Encoder

Inheritance Diagram

---

class ashpy.models.convolutional.encoders.Encoder(layer_spec_input_res, layer_spec_target_res, kernel_size, initial_filters, filters_cap, output_shape, use_dropout=True, dropout_prob=0.3, non_linearity=<class 'tensorflow.python.keras.layers.advanced_activations.LeakyReLU'>)

Bases: ashpy.models.convolutional.interfaces.Conv2DInterface

Primitive Model for all encoder (i.e., convolution) based architecture.

Notes

Default to DCGAN Discriminator architecture.

Examples

• Direct Usage:

  dummy_generator = Encoder(
      layer_spec_input_res=(64, 64),
      layer_spec_target_res=(8, 8),
      kernel_size=5,
      initial_filters=4,
      filters_cap=128,
      output_shape=1,
  )
  

• Subclassing

  class DummyDiscriminator(Encoder):
      def call(self, inputs, training=True):
          print("Dummy Discriminator!")
          # build the model using
          # self._layers and inputs
          return inputs
  
  dummy_discriminator = DummyDiscriminator(
      layer_spec_input_res=(64, 64),
      layer_spec_target_res=(8, 8),
      kernel_size=5,
      initial_filters=16,
      filters_cap=128,
      output_shape=1,
  )
  dummy_discriminator(tf.zeros((1,28,28,3)))
  

  Dummy Discriminator!
  

Methods

__init__(layer_spec_input_res, …[, …])

Instantiate the Decoder.

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__(layer_spec_input_res, layer_spec_target_res, kernel_size, initial_filters, filters_cap, output_shape, use_dropout=True, dropout_prob=0.3, non_linearity=<class 'tensorflow.python.keras.layers.advanced_activations.LeakyReLU'>)

Instantiate the Decoder.

Parameters:

• layer_spec_input_res (tuple of (int, int)) – Shape of the input tensors.
• layer_spec_target_res (Union[int, Tuple[int, int]]) – (tuple of (int, int)): Shape of tensor desired as output of _get_layer_spec().
• kernel_size (int) – Kernel used by the convolution layers.
• initial_filters (int) – Numbers of filters to used as a base value.
• filters_cap (int) – Cap filters to a set amount, in the case of an Encoder is a ceil value AKA the max amount of filters.
• output_shape (int) – Amount of units of the last tf.keras.layers.Dense.

Returns:

None

Raises:

ValueError – If filters_cap < initial_filters

_add_building_block(filters)

Construct the core of the tf.keras.Model.

The layers specified here get added to the tf.keras.Model multiple times consuming the hyper-parameters generated in the _get_layer_spec().

Parameters:filters (int) – Number of filters to use for this iteration of the Building Block.

_add_final_block(output_shape)

Prepare the results of _add_building_block() for the final output.

Parameters:output_shape (int) – Amount of units of the last tf.keras.layers.Dense