MindSpore
Design
MindSpore Design Overview
TENSOR VIEWS
Functional and Object-Oriented Fusion Programming Paradigm
Combination of Dynamic and Static Graphs
Static Graph Dynamic Shape
Distributed Parallel Native
High Performance Data Processing Engine
Full-scenarios Unified Architecture
Graph-Kernel Fusion Acceleration Engine
Third-Party Hardware Interconnection
Glossary
Models
Official Models
API
mindspore
mindspore.nn
mindspore.ops
mindspore.ops.primitive
mindspore.mint
mindspore.amp
mindspore.train
mindspore.communication
mindspore.communication.comm_func
mindspore.common.initializer
mindspore.hal
mindspore.dataset
mindspore.dataset.transforms
mindspore.mindrecord
mindspore.nn.probability
mindspore.rewrite
mindspore.multiprocessing
mindspore.boost
mindspore.numpy
mindspore.scipy
mindspore.experimental
API Mapping
PyTorch and MindSpore API Mapping Table
Migration Guide
Overview of Migration Guide
Environment Preparation
Model Analysis and Preparation
Network Constructing Comparison
Debugging and Tuning
Network Migration Debugging Example
FAQs
Syntax Support
Static Graph Syntax Support
Static Graph Syntax - Operators
Static Graph Syntax - Python Statements
Static Graph Syntax - Python Built-in Functions
Tensor Index Support
Environment Variables
Environment Variables
FAQ
Installation
Data Processing
Implement Problem
Network Compilation
Operators Compile
Performance Tuning
Precision Tuning
Distributed Parallel
Inference
Feature Advice
RELEASE NOTES
Release Notes
MindSpore
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MindSpore Documentation
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MindSpore Documentation
Design
The design concept of MindSpore's main functions to help framework developers better understand the overall architecture.
Model Libraries
Contains model examples and performance data for different domains.
API
MindSpore API description list.
API Mapping
API mapping between PyTorch and MindSpore provided by the community.
Migration Guide
The complete steps and considerations for migrating neural networks from other machine learning frameworks to MindSpore.
Syntax Support
Syntax support for static graphs, Tensor indexes, etc.
FAQ
Frequently asked questions and answers, including installation, data processing, compilation and execution, debugging and tuning, distributed parallelism, inference, etc.
RELEASE NOTES
Contains information on major features and augments, API changes for the release versions.