Deep Learning

MindSpore – deep learning framework

MindSpore is a deep learning framework for training and inference across cloud, edge, and mobile environments. It is designed to offer efficient execution while supporting a broad range of AI development workloads.

The framework includes automatic differentiation, distributed training capabilities, and native support for Ascend AI processors.

This is free and open source software.

Key Features

  • Develop and train deep learning models.
  • Supports both training and inference workloads.
  • Designed for cloud, edge, and mobile deployment scenarios.
  • Automatic differentiation based on source transformation.
  • Supports complex control flow, higher-order functions, and closures.
  • Automatic parallelisation for distributed model training.
  • Combines data parallelism, model parallelism, and hybrid parallelism.
  • Provides graph compilation optimisations for neural networks.
  • Native support for Ascend AI processors.
  • Supports CPU and GPU execution environments.
  • Software and hardware co-optimisation for improved execution efficiency.

Website: https://github.com/mindspore-ai/mindspore
Support:
Developer: MindSpore Community
License: Apache License 2.0

MindSpore is written in C++ and Python. Learn C++ with our recommended free books and free tutorials. Learn Python with our recommended free books and free tutorials.


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PyTorch LightningFramework for scaling PyTorch training workflows
JAXHigh-performance numerical computing and ML library
PyTensorLibrary for fast numerical computation
MindSporeFramework for training and deploying neural networks
ElephasDistributed deep learning with Keras and Spark
ChainerPowerful, flexible, and intuitive framework for neural networks
EquinoxNeural network library for building flexible models with JAX
CaffeConvolutional Architecture for Fast Feature Embedding
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CNTKDistributed deep learning
NeupyPython library for neural networks and deep learning

Read our verdict in the software roundup.


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