norse.torch.utils.tensorboard module¶
Tensorboard related utilities.
- norse.torch.utils.tensorboard.hook_spike_activity_mean(key, writer)[source]¶
Generates a hook that can be applied to stateful torch Modules. The hook plots the mean neuron activity as a line, assuming that the module output is a tuple of (spikes, state). That is, this will not work on modules that only returns a single tensor as output (i. e. have no state).
Read more about hooks in PyTorch Modules in the Module documentation.
Example
>>> from torch.utils.tensorboard import SummaryWriter >>> import norse.torch as snn >>> from snn.util import tensorboard >>> hook = tensorboard.hook_spike_activity_mean("lif", SummaryWriter()) >>> snn.LIFCell().register_forward_hook(hook)
- norse.torch.utils.tensorboard.hook_spike_activity_sum(key, writer)[source]¶
Generates a hook that can be applied to stateful torch Modules. The hook plots the summed neuron activity as a line, assuming that the module output is a tuple of (spikes, state). That is, this will not work on modules that only returns a single tensor as output (i. e. have no state).
Read more about hooks in PyTorch Modules in the Module documentation.
Example
>>> from torch.utils.tensorboard import SummaryWriter >>> import norse.torch as snn >>> from snn.util import tensorboard >>> hook = tensorboard.hook_spike_activity_sum("lif", SummaryWriter()) >>> snn.LIFCell().register_forward_hook(hook)
- norse.torch.utils.tensorboard.hook_spike_histogram_mean(key, writer)[source]¶
Generates a hook that can be applied to stateful torch Modules. The hook shows a histogram of mean neuron activity, assuming that the module output is a tuple of (spikes, state). That is, this will not work on modules that only returns a single tensor as output (i. e. have no state).
Read more about hooks in PyTorch Modules in the Module documentation.
Example
>>> from torch.utils.tensorboard import SummaryWriter >>> import norse.torch as snn >>> from snn.util import tensorboard >>> hook = tensorboard.hook_spike_histogram_mean("lif", SummaryWriter()) >>> snn.LIFCell().register_forward_hook(hook)
- norse.torch.utils.tensorboard.hook_spike_histogram_sum(key, writer)[source]¶
Generates a hook that can be applied to stateful torch Modules. The hook shows a histogram of the summed neuron activity, assuming that the module output is a tuple of (spikes, state). That is, this will not work on modules that only returns a single tensor as output (i. e. have no state).
Read more about hooks in PyTorch Modules in the Module documentation.
Example
>>> from torch.utils.tensorboard import SummaryWriter >>> import norse.torch as snn >>> from snn.util import tensorboard >>> hook = tensorboard.hook_spike_histogram_sum("lif", SummaryWriter()) >>> snn.LIFCell().register_forward_hook(hook)
- norse.torch.utils.tensorboard.hook_spike_image(key, writer)[source]¶
Generates a hook that can be applied to stateful torch Modules. The hook plots the spiked output, assuming that the module output is a tuple of (spikes, state). That is, this will not work on modules that only returns a single tensor as output (i. e. have no state).
Read more about hooks in PyTorch Modules in the Module documentation.
Example
>>> from torch.utils.tensorboard import SummaryWriter >>> import norse.torch as snn >>> from snn.util import tensorboard >>> hook = tensorboard.hook_spike_image("lif", SummaryWriter()) >>> snn.LIFCell().register_forward_hook(hook)
