!49312 modify format

Merge pull request !49312 from 俞涵/code_docs_2.0.0al

.devops/新的PR提交通知.yml

@@ -1,37 +0,0 @@
-version: 2
-name: 新的PR提交通知
-description: ""
-global:
-  concurrent: 1
-trigger:
-  webhook: gitlink@1.0.0
-  event:
-    - ref: pr
-      ruleset:
-        - param-ref: action
-          operator: EQ
-          value: "'opened'"
-      ruleset-operator: AND
-workflow:
-  - ref: start
-    name: 开始
-    task: start
-  - ref: dingtalk_notice_text_0
-    name: 钉钉通知-文本
-    task: dingtalk_notice_text@1.0.2
-    input:
-      boot_webhook_url: ((dingdingtalk.token_url))
-      secret: ((dingdingtalk.serect))
-      msg_text: '"【"+((trigger.user)) +
-        "】从"+((trigger.source_branch))+"提交PR到"+((trigger.target_branch)) +
-        "，请您立即确认是否合并。"'
-      at_user_ids: '"[]"'
-      at_mobiles: '"[]"'
-    needs:
-      - start
-  - ref: end
-    name: 结束
-    task: end
-    needs:
-      - dingtalk_notice_text_0
-

.gitignore

@@ -9,10 +9,6 @@ somas_meta/
 trace_code_graph_*
 
 # mindspore lite java
-mindspore/lite/java/.gradle/
-mindspore/lite/java/gradle
-mindspore/lite/java/gradlew
-mindspore/lite/java/gradlew.bat
 mindspore/lite/java/java/.gradle
 mindspore/lite/java/java/build
 mindspore/lite/java/java/gradle

.gitmodules

@@ -7,30 +7,3 @@
 [submodule "tests/models"]
 	path = tests/models
 	url = https://gitee.com/mindspore/models.git
-[submodule "MindSpore-first-experience"]
-	path = MindSpore-first-experience
-	url = ../MindSpore-first-experience.git
-[submodule "MindSpore-install"]
-	path = MindSpore-install
-	url = ../MindSpore-install.git
-[submodule "MindSpore-Application-practice"]
-	path = MindSpore-Application-practice
-	url = ../MindSpore-Application-practice.git
-[submodule "MindSpore-Model-Development"]
-	path = MindSpore-Model-Development
-	url = ../MindSpore-Model-Development.git
-[submodule "MindSpore-Data-preprocessing"]
-	path = MindSpore-Data-preprocessing
-	url = ../MindSpore-Data-preprocessing.git
-[submodule "Mindspore-Data-storage-use"]
-	path = Mindspore-Data-storage-use
-	url = ../Mindspore-Data-storage-use.git
-[submodule "MindSpore-Data-storage-kunpeng"]
-	path = MindSpore-Data-storage-kunpeng
-	url = ../MindSpore-Data-storage-kunpeng.git
-[submodule "MindSpore-LeNet-jzx3"]
-	path = MindSpore-LeNet-jzx3
-	url = ../MindSpore-LeNet-jzx3.git
-[submodule "MindSpore-competition"]
-	path = MindSpore-competition
-	url = ../MindSpore-competition.git

.jenkins/check/config/filter_cppcheck.txt

@@ -40,15 +40,6 @@
 "mindspore/mindspore/core/ops/max_pool.cc"                                                            "zerodivcond"
 "mindspore/core/utils/log_adapter.cc"                                                                 "stlIfStrFind"
 "mindspore/mindspore/ccsrc/transform/graph_ir/convert.cc"                                             "knownConditionTrueFalse"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_array_ops.cc"          "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_image_ops.cc"          "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_inner_ops.cc"          "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_math_ops.cc"           "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_nn_ops.cc"             "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_quant_ops.cc"          "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_scipy_ops.cc"          "internalAstError"
-"mindspore/mindspore/ccsrc/pipeline/pynative/grad/bprop_expander/grad_ops/grad_sparse_ops.cc"         "internalAstError"
-"mindspore/mindspore/ccsrc/plugin/device/cpu/kernel/xlogy_cpu_kernel.cc"                              "unreadVariable"
 
 # MindData
 "mindspore/mindspore/ccsrc/minddata/dataset/engine/dataset_iterator.cc"                               "useStlAlgorithm"
@@ -80,39 +71,3 @@
 "mindspore/mindspore/lite/src/litert/kernel/cpu/fp32/convolution_winograd_fp32.cc"                      "knownConditionTrueFalse"
 "mindspore/mindspore/lite/src/litert/kernel/cpu/fp32/convolution_winograd_fp32.cc"                      "shadowVariable"
 "mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/tbe/tbe_utils.cc"                      "knownConditionTrueFalse"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/op_proto/add_dsl.cc"               "syntaxError"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/op_proto/matmul_tik.cc"            "syntaxError"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend_new/op_proto/"                                    "syntaxError"
-
-# AICPU migration
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/" "constVariable"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/" "redundantAssignment"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/" "constArgument"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/" "unknownMacro"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/utils/" "constVariable"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/utils/" "unsignedLessThanZero"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "nullPointerRedundantCheck"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "variableScope"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "unreadVariable"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "useStlAlgorithm"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "constParameter"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "truncLongCastAssignment"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "knownConditionTrueFalse"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "passedByValue"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "uninitMemberVar"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "syntaxError"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "unusedVariable"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "shadowArgument"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "unsignedPositive"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "uninitvar"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "shadowVariable"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "unsignedPositive"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "zerodivcond"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "noConstructor"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "noExplicitConstructor"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "syntaxError"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "unsignedLessThanZero"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "identicalConditionAfterEarlyExit"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "uninitMemberVar"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "redundantInitialization"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "redundantCondition"

.jenkins/check/config/filter_cpplint.txt

@@ -86,59 +86,3 @@
 "mindspore/mindspore/lite/src/litert/delegate/nnapi/nnapi_implementation.cc"                       "build/include_order"
 "mindspore/mindspore/lite/src/extendrt/cxx_api/model/model_impl.cc"                                "whitespace/parens"
 "mindspore/mindspore/ccsrc/plugin/device/cpu/kernel/nnacl/experimental/HPC-generator/gemm_mask_avx512/" "runtime/int"
-# ascend samples
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/aicpu/sample/"                                "build/include_subdir"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "build/include_subdir"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "build/include_subdir"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/aicpu/sample/"                                "runtime/references"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "runtime/references"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "runtime/references"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/aicpu/sample/"                                "whitespace/comments"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "whitespace/comments"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "whitespace/comments"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/aicpu/sample/"                                "legal/copyright"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "legal/copyright"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "legal/copyright"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/aicpu/sample/"                                "whitespace/ending_newline"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "whitespace/ending_newline"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "whitespace/ending_newline"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/aicpu/sample/"                                "build/include"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "build/include"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "build/include"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend_new/op_proto/"                                "build/include"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend_new/cpukernel/impl/"                          "build/include"
-
-# AICPU migration
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "build/include_subdir"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "build/include_what_you_use"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/indent"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/ending_newline"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "runtime/explicit"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/braces"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/namespace"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/braces"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "build/include"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/end_of_line"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/casting"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "build/namespaces"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "runtime/references"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/multiline_comment"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/parens"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/alt_tokens"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/comments"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "runtime/string"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "runtime/arrays"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "legal/copyright"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/inheritance"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "runtime/int"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/empty_if_body"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/newline"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/operators"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/comma"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "runtime/indentation_namespace"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/blank_line"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/line_length"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "whitespace/semicolon"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/" "readability/nolint"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/expand_dims_kernels.h" "runtime/explicit"
-"mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/expand_dims_kernels.h" "build/include_order"

.jenkins/check/config/filter_linklint.txt

@@ -50,8 +50,8 @@ https://github.com/siju-samuel/darknet/blob/master/
 https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu
 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu
 https://dl.google.com/dl/android/maven2/
-https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.9.0/MindInsight/any/mindinsight-1.9.0-py3-none-any.whl
-https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.9.0/MindSpore/cpu/x86_64/mindspore-1.9.0-cp37-cp37m-linux_x86_64.whl
-https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.9.0/Serving/x86_64/mindspore_serving-1.9.0-cp37-cp37m-linux_x86_64.whl
-https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.9.0/MindSpore/gpu/x86_64/cuda-10.1/mindspore_gpu-1.9.0-cp37-cp37m-linux_x86_64.whl
-https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.9.0/MindSpore/gpu/x86_64/cuda-11.1/mindspore_gpu-1.9.0-cp37-cp37m-linux_x86_64.whl
+https://ms-release.obs.cn-north-4.myhuaweicloud.com/2.0.0a0/MindSpore/unified/x86_64/mindspore-2.0.0a0-cp37-cp37m-linux_x86_64.whl \
+https://ms-release.obs.cn-north-4.myhuaweicloud.com/2.0.0a0/MindInsight/any/mindinsight-2.0.0-py3-none-any.whl \
+https://ms-release.obs.cn-north-4.myhuaweicloud.com/2.0.0a0/Serving/x86_64/mindspore_serving-2.0.0-cp37-cp37m-linux_x86_64.whl
+https://mindspore.cn*/r2.0.0-alpha/*
+https://www.mindspore.cn*/r2.0.0-alpha/*

.jenkins/check/config/filter_pylint.txt

@@ -12,17 +12,14 @@
 "mindspore/mindspore/python/mindspore/_check_version.py"                                                                 "unused-import"
 "mindspore/mindspore/python/mindspore/_check_version.py"                                                                 "broad-except"
 "mindspore/mindspore/python/mindspore/common/api.py"                                                                     "protected-access"
-"mindspore/mindspore/python/mindspore/common/api.py"                                                                     "not-callable"
 "mindspore/mindspore/python/mindspore/common/parameter.py"                                                               "protected-access"
 "mindspore/mindspore/python/mindspore/common/parameter.py"                                                               "no-value-for-parameter"
 "mindspore/mindspore/python/mindspore/common/hook_handle.py"                                                             "protected-access"
 "mindspore/mindspore/python/mindspore/common/dtype.py"                                                                   "undefined-all-variable"
 "mindspore/mindspore/python/mindspore/context.py"                                                                        "protected-access"
-"mindspore/mindspore/python/mindspore/ops/function/clip_func.py"                                                         "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/operations"                                                                    "super-init-not-called"
 "mindspore/mindspore/python/mindspore/ops/operations/_quant_ops.py"                                                      "unused-import"
 "mindspore/mindspore/python/mindspore/ops/operations/nn_ops.py"                                                          "redefined-builtin"
-"mindspore/mindspore/python/mindspore/ops/operations/array_ops.py"                                                       "missing-docstring"
 "mindspore/mindspore/python/mindspore/ops/operations/_inner_ops.py"                                                      "dangerous-default-value"
 "mindspore/mindspore/python/mindspore/ops/operations/_thor_ops.py"                                                       "dangerous-default-value"
 "mindspore/mindspore/python/mindspore/ops/operations/_thor_ops.py"                                                       "redefined-outer-name"
@@ -61,7 +58,6 @@
 "mindspore/mindspore/python/mindspore/ops/function/__init__.py"                                                          "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/function/array_func.py"                                                        "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/function/array_func.py"                                                        "redefined-outer-name"
-"mindspore/mindspore/python/mindspore/ops/function/clip_func.py"                                                         "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/function/math_func.py"                                                         "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/functional.py"                                                                 "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/functional.py"                                                                 "wildcard-import"
@@ -69,15 +65,9 @@
 "mindspore/mindspore/python/mindspore/_extends/parse/standard_method.py"                                                 "redefined-builtin"
 "mindspore/mindspore/python/mindspore/_extends/parse/standard_method.py"                                                 "protected-access"
 "mindspore/mindspore/python/mindspore/_extends/parse/standard_method.py"                                                 "len-as-condition"
-"mindspore/mindspore/python/mindspore/_extends/parse/standard_method.py"                                                 "redefined-outer-name"
 "mindspore/mindspore/python/mindspore/common/tensor.py"                                                                  "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/function/array_func.py"                                                        "redefined-builtin"
 "mindspore/mindspore/python/mindspore/ops/operations/array_ops.py"                                                       "redefined-builtin"
-"mindspore/mindspore/python/mindspore/ops/_grad_experimental/grad_sparse_ops.py"                                         "unused-variable"
-"mindspore/mindspore/python/mindspore/ops/operations/_inner_ops.py"                                                      "not-callable"
-"mindspore/mindspore/python/mindspore/hypercomplex"                                                                      "useless-return"
-"mindspore/mindspore/python"                                                                                             "redefined-builtin"
-"mindspore/mindspore/python/mindspore/ops/function/array_func.py"                                                        "unidiomatic-typecheck"
 
 # MindData
 "mindspore/mindspore/python/mindspore/dataset/__init__.py"                                                               "redefined-builtin"
@@ -93,7 +83,6 @@
 "mindspore/tests/vm_impl/array_ops_vm_impl.py"                                                          "unused-variable"
 "mindspore/tests/ut/cpp/python_input/gtest_input/pipeline/parse/parse_compile.py"                       "unused-import"
 "mindspore/tests/ut/cpp/python_input/gtest_input/pipeline/infer/primitive_test.py"                      "super-init-not-called"
-"mindspore/tests/ut/cpp/python_input/gtest_input/mindir/mindir_test.py"                                 "unused-variable"
 "mindspore/tests/ut/cpp/python_input/gtest_input/pipeline/parse/parse_primitive.py"                     "super-init-not-called"
 "mindspore/tests/ut/cpp/python_input/gtest_input/pre_activate"                                          "unused-variable"
 "mindspore/tests/ut/cpp/python_input/gtest_input/tbe"                                                   "unused-variable"
@@ -133,8 +122,7 @@
 "mindspore/tests/ut/python/nn/test_cell_method_attribute.py"                                            "no-self-argument"
 "mindspore/tests/ut/python/onnx/test_onnx.py"                                                           "unused-variable"
 "mindspore/tests/ut/python/ops"                                                                         "super-init-not-called"
-"mindspore/tests/st/ops/test_tensor_slice.py"                                                           "redefined-outer-name"
-"mindspore/tests/st/ops/test_tensor_slice.py"                                                           "useless-super-delegation"
+"mindspore/tests/ut/python/ops/test_tensor_slice.py"                                                    "redefined-outer-name"
 "mindspore/tests/ut/python/optimizer/test_debug_location.py"                                            "super-init-not-called"
 "mindspore/tests/ut/python/parallel/"                                                                   "protected-access"
 "mindspore/tests/ut/python/parameter_feature/test_var_grad.py"                                          "bad-super-call"
@@ -182,12 +170,6 @@
 "mindspore/tests/ut/python/mindir/test_mindir_export.py"                                                "no-else-return"
 "mindspore/tests/"                                                                                      "c-extension-no-member"
 "mindspore/tests/st/parameter/test_parameter_celllist.py"                                               "protected-access"
-"mindspore/tests/ut/python/rewrite/test_cellcontainer.py"                                               "protected-access"
-"mindspore/tests/st/ms_adapter/_register/utils.py"                                                      "protected-access"
-"mindspore/tests/st/ms_adapter/_register/utils.py"                                                      "unused-variable"
-"mindspore/tests/st/ms_adapter/test_ms_adapter_base.py"                                                 "unidiomatic-typecheck"
-"mindspore/tests/st/ms_adapter/test_operator.py"                                                        "unidiomatic-typecheck"
-"mindspore/tests/st/ms_adapter/test_python_builtins.py"                                                 "unidiomatic-typecheck"
 
 #MindSpore Lite
 "mindspore/mindspore/ccsrc/plugin/device/cpu/kernel/nnacl/experimental/HPC-generator/generator.py"                                         "redefined-builtin"
@@ -199,10 +181,3 @@
 "mindspore/mindspore/lite/python/api/tensor.py"                                                          "protected-access"
 "mindspore/mindspore/lite/test"                                                                          "missing-docstring"
 "mindspore/mindspore/lite/test"                                                                          "unused-variable"
-# ascend samples
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "wrong-import-order"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "wrong-import-order"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "bad-whitespace"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "bad-whitespace"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_dsl/sample/"                              "bad-continuation"
-"mindspore/mindspore/lite/tools/kernel_builder/ascend/tbe_tik/sample/"                              "bad-continuation"

.jenkins/check/config/whitelizard.txt

@@ -5,12 +5,11 @@
 #
 mindspore/mindspore/core/mindrt/src/thread/actor_threadpool.cc:mindspore::ActorWorker::RunWithSpin
 mindspore/mindspore/lite/src/common/ops/primitive_c.cc:mindspore::lite::PrimitiveC::Create
-mindspore/mindspore/lite/src/extendrt/convert/runtime_convert.cc:RuntimeConvert
 mindspore/mindspore/ccsrc/minddata/dataset/engine/datasetops/source/csv_op.cc:mindspore::dataset::CsvOp::CsvParser::InitCsvParser
 mindspore/mindspore/lite/tools/converter/graphdef_transform.cc:mindspore::lite::GraphDefTransform::Transform
 mindspore/mindspore/lite/providers/nnie_proposal/src/proposal.cc:mindspore::proposal::Rpn
-mindspore/mindspore/core/abstract/ops/primitive_infer_map.cc:mindspore::abstract::GetPrimitiveInferMap
-mindspore/mindspore/core/abstract/ops/primitive_infer_map.cc:mindspore::abstract::GetInferDependsMap
+mindspore/mindspore/core/abstract/ops/primitive_infer_map.cc:mindspore::abstract::GetPrimitiveToEvalImplMap
+mindspore/mindspore/core/abstract/ops/primitive_infer_map.cc:mindspore::abstract::GetHostDependsMap
 mindspore/mindspore/core/ir/tensor.cc:mindspore::tensor::MakeTensorData
 mindspore/mindspore/ccsrc/kernel/common_utils.cc:mindspore::kernel::UnitSizeInBytes
 mindspore/mindspore/ccsrc/frontend/optimizer/irpass.cc:mindspore::opt::irpass::OptimizeIRPassLib::OptimizeIRPassLib
@@ -18,7 +17,7 @@ mindspore/mindspore/ccsrc/frontend/parallel/ops_info/gather_v2_p_info.cc:mindspo
 mindspore/mindspore/ccsrc/plugin/device/gpu/hal/device/gpu_kernel_runtime.cc:mindspore::device::gpu::GPUKernelRuntime::LaunchKernelDynamic
 mindspore/mindspore/ccsrc/pipeline/jit/init.cc:PYBIND11_MODULE
 mindspore/mindspore/ccsrc/pipeline/jit/parse/resolve.cc:mindspore::parse::ResolveObjectToNode
-mindspore/mindspore/ccsrc/include/common/utils/python_utils.h:mindspore::HandleExceptionRethrow
+mindspore/mindspore/ccsrc/pipeline/jit/pipeline.cc:mindspore::pipeline::GraphExecutorPy::Compile
 mindspore/mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc:mindspore::abstract::ConvertAbstractToPython
 mindspore/mindspore/ccsrc/pybind_api/ir/log_adapter_py.h:mindspore::PyExceptionInitializer::HandleExceptionPy
 mindspore/mindspore/ccsrc/plugin/device/gpu/kernel/math/unary_op_gpu_kernel.h:mindspore::kernel::UnaryOpGpuKernel::Launch
@@ -29,14 +28,6 @@ mindspore/model_zoo/official/recommend/wide_and_deep_multitable/src/wide_and_dee
 mindspore/mindspore/ccsrc/pipeline/jit/resource.cc:mindspore::pipeline::GetMethodMap
 mindspore/mindspore/python/mindspore/ops/operations/array_ops.py:_compute_slicing_shape
 mindspore/mindspore/python/mindspore/ops/function/array_func.py:scatter_nd
-mindspore/mindspore/python/mindspore/ops/function/nn_func.py:interpolate
-mindspore/mindspore/python/mindspore/ops/function/nn_func.py:max_unpool3d
-mindspore/mindspore/python/mindspore/ops/function/nn_func.py:max_unpool2d
-mindspore/mindspore/python/mindspore/ops/function/nn_func.py:max_unpool1d
-mindspore/mindspore/python/mindspore/ops/function/nn_func.py:pad
-mindspore/mindspore/python/mindspore/ops/function/math_func.py:cov
-mindspore/mindspore/python/mindspore/ops/function/math_func.py:norm
-mindspore/mindspore/python/mindspore/ops/function/math_func.py:einsum
 mindspore/mindspore/python/mindspore/context.py:set_auto_parallel_context
 mindspore/mindspore/python/mindspore/common/tensor.py:__init__
 mindspore/mindspore/python/mindspore/common/parameter.py:set_data
@@ -271,101 +262,5 @@ mindspore/mindspore/ccsrc/pybind_api/ir/tensor_py.cc:mindspore::tensor::RegMetaT
 mindspore/mindspore/ccsrc/plugin/device/cpu/kernel/eltwise_grad_cpu_kernel.cc:mindspore::kernel::EltWiseGradCpuTypeFunc<T>::InitFunc
 mindspore/mindspore/lite/tools/converter/quantizer/weight_quantizer.cc:mindspore::lite::quant::WeightQuantizer::LinearQuant
 mindspore/mindspore/python/mindspore/ops/function/nn_func.py:conv3d
+mindspore/mindspore/python/mindspore/ops/function/nn_func.py:max_unpool3d
 mindspore/mindspore/ccsrc/plugin/device/cpu/kernel/nnacl/fp32/matmul_avx512_mask_fp32.c:GemmRowxColMaskKernelFp32
-mindspore/mindspore/ccsrc/plugin/device/cpu/kernel/crop_and_resize_cpu_kernel.cc:mindspore::kernel::CropAndResizeCpuKernelMod::LaunchKernel
-mindspore/mindspore/ccsrc/plugin/device/cpu/hal/device/cpu_device_address.cc:mindspore::device::cpu::CPUDeviceAddress::SyncHostToDevice
-
-# AICPU migration
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/mediangrad.cc:aicpu::MedianGradCpuKernel::MedianGradCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/adaptive_max_pool_3d.cc:aicpu::AdaptiveMaxPool3dCpuKernel::AdaptiveMaxPool3dCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/adaptive_max_pool_3d_grad.cc:aicpu::AdaptiveMaxPool3dGradCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/avgpoolgrad.cc:aicpu::ComputeAvgPoolGradImpl
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/batch_norm_grad_grad.cc:aicpu::BatchNormGradGradCpuKernel::TrainingComputeNHWC
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/batch_norm_grad_grad.cc:aicpu::BatchNormGradGradCpuKernel::TrainingComputeNCHW
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/avgpool.cc:aicpu::AvgPoolCpuKernel::RealCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/bias_add.cc:aicpu::BiasAddCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/resize_bicubic.cc:aicpu::interpolate_with_caching                      
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/multinomial.cc:aicpu::Generate     
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/matrix_set_diag_v3.cc:aicpu::MatrixSetDiagV3CpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/max_unpool_2d.cc:aicpu::MaxUnpool2DCpuKernel::MaxUnpool2DCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparseaddmm.cc:aicpu::SparseAddmmCpuKernel::SparseAddmmCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/triplet_margin_loss.cc:aicpu::TripletMarginLossCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/triplet_margin_loss.cc:aicpu::TripletMarginLossCpuKernel::TripletMarginLossComputeRealType
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/triplet_margin_loss.cc:aicpu::TripletMarginLossCpuKernel::TripletMarginLossComputeComplexType
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/triplet_margin_loss.cc:aicpu::TripletMarginLossCpuKernel::TripletMarginLossComputeRealTypeFloat16
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_matrix_transpose.cc:aicpu::SparseMatrixTransposeCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_reshape.cc:aicpu::SparseReshapeCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/optimizer/mindir/aicpu_lib_select.cc:mindspore::opt::AICpuLibSelectPass::Process
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/matrix_solve_ls.cc:aicpu::MatrixSolveLsCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/tensor_scatter_update.cc:aicpu::TensorScatterUpdateCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/scatter_nd.cc:aicpu::ScatterNdCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/col2im.cc:aicpu::Col2imCpuKernel::Col2imParamCheck
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/csr_sparse_matrix_to_sparse_tensor.cc:aicpu::CSRSparseMatrixToSparseTensorCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/cumprod.cc:aicpu::CumprodCpuKernel::CumprodCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/combined_non_max_suppression.cc:aicpu::CombinedNonMaxSuppressionCpuKernel::CombinedNonMaxSuppressionCheck
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/scatter_nd_update.cc:aicpu::ScatterNdUpdateCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/ragged_tensor_to_sparse.cc:aicpu::RaggedTensorToSparseCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/max_unpool_3d_grad.cc:aicpu::MaxUnpool3DGradCpuKernel::MaxUnpool3DGradCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/ragged_tensor_to_tensor.cc:aicpu::RaggedTensorToTensorCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sample_distorted_bounding_box_ext2.cc:aicpu::SDBBExt2CpuKernel::GenerateRandomCrop
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sample_distorted_bounding_box_ext2.cc:aicpu::SDBBExt2CpuKernel::SDBBExt2Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/scatter_nd.cc:aicpu::ScatterNdCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maxpool.cc:aicpu::SpacialMaxPool
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/reduce_mean.cc:aicpu::ReduceMeanCpuKernel::ReduceMeanCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/reduce_mean.cc:aicpu::ReduceMeanCpuKernel::ReduceMeanCompute_Complex
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_mean.cc:aicpu::SegmentMeanCpuKernel::SegmentMeanCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_mean.cc:aicpu::SegmentMeanCpuKernel::SegmentMeanCompute_Complex
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/max_unpool_3d.cc:aicpu::MaxUnpool3DCpuKernel::MaxUnpool3DCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/slice.cc:aicpu::SliceCpuKernel::SliceCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_prod.cc:aicpu::SegmentProdCpuKernel::SegmentProdCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_prod.cc:aicpu::SegmentProdCpuKernel::SegmentProdCompute_Complex
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maxpool_grad.cc:aicpu::SpatialMaxPoolWithArgMaxHelper
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/reduce_prod.cc:aicpu::ReduceProdCpuKernel::ReduceProdCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/reduce_prod.cc:aicpu::ReduceProdCpuKernel::ReduceProdCompute_Complex
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/parameterized_truncated_normal.cc:aicpu::Generate
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/multi_margin_loss.cc:aicpu::MultiMarginLossCpuKernel::MultiMarginLossCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/multi_margin_loss_grad.cc:aicpu::MultiMarginLossGradCpuKernel::MultiMarginLossGradComputeFP16
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/multi_margin_loss_grad.cc:aicpu::MultiMarginLossGradCpuKernel::MultiMarginLossGradCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/multi_margin_loss.cc:aicpu::MultiMarginLossCpuKernel::MultiMarginLossComputeFP16
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/matrix_band_part.cc:aicpu::MatrixBandPartCpuKernel::BandCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/minimum.cc:aicpu::MinimumCpuKernel::SpecialComputeSameShape
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/minimum.cc:aicpu::MinimumCpuKernel::SpecialComputeXOneElement
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/minimum.cc:aicpu::MinimumCpuKernel::SpecialComputeYOneElement
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/minimum.cc:aicpu::MinimumCpuKernel::BcastComputeMultiKernel
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/minimum.cc:aicpu::MinimumCpuKernel::BcastComputeOneKernel
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maximum.cc:aicpu::MaximumCpuKernel::SpecialComputeSameShape
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maximum.cc:aicpu::MaximumCpuKernel::SpecialComputeXOneElement
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maximum.cc:aicpu::MaximumCpuKernel::SpecialComputeYOneElement
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maximum.cc:aicpu::MaximumCpuKernel::BcastComputeMultiKernel
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/maximum.cc:aicpu::MaximumCpuKernel::BcastComputeOneKernel
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/lu_unpack.cc:aicpu::LuUnpackCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/optimizer/mindir/aicpu_lib_select.cc:mindspore::opt::AICpuLibSelectPass::Process
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/crop_and_resize_grad_boxes.cc:aicpu::CropAndResizeGradBoxesCpuKernel::GradOfBoxesCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/fractional_max_pool_grad.cc:aicpu::FractionalMaxPoolGradCpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/fractional_avg_pool_grad.cc:aicpu::FractionalAvgPoolGradCpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/fractional_max_pool.cc:aicpu::FractionalMaxPoolCpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/fractional_avg_pool.cc:aicpu::FractionalAvgPoolCpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/densetosparsesetoperation.cc:aicpu::DenseToSparseSetOperationCpuKernel::ComputeDenseToSparse
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_dense_cwise_utils.cc:aicpu::SparseDenseCwiseOpKernel<Op>::SparseDenseCwiseOpSpecialCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/resize_area.cc:aicpu::ResizeAreaCpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/trace_grad.cc:aicpu::TraceGradCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sspaddmm.cc:aicpu::SspaddmmCpuKernel::ValidParam
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_sum.cc:aicpu::SegmentSumCpuKernel::SegmentSumCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_min.cc:aicpu::SegmentMinCpuKernel::SegmentMinCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_tensor_dense_mat_mul.cc:aicpu::SparseTensorDenseMatMulCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_tensor_dense_mat_mul.cc:aicpu::SparseTensorDenseMatMulCpuKernel::regular_calculate
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sspaddmm.cc:aicpu::SspaddmmCpuKernel::ScalarSparseMul
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_tensor_dense_add.cc:aicpu::SparseTensorDenseAddCpuKernel::ValidateInputs
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_dense_cwise_utils.cc:aicpu::SparseDenseCwiseOpKernel<Op>::SparseDenseCwiseOpBcastCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_dense_cwise_utils.cc:aicpu::SparseDenseCwiseOpKernel<Op>::SparseDenseCwiseOpSpecialComputeComplex
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_dense_cwise_utils.cc:aicpu::SparseDenseCwiseOpKernel<Op>::SparseDenseCwiseOpBcastComputeComplex
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/resize_bicubic_grad.cc:aicpu::ResizeBicubicGrad
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/segment_max.cc:aicpu::SegmentMaxCpuKernel::SegmentMaxCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/extract_glimpse.cc:aicpu::ExtractGlimpseCpuKernel::Compute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/max_pool_3d_grad_with_argmax.cc:aicpu::MaxPool3DGradWithArgmaxCpuKernel::MaxPool3DGradWithArgmaxCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/matrix_power.cc:aicpu::MatrixPowerCpuKernel::ComputeKernel
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/max_unpool_2d_grad.cc:aicpu::MaxUnpool2DGradCpuKernel::MaxUnpool2DGradCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/max_pool_3d_with_argmax.cc:aicpu::MaxPool3DWithArgmaxCpuKernel::MaxPool3DWithArgmaxCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/layer_norm_grad_grad.cc:aicpu::LayerNormGradGradCpuKernel::LayerNormGradGradCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/batchmatmul.cc:aicpu::BatchMatMulCpuKernel::DoCompute
-mindspore/mindspore/ccsrc/plugin/device/ascend/kernel/aicpu/aicpu_ops/cpu_kernel/ms_kernel/sparse_to_dense.cc:aicpu::SparseToDenseCpuKernel::ValidParam

CMakeLists.txt

@@ -4,8 +4,8 @@ project(MindSpore)
 if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
     if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS 7.3.0)
         message(FATAL_ERROR "GCC version must be 7.3.0 and above, but found ${CMAKE_CXX_COMPILER_VERSION}")
-    elseif(CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 11.3.0)
-        message(WARNING "GCC version ${CMAKE_CXX_COMPILER_VERSION} is greater than 11.3.0, may cause unknown problems.")
+    elseif(CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 9.4.0)
+        message(WARNING "GCC version ${CMAKE_CXX_COMPILER_VERSION} is greater than 9.4.0, may cause unknown problems.")
     endif()
 endif()
 
@@ -110,17 +110,17 @@ include_directories(${PYTHON_INCLUDE_DIRS})
 set(MS_CCSRC_PATH ${CMAKE_SOURCE_DIR}/mindspore/ccsrc)
 set(MS_CCSRC_BUILD_PATH ${BUILD_PATH}/mindspore/mindspore/ccsrc)
 
+if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
+    include(${CMAKE_SOURCE_DIR}/cmake/dependency_graphengine.cmake)
+endif()
+
 if(NOT MSVC)
 set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fvisibility=hidden")
 endif()
 
 include(${CMAKE_SOURCE_DIR}/cmake/init.cmake)
+add_subdirectory(mindspore/ccsrc)
 add_subdirectory(mindspore/core)
-if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
-    include(${CMAKE_SOURCE_DIR}/cmake/dependency_graphengine.cmake)
-endif()
-
-add_subdirectory_with_faster_option(mindspore/ccsrc)
 
 if(ENABLE_TESTCASES OR ENABLE_CPP_ST)
     add_subdirectory(tests)
@@ -133,10 +133,7 @@ if(${VERSION_NUMBER} MATCHES ".*dev.*")
     message("building dev mode")
     set(BUILD_DEV_MODE ON)
 endif()
-
-if(ONLY_BUILD_DEVICE_PLUGINS)
-    include(cmake/package_plugin.cmake)
-elseif(MODE_ASCEND_ACL)
+if(MODE_ASCEND_ACL)
     include(cmake/package_tar.cmake)
 elseif(CMAKE_SYSTEM_NAME MATCHES "Windows")
     include(cmake/package_win.cmake)

MindSpore-Application-practice

@@ -1 +0,0 @@
-Subproject commit 93e111f4a8eb443fb1b4cd585434efd1ac3eb643

MindSpore-Data-preprocessing

@@ -1 +0,0 @@
-Subproject commit 1670edd027f7fa452aafee412112fc0a7ab0110b

MindSpore-Data-storage-kunpeng

@@ -1 +0,0 @@
-Subproject commit b84ec7df965622652d47b89f0666d0432a81fdb9

MindSpore-LeNet-jzx3

@@ -1 +0,0 @@
-Subproject commit 3aa87bf5e2a84f4e4fdbd581d5309e0b11e55045

MindSpore-Model-Development

@@ -1 +0,0 @@
-Subproject commit fc667cda70ce83f3bd02840795598e4d81ca6cd9

MindSpore-competition

@@ -1 +0,0 @@
-Subproject commit 3aa87bf5e2a84f4e4fdbd581d5309e0b11e55045

MindSpore-first-experience

@@ -1 +0,0 @@
-Subproject commit bdc42fc803d50a57d3a19da9dc7350ff747e8926

MindSpore-install

@@ -1 +0,0 @@
-Subproject commit 8657fa27f818403e98364cb711731e9686fc413a

Mindspore-Data-storage-use

@@ -1 +0,0 @@
-Subproject commit b84ec7df965622652d47b89f0666d0432a81fdb9

README.md

@@ -281,11 +281,10 @@ Project stable branches will be in one of the following states:
 
 | **Branch** | **Status**   | **Initial Release Date** | **Next Phase**                         | **EOL Date**|
 |------------|--------------|--------------------------|----------------------------------------|-------------|
-| **r1.10**  | Maintained   | 2023-02-02               | Unmaintained <br> 2024-02-02 estimated |             |
 | **r1.9**   | Maintained   | 2022-10-26               | Unmaintained <br> 2023-10-26 estimated |             |
 | **r1.8**   | Maintained   | 2022-07-29               | Unmaintained <br> 2023-07-29 estimated |             |
 | **r1.7**   | Maintained   | 2022-04-29               | Unmaintained <br> 2023-04-29 estimated |             |
-| **r1.6**   | End Of Life  | 2022-01-29               |                                        | 2023-01-29  |
+| **r1.6**   | Maintained   | 2022-01-29               | Unmaintained <br> 2023-01-29 estimated |             |
 | **r1.5**   | End Of Life  | 2021-10-15               |                                        | 2022-10-15  |
 | **r1.4**   | End Of Life  | 2021-08-15               |                                        | 2022-08-15  |
 | **r1.3**   | End Of Life  | 2021-07-15               |                                        | 2022-07-15  |

README_CN.md

@@ -274,11 +274,10 @@ MindSpore的版本分支有以下几种维护阶段：
 
 | **分支名** | **当前状态**  | **上线时间**          | **后续状态**                           | **EOL 日期**|
 |------------|--------------|----------------------|----------------------------------------|------------|
-| **r1.10**  | Maintained   | 2023-02-02           | Unmaintained <br> 2024-02-02 estimated |            |
 | **r1.9**   | Maintained   | 2022-10-26           | Unmaintained <br> 2023-10-26 estimated |            |
 | **r1.8**   | Maintained   | 2022-07-29           | Unmaintained <br> 2023-07-29 estimated |            |
 | **r1.7**   | Maintained   | 2022-04-29           | Unmaintained <br> 2023-04-29 estimated |            |
-| **r1.6**   | End Of Life  | 2022-01-29           |                                        | 2023-01-29 |
+| **r1.6**   | Maintained   | 2022-01-29           | Unmaintained <br> 2023-01-29 estimated |            |
 | **r1.5**   | End Of Life  | 2021-10-15           |                                        | 2022-10-15 |
 | **r1.4**   | End Of Life  | 2021-08-15           |                                        | 2022-08-15 |
 | **r1.3**   | End Of Life  | 2021-07-15           |                                        | 2022-07-15 |

RELEASE.md

@@ -8,13 +8,13 @@
 
 #### PyNative
 
-- The default mode of MindSpore is switched to PyNative. If you want to manually set the mode, please refer to [Computational Graph](https://www.mindspore.cn/tutorials/en/r2.0.0-alpha/advanced/compute_graph.html).
-- Support dynamic shape without padding, three networks are supported as demos: Transformer-GPU, YOLOV5-GPU, ASR-Ascend. Transformer-GPU and YOLOV5-GPU can be downloaded from [models](https://gitee.com/mindspore/models/tree/dynamic_shape). Only the following operators are available on Ascend backend：Add、Assign、BatchMatMul、BiasAdd、BiasAddGrad、Cast、Conv2D、Conv2DBackpropFilter、Conv2DBackpropInput、CTCLoss、Div、Dropout、DropoutDoMask、Equal、ExpandDims、Gather、GetNext、LayerNorm、LayerNormGrad、LessEqual、Load、Log、LogicalAnd、LogicalNot、LogicalOr、LogSoftmax、LogSoftmaxGrad、MatMul、Maximum、Mul、Neg、NotEqual、NPUAllocFloatStatus、NPUClearFloatStatus、OneHot、RealDiv、Reciprocal、ReduceMean、ReduceSum、ReLU、ReluGrad、Reshape、Select、Softmax、StridedSlice、Sub、Tile、Transpose、UnsortedSegmentSum、ZerosLike。The remaining operators have not been fully verified, please use them as appropriate.
+- The default mode of MindSpore is switched to PyNative. If you want to manually set the mode, please refer to https://www.mindspore.cn/tutorials/zh-CN/master/advanced/compute_graph.html.
+- Support dynamic shape without padding, three networks are supported as demos: Transformer-GPU, YOLOV5-GPU, ASR-Ascend. Transformer-GPU and YOLOV5-GPU can be downloaded from https://gitee.com/mindspore/models/tree/dynamic_shape. Only the following operators are available on Ascend backend：Add、Assign、BatchMatMul、BiasAdd、BiasAddGrad、Cast、Conv2D、Conv2DBackpropFilter、Conv2DBackpropInput、CTCLoss、Div、Dropout、DropoutDoMask、Equal、ExpandDims、Gather、GetNext、LayerNorm、LayerNormGrad、LessEqual、Load、Log、LogicalAnd、LogicalNot、LogicalOr、LogSoftmax、LogSoftmaxGrad、MatMul、Maximum、Mul、Neg、NotEqual、NPUAllocFloatStatus、NPUClearFloatStatus、OneHot、RealDiv、Reciprocal、ReduceMean、ReduceSum、ReLU、ReluGrad、Reshape、Select、Softmax、StridedSlice、Sub、Tile、Transpose、UnsortedSegmentSum、ZerosLike。The remaining operators have not been fully verified, please use them as appropriate.
 
 #### DataSet
 
 - The TFRecordDataset API can directly read TFRecord files compressed by GZIP or ZLIB.
-- The NumpySlicesDataset API can process data of different dimensions at the same time.
+- The NumpySliceDataset API can process data of different dimensions at the same time.
 - Optimize the structure of error log to display more clear call stack information for debugging.
 - Fixed `mindspore.dataset.config.set_seed` does not take effect for random seeds in distributed training scenarios.
 
@@ -28,7 +28,7 @@
 
   Scatter Operators:ScatterAdd,ScatterDiv,ScatterMax,ScatterMul,ScatterNdAdd,ScatterNdSub,ScatterNdUpdate,ScatterSub,TensorScatterAdd,TensorScatterDiv,TensorScatterMax,TensorScatterMax,TensorScatterMul,TensorScatterAdd,TensorScatterUpdate.
 
-- Add new apis `transform_checkpoints` and `transform_checkpoint_by_rank` to transfer the distributed checkpoint files by strategy files. Please refer to [Distributed Resilience Training and Inference](https://www.mindspore.cn/tutorials/experts/en/r2.0.0-alpha/parallel/resilience_train_and_predict.html)。
+- Add new apis `transform_checkpoints` and `transform_checkpoint_by_rank` to transfer the distributed checkpoint files by strategy files. Please refer to https://www.mindspore.cn/tutorials/experts/en/master/parallel/resilience_train_and_predict.html。
 
 ### API Change
 
@@ -102,7 +102,6 @@
 
 - The `mindspore.ms_function` interface is renamed to `mindspore.jit`, and `mindspore.ms_function` will be deprecated and removed in a future version.
 - The `mindspore.ms_class` interface is renamed to `mindspore.jit_class`, and `mindspore.ms_class` will be deprecated and removed in a future version.
-- The `mindspore.ops.ms_kernel` interface is renamed to `mindspore.ops.kernel`, and `mindspore.ops.ms_kernel` will be deprecated and removed in a future version.
 - The `mindspore.dataset.map` interface parameter `column_order` does not take effect, use`mindspore.dataset.project`.
 - The `mindspore.dataset.close_pool` and `mindspore.dataset.to_device` and `mindspore.dataset.set_dynamic_columns` are deprecated and removed in this version.
 
@@ -119,55 +118,6 @@ AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bing
 
 Contributions of any kind are welcome!
 
-## MindSpore 1.10.1 Release Notes
-
-### Bug fixes
-
-- Fixed the issue that the specified axis is not considered in logsumexp anti-overflow processing
-- Fixed the compilation dependency of proto file
-- Fixed the issue that the print operator printing result is not normal
-- Fixed the issue that the equal operator is out of range
-- Fixed the problem that when function wrapped by @jit，the cell id is not correct
-- Fixed the GNN scenario data type verification error
-- Fixed the problem that the dataset.map multi-process degenerates into threads
-
-### Contributors
-
-Thanks goes to these wonderful people:
-
-archer2049, caifubi, chenfei_mindspore, gaoshuanglong, Greatpan, guozhijian, huoxinyou, Kxiong, lanzhineng, lijunbin, liubuyu, liuchuting, luochao60, lyqlola, nomindcarry, TuDouNi, xiaotianci, xupan, yangshuo, yefeng, YingtongHu, yuchaojie, zhoufeng, ZPaC, 刘勇琪, 吕昱峰, 王禹程, 于振华.
-
-Contributions of any kind are welcome!
-
-## MindSpore 1.10.0 Release Notes
-
-### Major Features and Improvements
-
-#### DataSet
-
-- [STABLE]The timeout waiting time is adjusted in data sinking mode. The default value is 600s after adjusted. This solves the isuses that the GetNext operator may timeout due to environment resource competition and large computing workload when training in sink mode.
-
-### Bug fixes
-
-- Fixed an issue where some Primitive operators in AMP cannot be instantiated in graph mode and the interface is unavailable.
-- Fixed an issue of DynamicRNN execution failure in LSTM network under the scenario of computational force segmentation on Ascend platform.
-- Fixed DEVICE_ID cannot be set by single card train scripts parameters in mobilenet, fasterrcnn, yolo, etc.
-
-### Contributors
-
-Thanks goes to these wonderful people:
-
-AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking, shu-kun-zhang.
-
-Contributions of any kind are welcome!
-
-## MindSpore Lite 1.10.0 Release Notes
-
-### Bug fixes
-
-- Fixed potential accuracy problem of arithmetic type CPU kernels at dynamical shape case.
-- Fixed the Incorrect Write Address of the Deconv Quantization Operator.
-
 ## MindSpore 1.9.0 Release Notes
 
 ### Major Features and Improvements
@@ -481,15 +431,7 @@ For examples:
 
 The API pages are aggregated to <https://www.mindspore.cn/docs/en/master/api_python/mindspore.html>.
 
-### Contributors
-
-Thanks goes to these wonderful people:
-
-AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking, shu-kun-zhang.
-
-Contributions of any kind are welcome!
-
-## MindSpore Lite 1.8.0 Release Notes
+## MindSpore Lite
 
 ### Major Features and Improvements
 
@@ -502,6 +444,14 @@ Contributions of any kind are welcome!
 
 - [STABLE] Support perlayer quantization, and built-in CLE to optimize perlayer quantization accuracy.
 
+### Contributors
+
+Thanks goes to these wonderful people:
+
+AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking, shu-kun-zhang.
+
+Contributions of any kind are welcome!
+
 ## MindSpore 1.7.0 Release Notes
 
 ### Major Features and Improvements
@@ -570,15 +520,7 @@ Contributions of any kind are welcome!
 - Deprecate `mindspore.SparseTensor` and use `mindspore.COOTensor` instead. ([!28505](https://gitee.com/mindspore/mindspore/pulls/28505))
 - Add Tensor init arg `internal` for internal use.
 
-### Contributors
-
-Thanks goes to these wonderful people:
-
-AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking.
-
-Contributions of any kind are welcome!
-
-## MindSpore Lite 1.7.0 Release Notes
+## MindSpore Lite
 
 ### Major Features and Improvements
 
@@ -587,6 +529,14 @@ Contributions of any kind are welcome!
 - [STABLE] Support post quantization to run dynamic quantization algorithm.
 - [BETA] Support post quantized model to run on NVIDIA GPU.
 
+## Contributors
+
+Thanks goes to these wonderful people:
+
+AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking.
+
+Contributions of any kind are welcome!
+
 # MindSpore 1.6.0
 
 ## MindSpore 1.6.0 Release Notes

RELEASE_CN.md

@@ -8,13 +8,13 @@
 
 #### PyNative
 
-- MindSpore默认模式切换成PyNative模式。需要手动设置模式可以参考文档[计算图](https://www.mindspore.cn/tutorials/zh-CN/r2.0.0-alpha/advanced/compute_graph.html)。
-- 完成动态shape执行方案重构，提升反向构图性能，支持非padding方案的动态shape网络编程，当前主要验证网络Transformer-GPU、YOLOV5-GPU、ASR-Ascend。从[models仓](https://gitee.com/mindspore/models/tree/dynamic_shape)获取Transformer-GPU和YOLOV5-GPU。Ascend后端受算子适配度限制，只支持下列算子：Add、Assign、BatchMatMul、BiasAdd、BiasAddGrad、Cast、Conv2D、Conv2DBackpropFilter、Conv2DBackpropInput、CTCLoss、Div、Dropout、DropoutDoMask、Equal、ExpandDims、Gather、GetNext、LayerNorm、LayerNormGrad、LessEqual、Load、Log、LogicalAnd、LogicalNot、LogicalOr、LogSoftmax、LogSoftmaxGrad、MatMul、Maximum、Mul、Neg、NotEqual、NPUAllocFloatStatus、NPUClearFloatStatus、OneHot、RealDiv、Reciprocal、ReduceMean、ReduceSum、ReLU、ReluGrad、Reshape、Select、Softmax、StridedSlice、Sub、Tile、Transpose、UnsortedSegmentSum、ZerosLike。其余算子未经过完整验证，请酌情使用。
+- MindSpore默认模式切换成PyNative模式。需要手动设置模式可以参考文档:https://www.mindspore.cn/tutorials/zh-CN/master/advanced/compute_graph.html
+- 完成动态shape执行方案重构，提升反向构图性能，支持非padding方案的动态shape网络编程，当前主要验证网络Transformer-GPU、YOLOV5-GPU、ASR-Ascend。Transformer-GPU和YOLOV5-GPU可以从以下链接获取：https://gitee.com/mindspore/models/tree/dynamic_shape 。Ascend后端受算子适配度限制，只支持下列算子：Add、Assign、BatchMatMul、BiasAdd、BiasAddGrad、Cast、Conv2D、Conv2DBackpropFilter、Conv2DBackpropInput、CTCLoss、Div、Dropout、DropoutDoMask、Equal、ExpandDims、Gather、GetNext、LayerNorm、LayerNormGrad、LessEqual、Load、Log、LogicalAnd、LogicalNot、LogicalOr、LogSoftmax、LogSoftmaxGrad、MatMul、Maximum、Mul、Neg、NotEqual、NPUAllocFloatStatus、NPUClearFloatStatus、OneHot、RealDiv、Reciprocal、ReduceMean、ReduceSum、ReLU、ReluGrad、Reshape、Select、Softmax、StridedSlice、Sub、Tile、Transpose、UnsortedSegmentSum、ZerosLike。其余算子未经过完整验证, 请酌情使用。
 
 #### DataSet
 
 - TFRecordDataset API支持直接读取通过GZIP或ZLIB压缩后的TFRecord文件。
-- NumpySlicesDataset API支持同时处理不同维度的数据。
+- NumpySliceDataset API支持同时处理不同维度的数据。
 - 优化错误日志信息的结构，展示更清晰的调用栈信息便于调试、定位问题。
 - 修复分布式训练场景下 `mindspore.dataset.config.set_seed` 对随机种子设置不生效的问题。
 
@@ -26,7 +26,7 @@
 
   Math类算子：SquaredDifference、 Erfinv、 MaskedFill、 SplitV、 Gamma、 KLDivLoss、 LinSpace。Scatter类算子：ScatterAdd、ScatterDiv、ScatterMax、ScatterMul、ScatterNdAdd、ScatterNdSub、ScatterNdUpdate、ScatterSub、TensorScatterAdd、TensorScatterDiv、TensorScatterMax、TensorScatterMax、TensorScatterMul、TensorScatterAdd、TensorScatterUpdate。
 
-- 增加`transform_checkpoints`和`transform_checkpoint_by_rank`接口。给定转换前后的策略文件，即可实现对分布式权重转换。详情请参考[分布式弹性训练与推理](https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/parallel/resilience_train_and_predict.html)。
+- 增加`transform_checkpoints`和`transform_checkpoint_by_rank`接口。给定转换前后的策略文件，即可实现对分布式权重转换。详情可以参考：https://www.mindspore.cn/tutorials/experts/zh-CN/master/parallel/resilience_train_and_predict.html 。
 
 ### API变更
 
@@ -91,8 +91,8 @@
 - [STABLE] `mindspore.ops.Trace` 新增算子原语。
 - [STABLE] `mindspore.ops.UpsampleNearest3D` 新增算子原语。
 - [STABLE] `mindspore.ops.UpsampleTrilinear3D` 新增算子原语。
-- [STABLE] `mindspore.parallel.transform_checkpoints` 新增分布式权重转换接口。
-- [STABLE] `mindspore.parallel.transform_checkpoint_by_rank` 新增分布式权重转换接口。
+- [STABLE]`mindspore.parallel.transform_checkpoints` 新增分布式权重转换接口。
+- [STABLE]`mindspore.parallel.transform_checkpoint_by_rank` 新增分布式权重转换接口。
 
 #### 非兼容性变更
 
@@ -100,7 +100,6 @@
 
 - `mindspore.ms_function`接口名替换为`mindspore.jit`，`mindspore.ms_function` 将在未来版本中弃用并删除。
 - `mindspore.ms_class`接口名替换为`mindspore.jit_class`，`mindspore.ms_class` 将在未来版本中弃用并删除。
-- `mindspore.ops.ms_kernel`接口名替换为`mindspore.ops.kernel`，`mindspore.ops.ms_kernel` 将在未来版本中弃用并删除。
 - `mindspore.dataset.map`接口参数 `column_order` 不再生效，使用`mindspore.dataset.project`替换。
 - `mindspore.dataset.close_pool`、`mindspore.dataset.to_device`、`mindspore.dataset.set_dynamic_columns` 接口在之前版本已废弃，当前版本正式删除。
 
@@ -117,55 +116,6 @@ AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bing
 
 欢迎以任何形式对项目提供贡献！
 
-## MindSpore 1.10.1 Release Notes
-
-### 问题修复
-
-- 修复logsumexp防溢出处理中未考虑指定axis的问题
-- 修复proto文件的编译依赖问题
-- 修复print算子打印结果不正常的问题
-- 修复equal算子越界问题
-- 修复函数被@jit修饰后，导致的cell_id解析不正确的问题
-- 修复GNN场景数据类型校验错误
-- 修复Dataset map多进程退化成线程的问题
-
-### 贡献者
-
-感谢以下人员做出的贡献:
-
-archer2049, caifubi, chenfei_mindspore, gaoshuanglong, Greatpan, guozhijian, huoxinyou, Kxiong, lanzhineng, lijunbin, liubuyu, liuchuting, luochao60, lyqlola, nomindcarry, TuDouNi, xiaotianci, xupan, yangshuo, yefeng, YingtongHu, yuchaojie, zhoufeng, ZPaC, 刘勇琪, 吕昱峰, 王禹程, 于振华.
-
-欢迎以任何形式对项目提供贡献！
-
-## MindSpore 1.10.0 Release Notes
-
-### 主要特性和增强
-
-#### DataSet
-
-- [STABLE]下沉模式超时等待时间调整，默认调整到600s，以解决数据下沉模式时因环境资源竞争、计算量大等因素容易导致GetNext算子等待超时的问题。
-
-### Bug fixes
-
-- 修复AMP中部分Primitive算子无法在图模式下实例化导致接口不可用的问题。
-- 修复昇腾平台算力切分场景下LSTM网络中DynamicRNN算子执行失败的问题。
-- 修复mobilenet, fasterrcnn, yolo等网络单卡训练脚本DEVICE_ID在启动脚本中写死的问题。
-
-### 贡献者
-
-感谢以下人员做出的贡献:
-
-AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking, shu-kun-zhang.
-
-欢迎以任何形式对项目提供贡献！
-
-## MindSpore Lite 1.10.0 Release Notes
-
-### Bug fixes
-
-- 修复Arithmetic类CPU算子动态shape场景下可能的计算精度问题。
-- 修复Deconv int8量化算子重量化写入地址错误问题。
-
 ## MindSpore 1.9.0 Release Notes
 
 ### 主要特性和增强
@@ -479,15 +429,7 @@ mindspore.context、mindspore.parallel、mindspore.profiler、mindspore.train模
 
 API页面统一汇总至：<https://www.mindspore.cn/docs/zh-CN/master/api_python/mindspore.html>。
 
-### 贡献者
-
-感谢以下人员做出的贡献：
-
-AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking, shu-kun-zhang.
-
-欢迎以任何形式对项目提供贡献！
-
-## MindSpore Lite 1.8.0 Release Notes
+## MindSpore Lite
 
 ### 主要特性和增强
 
@@ -500,6 +442,14 @@ AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bing
 
 - [STABLE] 后量化支持PerLayer量化，同时内置CLE算法优化精度。
 
+### 贡献者
+
+感谢以下人员做出的贡献：
+
+AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking, shu-kun-zhang.
+
+欢迎以任何形式对项目提供贡献！
+
 ## MindSpore 1.7.0 Release Notes
 
 ### 主要特性和增强
@@ -568,15 +518,7 @@ AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bing
 - `mindspore.SparseTensor`接口废弃使用，对应新接口为`mindspore.COOTensor`。 ([!28505](https://gitee.com/mindspore/mindspore/pulls/28505))
 - Tensor新增一个入参`internal`，作为框架内部使用。
 
-### 贡献者
-
-感谢以下人员做出的贡献:
-
-AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking.
-
-欢迎以任何形式对项目提供贡献！
-
-## MindSpore Lite 1.7.0 Release Notes
+## MindSpore Lite
 
 ### 主要特性和增强
 
@@ -584,3 +526,11 @@ AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bing
 
 - [STABLE] 后量化支持动态量化算法。
 - [BETA] 后量化模型支持在英伟达GPU上执行推理。
+
+## 贡献者
+
+感谢以下人员做出的贡献:
+
+AGroupofProbiotocs, anzhengqi, askmiao, baihuawei, baiyangfan, bai-yangfan, bingyaweng, BowenK, buxue, caifubi, CaoJian, caojian05, caozhou, Cathy, changzherui, chenbo116, chenfei, chengxianbin, chenhaozhe, chenjianping, chenzomi, chenzupeng, chujinjin, cj, cjh9368, Corleone, damon0626, danish, Danish, davidmc, dayschan, doitH, dong-li001, fary86, fuzhiye, Gaoxiong, GAO_HYP_XYJ, gengdongjie, Gogery, gongdaguo, gray0v0, gukecai, guoqi, gzhcv, hangq, hanhuifeng2020, Harshvardhan, He, heleiwang, hesham, hexia, Hoai, HuangBingjian, huangdongrun, huanghui, huangxinjing, huqi, huzhifeng, hwjiaorui, Jiabin Liu, jianghui58, Jiaqi, jin-xiulang, jinyaohui, jjfeing, John, jonyguo, JulyAi, jzg, kai00, kingfo, kingxian, kpy, kswang, liuyongqi, laiyongqiang, leonwanghui, liangchenghui, liangzelang, lichen_101010, lichenever, lihongkang, lilei, limingqi107, ling, linqingke, Lin Xh, liubuyu, liuwenhao4, liuxiao78, liuxiao93, liuyang_655, liuzhongkai, Lixia, lixian, liyanliu, liyong, lizhenyu, luopengting, lvchangquan, lvliang, lz, maning202007, Margaret_wangrui, mengyuanli, Ming_blue, ms_yan, ougongchang, panfengfeng, panyifeng, Payne, Peilin, peixu_ren, Pengyongrong, qianlong, qianjiahong, r1chardf1d0, riemann_penn, rmdyh, Sheng, shenwei41, simson, Simson, Su, sunsuodong, tao_yunhao, tinazhang, VectorSL, , Wan, wandongdong, wangdongxu, wangmin,  wangyue01, wangzhe, wanyiming, Wei, wenchunjiang, wilfChen, WilliamLian, wsc, wudenggang, wukesong, wuweikang, wuxuejian, Xiao Tianci, Xiaoda, xiefangqi, xinyunfan, xuanyue, xuyongfei, yanghaitao, yanghaitao1, yanghaoran, YangLuo, yangruoqi713, yankai, yanzhenxiang2020, yao_yf, yepei6, yeyunpeng, Yi, yoni, yoonlee666, yuchaojie, yujianfeng, yuximiao, zengzitao, Zhang,  zhanghuiyao, zhanghui_china, zhangxinfeng3, zhangyihui, zhangz0911gm, zhanke, zhanyuan, zhaodezan, zhaojichen, zhaoting, zhaozhenlong, zhengjun10, zhiqwang, zhoufeng, zhousiyi, zhouyaqiang, zhouyifengCode, Zichun, Ziyan, zjun, ZPaC, wangfengwfwf, zymaa, gerayking.
+
+欢迎以任何形式对项目提供贡献！

Third_Party_Open_Source_Software_Notice

@@ -384,7 +384,7 @@ apply, that proxy's public statement of acceptance of any version is
 permanent authorization for you to choose that version for the
 Library.
 
-Software: Eigen 3.4.0
+Software: Eigen 3.3.7
 Copyright notice: 
 Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
 Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
@@ -705,7 +705,7 @@ Exhibit B - “Incompatible With Secondary Licenses” Notice
 This Source Code Form is “Incompatible With Secondary Licenses”, as defined by the Mozilla Public License, v. 2.0.
 
 
-Software: JSON for Modern C++ 3.10.1
+Software: JSON for Modern C++ 3.6.1
 Copyright notice: 
 Copyright 2015 Google Inc. All rights reserved.
 Copyright 2018 Google Inc. All rights reserved.
@@ -745,7 +745,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 THE SOFTWARE.
 
 
-Software: oneDNN 2.2
+Software: oneDNN 1.6
 Copyright (c) 2011, Intel Corporation All rights reserved.
 Copyright 2015, Google Inc.
 Copyright 2008, Google Inc.
@@ -1178,7 +1178,7 @@ FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
 ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
 DEALINGS IN THE SOFTWARE.
 
-Software: NCCL 2.7.6-1
+Software: NCCL 2.4.8-1
 Copyright (c) 2016-2019, NVIDIA CORPORATION. All rights reserved.
 Copyright (c) 2015-2019, NVIDIA CORPORATION. All rights reserved.
 Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
@@ -1222,7 +1222,7 @@ Copyright (c) 2015-2019, NVIDIA CORPORATION. All rights reserved.
  The U.S. Department of Energy funded the development of this software
  under subcontract 7078610 with Lawrence Berkeley National Laboratory.
 
-Software: OpenMPI 4.0.3
+Software: OpenMPI 3.1.5
 Copyright (c) 2015 Cisco Systems, Inc.  All rights reserved.
 $COPYRIGHT$
 Copyright (c) 2015      Los Alamos National Security, LLC. All rights
@@ -2437,7 +2437,7 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 
-Software: Scipy 1.5.4
+Software: Scipy 1.6.0
 Copyright notice: 
 Jamfile.v2: Copyright Daryle Walker, Hubert Holin, John Maddock 2006 - 2007
 Copyright 2002 Gary Strangman.  All rights reserved
@@ -3048,14 +3048,6 @@ Copyright (c) Facebook Inc. and Microsoft Corporation.
 License: MIT License
 Please see above.
 
-Software: onnxruntime 1.6.0
-Copyright notice: 
-Copyright (c) ONNX Project Contributors.
-Copyright (c) Facebook Inc. and Microsoft Corporation.
-
-License: MIT License
-Please see above.
-
 Software: flatbuffers 2.0.0
 Copyright notice: 
 Copyright (c) 2015 Google, Inc.
@@ -3365,7 +3357,7 @@ OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 Please also refer to the file CONTRIBUTING.md, which clarifies licensing of
 external contributions to this project including patches, pull requests, etc.
 
-Software: SQLite 3.36.0
+Software: SQLite 3.32.2
 Copyright notice:
 Copyright (c) 1991-2011 Unicode, Inc.
 Copyright 2008 D. Richard Hipp and Hipp, Wyrick & Company, Inc.
@@ -4235,7 +4227,7 @@ Software: tinyxml2 8.0.0
 Copyright 2011, John Resig.
 Copyright 2011, The Dojo Foundation.
 
-Software: icu 69.1
+Software: icu 67.1
 Copyright (C) 2000-2004, International Business Machines Corporation
 Copyright (C) 2002-2014, International Business Machines(C) Copyright IBM Corp. 1998-2011 - All Rights Reserved
 Copyright (C) 2003-2008, International Business Machines
@@ -4967,7 +4959,389 @@ Copyright 2015 gRPC authors.
 Copyright 2016 gRPC authors.
 Copyright 2020 The gRPC Authors
 
-Software: opencv 4.5.2
+Software: opencv 4.2.0
+Copyright notice:
+Copyright (C) 2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
+Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+Copyright (c) 2010, Google Inc. All rights reserved.
+Copyright 2013 Google Inc. All Rights Reserved.
+Copyright 2011 Google Inc. All Rights Reserved.
+Copyright 2015 Google Inc. All Rights Reserved.
+Copyright 2010 Google Inc. All Rights Reserved.
+Copyright 2012 Google Inc. All Rights Reserved.
+Copyright 2014 Google Inc. All Rights Reserved.
+Copyright 2017 Google Inc. All Rights Reserved.
+Copyright 2016 Google Inc. All Rights Reserved.
+Copyright 2018 Google Inc. All Rights Reserved.
+Copyright (c) 2015 The Regents of the University of California (Regents)
+Copyright (c) 2015, 2015 The Regents of the University of California (Regents)
+Copyright (C) 2000, Intel Corporation, all rights reserved.
+Copyright (C) 2016, Itseez, Inc, all rights reserved.
+Copyright (C) 2014, Itseez, Inc, all rights reserved.
+Copyright (C) 2008-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2018 Intel Corporation
+Copyright (C) 2014, Itseez Inc, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (c) 2013, Bo Li (prclibo@gmail.com), ETH Zurich
+Copyright (C) 2014, Samson Yilma (samsonyilma@yahoo.com), all rights reserved.
+Copyright (C) 2018, Intel Corporation, all rights reserved.
+Copyright 2017 Toby Collins
+Copyright (c) 2007, Miroslav Balda
+Copyright (C) 2015, Itseez Inc., all rights reserved.
+Copyright (C) 2009, Intel Corporation and others, all rights reserved.
+Copyright (C) 2019 Intel Corporation
+Copyright (C) 2018-2019 Intel Corporation
+Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2010-2012, MulticoreWare Inc., all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
+Copyright (C) 2014, Intel Corporation, all rights reserved.
+Copyright (C) 2014, Itseez, Inc., all rights reserved.
+Copyright (C) 2001 Fabrice Bellard
+Copyright (C) 1991, 1999 Free Software Foundation, Inc.
+Copyright (C) 2015, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2014-2015, NVIDIA Corporation, all rights reserved.
+Copyright 2012. All rights reserved.
+Copyright (c) Microsoft Open Technologies, Inc.
+Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
+Copyright (C) 2014, Itseez Inc., all rights reserved.
+Copyright (C) 2008-2013, Willow Garage Inc., all rights reserved.
+Copyright 2015-2017 Philippe Tillet
+Copyright (c) 2017, Intel Corporation
+Copyright (C) 2000-2018, Intel Corporation, all rights reserved.
+Copyright (c) 2011. Philipp Wagner <bytefish[at]gmx[dot]de>.
+Copyright (c) 2008 - 2012 The Khronos Group Inc.
+Copyright (C) 2016, Intel Corporation, all rights reserved.
+Copyright (C) 2015, Itseez, Inc., all rights reserved.
+Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
+Copyright (C) 2015, OpenCV Foundation, all rights reserved.
+Copyright (c) 2005-2014 Intel Corporation. All rights reserved.
+Copyright (c) 2011, Intel Corporation
+Copyright (C) 1989, 1991 Free Software Foundation, Inc.
+Copyright (c) 2008 - 2009 NVIDIA Corporation.  All rights reserved.
+Copyright (c) 2007-2009
+Copyright (c) 2014, 2015, The Regents of the University of California (Regents)
+Copyright (c) 2014, 2015, the respective contributors
+Copyright 2010 Argus Corp. All rights reserved.
+Copyright (c) 2015, Piotr Dobrowolski dobrypd[at]gmail[dot]com
+Copyright 2008, Google Inc.
+Copyright 2005, Google Inc.
+Copyright 2007, Google Inc.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2009-2010, Willow Garage Inc., all rights reserved.
+Copyright 2008 Google Inc.  All rights reserved.
+Copyright (C) 2017, Intel Corporation, all rights reserved.
+Copyright (C) 2018-2019, Intel Corporation, all rights reserved.
+Copyright (C) 2017-2019, Intel Corporation, all rights reserved.
+Copyright (C) 2008-2012, Willow Garage Inc., all rights reserved.
+Copyright( C) 2000, Intel Corporation, all rights reserved.
+Copyright (c) 2000-2003 Chih-Chung Chang and Chih-Jen Lin
+Copyright (C) 2016, Itseez Inc, all rights reserved.
+Copyright (C) 2018 Ya-Chiu Wu, all rights reserved.
+Copyright (C) 2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2010 The Android Open Source Project
+Copyright (C) 2016 The Android Open Source Project
+Copyright (c) 2010-2011, Ethan Rublee
+Copyright (c) 2011-2014, Andrey Kamaev
+Copyright (c) 2013 NVIDIA Corporation. All rights reserved.
+Copyright (c) 2014, The Regents of the University of California (Regents)
+Copyright (c) 2014, the respective contributors
+Copyright (c) 1988-1997 Sam Leffler
+Copyright (c) 1991-1997 Silicon Graphics, Inc.
+Copyright (c) 2009 Frank Warmerdam
+Copyright (c) 1991-1997 Sam Leffler
+Copyright (c) 1990-1997 Sam Leffler
+Copyright (C) 1990, 1995  Frank D. Cringle.
+Copyright (c) 1994-1997 Sam Leffler
+Copyright (c) 1994-1997 Silicon Graphics, Inc.
+Copyright (c) 1997 Greg Ward Larson
+Copyright (c) 1997 Silicon Graphics, Inc.
+Copyright (c) 2010, Andrey Kiselev <dron@ak4719.spb.edu>
+Copyright (c) Joris Van Damme <info@awaresystems.be>
+Copyright (c) AWare Systems <http:www.awaresystems.be/>
+Copyright (c) 1996-1997 Sam Leffler
+Copyright (c) 1996 Pixar
+Copyright (c) 1995-1997 Sam Leffler
+Copyright (c) 1995-1997 Silicon Graphics, Inc.
+Copyright (c) 1988-1996 Sam Leffler
+Copyright (c) 1991-1996 Silicon Graphics, Inc.
+Copyright (c) 1992-1997 Sam Leffler
+Copyright (c) 1992-1997 Silicon Graphics, Inc.
+Copyright (c) 2018, Mapbox
+Copyright (c) 2017, Planet Labs
+Copyright (C) 2014, Itseez Inc. See the license at http:opencv.org
+Copyright (c) 1995-2019 The PNG Reference Library Authors.
+Copyright (c) 2018-2019 Cosmin Truta.
+Copyright (c) 2000-2002, 2004, 2006-2018 Glenn Randers-Pehrson.
+Copyright (c) 1996-1997 Andreas Dilger.
+Copyright (c) 1995-1996 Guy Eric Schalnat, Group 42, Inc.
+Copyright (c) 2000-2002, 2004, 2006-2018 Glenn Randers-Pehrson, are
+Copyright (c) 1998-2000 Glenn Randers-Pehrson, are derived from
+Copyright (c) 1996-1997 Andreas Dilger, are derived from libpng-0.88,
+Copyright (c) 2018-2019 Cosmin Truta
+Copyright (c) 1998-2002,2004,2006-2018 Glenn Randers-Pehrson
+Copyright (c) 1996-1997 Andreas Dilger
+Copyright (c) 1998-2002,2004,2006-2016,2018 Glenn Randers-Pehrson
+Copyright (c) 2018 Cosmin Truta
+Copyright (c) 1998-2002,2004,2006-2013 Glenn Randers-Pehrson
+Copyright (c) 1998-2002,2004,2006-2017 Glenn Randers-Pehrson
+Copyright (c) 1998-2002,2004,2006-2013,2018 Glenn Randers-Pehrson
+Copyright (c) 1998-2002,2004,2006-2014,2016 Glenn Randers-Pehrson
+Copyright (c) 1998-2018 Glenn Randers-Pehrson
+Copyright (c) 1998-2002,2004,2006-2014,2016,2018 Glenn Randers-Pehrson
+Copyright 2008-2009  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
+Copyright 2008-2009  David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
+(C) Copyright Christopher Diggins 2005-2011
+(C) Copyright Pablo Aguilar 2005
+(C) Copyright Kevlin Henney 2001
+Copyright 2008-2011  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
+Copyright 2008-2011  David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
+Copyright (c) 2004, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2004-2012, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2002-2012, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2012, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2011-2012, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2006-2012, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2002, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2016-2017 Fabian David Tschopp, all rights reserved.
+Copyright (C) 2014, Intel, Inc., all rights reserved.
+Copyright 2015, Google Inc.
+Copyright 2014, Google Inc.  All rights reserved.
+Copyright 2012 Google Inc.  All rights reserved.
+Copyright 2013 Red Hat Inc.  All rights reserved.
+Copyright 2014 Bloomberg Finance LP. All rights reserved.
+Copyright 2015 Google Inc.  All rights reserved.
+Copyright 2014 Google Inc. All rights reserved.
+Copyright 2013 Google Inc.  All rights reserved.
+Copyright 2014 Google Inc.  All rights reserved.
+Copyright (c) 2006, Google Inc.
+Copyright 2005-2008 Google Inc. All Rights Reserved.
+Copyright 2005 Google Inc.
+Copyright (C) 2010-2012 Daniel Beer <dlbeer@gmail.com>
+Copyright (c) 2001-2003 Michael David Adams.
+Copyright (c) 2001-2006 Michael David Adams
+Copyright (c) 1999-2000 Image Power, Inc.
+Copyright (c) 1999-2000 The University of British Columbia
+Copyright (c) 2002-2003 Michael David Adams.
+Copyright (c) 2001-2002 Michael David Adams.
+Copyright (c) 1999-2000 Image Power, Inc. and the University of
+Copyright (c) 2004 Michael David Adams.
+Copyright (c) Microsoft Corporation. All rights reserved.
+Copyright (c) 2008-2013 The Khronos Group Inc.
+Copyright (c) 2016 Glenn Randers-Pehrson
+copyright or license text in that file.
+Copyright (C)2009-2019 D. R. Commander.  All Rights Reserved.
+Copyright (C)2015 Viktor Szathmáry.  All Rights Reserved.
+Copyright (C) 2008-2010, Willow Garage Inc., all rights reserved.
+Copyright (c) 2014-2016, Joseph Howse (Nummist Media Corporation Limited, Halifax, Nova Scotia, Canada). All rights reserved.
+Copyright (c) 2017, Puttemans Steven, Can Ergun and Toon Goedeme
+Copyright (c) 2015, Advanced Micro Devices, Inc.
+Copyright (c) 2008-2012 The Khronos Group Inc.
+Copyright (c) 2008-2009 The Khronos Group Inc.
+Copyright (c) 2008-2010 The Khronos Group Inc.
+Copyright (c) 2008-2015 The Khronos Group Inc.
+Copyright (c) 2006, Industrial Light & Magic, a division of Lucasfilm
+Copyright 2011, 2012, 2013, 2014, 2015, 2016, 2017 The Regents of the University of California.  All rights reserved.
+Copyright (c) 2014-2017 The Khronos Group Inc.
+Copyright (c) 2015-2018 The Khronos Group Inc.
+Copyright (c) 2002-2018, Industrial Light & Magic, a division of Lucas
+Copyright (c) Microsoft. All rights reserved.
+Copyright (c) Microsoft Corporation. All rights reserved
+Copyright (c) 2014,2016 Glenn Randers-Pehrson
+Copyright (c) 2017-2018 Arm Holdings. All rights reserved.
+Copyright (C) Microsoft Corporation. All rights reserved.
+Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2015-2016, Itseez Inc., all rights reserved.
+Copyright (c) 2017 Glenn Randers-Pehrson
+Copyright (c) 2016-2017 Glenn Randers-Pehrson
+Copyright (c) 2004, Hannes Kruppa and Bernt Schiele (ETH Zurich, Switzerland).
+Copyright (c) 2011, Modesto Castrillon-Santana (IUSIANI, Universidad de
+Copyright (C) 2014, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2012-2015, NVIDIA Corporation, all rights reserved.
+Copyright (c) 2006, 2008 Edward Rosten
+Copyright (C) 2012-2014, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2014-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2013-2015, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010  Elmar Mair
+Copyright (C) 2008, Willow Garage Inc., all rights reserved.
+Copyright (C) 2011  The Autonomous Systems Lab (ASL), ETH Zurich, Stefan Leutenegger, Simon Lynen and Margarita Chli.
+Copyright (c) 2009, Willow Garage, Inc.
+Copyright (C) 2009, Liu Liu All rights reserved.
+Copyright (c) 2017 Joseph Redmon
+Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
+Copyright (c) 2012-2014 Deepmind Technologies (Koray Kavukcuoglu)
+Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu)
+Copyright (c) 2011-2013 NYU (Clement Farabet)
+Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston)
+Copyright (c) 2006      Idiap Research Institute (Samy Bengio)
+Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz)
+Copyright (C) 1991-2012, Thomas G. Lane, Guido Vollbeding.
+Copyright (C) 1995-2012 Jean-loup Gailly and Mark Adler.
+Copyright (c) 2001-2003 Michael David Adams Entertainment Company Ltd. Portions contributed and copyright held by others as indicated. All rights reserved.
+Copyright (c) 2001 Fabrice Bellard
+Copyright (C) 2008-2013, Itseez Inc., all rights reserved.
+Copyright (C) 2013, Itseez Inc, all rights reserved.
+Copyright (c) 1999-2000, Image Power, Inc. and the University of
+Copyright (c) 2001-2004 Michael David Adams.
+Copyright (C) 2000-2019, Intel Corporation, all rights reserved.
+Copyright (C) 2019, Xperience AI, all rights reserved.
+Copyright (c) 2005-2012, Industrial Light & Magic, a division of Lucas
+Copyright (C) 2008, 2011, Nils Hasler, all rights reserved.
+Copyright (C) 2008, Nils Hasler, all rights reserved.
+Copyright (C) 2015, 2018, D. R. Commander.
+Copyright (C) 1994-1998, Thomas G. Lane.
+Copyright (C) 1994-1996, Thomas G. Lane.
+Copyright (C) 1994-1997, Thomas G. Lane.
+Copyright (C) 1991-1996, Thomas G. Lane.
+Copyright (C) 2009-2012, 2015, D. R. Commander.
+Copyright 2009 Pierre Ossman <ossman@cendio.se> for Cendio AB
+Copyright (C) 2014, MIPS Technologies, Inc., California.
+Copyright (C) 1999-2006, MIYASAKA Masaru.
+Copyright (C) 2011, 2014-2015, D. R. Commander.
+Copyright (C) 1991-1997, Thomas G. Lane.
+Copyright (C) 2009-2011, 2014-2016, 2018, D. R. Commander.
+Copyright (C) 2015, Matthieu Darbois.
+Copyright (C) 1997-1998, Thomas G. Lane, Todd Newman.
+Copyright (C) 2017, D. R. Commander.
+Copyright (C) 1991-1998, Thomas G. Lane.
+Copyright (C) 2010, D. R. Commander.
+Copyright (C) 2010, 2016, 2018, D. R. Commander.
+Copyright (C) 2009-2011, 2018, D. R. Commander.
+Copyright (C) 1995-1997, Thomas G. Lane.
+Copyright (C) 2011, 2015, 2018, D. R. Commander.
+Copyright (C) 2016, 2018, Matthieu Darbois.
+Copyright (C) 2015, D. R. Commander.
+Copyright (C) 1995-1998, Thomas G. Lane.
+Copyright (C) 2016, D. R. Commander.
+Copyright (C) 2010, 2015-2018, D. R. Commander.
+Copyright (C) 2015, Google, Inc.
+Copyright (C) 2015-2018, D. R. Commander.
+Copyright (C) 2013, 2016, D. R. Commander.
+Copyright (C) 2010, 2015-2016, D. R. Commander.
+Copyright (C) 2013, Linaro Limited.
+Copyright (C) 2014-2015, D. R. Commander.
+Copyright (C) 2009, 2011, 2015, D. R. Commander.
+Copyright (C) 2009, 2011-2012, 2014-2015, D. R. Commander.
+Copyright (C) 2010, 2015, D. R. Commander.
+Copyright (C) 2013, MIPS Technologies, Inc., California.
+Copyright (C) 2009-2011, 2016, 2018, D. R. Commander.
+Copyright (C) 2010-2011, 2015-2016, D. R. Commander.
+Copyright (C) 2010, 2016, D. R. Commander.
+Copyright (C) 2012, 2015, D. R. Commander.
+Copyright (C) 2009-2011, 2016, D. R. Commander.
+Copyright (C) 1991-1995, Thomas G. Lane.
+Copyright (C) 2009, 2011, 2014-2015, D. R. Commander.
+Copyright (C) 2014-2015, 2018, D. R. Commander.
+Copyright (C) 2011, 2015, D. R. Commander.
+Copyright (C) 2015-2016, 2018, D. R. Commander.
+Copyright (C) 2014, 2017, D. R. Commander.
+Copyright (C) 2014, D. R. Commander.
+Copyright (C) 1991-1994, Thomas G. Lane.
+Copyright (C) 1992-1996, Thomas G. Lane.
+Copyright (C) 2017-2018, D. R. Commander.
+Copyright (C) 1992-1997, Thomas G. Lane.
+Copyright (C) 2009, 2011, 2014-2015, 2018, D. R. Commander.
+Copyright (C) 2015-2016, D. R. Commander.
+Copyright (C) 2009-2011, 2013-2014, 2016-2017, D. R. Commander.
+Copyright (C) 2009, 2015, D. R. Commander.
+Copyright (C) 2009, 2014-2015, D. R. Commander.
+Copyright (C) 2011, 2014, D. R. Commander.
+Copyright (C) 2015-2016, 2018, Matthieu Darbois.
+Copyright (C) 2009-2011, 2014, D. R. Commander.
+Copyright (C) 2013, D. R. Commander.
+Copyright (C) 2010, 2012-2019, D. R. Commander.
+Copyright (C) 1995-2011, 2016 Mark Adler
+Copyright (C) 1995-2005, 2014, 2016 Jean-loup Gailly, Mark Adler
+Copyright (C) 1995-2006, 2010, 2011, 2012, 2016 Mark Adler
+Copyright (C) 1995-2017 Jean-loup Gailly and Mark Adler
+Copyright (C) 1995-2016 Jean-loup Gailly
+Copyright (C) 2004, 2010 Mark Adler
+Copyright (C) 2004, 2005, 2010, 2011, 2012, 2013, 2016 Mark Adler
+Copyright (C) 2004-2017 Mark Adler
+Copyright (C) 1995-2016 Mark Adler
+Copyright (C) 1995-2017 Mark Adler
+Copyright (C) 1995-2003, 2010 Mark Adler
+Copyright (C) 1995-2005, 2010 Mark Adler(C) 1995-2017 Jean-loup Gailly and Mark Adler
+Copyright (C) 1995-2017 Jean-loup Gailly
+Copyright (C) 1995-2003, 2010, 2014, 2016 Jean-loup Gailly, Mark Adler
+Copyright (C) 1995-2016 Jean-loup Gailly, Mark Adler
+Copyright (C) 2013, NVIDIA Corporation, all rights reserved.
+Copyright (c) 2009-2014 DreamWorks Animation LLC.
+Copyright (c) 2007, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2006, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2009, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2003, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2012, Weta Digital Ltd
+Copyright (c) 2011, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2013, Industrial Light & Magic, a division of Lucas
+Copyright (c) 2007, Weta Digital Ltd(c) 2012 Weta Digital Ltd
+Copyright (c) 2012, Autodesk, Inc.
+Copyright (c) 2004, Pixar Animation Studios
+Copyright (c) 2004, Industrial Light & Magic, a division of Lucasfilm
+Copyright (c) 2005, Industrial Light & Magic, a division of Lucas
+Copyright (C) 2000-2008, 2018, Intel Corporation, all rights reserved.
+Copyright (C) 1998 Yossi Rubner
+Copyright (C) 2009-2012, Willow Garage Inc., all rights reserved.
+Copyright (C) 2006 Simon Perreault
+Copyright (C) 2013, Ovidiu Parvu, all rights reserved.
+Copyright (c) 2008-2011, William Lucas
+Copyright (C) 2000-2008, 2017, Intel Corporation, all rights reserved.
+Copyright (C) 2019, Intel Corporation, all rights reserved.
+Copyright (C) 2000-2008,2019 Intel Corporation, all rights reserved.
+Copyright (c) 2007-2008 Intel Corporation. All Rights Reserved.
+Copyright (c) 2008, Industrial Light & Magic, a division of Lucas
+Copyright (C) 1991-2018, Thomas G. Lane, Guido Vollbeding.
+
+License: 3-clause BSD License
+By downloading, copying, installing or using the software you agree to this license.
+If you do not agree to this license, do not download, install,
+copy or use the software.
+
+
+                          License Agreement
+               For Open Source Computer Vision Library
+                       (3-clause BSD License)
+
+Copyright (C) 2000-2019, Intel Corporation, all rights reserved.
+Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
+Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
+Copyright (C) 2015-2016, Itseez Inc., all rights reserved.
+Copyright (C) 2019, Xperience AI, all rights reserved.
+Third party copyrights are property of their respective owners.
+
+Redistribution and use in source and binary forms, with or without modification,
+are permitted provided that the following conditions are met:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions in binary form must reproduce the above copyright notice,
+    this list of conditions and the following disclaimer in the documentation
+    and/or other materials provided with the distribution.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may be used to endorse or promote products derived from this software
+    without specific prior written permission.
+
+This software is provided by the copyright holders and contributors "as is" and
+any express or implied warranties, including, but not limited to, the implied
+warranties of merchantability and fitness for a particular purpose are disclaimed.
+In no event shall copyright holders or contributors be liable for any direct,
+indirect, incidental, special, exemplary, or consequential damages
+(including, but not limited to, procurement of substitute goods or services;
+loss of use, data, or profits; or business interruption) however caused
+and on any theory of liability, whether in contract, strict liability,
+or tort (including negligence or otherwise) arising in any way out of
+the use of this software, even if advised of the possibility of such damage.
+
+Software: opencv 4.5.1
 Copyright notice:
 Copyright 2015-2017 Philippe Tillet
 Copyright (C) 1991-2012, Thomas G. Lane, Guido Vollbeding.
@@ -6375,7 +6749,7 @@ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
    See the License for the specific language governing permissions and
    limitations under the License.
 
-Software: abseil-cpp 20210324.2
+Software: abseil-cpp 20200923.3
 Copyright notice:
 Copyright 2016 Google Inc. All Rights Reserved.
 Copyright 2017 Google Inc. All Rights Reserved.
@@ -6818,7 +7192,7 @@ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 
-Software: pandas 1.0.2
+Software: pandas 1.0.4
 Copyright notice:
 Copyright (c) 2005-2011, NumPy Developers.
 Copyright (c) 2007  Nick Galbreath -- nickg [at] modp [dot] com. All rights reserved.
@@ -6898,7 +7272,7 @@ CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-Software: Pillow 6.2.0
+Software: Pillow 8.2.0
 Copyright notice:
 Copyright (c) 2001-2004 by Fredrik Lundh
 Copyright (c) 1997-2001 by Secret Labs AB
@@ -8851,7 +9225,7 @@ Apache License
    See the License for the specific language governing permissions and
    limitations under the License.
 
-Software: sqlite3 3.36.0
+Software: sqlite3 3.32.2
 Copyright notice:
 Copyright (C) 1994-1996, 1999-2002, 2004-2011 Free Software Foundation, Inc.
 Copyright 1992-2019 Free Software Foundation, Inc.
@@ -9014,6 +9388,268 @@ Copyright (c) 1990-2000 Info-ZIP.  All rights reserved.
      misrepresented as being the original software.
   3. This notice may not be removed or altered from any source distribution.
 
+Software: okhttp 3.14.9
+Copyright notice:
+Copyright (C) 2012 Google Inc.
+Copyright (C) 2011 The Android Open Source Project
+Copyright (C) 2010 The Android Open Source Project
+Copyright 2016 The Netty Project
+Copyright 2014 Square Inc.
+Copyright (C) 2011 The Guava Authors
+Copyright (C) 2011 Google Inc.
+Copyright (c) 2013 Karl Swedberg
+<pre>Copyright 2016 Square, Inc.
+Copyright (C) 2009 The Android Open Source Project
+Copyright (C) 2014 Square, Inc.
+Copyright (C) 2013 The Android Open Source Project
+Copyright 2012 Twitter, Inc.
+Copyright (C) 2012 The Android Open Source Project
+Copyright (C) 2012 Square, Inc.
+Copyright (C) 2015 Square, Inc.
+Copyright (C) 2016 Google Inc.
+Copyright (C) 2013 Square, Inc.
+Copyright (C) 2019 Square, Inc.
+Copyright 2013 Twitter, Inc.
+Copyright (C) 2016 Square, Inc.
+Copyright (C) 2017 Square, Inc.
+Copyright 2012 Twitter, Inc Licensed under the Apache License v2.0
+Copyright (C) 2018 Square, Inc.
+Copyright (C) 2020 Square, Inc.
+
+                                 Apache License
+                           Version 2.0, January 2004
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+
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+Software: The Legion of the Bouncy Castle 1.68
+Copyright notice:
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+Copyright (c) 2000-2021 The Legion of the Bouncy Castle Inc. (https:www.bouncycastle.org)
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+
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+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+DEALINGS IN THE SOFTWARE.
+
 Software: astunparse 1.6.3
 Copyright notice:
 Copyright (c) 2014, Simon Percivall

akg

@@ -1 +1 @@
-Subproject commit d57276ed0eb49e6958e56162cc727318f8f353cb
+Subproject commit 6ab4b3fbc650d15086b01db0ffcd21321c575e96

build.bat

@@ -15,8 +15,6 @@
 @echo off
 @title mindspore_build
 
-setlocal EnableDelayedExpansion
-
 @echo off
 echo Start build at: %date% %time%
 
@@ -25,6 +23,7 @@ SET BUILD_PATH=%BASE_PATH%/build
 
 SET threads=8
 SET ENABLE_GITEE=OFF
+SET ENABLE_INCREDIBUILD=OFF
 SET ENABLE_MSVC=OFF
 set BUILD_TYPE=Release
 set VERSION_STR=''
@@ -48,6 +47,14 @@ IF %errorlevel% == 0 (
     echo "use mingw compiler"
 )
 
+where buildconsole
+IF %errorlevel% == 0 (
+    echo "use buildconsole to speed up compile"
+    SET ENABLE_INCREDIBUILD=ON
+) else (
+    echo "fail to find buildconsole"
+)
+
 IF NOT EXIST "%BUILD_PATH%" (
     md "build"
 )
@@ -75,17 +82,8 @@ IF "%1%" == "lite" (
             -G "Visual Studio 16 2019" -A x64 ../..
     ) ELSE IF "%1%" == "ms_vs_cpu" (
         echo "======Start gen VS2019 Project for MS cpu ======"
-        for /f "delims=" %%i in ('powershell.exe -ExecutionPolicy Bypass -Command "Get-ChildItem HKLM:\SOFTWARE\Wow6432Node\Microsoft\Windows\CurrentVersion\Uninstall | foreach { Get-ItemProperty $_.PsPath } | where { $_.DisplayName -like '*Visual Studio*' -and $_.InstallLocation.Length -gt 0 } | sort InstallDate -Descending | foreach { Join-Path $_.InstallLocation 'VC\Auxiliary\Build'}"') do (call "%%i\vcvars64.bat")
-        where sccache
-        IF !errorlevel! == 0 (
-            echo "use sccache to speed up compile"
-            cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER_LAUNCHER=sccache -DCMAKE_CXX_COMPILER_LAUNCHER=sccache -DENABLE_CPU=ON -DENABLE_MINDDATA=ON -DUSE_GLOG=ON -DENABLE_GITEE=%ENABLE_GITEE% ^
-                -G Ninja ../..
-        ) ELSE (
-            echo "fail to find sccache"
-            cmake -DCMAKE_BUILD_TYPE=Release -DENABLE_CPU=ON -DENABLE_MINDDATA=ON -DUSE_GLOG=ON -DENABLE_GITEE=%ENABLE_GITEE% ^
-                -G Ninja ../..
-        )
+        cmake -DCMAKE_BUILD_TYPE=Release -DENABLE_CPU=ON -DENABLE_MINDDATA=ON -DUSE_GLOG=ON -DENABLE_GITEE=%ENABLE_GITEE% ^
+            -G "Visual Studio 16 2019" -A x64 ../..
     ) ELSE IF "%1%" == "ms_vs_cpu_debug" (
         echo "======Start gen VS2019 Project for MS cpu debug======"
         cmake -DCMAKE_BUILD_TYPE=Debug -DDEBUG_MODE=ON -DENABLE_CPU=ON -DENABLE_MINDDATA=ON -DUSE_GLOG=ON -DENABLE_GITEE=%ENABLE_GITEE% ^
@@ -104,7 +102,11 @@ IF NOT %errorlevel% == 0 (
 )
 
 IF ON == %ENABLE_MSVC% (
-    cmake --build . --config %BUILD_TYPE% --target package
+    IF ON == %ENABLE_INCREDIBUILD% (
+        buildconsole /command="cmake --build . --config %BUILD_TYPE% --target package"
+    ) ELSE (
+        cmake --build . --config %BUILD_TYPE% --target package
+    )
 ) ELSE (
     cmake --build . --target package -- -j%threads%
 )

build.sh

@@ -92,10 +92,7 @@ else
   if [[ "X$ENABLE_ACL" == "Xon" ]] && [[ "X$ENABLE_D" == "Xoff" ]]; then
       echo "acl mode, skipping deploy phase"
       rm -rf ${BASEPATH}/output/_CPack_Packages/
-  elif [[ "X$FASTER_BUILD_FOR_PLUGINS" == "Xon" ]]; then
-      echo "plugin mode, skipping deploy phase"
-      rm -rf ${BASEPATH}/output/_CPack_Packages/
-  else
+    else
       cp -rf ${BUILD_PATH}/package/mindspore/lib ${BASEPATH}/mindspore/python/mindspore
       cp -rf ${BUILD_PATH}/package/mindspore/*.so ${BASEPATH}/mindspore/python/mindspore
   fi

cmake/ascend_variables.cmake

@@ -9,18 +9,16 @@ set(ASCEND_DRIVER_HAL_PATH ${ASCEND_PATH}/driver/lib64/driver)
 
 # CANN packages
 set(ASCEND_CANN_RUNTIME_PATH ${ASCEND_PATH}/latest/lib64)
-set(ASCEND_CANN_OPP_PATH ${ASCEND_PATH}/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux)
-set(ASCEND_CANN_OPP_AARCH64_PATH ${ASCEND_CANN_OPP_PATH}/aarch64)
-set(ASCEND_CANN_OPP_X86_64_PATH ${ASCEND_CANN_OPP_PATH}/x86_64)
+set(ASCEND_CANN_OPP_PATH ${ASCEND_PATH}/latest/opp/op_impl/built-in/ai_core/tbe/op_tiling)
+set(ASCEND_CANN_OPP_PATH_TEMP ${ASCEND_PATH}/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
 set(ASCEND_CANN_PLUGIN_PATH ${ASCEND_CANN_RUNTIME_PATH}/plugin/opskernel)
 
 # Ascend-toolkit packages
 set(ASCEND_TOOLKIT_RUNTIME_PATH ${ASCEND_PATH}/ascend-toolkit/latest/lib64)
-set(ASCEND_TOOLKIT_OPP_PATH ${ASCEND_PATH}/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux)
-set(ASCEND_TOOLKIT_OPP_AARCH64_PATH ${ASCEND_TOOLKIT_OPP_PATH}/aarch64)
-set(ASCEND_TOOLKIT_OPP_X86_64_PATH ${ASCEND_TOOLKIT_OPP_PATH}/x86_64)
+set(ASCEND_TOOLKIT_OPP_PATH ${ASCEND_PATH}/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe/op_tiling)
+set(ASCEND_TOOLKIT_OPP_PATH_TEMP ${ASCEND_PATH}/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
 set(ASCEND_TOOLKIT_PLUGIN_PATH ${ASCEND_TOOLKIT_RUNTIME_PATH}/plugin/opskernel)
 
 # nnae packages (for rpath only)
 set(ASCEND_NNAE_RUNTIME_PATH ${ASCEND_PATH}/nnae/latest/lib64)
-set(ASCEND_NNAE_OPP_PATH ${ASCEND_PATH}/nnae/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling)
+set(ASCEND_NNAE_OPP_PATH ${ASCEND_PATH}/nnae/latest/opp/op_impl/built-in/ai_core/tbe/op_tiling)

cmake/dependency_securec_arm.cmake

@@ -21,14 +21,16 @@ if(NOT TARGET securec_arm)
 endif()
 
 if(NOT MSVC)
+    SET(CMAKE_BUILD_TYPE "Debug")
     if(CMAKE_SYSTEM_NAME MATCHES "Windows")
-        SET(CMAKE_C_FLAGS "$ENV{CFLAGS} -fPIC -O2 -Wall -Wno-deprecated-declarations \
+        SET(CMAKE_C_FLAGS_DEBUG "$ENV{CFLAGS} -fPIC -O0 -Wall -Wno-deprecated-declarations -g2 -ggdb \
             -fno-inline-functions -fno-omit-frame-pointer -fstack-protector-all")
     else()
-        SET(CMAKE_C_FLAGS "$ENV{CFLAGS} -Wno-nullability-completeness -fPIC -O2 -Wall \
-            -Wno-deprecated-declarations -fno-inline-functions -fno-omit-frame-pointer \
+        SET(CMAKE_C_FLAGS_DEBUG "$ENV{CFLAGS} -Wno-nullability-completeness -fPIC -O0 -Wall \
+            -Wno-deprecated-declarations -g2 -ggdb -fno-inline-functions -fno-omit-frame-pointer \
             -fstack-protector-all -D_LIBCPP_INLINE_VISIBILITY='' -D'_LIBCPP_EXTERN_TEMPLATE(...)='")
     endif()
+    SET(CMAKE_C_FLAGS_RELEASE "$ENV{CFLAGS} -fPIC -O3 -Wall -Wno-deprecated-declarations -fstack-protector-all")
     set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
 
     #add flags

cmake/external_libs/cmsis.cmake

@@ -1,6 +1,6 @@
 set(cmsis_pkg_name cmsis)
 
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     set(REQ_URL "https://gitee.com/mirrors/CMSIS_5/repository/archive/5.7.0.tar.gz")
     set(SHA256 "1b4aa6d47c7d3a5032555049b95f4962a700e2022405f863781010606fe7f8f1")
 else()

cmake/external_libs/fast_transformers.cmake

@@ -2,9 +2,6 @@ set(REQ_URL "https://github.com/NVIDIA/FasterTransformer/archive/refs/tags/relea
 set(SHA256 "7adffe2d53b3c1544295a6b7d1887e59b044eba25dd3e150bc909168d5e99081")
 set(ft_libs "transformer-shared")
 
-if(DEFINED ENV{MSLITE_GPU_ARCH})
-  set(arch_opt -DSM=$ENV{MSLITE_GPU_ARCH})
-endif()
 
 mindspore_add_pkg(fast_transformers
         VER 0.5.0
@@ -13,7 +10,7 @@ mindspore_add_pkg(fast_transformers
         LIBS ${ft_libs}
         LIB_PATH lib
         PATCHES ${MINDSPORE_PROJECT_DIR}/third_party/patch/fast_transformer/001-fast_transformer.patch
-        CMAKE_OPTION -DCMAKE_BUILD_TYPE=Release ${arch_opt} -DEXAMPLES=off)
+        CMAKE_OPTION -DCMAKE_BUILD_TYPE=Release -DEXAMPLES=off)
 include_directories(${fast_transformers_INC})
 
 add_library(mindspore::fast_transformers ALIAS fast_transformers::transformer-shared)

cmake/external_libs/flatbuffers.cmake

@@ -17,7 +17,7 @@ if(ENABLE_GITEE_EULER)
     set(GIT_REPOSITORY "https://gitee.com/src-openeuler/flatbuffers.git")
     set(GIT_TAG "openEuler-22.03-LTS")
     set(SHA256 "d94ef2fb0c22198c7ffe2a6044e864bd467ca70b8cfdc52720dc94313321777b")
-    set(FLATBUFFER_SRC "${CMAKE_BINARY_DIR}/_deps/flatbuffers-src")
+    set(FLATBUFFER_SRC "${TOP_DIR}/mindspore/lite/build/_deps/flatbuffers-src")
     set(FLATBUFFER_DIR "${FLATBUFFER_SRC}/flatbuffers-2.0.0")
     __download_pkg_with_git(flatbuffers ${GIT_REPOSITORY} ${GIT_TAG} ${SHA256})
     execute_process(COMMAND tar -xf ${FLATBUFFER_SRC}/v2.0.0.tar.gz WORKING_DIRECTORY ${FLATBUFFER_SRC})

cmake/external_libs/glog.cmake

@@ -32,7 +32,7 @@ if(NOT ENABLE_GLIBCXX)
     set(glog_CXXFLAGS "${glog_CXXFLAGS} -D_GLIBCXX_USE_CXX11_ABI=0")
 endif()
 
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     set(REQ_URL "https://gitee.com/mirrors/glog/repository/archive/v0.4.0.tar.gz")
     set(SHA256 "e17cd4bb7c06951a12fc9db5130ec63a9f090b84340b8556fa0d530f73c6b634")
 else()

cmake/external_libs/json.cmake

@@ -7,7 +7,7 @@ else()
     set(nlohmann_json3101_CFLAGS "-D_FORTIFY_SOURCE=2 -O2")
 endif()
 
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     set(REQ_URL "https://gitee.com/mirrors/JSON-for-Modern-CPP/repository/archive/v3.10.1.zip")
     set(SHA256 "5c7d0a0542431fef628f8dc4c34fd022fe8747ccb577012d58f38672d8747e0d")
     set(INCLUDE "./include")

cmake/external_libs/libevent.cmake

@@ -8,7 +8,7 @@ if(NOT MINDSPORE_PROJECT_DIR)
 set(MINDSPORE_PROJECT_DIR ${CMAKE_SOURCE_DIR})
 endif()
 
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     set(REQ_URL "https://gitee.com/mirrors/libevent/repository/archive/release-2.1.12-stable.tar.gz")
     set(SHA256 "7180a979aaa7000e1264da484f712d403fcf7679b1e9212c4e3d09f5c93efc24")
 else()

cmake/external_libs/mkl_dnn.cmake

@@ -15,7 +15,7 @@ if(ENABLE_GITEE_EULER)
         set(GIT_TAG "0d726f1")
         set(SHA256 "4d655c0751ee6439584ef5e3d465953fe0c2f4ee2700bc02699bdc1d1572af0d")
     __download_pkg_with_git(ONEDNN ${GIT_REPOSITORY} ${GIT_TAG} ${SHA256})
-    set(ONE_DNN_SRC "${CMAKE_BINARY_DIR}/_deps/onednn-src")
+    set(ONE_DNN_SRC "${TOP_DIR}/mindspore/lite/build/_deps/onednn-src")
     execute_process(COMMAND tar -xf ${ONE_DNN_SRC}/v2.2.tar.gz --strip-components 1 -C ${ONE_DNN_SRC})
 endif()
 if(CMAKE_SYSTEM_NAME MATCHES "Windows")

cmake/external_libs/opencl-clhpp.cmake

@@ -1,12 +0,0 @@
-# Note: OpenCL-CLHPP depends on OpenCL-Headers
-if(ENABLE_GITEE_EULER)
-    # Already downloaded in opencl-header.cmake
-elseif(ENABLE_GITEE)
-    set(REQ_URL "https://gitee.com/mirrors/OpenCL-CLHPP/repository/archive/v2.0.12.tar.gz")
-    set(SHA256 "d5bdbfb614a6494de97abf7297db6d2c88a55a095b12949d797ce562f5d4fdce")
-    __download_pkg(OpenCL-CLHPP ${REQ_URL} ${SHA256})
-else()
-    set(REQ_URL "https://github.com/KhronosGroup/OpenCL-CLHPP/archive/v2.0.12.tar.gz")
-    set(SHA256 "20b28709ce74d3602f1a946d78a2024c1f6b0ef51358b9686612669897a58719")
-    __download_pkg(OpenCL-CLHPP ${REQ_URL} ${SHA256})
-endif()

cmake/external_libs/opencl-headers.cmake

@@ -1,46 +0,0 @@
-if(ENABLE_GITEE_EULER)
-    set(GIT_REPOSITORY "git@gitee.com:src-openeuler/opencl-clhpp.git")
-    set(GIT_TAG "7347fa1bb52ebee9f3d6c44ff65ef3c4253cab79")
-    set(SHA256 "d41d8cd98f00b204e9800998ecf8427e")
-
-    if(EXISTS "${CMAKE_BINARY_DIR}/_deps/opencl-clhpp-src")
-        # Extracting tarball into git repository would make git-status tainted, and case cmake rebuild error.
-        # Here we clean source dir before rebuild to fix this error.
-        file(REMOVE_RECURSE "${CMAKE_BINARY_DIR}/_deps/opencl-clhpp-src")
-        file(REMOVE_RECURSE "${CMAKE_BINARY_DIR}/_deps/opencl-clhpp-build")
-        file(REMOVE_RECURSE "${CMAKE_BINARY_DIR}/_deps/opencl-clhpp-subbuild")
-    endif()
-
-    __download_pkg_with_git(OpenCL-CLHPP ${GIT_REPOSITORY} ${GIT_TAG} ${SHA256})
-    set(OPENCL_CLHPP_SRC "${CMAKE_BINARY_DIR}/_deps/opencl-clhpp-src")
-    execute_process(COMMAND tar -xf ${OPENCL_CLHPP_SRC}/v2.0.12.tar.gz --strip-components 1 -C ${OPENCL_CLHPP_SRC})
-
-    set(OPENCL_HEADER_SRC "${CMAKE_BINARY_DIR}/_deps/opencl-headers-src")
-    file(MAKE_DIRECTORY "${OPENCL_HEADER_SRC}")
-    execute_process(COMMAND tar -xf ${OPENCL_CLHPP_SRC}/v2020.12.18.tar.gz --strip-components 1 -C ${OPENCL_HEADER_SRC})
-elseif(ENABLE_GITEE)
-    set(REQ_URL "https://gitee.com/mirrors/OpenCL-Headers/repository/archive/v2020.12.18.tar.gz")
-    set(SHA256 "076251b94284b931399ee525527bc9aef3f5f6f3f3b1964ae485218cc88956ba")
-    __download_pkg(OpenCL-Headers ${REQ_URL} ${SHA256})
-else()
-    set(REQ_URL "https://github.com/KhronosGroup/OpenCL-Headers/archive/v2020.12.18.tar.gz")
-    set(SHA256 "5dad6d436c0d7646ef62a39ef6cd1f3eba0a98fc9157808dfc1d808f3705ebc2")
-    __download_pkg(OpenCL-Headers ${REQ_URL} ${SHA256})
-endif()
-
-function(gene_opencl CL_SRC_DIR)
-    message(STATUS "**********gene opencl********* cl path: " "${CL_SRC_DIR}")
-    if(NOT EXISTS ${CL_SRC_DIR})
-        return()
-    endif()
-    file(GLOB_RECURSE CL_LIST ${CL_SRC_DIR}/*.cl)
-    foreach(file_path ${CL_LIST})
-        set(out_file_path "${file_path}.inc")
-        file(REMOVE ${out_file_path})
-
-        string(REGEX REPLACE ".+/(.+)\\..*" "\\1" kernel_name "${file_path}")
-        file(READ ${file_path} cl_program)
-        string(CONCAT cl_str "static const std::string ${kernel_name}_source = R\"(\n" "${cl_program}" ")\";")
-        file(WRITE ${out_file_path} "${cl_str}")
-    endforeach()
-endfunction()

cmake/external_libs/opencl.cmake

@@ -0,0 +1,55 @@
+if(ENABLE_GITEE_EULER)
+    set(GIT_REPOSITORY "git@gitee.com:src-openeuler/opencl-clhpp.git")
+    set(GIT_TAG "7347fa1bb52ebee9f3d6c44ff65ef3c4253cab79")
+    set(SHA256 "d41d8cd98f00b204e9800998ecf8427e")
+
+    __download_pkg_with_git(OpenCL-CLHPP ${GIT_REPOSITORY} ${GIT_TAG} ${SHA256})
+    set(OPENCL_CLHPP_SRC "${TOP_DIR}/mindspore/lite/build/_deps/opencl-clhpp-src")
+    execute_process(COMMAND tar -xf ${OPENCL_CLHPP_SRC}/v2.0.12.tar.gz --strip-components 1 -C ${OPENCL_CLHPP_SRC})
+
+    set(OPENCL_HEADER_SRC "${TOP_DIR}/mindspore/lite/build/_deps/opencl-headers-src")
+    execute_process(COMMAND mkdir -p ${OPENCL_HEADER_SRC})
+    execute_process(COMMAND tar -xf ${OPENCL_CLHPP_SRC}/v2020.12.18.tar.gz --strip-components 1 -C ${OPENCL_HEADER_SRC})
+elseif(ENABLE_GITEE)
+    set(REQ_URL "https://gitee.com/mirrors/OpenCL-Headers/repository/archive/v2020.12.18.tar.gz")
+    set(SHA256 "076251b94284b931399ee525527bc9aef3f5f6f3f3b1964ae485218cc88956ba")
+    __download_pkg(OpenCL-Headers ${REQ_URL} ${SHA256})
+    set(REQ_URL "https://gitee.com/mirrors/OpenCL-CLHPP/repository/archive/v2.0.12.tar.gz")
+    set(SHA256 "d5bdbfb614a6494de97abf7297db6d2c88a55a095b12949d797ce562f5d4fdce")
+    __download_pkg(OpenCL-CLHPP ${REQ_URL} ${SHA256})
+else()
+    set(REQ_URL "https://github.com/KhronosGroup/OpenCL-Headers/archive/v2020.12.18.tar.gz")
+    set(SHA256 "5dad6d436c0d7646ef62a39ef6cd1f3eba0a98fc9157808dfc1d808f3705ebc2")
+    __download_pkg(OpenCL-Headers ${REQ_URL} ${SHA256})
+    set(REQ_URL "https://github.com/KhronosGroup/OpenCL-CLHPP/archive/v2.0.12.tar.gz")
+    set(SHA256 "20b28709ce74d3602f1a946d78a2024c1f6b0ef51358b9686612669897a58719")
+    __download_pkg(OpenCL-CLHPP ${REQ_URL} ${SHA256})
+endif()
+
+function(gene_opencl CL_SRC_DIR)
+    message(STATUS "**********gene opencl********* cl path: " "${CL_SRC_DIR}")
+    if(NOT EXISTS ${CL_SRC_DIR})
+        return()
+    endif()
+    file(GLOB_RECURSE CL_LIST ${CL_SRC_DIR}/*.cl)
+    foreach(file_path ${CL_LIST})
+        file(REMOVE ${file_path}.inc)
+        string(REGEX REPLACE ".+/(.+)\\..*" "\\1" kernel_name "${file_path}")
+        set(inc_file_ex "${file_path}.inc")
+        execute_process(
+                COMMAND bash -c "sed 's/\\\\/\\\\\\\\/g' "
+                COMMAND bash -c "sed 's/\\\"/\\\\\\\"/g' "
+                COMMAND bash -c "sed 's/$/\\\\n\\\" \\\\/' "
+                COMMAND bash -c "sed 's/^/\\\"/' "
+                WORKING_DIRECTORY ${CL_SRC_DIR}
+                INPUT_FILE ${file_path}
+                OUTPUT_FILE ${inc_file_ex}
+                RESULT_VARIABLE RESULT)
+        if(NOT RESULT EQUAL "0")
+            message(FATAL_ERROR "error! when generate ${inc_file_ex}")
+        endif()
+        __exec_cmd(COMMAND sed -i "1i\\static const char *${kernel_name}_source =\\\"\\\\n\\\" \\\\"
+          ${inc_file_ex} WORKING_DIRECTORY ${CL_SRC_DIR})
+        __exec_cmd(COMMAND sed -i "$a\\\\\;" ${inc_file_ex} WORKING_DIRECTORY ${CL_SRC_DIR})
+    endforeach()
+endfunction()

cmake/external_libs/opencv.cmake

@@ -28,7 +28,7 @@ if(ENABLE_GITEE_EULER)
     set(GIT_REPOSITORY "https://gitee.com/src-openeuler/opencv.git")
     set(GIT_TAG "openEuler-22.03-LTS")
     set(SHA256 "d8b00a5440c8e5d275aa5b141f89d69ee196d9dcd2d2032ddd8ef4b04010999a")
-    set(OPENCV_SRC "${CMAKE_BINARY_DIR}/_deps/opencv-src")
+    set(OPENCV_SRC "${TOP_DIR}/build/mindspore/_deps/opencv-src")
     __download_pkg_with_git(opencv ${GIT_REPOSITORY} ${GIT_TAG} ${SHA256})
     execute_process(COMMAND tar -xf ${OPENCV_SRC}/opencv-4.5.2.tar.gz --strip-components 1 -C ${OPENCV_SRC})
 else()

cmake/external_libs/openssl.cmake

@@ -1,4 +1,4 @@
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
   set(REQ_URL "https://gitee.com/mirrors/openssl/repository/archive/OpenSSL_1_1_1k.tar.gz")
   set(SHA256 "b92f9d3d12043c02860e5e602e50a73ed21a69947bcc74d391f41148e9f6aa95")
 else()
@@ -33,10 +33,6 @@ if(BUILD_LITE)
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-1292.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2068.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2097.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4304.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4450.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0215.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0286.patch
                 )
     elseif(PLATFORM_ARM32 AND ANDROID_NDK_TOOLCHAIN_INCLUDED)
         set(openssl_USE_STATIC_LIBS OFF)
@@ -58,10 +54,6 @@ if(BUILD_LITE)
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-1292.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2068.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2097.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4304.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4450.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0215.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0286.patch
                 )
     elseif(${CMAKE_SYSTEM_NAME} MATCHES "Linux" OR APPLE)
         set(openssl_CFLAGS -fvisibility=hidden)
@@ -78,10 +70,6 @@ if(BUILD_LITE)
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-1292.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2068.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2097.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4304.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4450.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0215.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0286.patch
                 )
     else()
         MESSAGE(FATAL_ERROR "openssl does not support compilation for the current environment.")
@@ -105,10 +93,6 @@ else()
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-1292.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2068.patch
                 PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-2097.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4304.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2022-4450.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0215.patch
-                PATCHES ${OPENSSL_PATCH_ROOT}/CVE-2023-0286.patch
                 )
         include_directories(${openssl_INC})
         add_library(mindspore::ssl ALIAS openssl::ssl)

cmake/external_libs/protobuf.cmake

@@ -50,7 +50,7 @@ set(CMAKE_CXX_FLAGS ${_ms_tmp_CMAKE_CXX_FLAGS})
 string(REPLACE " -Wall" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
 string(REPLACE " -Werror" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
 
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     set(REQ_URL "https://gitee.com/mirrors/protobuf_source/repository/archive/v3.13.0.tar.gz")
     set(SHA256 "ab9b39e7053a6fb06b01bf75fb6ec6a71a1ada5a5f8e2446f927336e97b9e7bb")
 else()
@@ -165,7 +165,7 @@ function(ms_protobuf_generate_py c_var h_var py_var)
                     COMMAND perl -pi.bak -e "s/import (.+_pb2.*)/from . import \\1/"
                             "${CMAKE_BINARY_DIR}/proto_py/proto/${file_name}_pb2.py"
                     COMMAND ${CMAKE_COMMAND} -E copy "${CMAKE_BINARY_DIR}/proto_py/proto/${file_name}_pb2.py"
-                            "${TOP_DIR}/mindspore/python/mindspore/train/"
+                            "${PROJECT_SOURCE_DIR}/mindspore/python/mindspore/train/"
                     DEPENDS protobuf::protoc ${abs_file}
                     COMMENT "Running C++ protocol buffer compiler on ${file}" VERBATIM)
         else()
@@ -180,7 +180,7 @@ function(ms_protobuf_generate_py c_var h_var py_var)
                     COMMAND perl -pi -e "s/import (.+_pb2.*)/from . import \\1/"
                             "${CMAKE_BINARY_DIR}/proto_py/proto/${file_name}_pb2.py"
                     COMMAND cp "${CMAKE_BINARY_DIR}/proto_py/proto/${file_name}_pb2.py"
-                            "${TOP_DIR}/mindspore/python/mindspore/train/"
+                            "${PROJECT_SOURCE_DIR}/mindspore/python/mindspore/train/"
                     DEPENDS protobuf::protoc ${abs_file}
                     COMMENT "Running C++ protocol buffer compiler on ${file}" VERBATIM)
         endif()

cmake/external_libs/pybind11.cmake

@@ -1,6 +1,6 @@
 set(PYTHON_VERSION ${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR})
 
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     if(PYTHON_VERSION MATCHES "3.9")
         set(REQ_URL "https://gitee.com/mirrors/pybind11/repository/archive/v2.6.1.tar.gz")
         set(SHA256 "c840509be94ac97216c3b4a3ed9f3fdba9948dbe38c16fcfaee3acc6dc93ed0e")

cmake/external_libs/robin.cmake

@@ -1,4 +1,4 @@
-if(ENABLE_GITEE OR ENABLE_GITEE_EULER) # Channel GITEE_EULER is NOT supported now, use GITEE instead.
+if(ENABLE_GITEE)
     set(REQ_URL "https://gitee.com/mirrors/robin-hood-hashing/repository/archive/3.11.5.zip")
     set(SHA256 "8d1f5d5ee447e5827032d1eb8b1609134618b1cc5c5bcadfcbfed99a2d3583d4")
 else()

cmake/external_libs/zlib.cmake

@@ -6,20 +6,14 @@ else()
     set(SHA256 "629380c90a77b964d896ed37163f5c3a34f6e6d897311f1df2a7016355c45eff")
 endif()
 
-if(BUILD_LITE)
-    set(ZLIB_PATCH_ROOT ${TOP_DIR}/third_party/patch/zlib)
-else()
-    set(ZLIB_PATCH_ROOT ${CMAKE_SOURCE_DIR}/third_party/patch/zlib)
-endif()
-
 mindspore_add_pkg(zlib
         VER 1.2.11
         LIBS z
         URL ${REQ_URL}
         SHA256 ${SHA256}
         CMAKE_OPTION -DCMAKE_BUILD_TYPE:STRING=Release
-        PATCHES ${ZLIB_PATCH_ROOT}/CVE-2018-25032.patch
-        PATCHES ${ZLIB_PATCH_ROOT}/CVE-2022-37434.patch)
+        PATCHES ${CMAKE_SOURCE_DIR}/third_party/patch/zlib/CVE-2018-25032.patch
+        PATCHES ${CMAKE_SOURCE_DIR}/third_party/patch/zlib/CVE-2022-37434.patch)
 
 include_directories(${zlib_INC})
 add_library(mindspore::z ALIAS zlib::z)

cmake/graphengine_variables.cmake

@@ -1,14 +0,0 @@
-# path variables for graphengine submodule, it has to be included after mindspore/core
-# and minspore/ccsrc to prevent conflict of op headers
-if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/external)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/framework)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/base)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/aicpu)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/toolchain)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external)
-    include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external/graph)
-endif()

cmake/mind_expression.cmake

@@ -64,6 +64,18 @@ if(ENABLE_GPU AND GPU_BACKEND_CUDA)
     endif()
 endif()
 
+if(ENABLE_D OR ENABLE_ACL OR ENABLE_TESTCASES)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/external)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/inc/framework)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/aicpu)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/toolchain)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external)
+    include_directories(${CMAKE_SOURCE_DIR}/graphengine/metadef/inc/external/graph)
+endif()
+
 if(ENABLE_MINDDATA)
     include(${CMAKE_SOURCE_DIR}/cmake/external_libs/icu4c.cmake)
     include(${CMAKE_SOURCE_DIR}/cmake/external_libs/opencv.cmake)

cmake/options.cmake

@@ -17,7 +17,7 @@ option(ENABLE_DUMP_IR "Enable dump function graph ir, default on" ON)
 option(ENABLE_MPI "enable mpi" OFF)
 option(ENABLE_AKG "enable akg" OFF)
 option(ENABLE_DEBUGGER "enable debugger" OFF)
-option(ENABLE_RDMA "enable RDMA for RPC" OFF)
+option(ENABLE_IBVERBS "enable IBVERBS for parameter server" OFF)
 option(ENABLE_PYTHON "Enable python" ON)
 option(ENABLE_ACL "enable acl" OFF)
 option(ENABLE_GLIBCXX "enable_glibcxx" OFF)
@@ -28,21 +28,6 @@ option(BUILD_DEV_MODE "MindSpore build nightly dev mode" OFF)
 option(ENABLE_FAST_HASH_TABLE "Enable use fast hash table instead of std ones" ON)
 option(USE_LLVM "use llvm" OFF)
 option(USE_MS_THREADPOOL_FOR_DNNL "use ms threadpool for onednn ops" ON)
-option(ONLY_BUILD_DEVICE_PLUGINS "only build device plugins" OFF)
-
-if(ONLY_BUILD_DEVICE_PLUGINS)
-    if(NOT CMAKE_SYSTEM_NAME MATCHES "Linux")
-        set(ONLY_BUILD_DEVICE_PLUGINS OFF)
-        message(WARNING "-f is supported on only linux.")
-    endif()
-    if(ENABLE_CPU)
-        set(ENABLE_CPU OFF)
-    endif()
-endif()
-
-if(NOT CMAKE_SYSTEM_NAME MATCHES "Linux")
-    set(ENABLE_MPI OFF)
-endif()
 
 if(NOT CMAKE_SYSTEM_NAME MATCHES "Linux")
     set(USE_MS_THREADPOOL_FOR_DNNL OFF)

cmake/package.cmake

@@ -184,10 +184,9 @@ if(ENABLE_GPU)
         endif()
     endif()
     install(
-            TARGETS cuda_ops LIBRARY
+            TARGETS cuda_ops
             DESTINATION ${INSTALL_PLUGIN_DIR}/gpu${CUDA_VERSION}
             COMPONENT mindspore
-            NAMELINK_SKIP
     )
 endif()
 
@@ -270,12 +269,6 @@ install(
     COMPONENT mindspore
 )
 
-file(GLOB NOTICE ${CMAKE_SOURCE_DIR}/Third_Party_Open_Source_Software_Notice)
-install(
-    FILES ${NOTICE}
-    DESTINATION ${INSTALL_PY_DIR}
-    COMPONENT mindspore
-)
 install(
     DIRECTORY
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/nn
@@ -290,6 +283,7 @@ install(
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/ops
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/communication
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/profiler
+        ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/compression
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/rewrite
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/run_check
         ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/experimental
@@ -386,7 +380,6 @@ install(
 ## config files
 install(
     FILES ${CMAKE_SOURCE_DIR}/config/op_info.config
-          ${CMAKE_SOURCE_DIR}/config/super_bar_config.json
     DESTINATION ${INSTALL_CFG_DIR}
     COMPONENT mindspore
 )

cmake/package_lite.cmake

@@ -12,7 +12,6 @@ else()
 endif()
 set(TEST_CASE_DIR ${TOP_DIR}/mindspore/lite/test/build)
 set(EXTENDRT_BUILD_DIR ${TOP_DIR}/mindspore/lite/build/src/extendrt)
-set(EXECUTOR_BUILD_DIR ${TOP_DIR}/mindspore/lite/build/src/extendrt/unified_executor)
 
 set(RUNTIME_DIR ${RUNTIME_PKG_NAME}/runtime)
 set(RUNTIME_INC_DIR ${RUNTIME_PKG_NAME}/runtime/include)
@@ -21,13 +20,11 @@ set(PROVIDERS_LIB_DIR ${RUNTIME_PKG_NAME}/providers)
 set(MIND_DATA_INC_DIR ${RUNTIME_PKG_NAME}/runtime/include/dataset)
 set(TURBO_DIR ${RUNTIME_PKG_NAME}/runtime/third_party/libjpeg-turbo)
 set(GLOG_DIR ${RUNTIME_PKG_NAME}/runtime/third_party/glog)
-set(DNNL_DIR ${RUNTIME_PKG_NAME}/runtime/third_party/dnnl)
 set(SECUREC_DIR ${RUNTIME_PKG_NAME}/runtime/third_party/securec)
 set(MINDSPORE_LITE_LIB_NAME libmindspore-lite)
 set(MINDSPORE_LITE_EXTENDRT_LIB_NAME libmindspore-lite)
 set(MINDSPORE_CORE_LIB_NAME libmindspore_core)
 set(MINDSPORE_GE_LITERT_LIB_NAME libmsplugin-ge-litert)
-set(MINDSPORE_LITE_EXECUTOR_LIB_NAME liblite-unified-executor)
 set(BENCHMARK_NAME benchmark)
 set(MSLITE_NNIE_LIB_NAME libmslite_nnie)
 set(MSLITE_PROPOSAL_LIB_NAME libmslite_proposal)
@@ -216,7 +213,7 @@ function(__install_white_list_ops)
             ${TOP_DIR}/mindspore/core/ops/base_operator.h
             ${TOP_DIR}/mindspore/core/ops/return.h
             ${TOP_DIR}/mindspore/core/ops/pad.h
-            DESTINATION ${CONVERTER_ROOT_DIR}/include/ops
+            DESTINATION ${CONVERTER_ROOT_DIR}/include/core/ops
             COMPONENT ${RUNTIME_COMPONENT_NAME}
             )
     install(FILES
@@ -249,7 +246,7 @@ function(__install_white_list_ops)
             ${TOP_DIR}/mindspore/core/ops/fusion/sub_fusion.h
             ${TOP_DIR}/mindspore/core/ops/fusion/tile_fusion.h
             ${TOP_DIR}/mindspore/core/ops/fusion/topk_fusion.h
-            DESTINATION ${CONVERTER_ROOT_DIR}/include/ops/fusion
+            DESTINATION ${CONVERTER_ROOT_DIR}/include/core/ops/fusion
             COMPONENT ${RUNTIME_COMPONENT_NAME}
             )
 endfunction()
@@ -268,7 +265,7 @@ if(MSLITE_MINDDATA_IMPLEMENT STREQUAL "full")
         DESTINATION ${MIND_DATA_INC_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
 
     if(PLATFORM_ARM64)
-        if((MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE) AND MSLITE_ENABLE_ACL)
+        if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE AND MSLITE_ENABLE_ACL)
             install(FILES ${TOP_DIR}/mindspore/ccsrc/minddata/dataset/include/dataset/vision_ascend.h
                     DESTINATION ${MIND_DATA_INC_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(FILES ${TOP_DIR}/mindspore/lite/build/minddata/kernels-dvpp-image/utils/libdvpp_utils.so
@@ -290,7 +287,7 @@ if(MSLITE_MINDDATA_IMPLEMENT STREQUAL "full")
         install(FILES ${TOP_DIR}/mindspore/lite/build/securec/src/libsecurec.a
                 DESTINATION ${SECUREC_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
     else()
-        if((MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE) AND MSLITE_ENABLE_ACL)
+        if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE AND MSLITE_ENABLE_ACL)
                 install(FILES ${TOP_DIR}/mindspore/ccsrc/minddata/dataset/include/dataset/vision_ascend.h
                         DESTINATION ${MIND_DATA_INC_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
                 install(FILES ${TOP_DIR}/mindspore/lite/build/minddata/kernels-dvpp-image/utils/libdvpp_utils.so
@@ -421,13 +418,11 @@ if(PLATFORM_ARM64)
             COMPONENT ${RUNTIME_COMPONENT_NAME})
     install(FILES ${TOP_DIR}/mindspore/lite/build/schema/ops_types_generated.h DESTINATION ${RUNTIME_INC_DIR}/schema
             COMPONENT ${RUNTIME_COMPONENT_NAME})
-    if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE)
+    if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE)
         install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/${MINDSPORE_LITE_EXTENDRT_LIB_NAME}.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${EXTENDRT_BUILD_DIR}/delegate/graph_executor/litert/${MINDSPORE_GE_LITERT_LIB_NAME}.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(FILES ${EXECUTOR_BUILD_DIR}/${MINDSPORE_LITE_EXECUTOR_LIB_NAME}.so
-                DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${glog_LIBPATH}/libmindspore_glog.so.0.4.0 DESTINATION ${RUNTIME_LIB_DIR}
                 RENAME libmindspore_glog.so.0 COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(TARGETS mindspore_core DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
@@ -436,8 +431,10 @@ if(PLATFORM_ARM64)
         if(MSLITE_ENABLE_ACL)
             install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/kernel/ascend/libascend_kernel_plugin.so
                     DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-            install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/ascend_ge/libascend_ge_plugin.so
-                    DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
+            if(MSLITE_ENABLE_HELPER)
+                install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/ascend_ge/libascend_ge_plugin.so
+                        DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
+            endif()
         endif()
         if(MSLITE_GPU_BACKEND STREQUAL tensorrt)
             install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/tensorrt/libtensorrt_plugin.so
@@ -513,11 +510,21 @@ if(PLATFORM_ARM64)
                     ${CONVERTER_ROOT_DIR}/include/registry COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(FILES ${API_HEADER}  DESTINATION ${CONVERTER_ROOT_DIR}/include/api
                     COMPONENT ${RUNTIME_COMPONENT_NAME})
-            install(FILES ${MINDAPI_BASE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/mindapi/base
+            install(FILES ${MINDAPI_BASE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/mindapi/base
                     COMPONENT ${RUNTIME_COMPONENT_NAME})
-            install(FILES ${MINDAPI_IR_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/mindapi/ir
+            install(FILES ${MINDAPI_IR_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/mindapi/ir
+                    COMPONENT ${RUNTIME_COMPONENT_NAME})
+            install(FILES ${ABSTRACT_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/abstract
+                    COMPONENT ${RUNTIME_COMPONENT_NAME})
+            install(FILES ${BASE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/base
+                    COMPONENT ${RUNTIME_COMPONENT_NAME})
+            install(FILES ${IR_DTYPE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/ir/dtype
+                    COMPONENT ${RUNTIME_COMPONENT_NAME})
+            install(FILES ${IR_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/ir
                     COMPONENT ${RUNTIME_COMPONENT_NAME})
             __install_white_list_ops()
+            install(FILES ${UTILS_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/utils
+                    COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(DIRECTORY ${TOP_DIR}/mindspore/lite/build/schema/
                     DESTINATION ${CONVERTER_ROOT_DIR}/include/schema
                     COMPONENT ${RUNTIME_COMPONENT_NAME}
@@ -536,8 +543,6 @@ if(PLATFORM_ARM64)
                     DESTINATION ${CONVERTER_ROOT_DIR}/lib COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(FILES ${TOP_DIR}/mindspore/lite/build/tools/converter/registry/libmslite_converter_plugin.so
                     DESTINATION ${CONVERTER_ROOT_DIR}/lib COMPONENT ${RUNTIME_COMPONENT_NAME})
-            install(DIRECTORY ${TOP_DIR}/third_party/proto/ DESTINATION ${CONVERTER_ROOT_DIR}/third_party/proto
-                    COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(FILES ${glog_LIBPATH}/libmindspore_glog.so.0.4.0 DESTINATION ${CONVERTER_ROOT_DIR}/lib
                     RENAME libmindspore_glog.so.0 COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(TARGETS mindspore_core DESTINATION ${CONVERTER_ROOT_DIR}/lib COMPONENT ${RUNTIME_COMPONENT_NAME})
@@ -648,13 +653,11 @@ elseif(PLATFORM_ARM32)
             COMPONENT ${RUNTIME_COMPONENT_NAME})
     install(FILES ${TOP_DIR}/mindspore/lite/build/schema/ops_types_generated.h DESTINATION ${RUNTIME_INC_DIR}/schema
             COMPONENT ${RUNTIME_COMPONENT_NAME})
-    if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE)
+    if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE)
         install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/${MINDSPORE_LITE_EXTENDRT_LIB_NAME}.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${EXTENDRT_BUILD_DIR}/delegate/graph_executor/litert/${MINDSPORE_GE_LITERT_LIB_NAME}.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(FILES ${EXECUTOR_BUILD_DIR}/${MINDSPORE_LITE_EXECUTOR_LIB_NAME}.so
-                DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${glog_LIBPATH}/libmindspore_glog.so.0.4.0 DESTINATION ${RUNTIME_LIB_DIR}
                 RENAME libmindspore_glog.so.0 COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(TARGETS mindspore_core DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
@@ -663,8 +666,10 @@ elseif(PLATFORM_ARM32)
         if(MSLITE_ENABLE_ACL)
             install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/kernel/ascend/libascend_kernel_plugin.so
                     DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-            install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/ascend_ge/libascend_ge_plugin.so
-                    DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
+            if(MSLITE_ENABLE_HELPER)
+                install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/ascend_ge/libascend_ge_plugin.so
+                        DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
+            endif()
         endif()
         if(MSLITE_GPU_BACKEND STREQUAL tensorrt)
             install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/tensorrt/libtensorrt_plugin.so
@@ -748,7 +753,7 @@ elseif(WIN32)
                 ${opencv_LIBPATH}/../bin/libopencv_imgproc*
                 )
         install(FILES ${OPENCV_LIB_LIST} DESTINATION ${CONVERTER_ROOT_DIR}/lib COMPONENT ${RUNTIME_COMPONENT_NAME})
-        if(NOT MSVC AND NOT (MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE))
+        if(NOT MSVC AND NOT MSLITE_ENABLE_CLOUD_FUSION_INFERENCE)
             __install_micro_wrapper()
             __install_micro_codegen()
         endif()
@@ -844,25 +849,23 @@ else()
             COMPONENT ${RUNTIME_COMPONENT_NAME} FILES_MATCHING PATTERN "*.h" PATTERN "ops*" EXCLUDE)
     install(DIRECTORY ${TOP_DIR}/include/c_api/ DESTINATION ${RUNTIME_INC_DIR}/c_api
             COMPONENT ${RUNTIME_COMPONENT_NAME} FILES_MATCHING PATTERN "*.h")
-    if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE)
+    if(MSLITE_ENABLE_CLOUD_FUSION_INFERENCE)
         install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/${MINDSPORE_LITE_EXTENDRT_LIB_NAME}.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${EXTENDRT_BUILD_DIR}/delegate/graph_executor/litert/${MINDSPORE_GE_LITERT_LIB_NAME}.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(FILES ${EXECUTOR_BUILD_DIR}/${MINDSPORE_LITE_EXECUTOR_LIB_NAME}.so
-                DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${glog_LIBPATH}/libmindspore_glog.so.0.4.0 DESTINATION ${RUNTIME_LIB_DIR}
                 RENAME libmindspore_glog.so.0 COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(FILES ${onednn_LIBPATH}/libdnnl.so.2.2 DESTINATION ${DNNL_DIR}
-                RENAME libdnnl.so.2 COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(TARGETS mindspore_core DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/convert/libruntime_convert_plugin.so
                 DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
         if(MSLITE_ENABLE_ACL)
             install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/kernel/ascend/libascend_kernel_plugin.so
                     DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-            install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/ascend_ge/libascend_ge_plugin.so
-                    DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
+            if(MSLITE_ENABLE_HELPER)
+                install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/ascend_ge/libascend_ge_plugin.so
+                        DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
+            endif()
         endif()
         if(MSLITE_GPU_BACKEND STREQUAL tensorrt)
             install(FILES ${TOP_DIR}/mindspore/lite/build/src/extendrt/delegate/tensorrt/libtensorrt_plugin.so
@@ -894,25 +897,33 @@ else()
                 COMPONENT ${RUNTIME_COMPONENT_NAME} FILES_MATCHING PATTERN "*.h")
     endif()
     if(MSLITE_ENABLE_CONVERTER)
-        install(FILES ${TOP_DIR}/mindspore/lite/include/converter.h DESTINATION ${CONVERTER_ROOT_DIR}/include
-                COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${TOP_DIR}/mindspore/lite/include/kernel_interface.h DESTINATION ${CONVERTER_ROOT_DIR}/include
                 COMPONENT ${RUNTIME_COMPONENT_NAME})
+        install(FILES ${TOP_DIR}/mindspore/lite/include/converter.h DESTINATION ${CONVERTER_ROOT_DIR}/include
+                COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(DIRECTORY ${TOP_DIR}/mindspore/lite/include/registry/ DESTINATION ${CONVERTER_ROOT_DIR}/include/registry
                 COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(FILES ${API_HEADER}  DESTINATION ${CONVERTER_ROOT_DIR}/include/api
                 COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(FILES ${MINDAPI_BASE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/mindapi/base
+        install(FILES ${MINDAPI_BASE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/mindapi/base
                 COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(FILES ${MINDAPI_IR_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/mindapi/ir
+        install(FILES ${MINDAPI_IR_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/mindapi/ir
+                COMPONENT ${RUNTIME_COMPONENT_NAME})
+        install(FILES ${ABSTRACT_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/abstract
+                COMPONENT ${RUNTIME_COMPONENT_NAME})
+        install(FILES ${BASE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/base
+                COMPONENT ${RUNTIME_COMPONENT_NAME})
+        install(FILES ${IR_DTYPE_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/ir/dtype
+                COMPONENT ${RUNTIME_COMPONENT_NAME})
+        install(FILES ${IR_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/ir
                 COMPONENT ${RUNTIME_COMPONENT_NAME})
         __install_white_list_ops()
+        install(FILES ${UTILS_HEADER} DESTINATION ${CONVERTER_ROOT_DIR}/include/core/utils
+                COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(DIRECTORY ${TOP_DIR}/mindspore/lite/build/schema/ DESTINATION ${CONVERTER_ROOT_DIR}/include/schema
                 COMPONENT ${RUNTIME_COMPONENT_NAME} FILES_MATCHING PATTERN "*.h" PATTERN "schema_generated.h" EXCLUDE)
         install(DIRECTORY ${flatbuffers_INC}/ DESTINATION ${CONVERTER_ROOT_DIR}/include/third_party
                 COMPONENT ${RUNTIME_COMPONENT_NAME})
-        install(DIRECTORY ${TOP_DIR}/third_party/proto/ DESTINATION ${CONVERTER_ROOT_DIR}/third_party/proto
-                COMPONENT ${RUNTIME_COMPONENT_NAME})
         install(DIRECTORY ${glog_LIBPATH}/../include/glog/ DESTINATION ${CONVERTER_ROOT_DIR}/include/third_party/glog
                 COMPONENT ${RUNTIME_COMPONENT_NAME} FILES_MATCHING PATTERN "*.h")
         install(DIRECTORY ${TOP_DIR}/third_party/securec/include/
@@ -981,7 +992,7 @@ else()
                     DESTINATION ${RUNTIME_LIB_DIR} RENAME libopencv_imgproc.so.4.5
                     COMPONENT ${RUNTIME_COMPONENT_NAME})
         endif()
-        if(NOT (MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE))
+        if(NOT MSLITE_ENABLE_CLOUD_FUSION_INFERENCE)
             __install_micro_wrapper()
             __install_micro_codegen()
         endif()
@@ -995,7 +1006,7 @@ else()
             install(TARGETS ${BENCHMARK_TRAIN_NAME} RUNTIME DESTINATION ${BENCHMARK_TRAIN_ROOT_DIR} COMPONENT
                     ${RUNTIME_COMPONENT_NAME})
         endif()
-        if(NOT (MSLITE_ENABLE_CLOUD_FUSION_INFERENCE OR MSLITE_ENABLE_CLOUD_INFERENCE))
+        if(NOT MSLITE_ENABLE_CLOUD_FUSION_INFERENCE)
             install(TARGETS cropper RUNTIME DESTINATION ${CROPPER_ROOT_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
             install(FILES ${TOP_DIR}/mindspore/lite/build/tools/cropper/cropper_mapping_cpu.cfg
                 DESTINATION ${CROPPER_ROOT_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
@@ -1066,8 +1077,10 @@ if(MSLITE_ENABLE_KERNEL_EXECUTOR)
             ${RUNTIME_INC_DIR}/api COMPONENT ${RUNTIME_COMPONENT_NAME})
     install(TARGETS kernel_executor DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
     install(TARGETS mindspore_core DESTINATION ${RUNTIME_LIB_DIR} COMPONENT ${RUNTIME_COMPONENT_NAME})
-    install(FILES ${glog_LIBPATH}/libmindspore_glog.so.0.4.0 DESTINATION ${RUNTIME_LIB_DIR}
-        RENAME libmindspore_glog.so.0 COMPONENT ${RUNTIME_COMPONENT_NAME})
+    if(MSLITE_ENABLE_CONVERTER)
+        install(FILES ${glog_LIBPATH}/libmindspore_glog.so.0.4.0 DESTINATION ${RUNTIME_LIB_DIR}
+            RENAME libmindspore_glog.so.0 COMPONENT ${RUNTIME_COMPONENT_NAME})
+    endif()
 endif()
 
 if(CMAKE_SYSTEM_NAME MATCHES "Windows")

cmake/package_mac.cmake

@@ -164,6 +164,7 @@ install(
     ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/ops
     ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/communication
     ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/profiler
+    ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/compression
     ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/rewrite
     ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/run_check
     ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/experimental

cmake/package_plugin.cmake

@@ -1,125 +0,0 @@
-# include dependency
-include(CMakePackageConfigHelpers)
-include(GNUInstallDirs)
-
-# prepare output directory
-file(REMOVE_RECURSE ${CMAKE_SOURCE_DIR}/output)
-file(MAKE_DIRECTORY ${CMAKE_SOURCE_DIR}/output)
-
-# cpack variables
-string(TOLOWER linux_${CMAKE_HOST_SYSTEM_PROCESSOR} PLATFORM_NAME)
-if(PYTHON_VERSION MATCHES "3.9")
-    set(CPACK_PACKAGE_FILE_NAME mindspore.py39)
-elseif(PYTHON_VERSION MATCHES "3.8")
-    set(CPACK_PACKAGE_FILE_NAME mindspore.py38)
-elseif(PYTHON_VERSION MATCHES "3.7")
-    set(CPACK_PACKAGE_FILE_NAME mindspore.py37)
-else()
-    message("Could not find 'Python 3.9' OR 'Python 3.8' or 'Python 3.7'")
-    return()
-endif()
-
-set(CPACK_GENERATOR "ZIP")
-set(CPACK_PACKAGE_DIRECTORY ${CMAKE_SOURCE_DIR}/output)
-
-set(INSTALL_LIB_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Installation directory for libraries")
-set(INSTALL_BASE_DIR ".")
-set(INSTALL_LIB_DIR "lib")
-set(INSTALL_PLUGIN_DIR "${INSTALL_LIB_DIR}/plugin")
-
-# set package files
-install(
-        TARGETS mindspore_shared_lib
-        DESTINATION ${INSTALL_LIB_DIR}
-        COMPONENT mindspore
-)
-
-if(ENABLE_D OR ENABLE_GPU)
-    install(
-            TARGETS api_lib
-            DESTINATION ${INSTALL_LIB_DIR}
-            COMPONENT mindspore
-    )
-endif()
-
-if(ENABLE_D)
-    install(
-            TARGETS mindspore_ascend
-            DESTINATION ${INSTALL_PLUGIN_DIR}
-            COMPONENT mindspore
-    )
-    if(ENABLE_MPI)
-        install(
-                TARGETS ascend_collective
-                DESTINATION ${INSTALL_PLUGIN_DIR}/ascend
-                COMPONENT mindspore
-        )
-    endif()
-    install(
-            TARGETS hccl_plugin
-            DESTINATION ${INSTALL_PLUGIN_DIR}/ascend
-            COMPONENT mindspore
-    )
-endif()
-
-if(ENABLE_ACL)
-    install(
-            TARGETS dvpp_utils
-            DESTINATION ${INSTALL_PLUGIN_DIR}/ascend
-            COMPONENT mindspore
-    )
-endif()
-
-if(ENABLE_GPU)
-    install(
-            TARGETS mindspore_gpu LIBRARY
-            DESTINATION ${INSTALL_PLUGIN_DIR}
-            COMPONENT mindspore
-            NAMELINK_SKIP
-    )
-    if(ENABLE_MPI)
-        install(
-                TARGETS nvidia_collective
-                DESTINATION ${INSTALL_PLUGIN_DIR}/gpu${CUDA_VERSION}
-                COMPONENT mindspore
-        )
-        if(CMAKE_SYSTEM_NAME MATCHES "Linux" AND GPU_BACKEND_CUDA)
-            install(FILES ${nccl_LIBPATH}/libnccl.so.2.7.6 DESTINATION ${INSTALL_PLUGIN_DIR}/gpu${CUDA_VERSION}
-                    RENAME libnccl.so.2 COMPONENT mindspore)
-        endif()
-    endif()
-    install(
-            TARGETS cuda_ops LIBRARY
-            DESTINATION ${INSTALL_PLUGIN_DIR}/gpu${CUDA_VERSION}
-            COMPONENT mindspore
-            NAMELINK_SKIP
-    )
-endif()
-
-if(ENABLE_AKG AND CMAKE_SYSTEM_NAME MATCHES "Linux")
-    if(ENABLE_GPU)
-        install(
-                TARGETS akg
-                DESTINATION ${INSTALL_PLUGIN_DIR}/gpu${CUDA_VERSION}
-                COMPONENT mindspore
-        )
-    endif()
-
-    if(ENABLE_D)
-        install(
-                TARGETS akg
-                DESTINATION ${INSTALL_PLUGIN_DIR}/ascend
-                COMPONENT mindspore
-        )
-    endif()
-endif()
-
-if(ENABLE_SYM_FILE)
-    install(CODE "\
-      execute_process(COMMAND ${CMAKE_COMMAND} -DMS_PACK_ROOT_DIR=${CPACK_PACKAGE_DIRECTORY} \
-        -DMS_INSTALL_DIR=${CPACK_PACKAGE_DIRECTORY}/_CPack_Packages/${CMAKE_HOST_SYSTEM_NAME}/${CPACK_GENERATOR} \
-        -DMS_PACKAGE_FILE_NAME=${CPACK_PACKAGE_FILE_NAME} -P ${CMAKE_SOURCE_DIR}/cmake/plugin_debuginfo_script.cmake)"
-    )
-endif()
-
-include(CPack)

cmake/package_tar.cmake

@@ -100,7 +100,7 @@ if(ENABLE_MINDDATA)
     if(ENABLE_ACL)
         install(
                 TARGETS dvpp_utils
-                DESTINATION ${INSTALL_PLUGIN_DIR}/ascend
+                DESTINATION ${INSTALL_PLUGIN_DIR}
                 COMPONENT mindspore
         )
     endif()
@@ -180,7 +180,6 @@ install(
 ## config files
 install(
         FILES ${CMAKE_SOURCE_DIR}/config/op_info.config
-              ${CMAKE_SOURCE_DIR}/config/super_bar_config.json
         DESTINATION ${INSTALL_CFG_DIR}
         COMPONENT mindspore
 )

cmake/package_win.cmake

@@ -199,9 +199,10 @@ if(ENABLE_GPU)
     COMPONENT mindspore
   )
   install(
-    TARGETS mindspore_gpu
+    TARGETS mindspore_gpu LIBRARY
     DESTINATION ${INSTALL_PLUGIN_DIR}
     COMPONENT mindspore
+    NAMELINK_SKIP
   )
 endif()
 
@@ -249,6 +250,7 @@ install(
   ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/ops
   ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/communication
   ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/profiler
+  ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/compression
   ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/rewrite
   ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/run_check
   ${CMAKE_SOURCE_DIR}/mindspore/python/mindspore/experimental

cmake/plugin_debuginfo_script.cmake

@@ -1,34 +0,0 @@
-set(CMAKE_OBJCOPY $ENV{CROSS_COMPILE}objcopy)
-set(CMAKE_STRIP $ENV{CROSS_COMPILE}strip)
-
-file(GLOB ALL_BINARIES
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/*.so
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/lib/*.so
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/lib/plugin/*.so*
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/lib/plugin/*/*.so
-        )
-
-foreach(item ${ALL_BINARIES})
-    execute_process(
-            COMMAND ${CMAKE_OBJCOPY} --only-keep-debug ${item} ${item}.sym
-            WORKING_DIRECTORY ${MS_PACK_ROOT_DIR}
-    )
-    execute_process(
-            COMMAND ${CMAKE_STRIP} ${item}
-            WORKING_DIRECTORY ${MS_PACK_ROOT_DIR}
-    )
-endforeach()
-
-file(GLOB DEBUG_SYM_FILE
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/*.sym
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/lib/*.sym
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/lib/plugin/*.sym
-        ${MS_INSTALL_DIR}/${MS_PACKAGE_FILE_NAME}/lib/plugin/*/*.sym
-        )
-
-file(MAKE_DIRECTORY ${MS_PACK_ROOT_DIR}/debug_info)
-file(COPY ${DEBUG_SYM_FILE} DESTINATION ${MS_PACK_ROOT_DIR}/debug_info/)
-file(REMOVE_RECURSE ${DEBUG_SYM_FILE})
-execute_process(COMMAND ${CMAKE_COMMAND} -E tar cfv ${MS_PACKAGE_FILE_NAME}.debuginfo.zip debug_info/
-        --format=zip WORKING_DIRECTORY ${MS_PACK_ROOT_DIR})
-file(REMOVE_RECURSE ${MS_PACK_ROOT_DIR}/debug_info)

cmake/utils.cmake

@@ -484,50 +484,4 @@ function(src_separate_compile)
     endwhile()
     set(${STUDENT_OBJECT_SIZE} "${OBJECT_COUNT}" PARENT_SCOPE)
     message("${STUDENT_OBJECT_SIZE} object count is ${OBJECT_COUNT}")
-endfunction()
-
-function(enable_target_when_only_build_plugins target)
-    if(ONLY_BUILD_DEVICE_PLUGINS)
-        set_target_properties(${target} PROPERTIES EXCLUDE_FROM_ALL FALSE)
-    endif()
-endfunction()
-
-function(disable_target_when_only_build_plugins target)
-    if(ONLY_BUILD_DEVICE_PLUGINS)
-        get_property(is_set TARGET ${target} PROPERTY EXCLUDE_FROM_ALL)
-        if(NOT DEFINED is_set)
-            set_target_properties(${target} PROPERTIES EXCLUDE_FROM_ALL TRUE)
-        endif()
-    endif()
-endfunction()
-
-function(enable_directory_when_only_build_plugins dir)
-    get_property(targets DIRECTORY ${dir} PROPERTY BUILDSYSTEM_TARGETS)
-    foreach(target ${targets})
-        enable_target_when_only_build_plugins(${target})
-    endforeach()
-    get_property(items DIRECTORY ${dir} PROPERTY SUBDIRECTORIES)
-    foreach(item ${items})
-        enable_directory_when_only_build_plugins(${item})
-    endforeach()
-endfunction()
-
-function(disable_directory_when_only_build_plugins dir)
-    get_property(targets DIRECTORY ${dir} PROPERTY BUILDSYSTEM_TARGETS)
-    foreach(target ${targets})
-        disable_target_when_only_build_plugins(${target})
-    endforeach()
-    get_property(items DIRECTORY ${dir} PROPERTY SUBDIRECTORIES)
-    foreach(item ${items})
-        disable_directory_when_only_build_plugins(${item})
-    endforeach()
-endfunction()
-
-function(add_subdirectory_with_faster_option dir)
-    if(ONLY_BUILD_DEVICE_PLUGINS)
-        add_subdirectory(${dir})
-        disable_directory_when_only_build_plugins(${dir})
-    else()
-        add_subdirectory(${dir})
-    endif()
-endfunction()
+endfunction()

config/OWNERS

@@ -1,9 +0,0 @@
-approvers:
-- jjfeing
-- laiyongqiang
-- yuchaojie
-- zhoufeng
-- guoqi1024
-
-options:
-    no_parent_owners: true

config/super_bar_config.json

@@ -1,495 +0,0 @@
-{
-  "NodeAttrMap": {
-    "AvgPool3DD": {
-      "ksize": "kernel_size",
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "AvgPool3DGradD": {
-      "orig_input_shape": "origin_input_shape",
-      "ksize": "kernel_size",
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "AvgPoolGradD": {
-      "orig_input_shape": "x_origin",
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "data_format": "format"
-    },
-    "AvgPoolGrad": {
-      "orig_input_shape": "x_origin",
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "data_format": "format"
-    },
-    "AccumulateNV2": {
-      "N": "n"
-    },
-    "AddN": {
-      "N": "n"
-    },
-    "Conv2D": {
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "Dilation2D": {
-      "strides": "stride"
-    },
-    "Conv3DTransposeD": {
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "Conv3D": {
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "Conv3DBackpropInputD": {
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "Conv3DBackpropFilterD": {
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "Conv2DTransposeD": {
-      "input_size": "input_sizes",
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "MaxPoolWithArgmax": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode"
-    },
-    "SoftmaxGradExt": {
-      "axes": "axis",
-      "keep_dims": "keepdims"
-    },
-    "Conv2DBackpropFilterD": {
-      "filter_size": "filter_sizes",
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "Conv2DBackpropInputD": {
-      "input_size": "input_sizes",
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "Conv2DBackpropFilter": {
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "Conv2DBackpropInput": {
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "ConcatD": {
-      "concat_dim": "axis"
-    },
-    "DepthwiseConv2D": {
-      "strides": "stride",
-      "dilations": "dilation",
-      "pads": "pad_list",
-      "data_format": "format",
-      "offfset_x": "offset_a"
-    },
-    "ExtractVolumePatches": {
-      "ksizes": "kernel_size"
-    },
-    "L2Normalize": {
-      "eps": "epsilon"
-    },
-    "L2NormalizeGrad": {
-      "dim": "axis",
-      "eps": "epsilon"
-    },
-    "MaxPoolGradWithArgmax": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode"
-    },
-    "BiasAddGrad": {
-      "data_format": "format"
-    },
-    "FusedDbnDw": {
-      "filter_size": "filter_sizes",
-      "strides": "stride",
-      "pads": "pad_list",
-      "dilations": "dilation",
-      "data_format": "format"
-    },
-    "MaxPool": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "data_format": "format"
-    },
-    "ReduceMeanD": {
-      "axes": "axis"
-    },
-    "ReduceSumD": {
-      "axes": "axis"
-    },
-    "ReduceAnyD": {
-      "axes": "axis"
-    },
-    "ReduceMaxD": {
-      "axes": "axis"
-    },
-    "ReduceMinD": {
-      "axes": "axis"
-    },
-    "ReduceAllD": {
-      "axes": "axis"
-    },
-    "ReduceProdD": {
-      "axes": "axis"
-    },
-    "ReduceStd": {
-      "dim": "axis",
-      "keepdim": "keep_dims"
-    },
-    "SoftmaxV2": {
-      "axes": "axis"
-    },
-    "LogSoftmaxV2": {
-      "axes": "axis"
-    },
-    "ArgMaxD": {
-      "dimension": "axis"
-    },
-    "BatchMatMul": {
-      "adj_x1": "transpose_x1",
-      "adj_x2": "transpose_x2"
-    },
-    "BatchMatMulV2": {
-      "adj_x1": "transpose_x1",
-      "adj_x2": "transpose_x2"
-    },
-    "BatchNormal": {
-      "data_format": "format"
-    },
-    "ArgMaxWithValue": {
-      "dimension": "axis"
-    },
-    "SplitD": {
-      "split_dim": "axis",
-      "num_split": "output_num"
-    },
-    "BiasAdd": {
-      "data_format": "format"
-    },
-    "SliceD": {
-      "offsets": "begin"
-    },
-    "MaxPoolGrad": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "data_format": "format"
-    },
-    "MaxPool3D": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "MaxPool3DGrad": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "pads": "pad_list",
-      "data_format": "format"
-    },
-    "MaxPoolGradGrad": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "data_format": "format"
-    },
-    "AvgPool": {
-      "ksize": "kernel_size",
-      "padding": "pad_mode",
-      "data_format": "format"
-    },
-    "BatchNorm": {
-      "data_format": "format"
-    },
-    "BatchNormGrad": {
-      "data_format": "format"
-    },
-    "ArgMin": {
-      "dimension": "axis"
-    },
-    "ArgMinD": {
-      "dimension": "axis"
-    },
-    "LpNorm": {
-      "axes": "axis",
-      "keepdim": "keep_dims"
-    },
-    "SmoothL1LossV2": {
-      "sigma": "beta"
-    },
-    "Roll": {
-      "shifts": "shift",
-      "dims": "axis"
-    },
-    "SmoothL1LossGradV2": {
-      "sigma": "beta"
-    },
-    "Centralization": {
-      "axes": "axis"
-    },
-    "MaxPool3DGradGradD": {
-      "ksize": "kernel_size",
-      "pads": "pad_list",
-      "data_format": "format"
-    }
-  },
-  "AttrDefaultValue": {
-    "Log": {
-      "base": "-1.0",
-      "scale": "1.0",
-      "shift": "0.0"
-    },
-    "ScatterNdUpdate": {
-      "use_locking": "false"
-    },
-    "OneHotD": {
-      "axis": "-1"
-    },
-    "Iou": {
-      "mode": "iou",
-      "eps": "1.0"
-    },
-    "GatherV2D": {
-      "axis": "-1"
-    },
-    "MaxPoolGrad": {
-      "data_format": "NHWC"
-    },
-    "ResizeNearestNeighborV2D": {
-      "align_corners": "false",
-      "half_pixel_centers": "false"
-    },
-    "ResizeNearestNeighborV2GradD": {
-      "align_corners": "false",
-      "half_pixel_centers": "false"
-    },
-    "MaxPool3D": {
-      "pads": "0,0,0",
-      "dilation": "1,1,1",
-      "ceil_mode": "0"
-    },
-    "BasicLSTMCellCStateGradV2": {
-      "gate_order": "ijfo"
-    }
-  },
-  "InputOrders": {
-    "LogSoftmaxGrad": [
-      1,
-      0
-    ],
-    "LayerNormGrad": [
-      1,
-      0,
-      2,
-      3,
-      4
-    ],
-    "LayerNormBetaGammaBackprop": [
-      1,
-      0,
-      2,
-      3
-    ],
-    "LayerNormXBackprop": [
-      1,
-      0,
-      2,
-      3,
-      4
-    ],
-    "LayerNormXBackpropV2": [
-      1,
-      0,
-      2,
-      3,
-      4
-    ],
-    "ApplyCenteredRMSPropD": [
-      0,
-      1,
-      2,
-      3,
-      5,
-      6,
-      7,
-      8,
-      4
-    ],
-    "Conv2DBackpropInputD": [
-      1,
-      0
-    ],
-    "Conv2DBackpropFilterD": [
-      1,
-      0
-    ],
-    "MinimumGrad": [
-      2,
-      0,
-      1
-    ],
-    "MaximumGrad": [
-      2,
-      0,
-      1
-    ],
-    "StridedSliceGrad": [
-      1,
-      2,
-      3,
-      4,
-      0
-    ],
-    "Conv2DBackpropInput": [
-      2,
-      1,
-      0
-    ],
-    "Conv2DBackpropFilter": [
-      1,
-      2,
-      0
-    ],
-    "FusionOp_Conv2DBackpropInputD_AddN_ReluGradV2": [
-      1,
-      0,
-      2,
-      3
-    ],
-    "FusionOp_Conv2DBackpropInputD_Add_ReluGradV2": [
-      1,
-      0,
-      2,
-      3
-    ],
-    "FusionOp_Conv2DBackpropInputD_ReluGradV2": [
-      1,
-      0,
-      2
-    ],
-    "FusionOp_Conv2DBackpropInputD_Relu": [
-      1,
-      0,
-      2
-    ],
-    "FusionOp_Conv2DBackpropInputD_LeakyRelu": [
-      1,
-      0,
-      2
-    ],
-    "FusionOp_Conv2DBackpropInputD_PRelu": [
-      1,
-      0,
-      2
-    ],
-    "FusionOp_Conv2DBackpropInputD_Add": [
-      1,
-      0,
-      2
-    ]
-  },
-  "SkipDynamicCompileStatic": [
-    "SoftmaxV2",
-    "PRelu",
-    "Trunc",
-    "AccumulateNV2",
-    "SoftmaxCrossEntropyWithLogits",
-    "ReduceMeanD",
-    "SquareSumV1",
-    "SplitVD",
-    "BiasAddGrad"
-  ],
-  "SkipNodesComments": {
-    "Im2col": "not support int8, uint8, float16 in op json, need add pass",
-    "BroadcastTo": "The name is occupied",
-    "DynamicBroadcastTo ": "The name is occupied",
-    "BatchToSpaceD ": "attr type is listInt, not listListInt",
-    "BatchToSpaceNDD ": "attr type is listInt, not listListInt",
-    "SpaceToBatchD ": "attr type is listInt, not listListInt",
-    "SpaceToBatchNDD ": "attr type is listInt, not listListInt",
-    "DynamicGRUV2": "input4 is None, GE will change to hidden op by pass",
-    "DynamicRNN ": "input4 is None, GE will change to hidden op by pass",
-    "KLDivLossGrad": " Accuracy issues",
-    "ScatterNdUpdate": " not support int8 in op json",
-    "ScatterNdAdd": "not support int8 in op json",
-    "UnsortedSegmentSum ": " check support failed when shape is -2",
-    "ConcatOffset": "Hadn't adapted tbe implementation",
-    "MirrorPad ": "Hadn't adapted tbe implementation",
-    "InplaceIndexAdd": "check support failed if var has only one dimension",
-    "Expand": "Hadn't adapted tbe implementation",
-    "ExpandD": "Hadn't adapted tbe implementation",
-    "Cross ": "Hadn't adapted tbe implementation",
-    "LinSpaceD": "Hadn't adapted tbe implementation",
-    "Cast ": "Accuracy issues",
-    "AvgPool3DGradD": "second device format is facz_3d, but in json, the key is ndhwc",
-    "DataFormatDimMap ": "attr order swap",
-    "DepthwiseConv2D": "Accuracy issues(second format is error in python)",
-    "ACos": "dynamic impl error",
-    "TransData ": "support boll",
-    "ScatterNdD ": "Accuracy issues",
-    "Trace": "Hadn't adapted tbe implementation",
-    "AssignAdd": "Frac_nz in pangu not support",
-    "Range": "not support dynamic shape with tiling failed",
-    "AtomicAddrClean": "need to clean addr larger than 2G, int32 is not enough"
-  },
-  "SkipNodes": [
-    "Im2col",
-    "BroadcastTo",
-    "DynamicBroadcastTo",
-    "BatchToSpaceD",
-    "BatchToSpaceNDD",
-    "SpaceToBatchD",
-    "SpaceToBatchNDD",
-    "DynamicGRUV2",
-    "DynamicRNN",
-    "KLDivLossGrad",
-    "ScatterNdUpdate",
-    "ScatterNdAdd",
-    "ConcatOffset",
-    "MirrorPad",
-    "InplaceIndexAdd",
-    "Expand",
-    "ExpandD",
-    "Cross",
-    "LinSpaceD",
-    "Cast",
-    "AvgPool3DGradD",
-    "DataFormatDimMap",
-    "DepthwiseConv2D",
-    "Trace",
-    "ACos",
-    "TransData",
-    "ScatterNdD",
-    "AssignAdd",
-    "Range",
-    "AtomicAddrClean",
-    "Assign"
-  ],
-  "FallbackOps": {
-    "DeformableOffsets": [
-      1,
-      2
-    ]
-  }
-}

docs/api/api_python/amp/mindspore.amp.all_finite.rst

@@ -12,6 +12,7 @@ mindspore.amp.all_finite
 
     参数：
         - **inputs** (Union(tuple(Tensor), list(Tensor))) - 可迭代的Tensor。
+        - **status** (Tensor) - 溢出检测时所需要的初始状态，仅在Ascend需要。默认值：None。
 
     返回：
         Tensor，布尔类型的标量Tensor。

docs/api/api_python/amp/mindspore.amp.init_status.rst

@@ -0,0 +1,12 @@
+mindspore.amp.init_status
+===========================
+
+.. py:function:: mindspore.amp.init_status()
+
+    初始化溢出状态检测变量。
+
+    .. note::
+        该接口仅在Ascend后端有效，在GPU、CPU上调用的返回值没有作用。
+
+    返回：
+        Tensor，shape为 (8,) 。

docs/api/api_python/dataset/dataset_method/iterator/mindspore.dataset.Dataset.create_dict_iterator.rst

@@ -1,14 +1,13 @@
 mindspore.dataset.Dataset.create_dict_iterator
 ==============================================
 
-.. py:method:: mindspore.dataset.Dataset.create_dict_iterator(num_epochs=-1, output_numpy=False, do_copy=True)
+.. py:method:: mindspore.dataset.Dataset.create_dict_iterator(num_epochs=-1, output_numpy=False)
 
     基于数据集对象创建迭代器。输出的数据为字典类型。
 
     参数：
         - **num_epochs** (int, 可选) - 迭代器可以迭代的最大次数。默认值：-1，迭代器可以迭代无限次。
         - **output_numpy** (bool, 可选) - 输出的数据是否转为NumPy类型。如果为False，迭代器输出的每列数据类型为MindSpore.Tensor，否则为NumPy。默认值：False。
-        - **do_copy** (bool, 可选) - 当参数 `output_numpy` 为False，即输出数据类型为mindspore.Tensor时，可以将此参数指定为False以减少拷贝，获得更好的性能。默认值：True。
 
     返回：
         DictIterator，基于数据集对象创建的字典迭代器。

docs/api/api_python/dataset/dataset_method/operation/mindspore.dataset.Dataset.map.rst

@@ -12,9 +12,9 @@ mindspore.dataset.Dataset.map
     最后一个数据增强的输出列的列名由 `output_columns` 指定，如果没有指定 `output_columns` ，输出列名与 `input_columns` 一致。
 
     - 如果使用的是 `mindspore` `dataset` 提供的数据增强（
-      `vision类 <https://mindspore.cn/docs/zh-CN/master/api_python/mindspore.dataset.transforms.html#视觉>`_ ，
-      `nlp类 <https://mindspore.cn/docs/zh-CN/master/api_python/mindspore.dataset.transforms.html#文本>`_ ，
-      `audio类 <https://mindspore.cn/docs/zh-CN/master/api_python/mindspore.dataset.transforms.html#音频>`_ ），请使用如下参数：
+      `vision类 <https://mindspore.cn/docs/zh-CN/r2.0.0-alpha/api_python/mindspore.dataset.transforms.html#视觉>`_ ，
+      `nlp类 <https://mindspore.cn/docs/zh-CN/r2.0.0-alpha/api_python/mindspore.dataset.transforms.html#文本>`_ ，
+      `audio类 <https://mindspore.cn/docs/zh-CN/r2.0.0-alpha/api_python/mindspore.dataset.transforms.html#音频>`_ ），请使用如下参数：
 
       .. image:: map_parameter_cn.png
 
@@ -31,9 +31,9 @@ mindspore.dataset.Dataset.map
 
           - python_multiprocessing (bool, 可选) - 启用Python多进程模式加速map操作。当传入的 `operations` 计算量很大时，开启此选项可能会有较好效果。默认值：False。
           - max_rowsize (int, 可选) - 指定在多进程之间复制数据时，共享内存分配的最大空间，仅当 `python_multiprocessing` 为True时，该选项有效。默认值：16，单位为MB。
-          - cache (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+          - cache (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
           - callbacks (DSCallback, list[DSCallback], 可选) - 要调用的Dataset回调函数列表。默认值：None。
-          - offload (bool, 可选) - 是否进行异构硬件加速，详情请阅读 `数据准备异构加速 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/dataset_offload.html>`_ 。默认值：None。
+          - offload (bool, 可选) - 是否进行异构硬件加速，详情请阅读 `数据准备异构加速 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/dataset_offload.html>`_ 。默认值：None。
 
     .. note::
         - `operations` 参数接收 `TensorOperation` 类型的数据处理操作，以及用户定义的Python函数(PyFuncs)。

docs/api/api_python/dataset/dataset_method/operation/mindspore.dataset.Dataset.split.rst

@@ -7,6 +7,7 @@ mindspore.dataset.Dataset.split
 
     参数：
         - **sizes** (Union[list[int], list[float]]) - 如果指定了一列整数[s1, s2, …, sn]，数据集将被拆分为n个大小为s1、s2、...、sn的数据集。如果所有输入大小的总和不等于原始数据集大小，则报错。如果指定了一列浮点数[f1, f2, …, fn]，则所有浮点数必须介于0和1之间，并且总和必须为1，否则报错。数据集将被拆分为n个大小为round(f1*K)、round(f2*K)、...、round(fn*K)的数据集，其中K是原始数据集的大小。
+
           如果round四舍五入计算后：
 
           - 任何子数据集的的大小等于0，都将发生错误。

docs/api/api_python/dataset/dataset_method/operation/mindspore.dataset.TextBaseDataset.build_sentencepiece_vocab.rst

@@ -6,8 +6,6 @@ mindspore.dataset.TextBaseDataset.build_sentencepiece_vocab
     迭代源数据集对象获取数据并构建SentencePiece词汇表。
     源数据集要求的是文本类数据集。
 
-    .. note:: mindspore.dataset.Dataset.build_sentencepiece_vocab 从2.0版本开始弃用。请使用mindspore.dataset.text.SentencePieceVocab.from_dataset代替。
-
     参数：
         - **columns** (list[str]) - 指定 `build_sentencepiece_vocab` 操作的输入列，会从该列获取数据构造词汇表。
         - **vocab_size** (int) - 词汇表的容量。

docs/api/api_python/dataset/dataset_method/operation/mindspore.dataset.TextBaseDataset.build_vocab.rst

@@ -8,8 +8,6 @@ mindspore.dataset.TextBaseDataset.build_vocab
 
     收集数据集中所有的不重复单词。返回 `top_k` 个最常见的单词组成的词汇表（如果指定了 `top_k` ）。
 
-    .. note:: mindspore.dataset.Dataset.build_vocab 从2.0版本开始弃用。请使用mindspore.dataset.text.Vocab.from_dataset代替。
-
     参数：
         - **columns** (Union[str, list[str]]) - 指定 `build_vocab` 操作的输入列，会从该列获取数据构造词汇表。
         - **freq_range** (tuple[int]) - 由(min_frequency, max_frequency)组成的整数元组，代表词汇出现的频率范围，在这个频率范围的词汇会被保存下来。

docs/api/api_python/dataset/mindspore.dataset.AGNewsDataset.rst

@@ -21,7 +21,7 @@ mindspore.dataset.AGNewsDataset
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.AmazonReviewDataset.rst

@@ -23,7 +23,7 @@ mindspore.dataset.AmazonReviewDataset
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.ArgoverseDataset.rst

@@ -1,7 +1,7 @@
 mindspore.dataset.ArgoverseDataset
 ====================================
 
-.. py:class:: mindspore.dataset.ArgoverseDataset(data_dir, column_names="graph", num_parallel_workers=1, shuffle=None, python_multiprocessing=True, perf_mode=True)
+.. py:class:: mindspore.dataset.ArgoverseDataset(data_dir, column_names="graph", shuffle=None, num_parallel_workers=1, python_multiprocessing=True, perf_mode=True)
 
     加载argoverse数据集并进行图（Graph）初始化。
 
@@ -16,45 +16,6 @@
         - **python_multiprocessing** (bool，可选) - 启用Python多进程模式加速运算。默认值：True。当传入 `source` 的Python对象的计算量很大时，开启此选项可能会有较好效果。
         - **perf_mode** (bool，可选) - 遍历创建的dataset对象时获得更高性能的模式（在此过程中将调用 `__getitem__` 方法）。默认值：True，将Graph的所有数据（如边的索引、节点特征和图的特征）都作为图特征进行存储。
 
-    异常：
-        - **TypeError** - 如果 `data_dir` 不是str类型。
-        - **TypeError** - 如果 `num_parallel_workers` 不是int类型。
-        - **TypeError** - 如果 `shuffle` 不是bool类型。
-        - **TypeError** - 如果 `python_multiprocessing` 不是bool类型。
-        - **TypeError** - 如果 `perf_mode` 不是bool类型。
-        - **RuntimeError** - 如果 `data_dir` 无效或不存在。
-        - **ValueError** - `num_parallel_workers` 参数超过系统最大线程数。
-
-    **关于Argoverse数据集：**
-
-    Argoverse是第一个包含高精地图的数据集，它包含了290KM的带有几何形状和语义信息的高精度地图数据。
-
-    可以将数据集文件解压缩到以下结构中，并通过MindSpore的API读取：
-
-    .. code-block::
-
-        .
-        └── argoversedataset_dir
-            ├── train
-            │    ├──...
-            ├── val
-            │    └──...
-            ├── test
-            │    └──...
-
-    **引用：**
-
-    .. code-block::
-
-        @inproceedings{Argoverse,
-        author     = {Ming-Fang Chang and John W Lambert and Patsorn Sangkloy and Jagjeet Singh
-                   and Slawomir Bak and Andrew Hartnett and De Wang and Peter Carr
-                   and Simon Lucey and Deva Ramanan and James Hays},
-        title      = {Argoverse: 3D Tracking and Forecasting with Rich Maps},
-        booktitle  = {Conference on Computer Vision and Pattern Recognition (CVPR)},
-        year       = {2019}
-        }
-
 
     .. py:method:: load()
 

docs/api/api_python/dataset/mindspore.dataset.CLUEDataset.rst

@@ -22,7 +22,7 @@ mindspore.dataset.CLUEDataset
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     根据给定的 `task` 参数 和 `usage` 配置，数据集会生成不同的输出列：
 

docs/api/api_python/dataset/mindspore.dataset.CSVDataset.rst

@@ -21,7 +21,7 @@
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_files` 参数所指向的文件无效或不存在。

docs/api/api_python/dataset/mindspore.dataset.Caltech256Dataset.rst

@@ -16,7 +16,7 @@ mindspore.dataset.Caltech256Dataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含任何数据文件。

docs/api/api_python/dataset/mindspore.dataset.CelebADataset.rst

@@ -18,7 +18,7 @@ mindspore.dataset.CelebADataset
         - **num_samples** (int, 可选) - 指定从数据集中读取的样本数，可以小于数据集总数。默认值：None，读取全部样本图片。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
         - **decrypt** (callable, 可选) - 图像解密函数，接受加密的图片路径并返回bytes类型的解密数据。默认值：None，不进行解密。
 
     异常：

docs/api/api_python/dataset/mindspore.dataset.Cifar100Dataset.rst

@@ -17,7 +17,7 @@ mindspore.dataset.Cifar100Dataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。

docs/api/api_python/dataset/mindspore.dataset.Cifar10Dataset.rst

@@ -17,7 +17,7 @@ mindspore.dataset.Cifar10Dataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。

docs/api/api_python/dataset/mindspore.dataset.CityscapesDataset.rst

@@ -21,7 +21,7 @@ mindspore.dataset.CityscapesDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含任何数据文件。

docs/api/api_python/dataset/mindspore.dataset.CoNLL2000Dataset.rst

@@ -22,7 +22,7 @@ mindspore.dataset.CoNLL2000Dataset
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。指定此参数后， `num_samples` 表示每个分片的最大样本数。默认值：None。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。只有当指定了 `num_shards` 时才能指定此参数。默认值：None。
         - **num_parallel_workers** (int, 可选) - 指定读取数据的工作线程数。默认值：None，使用mindspore.dataset.config中配置的线程数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.CocoDataset.rst

@@ -16,7 +16,7 @@
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None，表2中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
         - **extra_metadata** (bool, 可选) - 用于指定是否额外输出一个数据列用于表示图片元信息。如果为True，则将额外输出一个名为 `[_meta-filename, dtype=string]` 的数据列。默认值：False。
         - **decrypt** (callable, 可选) - 图像解密函数，接受加密的图片路径并返回bytes类型的解密数据。默认值：None，不进行解密。
 

docs/api/api_python/dataset/mindspore.dataset.DBpediaDataset.rst

@@ -22,7 +22,7 @@ mindspore.dataset.DBpediaDataset
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.DIV2KDataset.rst

@@ -20,7 +20,7 @@ mindspore.dataset.DIV2KDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含任何数据文件。

docs/api/api_python/dataset/mindspore.dataset.DatasetCache.rst

@@ -5,7 +5,7 @@ mindspore.dataset.DatasetCache
 
     创建数据缓存客户端实例。
 
-    关于单节点数据缓存的使用，请参阅 `单节点数据缓存教程 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。
+    关于单节点数据缓存的使用，请参阅 `单节点数据缓存教程 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。
 
     参数：
         - **session_id** (int) - 当前数据缓存客户端的会话ID，用户在命令行开启缓存服务端后可通过 `cache_admin -g` 获取。

docs/api/api_python/dataset/mindspore.dataset.EMnistDataset.rst

@@ -18,7 +18,7 @@ mindspore.dataset.EMnistDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - 同时指定了 `sampler` 和 `shuffle` 参数。

docs/api/api_python/dataset/mindspore.dataset.EnWik9Dataset.rst

@@ -3,13 +3,15 @@ mindspore.dataset.EnWik9Dataset
 
 .. py:class:: mindspore.dataset.EnWik9Dataset(dataset_dir, num_samples=None, num_parallel_workers=None, shuffle=True, num_shards=None, shard_id=None, cache=None)
 
-    读取和解析EnWik9数据集。
+    读取和解析EnWik9 Full和EnWik9 Polarity数据集。
 
     生成的数据集有一列 `[text]` ，数据类型为string。
 
     参数：
         - **dataset_dir** (str) - 包含数据集文件的根目录路径。
-        - **num_samples** (int, 可选) - 指定从数据集中读取的样本数。默认值：None，读取所有样本。
+        - **num_samples** (int, 可选) - 指定从数据集中读取的样本数。
+          对于Polarity数据集， 'train'将读取360万个训练样本， 'test'将读取40万个测试样本， 'all'将读取所有400万个样本。
+          对于Full数据集， 'train'将读取300万个训练样本， 'test'将读取65万个测试样本， 'all'将读取所有365万个样本。默认值：None，读取所有样本。
         - **num_parallel_workers** (int, 可选) - 指定读取数据的工作线程数。默认值：None，使用mindspore.dataset.config中配置的线程数。
         - **shuffle** (Union[bool, Shuffle], 可选) - 每个epoch中数据混洗的模式，支持传入bool类型与枚举类型进行指定。默认值：True。
           如果 `shuffle` 为False，则不混洗，如果 `shuffle` 为True，等同于将 `shuffle` 设置为mindspore.dataset.Shuffle.GLOBAL。
@@ -20,7 +22,7 @@ mindspore.dataset.EnWik9Dataset
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.FakeImageDataset.rst

@@ -18,7 +18,7 @@ mindspore.dataset.FakeImageDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - 同时指定了 `sampler` 和 `shuffle` 参数。

docs/api/api_python/dataset/mindspore.dataset.FashionMnistDataset.rst

@@ -17,7 +17,7 @@ mindspore.dataset.FashionMnistDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。

docs/api/api_python/dataset/mindspore.dataset.FlickrDataset.rst

@@ -17,7 +17,7 @@
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None，表2中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含任何数据文件。

docs/api/api_python/dataset/mindspore.dataset.Food101Dataset.rst

@@ -1,102 +0,0 @@
-mindspore.dataset.Food101Dataset
-================================
-
-.. py:class:: mindspore.dataset.Food101Dataset(dataset_dir, usage=None, num_samples=None, num_parallel_workers=None, shuffle=None, decode=False, sampler=None, num_shards=None, shard_id=None, cache=None)
-
-    读取和解析Food101数据集的源文件构建数据集。
-
-    生成的数据集有两列: `[image, label]` 。 `image` 列的数据类型为uint8。 `label` 列的数据类型为string。
-
-    参数：
-        - **dataset_dir** (str) - 包含数据集文件的根目录路径。
-        - **usage** (str, 可选) - 指定数据集的子集，可取值为 'train'、'test' 或 'all'。
-          取值为'train'时将会读取75,750个训练样本，取值为'test'时将会读取25,250个测试样本，取值为'all'时将会读取全部101,000个样本。默认值：None，读取全部样本图片。
-        - **num_samples** (int, 可选) - 指定从数据集中读取的样本数，可以小于数据集总数。默认值：None，读取全部样本图片。
-        - **num_parallel_workers** (int, 可选) - 指定读取数据的工作线程数。默认值：None，使用mindspore.dataset.config中配置的线程数。
-        - **shuffle** (bool, 可选) - 是否混洗数据集。默认值：None，下表中会展示不同参数配置的预期行为。
-        - **decode** (bool, 可选) - 是否对读取的图片进行解码操作。默认值：False，不解码。
-        - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None，下表中会展示不同配置的预期行为。
-        - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
-        - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
-
-    异常：
-        - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。
-        - **RuntimeError** - 同时指定了 `sampler` 和 `shuffle` 参数。
-        - **RuntimeError** - 同时指定了 `sampler` 和 `num_shards` 参数或同时指定了 `sampler` 和 `shard_id` 参数。
-        - **RuntimeError** - 指定了 `num_shards` 参数，但是未指定 `shard_id` 参数。
-        - **RuntimeError** - 指定了 `shard_id` 参数，但是未指定 `num_shards` 参数。
-        - **ValueError** - `shard_id` 参数错误，小于0或者大于等于 `num_shards` 。
-        - **ValueError** - `num_parallel_workers` 参数超过系统最大线程数。
-        - **ValueError** - `usage` 参数取值不为'train'、'test'或'all'。
-        - **ValueError** - `dataset_dir` 指定的文件夹不存在。
-
-    .. note:: 此数据集可以指定参数 `sampler` ，但参数 `sampler` 和参数 `shuffle` 的行为是互斥的。下表展示了几种合法的输入参数组合及预期的行为。
-
-    .. list-table:: 配置 `sampler` 和 `shuffle` 的不同组合得到的预期排序结果
-       :widths: 25 25 50
-       :header-rows: 1
-
-       * - 参数 `sampler`
-         - 参数 `shuffle`
-         - 预期数据顺序
-       * - None
-         - None
-         - 随机排列
-       * - None
-         - True
-         - 随机排列
-       * - None
-         - False
-         - 顺序排列
-       * - `sampler` 实例
-         - None
-         - 由 `sampler` 行为定义的顺序
-       * - `sampler` 实例
-         - True
-         - 不允许
-       * - `sampler` 实例
-         - False
-         - 不允许
-
-    **关于Food101数据集：**
-    
-    Food101是一个具有挑战性的数据集，包含101种食品类别，共101000张图片。每一个类别有250张测试图片和750张训练图片。所有图像都被重新缩放，最大边长为512像素。
-
-    以下为原始Food101数据集的结构，您可以将数据集文件解压得到如下的文件结构，并通过MindSpore的API进行读取。
-
-    .. code-block::
-
-        .
-        └── food101_dir
-             ├── images
-             │    ├── apple_pie
-             │    │    ├── 1005649.jpg
-             │    │    ├── 1014775.jpg
-             │    │    ├──...
-             │    ├── baby_back_rips
-             │    │    ├── 1005293.jpg
-             │    │    ├── 1007102.jpg
-             │    │    ├──...
-             │    └──...
-             └── meta
-                  ├── train.txt
-                  ├── test.txt
-                  ├── classes.txt
-                  ├── train.json
-                  ├── test.json
-                  └── train.txt
-
-    **引用：**
-
-    .. code-block::
-
-        @inproceedings{bossard14,
-        title     = {Food-101 -- Mining Discriminative Components with Random Forests},
-        author    = {Bossard, Lukas and Guillaumin, Matthieu and Van Gool, Luc},
-        booktitle = {European Conference on Computer Vision},
-        year      = {2014}
-        }
-
-
-.. include:: mindspore.dataset.api_list_vision.rst

docs/api/api_python/dataset/mindspore.dataset.GeneratorDataset.rst

@@ -36,12 +36,6 @@
         - **ValueError** - `shard_id` 参数错误，小于0或者大于等于 `num_shards` 。
 
     .. note::
-        - 如果配置 `python_multiprocessing=True（默认值：True）` 和 `num_parallel_workers>1（默认值：1）` 表示启动了多进程方式进行数据load加速，
-          此时随着数据集迭代，子进程的内存占用会逐渐增加，主要是因为自定义数据集的子进程以 Copy-On-Write 的方式获取主进程中的成员变量。
-          举例：如果自定义数据集 `__init__` 函数中包含大量成员变量数据（例如：在数据集构建时加载了一个非常大的文件名列表）并且使用了多进程方式，
-          那这可能会导致产生OOM的问题（总内存的预估使用量是：(子进程数量 + 1) * 父进程的内存大小）。最简单的解决方法是成员变量用非引用数据类型
-          （如：Pandas、Numpy或PyArrow对象）替换Python对象（如：list / dict / int / float / string等），或者配置 `python_multiprocessing=False` 
-          使用多线程方式。
         - `source` 参数接收用户自定义的Python函数（PyFuncs），不要将 `mindspore.nn` 和 `mindspore.ops` 目录下或其他的网络计算算子添加
           到 `source` 中。
         - 此数据集可以指定参数 `sampler` ，但参数 `sampler` 和参数 `shuffle` 的行为是互斥的。下表展示了几种合法的输入参数组合及预期的行为。

docs/api/api_python/dataset/mindspore.dataset.GraphData.rst

@@ -7,7 +7,7 @@ mindspore.dataset.GraphData
     支持读取图数据集Cora、Citeseer和PubMed。
 
     关于如何将源数据集加载到mindspore中请参考 `图数据加载与处理 <https://www.mindspore.cn/tutorials/zh-CN/
-    master/advanced/dataset/augment_graph_data.html>`_ 。
+    r2.0.0-alpha/advanced/dataset/augment_graph_data.html>`_ 。
 
     参数：
         - **dataset_file** (str) - 数据集文件路径。

docs/api/api_python/dataset/mindspore.dataset.IMDBDataset.rst

@@ -10,13 +10,15 @@ mindspore.dataset.IMDBDataset
     参数：
         - **dataset_dir** (str) - 包含数据集文件的根目录路径。
         - **usage** (str, 可选) - 指定数据集的子集，可取值为 'train'， 'test'或 'all'。默认值：None，读取全部样本。
-        - **num_samples** (int, 可选) - 指定从数据集中读取的样本数。默认值：None，读取所有样本。
+        - **num_samples** (int, 可选) - 指定从数据集中读取的样本数。
+          对于Polarity数据集， 'train'将读取360万个训练样本， 'test'将读取40万个测试样本， 'all'将读取所有400万个样本。
+          对于Full数据集， 'train'将读取300万个训练样本， 'test'将读取65万个测试样本， 'all'将读取所有365万个样本。默认值：None，读取所有样本。
         - **num_parallel_workers** (int, 可选) - 指定读取数据的工作线程数。默认值：None，使用mindspore.dataset.config中配置的线程数。
         - **shuffle** (bool, 可选) - 是否混洗数据集。默认值：None。下表中会展示不同参数配置的预期行为。
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.IWSLT2016Dataset.rst

@@ -24,7 +24,7 @@ mindspore.dataset.IWSLT2016Dataset
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
         - **num_parallel_workers** (int, 可选) - 指定读取数据的工作线程数。默认值：None，使用mindspore.dataset.config中配置的线程数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。

docs/api/api_python/dataset/mindspore.dataset.IWSLT2017Dataset.rst

@@ -25,7 +25,7 @@ mindspore.dataset.IWSLT2017Dataset
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
         - **num_parallel_workers** (int, 可选) - 指定读取数据的工作线程数。默认值：None，使用mindspore.dataset.config中配置的线程数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。
@@ -33,7 +33,7 @@ mindspore.dataset.IWSLT2017Dataset
         - **RuntimeError** - 指定了 `shard_id` 参数，但是未指定 `num_shards` 参数。
         - **ValueError** - `num_parallel_workers` 参数超过系统最大线程数。
 
-    **关于IWSLT2017数据集：**
+    **关于IWSLT2016数据集：**
 
     IWSLT是一个专门讨论口译各个方面的重要年度科学会议。IWSLT评估活动中的MT任务被构成一个数据集，该数据集可通过 `wit3 <https://wit3.fbk.eu>`_ 公开获取。
     IWSLT2017数据集中有德语、英语、意大利语、荷兰语和罗马尼亚语，数据集包括其中任何两种语言的翻译。

docs/api/api_python/dataset/mindspore.dataset.ImageFolderDataset.rst

@@ -18,7 +18,7 @@ mindspore.dataset.ImageFolderDataset
         - **decode** (bool, 可选) - 是否对读取的图片进行解码操作。默认值：False，不解码。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
         - **decrypt** (callable, 可选) - 图像解密函数，接受加密的图片路径并返回bytes类型的解密数据。默认值：None，不进行解密。
 
     异常：

docs/api/api_python/dataset/mindspore.dataset.InMemoryGraphDataset.rst

@@ -21,18 +21,6 @@
         - **python_multiprocessing** (bool，可选) - 启用Python多进程模式加速运算。默认值：True。当传入 `source` 的Python对象的计算量很大时，开启此选项可能会有较好效果。
         - **max_rowsize** (int, 可选) - 指定在多进程之间复制数据时，共享内存分配的最大空间。默认值：6，单位为MB。仅当参数 `python_multiprocessing` 设为True时，此参数才会生效。
 
-    异常：
-        - **TypeError** - 如果 `data_dir` 不是str类型。
-        - **TypeError** - 如果 `save_dir` 不是str类型。
-        - **TypeError** - 如果 `num_parallel_workers` 不是int类型。
-        - **TypeError** - 如果 `shuffle` 不是bool类型。
-        - **TypeError** - 如果 `python_multiprocessing` 不是bool类型。
-        - **TypeError** - 如果 `perf_mode` 不是bool类型。
-        - **RuntimeError** - 如果 `data_dir` 无效或不存在。
-        - **RuntimeError** - 指定了 `num_shards` 参数，但是未指定 `shard_id` 参数。
-        - **RuntimeError** - 指定了 `shard_id` 参数，但是未指定 `num_shards` 参数。
-        - **ValueError** - `num_parallel_workers` 参数超过系统最大线程数。
-
     .. py:method:: load()
 
         从给定（处理好的）路径加载数据，也可以在自己实现的Dataset类中实现这个方法。

docs/api/api_python/dataset/mindspore.dataset.KMnistDataset.rst

@@ -17,7 +17,7 @@ mindspore.dataset.KMnistDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。

docs/api/api_python/dataset/mindspore.dataset.LJSpeechDataset.rst

@@ -16,7 +16,7 @@ mindspore.dataset.LJSpeechDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。

docs/api/api_python/dataset/mindspore.dataset.ManifestDataset.rst

@@ -18,7 +18,7 @@
         - **decode** (bool, 可选) - 是否对读取的图片进行解码操作。默认值：False，不解码。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_files` 路径下不包含任何数据文件。
@@ -60,25 +60,5 @@
          - False
          - 不允许
 
-    **关于Manifest数据集：**
-
-    Manifest文件包含数据集中包含的文件列表，包括文件名和文件ID等基本文件信息，以及扩展文件元数据。
-    Manifest是华为ModelArts支持的数据格式文件，详细说明请参见 `Manifest文档 <https://support.huaweicloud.com/engineers-modelarts/modelarts_23_0009.html>`_ 。
-
-    以下是原始Manifest数据集结构。可以将数据集文件解压缩到此目录结构中，并由MindSpore的API读取。
-
-    .. code-block::
-
-        .
-        └── manifest_dataset_directory
-            ├── train
-            │    ├── 1.JPEG
-            │    ├── 2.JPEG
-            │    ├── ...
-            ├── eval
-            │    ├── 1.JPEG
-            │    ├── 2.JPEG
-            │    ├── ...
-
 
 .. include:: mindspore.dataset.api_list_vision.rst

docs/api/api_python/dataset/mindspore.dataset.MindDataset.rst

@@ -23,7 +23,7 @@
         - **padded_sample** (dict, 可选) - 指定额外添加到数据集的样本，可用于在分布式训练时补齐分片数据，注意字典的键名需要与 `column_list` 指定的列名相同。默认值：None，不添加样本。需要与 `num_padded` 参数同时使用。
         - **num_padded** (int, 可选) - 指定额外添加的数据集样本的数量。在分布式训练时可用于为数据集补齐样本，使得总样本数量可被 `num_shards` 整除。默认值：None，不添加样本。需要与 `padded_sample` 参数同时使用。
         - **num_samples** (int, 可选) - 指定从数据集中读取的样本数。默认值：None，读取所有样本。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **ValueError** - `dataset_files` 参数所指向的文件无效或不存在。

docs/api/api_python/dataset/mindspore.dataset.MnistDataset.rst

@@ -17,7 +17,7 @@ mindspore.dataset.MnistDataset
         - **sampler** (Sampler, 可选) - 指定从数据集中选取样本的采样器。默认值：None。下表中会展示不同配置的预期行为。
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 路径下不包含数据文件。

docs/api/api_python/dataset/mindspore.dataset.OBSMindDataset.rst

@@ -26,7 +26,7 @@
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
         - **shard_equal_rows** (bool, 可选) - 分布式训练时，为所有分片获取等量的数据行数。默认值：True。
           如果 `shard_equal_rows` 为False，则可能会使得每个分片的数据条目不相等，从而导致分布式训练失败。
-          因此当每个MindRecord文件的数据数量不相等时，建议将此参数设置为True。注意，只有当指定了 `num_shards` 时才能指定此参数。
+          因此当每个TFRecord文件的数据数量不相等时，建议将此参数设置为True。注意，只有当指定了 `num_shards` 时才能指定此参数。
 
     异常：
         - **RuntimeError** - `sync_obs_path` 参数指定的目录不存在。

docs/api/api_python/dataset/mindspore.dataset.PennTreebankDataset.rst

@@ -22,7 +22,7 @@ mindspore.dataset.PennTreebankDataset
 
         - **num_shards** (int, 可选) - 指定分布式训练时将数据集进行划分的分片数。默认值：None。指定此参数后， `num_samples` 表示每个分片的最大样本数。
         - **shard_id** (int, 可选) - 指定分布式训练时使用的分片ID号。默认值：None。只有当指定了 `num_shards` 时才能指定此参数。
-        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/master/dataset/cache.html>`_ 。默认值：None，不使用缓存。
+        - **cache** (DatasetCache, 可选) - 单节点数据缓存服务，用于加快数据集处理，详情请阅读 `单节点数据缓存 <https://www.mindspore.cn/tutorials/experts/zh-CN/r2.0.0-alpha/dataset/cache.html>`_ 。默认值：None，不使用缓存。
 
     异常：
         - **RuntimeError** - `dataset_dir` 参数所指向的文件目录不存在或缺少数据集文件。