tf.contrib.distribute.StandardSingleLossStep

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

Inherits From: StandardInputStep

tf.contrib.distribute.StandardSingleLossStep(
    dataset_fn, loss_fn, optimizer, distribution, iterations_per_step=1
)

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.

Attributes
distribution

Methods

initialize

View source

initialize()

__call__

View source

__call__()

Perform one step of this training algorithm.