Package org.tensorflow.op.data

Class ParseExampleDataset

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.data.ParseExampleDataset

All Implemented Interfaces:

Op, Operand<java.lang.Object>

@Operator(group="data")
public final class ParseExampleDataset
extends PrimitiveOp
implements Operand<java.lang.Object>

Transforms `input_dataset` containing `Example` protos as vectors of DT_STRING into a dataset of `Tensor` or `SparseTensor` objects representing the parsed features.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	ParseExampleDataset.Options	Optional attributes for ParseExampleDataset

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method	Description
Output<java.lang.Object>	asOutput()	Returns the symbolic handle of a tensor.
static ParseExampleDataset	create(Scope scope, Operand<?> inputDataset, Operand<java.lang.Long> numParallelCalls, java.lang.Iterable<Operand<?>> denseDefaults, java.util.List<java.lang.String> sparseKeys, java.util.List<java.lang.String> denseKeys, java.util.List<java.lang.Class<?>> sparseTypes, java.util.List<Shape> denseShapes, java.util.List<java.lang.Class<?>> outputTypes, java.util.List<Shape> outputShapes, ParseExampleDataset.Options... options)	Factory method to create a class to wrap a new ParseExampleDataset operation to the graph.
Output<?>	handle()
static ParseExampleDataset.Options	sloppy(java.lang.Boolean sloppy)

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Method Detail

create

public static ParseExampleDataset create(Scope scope,
                                         Operand<?> inputDataset,
                                         Operand<java.lang.Long> numParallelCalls,
                                         java.lang.Iterable<Operand<?>> denseDefaults,
                                         java.util.List<java.lang.String> sparseKeys,
                                         java.util.List<java.lang.String> denseKeys,
                                         java.util.List<java.lang.Class<?>> sparseTypes,
                                         java.util.List<Shape> denseShapes,
                                         java.util.List<java.lang.Class<?>> outputTypes,
                                         java.util.List<Shape> outputShapes,
                                         ParseExampleDataset.Options... options)

Factory method to create a class to wrap a new ParseExampleDataset operation to the graph.

Parameters:

scope - current graph scope

inputDataset -

numParallelCalls -

denseDefaults - A dict mapping string keys to `Tensor`s. The keys of the dict must match the dense_keys of the feature.

sparseKeys - A list of string keys in the examples features. The results for these keys will be returned as `SparseTensor` objects.

denseKeys - A list of Ndense string Tensors (scalars). The keys expected in the Examples features associated with dense values.

sparseTypes - A list of `DTypes` of the same length as `sparse_keys`. Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`), and `tf.string` (`BytesList`) are supported.

denseShapes - List of tuples with the same length as `dense_keys`. The shape of the data for each dense feature referenced by `dense_keys`. Required for any input tensors identified by `dense_keys`. Must be either fully defined, or may contain an unknown first dimension. An unknown first dimension means the feature is treated as having a variable number of blocks, and the output shape along this dimension is considered unknown at graph build time. Padding is applied for minibatch elements smaller than the maximum number of blocks for the given feature along this dimension.

outputTypes - The type list for the return values.

outputShapes - The list of shapes being produced.

options - carries optional attributes values

Returns:

a new instance of ParseExampleDataset

sloppy

public static ParseExampleDataset.Options sloppy(java.lang.Boolean sloppy)

Parameters:

sloppy -

handle

public Output<?> handle()

asOutput

public Output<java.lang.Object> asOutput()

Description copied from interface: Operand

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

Specified by:

asOutput in interface Operand<java.lang.Object>

See Also:

OperationBuilder.addInput(Output)