GANContext¶
Inheritance Diagram
-
class
ashpy.contexts.gan.
GANContext
(dataset=None, generator_model=None, discriminator_model=None, generator_loss=None, discriminator_loss=None, metrics=None, log_eval_mode=<LogEvalMode.TRAIN: 2>, global_step=<tf.Variable 'global_step:0' shape=() dtype=int64, numpy=0>, checkpoint=None)[source]¶ Bases:
ashpy.contexts.context.Context
ashpy.contexts.gan.GANContext
measure the specified metrics on the GAN.Methods
__init__
([dataset, generator_model, …])Initialize the Context.
Attributes
current_batch
Return the current batch.
dataset
Retrieve the dataset.
Retrieve the discriminator loss.
Retrieve the discriminator model.
exception
Return the exception.
Retrieve the fake samples, i.e.
Retrieve the generator inputs.
Retrieve the generator loss.
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, generator_loss=None, discriminator_loss=None, metrics=None, log_eval_mode=<LogEvalMode.TRAIN: 2>, global_step=<tf.Variable 'global_step:0' shape=() dtype=int64, numpy=0>, checkpoint=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.generator_loss (
ashpy.losses.Executor()
) – The generator loss.discriminator_loss (
ashpy.losses.Executor()
) – The discriminator 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.checkpoint (
tf.train.Checkpoint
) – checkpoint to use to keep track of models status.
- Return type
-
property
discriminator_model
¶ Retrieve the discriminator model.
- Return type
Model
- Returns
-
property
fake_samples
¶ Retrieve the fake samples, i.e. output of the generator.
- Return type
Optional
[Tensor
]
-
property
generator_model
¶ Retrieve the generator model.
- Return type
Model
- Returns
-