 #include "paddle/fluid/framework/ir/graph_traits.h"
 #include "paddle/fluid/framework/ir/mkldnn/conv_elementwise_add_mkldnn_fuse_pass.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -267,6 +268,12 @@ TEST(ConvElementwiseAddMKLDNNFusePass, NoFusion) {
   AssertOpsCount(graph, 2, 1);
 }
 
+TEST(ConvElementwiseAddMKLDNNFusePass, pass_op_version_check) {
+  ASSERT_TRUE(
+      paddle::framework::compatible::PassVersionCheckerRegistrar::GetInstance()
+          .IsPassCompatible("conv_elementwise_add_mkldnn_fuse_pass"));
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass.cc

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass.h"
+
+#include <string>
+#include <unordered_set>
+#include <vector>
+
+#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+#include "paddle/fluid/platform/mkldnn_helper.h"
+#include "paddle/fluid/string/pretty_log.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+using string::PrettyLogDetail;
+
+void UnlinkNodes(ir::Node* a, ir::Node* b) {
+  a->outputs.erase(std::remove(a->outputs.begin(), a->outputs.end(), b),
+                   a->outputs.end());
+  b->inputs.erase(std::remove(b->inputs.begin(), b->inputs.end(), a),
+                  b->inputs.end());
+}
+
+void CPUBFloat16Pass::SetInputDataType(ir::Graph* graph) const {
+  GraphPatternDetector gpd;
+  patterns::FirstBfloat16Ops bfloat16_ops{gpd.mutable_pattern(),
+                                          "first_bfloat16_ops"};
+  bfloat16_ops();
+  int quantize_counter = 0;
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_IR_NODE_FROM_SUBGRAPH(prev_op, prev_op, bfloat16_ops);
+    GET_IR_NODE_FROM_SUBGRAPH(op_in, op_in, bfloat16_ops);
+    GET_IR_NODE_FROM_SUBGRAPH(op, op, bfloat16_ops);
+
+    if (op->Op()->Type() != "conv2d" && prev_op->Op()->Type() != "quantize") {
+      VarDesc quantize_out_desc(patterns::PDNodeName("quantize", "out"));
+      auto* quantize_out_node = g->CreateVarNode(&quantize_out_desc);
+
+      // create a quantize op node
+      OpDesc q_desc;
+      q_desc.SetType("quantize");
+      q_desc.SetInput("Input", std::vector<std::string>({op_in->Name()}));
+      q_desc.SetOutput("Output",
+                       std::vector<std::string>({quantize_out_node->Name()}));
+      q_desc.SetAttr("Scale", 1.f);
+      q_desc.SetAttr("bfloat16", true);
+      q_desc.SetAttr("output_format", Has("data_layout")
+                                          ? Get<std::string>("data_layout")
+                                          : "NCHW");
+      auto quantize_op = g->CreateOpNode(&q_desc);  // OpDesc will be copied.
+
+      std::string op_input_name;
+      for (auto name : op->Op()->InputNames()) {
+        for (auto input_name : op->Op()->Input(name)) {
+          if (input_name == op_in->Name()) op_input_name = name;
+        }
+      }
+
+      PADDLE_ENFORCE_NE(
+          op_input_name.empty(), true,
+          platform::errors::NotFound(
+              "Operator before operator should have input as op output"));
+
+      op->Op()->SetInput(op_input_name,
+                         std::vector<std::string>({quantize_out_node->Name()}));
+
+      UnlinkNodes(op_in, op);
+      IR_NODE_LINK_TO(op_in, quantize_op);
+      IR_NODE_LINK_TO(quantize_op, quantize_out_node);
+      IR_NODE_LINK_TO(quantize_out_node, op);
+      quantize_counter++;
+    }
+  };
+  gpd(graph, handler);
+  PrettyLogDetail("---    added %d quantize op before bfloat16 op",
+                  quantize_counter);
+}
+
+void CPUBFloat16Pass::SetOutputDataType(ir::Graph* graph) const {
+  GraphPatternDetector gpd;
+  patterns::LastBfloat16Ops bfloat16_ops{gpd.mutable_pattern(),
+                                         "last_bfloat16_ops"};
+  bfloat16_ops();
+  int force_fp32_counter = 0, dequantize_counter = 0;
+
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_IR_NODE_FROM_SUBGRAPH(op, op, bfloat16_ops);
+    GET_IR_NODE_FROM_SUBGRAPH(op_out, op_out, bfloat16_ops);
+    GET_IR_NODE_FROM_SUBGRAPH(next_op, next_op, bfloat16_ops);
+
+    if ((op->Op()->HasAttr("force_fp32_output") ||
+         op->Op()->HasProtoAttr("force_fp32_output")) &&
+        !op->Op()->GetAttrIfExists<bool>("fuse_residual_connection")) {
+      op->Op()->SetAttr("force_fp32_output", true);
+      force_fp32_counter++;
+    } else if (op->Op()->Type() != "prior_box") {
+      // Create dequantize input variable
+      VarDesc dequantize_in_desc(patterns::PDNodeName("dequantize", "in"));
+      auto* dequantize_in_node = g->CreateVarNode(&dequantize_in_desc);
+
+      // create a dequantize op node for output.
+      OpDesc deq_desc;
+      deq_desc.SetType("dequantize");
+      deq_desc.SetInput("Input",
+                        std::vector<std::string>({dequantize_in_node->Name()}));
+      deq_desc.SetOutput("Output", std::vector<std::string>({op_out->Name()}));
+      deq_desc.SetAttr("Scale", 1.0f);
+      auto dequantize_op = g->CreateOpNode(&deq_desc);
+
+      std::string op_output_name;
+      for (auto name : op->Op()->OutputNames()) {
+        for (auto output_name : op->Op()->Output(name)) {
+          if (output_name == op_out->Name()) op_output_name = name;
+        }
+      }
+
+      PADDLE_ENFORCE_NE(
+          op_output_name.empty(), true,
+          platform::errors::NotFound(
+              "Operator after operator should have input as op output"));
+
+      op->Op()->SetOutput(op_output_name, std::vector<std::string>(
+                                              {dequantize_in_node->Name()}));
+
+      UnlinkNodes(op, op_out);
+      IR_NODE_LINK_TO(op, dequantize_in_node);
+      IR_NODE_LINK_TO(dequantize_in_node, dequantize_op);
+      IR_NODE_LINK_TO(dequantize_op, op_out);
+      dequantize_counter++;
+    }
+  };
+  gpd(graph, handler);
+  PrettyLogDetail("---    added %d dequantize op and used %d force_fp32_output",
+                  dequantize_counter, force_fp32_counter);
+}
+
+void CPUBFloat16Pass::ApplyImpl(ir::Graph* graph) const {
+  SetInputDataType(graph);
+  SetOutputDataType(graph);
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(cpu_bfloat16_pass, paddle::framework::ir::CPUBFloat16Pass);

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass.h

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <memory>
+
+#include "paddle/fluid/framework/ir/pass.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+class CPUBFloat16Pass : public Pass {
+ protected:
+  void SetInputDataType(ir::Graph* graph) const;
+  void SetOutputDataType(ir::Graph* graph) const;
+  void ApplyImpl(ir::Graph* graph) const override;
+};
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass_tester.cc

+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <gtest/gtest.h>
+
+#include "paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass.h"
+#include "paddle/fluid/framework/naive_executor.h"
+#include "paddle/fluid/imperative/type_defs.h"
+#include "paddle/fluid/platform/place.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
+           const std::vector<std::string>& inputs,
+           const std::vector<std::string>& outputs, bool use_mkldnn,
+           const std::string& mkldnn_data_type = "float32",
+           const bool force_fp32_output = false) {
+  auto* op = prog->MutableBlock(0)->AppendOp();
+  op->SetType(type);
+  op->SetAttr("use_mkldnn", use_mkldnn);
+  op->SetAttr("name", name);
+
+  if (type == "conv2d") {
+    op->SetInput("Input", {inputs[0]});
+    op->SetOutput("Output", {outputs[0]});
+    op->SetAttr("mkldnn_data_type", mkldnn_data_type);
+    op->SetAttr("force_fp32_output", force_fp32_output);
+  } else if (type == "pool2d" || type == "transpose2" || type == "reshape2" ||
+             type == "dropout") {
+    op->SetInput("X", {inputs[0]});
+    op->SetOutput("Out", {outputs[0]});
+    op->SetAttr("mkldnn_data_type", mkldnn_data_type);
+  } else if (type == "fc") {
+    op->SetInput("Input", {inputs[0]});
+    op->SetOutput("Out", {outputs[0]});
+    op->SetAttr("mkldnn_data_type", mkldnn_data_type);
+  } else if (type == "concat") {
+    op->SetInput("X", inputs);
+    op->SetOutput("Out", outputs);
+    op->SetAttr("mkldnn_data_type", mkldnn_data_type);
+  } else if (type == "matmul" || type == "elementwise_add") {
+    op->SetInput("X", {inputs[0]});
+    if (inputs.size() > 1) op->SetInput("Y", {inputs[1]});
+    op->SetOutput("Out", {outputs[0]});
+    op->SetAttr("mkldnn_data_type", mkldnn_data_type);
+  }
+}
+
+void PreparePass(std::unique_ptr<ir::Graph>* graph, const ProgramDesc& prog,
+                 const std::initializer_list<std::string> variable_names,
+                 int* original_nodes_num, int* current_nodes_num) {
+  auto pass = PassRegistry::Instance().Get("cpu_bfloat16_pass");
+
+  graph->reset(pass->Apply(graph->release()));
+
+  *original_nodes_num = (*graph)->Nodes().size();
+  (*graph).reset(pass->Apply((*graph).release()));
+  *current_nodes_num = (*graph)->Nodes().size();
+}
+
+static const std::initializer_list<std::string> variable_names{
+    "z", "a", "b", "c", "d", "e", "f", "g", "h", "i"};
+
+ProgramDesc BuildProgramDesc(bool use_mkldnn) {
+  ProgramDesc prog;
+  for (auto& v : variable_names) {
+    prog.MutableBlock(0)->Var(v);
+  }
+  SetOp(&prog, "dropout", "Dropout1", {"z"}, {"a"}, use_mkldnn, "float32");
+  SetOp(&prog, "conv2d", "Conv1", {"a"}, {"b"}, use_mkldnn, "bfloat16");
+  SetOp(&prog, "pool2d", "Pool1", {"b"}, {"c"}, use_mkldnn, "bfloat16");
+  SetOp(&prog, "conv2d", "Conv1", {"c"}, {"d"}, use_mkldnn, "bfloat16");
+  SetOp(&prog, "dropout", "Dropout2", {"d"}, {"e"}, use_mkldnn, "float32");
+  SetOp(&prog, "transpose2", "Transpose1", {"e"}, {"f"}, use_mkldnn,
+        "bfloat16");
+  SetOp(&prog, "reshape2", "Reshape1", {"f"}, {"g"}, use_mkldnn, "bfloat16");
+  SetOp(&prog, "concat", "Concat1", {"g"}, {"h"}, use_mkldnn, "bfloat16");
+  SetOp(&prog, "dropout", "Dropout3", {"h"}, {"i"}, use_mkldnn, "float32");
+
+  return prog;
+}
+
+void MainTest(const ProgramDesc& prog, int conv_count, int pool_count,
+              int transpose_count, int quant_count, int dequant_count,
+              int added_nodes_count) {
+  std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
+  int original_nodes_num, current_nodes_num;
+  PreparePass(&graph, prog, variable_names, &original_nodes_num,
+              &current_nodes_num);
+
+  int quantize_nodes_count = 0;
+  int dequantize_nodes_count = 0;
+  int conv2d_nodes_count = 0;
+  int pool2d_nodes_count = 0;
+  int transpose2_nodes_count = 0;
+
+  for (auto* node : graph->Nodes()) {
+    if (node->IsOp()) {
+      auto* op = node->Op();
+      if (op->Type() == "conv2d") {
+        conv2d_nodes_count++;
+      } else if (op->Type() == "pool2d") {
+        pool2d_nodes_count++;
+      } else if (op->Type() == "transpose2") {
+        transpose2_nodes_count++;
+      } else if (op->Type() == "quantize") {
+        quantize_nodes_count++;
+      } else if (op->Type() == "dequantize") {
+        dequantize_nodes_count++;
+      }
+    }
+  }
+  EXPECT_EQ(conv2d_nodes_count, conv_count);
+  EXPECT_EQ(pool2d_nodes_count, pool_count);
+  EXPECT_EQ(transpose2_nodes_count, transpose_count);
+  EXPECT_EQ(quantize_nodes_count, quant_count);
+  EXPECT_EQ(dequantize_nodes_count, dequant_count);
+  EXPECT_EQ(original_nodes_num + added_nodes_count, current_nodes_num);
+}
+
+TEST(CpuQuantizePass, quantize) {
+  bool use_mkldnn = true;
+  // 1 quantize + 1 dequantize
+  int added_nodes = 2;
+  MainTest(BuildProgramDesc(use_mkldnn), 2, 1, 1, 1, 2, added_nodes);
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+USE_PASS(cpu_bfloat16_pass);

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_placement_pass.cc

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_placement_pass.h"
+
+#include <string>
+#include <unordered_set>
+
+#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+#include "paddle/fluid/platform/mkldnn_helper.h"
+#include "paddle/fluid/string/pretty_log.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+using string::PrettyLogDetail;
+
+void CPUBfloat16PlacementPass::SetMkldnnDataType(
+    ir::Graph* graph, int* bfloat16_operators) const {
+  const auto& op_types_list =
+      Get<std::unordered_set<std::string>>("bfloat16_enabled_op_types");
+  // set mkldnn_data_type to bfloat16 to all operators that are in
+  // bfloat16_enabled_op_types vector or they are included to Bfloat16Placement
+  // pattern
+  GraphPatternDetector gpd;
+  patterns::Bfloat16Placement bfloat16_placement_pattern{gpd.mutable_pattern(),
+                                                         "bfloat16_placement"};
+  bfloat16_placement_pattern(op_types_list);
+
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_IR_NODE_FROM_SUBGRAPH(op, op, bfloat16_placement_pattern);
+
+    if ((op->Op()->HasAttr("mkldnn_data_type") ||
+         op->Op()->HasProtoAttr("mkldnn_data_type")) &&
+        !platform::HasOpINT8DataType(op->Op())) {
+      op->Op()->SetAttr("mkldnn_data_type", std::string("bfloat16"));
+      (*bfloat16_operators)++;
+    }
+  };
+  gpd(graph, handler);
+}
+
+void CPUBfloat16PlacementPass::RemoveOrhanedOperators(
+    ir::Graph* graph, int* bfloat16_operators) const {
+  // find orphaned bfloat16 operator that is between two float32 operators
+  // revert mkldnn_data_type attr to float32
+  GraphPatternDetector gpd;
+  patterns::OrphanedBfloat16 orphaned_bfloat16_pattern{gpd.mutable_pattern(),
+                                                       "orphaned_bfloat16"};
+  orphaned_bfloat16_pattern();
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_IR_NODE_FROM_SUBGRAPH(op, op, orphaned_bfloat16_pattern);
+
+    op->Op()->SetAttr("mkldnn_data_type", std::string("float32"));
+    bfloat16_operators--;
+  };
+  gpd(graph, handler);
+}
+
+void CPUBfloat16PlacementPass::ApplyImpl(ir::Graph* graph) const {
+  int bfloat16_operators = 0;
+  SetMkldnnDataType(graph, &bfloat16_operators);
+  RemoveOrhanedOperators(graph, &bfloat16_operators);
+  PrettyLogDetail("---    marked %d operators to bfloat16 ",
+                  bfloat16_operators);
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(cpu_bfloat16_placement_pass,
+              paddle::framework::ir::CPUBfloat16PlacementPass)
+    // a vector of operator type names with bfloat16 support ("conv2d" etc.)
+    // the second param is the default value for this vector
+    .DefaultPassAttr("bfloat16_enabled_op_types",
+                     new std::unordered_set<std::string>());

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_placement_pass.h

+/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <memory>
+
+#include "paddle/fluid/framework/ir/pass.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+/*
+ * Specifies which operators should be run on bfloat16.
+ */
+class CPUBfloat16PlacementPass : public Pass {
+ protected:
+  void SetMkldnnDataType(ir::Graph* graph, int* bfloat16_operators) const;
+
+  void RemoveOrhanedOperators(ir::Graph* graph, int* bfloat16_operators) const;
+
+  void ApplyImpl(ir::Graph* graph) const override;
+};
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_placement_pass_tester.cc

+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <gtest/gtest.h>
+
+#include "paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_placement_pass.h"
+#include "paddle/fluid/platform/mkldnn_helper.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
+           const std::vector<std::string>& inputs,
+           const std::vector<std::string>& outputs,
+           const std::string& mkldnn_data_type = "float32") {
+  auto* op = prog->MutableBlock(0)->AppendOp();
+
+  op->SetType(type);
+  op->SetAttr("mkldnn_data_type", mkldnn_data_type);
+
+  if (type == "conv2d") {
+    op->SetAttr("name", name);
+    op->SetInput("Input", {inputs[0]});
+  } else if (type == "relu") {
+    op->SetInput("X", inputs);
+  } else if (type == "concat") {
+    op->SetAttr("axis", 1);
+    op->SetInput("X", {inputs[0], inputs[1]});
+  } else if (type == "pool2d") {
+    op->SetInput("X", {inputs[0]});
+  } else {
+    FAIL() << "Unexpected operator type.";
+  }
+  op->SetOutput("Out", {outputs[0]});
+}
+
+// operator                      mkldnn_data_type
+// ---------------------------------------
+// (a,b)->concat->c              float32
+// c->conv->f                    float32
+// f->relu->g                    float32
+// g->pool->h                    float32
+// h->conv->k                    float32
+// k->pool->l                    float32
+ProgramDesc BuildProgramDesc() {
+  ProgramDesc prog;
+
+  for (auto& v :
+       std::vector<std::string>({"a", "b", "c", "f", "g", "h", "k", "l"})) {
+    prog.MutableBlock(0)->Var(v);
+  }
+
+  SetOp(&prog, "concat", "concat1", {"a", "b"}, {"c"});
+  SetOp(&prog, "conv2d", "conv1", {"c"}, {"f"});
+  SetOp(&prog, "relu", "relu1", {"f"}, {"g"});
+  SetOp(&prog, "pool2d", "pool1", {"g"}, {"h"});
+  SetOp(&prog, "conv2d", "conv2", {"h"}, {"k"});
+  SetOp(&prog, "pool2d", "pool2", {"k"}, {"l"});
+
+  return prog;
+}
+
+void MainTest(std::initializer_list<std::string> bfloat16_enabled_op_types,
+              unsigned expected_bfloat16_data_type_count) {
+  auto prog = BuildProgramDesc();
+
+  std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
+
+  auto pass = PassRegistry::Instance().Get("cpu_bfloat16_placement_pass");
+  pass->Set("bfloat16_enabled_op_types",
+            new std::unordered_set<std::string>(bfloat16_enabled_op_types));
+
+  graph.reset(pass->Apply(graph.release()));
+
+  unsigned bfloat16_data_type_count = 0;
+
+  for (auto* node : graph->Nodes()) {
+    if (node->IsOp()) {
+      if (platform::HasOpBFLOAT16DataType(node->Op())) {
+        ++bfloat16_data_type_count;
+      }
+    }
+  }
+
+  EXPECT_EQ(bfloat16_data_type_count, expected_bfloat16_data_type_count);
+}
+
+void DefaultAttrTest(unsigned expected_bfloat16_data_type_count) {
+  auto prog = BuildProgramDesc();
+  std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
+  auto pass = PassRegistry::Instance().Get("cpu_bfloat16_placement_pass");
+  graph.reset(pass->Apply(graph.release()));
+
+  unsigned bfloat16_data_type_count = 0;
+  for (auto* node : graph->Nodes()) {
+    if (node->IsOp()) {
+      if (platform::HasOpBFLOAT16DataType(node->Op())) {
+        ++bfloat16_data_type_count;
+      }
+    }
+  }
+  EXPECT_EQ(bfloat16_data_type_count, expected_bfloat16_data_type_count);
+}
+
+TEST(Bfloat16PlacementPass, enable_all) {
+  MainTest({"conv2d", "pool2d", "relu", "concat"}, 6);
+}
+
+TEST(Bfloat16PlacementPass, enabled_conv_and_pool) {
+  // 2 conv2d + 2 pool2 - 1 orphaned conv2d
+  MainTest({"conv2d", "pool2d"}, 3);
+}
+
+TEST(Bfloat16PlacementPass, default_attr_value) { DefaultAttrTest(0); }
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+USE_PASS(cpu_bfloat16_placement_pass);

paddle/fluid/framework/ir/mkldnn/depthwise_conv_mkldnn_pass.cc

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #include "paddle/fluid/framework/ir/mkldnn/depthwise_conv_mkldnn_pass.h"
 #include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -57,3 +58,7 @@ void DepthwiseConvMKLDNNPass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(depthwise_conv_mkldnn_pass,
               paddle::framework::ir::DepthwiseConvMKLDNNPass);
+REGISTER_PASS_CAPABILITY(depthwise_conv_mkldnn_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination().EQ(
+            "depthwise_conv2d", 0));

paddle/fluid/framework/ir/mkldnn/depthwise_conv_mkldnn_pass_tester.cc

@@ -16,6 +16,8 @@
 
 #include <gtest/gtest.h>
 
+#include "paddle/fluid/framework/op_version_registry.h"
+
 namespace paddle {
 namespace framework {
 namespace ir {
@@ -70,6 +72,12 @@ ProgramDesc BuildProgramDesc() {
   return prog;
 }
 
+TEST(DepthwiseConvMKLDNNPass, pass_op_version_check) {
+  ASSERT_TRUE(
+      paddle::framework::compatible::PassVersionCheckerRegistrar::GetInstance()
+          .IsPassCompatible("depthwise_conv_mkldnn_pass"));
+}
+
 TEST(DepthwiseConvMKLDNNPass, basic) {
   auto prog = BuildProgramDesc();
 

paddle/fluid/framework/ir/multihead_matmul_fuse_pass.cc

@@ -19,6 +19,7 @@
 #include <vector>
 #include "paddle/fluid/framework/ddim.h"
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 #include "paddle/fluid/platform/errors.h"
 
 namespace paddle {
@@ -615,6 +616,16 @@ static int BuildFusionV2(Graph* graph, const std::string& name_scope,
     GET_IR_NODE_FROM_SUBGRAPH(transpose2_qkv_out, transpose2_qkv_out,
                               multihead_pattern);
 
+    // If weights or biases in qkv's fc are shared by multiple multihead_matmul
+    // patterns, we do not support this kind of fusion, this pass will not take
+    // effect.
+    bool is_fc_params_shared =
+        mul0_w->outputs.size() > 1 || mul1_w->outputs.size() > 1 ||
+        mul2_w->outputs.size() > 1 || eltadd0_b->outputs.size() > 1 ||
+        eltadd1_b->outputs.size() > 1 || eltadd2_b->outputs.size() > 1;
+    if (is_fc_params_shared) {
+      return;
+    }
     fuse_creater(input0, mul0, mul1, mul2, mul0_out, mul1_out, mul2_out, mul0_w,
                  mul1_w, mul2_w, eltadd0_b, eltadd1_b, eltadd2_b, eltadd_qk_b,
                  reshape2_0, reshape2_qkv_out, scale, scale_out);
@@ -697,3 +708,13 @@ REGISTER_PASS(multihead_matmul_fuse_pass,
 
 REGISTER_PASS(multihead_matmul_fuse_pass_v2,
               paddle::framework::ir::MultiHeadMatmulV2FusePass);
+REGISTER_PASS_CAPABILITY(multihead_matmul_fuse_pass_v2)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("mul", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("reshape2", 0)
+            .EQ("transpose2", 0)
+            .EQ("scale", 0)
+            .EQ("matmul", 0)
+            .EQ("softmax", 0));

paddle/fluid/framework/ir/multihead_matmul_fuse_pass_tester.cc

@@ -12,6 +12,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/ir/multihead_matmul_fuse_pass.h"  // NOLINT
 #include <gtest/gtest.h>
 #include "paddle/fluid/framework/ir/pass_tester_helper.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -133,6 +134,12 @@ TEST(MultiHeadMatmulFusePass, basic) {
                         num_fused_nodes_after));
 }
 
+TEST(MultiHeadMatmulFusePass, pass_op_version_check) {
+  ASSERT_TRUE(
+      paddle::framework::compatible::PassVersionCheckerRegistrar::GetInstance()
+          .IsPassCompatible("multihead_matmul_fuse_pass_v2"));
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.cc

@@ -18,6 +18,7 @@ limitations under the License. */
 #include <unordered_set>
 #include <vector>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 #define MAX_NUM_FC 10
 
@@ -174,6 +175,11 @@ void BuildRepeatedFCReluPattern(PDPattern* pattern,
             if (x->outputs.size() <= 0 || x->inputs.size() <= 0U) {
               return false;
             }
+            if (x->IsVar() && x->Var() && x->Var()->GetShape().size() > 2) {
+              VLOG(3) << "repeated fc relu only supports input dims = 2, so it "
+                         "is not applied.";
+              return false;
+            }
             int fc_idx = FindFCIdx(x);
             if (fc_idx < 0) {
               return false;
@@ -384,3 +390,8 @@ void RepeatedFCReluFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(repeated_fc_relu_fuse_pass,
               paddle::framework::ir::RepeatedFCReluFusePass);
+REGISTER_PASS_CAPABILITY(repeated_fc_relu_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("fc", 0)
+            .EQ("relu", 0));

paddle/fluid/framework/ir/seqconv_eltadd_relu_fuse_pass.cc

@@ -16,6 +16,7 @@
 #include <string>
 #include <unordered_set>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -98,3 +99,9 @@ void SeqConvEltAddReluFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(seqconv_eltadd_relu_fuse_pass,
               paddle::framework::ir::SeqConvEltAddReluFusePass);
+REGISTER_PASS_CAPABILITY(seqconv_eltadd_relu_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("sequence_conv", 0)
+            .EQ("elementwise_add", 0)
+            .EQ("relu", 0));

paddle/fluid/framework/ir/shuffle_channel_detect_pass.cc

@@ -16,6 +16,7 @@
 
 #include "paddle/fluid/framework/ir/graph_viz_pass.h"
 #include "paddle/fluid/framework/ir/shuffle_channel_detect_pass.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -82,6 +83,9 @@ void ShuffleChannelDetectPass::ApplyImpl(ir::Graph* graph) const {
     // Delete the unneeded nodes.
     GraphSafeRemoveNodes(graph, {reshape1_op, reshape1_out, transpose_op,
                                  transpose_out, reshape2_op});
+    LOG_FIRST_N(WARNING, 1)
+        << "There is fluid.layers.shuffle_channel API already, maybe you can "
+           "use it instead of (reshape + transpose + reshape)";
   };
 
   gpd(graph, handler);
@@ -93,3 +97,8 @@ void ShuffleChannelDetectPass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(shuffle_channel_detect_pass,
               paddle::framework::ir::ShuffleChannelDetectPass);
+REGISTER_PASS_CAPABILITY(shuffle_channel_detect_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("reshape2", 0)
+            .EQ("transpose2", 0));

paddle/fluid/framework/ir/skip_layernorm_fuse_pass.cc

@@ -17,6 +17,7 @@ limitations under the License. */
 #include <unordered_set>
 #include <vector>
 #include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -180,3 +181,8 @@ void SkipLayerNormFusePass::ApplyImpl(ir::Graph *graph) const {
 
 REGISTER_PASS(skip_layernorm_fuse_pass,
               paddle::framework::ir::SkipLayerNormFusePass);
+REGISTER_PASS_CAPABILITY(skip_layernorm_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("elementwise_add", 0)
+            .EQ("layer_norm", 0));

paddle/fluid/framework/ir/skip_layernorm_fuse_pass_tester.cc

@@ -16,6 +16,7 @@ limitations under the License. */
 
 #include <gtest/gtest.h>
 #include "paddle/fluid/framework/ir/pass_tester_helper.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -54,6 +55,12 @@ TEST(SkipLayerNormFusePass, basic) {
           "The number of fusion nodes does not meet expectations after fuse"));
 }
 
+TEST(SkipLayerNormFusePass, pass_op_version_check) {
+  ASSERT_TRUE(
+      paddle::framework::compatible::PassVersionCheckerRegistrar::GetInstance()
+          .IsPassCompatible("skip_layernorm_fuse_pass"));
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.cc

@@ -17,6 +17,7 @@
 #include <unordered_set>
 #include <vector>
 #include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -77,7 +78,8 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
   };
 
   auto is_fusion_input_var = [=](Node* x, const std::string& arg_name) {
-    bool basic = var_is_op_input(x, "matmul", arg_name) &&
+    bool basic = (var_is_op_input(x, "matmul_v2", arg_name) ||
+                  var_is_op_input(x, "matmul", arg_name)) &&
                  var_is_op_input(x, "square", "X");
     if (!basic) {
       return false;
@@ -88,7 +90,8 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
     }
     auto* squared_x = squared_x_op->outputs[0];
     bool next_is_matmul_from_arg =
-        var_is_op_input(squared_x, "matmul", arg_name) &&
+        (var_is_op_input(squared_x, "matmul_v2", arg_name) ||
+         var_is_op_input(squared_x, "matmul", arg_name)) &&
         squared_x->outputs.size() == 1 &&
         squared_x->outputs[0]->outputs.size() == 1;
     if (!next_is_matmul_from_arg) {
@@ -103,7 +106,8 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
   auto is_fusion_first_mul_out = [=](Node* x) -> bool {
     bool input_is_matmul_op = x && x->inputs.size() == 1 &&
                               x->inputs[0]->IsOp() &&
-                              x->inputs[0]->Op()->Type() == "matmul";
+                              (x->inputs[0]->Op()->Type() == "matmul_v2" ||
+                               x->inputs[0]->Op()->Type() == "matmul");
     if (!input_is_matmul_op) {
       return false;
     }
@@ -167,7 +171,8 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
 
   auto* matmul_xy_op = pattern->NewNode(
       [=](Node* x) {
-        return x && x->IsOp() && x->Op()->Type() == "matmul" &&
+        return x && x->IsOp() && (x->Op()->Type() == "matmul_v2" ||
+                                  x->Op()->Type() == "matmul") &&
                is_fusion_first_mul_out(x->outputs[0]);
       },
       name_scope + "/matmul_xy_op");
@@ -189,7 +194,9 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
 
   auto is_fusion_mat_squared_x_y_op_out = [=](Node* x) -> bool {
     bool basic = x && x->IsVar() && x->inputs.size() == 1 &&
-                 x->inputs[0]->IsOp() && x->inputs[0]->Op()->Type() == "matmul";
+                 x->inputs[0]->IsOp() &&
+                 (x->inputs[0]->Op()->Type() == "matmul_v2" ||
+                  x->inputs[0]->Op()->Type() == "matmul");
     if (!basic) {
       return false;
     }
@@ -206,7 +213,8 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
 
   auto* matmul_squared_x_y_op = pattern->NewNode(
       [=](Node* x) {
-        return x && x->IsOp() && x->Op()->Type() == "matmul" &&
+        return x && x->IsOp() && (x->Op()->Type() == "matmul_v2" ||
+                                  x->Op()->Type() == "matmul") &&
                is_fusion_mat_squared_x_y_op_out(x->outputs[0]);
       },
       name_scope + "/matmul_squared_x_y_op");
@@ -378,3 +386,13 @@ void SquaredMatSubFusePass::ApplyImpl(ir::Graph* graph) const {
 
 REGISTER_PASS(squared_mat_sub_fuse_pass,
               paddle::framework::ir::SquaredMatSubFusePass);
+REGISTER_PASS_CAPABILITY(squared_mat_sub_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("matmul", 0)
+            .EQ("matmul_v2", 0)
+            .EQ("square", 0)
+            .EQ("elementwise_mul", 0)
+            .EQ("elementwise_sub", 0)
+            .EQ("fill_constant", 0)
+            .EQ("fusion_squared_mat_sub", 0));

paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h

@@ -24,7 +24,7 @@ namespace framework {
 namespace ir {
 
 /**
- * Fuse ( (A.^2 * B.^2) - (A * B).^2 ) .* scalar
+ * Fuse ( (A * B).^2 - (A.^2 * B.^2) ) .* scalar
  */
 class SquaredMatSubFusePass : public FusePassBase {
  public:

paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.cc

@@ -20,6 +20,7 @@
 #include "paddle/fluid/framework/ir/graph_viz_pass.h"
 #include "paddle/fluid/framework/ir/node.h"
 #include "paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.h"
+#include "paddle/fluid/framework/op_version_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -145,3 +146,11 @@ void TransposeFlattenConcatFusePass::ApplyImpl(ir::Graph *graph) const {
 
 REGISTER_PASS(transpose_flatten_concat_fuse_pass,
               paddle::framework::ir::TransposeFlattenConcatFusePass);
+REGISTER_PASS_CAPABILITY(transpose_flatten_concat_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("transpose", 0)
+            .EQ("transpose2", 0)
+            .EQ("flatten", 0)
+            .EQ("concat", 0)
+            .EQ("fusion_transpose_flatten_concat", 0));

paddle/fluid/framework/op_info.h

@@ -69,7 +69,8 @@ class OpInfo {
 
   const OpCreator& Creator() const {
     PADDLE_ENFORCE_NOT_NULL(creator_,
-                            "Operator's Creator has not been registered");
+                            platform::errors::NotFound(
+                                "Operator's Creator has not been registered."));
     return creator_;
   }
 
@@ -79,11 +80,12 @@ class OpInfo {
     std::string type = proto_ ? proto_->type() : "unknown";
     PADDLE_ENFORCE_NOT_NULL(
         grad_op_maker_,
+        platform::errors::NotFound(
             "Operator %s's GradOpMaker has not been "
-        "registered.\nPlease check whether %s_op has "
-        "grad_op.\nIf not, please set stop_gradient to True "
+            "registered.\nPlease check whether (%s) operator has "
+            "gradient operator.\nIf not, please set stop_gradient to be True "
             "for its input and output variables using var.stop_gradient=True.",
-        type.c_str(), type.c_str());
+            type.c_str(), type.c_str()));
     return grad_op_maker_;
   }
 
@@ -100,11 +102,12 @@ class OpInfo {
     std::string type = proto_ ? proto_->type() : "unknown";
     PADDLE_ENFORCE_NOT_NULL(
         dygraph_grad_op_maker_,
+        platform::errors::NotFound(
             "Operator %s's DygraphGradOpMaker has not been "
-        "registered.\nPlease check whether %s_op has "
-        "grad_op.\nIf not, please set stop_gradient to True "
+            "registered.\nPlease check whether (%s) operator has "
+            "gradient operator.\nIf not, please set stop_gradient to be True "
             "for its input and output variables using var.stop_gradient=True.",
-        type.c_str(), type.c_str());
+            type.c_str(), type.c_str()));
     return dygraph_grad_op_maker_;
   }
 
@@ -130,14 +133,17 @@ class OpInfoMap {
   }
 
   void Insert(const std::string& type, const OpInfo& info) {
-    PADDLE_ENFORCE(!Has(type), "Operator %s has been registered", type);
+    PADDLE_ENFORCE_NE(Has(type), true,
+                      platform::errors::AlreadyExists(
+                          "Operator (%s) has been registered.", type));
     map_.insert({type, info});
   }
 
   const OpInfo& Get(const std::string& type) const {
     auto op_info_ptr = GetNullable(type);
-    PADDLE_ENFORCE_NOT_NULL(op_info_ptr, "Operator %s has not been registered",
-                            type);
+    PADDLE_ENFORCE_NOT_NULL(
+        op_info_ptr,
+        platform::errors::NotFound("Operator (%s) is not registered.", type));
     return *op_info_ptr;
   }
 

paddle/fluid/framework/op_kernel_type.cc

@@ -33,10 +33,18 @@ size_t OpKernelType::Hash::operator()(const OpKernelType& key) const {
   cur_loc += OpKernelType::kLibBits;
 
   int customized_value = key.customized_type_value_;
-  PADDLE_ENFORCE(customized_value < (1 << OpKernelType::kCustomizeBits));
+  PADDLE_ENFORCE_LT(customized_value, (1 << OpKernelType::kCustomizeBits),
+                    platform::errors::Unavailable(
+                        "Too many custom OpKernel attribute values, expected "
+                        "maximum value is %d, received value is %d.",
+                        (1 << OpKernelType::kCustomizeBits), customized_value));
   customized_value = customized_value << cur_loc;
   cur_loc += OpKernelType::kCustomizeBits;
-  PADDLE_ENFORCE(cur_loc < 64);
+  PADDLE_ENFORCE_LT(cur_loc, 64,
+                    platform::errors::Unavailable(
+                        "Too many OpKernel attribute values, expected maximum "
+                        "value is 64, received value is %d.",
+                        cur_loc));
 
   std::hash<int> hasher;
   return hasher(place + data_type + data_layout + library_type +

paddle/fluid/framework/op_proto_maker.cc

@@ -43,7 +43,9 @@ OpProtoAndCheckerMaker::VariableBuilder OpProtoAndCheckerMaker::AddOutput(
 void OpProtoAndCheckerMaker::CheckNoDuplicatedInOutAttrs() {
   std::unordered_set<std::string> names;
   auto checker = [&](const std::string& name) {
-    PADDLE_ENFORCE(!names.count(name), "[%s] is duplicated", name);
+    PADDLE_ENFORCE_EQ(
+        names.count(name), 0,
+        platform::errors::AlreadyExists("Attribute [%s] is duplicated.", name));
     names.insert(name);
   };
   for (auto& attr : proto_->attrs()) {

paddle/fluid/framework/op_registry.h

@@ -54,9 +54,10 @@ class Registrar {
 template <typename... ARGS>
 struct OperatorRegistrar : public Registrar {
   explicit OperatorRegistrar(const char* op_type) {
-    if (OpInfoMap::Instance().Has(op_type)) {
-      PADDLE_THROW("'%s' is registered more than once.", op_type);
-    }
+    PADDLE_ENFORCE_EQ(
+        OpInfoMap::Instance().Has(op_type), false,
+        platform::errors::AlreadyExists(
+            "Operator '%s' is registered more than once.", op_type));
     static_assert(sizeof...(ARGS) != 0,
                   "OperatorRegistrar should be invoked at least by OpClass");
     OpInfo info;

paddle/fluid/framework/op_registry_test.cc

@@ -58,7 +58,8 @@ class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
     AddInput("input", "input of cosine op").AsDuplicable();
     AddOutput("output", "output of cosine op").AsIntermediate();
     auto my_checker = [](int i) {
-      PADDLE_ENFORCE(i % 2 == 0, "'test_attr' must be even!");
+      PADDLE_ENFORCE_EQ(i % 2, 0, platform::errors::InvalidArgument(
+                                      "'test_attr' must be even!"));
     };
     AddAttr<int>("test_attr", "a simple test attribute")
         .AddCustomChecker(my_checker);

paddle/fluid/framework/op_version_registry.h

@@ -133,6 +133,9 @@ class OpVersion {
     checkpoints_.push_back(Checkpoint({note, op_version_desc}));
     return *this;
   }
+  uint32_t GetVersionID() const {
+    return static_cast<uint32_t>(checkpoints_.size());
+  }
 
  private:
   struct Checkpoint {
@@ -149,13 +152,21 @@ class OpVersionRegistrar {
     return instance;
   }
   OpVersion& Register(const std::string& op_type) {
-    if (op_version_map_.find(op_type) != op_version_map_.end()) {
-      PADDLE_THROW("'%s' is registered in operator version more than once.",
-                   op_type);
-    }
+    PADDLE_ENFORCE_EQ(
+        op_version_map_.find(op_type), op_version_map_.end(),
+        platform::errors::AlreadyExists(
+            "'%s' is registered in operator version more than once.", op_type));
     op_version_map_.insert({op_type, OpVersion()});
     return op_version_map_[op_type];
   }
+  uint32_t GetVersionID(const std::string& op_type) const {
+    auto it = op_version_map_.find(op_type);
+    if (it == op_version_map_.end()) {
+      return 0;
+    }
+
+    return it->second.GetVersionID();
+  }
 
  private:
   std::unordered_map<std::string, OpVersion> op_version_map_;
@@ -164,6 +175,125 @@ class OpVersionRegistrar {
   OpVersionRegistrar& operator=(const OpVersionRegistrar&) = delete;
 };
 
+class OpVersionComparator {
+ public:
+  virtual bool operator()() = 0;
+  virtual ~OpVersionComparator() = default;
+};
+
+#define ADD_OP_VERSION_COMPARATOR(cmp_name, cmp_math)                   \
+  class OpVersion##cmp_name##Comparator : public OpVersionComparator {  \
+   public:                                                              \
+    explicit OpVersion##cmp_name##Comparator(const std::string op_name, \
+                                             uint32_t target_version)   \
+        : op_name_(op_name), target_version_(target_version) {}         \
+    virtual bool operator()() {                                         \
+      return OpVersionRegistrar::GetInstance().GetVersionID(op_name_)   \
+          cmp_math target_version_;                                     \
+    }                                                                   \
+    virtual ~OpVersion##cmp_name##Comparator() {}                       \
+                                                                        \
+   private:                                                             \
+    std::string op_name_;                                               \
+    uint32_t target_version_;                                           \
+  };
+
+ADD_OP_VERSION_COMPARATOR(LE, <=);
+ADD_OP_VERSION_COMPARATOR(EQ, ==);
+ADD_OP_VERSION_COMPARATOR(GE, >=);
+ADD_OP_VERSION_COMPARATOR(NE, !=);
+
+class OpVersionComparatorCombination {
+ public:
+  OpVersionComparatorCombination() {}
+
+  OpVersionComparatorCombination& LE(const std::string& op_name,
+                                     int target_version) {
+    op_version_comparators_.push_back(std::shared_ptr<OpVersionComparator>(
+        new OpVersionLEComparator(op_name, target_version)));
+    return *this;
+  }
+  OpVersionComparatorCombination& EQ(const std::string& op_name,
+                                     int target_version) {
+    op_version_comparators_.push_back(std::shared_ptr<OpVersionComparator>(
+        new OpVersionEQComparator(op_name, target_version)));
+    return *this;
+  }
+  OpVersionComparatorCombination& GE(const std::string& op_name,
+                                     int target_version) {
+    op_version_comparators_.push_back(std::shared_ptr<OpVersionComparator>(
+        new OpVersionGEComparator(op_name, target_version)));
+    return *this;
+  }
+  OpVersionComparatorCombination& NE(const std::string& op_name,
+                                     int target_version) {
+    op_version_comparators_.push_back(std::shared_ptr<OpVersionComparator>(
+        new OpVersionNEComparator(op_name, target_version)));
+    return *this;
+  }
+
+  bool IsMatched() const {
+    for (const auto& cmp : op_version_comparators_) {
+      if (!(*cmp)()) {
+        return false;
+      }
+    }
+    return true;
+  }
+
+ private:
+  std::vector<std::shared_ptr<OpVersionComparator>> op_version_comparators_;
+};
+
+class PassVersionCheckers {
+ public:
+  PassVersionCheckers& AddCombination(
+      const OpVersionComparatorCombination& combinations) {
+    pass_version_checkers_.push_back(combinations);
+    return *this;
+  }
+  bool IsPassCompatible() const {
+    if (pass_version_checkers_.empty()) {
+      return true;
+    }
+    for (const auto& checker : pass_version_checkers_) {
+      if (checker.IsMatched()) {
+        return true;
+      }
+    }
+    return false;
+  }
+
+ private:
+  std::vector<OpVersionComparatorCombination> pass_version_checkers_;
+};
+
+class PassVersionCheckerRegistrar {
+ public:
+  static PassVersionCheckerRegistrar& GetInstance() {
+    static PassVersionCheckerRegistrar instance;
+    return instance;
+  }
+  PassVersionCheckers& Register(const std::string& pass_name) {
+    return pass_version_checkers_map_[pass_name];
+  }
+  bool IsPassCompatible(const std::string& fuse_pass_name) const {
+    auto iter = pass_version_checkers_map_.find(fuse_pass_name);
+    if (iter == pass_version_checkers_map_.end()) {
+      return true;
+    }
+    return iter->second.IsPassCompatible();
+  }
+
+ private:
+  std::unordered_map<std::string, PassVersionCheckers>
+      pass_version_checkers_map_;
+
+  PassVersionCheckerRegistrar() = default;
+  PassVersionCheckerRegistrar& operator=(const PassVersionCheckerRegistrar&) =
+      delete;
+};
+
 }  // namespace compatible
 }  // namespace framework
 }  // namespace paddle
@@ -173,3 +303,9 @@ class OpVersionRegistrar {
       RegisterOpVersion__##op_type =                                       \
           paddle::framework::compatible::OpVersionRegistrar::GetInstance() \
               .Register(#op_type)
+
+#define REGISTER_PASS_CAPABILITY(pass_name)                        \
+  static auto RegisterOpPassVersionChecker__##pass_name =          \
+      paddle::framework::compatible::PassVersionCheckerRegistrar:: \
+          GetInstance()                                            \
+              .Register(#pass_name)

paddle/fluid/framework/op_version_registry_test.cc

@@ -55,6 +55,72 @@ TEST(test_operator_version, test_operator_version) {
               .NewInput("X2", "The second input.")
               .NewOutput("Y2", "The second output."));
 }
+
+TEST(test_pass_op_version_checker, test_pass_op_version_checker) {
+  ASSERT_TRUE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "no_bind_pass"));
+
+  REGISTER_PASS_CAPABILITY(test_pass1)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .LE("mul", 1)
+              .EQ("fc", 0));
+  ASSERT_TRUE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass1"));
+
+  REGISTER_PASS_CAPABILITY(test_pass2)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .GE("mul", 0)
+              .NE("fc", 0));
+  ASSERT_FALSE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass2"));
+
+  REGISTER_PASS_CAPABILITY(test_pass3)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .GE("mul", 0)
+              .NE("fc", 0))
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .LE("mul", 1)
+              .EQ("fc", 0));
+  ASSERT_TRUE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass3"));
+
+  REGISTER_PASS_CAPABILITY(test_pass4)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .GE("test__", 5)
+              .EQ("fc", 0));
+  ASSERT_FALSE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass4"));
+
+  REGISTER_PASS_CAPABILITY(test_pass5)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .GE("test__", 4)
+              .EQ("fc", 0));
+  ASSERT_TRUE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass5"));
+
+  REGISTER_PASS_CAPABILITY(test_pass6)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .EQ("test__", 4)
+              .EQ("fc", 0));
+  ASSERT_TRUE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass6"));
+
+  REGISTER_PASS_CAPABILITY(test_pass7)
+      .AddCombination(
+          paddle::framework::compatible::OpVersionComparatorCombination()
+              .NE("test__", 4)
+              .EQ("fc", 0));
+  ASSERT_FALSE(PassVersionCheckerRegistrar::GetInstance().IsPassCompatible(
+      "test_pass7"));
+}
+
 }  // namespace compatible
 }  // namespace framework
 }  // namespace paddle