MindSpore
Design
Functional Differential Programming
Distributed Training Design
MindSpore IR (MindIR)
Second Order Optimizer
Design of Visualization↗
Glossary
Specification
Benchmarks
Network List
Operator List
Syntax Support
API
mindspore
mindspore.amp
mindspore.common.initializer
mindspore.communication
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.nn
mindspore.scipy
mindspore.boost
C++ API↗
API Mapping
PyTorch and MindSpore
TensorFlow and MindSpore
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.
Specifications
Specifications of benchmark performance, network support, operator support and syntax support.
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.