GANEncoderContext¶

Inheritance Diagram

class ashpy.contexts.gan.GANEncoderContext(dataset=None, generator_model=None, discriminator_model=None, encoder_model=None, generator_loss=None, discriminator_loss=None, encoder_loss=None, metrics=None, log_eval_mode=<LogEvalMode.TRAIN: 1>, global_step=<tf.Variable 'global_step:0' shape=() dtype=int64, numpy=0>, ckpt=None)[source]¶

Bases: ashpy.contexts.gan.GANContext

ashpy.contexts.gan.GANEncoderContext measure the specified metrics on the GAN.

Methods

__init__([dataset, generator_model, …])

Initialize the Context.

Attributes

`dataset`	Retrieve the dataset.
`discriminator_loss`	Retrieve the discriminator loss.
`discriminator_model`	Retrieve the discriminator model.
`encoder_loss`	Retrieve the encoder loss.
`encoder_model`	Retrieve the encoder model.
`generator_loss`	Retrieve the generator loss.
`generator_model`	Retrieve the generator model.
`global_step`	Retrieve the global_step.
`log_eval_mode`	Retrieve model(s) mode.
`metrics`	Retrieve the metrics.

__init__(dataset=None, generator_model=None, discriminator_model=None, encoder_model=None, generator_loss=None, discriminator_loss=None, encoder_loss=None, metrics=None, log_eval_mode=<LogEvalMode.TRAIN: 1>, global_step=<tf.Variable 'global_step:0' shape=() dtype=int64, numpy=0>, ckpt=None)[source]¶

Initialize the Context.

Parameters

dataset (tf.data.Dataset) – Dataset of tuples. [0] true dataset, [1] generator input dataset.
generator_model (tf.keras.Model) – The generator.
discriminator_model (tf.keras.Model) – The discriminator.
encoder_model (tf.keras.Model) – The encoder.
generator_loss (ashpy.losses.Executor()) – The generator loss.
discriminator_loss (ashpy.losses.Executor()) – The discriminator loss.
encoder_loss (ashpy.losses.Executor()) – The encoder loss.
metrics (list of [ashpy.metrics.metric.Metric]) – All the metrics to be used to evaluate the model.
log_eval_mode (ashpy.modes.LogEvalMode) – Models’ mode to use when evaluating and logging.
global_step (tf.Variable) – tf.Variable that keeps track of the training steps.
ckpt (tf.train.Checkpoint) – checkpoint to use to keep track of models status.

Return type

None

property encoder_loss¶

Retrieve the encoder loss.

Return type: Optional[Executor]

property encoder_model¶

Retrieve the encoder model.

Return type: Model
Returns: tf.keras.Model.