Module: tf.contrib.data

Defined in tensorflow/contrib/data/__init__.py.

Experimental API for building input pipelines.

This module contains experimental Dataset sources and transformations that can be used in conjunction with the tf.data.Dataset API. Note that the tf.contrib.data API is not subject to the same backwards compatibility guarantees as tf.data, but we will provide deprecation advice in advance of removing existing functionality.

See Importing Data for an overview.

Classes

class CheckpointInputPipelineHook: Checkpoints input pipeline state every N steps or seconds.

class CsvDataset: A Dataset comprising lines from one or more CSV files.

class RandomDataset: A Dataset of pseudorandom values.

class Reducer: A reducer is used for reducing a set of elements.

class SqlDataset: A Dataset consisting of the results from a SQL query.

class TFRecordWriter: Writes data to a TFRecord file.

Functions

Counter(...): Creates a Dataset that counts from start in steps of size step.

assert_element_shape(...): Assert the shape of this Dataset.

batch_and_drop_remainder(...): A batching transformation that omits the final small batch (if present). (deprecated)

bucket_by_sequence_length(...): A transformation that buckets elements in a Dataset by length.

choose_from_datasets(...): Creates a dataset that deterministically chooses elements from datasets.

copy_to_device(...): A transformation that copies dataset elements to the given target_device.

dense_to_sparse_batch(...): A transformation that batches ragged elements into tf.SparseTensors.

enumerate_dataset(...): A transformation that enumerate the elements of a dataset.

get_single_element(...): Returns the single element in dataset as a nested structure of tensors.

group_by_reducer(...): A transformation that groups elements and performs a reduction.

group_by_window(...): A transformation that groups windows of elements by key and reduces them.

ignore_errors(...): Creates a Dataset from another Dataset and silently ignores any errors.

make_batched_features_dataset(...): Returns a Dataset of feature dictionaries from Example protos.

make_csv_dataset(...): Reads CSV files into a dataset.

make_saveable_from_iterator(...): Returns a SaveableObject for saving/restore iterator state using Saver.

map_and_batch(...): Fused implementation of map and batch.

padded_batch_and_drop_remainder(...): A batching and padding transformation that omits the final small batch. (deprecated)

parallel_interleave(...): A parallel version of the Dataset.interleave() transformation.

prefetch_to_device(...): A transformation that prefetches dataset values to the given device.

read_batch_features(...): Reads batches of Examples. (deprecated)

rejection_resample(...): A transformation that resamples a dataset to achieve a target distribution.

sample_from_datasets(...): Samples elements at random from the datasets in datasets.

scan(...): A transformation that scans a function across an input dataset.

shuffle_and_repeat(...): Shuffles and repeats a Dataset returning a new permutation for each epoch.

sliding_window_batch(...): A sliding window with size of window_size and step of stride.

sloppy_interleave(...): A non-deterministic version of the Dataset.interleave() transformation. (deprecated)

unbatch(...): Splits elements of a dataset into multiple elements on the batch dimension.

unique(...): Creates a Dataset from another Dataset, discarding duplicates.

Other Members

AUTOTUNE