添加链接
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链接快照平台
  • 输入网页链接,自动生成快照
  • 标签化管理网页链接
  • Debug Tricks
  • Calculate the FLOPs and Parameters of Model
  • Setting the Frequency of Logging, Checkpoint Saving, and Validation
  • EpochBasedTraining to IterBasedTraining
  • Tutorials

  • Runner
  • Dataset and DataLoader
  • Model
  • Evaluation
  • OptimWrapper
  • Parameter Scheduler
  • Advanced tutorials

  • Registry
  • Config
  • BaseDataset
  • Data transform
  • Weight initialization
  • Visualization
  • Abstract Data Element
  • Distribution Communication
  • Logging
  • File IO
  • Global manager (ManagerMixin)
  • Use modules from other libraries
  • Test time augmentation
  • Model Complexity Analysis
  • Design

  • Runner
  • Evaluation
  • Visualization
  • Logging
  • Inference
  • Migration guide

  • Migrate Runner from MMCV to MMEngine
  • Migrate Hook from MMCV to MMEngine
  • Migrate Model from MMCV to MMEngine
  • Migrate parameter scheduler from MMCV to MMEngine
  • Migrate Data Transform to OpenMMLab 2.0
  • API Reference

  • mmengine.analysis
  • mmengine.registry
  • mmengine.config
  • mmengine.runner
  • mmengine._strategy
  • mmengine.hooks
  • mmengine.model
  • mmengine.optim
  • mmengine.evaluator
  • mmengine.structures
  • mmengine.dataset
  • mmengine.infer
  • mmengine.device
  • mmengine.hub
  • mmengine.logging
  • mmengine.visualization
  • mmengine.fileio
  • mmengine.dist
  • mmengine.utils
  • mmengine.utils.dl_utils
  • Notes

  • Changelog of v0.x
  • Contributing to OpenMMLab
  • Switch Language

  • English
  • Install PyTorch

    Before installing MMEngine , please make sure that PyTorch has been successfully installed in the environment. You can refer to PyTorch official installation documentation . Verify the installation with the following command:

    python -c 'import torch;print(torch.__version__)'
    

    If you only want to use the fileio, registry, and config modules in MMEngine, you can install mmengine-lite, which will only install the few third-party library dependencies that are necessary (e.g., it will not install opencv, matplotlib):

    pip install mmengine-lite
    

    Install with mim

    mim is a package management tool for OpenMMLab projects, which can be used to install the OpenMMLab project easily.

    pip install -U openmim
    mim install mmengine
    
  • Build the image

    docker build -t mmengine https://github.com/open-mmlab/mmengine.git#main:docker/release
    

    More information can be referred from mmengine/docker.

  • Run the image

    docker run --gpus all --shm-size=8g -it mmengine
    

    Build mmengine

    # if cloning speed is too slow, you can switch the source to https://gitee.com/open-mmlab/mmengine.git
    git clone https://github.com/open-mmlab/mmengine.git
    cd mmengine
    pip install -e . -v
    

    Build mmengine-lite

    # if cloning speed is too slow, you can switch the source to https://gitee.com/open-mmlab/mmengine.git
    git clone https://github.com/open-mmlab/mmengine.git
    cd mmengine
    MMENGINE_LITE=1 pip install -e . -v
    

    Verify the Installation

    To verify if MMEngine and the necessary environment are successfully installed, we can run this command:

    python -c 'import mmengine;print(mmengine.__version__)'
    
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