neuroaikit.tf.layers.snubasiccell.SNUBasicCell

class neuroaikit.tf.layers.snubasiccell.SNUBasicCell(*args, **kwargs)

Bases: keras.engine.base_layer.Layer

This is a basic SNU cell.

Parameters

• units – Number of units to create in the layer

• decay – Membrane potential decay multiplier, defaults to 0.8, i.e. 0.8 of the previous membrane potential is retained

• activation – Activation function, defaults to step_function. See TF_Misc.Activations.

• g – Internal state activation function that optionally constraints the state, defaults to tf.identity (no constraint)

• recurrent – bool, defaults to False. If True, SNU includes recurrent connections inside entire layer.

Constructor method

Methods

add_loss	Add loss tensor(s), potentially dependent on layer inputs.
add_metric	Adds metric tensor to the layer.
add_update	Add update op(s), potentially dependent on layer inputs.
add_variable	Deprecated, do NOT use! Alias for add_weight.
add_weight	Adds a new variable to the layer.
apply	Deprecated, do NOT use!
build	Overriding build method that creates the variables
call	Overriding call method that defines the cell dynamics’ graph
compute_mask	Computes an output mask tensor.
compute_output_shape	Computes the output shape of the layer.
compute_output_signature	Compute the output tensor signature of the layer based on the inputs.
count_params	Count the total number of scalars composing the weights.
finalize_state	Finalizes the layers state after updating layer weights.
from_config	Creates a layer from its config.
get_config	Returns the config of the layer.
get_input_at	Retrieves the input tensor(s) of a layer at a given node.
get_input_mask_at	Retrieves the input mask tensor(s) of a layer at a given node.
get_input_shape_at	Retrieves the input shape(s) of a layer at a given node.
get_losses_for	Deprecated, do NOT use!
get_output_at	Retrieves the output tensor(s) of a layer at a given node.
get_output_mask_at	Retrieves the output mask tensor(s) of a layer at a given node.
get_output_shape_at	Retrieves the output shape(s) of a layer at a given node.
get_updates_for	Deprecated, do NOT use!
get_weights	Returns the current weights of the layer, as NumPy arrays.
set_weights	Sets the weights of the layer, from NumPy arrays.
with_name_scope	Decorator to automatically enter the module name scope.

Attributes

activity_regularizer	Optional regularizer function for the output of this layer.
compute_dtype	The dtype of the layer’s computations.
dtype	The dtype of the layer weights.
dtype_policy	The dtype policy associated with this layer.
dynamic	Whether the layer is dynamic (eager-only); set in the constructor.
inbound_nodes	Deprecated, do NOT use! Only for compatibility with external Keras.
input	Retrieves the input tensor(s) of a layer.
input_mask	Retrieves the input mask tensor(s) of a layer.
input_shape	Retrieves the input shape(s) of a layer.
input_spec	InputSpec instance(s) describing the input format for this layer.
losses	List of losses added using the add_loss() API.
metrics	List of metrics added using the add_metric() API.
name	Name of the layer (string), set in the constructor.
name_scope	Returns a tf.name_scope instance for this class.
non_trainable_variables	Sequence of non-trainable variables owned by this module and its submodules.
non_trainable_weights	List of all non-trainable weights tracked by this layer.
outbound_nodes	Deprecated, do NOT use! Only for compatibility with external Keras.
output	Retrieves the output tensor(s) of a layer.
output_mask	Retrieves the output mask tensor(s) of a layer.
output_shape	Retrieves the output shape(s) of a layer.
stateful
submodules	Sequence of all sub-modules.
supports_masking	Whether this layer supports computing a mask using compute_mask.
trainable
trainable_variables	Sequence of trainable variables owned by this module and its submodules.
trainable_weights	List of all trainable weights tracked by this layer.
updates
variable_dtype	Alias of Layer.dtype, the dtype of the weights.
variables	Returns the list of all layer variables/weights.
weights	Returns the list of all layer variables/weights.

build(input_shape)

Overriding build method that creates the variables

Parameters

input_shape – Shape of the input

call(inputs, states)

Overriding call method that defines the cell dynamics’ graph

Parameters

• inputs – Tensor representing the input in particular timestep

• states – Tuple with previous state values

Returns

Output values, State values.