TensorFlow 2.0 version


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

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

class DatasetStructure: Represents a Dataset of structured values.

class DistributeOptions: Represents options for distributed data processing.

class MapVectorizationOptions: Represents options for the MapVectorization optimization.

class NestedStructure: Represents a nested structure in which each leaf is a Structure.

class OptimizationOptions: Represents options for dataset optimizations.

class Optional: Wraps a nested structure of tensors that may/may not be present at runtime.

class OptionalStructure: Represents an optional potentially containing a structured value.

class RaggedTensorStructure: Represents structural information about a tf.RaggedTensor.

class RandomDataset: A Dataset of pseudorandom values.

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

class SparseTensorStructure: Represents structural information about a tf.SparseTensor.

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

class StatsAggregator: A stateful resource that aggregates statistics from one or more iterators.

class StatsOptions: Represents options for collecting dataset stats using StatsAggregator.

class Structure: Represents structural information, such as type and shape, about a value.

class TFRecordWriter: Writes data to a TFRecord file.

class TensorArrayStructure: Represents structural information about a tf.TensorArray.

class TensorStructure: Represents structural information about a tf.Tensor.

class ThreadingOptions: Represents options for dataset threading.


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

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

bytes_produced_stats(...): Records the number of bytes produced by each element of the input dataset.

cardinality(...): Returns the cardinality of dataset, if known.

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 enumerates the elements of a dataset. (deprecated)

from_variant(...): Constructs a dataset from the given variant and structure.

get_next_as_optional(...): Returns an Optional that contains the next value from the iterator.

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

get_structure(...): Returns the of a Dataset or Iterator.

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.

latency_stats(...): Records the latency of producing each element of the input dataset.


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. (deprecated)

map_and_batch_with_legacy_function(...): Fused implementation of map and batch. (deprecated)

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

parse_example_dataset(...): A transformation that parses Example protos into a dict of tensors.

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

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. (deprecated)

take_while(...): A transformation that stops dataset iteration based on a predicate.

to_variant(...): Returns a variant representing the given dataset.

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 = -1