tf.contrib.distribute.StandardSingleLossStep

Class StandardSingleLossStep

Inherits From: StandardInputStep

Defined in tensorflow/contrib/distribute/python/step_fn.py.

A step function that implements a training step for a feed forward network.

An instance of this class is intended to be used as a callable:

...
step = step_fn.StandardSingleLossStep(
    dataset, loss_fn, optimizer, distribution)

# Run a single training step on a given DistributionStrategy:
step(distribution)
...

Args:

• dataset_fn: a function that returns a tf.data Dataset that produces the input for the model.
• loss_fn: a function that takes a context and inputs as arguments. It returns the loss for those inputs. context is an instance of values.MultiStepContext that will be passed when loss_fn is run. context can be used to specify the outputs to be returned from loss_fn, among other things.
• optimizer: an optimizer that implements an update rule.
• distribution: a DistributionStrategy object.

__init__

__init__(
    dataset_fn,
    loss_fn,
    optimizer,
    distribution,
    iterations_per_step=1
)

Initialize self. See help(type(self)) for accurate signature.

Properties

distribution

Methods

tf.contrib.distribute.StandardSingleLossStep.__call__

__call__()

Perform one step of this training algorithm.