FCNNDecoder

Inheritance Diagram

---

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

Bases: ashpy.models.convolutional.decoders.Decoder

Fully Convolutional Decoder. Expected input is a feature map.

Examples

• Direct Usage:

  dummy_generator = FCNNDecoder(
      layer_spec_input_res=(8, 8),
      layer_spec_target_res=(64, 64),
      kernel_size=(5, 5),
      initial_filters=1024,
      filters_cap=16,
      channels=3,
  )
  
  print(dummy_generator(tf.zeros((1, 1, 1, 100))).shape)
  

  (1, 64, 64, 3)
  

Methods

__init__(layer_spec_input_res, …[, …])

Build a Fully Convolutional 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, channels, use_dropout=True, dropout_prob=0.3, non_linearity=<class 'tensorflow.python.keras.layers.advanced_activations.LeakyReLU'>)

Build a Fully Convolutional Decoder.

_add_initial_block(initial_filters, input_res)

Ingest the tf.keras.Model inputs and prepare them for _add_building_block().

Parameters:

• initial_filters (int) – Numbers of filters to used as a base value.
• input_res (tuple of (int, int)) – Shape of the _get_layer_spec() input tensors.