Data Processing

Auto Augmentation
Lightweight Data Processing
Single-Node Data Cache
Optimizing the Data Processing

Graph Compilation

Process Control Statements
Compiling Performance Optimization for Static Graph Network
Customizing Reverse Propagation Function of Cell
Calling the Custom Class
Construct Constants In the Network
Dependency Control

Model Training Optimization

Enabling Mixed Precision
Gradient Accumulation Algorithm
Adaptive Gradient Summation Algorithm
Dimension Reduction Training Algorithm

Custom Operator

Custom Operators (Custom-based)

Model Inference

Inference Model Overview
Inference on a GPU
Inference on the Ascend 910 AI processor
Inference Using the MindIR Model on Ascend 310 AI Processors
Inference on the Ascend 310 AI Processor

Debugging and Tuning

Function Debug
Performance Tuning
Precision Optimization↗

Distributed Parallel

Distributed Parallel Training Mode
Distributed Case
Distributed Inference
Saving and Loading Models in Hybrid Parallel Mode
Multi Dimensional
Other Features

Environment Variables

Environment Variables

MindSpore

»
Function Debug
View page source

Function Debug

https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r1.9/resource/_static/logo_source_en.png

Custom Debugging Information
Reading IR
Using Dump in the Graph Mode
Applying PyNative Mode
Fixed Randomness to Reproduce Run Results of Script

Previous Next

© Copyright MindSpore.

Built with Sphinx using a theme provided by Read the Docs.