IBM Analog Hardware Acceleration Kit

Get started

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

Analog AI Concepts

  • Analog AI
  • Analog AI Hardware
  • Advantages and Challenges

Cloud/Composer

  • Analog AI Cloud Composer Overview
  • Composer CLI

Using the Simulator

  • Using aihwkit Simulator

Analog DNN Training

  • Specialized Update Algorithms
  • Analog Training Presets

Analog DNN Inference

  • Inference and PCM Statistical Model
  • Analog Hardware-aware Training
  • Inference with Analog CMO-ReRAM Statistical Model

Advanced Guides

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

References

  • API Reference
  • Paper References
IBM Analog Hardware Acceleration Kit
  • aihwkit.nn package
  • View page source

aihwkit.nn package

Neural network modules.

Subpackages

  • aihwkit.nn.modules package
    • Subpackages
      • aihwkit.nn.modules.rnn package
        • Submodules
    • Submodules
      • aihwkit.nn.modules.base module
        • AnalogLayerBase
      • aihwkit.nn.modules.container module
        • AnalogContainerBase
        • AnalogSequential
        • AnalogWrapper
      • aihwkit.nn.modules.conv module
        • AnalogConv1d
        • AnalogConv2d
        • AnalogConv3d
      • aihwkit.nn.modules.conv_mapped module
        • AnalogConv1dMapped
        • AnalogConv2dMapped
        • AnalogConv3dMapped
      • aihwkit.nn.modules.linear module
        • AnalogLinear
      • aihwkit.nn.modules.linear_mapped module
        • AnalogLinearMapped

Submodules

  • aihwkit.nn.conversion module
    • convert_to_analog()
    • convert_to_digital()
    • specific_rpu_config_id()

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