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itersmooth 配置说明
kvsmooth 配置说明
linearquant 配置说明
load 配置说明
oasq 配置说明
onlinequarot 配置说明
quarot 配置说明
saver 配置说明
smoothquant 配置说明
svdres 配置说明
trainablelinearquant 配置说明
unaryanalysis 配置说明
quant
quant
modelslimconvert 配置说明
modelslimv1 配置说明
multimodalsdmodelslimv1 配置说明
multimodalvlmmodelslimv1 配置说明
PracticeConfig 配置说明
tuning
tuning
evaluationserviceoriented 配置说明
binaryfallback 配置说明
standinghigh 配置说明
standinghighwithexperience 配置说明
tuningplan 配置说明
python_api
python_api
python_api_v0
python_api_v0
distillation_apis
distillation_apis
KnowledgeDistillConfig
KnowledgeDistillConfig
addcustomlossfunc
addintersoftlabel
addoutputsoftlabel
sethardlabel
setteachertrain
getdistillmodel
foundation_model_compression_apis
foundation_model_compression_apis
foundation_model_quantization_apis
foundation_model_quantization_apis
AntiOutlier
AntiOutlierConfig
CalibrationData
FakeQuantizeCalibrator
LayerSelector
AntiOutlierAdapter
CalibratorAdapter
ModelAdapter
process()
Calibrator
QuantConfig
run()
save()
process()
Calibrator
FAQuantizer
quant()
QuantConfig
run()
save()
foundation_model_sparsification_apis
foundation_model_sparsification_apis
compress()
Compressor
SparseConfig
long_sequence_compression_apis
long_sequence_compression_apis
getalibiwindows
getcompressheads
RACompressConfig
RACompressor
RARopeCompressConfig
RARopeCompressor
weight_compress_apis
weight_compress_apis
CompressConfig
Compressor
export()
exportsafetensors()
run()
low_rank_decompression_apis
low_rank_decompression_apis
Decompose
Decompose
init
decomposenetwork
fromdict
fromfile
fromfixed
fromratio
fromvbmf
countparameters
multimodal_inference_apis
multimodal_inference_apis
DitCache
DitCache
DitCacheAdaptor: DiT模型缓存适配器
DitCacheSearchConfig
sampling_optimization_apis
sampling_optimization_apis
ReStepAdaptor
ReStepSearchConfig
pruning_apis
pruning_apis
PruneConfig
PruneConfig
addblocksparams
setsteps
PruneTorch
PruneTorch
init
analysis
prune
prunebydesc
setimportanceevaluationfunction
setnodereservedratio
prunemodelweight
quantization_apis
quantization_apis
[mindspore]post_training_quantization
[mindspore]post_training_quantization
createquantconfig
quantizemodel
savemodel
[onnx]post_training_quantization
[onnx]post_training_quantization
exportquantonnx
OnnxCalibrator
preprocessfunccoco
preprocessfuncimagenet
QuantConfig
QuantConfig
run()
runquantize
[pytorch]post_training_quantization
[pytorch]post_training_quantization
Calibrator
exportparam
exportquantonnx
exportquantsafetensor()
getquantparams
QuantConfig
quantization_aware_training
quantization_aware_training
QatConfig
qsinqat
saveqsinqatmodel
sparse_acceleration_training_apis
sparse_acceleration_training_apis
sparsemodeldepth
sparsemodelwidth
unified_multimodal_generation_apis
unified_multimodal_generation_apis
quantmodel()
量化会话配置
settimestepidx()
公共接口
best_practices
best_practices
DeepSeek-V4-Flash W8A8 一键量化案例
DeepSeek-V4-Pro 新模型 W4A8 量化案例
Kimi-K3 新模型 W4A8 量化案例
msModelSlim量化权重转AutoAWQ&AutoGPTQ使用指南
Qwen3-32B W8A8精度调优案例
Wan2.2 新模型 W4A4F4 量化案例
contributing
contributing
development_guide
development_guide
docs_standards
docs_standards
公共校验清单
术语词条校验清单
{{ termname }}
流程指南校验清单
{{workflowname}}流程指南
案例参考校验清单
{{modelname}}-{{scenariotype}}案例
配置文档校验清单
{{ configname }} 配置说明
命令行 API 文档校验清单
{{ commandname }} 命令行 API 文档
msModelSlim 架构
编码规范
项目目录结构总览
开发者测试指南
算法贡献指南
Contributing to Mindstudio ModelSlim
install_guide
install_guide
msModelSlim 安装指南
knowledge_base
knowledge_base
dtype_ops
dtype_ops
FP16 / BF16
FP8
INT4
INT8
MXFP4
MXFP8
量化与反量化
量化数据类型 ops 使用流程指南
model
model
parallel
parallel
data_parallelism
data_parallelism
数据并行使用指南
数据并行
distributed_task_scheduler
distributed_task_scheduler
分布式任务调度器使用指南
分布式任务调度器
expert_parallelism
expert_parallelism
专家并行使用指南
专家并行
ptq
ptq
convert
convert
权重转换量化术语百科词条
权重转换使用指南
dit
dit
DiT 模型接入量化流程指南
Diffusion Transformer 量化
多模态生成模型（DiT）量化使用指南
llm
llm
LLM 模型接入量化流程指南
大语言模型量化
大语言模型（LLM）量化使用指南
vlm
vlm
VLM 模型接入量化流程指南
视觉语言模型量化
多模态理解模型（VLM）量化使用指南
训练后量化（PTQ）
quantization_algorithms
quantization_algorithms
adapt_rotation
adapt_rotation
Adapt Rotation 自适应旋转优化算法 量化术语百科词条
Adapt Rotation 自适应旋转量化算法使用指南
attention_mse
attention_mse
Attention MSE 敏感层分析算法 量化术语百科词条
Attention MSE 分析配置流程指南
autoround
autoround
AutoRound 低比特量化算法 量化术语百科词条
AutoRound 低比特量化算法使用指南
awq_smooth
awq_smooth
AWQ 激活感知权重量化算法 量化术语百科词条
AWQ Smooth 参数配置流程指南
ceil_x
ceil_x
CeilX 自适应除数 MXFP4 量化算法 量化术语百科词条
CeilX 参数配置流程指南
daos
daos
DAOS 低比特量化方案 量化术语百科词条
DAOS 参数配置流程指南
dual_scale
dual_scale
DualScale 双尺度量化算法 量化术语百科词条
DualScale 参数配置流程指南
fa3_quant
fa3_quant
FA3 Quant 注意力激活量化算法 量化术语百科词条
FA3 Quant 参数配置流程指南
flex_awq_ssz
flex_awq_ssz
Flex AWQ SSZ 灵活激活感知权重量化平滑算法 量化术语百科词条
Flex AWQ SSZ 参数配置流程指南
flex_smooth_quant
flex_smooth_quant
Flex Smooth Quant 灵活平滑量化算法 量化术语百科词条
Flex Smooth Quant 灵活平滑量化算法使用指南
float_sparse
float_sparse
浮点稀疏（ADMM）算法 量化术语百科词条
浮点稀疏参数配置流程指南
fouroversix
fouroversix
FouroverSix 自适应块缩放量化算法 量化术语百科词条
FourOverSix 参数配置流程指南
gptq
gptq
GPTQ 权重量化算法 量化术语百科词条
GPTQ 参数配置流程指南
histogram_activation_quantization
histogram_activation_quantization
Histogram 直方图激活值量化算法 量化术语百科词条
Histogram 参数配置流程指南
hqq
hqq
HQQ 权重量化算法 量化术语百科词条
HQQ 参数配置流程指南
iterative_smooth
iterative_smooth
Iterative Smooth 迭代平滑算法 量化术语百科词条
Iterative Smooth 迭代平滑算法使用指南
kurtosis
kurtosis
Kurtosis 敏感层分析算法 量化术语百科词条
Kurtosis 参数配置流程指南
kv_smooth
kv_smooth
KV Smooth 缓存平滑算法 量化术语百科词条
KV Smooth 缓存平滑算法使用指南
kvcache_quant
kvcache_quant
KVCache Quant 缓存量化算法 量化术语百科词条
KVCache Quant 参数配置流程指南
laos
laos
LAOS 低比特量化方案 量化术语百科词条
LAOS 低比特量化算法使用指南
linear_quant
linear_quant
线性量化算法 量化术语百科词条
线性量化参数配置流程指南
minmax
minmax
MinMax 最小最大值量化算法 量化术语百科词条
MinMax 参数配置流程指南
mse_layer_wise
mse_layer_wise
层级 MSE 敏感层分析算法 量化术语百科词条
层级 MSE 分析配置流程指南
mse_model_wise
mse_model_wise
模型级 MSE 敏感层分析算法 量化术语百科词条
模型级 MSE 分析配置使用指南
mse_round
mse_round
MSERound 权重量化算法 量化术语百科词条
MSERound 参数配置流程指南
oasq
oasq
OASQ 离群感知平滑量化算法 量化术语百科词条
OASQ 离群感知平滑量化算法使用指南
pdmix
pdmix
PDMIX 阶段间混合量化算法 量化术语百科词条
PDMIX 参数配置流程指南
quantile
quantile
Quantile 敏感层分析算法 量化术语百科词条
Quantile 参数配置流程指南
quarot
quarot
QuaRot 旋转量化算法 量化术语百科词条
QuaRot 旋转量化算法使用指南
ra_compress
ra_compress
RA Compress 长序列压缩算法 量化术语百科词条
RA Compress 注意力头分析使用指南
smooth_quant
smooth_quant
SmoothQuant 平滑量化算法 量化术语百科词条
SmoothQuant 平滑量化算法使用指南
ssz
ssz
SSZ 权重量化算法 量化术语百科词条
SSZ 参数配置流程指南
std
std
Std 敏感层分析算法 量化术语百科词条
Std 参数配置流程指南
svdquant
svdquant
SVDQuant 低秩残差量化算法 量化术语百科词条
SVDQuant 参数配置流程指南
trainable_linear_quant
trainable_linear_quant
Trainable Linear Quant 可训练线性量化算法 量化术语百科词条
Trainable Linear Quant 可训练线性量化算法使用指南
quantization_format
quantization_format
ascendv1
ascendv1
AscendV1 使用指南
AscendV1 量化格式 量化术语百科词条
compressed_tensors
compressed_tensors
compressed-tensors 使用指南
compressed-tensors 量化格式 量化术语百科词条
mindie_sd
mindie_sd
MindIE SD 使用指南
MindIE SD 量化格式 量化术语百科词条
量化格式接入指南
quantization_mode
quantization_mode
fa_quantization
fa_quantization
FA FP8 动态量化
FA INT8 动态量化
FA INT8 PerHead 量化
FA MXFP4 动态量化
FA Q-FP8 动态 K/V-FP8 静态量化
FA Q-INT8 动态 K/V-INT8 静态量化
FA QK-MXFP8 动态 / V-MXFP8 PerChannel 静态量化
kv_cache_quantization
kv_cache_quantization
KVCache-PerChannel 量化
linear_layer_quantization
linear_layer_quantization
浮点稀疏量化
SVDQuant 量化
W4A4 动态量化
W4A4 MX 双 Scale 量化
W4A4 MX 动态量化
W4A8 动态量化
W4A8 MX 动态量化
W8A16 静态量化
W8A8 动态量化
W8A8 FP8 动态量化
W8A8 MX 动态量化
W8A8 PD-Mix 量化
W8A8 稀疏量化
W8A8 静态量化
GEMM
tuning_strategies
tuning_strategies
binary_fallback
binary_fallback
Binary Fallback 调优算法
standing_high
standing_high
Standing High 调优算法
standing_high_with_experience
standing_high_with_experience
Standing High With Experience 调优算法
legal
legal
致msModelSlim使用者
LICENSE声明
msModelSlim安全声明
quick_start
quick_start
msModelSlim 快速入门
support
support
FAQ
部署与推理 FAQ
硬件兼容 FAQ
安装与依赖 FAQ
精度与调优 FAQ
运行与资源 FAQ
告警与提示 FAQ
user_guide
user_guide
traditional_quantization_v0
traditional_quantization_v0
伪量化精度测试工具（Precision Tool）
压缩与结构优化（大模型为主）
大模型量化与校准
Install torchnpu and decord
mindspeed_adapter
训练加速与模型改造
量化代码示例
msmodelslim量化权重格式
稀疏加速训练
传统模型量化与校准
量化与校准
主流模型量化部署流程指南
新模型量化调优流程
量化推理精度异常定位流程指南
量化精度调优指南
自动调优使用说明
调试模式使用指南
伪量化推理使用指南
一键量化使用指南
组合处理器 (Group Processor)
Attention 敏感层分析使用指南
Attention Head 筛选分析使用指南
层级敏感层分析使用指南
线性层敏感层分析使用指南
权重量化使用指南
msmonitor
msmonitor
docs
docs
zh
zh
advanced_features
advanced_features
mindstudiomonitor模块接口参考
Monitor 特性介绍
design
design
MindStudio Monitor特性分析与设计说明书
developer_guide
developer_guide
开发指南
getting_started
getting_started
msMonitor工具安装指南
msMonitor工具快速入门
legal
legal
MindStudio漏洞机制说明
公网地址
msMonitor安全声明
user_guide
user_guide
dyno使用说明
dynolog使用说明
MindSpore框架下msMonitor的使用方法
npu-monitor使用说明
nputrace使用说明
项目目录
FAQ
总体介绍
版本说明
msopcom
msopcom
docs
docs
en
en
contributing
contributing
Contribution Guide
development_guide
development_guide
MindStudio Ops Common Architecture Design
MindStudio Ops Common Development Environment Setup, Compilation, and Unit Testing
legal
legal
Disclaimer
LICENSE Statement
Security Statement
MindStudio Vulnerability Mechanism
zh
zh
contributing
contributing
贡献指南
development_guide
development_guide
MindStudio Ops Common 架构设计说明
MindStudio Ops Common 开发环境搭建及编译和UT方法
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
msopgen
msopgen
docs
docs
en
en
best_practices
best_practices
Typical Cases of MindStudio Ops Generator
contributing
contributing
Contribution Guide
development_guide
development_guide
msOpGen Architecture Design Specifications
MindStudio msOpGen Development Environment Setup and UT Methods
install_guide
install_guide
MindStudio Ops Generator Installation Guide
legal
legal
Disclaimer
LICENSE Statement
Security Statement
MindStudio Vulnerability Handling Mechanism Description
overview
overview
Overview
quick_start
quick_start
MindStudio Ops Generator Quick Start
MindStudio Ops System Test Quick Start
release_notes
release_notes
MindStudio Ops Generator Release Notes
support
support
msOpGen FAQ
user_guide
user_guide
MindStudio Ops Generator User Guide
zh
zh
best_practices
best_practices
MindStudio Ops Generator典型案例
contributing
contributing
贡献指南
development_guide
development_guide
msOpGen 架构设计说明书
MindStudio msOpGen 开发环境搭建和UT方法
install_guide
install_guide
msOpGen 安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
overview
overview
简介
quick_start
quick_start
msOpGen算子调试工具快速入门
MindStudio Ops System Test快速入门
support
support
msOpGen 常见问题
user_guide
user_guide
MindStudio Ops Generator工具用户指南
msopmodeling
msopmodeling
docs
docs
zh
zh
contributing
contributing
贡献指南
development_guide
development_guide
算子性能建模工具开发指南
install_guide
install_guide
算子性能建模工具安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
quick_start
quick_start
算子性能建模工具快速入门
user_guide
user_guide
算子性能建模工具使用指南
msopprof
msopprof
docs
docs
en
en
best_practices
best_practices
Typical Cases
contributing
contributing
Contributing Guide
development_guide
development_guide
MindStudio Ops Profiler Architecture Design Specifications
MindStudio Ops Profiler Development Environment Setup, Compilation, and UT Methods
install_guide
install_guide
MindStudio Ops Profiler Installation Guide
legal
legal
Disclaimer
LICENSE Statement
Security Declaration
MindStudio Vulnerability Handling Mechanism Description
quick_start
quick_start
MindStudio Ops Profiler Quick Start
release_notes
release_notes
MindStudio Ops Profiler Release Notes
user_guide
user_guide
Constraints and Precautions for MindStudio Ops Profiler
Extended Functions
msOpProf Profile Data
msOpProf Simulator Mode Performance Data
msOpProf Simulator Mode User Guide
msOpProf Usage Scenarios
msOpProf Mode User Guide
zh
zh
best_practices
best_practices
典型案例
contributing
contributing
贡献指南
development_guide
development_guide
MindStudio Ops Profiler 架构设计说明书
msOpProf 开发指南
install_guide
install_guide
msOpProf 安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
quick_start
quick_start
msOpProf 算子性能调优工具快速入门
user_guide
user_guide
MindStudio Ops Profiler 工具限制与注意事项
扩展功能
msopprof模式性能数据
msOpProf simulator模式性能数据
msopprof simulator模式用户指南
msOpProf使用场景
msOpProf模式用户指南
msoptuner
msoptuner
docs
docs
en
en
install_guide
install_guide
MindStudio Ops Tuner Installation Guide
legal
legal
Disclaimer
LICENSE Statement
Security Statement
MindStudio Vulnerability Mechanism
zh
zh
install_guide
install_guide
MindStudio Ops Tuner安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
msot
msot
docs
docs
design
design
26.0.0
26.0.0
检测工具功能设计文档
检测工具功能设计文档
算子检测工具功能设计文档
调优工具功能设计文档
调优工具功能设计文档
MindStudio-Ops-Profiler特性设计说明书
调试工具功能设计文档
调试工具功能设计文档
算子调试工具功能设计文档
26.1.0
26.1.0
检测工具功能设计文档
检测工具功能设计文档
MindStudio Sanitizer 功能设计文档
调优工具功能设计文档
调优工具功能设计文档
MindStudio Ops Profiler 功能设计说明书
调试工具功能设计文档
调试工具功能设计文档
MindStudio Debugger 功能设计说明书
26.2.0
26.2.0
检测工具功能设计文档
检测工具功能设计文档
MindStudio Sanitizer 功能设计文档
调优工具功能设计文档
调优工具功能设计文档
MindStudio Ops Profiler 功能设计说明书
调试工具功能设计文档
调试工具功能设计文档
MindStudio Debugger 功能设计说明书
en
en
common
common
Contribution Workflow and Code Style Guide
MindStudio Tool Development Environment Setup Guide
MindStudio Unified Build Image Creation Guide
contributing
contributing
Contributing Guide
install_guide
install_guide
MindStudio Operator Tools Installation Guide
legal
legal
Disclaimer
LICENSE Statement
Security Statement
MindStudio Vulnerability Mechanism Description
overview
overview
Introduction
quick_start
quick_start
Ascend AI Operator Development Toolchain Learning Environment Installation Guide
Operator Development Toolchain Quick Start
release_notes
release_notes
MindStudio Operator Tools Release Notes
user_guide
user_guide
msOT Tool Selection Guide
zh
zh
common
common
贡献流程和规范说明
MindStudio 工具开发环境安装指导
MindStudio 统一构建镜像制作指南
contributing
contributing
贡献指南
install_guide
install_guide
msOT 安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
overview
overview
简介
quick_start
quick_start
昇腾 AI 算子开发工具链学习环境安装指南
算子开发工具链快速入门
user_guide
user_guide
msOT 工具选型指南
msprobe
msprobe
docs
docs
en
en
baseline
baseline
Precision Pre-check Baseline in MindSpore
Precision Data Collection Baseline in MindSpore
Performance Baseline Report of the Training Status Monitoring Tool
Precision Data Collection Baseline in PyTorch
best_practices
best_practices
Enabling Tools for Common Frameworks
Foundation Model Inference Accuracy Debugging Guide
Foundation Model Training Accuracy Debugging Guide
contributing
contributing
Contributing to MindStudio Probe
development_guide
development_guide
Developer Guide
MindStudio 26.0.0 Precision Debugging Feature Analysis and Design Specification
MindStudio 26.1.0 Precision Debugging Feature Analysis and Design Specification
examples
examples
Configuring Layer Mapping for Hierarchical Model Visualization
Data Collection and Automatic Comparison in MindSpeed and LLamaFactory
install_guide
install_guide
msProbe Installation Guide
legal
legal
Disclaimer
License Description
MindStudio Vulnerability Handling Mechanism Description
Public Network Addresses
msProbe Security Statement
quick_start
quick_start
Quick Start of msProbe in the MindSpore Scenario
msProbe PyTorch Quick Start
support
support
FAQs
user_guide
user_guide
accuracy_checker
accuracy_checker
Offline Precision Pre-check for MindSpore Dynamic Graphs
Offline Precision Pre-check in PyTorch
accuracy_compare
accuracy_compare
ATB Data Precision Comparison
One-Click Precision Comparison for Offline Inference Models
Comparison Result Description
Precision Comparison in MindSpore
Graph Comparison in Hierarchical Visualization (MindSpore)
Comparison of Dump Data Precision for Offline Models
Precision Comparison in PyTorch
Compilation Accuracy Comparison in PyTorch
Graph Comparison in Hierarchical Visualization (PyTorch)
Network-wide Operator Precision Comparison in TorchAir Mode
Trend Visualization
dump
dump
aclgraphdump User Guide
Precision Data Collection in ATB
Configuration File Introduction
Data Conversion
Single-Point Saving Tool
Inference Offline Model Data Collection
Precision Data Collection in MindSpore
Precision Data Collection in MindSpore Dynamic Graph Mode
Precision Data Collection in MSAdapter
Precision Data Collection in PyTorch
Kernel-Level Precision Data Collection in PyTorch
nancheck Usage Example
Precision Data Collection in SGLang (SGLang Version < 0.5.11)
Precision Data Collection in SGLang (SGLang Version >= 0.5.11)
Inference in Torch Graph Mode (TorchAir)
Collecting Data for Asynchronous verl Training-Inference Consistency Comparison
Collecting Data for Verifying Data Consistency Between verl Training and Inference Based on FSDP
Collecting Data for Verifying Data Consistency Between verl Training and Inference Based on Megatron
Training-Inference Consistency Monitoring: Token-Level probsdiff Monitoring
Precision Data Collection in the vLLM Scenario
overflow_check
overflow_check
First Network Overflow/Underflow Node Analysis
Checkpoint Comparison
Configuration Check Before Training
msProbe: Functional Modules, Scenarios, and Limitations
Lightweight Training Status Monitoring Tool
Lightweight Training Status Monitoring Tool
Response Anomaly
verl Training-Inference Cross-Instrumentation
verl Hyperparameter Comparison and Key Hyperparameter Verification
zh
zh
baseline
baseline
MindSpore 场景的精度预检基线
MindSpore 场景的精度数据采集基线
训练状态监测工具标准性能基线报告
PyTorch 场景的精度数据采集基线
best_practices
best_practices
基于昇腾的80卡大模型训练确定性排查
基于昇腾的复杂dump数据分析GradNorm NaN定位实践
基于昇腾的DeepSeek-V4 GPQA精度优化
基于昇腾的Gemma模型重复训练Loss差异定位
基于昇腾的GLM5适配与训推一致性优化
基于昇腾的Kimi2.5训推一致性优化
基于昇腾的mmdetection训练NaN问题定位
基于昇腾的MOVA模型NaN问题定位分析
基于昇腾的多模态理解训练NaN问题定位
基于昇腾的Qwen2.5-omni模型确定性排查
基于昇腾的Qwen2.5-omni框架迁移Loss差异定位
基于昇腾的Qwen-Image-Edit模型TP8花图问题定位
强化学习训推一致性排查
基于昇腾的tora模型推理差异定位
基于昇腾的VL模型迁移vLLM精度问题
常见框架dump工具使能
大模型推理精度定位指南
Qwen2.5模型推理回复复读问题
CANN版本升级后的推理请求回复乱码问题
大模型训练精度定位指南
contributing
contributing
为MindStudio Probe贡献
development_guide
development_guide
msProbe 开发指南
MindStudio26.0.0精度调试特性分析与设计说明书
MindStudio26.1.0精度调试特性分析与设计说明书
MindStudio26.2.0精度调试特性分析与设计说明书
examples
examples
模型分级可视化如何配置layer mapping映射文件
MindSpeed&LLamaFactory数据采集和自动比对
install_guide
install_guide
msProbe 安装指南
legal
legal
免责声明
License说明
MindStudio漏洞机制说明
公网地址
msProbe安全声明
quick_start
quick_start
MindSpore场景精度调试工具快速入门
msProbe PyTorch 场景快速入门
support
support
FAQ
user_guide
user_guide
accuracy_checker
accuracy_checker
MindSpore动态图场景离线精度预检
PyTorch场景离线精度预检
accuracy_compare
accuracy_compare
ATB场景精度比对
推理离线模型一键式精度比对
比对结果说明
MindSpore场景精度比对
MindSpore场景分级可视化构图比对
离线模型dump数据精度比对
PyTorch场景精度比对
PyTorch场景编译精度比对
PyTorch场景的分级可视化构图比对
基于torch图模式（torchair）整网算子精度比对
趋势可视化
dump
dump
aclgraphdump 使用指南
ATB场景精度数据采集
配置文件介绍
数据转换功能
单点保存工具
推理离线模型数据采集
MindSpore场景精度数据采集
MindSpore动态图精度数据采集快速入门
MSAdapter场景精度数据采集
PyTorch场景精度数据采集
PyTorch场景精度数据覆盖加载
PyTorch场景kernel级精度数据采集
nancheck 使用示例
SGLang精度数据采集（SGLang版本<0.5.11）
SGLang精度数据采集（SGLang版本>=0.5.11）
slime框架训推一致性预处理与数据采集
slime框架训推精度数据采集
基于torch图模式（torchair）推理场景
异步架构verl训推一致性比对数据采集
fsdp训练后端verl训推一致性比对数据采集
megatron训练后端verl训推一致性比对数据采集
训推一致性监控：逐Token级别的probsdiff监控
verl V1 Trainer训推一致性比对数据采集
vLLM采集
overflow_check
overflow_check
整网首个溢出节点分析
Checkpoint比对
训练前配置检查
msProbe 工具功能模块简介、适用场景和当前版本局限性
Monitor训练状态轻量化监测工具
训练状态轻量化监测工具
推理异常检测
训推权重一致性验证定位指南
slime超参比对与关键超参校验
VeRL 训推交叉打桩功能指南
verl超参比对与关键超参校验
msprof
msprof
docs
docs
en
en
best_practices
best_practices
Troubleshooting Guide: Asynchronous Scheduling Does Not Take Effect
msProf Use Case: Performance Analysis of a ResNet50 Inference Model
Request Length Imbalance Within the Same Batch
1. Background
Performance Degradation Caused by Misaligned Communication Addresses
CPU Cache Miss Resource Contention and Constraints
Frequent CPU Thread Switching
1. Background
DP Load Imbalance
EP Load Imbalance
Troubleshooting Guide: Framework Scheduling and Dispatch Synchronization
GIL Contention Analysis
IR Interrupt Preemption Analysis
Frequent Kernel Thread Switching Analysis
Insufficient KV Blocks
Impact of KV Cache Transfer on Model Performance
Memory Fragmentation Analysis
Memory Leak Analysis
Model Performance Degradation Causing SLO Degradation
Analysis of Excessive Preprocessing and Postprocessing Time in Model Inference
Multi-Instance Load Imbalance
1. Background
PrefixCache Misses
Pthread Lock Wait
High Python GC Overhead
Troubleshooting Guide: Long Wait Time for Model Inference Requests
Analysis of Excessive Sampler Execution Time
Excessive Scheduler Execution Time
Optimization Guide for Large Performance Gaps Between Serving and Pure-Model Inference
1. Background
High-Latency System Calls
contributing
contributing
Contributing to MindStudio Profiler
development_guide
development_guide
Developer Guide
Background
MindStudio Profiler Feature Analysis and Design Specifications
install_guide
install_guide
MindStudio Profiler Installation Guide
legal
legal
Disclaimer
License
MindStudio Profiler Security Statement
quick_start
quick_start
msProf Quick Start
support
support
FAQ
user_guide
user_guide
Extended Functions
msProf Parsing Tool
Profile Data File Reference
Profile Data File Reference (DB)
zh
zh
best_practices
best_practices
ResNet50推理模型性能分析
代码高耗时函数段优化
通信地址不对齐导致性能下降
CPU Cache Miss资源冲突与受限
CPU 线程频繁切换
下发性能不及预期
GIL锁抢占问题分析
IRQ中断问题分析
内核进程频繁切换
内存碎片
内存泄漏
算子编译高耗时
Pthread线程锁等待
Python GC回收高耗时
同步接口频繁调用
系统调用高耗时函数
contributing
contributing
为MindStudio Profiler贡献
development_guide
development_guide
msProf 开发指南
背景描述（Background）
MindStudio Profiler 性能调优特性分析与设计说明书
install_guide
install_guide
msProf 安装指南
legal
legal
免责声明
License
msProf安全声明
quick_start
quick_start
msProf 快速入门
support
support
FAQ
user_guide
user_guide
扩展功能
msProf解析工具
profile_data_file_references
DB格式性能数据文件参考
msprof-analyze
msprof-analyze
docs
docs
en
en
advanced_features
advanced_features
calibratenpugpu
Cluster Operator Duration Analysis
clustertimecomparesummary
clustertimesummary
communicationbottleneck
computationalopmasking
Custom Analysis Rule Development Guide
exportsummary
freeanalysis
modulestatistic
operatormfu
ppchart
Table Structures of Parsing Results and clusteranalysis.db Deliverables
development_guide
development_guide
MindStudio Profiler Analyze Feature Analysis and Design Specifications
Developer Guide
install_guide
install_guide
msprof-analyze Installation Guide
legal
legal
Disclaimer
License Notice
MindStudio Profiler Analyze Security Statement
quick_start
quick_start
msprof-analyze Quick Start
user_guide
user_guide
advisor
clusteranalyse
compare
AICPU Operator Replacement Examples
Examples for Fused Operator API Replacement During Migration to Ascend
zh
zh
advanced_features
advanced_features
NPU 和 GPU 性能数据拆解比对
集群算子耗时分析
集群性能数据细粒度比对
集群性能数据细粒度拆解
通信瓶颈分析
集群算子掩盖线性度分析
自定义分析规则开发指导
集群算子信息导出
空闲时间原因分析
性能数据模型结构拆解
算子 MFU 分析
pp流水图数据分析
解析结果和clusteranalysis.db交付件表结构说明
development_guide
development_guide
MindStudio Profiler Analyze特性分析与设计说明书
msprof-analyze 开发指南
install_guide
install_guide
msprof-analyze 安装指南
legal
legal
免责声明
License 声明
msprof-analyze安全声明
quick_start
quick_start
msprof-analyze 快速入门
user_guide
user_guide
专家建议
cluster_analyse_instruct
性能比对
AI CPU算子替换样例
昇腾迁移融合算子API替换样例
mspti
mspti
docs
docs
en
en
api_reference
api_reference
c_api
c_api
context
context
msptiActivity
msptiActivityApi
msptiActivityCommunication
msptiActivityDisable
msptiActivityDisableMarkerDomain
msptiActivityEnable
msptiActivityEnableMarkerDomain
msptiActivityExternalCorrelation
msptiActivityFlag
msptiActivityFlushAll
msptiActivityFlushPeriod
msptiActivityGetNextRecord
msptiActivityHccl
msptiActivityIsEnabled
msptiActivityKernel
msptiActivityKind
msptiActivityMarker
msptiActivityMemcpy
msptiActivityMemcpyKind
msptiActivityMemory
msptiActivityMemoryKind
msptiActivityMemoryOperationType
msptiActivityMemset
msptiActivityPopExternalCorrelationId
msptiActivityPushExternalCorrelationId
msptiActivityRegisterCallbacks
msptiActivitySourceKind
msptiApiCallbackSite
msptiBuffersCallbackCompleteFunc
msptiBuffersCallbackRequestFunc
msptiCallbackData
msptiCallbackDomain
msptiCallbackFunc
msptiCallbackId
msptiCallbackIdHccl
msptiCallbackIdRuntime
msptiCommunicationDataType
msptiEnableCallback
msptiEnableDomain
msptiExternalCorrelationKind
msptiGetResultString
msptiObjectId
msptiPmSamplingBufferAppendMode
msptiPmSamplingCounterDataImageInitialize
msptiPmSamplingDecodeData
msptiPmSamplingDecodeStopReason
msptiPmSamplingDisable
msptiPmSamplingEnable
msptiPmSamplingGetCounterAvailability
msptiPmSamplingGetCounterDataInfo
msptiPmSamplingGetCounterDataSize
msptiPmSamplingGetMetricProperties
msptiPmSamplingGetNumMetrics
msptiPmSamplingGetSampleEntries
msptiPmSamplingGetSampleInfo
msptiPmSamplingMetricDataType
msptiPmSamplingMetricGroup
msptiPmSamplingMetricId
msptiPmSamplingMetricProperties
msptiPmSamplingObjectPtr
msptiPmSamplingSampleEntry
msptiPmSamplingSetConfig
msptiPmSamplingStart
msptiPmSamplingStop
msptiPmSamplingTriggerMode
msptiResult
msptiSubscribe
msptiSubscriberHandle
msptiUnsubscribe
python_api
python_api
context
context
CommunicationData
CommunicationMonitor.flushall
CommunicationMonitor.setbuffersize
CommunicationMonitor.start
CommunicationMonitor.stop
HcclData
HcclMonitor.flush\all
HcclMonitor.set\buffer\size
HcclMonitor.start
HcclMonitor.stop
KernelData
KernelMonitor.flush\all
KernelMonitor.set\buffer\size
KernelMonitor.start
KernelMonitor.stop
MarkerData
MsptiActivityFlag
MsptiActivityKind
MsptiActivitySourceKind
MsptiCommunicationDataType
MsptiResult
MstxMonitor.disable\domain
MstxMonitor.enable\domain
MstxMonitor.flush\all
MstxMonitor.set\buffer\size
MstxMonitor.start
MstxMonitor.stop
RangeMarkerData
best_practices
best_practices
msPTI Best Practices and Typical Use Cases
contributing
contributing
Contributing to the MindStudio Profiler Tools Interface
development_guide
development_guide
Development Guide
msPTI Feature Design Specifications
install_guide
install_guide
msPTI Installation Guide
legal
legal
Disclaimer
License
msPTI Security Statement
quick_start
quick_start
msPTI Quick Start
support
support
msPTI FAQ
user_guide
user_guide
Activity API Usage Guide
Callback API User Guide
msPTI User Guide
PM Sampling API Usage Guide
Python API Usage Guide
msPTI Tool Sample Guide
zh
zh
api_reference
api_reference
c_api
c_api
context
context
msptiActivity
msptiActivityApi
msptiActivityAttribute
msptiActivityCommunication
msptiActivityDisable
msptiActivityDisableMarkerDomain
msptiActivityEnable
msptiActivityEnableMarkerDomain
msptiActivityExternalCorrelation
msptiActivityFlag
msptiActivityFlushAll
msptiActivityFlushPeriod
msptiActivityGetAttribute
msptiActivityGetEnabledKinds
msptiActivityGetNextRecord
msptiActivityGetNumDroppedRecords
msptiActivityGetStructSize
msptiActivityHccl
msptiActivityIsEnabled
msptiActivityKernel
msptiActivityKind
msptiActivityMarker
msptiActivityMemcpy
msptiActivityMemcpyKind
msptiActivityMemory
msptiActivityMemoryKind
msptiActivityMemoryOperationType
msptiActivityMemset
msptiActivityObjectKind
msptiActivityOverhead
msptiActivityOverheadKind
msptiActivityPopExternalCorrelationId
msptiActivityPushExternalCorrelationId
msptiActivityRegisterCallbacks
msptiActivityRegisterTimestampCallback
msptiActivitySetAttribute
msptiActivitySourceKind
msptiApiCallbackSite
msptiBuffersCallbackCompleteFunc
msptiBuffersCallbackRequestFunc
msptiCallbackData
msptiCallbackDomain
msptiCallbackFunc
msptiCallbackId
msptiCallbackIdHccl
msptiCallbackIdRuntime
msptiCommunicationDataType
msptiDomainTable
msptiEnableAllDomains
msptiEnableCallback
msptiEnableDomain
msptiExternalCorrelationKind
msptiFinalize
msptiGetCallbackName
msptiGetCallbackState
msptiGetEnabledCallbacks
msptiGetResultString
msptiGetTimestamp
msptiGetVersion
msptiIsTracingSessionRunning
msptiObjectId
msptiPmSamplingBufferAppendMode
msptiPmSamplingCounterDataImageInitialize
msptiPmSamplingDecodeData
msptiPmSamplingDecodeStopReason
msptiPmSamplingDisable
msptiPmSamplingEnable
msptiPmSamplingGetCounterAvailability
msptiPmSamplingGetCounterDataInfo
msptiPmSamplingGetCounterDataSize
msptiPmSamplingGetMetricProperties
msptiPmSamplingGetNumMetrics
msptiPmSamplingGetSampleEntries
msptiPmSamplingGetSampleInfo
msptiPmSamplingMetricDataType
msptiPmSamplingMetricGroup
msptiPmSamplingMetricId
msptiPmSamplingMetricProperties
msptiPmSamplingObjectPtr
msptiPmSamplingSampleEntry
msptiPmSamplingSetConfig
msptiPmSamplingStart
msptiPmSamplingStop
msptiPmSamplingTriggerMode
msptiResult
msptiSubscribe
msptiSubscriberHandle
msptiSupportedDomains
msptiTimestampCallbackFunc
msptiUnsubscribe
python_api
python_api
context
context
CommunicationData
CommunicationMonitor.flush\all
CommunicationMonitor.set\buffer\size
CommunicationMonitor.start
CommunicationMonitor.stop
HcclData
HcclMonitor.flush\all
HcclMonitor.set\buffer\size
HcclMonitor.start
HcclMonitor.stop
KernelData
KernelMonitor.flush\all
KernelMonitor.set\buffer\size
KernelMonitor.start
KernelMonitor.stop
MarkerData
MsptiActivityFlag
MsptiActivityKind
MsptiActivitySourceKind
MsptiCommunicationDataType
MsptiResult
MstxMonitor.disable\domain
MstxMonitor.enable\domain
MstxMonitor.flush\all
MstxMonitor.set\buffer\size
MstxMonitor.start
MstxMonitor.stop
RangeMarkerData
best_practices
best_practices
msPTI 最佳实践与典型案例
contributing
contributing
为 MindStudio Profiler Tools Interface 贡献
development_guide
development_guide
msPTI 开发指南
msPTI特性设计说明书
install_guide
install_guide
msPTI 安装指南
legal
legal
免责声明
License
msPTI安全声明
quick_start
quick_start
msPTI 快速入门
support
support
msPTI 常见问题（FAQ）
user_guide
user_guide
Activity API 使用指南
Callback API 使用指南
msPTI 用户指南
PM Sampling API 使用指南
Python API 使用指南
msPTI工具样例指南
mssanitizer
mssanitizer
docs
docs
en
en
api_reference
api_reference
MindStudio Sanitizer API Reference
best_practices
best_practices
Basic Cases
contributing
contributing
Contribution Guide
development_guide
development_guide
msSanitizer Architecture Design Specifications
MindStudio Sanitizer Development Environment Setup, Build, and UT Methods
install_guide
install_guide
MindStudio Sanitizer Installation Guide
legal
legal
Disclaimer
LICENSE Statement
Security Statement
MindStudio Vulnerability Handling Mechanism Description
quick_start
quick_start
msSanitizer Quick Start
release_notes
release_notes
MindStudio Sanitizer Release Notes
support
support
MindStudio Sanitizer FAQs
user_guide
user_guide
Enabling Full Check
MindStudio Sanitizer User Guide
zh
zh
api_reference
api_reference
MindStudio Sanitizer 对外接口使用说明
best_practices
best_practices
基础案例
contributing
contributing
贡献指南
development_guide
development_guide
msSanitizer 架构设计说明书
msSanitizer 开发指南
install_guide
install_guide
msSanitizer 安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
quick_start
quick_start
msSanitizer 算子检测工具快速入门
support
support
MindStudio Sanitizer常见问题
user_guide
user_guide
开启全量检测
MindStudio Sanitizer 使用指南
通路事件过滤使用说明
msserviceprofiler
msserviceprofiler
docs
docs
community_extension_docs
community_extension_docs
社区扩展与插件列表
社区扩展指南：如何提交扩展
design
design
MindStudio Service Profiler 特性设计说明书
【B050】LLM推理监控平台设计文档
ms-service-metric 可扩展指标架构重构设计文档
三元关系详设
vLLM Hook Tracing 特性详细设计
en
en
best_practices
best_practices
Asynchronous Dual Dispatch Not Taking Effect
Request Length Imbalance Within the Same Batch
DP Load Imbalance
EP Load Imbalance
Framework Scheduling and Dispatch Not Synchronized
New Evaluation Dataset Triggers a KVCache Capacity Bottleneck
Impact of KV Cache Transfer on Model Performance
Model Performance Degradation Causing SLO Degradation
Excessive Preprocessing and Postprocessing Time in Model Inference
Multi-Instance Load Imbalance
PrefixCache Misses
Long Wait Time for Model Inference Requests
Excessive Sampler Execution Time
Excessive Scheduler Execution Time
Large Performance Gaps Between Serving and Pure-Model Inference
Speculative Inference Acceptance Rate Drops After Dynamic EPLB Is Enabled
vLLM-Ascend Observability Performance Diagnostics Guide
cpp_api
cpp_api
serving_tuning
serving_tuning
ArrayAttr
ArrayResource
Attr Functions
Domain
Event
GetMsg
IsEnable
Launch
Link
Macro Definition
Metric
MetricInc
MetricScope
MetricScopeAsGlobal
MetricScopeAsReqID
NumArrayAttr
Resource
SpanEnd
SpanStart
trace_data_monitoring
trace_data_monitoring
Activate
addResAttribute
Attach
End
ExtractAndAttach
GetCurrent
GetTraceCtx
IsEnable
SetAttribute
SetStatus
Span
Span Class
StartSpanAsActive
TraceContext Class
Tracer Class
Unattach
developer_guide
developer_guide
msServiceProfiler Development Guide
install_guide
install_guide
msServiceProfiler Installation Guide
legal
legal
Disclaimer
License
Public Network Address
msServiceProfiler Security Statement
MindStudio Vulnerability Handling Mechanism Description
python_api
python_api
context
context
\\enter\\/\\exit\\
attr
domain
event
get\msg
init
launch
link
metric
metric\inc
metric\scope
metric\scope\as\req\id
res
span\end
span\start
quick_start
quick_start
Quick Start Guide for msServiceProfiler
user_guide
user_guide
msServiceProfiler Compare Tool
msServiceProfiler Multi Analyze
Serving Performance Tuning Tool
msServiceProfiler Trace for Data Monitoring
Service Performance Split Tool
Service Profiling Advisor
Serviceparam Optimizer
Custom Plugin Developer Guide
SGLang Service Profiler User Guide
vLLM Hook Tracing User Guide
vLLM Serving Prometheus Metric Monitoring Tool User Guide
vLLM Service Profiler User Guide
Project Directory
Overview
zh
zh
best_practices
best_practices
异步双发未生效
同一Batch内请求长度不均
DP负载不均
EP负载不均
框架调度下发不同步
新测评数据集触发 KVCache 容量瓶颈
KVCache传输影响模型性能
模型性能劣化导致SLO劣化
模型前后处理耗时过长
多实例负载不均
PrefixCache未命中
模型推理请求等待时间过长
sampler执行耗时过长
scheduler耗时过长
服务化与纯模型性能差异过大
动态 EPLB 开启后投机推理接受率下降
vLLM-Ascend 可观测性性能诊断指南
cpp_api
cpp_api
serving_tuning
serving_tuning
ArrayAttr
ArrayResource
Attr系列
Domain
Event
GetMsg
IsEnable
Launch
Link
宏定义
Metric
MetricInc
MetricScope
MetricScopeAsGlobal
MetricScopeAsReqID
NumArrayAttr
Resource
SpanEnd
SpanStart
trace_data_monitoring
trace_data_monitoring
Activate
addResAttribute
Attach
End
ExtractAndAttach
GetCurrent
GetTraceCtx
IsEnable
SetAttribute
SetStatus
Span
Span类
StartSpanAsActive
TraceContext类
Tracer类
Unattach
developer_guide
developer_guide
msServiceProfiler 开发指南
install_guide
install_guide
msServiceProfiler 安装指南
legal
legal
免责声明
License
公网地址
msServiceProfiler安全声明
MindStudio 漏洞机制说明
python_api
python_api
context
context
\\enter\\/\\exit\\
attr
domain
event
get\msg
init
launch
link
metric
metric\inc
metric\scope
metric\scope\as\req\id
res
span\end
span\start
quick_start
quick_start
服务化性能调优工具快速入门
user_guide
user_guide
服务化性能数据比对工具
服务化多维度解析工具
推理服务化性能调优工具
msServiceProfiler Trace数据监测
服务化拆解工具
服务化专家建议工具
服务化自动寻优工具
自定义插件开发指导
SGLang 服务化性能采集工具使用指南
vLLM Hook Tracing 使用指南
vLLM 服务化 Prometheus 数据监测工具使用指南
vLLM 服务化性能采集工具使用指南
项目目录
简介
{% include-markdown "../CONTRIBUTING.md" %}
mstt
mstt
docs
docs
en
en
best_practices
best_practices
general_performance_issue_troubleshooting_guide
general_performance_issue_troubleshooting_guide
Introduction
Overview
Performance Tool Usage
Performance Troubleshooting Process
Communication Tuning Solution
Operator Performance Tuning Solution
Host Bound Troubleshooting
Methodology for Locating Performance Fluctuation Problems in a Cluster
Solution for ONNX Offline Inference
Solution for the MindIE Inference Performance
Methodology for Locating Performance Deterioration During Version Upgrade
Overview
Case Study on Locating Foundation Model Training Performance Bottlenecks
common
common
Contribution Workflow and Guidelines
contributing
contributing
Contribution Guide
legal
legal
Disclaimer
LICENSE Statement
MindStudio Vulnerability Mechanism Description
Public Network Addresses
msTT Security Statement
quick_start
quick_start
Training Development Toolchain Quick Start
user_guide
user_guide
msTT Tool Selection Guide
zh
zh
best_practices
best_practices
general_performance_issue_troubleshooting_guide
general_performance_issue_troubleshooting_guide
导读
简介
性能工具的使用
性能问题的定位流程
通信问题优化方案
算子性能问题优化方案
Host Bound问题定位及解决方法
集群性能异常波动问题定位方法论
ONNX离线推理场景解决方案
MindIE推理性能解决方案
版本升级性能劣化定位方法论
简介
大模型训练性能瓶颈定位流程案例
contributing
contributing
贡献流程和规范说明
贡献指南
legal
legal
免责声明
LICENSE声明
MindStudio漏洞机制说明
公网地址
msTT安全声明
quick_start
quick_start
训练开发工具链快速入门
user_guide
user_guide
msTT 工具选型指南
mstx
mstx
docs
docs
en
en
api_reference
api_reference
Common
Common
mstxDomainCreateA
mstxDomainDestroy
mstxDomainMarkA
mstxDomainRangeEnd
mstxDomainRangeStartA
mstxGetToolId
mstxMarkA
mstxRangeEnd
mstxRangeStartA
Mem
Mem
mstxMemHeapRegister
mstxMemHeapUnregister
mstxMemPermissionsAssign
mstxMemRegionsRegister
mstxMemRegionsUnregister
contributing
contributing
Contribution Guide
development_guide
development_guide
MindStudio Tools Extension Library Development Guide
install_guide
install_guide
MindStudio Tools Extension Library Installation Guide
legal
legal
Disclaimer
LICENSE Statement
Security Statement
MindStudio Vulnerability Mechanism
release_notes
release_notes
MindStudio Tools Extension Library Release Notes
zh
zh
api_reference
api_reference
Common
Common
mstxDomainCreateA
mstxDomainDestroy
mstxDomainMarkA
mstxDomainRangeEnd
mstxDomainRangeStartA
mstxGetToolId
mstxMarkA
mstxRangeEnd
mstxRangeStartA
Mem
Mem
mstxMemHeapRegister
mstxMemHeapUnregister
mstxMemPermissionsAssign
mstxMemRegionsRegister
mstxMemRegionsUnregister
contributing
contributing
贡献指南
development_guide
development_guide
MindStudio Tools Extension Library 开发指南
install_guide
install_guide
msTX 安装指南
legal
legal
免责声明
LICENSE声明
安全声明
MindStudio 漏洞机制说明
msagent
msagent
docs
docs
en
en
agent_guide
agent_guide
Accuracy Precision Debugging
Minos Document Assistant
Modeling: Simulation Modeling
Operator Tuning
Profiler Performance Tuning
Quantizer: Model Quantization Tuning
best_practices
best_practices
Best Practices for Operator-Level MFU Measurement and Analysis
design
design
msAgent Design Document
msprof_mcp_design
NPU Platform Memory Snapshot Analysis Design
developer_guide
developer_guide
Adding a Custom Agent
1. Overview
Building and Packaging
Contribution Guide
Validating ReadTheDocs Builds Locally
Version and Compatibility
example
example
Accuracy Usage Example
getting_started
getting_started
msAgent Installation Guide
msAgent Quick Start
legal
legal
Disclaimer
LICENSE1
LICENSE2
LICENSE_intro
Security Statement
user_guide
user_guide
Agent YAML Tool/Skills Filter Rules
Configuration and Extension
Context Compaction User Guide
📝 document-ux-review Usage
FAQ
Integrating msAgent Debugging and Tuning Capabilities
Retry Middleware User Guide (Deep Agents/LangChain)
msAgent User Guide
zh
zh
agent_guide
agent_guide
Accuracy 精度调试
Minos 文档辅助
Modeling 仿真建模
Operator 算子调优
Profiler 性能调优
Quantizer 模型量化调优
SpecTrainer 投机解码 on-policy 重采样
best_practices
best_practices
torchnpu.profiler 接口适配最佳实践
精度问题——NaN溢出问题最佳实践
模型融合算子识别与替换最佳实践
算子级 MFU 实测分析最佳实践
模型量化自动调优最佳实践
精度问题——梯度尖刺（Gradient Spike）最佳实践
contributing
contributing
贡献指南
development_guide
development_guide
design
design
msAgent 设计文档
msprof-mcp 设计文档
NPU平台内存快照分析设计文档
添加自定义 Agent
1. 概述
编译与打包
ReadTheDocs 本地验证说明
版本与兼容性
example
example
Accuracy 使用示例
install_guide
install_guide
msAgent安装指南
legal
legal
免责声明
LICENSE1
LICENSE2
License说明
MindStudio-Agent 安全声明
quick_start
quick_start
msAgent快速入门
support
support
FAQ
user_guide
user_guide
Agent YAML Tool/Skills 过滤规则说明
配置与扩展
上下文压缩使用指南
document-ux-review 使用说明
接入 msAgent 调试调优能力
Retry Middleware 使用指南（Deepagents/LangChain）
msAgent使用指南
msboost
msboost
docs
docs
zh
zh
contributing
contributing
贡献流程和规范说明
install_guide
install_guide
MindStudio Boost 安装指南
release_notes
release_notes
MindStudio Boost 版本发布说明
user_guide
user_guide
MindStudio Boost 使用指南
msmonitor-dyno
msmonitor-dyno
docs
docs
en
en
advanced_features
advanced_features
mindstudiomonitor Interfaces
Monitor Features
best_practices
best_practices
msMonitor Use Cases
contributing
contributing
Contributing to MindStudio Monitor
development_guide
development_guide
Development Guide
MindStudio Monitor Feature Analysis and Design Specification
install_guide
install_guide
msMonitor Tool Installation Guide
legal
legal
Disclaimer
License
MindStudio Vulnerability Handling Mechanism
Public Network Address
msMonitor Security Statement
quick_start
quick_start
msMonitor Quick Start
support
support
FAQs
user_guide
user_guide
dyno Usage Guide
dynolog Usage Guide
Using msMonitor with the MindSpore Framework
npu-monitor Usage Guide
nputrace Usage Guide
Overview
zh
zh
advanced_features
advanced_features
mindstudiomonitor模块接口参考
Monitor 特性介绍
best_practices
best_practices
msMonitor 使用案例
contributing
contributing
为MindStudio Monitor贡献
design
design
msmonitor DCMI 采集 + Chrome Trace 分层可视化技术方案设计（RFC）
development_guide
development_guide
msMonitor 开发指南
MindStudio Monitor特性分析与设计说明书
install_guide
install_guide
msMonitor 安装指南
legal
legal
免责声明
License
MindStudio漏洞机制说明
公网地址
msMonitor安全声明
quick_start
quick_start
msMonitor工具快速入门
support
support
FAQ
user_guide
user_guide
dyno使用说明
dynolog使用说明
MindSpore框架下msMonitor的使用方法
npu-monitor使用说明
nputrace使用说明
总体介绍
msmonitor-whl
msmonitor-whl
docs
docs
en
en
advanced_features
advanced_features
mindstudiomonitor Interfaces
Monitor Features
best_practices
best_practices
msMonitor Use Cases
contributing
contributing
Contributing to MindStudio Monitor
development_guide
development_guide
Development Guide
MindStudio Monitor Feature Analysis and Design Specification
install_guide
install_guide
msMonitor Tool Installation Guide
legal
legal
Disclaimer
License
MindStudio Vulnerability Handling Mechanism
Public Network Address
msMonitor Security Statement
quick_start
quick_start
msMonitor Quick Start
support
support
FAQs
user_guide
user_guide
dyno Usage Guide
dynolog Usage Guide
Using msMonitor with the MindSpore Framework
npu-monitor Usage Guide
nputrace Usage Guide
Overview
zh
zh
advanced_features
advanced_features
mindstudiomonitor模块接口参考
Monitor 特性介绍
best_practices
best_practices
msMonitor 使用案例
contributing
contributing
为MindStudio Monitor贡献
design
design
msmonitor DCMI 采集 + Chrome Trace 分层可视化技术方案设计（RFC）
development_guide
development_guide
msMonitor 开发指南
MindStudio Monitor特性分析与设计说明书
install_guide
install_guide
msMonitor 安装指南
legal
legal
免责声明
License
MindStudio漏洞机制说明
公网地址
msMonitor安全声明
quick_start
quick_start
msMonitor工具快速入门
support
support
FAQ
user_guide
user_guide
dyno使用说明
dynolog使用说明
MindSpore框架下msMonitor的使用方法
npu-monitor使用说明
nputrace使用说明
总体介绍
TraceContext类
¶
GetTraceCtx
addResAttribute
ExtractAndAttach
Attach
Unattach
GetCurrent
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