BaseAutoencoder

Inheritance Diagram

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class ashpy.models.fc.autoencoders.BaseAutoencoder(hidden_units, encoding_dimension, output_shape)

Bases: tensorflow.python.keras.engine.training.Model

Primitive Model for all fully connected autoencoders.

Examples

• Direct Usage:

  autoencoder = BaseAutoencoder(
      hidden_units=[256,128,64],
      encoding_dimension=100,
      output_shape=55
  )
  
  encoding, reconstruction = autoencoder(tf.zeros((1, 55)))
  print(encoding.shape)
  print(reconstruction.shape)
  

Methods

__init__(hidden_units, encoding_dimension, …)	Instantiate the BaseDecoder.
call(inputs[, training])	Execute the model on input data.

Attributes

activity_regularizer	Optional regularizer function for the output of this layer.
dtype
dynamic
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	Gets the network’s input specs.
layers
losses	Losses which are associated with this Layer.
metrics	Returns the model’s metrics added using compile, add_metric APIs.
metrics_names	Returns the model’s display labels for all outputs.
name	Returns the name of this module as passed or determined in the ctor.
name_scope	Returns a tf.name_scope instance for this class.
non_trainable_variables
non_trainable_weights
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.
run_eagerly	Settable attribute indicating whether the model should run eagerly.
sample_weights
state_updates	Returns the updates from all layers that are stateful.
stateful
submodules	Sequence of all sub-modules.
trainable
trainable_variables	Sequence of variables owned by this module and it’s submodules.
trainable_weights
updates
variables	Returns the list of all layer variables/weights.
weights	Returns the list of all layer variables/weights.

__init__(hidden_units, encoding_dimension, output_shape)

Instantiate the BaseDecoder.

Parameters

• hidden_units (tuple of int) – Number of units per hidden layer.

• encoding_dimension (int) – encoding dimension.

• output_shape (int) – output shape, usual equal to the input shape.

Returns

None

call(inputs, training=True)

Execute the model on input data.

Parameters

• inputs (tf.Tensor) – Input tensors.

• training (bool) – Training flag.

Returns

(encoding, reconstruction) – Pair of tensors.