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GETTING STARTED
Installation
Fundamentals of Sinabs
A quick (and over-simplified) introduction to spiking neurons
Quickstart Sinabs
Python versions, pyenv and pipenv
Speck/DynapCNN
Overview
The Basics
Advanced
Dangers
Dynapcnn Visualizer
Specksim
FAQs
Troubleshooting and Tips
Chip Errata(Hardware Bugs)
Available Network Architecture
Available Operations
Device Management
Output Monitoring
Save Samna Config As Binary
How to add support for a new chip
How To Leak The Neurons On The Devkit
SINABS GALLERY
Neuron models
Exponential Leaky Layer (ExpLeak)
Adaptive Leaky Integrate and Fire (ALIF)
Integrate and Fire (IAF)
Leaky Integrate and Fire (LIF)
Spike functions
MultiSpike
SingleSpike
MaxSpike
Surrogate gradient functions
Gaussian
Heaviside
MultiGaussian
SingleExponential
PeriodicExponential
TUTORIALS
Training by backpropagation through time (BPTT)
Converting an ANN to an SNN
Training NMNIST for deployment on Speck using EXODUS
Scaling parameters for rate-coded conversion to SNNs
Import a model from NIR and deploy it to SPECK
sinabs Tutorial 使用入门
Hardware Tutorials
Quick Start With N-MNIST
Visualize DVS Input
Play With Speck’s DVS
How To Leak The Neurons On The Devkit
Power Monitoring
Spike Count Visualization
Using Readout Layer
HOW TOS
Training an ANN with fewer SynOps
Training an SNN with fewer SynOps and monitoring the firing rate
Add custom hooks to monitor network properties
Change activations in spiking layers
PLUGINS
API REFERENCE
network
layers
StatefulLayer
SqueezeMixin
IAF
IAFSqueeze
IAFRecurrent
LIF
LIFSqueeze
LIFRecurrent
ALIF
ALIFRecurrent
ExpLeak
ExpLeakSqueeze
SpikingMaxPooling2dLayer
SumPool2d
Img2SpikeLayer
Sig2SpikeLayer
Cropping2dLayer
Repeat
FlattenTime
UnflattenTime
NeuromorphicReLU
QuantizeLayer
activation
SingleSpike
MultiSpike
MaxSpike
MembraneReset
MembraneSubtract
SingleExponential
PeriodicExponential
Heaviside
Gaussian
MultiGaussian
from_torch
hooks
SynOpCounter
utils
nir
sinabs.backend.dynapcnn
chip_factory
config_builder
crop2d
discretize
dvs_layer
dynapcnn_network
dynapcnn_layer
exceptions
flipdims
io
mapping
utils
dynapcnn_visualizer
specksim
ABOUT
About this project
How is Sinabs different?
Contributing to sinabs
Release notes
CONTACT US
Repository
Suggest edit
Open issue
.rst
.pdf
io
io
#
This module contains methods to handle
samna
devices, IO and other convenience methods.
