NNFusion v0.1 Release
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Build and Installation:
- Support out-of-box installation with docker image
- Support source code install on native system and docker
- Support devices like CUDA GPUs, and ROCm GPUs.
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Models, Framework and Operators:
- Support DNN model formats including TensorFlow and ONNX
- Support commonly used models including AlexNet, VGG11, ResNet50, seq2seq, BERT, etc.
- Support more than 100 commonly used operators.
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Model Compilation and Execution:
- Provide a full-stack optimization mechanism, including data-flow graph optimizations, model-specific kernel selection, kernel co-scheduling, etc.
- Provide ahead-of-time and source-to-source(model-to-code) compilation to reduce runtime overhead
- Remove third-party library or framework dependencies
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Usability:
- Provide command line tool
nnfusion
- Provide tools for users to freeze TensorFlow and PyTorch models
- Provide flexible way to customize optimization through direct code modification on generated code
- Provide command line tool
中文版本说明快捷通道--> #72 (comment)