alpha-4 release

What's new?

• refactored structure of neuron models to make it easier to integrate custom neurons
• added recurrent Leaky neuron RLeaky
• added recurrent Synaptic neuron RSynaptic
• Spiking LSTM neurons added SLSTM
• Spiking Convolutional 2d LSTMs added SConv2dLSTM
• learnable thresholds for all neurons
• learnable explicit recurrence
• Reset mechanism now includes 'none' as an option
• update unit tests

snntorch.surrogate

• Triangular surrogate
• Straight through estimator

snntorch.functional

• mse_temporal_loss function added
  Applies mean square error the first F spikes. Option for tolerance included, as well as passing labels to be converted into spike-time targets.

• ce_temporal_loss added
  Applies cross entropy loss to an inversion of the first spike. Inversion options include -1 * x and 1/x which means maximizing the logit of the correct class corresponds to minimizing the correct neuron's firing time.

• accuracy_temporal added
  Measures accuracy based on the occurrence of the first spike

Full Changelog: v0.4.11...v0.5.0