public final class ExperimentalParseExampleDataset extends PrimitiveOp implements Operand<Object>
Modifier and Type | Class and Description |
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static class |
ExperimentalParseExampleDataset.Options
Optional attributes for
ExperimentalParseExampleDataset |
operation
Modifier and Type | Method and Description |
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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,
ExperimentalParseExampleDataset.Options... options)
Factory method to create a class wrapping a new ExperimentalParseExampleDataset operation.
|
Output<?> |
handle() |
static ExperimentalParseExampleDataset.Options |
sloppy(Boolean sloppy) |
equals, hashCode, op, toString
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, ExperimentalParseExampleDataset.Options... options)
scope
- current scopeinputDataset
- 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 valuespublic static ExperimentalParseExampleDataset.Options sloppy(Boolean sloppy)
sloppy
- public Output<?> handle()
public Output<Object> asOutput()
Operand
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.
asOutput
in interface Operand<Object>
OperationBuilder.addInput(Output)
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