IBM Analog Hardware Acceleration Kit
0.6.0

Get started

  • Installation
  • Advanced installation guide
  • Using the PyTorch integration
  • Glossary

Analog AI Concepts

  • Analog AI
  • Analog AI Hardware
  • Advantages and Challenges

Using the Simulator

  • Using aihwkit Simulator
  • Using Experiments

Analog DNN Training

  • Specialized Update Algorithms
  • Analog Training Presets

Analog DNN Inference

  • Inference and PCM Statistical Model
  • Analog Hardware-aware Training

Advanced Guides

  • aihwkit design
  • Development setup
  • Development conventions
  • Project roadmap
  • Changelog

References

  • API Reference
  • Paper References
IBM Analog Hardware Acceleration Kit
  • »
  • aihwkit.nn.modules package
  • Edit on GitHub

aihwkit.nn.modules package¶

Neural network modules.

Submodules¶

  • aihwkit.nn.modules.base module
  • aihwkit.nn.modules.container module
  • aihwkit.nn.modules.conv module
  • aihwkit.nn.modules.conv_mapped module
  • aihwkit.nn.modules.linear_mapped module
  • aihwkit.nn.modules.linear module
  • aihwkit.nn.modules.rnn module
    • Submodules
      • aihwkit.nn.modules.rnn.cells module
      • aihwkit.nn.modules.rnn.layers module
      • aihwkit.nn.modules.rnn.rnn module

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