dataset_use_spec {tfdatasets} | R Documentation |
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 |
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)