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.cloud.converter package
  • View page source

aihwkit.cloud.converter package

Conversion utilities for interacting with the AIHW Composer API.

Subpackages

  • aihwkit.cloud.converter.definitions package
  • aihwkit.cloud.converter.v1 package
    • Submodules
      • aihwkit.cloud.converter.v1.analog_info module
        • AnalogInfo
      • aihwkit.cloud.converter.v1.i_mappings module
        • Function
        • InverseMappings
        • LayerFunction
        • Mappings
        • Type
        • build_inverse_mapping()
      • aihwkit.cloud.converter.v1.inferencing module
        • BasicInferencingConverter
        • BasicInferencingResultConverter
      • aihwkit.cloud.converter.v1.noise_model_info module
        • NoiseModelInfo
      • aihwkit.cloud.converter.v1.rpu_config_info module
        • NoiseModelDeviceIDException
        • RPUconfigInfo

Submodules

  • aihwkit.cloud.converter.exceptions module
    • ConversionError

© Copyright 2020, 2021, 2022, 2023, 2024, 2025, 2026 IBM Research.

Built with Sphinx using a theme provided by Read the Docs.