Module: tfdf.keras.core

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Core wrapper.

This file contains the Keras model wrapper around an Yggdrasil model/learner. While it can be used directly, the helper functions in / should be preferred as they explicit more directly the learner specific hyper-parameters.

Usage example:

# Indirect usage
import tensorflow_decision_forests as tfdf

model = tfdf.keras.RandomForestModel()
train_ds = tfdf.keras.pd_dataframe_to_tf_dataset(...)

# Direct usage
import tensorflow_decision_forests as tfdf

model = tfdf.keras.CoreModel(learner="RANDOM_FOREST")
train_ds = tfdf.keras.pd_dataframe_to_tf_dataset(...)

See "CoreModel" for more details


class AdvancedArguments: Advanced control of the model that most users won't need to use.

class CoreModel: Keras Model V2 wrapper around an Yggdrasil Learner and Model.

class FeatureSemantic: Semantic (e.g.

class FeatureUsage: Semantic and hyper-parameters for a single feature.

class HyperParameterTemplate: Named and versionned set of hyper-parameters.

class InferenceCoreModel: Keras Model V2 wrapper around an Yggdrasil Model.

class YggdrasilDeploymentConfig: A ProtocolMessage

class YggdrasilTrainingConfig: A ProtocolMessage

class datetime: datetime(year, month, day[, hour[, minute[, second[, microsecond[,tzinfo]]]]])


get_data_handler(...): Creates a DataHandler, providing standardized access to a Dataset.

get_worker_idx_and_num_workers(...): Gets the current worker index and the total number of workers.

no_automatic_dependency_tracking(...): Disables automatic dependency tracking on attribute assignment.

pd_dataframe_to_tf_dataset(...): Converts a Panda Dataframe into a TF Dataset compatible with Keras.

yggdrasil_model_to_keras_model(...): Converts an Yggdrasil model into a Keras model.

Type Aliases


Task Instance of google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper
TaskType 'abstract_model_pb2.Task'
absolute_import Instance of __future__._Feature
division Instance of __future__._Feature
print_function Instance of __future__._Feature