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|
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
initialize()
__call__
__call__()
Perform one step of this training algorithm.