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0.3.3
  • GETTING STARTED
    • Installation
    • Fundamentals of Sinabs
    • A quick (and over-simplified) introduction to spiking neurons
    • Quickstart Sinabs
    • Python versions, pyenv and pipenv
  • TUTORIALS
    • Training by backpropagation through time (BPTT)
    • Converting an ANN to an SNN
    • sinabs Tutorial 使用入门
    • Number of synaptic operations and how to minimise them
    • Choosing a neuron model
    • Changing activations in spiking layers
  • PLUGINS
  • API REFERENCE
    • network
    • layers
      • IAF
      • LIF
      • ALIF
      • ExpLeak
    • activation
      • spike generation
      • reset mechanisms
      • surrogate gradients
    • from_torch
    • SynOpCounter
  • ABOUT
    • About this project
    • How is Sinabs different?
    • Contributing to sinabs
    • Release notes
Theme by the Executable Book Project
  • repository
  • open issue
  • suggest edit
  • .rst

API REFERENCE

API REFERENCE#

  • network
  • layers
    • Main spiking layers
      • IAF
      • IAFRecurrent
      • IAFSqueeze
      • LIF
      • LIFRecurrent
      • LIFSqueeze
      • ALIF
      • ALIFRecurrent
    • Non-spiking layers
      • ExpLeak
      • ExpLeakSqueeze
    • Pooling
    • Conversion from images / analog signals
    • Parent layers
    • Auxiliary layers
    • ANN layers
  • activation
    • spiking activation
      • spike generation
        • SingleSpike
        • MultiSpike
      • reset mechanisms
        • MembraneReset
        • MembraneSubtract
      • surrogate gradients
        • Heaviside
        • MultiGaussian
        • SingleExponential
  • from_torch
  • SynOpCounter
    • SNNSynOpCounter
    • SynOpCounter

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