brainpy.dyn.base.Container#

class brainpy.dyn.base.Container(*ds_tuple, name=None, mode=NormalMode, **ds_dict)[source]#

Container object which is designed to add other instances of DynamicalSystem.

Parameters
  • steps (tuple of function, tuple of str, dict of (str, function), optional) – The step functions.

  • monitors (tuple, list, Monitor, optional) – The monitor object.

  • name (str, optional) – The object name.

  • show_code (bool) – Whether show the formatted code.

  • ds_dict (dict of (str, )) – The instance of DynamicalSystem with the format of “key=dynamic_system”.

__init__(*ds_tuple, name=None, mode=NormalMode, **ds_dict)[source]#

Methods

__init__(*ds_tuple[, name, mode])

clear_input()

get_delay_data(identifier, delay_step, *indices)

Get delay data according to the provided delay steps.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

offline_fit(target, fit_record)

offline_init()

online_fit(target, fit_record)

online_init()

register_delay(identifier, delay_step, ...)

Register delay variable.

register_implicit_nodes(*nodes, **named_nodes)

register_implicit_vars(*variables, ...)

reset([batch_size])

Reset function which reset the whole variables in the model.

reset_local_delays([nodes])

Reset local delay variables.

reset_state([batch_size])

Reset function which reset the states in the model.

save_states(filename[, variables])

Save the model states.

train_vars([method, level, include_self])

The shortcut for retrieving all trainable variables.

unique_name([name, type_])

Get the unique name for this object.

update(tdi, *args, **kwargs)

Update function of a container.

update_local_delays([nodes])

Update local delay variables.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

global_delay_data

mode

Mode of the model, which is useful to control the multiple behaviors of the model.

name

Name of the model.