NengoDL

• Introduction
• Installation
  • Installing NengoDL
  • Requirements
  • Developer installation
  • Installing TensorFlow
• User guide
  • NengoDL Simulator
    • Keras integration
    • Choosing which elements to optimize
    • Saving and loading parameters
    • Examples
  • TensorNodes
    • Examples
  • Converter
    • Extending the converter
    • Examples
  • Configuration options
    • trainable
    • planner
    • sorter
    • simplifications
    • inference_only
    • lif_smoothing
    • dtype
    • keep_history
    • stateful
    • use_loop
  • Tips and tricks
    • Speed improvements
    • Training a spiking deep network
• API reference
  • Users
    • Simulator
    • TensorNodes
    • Converter
    • Configuration system
    • Neuron types
    • Distributions
    • Loss functions
    • Callbacks
  • Developers
    • Builder
    • Operator builders
    • Graph construction
    • Signals
    • Graph optimization
    • Layer converters
    • Utilities
    • Benchmarks
• Examples
  • Coming from Nengo to NengoDL
    • Simulating a network with NengoDL
    • Batch processing
    • Specifying model inputs at run time
    • Optimizing model parameters
    • Evaluating model performance
    • Integrating TensorFlow code
    • Conclusion
  • Coming from TensorFlow to NengoDL
    • What is Nengo
    • Simulating a network
    • Spiking networks
    • Inserting TensorFlow code
    • Deep learning parameter optimization
    • NEF parameter optimization
    • Running on neuromorphic hardware
    • Conclusion
  • Integrating a Keras model into a Nengo network
    • Inserting a whole Keras model
    • Inserting Keras layers
    • Building an equivalent network with Nengo objects
    • Conclusion
  • Optimizing a spiking neural network
  • Converting a Keras model to a spiking neural network
    • Converting a Keras model to a Nengo network
    • Converting to a spiking neural network
    • Conclusions
  • Legendre Memory Units in NengoDL
  • Optimizing a cognitive model
  • Optimizing a cognitive model with temporal dynamics
    • Optimizing a memory network
    • Adding memory to the cognitive model
• Additional resources
• Project information
  • Release history
    • Changelog
  • Migration guide
    • NengoDL 2 to 3
  • Contributing to NengoDL
    • Filing issues
    • Making pull requests
    • Contributor agreement
    • More details
  • NengoDL license
    • Licensed code
  • Citation

Github | PyPI