autoencoders¶

Collection of Fully Connected Autoencoders.

Classes

Autoencoder Primitive Model for all fully connected autoencoders.

class ashpy.models.fc.autoencoders.Autoencoder(hidden_units, encoding_dimension, output_shape)[source]¶

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

Primitive Model for all fully connected autoencoders.

Examples

Direct Usage:

autoencoder = Autoencoder(
    hidden_units=[256,128,64],
    encoding_dimension=100,
    output_shape=55
)

encoding, reconstruction = autoencoder(tf.zeros((1, 55)))
print(encoding.shape)
print(reconstruction.shape)

__init__(hidden_units, encoding_dimension, output_shape)[source]¶

Instantiate the Decoder.

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)[source]¶

Execute the model on input data.

Parameters:	inputs (`tf.Tensor`) – Input tensors. training (`bool`) – Training flag.
Returns:	(encoding, reconstruction) – Pair of tensors.