Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

ExperimentalParseExampleDataset

public final class ExperimentalParseExampleDataset

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

Nested Classes

class ExperimentalParseExampleDataset.Options Optional attributes for ExperimentalParseExampleDataset  

Public Methods

Output<Object>
asOutput()
Returns the symbolic handle of a tensor.
static ExperimentalParseExampleDataset
create(Scope scope, Operand<?> inputDataset, Operand<Long> numParallelCalls, Iterable<Operand<?>> denseDefaults, List<String> sparseKeys, List<String> denseKeys, List<Class<?>> sparseTypes, List<Shape> denseShapes, List<Class<?>> outputTypes, List<Shape> outputShapes, Options... options)
Factory method to create a class wrapping a new ExperimentalParseExampleDataset operation.
Output<?>
handle()
static ExperimentalParseExampleDataset.Options
sloppy(Boolean sloppy)

Inherited Methods

Public Methods

public Output<Object> asOutput ()

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.

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

Factory method to create a class wrapping a new ExperimentalParseExampleDataset operation.

Parameters
scope current scope
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 ExperimentalParseExampleDataset

public Output<?> handle ()

public static ExperimentalParseExampleDataset.Options sloppy (Boolean sloppy)