spikingjelly.activation_based.examples package#

Spiking FCNet for MNIST#

Spiking CNN for Fashion MNIST#

Spike-based BP for CIFAR-10#

DVS Gesture Classification#

Optimizing Training Memory: Spiking VGG for CIFAR10-DVS#

See the tutorial and the Github repo for more details.

class spikingjelly.activation_based.examples.memopt.lightning_modules.ClassificationLightningModule(*args, **kwargs)[源代码]#

基类：LightningModule

参数:

net (Module)
criterion (Module)
num_classes (int)
y_with_T (bool)

forward(x)[源代码]#

training_step(batch, batch_idx)[源代码]#

on_train_epoch_end()[源代码]#

validation_step(batch, batch_idx)[源代码]#

on_validation_epoch_end()[源代码]#

Speech Commands#

RSNN for Sequential Fashion MNIST#

Spiking LSTM for Sequential MNIST#

class spikingjelly.activation_based.examples.spiking_lstm_sequential_mnist.Net[源代码]#

基类：Module

forward(x)[源代码]#

spikingjelly.activation_based.examples.spiking_lstm_sequential_mnist.main()[源代码]#

Spiking LSTM for Text Classification#

A2C#

DQN_state#

class spikingjelly.activation_based.examples.dqn_state.ReplayMemory(capacity)[源代码]#

基类：object

push(*args)[源代码]#: Saves a transition.

sample(batch_size)[源代码]#

class spikingjelly.activation_based.examples.dqn_state.DQN(input_size, hidden_size, output_size)[源代码]#

基类：Module

forward(x)[源代码]#

PPO#

spikingjelly.activation_based.examples.ppo.make_env()[源代码]#

class spikingjelly.activation_based.examples.ppo.ActorCritic(num_inputs, num_outputs, hidden_size, std=0.0)[源代码]#

基类：Module

forward(x)[源代码]#

Common Utilities#

common