Frequently Used Import Targets
Includes a brief summary of important symbols and modules.
Service Users
If you write client code interacting with the OSS Vizier service, use these import targets:
from vizier.service import pyvizier as vz: Exposes the same set of symbol names as
vizier.pyvizier
.vizier.service.pyvizier.Foo
is a subclass or an alias ofvizier.pyvizier.Foo
, and can be converted into protobufs.from vizier.service import …: Include binaries and internal utilities.
Algorithm Developers
If you write algorithm code (Designers or Pythia policies) in OSS Vizier, use these import targets:
from vizier import pyvizier as vz: Pure python building blocks of OSS Vizier. Cross-platform code, including Pythia policies, must use this
pyvizier
instance.Trial
andProblemStatement
are important classes.
from vizier.pyvizier import converters: Convert between
pyvizier
objects and numpy arrays.TrialToNumpyDict
: Converts parameters (and metrics) into a dict of numpy arrays. Preferred conversion method if you intended to train an embedding of categorical/discrete parameters, or data includes missing parameters or metrics.TrialToArrayConverter
: Converts parameters (and metrics) into an array.
from vizier.interfaces import serializable: Abstractions for serializable objects.
PartiallySerializable
,Serializable
Algorithm Abstractions
from vizier import pythia: Abstractions for Pythia policies.
Policy
,PolicySupporter
: Key abstractions.LocalPolicyRunner
: Use it for running aPolicy
in RAM.
from vizier import algorithms: Abstractions for algorithms.
Designer
: Stateful algorithm abstraction.DesignerPolicy
: WrapsDesigner
into a Pythia Policy.GradientFreeMaximizer
: For optimizing acquisition functions.(Partially)SerializableDesigner
: Designers who wish to optimize performance by saving states.
Tensorflow Modules
from vizier import tfp: Tensorflow-Probability utilities.
acquisitions
: Acquisition functions module.AcquisitionFunction
: Abstraction.UpperConfidenceBound
,ExpectedImprovement
, etc.
bijectors
: Bijectors module.YeoJohnson
: Implements both Yeo-Johnson and Box-Cox transformations.optimal_power_transformation
: Returns the optimal power transformation.flip_sign
: returns a sign-flip bijector.
from vizier import keras as vzk:
vzk.layers
: Layers usually wrappingtfp
classes.variable_from_prior
: Utility layer for handling regularized variables.
vzk.models
: Most of the useful models don’t easily fit into Keras’sModel
abstraction, but we may add some for display.vzk.optim
: Wrappers around optimizers intfp
orkeras
.