ParseSingleExample

public final class ParseSingleExample

Transforms a tf.Example proto (as a string) into typed tensors.

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

static ParseSingleExample
create(Scope scope, Operand<TString> serialized, Iterable<Operand<?>> denseDefaults, Long numSparse, List<String> sparseKeys, List<String> denseKeys, List<Class<? extends TType>> sparseTypes, List<Shape> denseShapes)
Factory method to create a class wrapping a new ParseSingleExample operation.
List<Output<?>>
denseValues()
List<Output<TInt64>>
sparseIndices()
List<Output<TInt64>>
sparseShapes()
List<Output<?>>
sparseValues()

Inherited Methods

org.tensorflow.op.RawOp
final boolean
equals(Object obj)
final int
hashCode()
Operation
op()
Return this unit of computation as a single Operation.
final String
toString()
boolean
equals(Object arg0)
final Class<?>
getClass()
int
hashCode()
final void
notify()
final void
notifyAll()
String
toString()
final void
wait(long arg0, int arg1)
final void
wait(long arg0)
final void
wait()
org.tensorflow.op.Op
abstract ExecutionEnvironment
env()
Return the execution environment this op was created in.
abstract Operation
op()
Return this unit of computation as a single Operation.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "ParseSingleExample"

Public Methods

public static ParseSingleExample create (Scope scope, Operand<TString> serialized, Iterable<Operand<?>> denseDefaults, Long numSparse, List<String> sparseKeys, List<String> denseKeys, List<Class<? extends TType>> sparseTypes, List<Shape> denseShapes)

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

Parameters
scope current scope
serialized A vector containing a batch of binary serialized Example protos.
denseDefaults A list of Tensors (some may be empty), whose length matches the length of `dense_keys`. dense_defaults[j] provides default values when the example's feature_map lacks dense_key[j]. If an empty Tensor is provided for dense_defaults[j], then the Feature dense_keys[j] is required. The input type is inferred from dense_defaults[j], even when it's empty. If dense_defaults[j] is not empty, and dense_shapes[j] is fully defined, then the shape of dense_defaults[j] must match that of dense_shapes[j]. If dense_shapes[j] has an undefined major dimension (variable strides dense feature), dense_defaults[j] must contain a single element: the padding element.
numSparse The number of sparse features to be parsed from the example. This must match the lengths of `sparse_keys` and `sparse_types`.
sparseKeys A list of `num_sparse` strings. The keys expected in the Examples' features associated with sparse values.
denseKeys The keys expected in the Examples' features associated with dense values.
sparseTypes A list of `num_sparse` types; the data types of data in each Feature given in sparse_keys. Currently the ParseSingleExample op supports DT_FLOAT (FloatList), DT_INT64 (Int64List), and DT_STRING (BytesList).
denseShapes The shapes of data in each Feature given in dense_keys. The length of this list must match the length of `dense_keys`. The number of elements in the Feature corresponding to dense_key[j] must always equal dense_shapes[j].NumEntries(). If dense_shapes[j] == (D0, D1, ..., DN) then the shape of output Tensor dense_values[j] will be (D0, D1, ..., DN): In the case dense_shapes[j] = (-1, D1, ..., DN), the shape of the output Tensor dense_values[j] will be (M, D1, .., DN), where M is the number of blocks of elements of length D1 * .... * DN, in the input.
Returns
  • a new instance of ParseSingleExample

public List<Output<?>> denseValues ()

public List<Output<TInt64>> sparseIndices ()

public List<Output<TInt64>> sparseShapes ()

public List<Output<?>> sparseValues ()