R: Interface to 'TensorFlow' Datasets

# Interface to 'TensorFlow' Datasets

## Documentation for package ‘tfdatasets’ version 2.18.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

all_nominal | Find all nominal variables.
all_numeric | Speciy all numeric variables.
as.array.tensorflow.python.data.ops.dataset_ops.DatasetV2 | Get the single element of the dataset.
as_array_iterator | Convert tf_dataset to an iterator that yields R arrays.
as_tensor.tensorflow.python.data.ops.dataset_ops.DatasetV2 | Get the single element of the dataset.
choose_from_datasets | Creates a dataset that deterministically chooses elements from datasets.
csv_record_spec | Specification for reading a record from a text file with delimited values
cur_info_env | Selectors
dataset_batch | Combines consecutive elements of this dataset into batches.
dataset_bucket_by_sequence_length | A transformation that buckets elements in a 'Dataset' by length
dataset_cache | Caches the elements in this dataset.
dataset_collect | Collects a dataset
dataset_concatenate | Creates a dataset by concatenating given dataset with this dataset.
dataset_decode_delim | Transform a dataset with delimted text lines into a dataset with named columns
dataset_enumerate | Enumerates the elements of this dataset
dataset_filter | Filter a dataset by a predicate
dataset_flat_map | Maps map_func across this dataset and flattens the result.
dataset_group_by_window | Group windows of elements by key and reduce them
dataset_interleave | Maps map_func across this dataset, and interleaves the results
dataset_map | Map a function across a dataset.
dataset_map_and_batch | Fused implementation of dataset_map() and dataset_batch()
dataset_options | Get or Set Dataset Options
dataset_padded_batch | Combines consecutive elements of this dataset into padded batches.
dataset_prefetch | Creates a Dataset that prefetches elements from this dataset.
dataset_prefetch_to_device | A transformation that prefetches dataset values to the given 'device'
dataset_prepare | Prepare a dataset for analysis
dataset_rebatch | Rebatch elements from this dataset into batches of specified size.
dataset_reduce | Reduces the input dataset to a single element.
dataset_rejection_resample | A transformation that resamples a dataset to a target distribution.
dataset_repeat | Repeats a dataset count times.
dataset_scan | A transformation that scans a function across an input dataset
dataset_shard | Creates a dataset that includes only 1 / num_shards of this dataset.
dataset_shuffle | Randomly shuffles the elements of this dataset.
dataset_shuffle_and_repeat | Shuffles and repeats a dataset returning a new permutation for each epoch.
dataset_skip | Creates a dataset that skips count elements from this dataset
dataset_snapshot | Persist the output of a dataset
dataset_take | Creates a dataset with at most count elements from this dataset
dataset_take_while | A transformation that stops dataset iteration based on a predicate.
dataset_unbatch | Unbatch a dataset
dataset_unique | A transformation that discards duplicate elements of a Dataset.
dataset_use_spec | Transform the dataset using the provided spec.
dataset_window | Combines input elements into a dataset of windows.
delim_record_spec | Specification for reading a record from a text file with delimited values
dense_features | Dense Features
feature_spec | Creates a feature specification.
file_list_dataset | A dataset of all files matching a pattern
fit.FeatureSpec | Fits a feature specification.
fixed_length_record_dataset | A dataset of fixed-length records from one or more binary files.
get_single_element | Get the single element of the dataset.
has_type | Identify the type of the variable.
hearts | Heart Disease Data Set
iterator_get_next | Get next element from iterator
iterator_initializer | An operation that should be run to initialize this iterator.
iterator_make_initializer | Create an operation that can be run to initialize this iterator
iterator_string_handle | String-valued tensor that represents this iterator
layer_input_from_dataset | Creates a list of inputs from a dataset
length.tensorflow.python.data.ops.dataset_ops.DatasetV2 | Get Dataset length
length.tf_dataset | Get Dataset length
make-iterator | Creates an iterator for enumerating the elements of this dataset.
make_csv_dataset | Reads CSV files into a batched dataset
make_iterator_from_string_handle | Creates an iterator for enumerating the elements of this dataset.
make_iterator_from_structure | Creates an iterator for enumerating the elements of this dataset.
make_iterator_initializable | Creates an iterator for enumerating the elements of this dataset.
make_iterator_one_shot | Creates an iterator for enumerating the elements of this dataset.
next_batch | Tensor(s) for retrieving the next batch from a dataset
output_shapes | Output types and shapes
output_types | Output types and shapes
out_of_range_handler | Execute code that traverses a dataset until an out of range condition occurs
random_integer_dataset | Creates a 'Dataset' of pseudorandom values
range_dataset | Creates a dataset of a step-separated range of values.
read_files | Read a dataset from a set of files
sample_from_datasets | Samples elements at random from the datasets in 'datasets'.
scaler | List of pre-made scalers
scaler_min_max | Creates an instance of a min max scaler
scaler_standard | Creates an instance of a standard scaler
selectors | Selectors
sparse_tensor_slices_dataset | Splits each rank-N 'tf$SparseTensor' in this dataset row-wise.
sqlite_dataset | A dataset consisting of the results from a SQL query
sql_dataset | A dataset consisting of the results from a SQL query
sql_record_spec | A dataset consisting of the results from a SQL query
steps | Steps for feature columns specification.
step_bucketized_column | Creates bucketized columns
step_categorical_column_with_hash_bucket | Creates a categorical column with hash buckets specification
step_categorical_column_with_identity | Create a categorical column with identity
step_categorical_column_with_vocabulary_file | Creates a categorical column with vocabulary file
step_categorical_column_with_vocabulary_list | Creates a categorical column specification
step_crossed_column | Creates crosses of categorical columns
step_embedding_column | Creates embeddings columns
step_indicator_column | Creates Indicator Columns
step_numeric_column | Creates a numeric column specification
step_remove_column | Creates a step that can remove columns
step_shared_embeddings_column | Creates shared embeddings for categorical columns
tensors_dataset | Creates a dataset with a single element, comprising the given tensors.
tensor_slices_dataset | Creates a dataset whose elements are slices of the given tensors.
text_line_dataset | A dataset comprising lines from one or more text files.
tfrecord_dataset | A dataset comprising records from one or more TFRecord files.
tsv_record_spec | Specification for reading a record from a text file with delimited values
until_out_of_range | Execute code that traverses a dataset until an out of range condition occurs
with_dataset | Execute code that traverses a dataset
zip_datasets | Creates a dataset by zipping together the given datasets.