dataset_use_spec: Transform the dataset using the provided spec.

In tfdatasets: Interface to 'TensorFlow' Datasets

Transform the dataset using the provided spec.

Description

Prepares the dataset to be used directly in a model.The transformed dataset is prepared to return tuples (x,y) that can be used directly in Keras.

Usage

dataset_use_spec(dataset, spec)

Arguments

dataset	A TensorFlow dataset.
spec	A feature specification created with feature_spec().

Value

A TensorFlow dataset.

See Also

• feature_spec() to initialize the feature specification.

• fit.FeatureSpec() to create a tensorflow dataset prepared to modeling.

• steps to a list of all implemented steps.

Other Feature Spec Functions: feature_spec(), fit.FeatureSpec(), step_bucketized_column(), step_categorical_column_with_hash_bucket(), step_categorical_column_with_identity(), step_categorical_column_with_vocabulary_file(), step_categorical_column_with_vocabulary_list(), step_crossed_column(), step_embedding_column(), step_indicator_column(), step_numeric_column(), step_remove_column(), step_shared_embeddings_column(), steps

Examples

## Not run: 
library(tfdatasets)
data(hearts)
hearts <- tensor_slices_dataset(hearts) %>% dataset_batch(32)

# use the formula interface
spec <- feature_spec(hearts, target ~ age) %>%
  step_numeric_column(age)

spec_fit <- fit(spec)
final_dataset <- hearts %>% dataset_use_spec(spec_fit)

## End(Not run)

tfdatasets documentation built on June 30, 2022, 1:04 a.m.