neuroaikit.tf.layers.snubasiccell.SNUBasicCell

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

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)[source]

Overriding build method that creates the variables

Parameters

input_shape – Shape of the input

call(inputs, states)[source]

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.