MindSpore
Design
Technical White Paper
MindSpore Automatic Differentiation
Distributed Training Design
MindSpore IR (MindIR)
High Performance Data Processing Engine
Graph Kernel Fusion
Second Order Optimizer
Design of Visualization↗
Glossary
Note
Benchmarks
Network List
Operator List
Syntax Support
Environment Variables
API Mapping
API
mindspore
mindspore.common.initializer
mindspore.communication
mindspore.context
mindspore.dataset
mindspore.dataset.audio
mindspore.dataset.config
mindspore.dataset.text
mindspore.dataset.transforms
mindspore.dataset.vision
mindspore.mindrecord
mindspore.nn
mindspore.nn.probability
mindspore.nn.transformer
mindspore.numpy
mindspore.ops
mindspore.ops.functional
mindspore.parallel
mindspore.parallel.nn
mindspore.profiler
mindspore.scipy
mindspore.train
mindspore.boost (experimental)
C++ API↗
Migration Guide
Overview
Preparation
Network Script Analysis
Network Script Development
Network Debugging
Performance Profiling
Inference Execution
Network Migration Debugging Example
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
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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.
Syntax Support
Support for static graph syntax, tensor index, etc.
API
MindSpore API description list.
API Mapping
API mapping between PyTorch and MindSpore, TensorFlow and MindSpore provided by the community.
Migration Guide
The complete steps and considerations for migrating neural networks from other machine learning frameworks to MindSpore.
FAQ
Frequently asked questions and answers, including installation, data processing, compilation and execution, debugging and tuning, distributed parallelism, inference, etc.