upgrade_ascend_20230207_master
This commit is contained in:
parent
ea725736a6
commit
2151611a32
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@ -110,17 +110,17 @@ include_directories(${PYTHON_INCLUDE_DIRS})
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set(MS_CCSRC_PATH ${CMAKE_SOURCE_DIR}/mindspore/ccsrc)
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set(MS_CCSRC_BUILD_PATH ${BUILD_PATH}/mindspore/mindspore/ccsrc)
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if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
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include(${CMAKE_SOURCE_DIR}/cmake/dependency_graphengine.cmake)
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endif()
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if(NOT MSVC)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fvisibility=hidden")
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endif()
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include(${CMAKE_SOURCE_DIR}/cmake/init.cmake)
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add_subdirectory_with_faster_option(mindspore/ccsrc)
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add_subdirectory(mindspore/core)
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if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
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include(${CMAKE_SOURCE_DIR}/cmake/dependency_graphengine.cmake)
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endif()
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add_subdirectory_with_faster_option(mindspore/ccsrc)
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if(ENABLE_TESTCASES OR ENABLE_CPP_ST)
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add_subdirectory(tests)
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@ -9,14 +9,16 @@ set(ASCEND_DRIVER_HAL_PATH ${ASCEND_PATH}/driver/lib64/driver)
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# CANN packages
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set(ASCEND_CANN_RUNTIME_PATH ${ASCEND_PATH}/latest/lib64)
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set(ASCEND_CANN_OPP_PATH ${ASCEND_PATH}/latest/opp/op_impl/built-in/ai_core/tbe/op_tiling)
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set(ASCEND_CANN_OPP_PATH_TEMP ${ASCEND_PATH}/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
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set(ASCEND_CANN_OPP_PATH ${ASCEND_PATH}/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux)
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set(ASCEND_CANN_OPP_AARCH64_PATH ${ASCEND_CANN_OPP_PATH}/aarch64)
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set(ASCEND_CANN_OPP_X86_64_PATH ${ASCEND_CANN_OPP_PATH}/x86_64)
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set(ASCEND_CANN_PLUGIN_PATH ${ASCEND_CANN_RUNTIME_PATH}/plugin/opskernel)
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# Ascend-toolkit packages
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set(ASCEND_TOOLKIT_RUNTIME_PATH ${ASCEND_PATH}/ascend-toolkit/latest/lib64)
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set(ASCEND_TOOLKIT_OPP_PATH ${ASCEND_PATH}/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe/op_tiling)
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set(ASCEND_TOOLKIT_OPP_PATH_TEMP ${ASCEND_PATH}/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
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set(ASCEND_TOOLKIT_OPP_PATH ${ASCEND_PATH}/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux)
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set(ASCEND_TOOLKIT_OPP_AARCH64_PATH ${ASCEND_TOOLKIT_OPP_PATH}/aarch64)
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set(ASCEND_TOOLKIT_OPP_X86_64_PATH ${ASCEND_TOOLKIT_OPP_PATH}/x86_64)
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set(ASCEND_TOOLKIT_PLUGIN_PATH ${ASCEND_TOOLKIT_RUNTIME_PATH}/plugin/opskernel)
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# nnae packages (for rpath only)
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@ -0,0 +1,14 @@
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# path variables for graphengine submodule, it has to be included after mindspore/core
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# and minspore/ccsrc to prevent conflict of op headers
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if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/external)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/framework)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/base)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/aicpu)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/toolchain)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external/graph)
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endif()
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@ -64,18 +64,6 @@ if(ENABLE_GPU AND GPU_BACKEND_CUDA)
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endif()
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endif()
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if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/external)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/framework)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/aicpu)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/toolchain)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external)
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include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external/graph)
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endif()
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if(ENABLE_MINDDATA)
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include(${CMAKE_SOURCE_DIR}/cmake/external_libs/icu4c.cmake)
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include(${CMAKE_SOURCE_DIR}/cmake/external_libs/opencv.cmake)
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@ -415,7 +415,8 @@
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"TransData ": "support boll",
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"ScatterNdD ": "Accuracy issues",
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"Trace": "Hadn't adapted tbe implementation",
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"AssignAdd": "Frac_nz in pangu not support"
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"AssignAdd": "Frac_nz in pangu not support",
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"Range": "not support dynamic shape with tiling failed"
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},
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"SkipNodes": [
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"BroadcastTo",
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@ -444,7 +445,8 @@
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"ACos",
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"TransData",
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"ScatterNdD",
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"AssignAdd"
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"AssignAdd",
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"Range"
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],
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"FallbackOps": {
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"DeformableOffsets": [
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@ -1 +1 @@
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Subproject commit 236001806129e36c0f48b240c4f61b2e1d92c470
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Subproject commit f5f74bb7a124f99bbaeaec17b55aa466fdd34285
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@ -5,6 +5,10 @@ include_directories(${CMAKE_BINARY_DIR})
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include_directories(${CMAKE_SOURCE_DIR}/mindspore/core/mindrt/include)
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include_directories(${CMAKE_SOURCE_DIR}/mindspore/core/mindrt/src)
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# graphengine include directories
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if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
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include(${CMAKE_SOURCE_DIR}/cmake/graphengine_variables.cmake)
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endif()
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set(SERVER_FLATBUFFER_OUTPUT "${CMAKE_BINARY_DIR}/schema")
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@ -19,6 +19,7 @@
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#include "include/transform/graph_ir/utils.h"
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#include "cxx_api/model/model_converter_utils/multi_process.h"
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#include "graph/model.h"
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#include "graph/utils/graph_utils_ex.h"
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#include "acl/acl_rt.h"
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#include "cxx_api/model/aoe/auto_tune_process.h"
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#include "plugin/device/ascend/optimizer/ge_optimization.h"
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@ -194,7 +195,7 @@ Buffer ModelConverter::LoadMindIR(const FuncGraphPtr &func_graph) {
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}
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ge::Model model;
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ge::Buffer model_data;
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model.SetGraph(*df_graph);
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model.SetGraph(::ge::GraphUtilsEx::GetComputeGraph(*df_graph));
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auto ge_ret = model.Save(model_data);
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if (ge_ret != ge::SUCCESS) {
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MS_LOG(ERROR) << "Save ge model to buffer failed.";
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@ -263,7 +264,8 @@ Buffer ModelConverter::LoadAscendIRInner(const Buffer &model_data) {
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return Buffer();
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}
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transform::DfGraphPtr df_graph = std::make_shared<transform::DfGraph>(load_model.GetGraph());
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transform::DfGraphPtr df_graph =
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std::make_shared<transform::DfGraph>(::ge::GraphUtilsEx::CreateGraphFromComputeGraph(load_model.GetGraph()));
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if (df_graph == nullptr) {
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MS_LOG(ERROR) << "Convert FuncGraph to AscendIR failed.";
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return Buffer();
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@ -6,11 +6,22 @@ include_directories(${CMAKE_SOURCE_DIR}/mindspore/ccsrc/minddata/dataset)
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set(ASCEND_RPATH ${ASCEND_RPATH}:/usr/local/Ascend/nnae/latest/lib64)
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set(ASCEND_RPATH ${ASCEND_RPATH}:/usr/local/Ascend/ascend-toolkit/latest/lib64)
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set(ASCEND_RPATH ${ASCEND_RPATH}:/usr/local/Ascend/latest/lib64)
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set(ASCEND_RPATH ${ASCEND_RPATH}:/usr/local/Ascend/opp/built-in/op_impl/ai_core/tbe/op_tiling)
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set(ASCEND_RPATH ${ASCEND_RPATH}:/usr/local/Ascend/nnae/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
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set(ASCEND_RPATH ${ASCEND_RPATH}:/usr/local/Ascend/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
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if(CMAKE_HOST_SYSTEM_PROCESSOR MATCHES "x86_64")
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/nnae/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/x86_64)
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/x86_64)
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/x86_64)
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else()
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/nnae/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/aarch64)
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/aarch64)
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set(ASCEND_RPATH
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${ASCEND_RPATH}:/usr/local/Ascend/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/aarch64)
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endif()
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### cxx api need file ###
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if(ENABLE_ACL)
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@ -87,8 +98,11 @@ if(MODE_ASCEND_ALL)
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find_library(PLATFORM platform ${ASCEND_CANN_RUNTIME_PATH} ${ASCEND_TOOLKIT_RUNTIME_PATH})
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find_library(OPT_FEATURE opt_feature ${ASCEND_CANN_RUNTIME_PATH} ${ASCEND_TOOLKIT_RUNTIME_PATH})
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find_library(adump_server libadump_server.a ${ASCEND_CANN_RUNTIME_PATH} ${ASCEND_TOOLKIT_RUNTIME_PATH})
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find_library(OPTILING optiling ${ASCEND_CANN_OPP_PATH} ${ASCEND_TOOLKIT_OPP_PATH}
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${ASCEND_CANN_OPP_PATH_TEMP} ${ASCEND_TOOLKIT_OPP_PATH_TEMP})
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if(CMAKE_HOST_SYSTEM_PROCESSOR MATCHES "x86_64")
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find_library(OPTILING optiling ${ASCEND_CANN_OPP_X86_64_PATH} ${ASCEND_TOOLKIT_OPP_X86_64_PATH})
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else()
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find_library(OPTILING optiling ${ASCEND_CANN_OPP_AARCH64_PATH} ${ASCEND_TOOLKIT_OPP_AARCH64_PATH})
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endif()
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find_library(ACL_OP_COMPILER acl_op_compiler ${ASCEND_CANN_RUNTIME_PATH} ${ASCEND_TOOLKIT_RUNTIME_PATH})
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target_link_libraries(mindspore_ascend PRIVATE ${RUNTIME_LIB} ${TSDCLIENT} ${DATATRANSFER} ${ERROR_MANAGER}
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@ -254,7 +254,7 @@ size_t AscendMemAdapter::GetDeviceMemSizeFromContext() const {
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uint8_t *AscendMemAdapter::MallocFromRts(size_t size) const {
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uint8_t *ptr = nullptr;
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auto ret = rtMalloc(reinterpret_cast<void **>(&ptr), size, RT_MEMORY_HBM);
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auto ret = rtMalloc(reinterpret_cast<void **>(&ptr), size, RT_MEMORY_HBM, 0);
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if (ret != ACL_RT_SUCCESS) {
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if (ret == ACL_ERROR_RT_MEMORY_ALLOCATION) {
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auto context_ptr = MsContext::GetInstance();
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@ -277,12 +277,12 @@ void DataDumper::OpDebugRegister() {
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MS_LOG(EXCEPTION) << "[DataDump] Call rt api rtGetRtCapability failed, ret = " << rt_ret;
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}
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auto memory_type = (value == static_cast<int64_t>(RT_CAPABILITY_SUPPORT)) ? RT_MEMORY_TS : RT_MEMORY_HBM;
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rt_ret = rtMalloc(&op_debug_buffer_addr_, kOpDebugHostMemSize, memory_type);
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rt_ret = rtMalloc(&op_debug_buffer_addr_, kOpDebugHostMemSize, memory_type, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "[DataDump] Call rt api rtMalloc failed, ret = " << rt_ret;
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}
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rt_ret = rtMalloc(&op_debug_dump_args_, kOpDebugDevMemSize, RT_MEMORY_HBM);
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rt_ret = rtMalloc(&op_debug_dump_args_, kOpDebugDevMemSize, RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "[DataDump] Call rtMalloc failed, ret = " << rt_ret;
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}
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@ -101,7 +101,7 @@ void RtLoadDumpData(const aicpu::dump::OpMappingInfo &dump_info, void **ptr) {
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return;
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}
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rtError_t rt_ret = rtMalloc(ptr, proto_size, RT_MEMORY_HBM);
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rtError_t rt_ret = rtMalloc(ptr, proto_size, RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "[DumperBase] Call rtMalloc failed";
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}
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@ -184,7 +184,7 @@ void KernelDumper::ExecutorDumpOp(const aicpu::dump::OpMappingInfo &op_mapping_i
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}
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std::string proto_json;
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(void)google::protobuf::util::MessageToJsonString(op_mapping_info, &proto_json);
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rtError_t rt_ret = rtMalloc(&proto_dev_mem_, proto_size, RT_MEMORY_HBM);
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rtError_t rt_ret = rtMalloc(&proto_dev_mem_, proto_size, RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(ERROR) << "[KernelDumper] Call rt api rtMalloc failed, ret = " << rt_ret;
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return;
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@ -196,7 +196,7 @@ void KernelDumper::ExecutorDumpOp(const aicpu::dump::OpMappingInfo &op_mapping_i
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return;
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}
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rt_ret = rtMalloc(&proto_size_dev_mem_, sizeof(size_t), RT_MEMORY_HBM);
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rt_ret = rtMalloc(&proto_size_dev_mem_, sizeof(size_t), RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(ERROR) << "[KernelDumper] Call rt api rtMalloc failed, ret = " << rt_ret;
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return;
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@ -372,7 +372,7 @@ void KernelDumper::MallocP2PDebugMem(const void *const op_debug_addr) {
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MS_LOG(EXCEPTION) << "[KernelDumper] Call rt api rtGetRtCapability failed, ret = " << rt_ret;
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}
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auto memory_type = (value == static_cast<int64_t>(RT_CAPABILITY_SUPPORT)) ? RT_MEMORY_TS : RT_MEMORY_HBM;
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rtMalloc(&p2p_debug_addr_, kDebugP2pSize, memory_type);
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rtMalloc(&p2p_debug_addr_, kDebugP2pSize, memory_type, 0);
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rtMemcpy(p2p_debug_addr_, sizeof(uint64_t), &debug_addrs_tmp, sizeof(uint64_t), RT_MEMCPY_HOST_TO_DEVICE);
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}
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@ -416,7 +416,7 @@ void KernelDumper::OpDebugRegisterForStream(const CNodePtr &kernel) {
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MS_LOG(EXCEPTION) << "[KernelDumper] Call rt api rtGetRtCapability failed, ret = " << rt_ret;
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}
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auto memory_type = (value == static_cast<int64_t>(RT_CAPABILITY_SUPPORT)) ? RT_MEMORY_TS : RT_MEMORY_HBM;
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rt_ret = rtMalloc(&op_debug_task->op_debug_addr, kOpDebugMemorySize, memory_type);
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rt_ret = rtMalloc(&op_debug_task->op_debug_addr, kOpDebugMemorySize, memory_type, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "[KernelDumper] Call rt api rtMalloc failed, ret = " << rt_ret;
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}
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@ -91,7 +91,7 @@ void AicpuTask::Distribute() {
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sizeof(uint32_t);
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// Malloc device memory for args
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rtError_t rt_ret = rtMalloc(&args_, args_size_, RT_MEMORY_HBM);
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rtError_t rt_ret = rtMalloc(&args_, args_size_, RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "Call rt api rtMalloc failed, ret: " << rt_ret;
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}
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@ -165,7 +165,7 @@ void AicpuTask::SetAicpuParamHead(uint32_t args_size, uint32_t io_addrs_num) {
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}
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}
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// alloc extinfo address
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rtError_t flag = rtMalloc(&ext_info_addr_, ext_info_handler->GetExtInfoLen(), RT_MEMORY_HBM);
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rtError_t flag = rtMalloc(&ext_info_addr_, ext_info_handler->GetExtInfoLen(), RT_MEMORY_HBM, 0);
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if (flag != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "Call rt api rtMalloc failed, ret: " << flag;
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}
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@ -61,7 +61,7 @@ void LabelGotoTask::Distribute() {
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MS_EXCEPTION_IF_NULL(label_info_);
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if (index_value_ == nullptr) {
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rtError_t rt_ret = rtMalloc(&index_value_, sizeof(uint64_t), RT_MEMORY_HBM);
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rtError_t rt_ret = rtMalloc(&index_value_, sizeof(uint64_t), RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(EXCEPTION) << "Call rt api rtMalloc failed, ret: " << rt_ret;
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}
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@ -106,7 +106,7 @@ std::shared_ptr<LabelGuard> LabelManager::GetLabelInfo(rtModel_t model, const st
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return nullptr;
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}
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rt_ret = rtMalloc(&label_info, label_info_size, (value == RT_CAPABILITY_SUPPORT) ? RT_MEMORY_TS : RT_MEMORY_HBM);
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rt_ret = rtMalloc(&label_info, label_info_size, (value == RT_CAPABILITY_SUPPORT) ? RT_MEMORY_TS : RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
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MS_LOG(ERROR) << "Call rt api rtMalloc failed, ret: " << rt_ret;
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return nullptr;
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@ -78,7 +78,7 @@ void TbeTask::Distribute() {
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task_info_->workspace_addrs().cend());
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args_size_ = static_cast<uint32_t>(tensor_device_addrs.size() * sizeof(void *));
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rt_ret = rtMalloc(&args_, args_size_, RT_MEMORY_HBM);
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rt_ret = rtMalloc(&args_, args_size_, RT_MEMORY_HBM, 0);
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if (rt_ret != RT_ERROR_NONE) {
|
||||
MS_LOG(EXCEPTION) << "Call rt api rtMalloc failed, ret: " << rt_ret << " mem size " << args_size_;
|
||||
}
|
||||
|
|
|
@ -31,6 +31,7 @@
|
|||
#include "plugin/device/ascend/hal/profiler/parallel_strategy_profiling.h"
|
||||
#include "plugin/device/ascend/optimizer/enhancer/add_placeholder_for_dynamic_rnn.h"
|
||||
#include "cxx_api/graph/acl/acl_env_guard.h"
|
||||
#include "graph/utils/graph_utils_ex.h"
|
||||
|
||||
using mindspore::abstract::AbstractScalar;
|
||||
using mindspore::abstract::AbstractTensor;
|
||||
|
@ -166,7 +167,7 @@ void AscendDeprecatedInterface::ExportDFGraph(const std::string &file_name, cons
|
|||
}
|
||||
// get model stream
|
||||
::ge::Model model("", "");
|
||||
model.SetGraph(*ge_graph);
|
||||
model.SetGraph(::ge::GraphUtilsEx::GetComputeGraph(*ge_graph));
|
||||
::ge::Buffer model_data;
|
||||
auto ge_ret = model.Save(model_data);
|
||||
if (ge_ret != ::ge::SUCCESS) {
|
||||
|
|
|
@ -224,14 +224,14 @@ bool AicpuOpKernelLoad::CacheBinaryFileToDevice(const uintptr_t &resource_id, st
|
|||
void *d_aicpu_data = nullptr;
|
||||
void *d_so_name = nullptr;
|
||||
|
||||
status = rtMalloc(&d_aicpu_data, aicpu_data_length, RT_MEMORY_HBM);
|
||||
status = rtMalloc(&d_aicpu_data, aicpu_data_length, RT_MEMORY_HBM, 0);
|
||||
if (status != RT_ERROR_NONE) {
|
||||
MS_LOG(ERROR) << "Call rtMalloc failed, size:" << aicpu_data_length << ", ret = 0x" << status;
|
||||
return false;
|
||||
}
|
||||
allocated_mem->emplace_back(d_aicpu_data);
|
||||
|
||||
status = rtMalloc(&d_so_name, so_name.size(), RT_MEMORY_HBM);
|
||||
status = rtMalloc(&d_so_name, so_name.size(), RT_MEMORY_HBM, 0);
|
||||
if (status != RT_ERROR_NONE) {
|
||||
MS_LOG(ERROR) << "Call rtMalloc failed, size:" << so_name.size() << ", ret = 0x" << status;
|
||||
return false;
|
||||
|
@ -267,7 +267,7 @@ bool AicpuOpKernelLoad::CacheBinaryFileToDevice(const uintptr_t &resource_id, st
|
|||
|
||||
void *args = nullptr;
|
||||
uint32_t args_size = sizeof(CustAicpuSoBuf) * v_cust_so.size();
|
||||
status = rtMalloc(&args, args_size, RT_MEMORY_HBM);
|
||||
status = rtMalloc(&args, args_size, RT_MEMORY_HBM, 0);
|
||||
if (status != RT_ERROR_NONE) {
|
||||
MS_LOG(ERROR) << "Call rtMalloc failed, size:" << args_size << ", ret = 0x" << status;
|
||||
return false;
|
||||
|
|
|
@ -78,7 +78,7 @@ const std::map<TypeId, std::string> type_id_str_maps = {
|
|||
const std::unordered_map<std::string, size_t> type_nbyte_maps = {
|
||||
{"float16", sizeof(float) / 2}, {"float32", sizeof(float)},
|
||||
{"float64", sizeof(float) * 2}, {"int8", sizeof(int) / 4},
|
||||
{"uint1", sizeof(int) / 4}, {"int16", sizeof(int) / 2},
|
||||
{"int1", sizeof(int) / 8}, {"int16", sizeof(int) / 2},
|
||||
{"int32", sizeof(int)}, {"int64", sizeof(int) * 2},
|
||||
{"uint8", sizeof(int) / 4}, {"uint16", sizeof(int) / 2},
|
||||
{"uint32", sizeof(int)}, {"uint64", sizeof(int) * 2},
|
||||
|
|
|
@ -14,6 +14,9 @@
|
|||
* limitations under the License.
|
||||
*/
|
||||
#include "include/common/utils/python_fallback_running.h"
|
||||
#include "ops/tuple_get_item.h"
|
||||
#include "ops/primitive_c.h"
|
||||
#include "mindapi/src/helper.h"
|
||||
|
||||
namespace mindspore {
|
||||
ScopedFallbackRunning::ScopedFallbackRunning() { on_ = true; }
|
||||
|
|
|
@ -2,6 +2,7 @@ include_directories(${TOP_DIR}/graphengine/metadef/inc/external)
|
|||
include_directories(${TOP_DIR}/graphengine/inc)
|
||||
include_directories(${TOP_DIR}/graphengine/inc/external)
|
||||
include_directories(${TOP_DIR}/graphengine/ge)
|
||||
include_directories(${TOP_DIR}/graphengine/base)
|
||||
include_directories(${TOP_DIR}/graphengine/metadef/inc)
|
||||
include_directories(${TOP_DIR}/graphengine/inc/framework)
|
||||
include_directories(${TOP_DIR}/graphengine/third_party/fwkacllib/inc)
|
||||
|
|
|
@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
|
|
|
@ -18,8 +18,8 @@ from __future__ import absolute_import
|
|||
|
||||
import te
|
||||
from te import tvm
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
batch_norm_op_info = TBERegOp("BatchNormFoldD") \
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
|
|
@ -17,9 +17,9 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from te.platform.cce_build import build_config
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.common.buildcfg import build_config
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
@ -101,5 +101,5 @@ def batchnorm_fold2_grad_reduce(dout, x, dout_reduce, dout_x_reduce, kernel_name
|
|||
return
|
||||
from impl.bn_training_reduce import bn_training_reduce_schedule_nd
|
||||
sch, tensor_list = bn_training_reduce_schedule_nd(res_list)
|
||||
with build_config:
|
||||
with build_config():
|
||||
tvm.build(sch, tensor_list, "cce", name=kernel_name)
|
||||
|
|
|
@ -18,8 +18,8 @@
|
|||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
import te.lang.cce
|
||||
from te import tvm
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
|
||||
batch_norm_op_info = TBERegOp("BatchNormFoldGradD") \
|
||||
.fusion_type("OPAQUE") \
|
||||
|
|
|
@ -17,7 +17,7 @@ from __future__ import absolute_import
|
|||
import logging
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
logging.basicConfig(level=logging.DEBUG, format="%(asctime)s %(levelname)s %(message)s")
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
|
|
@ -15,7 +15,7 @@
|
|||
"""dsd back impl"""
|
||||
from __future__ import absolute_import
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import DataType, TBERegOp, op_info_register
|
||||
|
||||
dsd_grad_info = TBERegOp('DSDGrad') \
|
||||
|
|
|
@ -15,7 +15,7 @@
|
|||
""" dense sparse to densne matmul"""
|
||||
from __future__ import absolute_import
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import DataType, TBERegOp, op_info_register
|
||||
|
||||
dsd_matmul_info = TBERegOp('DSDMatmul') \
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
fake_learned_scale_quant_perchannel_op_info = TBERegOp("FakeLearnedScaleQuantPerChannel") \
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
NEG_SCALAR_MIN_FP16 = -(2 ** (-24))
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
|
||||
|
|
|
@ -18,8 +18,8 @@ from functools import reduce as functools_reduce
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
fake_learned_scale_quant_perlayer_op_info = TBERegOp("FakeLearnedScaleQuantPerLayer") \
|
||||
|
|
|
@ -19,8 +19,8 @@ from functools import reduce as functools_reduce
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
NEG_SCALAR_MIN_FP16 = -(2 ** (-24))
|
||||
|
|
|
@ -19,8 +19,8 @@ from functools import reduce as functools_reduce
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
|
||||
|
|
|
@ -19,8 +19,8 @@ from __future__ import absolute_import
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
fake_quant_perchannel_op_info = TBERegOp("FakeQuantPerChannel") \
|
||||
|
|
|
@ -19,8 +19,8 @@ from __future__ import absolute_import
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
|
|
@ -20,8 +20,8 @@ from functools import reduce as functools_reduce
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
fake_quant_per_layer_op_info = TBERegOp("FakeQuantPerLayer") \
|
||||
|
|
|
@ -20,8 +20,8 @@ from functools import reduce as functools_reduce
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
SHAPE_SIZE_LIMIT = 2147483648
|
||||
|
|
|
@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
|
|
|
@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
cus_img2col_info = TBERegOp("CusImg2Col") \
|
||||
|
|
|
@ -21,8 +21,8 @@ import te.lang.cce
|
|||
import te.platform.cce_params as cce
|
||||
from te import tik
|
||||
from te import tvm
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
from mindspore.ops._op_impl._custom_op._basic import _shape_check, _get_bias, _get_input_shape
|
||||
|
||||
|
|
|
@ -20,7 +20,7 @@ matmul
|
|||
from __future__ import absolute_import
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
matmul_cube_dense_right_op_info = TBERegOp("CusMatMulCubeDenseRight") \
|
||||
|
|
|
@ -22,7 +22,7 @@ import collections
|
|||
|
||||
import te.platform.cce_params as cce
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
from mindspore.ops._op_impl._custom_op._basic import _shape_check, _get_bias, _get_input_shape
|
||||
|
||||
|
|
|
@ -23,7 +23,7 @@ from collections import namedtuple
|
|||
import logging
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
# General limitation of the size for input shape: 2**31
|
||||
|
|
|
@ -22,8 +22,8 @@ from impl.matmul_vector import matmul_vector_cce
|
|||
import te.platform.cce_params as cce
|
||||
import te.lang.cce
|
||||
from te import tvm
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
from mindspore.ops._op_impl._custom_op._basic import _shape_check, _get_bias, _get_input_shape
|
||||
|
||||
|
|
|
@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
cus_matrix_combine_op_info = TBERegOp("CusMatrixCombine") \
|
||||
|
|
|
@ -17,8 +17,8 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
minmax_update_perchannel_op_info = TBERegOp("MinMaxUpdatePerChannel") \
|
||||
|
|
|
@ -18,8 +18,8 @@ from functools import reduce as functools_reduce
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
minmax_update_perlayer_op_info = TBERegOp("MinMaxUpdatePerLayer") \
|
||||
|
|
|
@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
|
||||
|
||||
from te import tik
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
cus_transpose02314_op_info = TBERegOp("CusTranspose02314") \
|
||||
|
|
|
@ -255,7 +255,7 @@ class AscendEnvChecker(EnvChecker):
|
|||
|
||||
def __init__(self, library_path):
|
||||
self.library_path = library_path
|
||||
self.version = ["1.84"]
|
||||
self.version = ["6.3"]
|
||||
atlas_nnae_version = "/usr/local/Ascend/nnae/latest/compiler/version.info"
|
||||
atlas_toolkit_version = "/usr/local/Ascend/ascend-toolkit/latest/compiler/version.info"
|
||||
hisi_fwk_version = "/usr/local/Ascend/latest/compiler/version.info"
|
||||
|
@ -331,7 +331,7 @@ class AscendEnvChecker(EnvChecker):
|
|||
|
||||
def check_deps_version(self):
|
||||
"""
|
||||
te, topi, hccl wheel package version check
|
||||
te and hccl wheel package version check
|
||||
in order to update the change of 'LD_LIBRARY_PATH' env, run a sub process
|
||||
"""
|
||||
|
||||
|
@ -345,12 +345,6 @@ class AscendEnvChecker(EnvChecker):
|
|||
attention_warning = True
|
||||
logger.warning(f"MindSpore version {mindspore_version} and \"te\" wheel package version {v} does not "
|
||||
"match, reference to the match info on: https://www.mindspore.cn/install")
|
||||
from topi import version as topiver
|
||||
v = '.'.join(topiver.version.split('.')[0:2])
|
||||
if v not in supported_version:
|
||||
attention_warning = True
|
||||
logger.warning(f"MindSpore version {mindspore_version} and \"topi\" wheel package version {v} does not "
|
||||
"match, reference to the match info on: https://www.mindspore.cn/install")
|
||||
from hccl import sys_version as hccl_version
|
||||
v = '.'.join(hccl_version.__sys_version__.split('.')[0:2])
|
||||
if v not in supported_version:
|
||||
|
@ -361,7 +355,7 @@ class AscendEnvChecker(EnvChecker):
|
|||
# pylint: disable=broad-except
|
||||
except Exception as e:
|
||||
logger.error("CheckFailed:", e.args)
|
||||
logger.error("MindSpore relies on the 3 whl packages of \"te\", \"topi\" and \"hccl\" in the \"latest\" "
|
||||
logger.error("MindSpore relies on whl packages of \"te\" and \"hccl\" in the \"latest\" "
|
||||
"folder of the Ascend AI software package (Ascend Data Center Solution), please check whether"
|
||||
" they are installed correctly or not, reference to the match info on: "
|
||||
"https://www.mindspore.cn/install")
|
||||
|
|
|
@ -8,6 +8,11 @@ include_directories(${CMAKE_SOURCE_DIR}/mindspore/core)
|
|||
include_directories(${CMAKE_BINARY_DIR})
|
||||
include_directories(${CUDA_INCLUDE_DIRS})
|
||||
|
||||
# graphengine include directories
|
||||
if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
|
||||
include(${CMAKE_SOURCE_DIR}/cmake/graphengine_variables.cmake)
|
||||
endif()
|
||||
|
||||
if(ENABLE_ACL)
|
||||
add_definitions(-D ENABLE_ACL)
|
||||
endif()
|
||||
|
|
|
@ -174,7 +174,7 @@ class TimeMonitor(Callback):
|
|||
self.per_step_mseconds_list.append(epoch_mseconds / self.data_size)
|
||||
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.level1
|
||||
@pytest.mark.platform_arm_ascend_training
|
||||
@pytest.mark.platform_x86_ascend_training
|
||||
@pytest.mark.env_onecard
|
||||
|
|
|
@ -23,7 +23,7 @@ from mindspore import Tensor
|
|||
context.set_context(device_target="Ascend")
|
||||
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.level1
|
||||
@pytest.mark.platform_x86_ascend_training
|
||||
@pytest.mark.platform_arm_ascend_training
|
||||
@pytest.mark.env_onecard
|
||||
|
|
|
@ -59,7 +59,7 @@ class Grad(nn.Cell):
|
|||
return self.grad(self.network)(x, w, offset, output_grad)
|
||||
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.level1
|
||||
@pytest.mark.platform_x86_ascend_training
|
||||
@pytest.mark.platform_arm_ascend_training
|
||||
@pytest.mark.env_onecard
|
||||
|
|
|
@ -126,7 +126,7 @@ class TestUnsortedSegmentArithmeticNet(nn.Cell):
|
|||
return self.func(x, segment_ids, self.num_segments)
|
||||
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.level1
|
||||
@pytest.mark.platform_arm_ascend_training
|
||||
@pytest.mark.platform_x86_ascend_training
|
||||
@pytest.mark.env_onecard
|
||||
|
|
|
@ -16,8 +16,8 @@ from __future__ import absolute_import
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
@fusion_manager.register("add3")
|
||||
|
|
|
@ -15,9 +15,9 @@
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform import CUBE_MKN
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from topi.cce.util import is_v200_version
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
from tbe.tvm.topi.cce.util import is_v200_version
|
||||
|
||||
# pylint: disable=R0912,R0913,R0914,R0915,E1101
|
||||
# the dim of shape in conv must be 4
|
||||
|
|
|
@ -17,8 +17,8 @@ from __future__ import absolute_import
|
|||
import te.lang.cce
|
||||
from te import tvm
|
||||
from te.platform.fusion_manager import fusion_manager
|
||||
from topi import generic
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi import generic
|
||||
from tbe.tvm.topi.cce import util
|
||||
|
||||
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
|
||||
|
||||
|
|
|
@ -114,7 +114,7 @@ class TensorSetItem(nn.Cell):
|
|||
return tensor1, tensor2
|
||||
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.level1
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.platform_x86_gpu_training
|
||||
@pytest.mark.platform_arm_ascend_training
|
||||
|
|
|
@ -33,7 +33,7 @@ from mindspore.ops.composite.multitype_ops.zeros_like_impl import zeros_like
|
|||
def square_with_bias(input_x, output_y, bias=0.0, kernel_name="square_with_bias"):
|
||||
import te.lang.cce
|
||||
from te import tvm
|
||||
from topi.cce import util
|
||||
from tbe.tvm.topi.cce import util
|
||||
|
||||
shape = input_x.get("shape")
|
||||
dtype = input_x.get("dtype").lower()
|
||||
|
|
|
@ -34,6 +34,10 @@ include_directories(${CMAKE_BINARY_DIR}/proto/metadef_protos)
|
|||
include_directories(${CMAKE_BINARY_DIR}/proto/ge)
|
||||
include_directories(${CUDA_INCLUDE_DIRS})
|
||||
include_directories(${CMAKE_SOURCE_DIR}/mindspore/ccsrc/plugin/device/cpu/kernel)
|
||||
# graphengine include directories
|
||||
if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
|
||||
include(${CMAKE_SOURCE_DIR}/cmake/graphengine_variables.cmake)
|
||||
endif()
|
||||
MESSAGE("check ut_test ${CMAKE_BINARY_DIR}")
|
||||
|
||||
link_directories(${MS_CCSRC_BUILD_PATH})
|
||||
|
|
|
@ -30,7 +30,7 @@ rtError_t rtEventCreateWithFlag(rtEvent_t *event, uint32_t flag) { return RT_ERR
|
|||
|
||||
rtError_t rtEventElapsedTime(float *time, rtEvent_t start, rtEvent_t end) { return RT_ERROR_NONE; }
|
||||
|
||||
rtError_t rtMalloc(void **devPtr, uint64_t size, rtMemType_t type) { return RT_ERROR_NONE; }
|
||||
rtError_t rtMalloc(void **devPtr, uint64_t size, rtMemType_t type, const uint16_t moduleId) { return RT_ERROR_NONE; }
|
||||
|
||||
rtError_t rtMemcpy(void *dst, uint64_t destMax, const void *src, uint64_t count, rtMemcpyKind_t kind) {
|
||||
return RT_ERROR_NONE;
|
||||
|
|
Loading…
Reference in New Issue