MindSpore
Design
MindSpore Design Overview
Functional Differential Programming
Distributed Training Design
Combination of Dynamic and Static Graphs
Graph-Kernel Fusion Acceleration Engine
MindSpore IR (MindIR)
Full-scenarios Unification
Second Order Optimizer
ResNet-50 Second-Order Optimization Practice
Design of Visualization↗
High Performance Data Processing Engine
Glossary
Specification
Benchmarks
Network List↗
API List
Syntax Support
API
mindspore
mindspore.nn
mindspore.ops
mindspore.ops.primitive
mindspore.amp
mindspore.train
mindspore.communication
mindspore.common.initializer
mindspore.dataset
mindspore.dataset.transforms
mindspore.mindrecord
mindspore.nn.probability
mindspore.nn.transformer
mindspore.rewrite
mindspore.boost
mindspore.numpy
mindspore.scipy
C++ API↗
API Mapping
PyTorch and MindSpore API Mapping Table
TensorFlow and MindSpore API Mapping Table
Migration Guide
Overview of Migration Guide
Environment Preparation and Information Acquisition
Model Analysis and Preparation
Constructing MindSpore Network
Debugging and Tuning
Network Migration Debugging Example
FAQs
Differences Between MindSpore and PyTorch
Using Third-party Operator Libraries Based on Customized Interfaces
FAQ
Installation
Data Processing
Implement Problem
Network Compilation
Operators Compile
Migration from a Third-party Framework
Performance Tuning
Precision Tuning
Distributed Configuration
Inference
Feature Advice
RELEASE NOTES
Release Notes
MindSpore
»
Second Order Optimizer
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Second Order Optimizer
ResNet-50 Second-Order Optimization Practice