Defined in tensorflow/contrib/data/

Experimental API for building input pipelines.

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

See the Importing Data Programmer's Guide for an overview.


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


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).

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

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_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.

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.

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(...): A Transformation which splits the elements of a dataset.

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