brainpy.layers.LSTM

class brainpy.layers.LSTM(*args, **kwargs)

LSTM.

Deprecated since version 2.2.3.4: Use LSTMCell instead. LSTM will be removed since version 2.4.0.

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
clear_input()
cpu()	Move all variable into the CPU device.
cuda()	Move all variables into the GPU device.
get_delay_data(identifier, delay_step, *indices)	Get delay data according to the provided delay steps.
load_state_dict(state_dict[, warn])	Copy parameters and buffers from state_dict into this module and its descendants.
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[, node_cls])
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.
state_dict()	Returns a dictionary containing a whole state of the module.
to(device)	Moves all variables into the given device.
tpu()	Move all variables into the TPU device.
train_vars([method, level, include_self])	The shortcut for retrieving all trainable variables.
tree_flatten()	Flattens the object as a PyTree.
tree_unflatten(aux, dynamic_values)	New in version 2.3.1.
unique_name([name, type_])	Get the unique name for this object.
update(sha, x)	The function to specify the updating rule.
update_local_delays([nodes])	Update local delay variables.
vars([method, level, include_self, ...])	Collect all variables in this node and the children nodes.

Attributes

c	Memory cell.
global_delay_data	Global delay data, which stores the delay variables and corresponding delay targets.
h	Hidden state.
mode	Mode of the model, which is useful to control the multiple behaviors of the model.
name	Name of the model.