@Namespace(value="tensorflow::ops") @NoOffset public static class tensorflow.DeserializeSparse extends Pointer
SparseTensor objects.
The input serialized_sparse must have the shape [?, ?, ..., ?, 3] where
the last dimension stores serialized SparseTensor objects and the other N
dimensions (N >= 0) correspond to a batch. The ranks of the original
SparseTensor objects must all match. When the final SparseTensor is
created, its rank is the rank of the incoming SparseTensor objects plus N;
the sparse tensors have been concatenated along new dimensions, one for each
batch.
The output SparseTensor object's shape values for the original dimensions
are the max across the input SparseTensor objects' shape values for the
corresponding dimensions. The new dimensions match the size of the batch.
The input SparseTensor objects' indices are assumed ordered in
standard lexicographic order. If this is not the case, after this
step run SparseReorder to restore index ordering.
For example, if the serialized input is a [2 x 3] matrix representing two
original SparseTensor objects:
index = [ 0]
[10]
[20]
values = [1, 2, 3]
shape = [50]
and
index = [ 2]
[10]
values = [4, 5]
shape = [30]
then the final deserialized SparseTensor will be:
index = [0 0]
[0 10]
[0 20]
[1 2]
[1 10]
values = [1, 2, 3, 4, 5]
shape = [2 50]
Arguments:
* scope: A Scope object
* serialized_sparse: The serialized SparseTensor objects. The last dimension
must have 3 columns.
* dtype: The dtype of the serialized SparseTensor objects.
Returns:
* Output sparse_indices
* Output sparse_values
* Output sparse_shapePointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator| Constructor and Description |
|---|
DeserializeSparse(Pointer p)
Pointer cast constructor.
|
DeserializeSparse(tensorflow.Scope scope,
tensorflow.Input serialized_sparse,
int dtype) |
| Modifier and Type | Method and Description |
|---|---|
tensorflow.Operation |
operation() |
tensorflow.DeserializeSparse |
operation(tensorflow.Operation operation) |
tensorflow.Output |
sparse_indices() |
tensorflow.DeserializeSparse |
sparse_indices(tensorflow.Output sparse_indices) |
tensorflow.Output |
sparse_shape() |
tensorflow.DeserializeSparse |
sparse_shape(tensorflow.Output sparse_shape) |
tensorflow.Output |
sparse_values() |
tensorflow.DeserializeSparse |
sparse_values(tensorflow.Output sparse_values) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zeropublic DeserializeSparse(Pointer p)
Pointer.Pointer(Pointer).public DeserializeSparse(@Const @ByRef tensorflow.Scope scope, @ByVal tensorflow.Input serialized_sparse, @Cast(value="tensorflow::DataType") int dtype)
@ByRef public tensorflow.Operation operation()
public tensorflow.DeserializeSparse operation(tensorflow.Operation operation)
@ByRef public tensorflow.Output sparse_indices()
public tensorflow.DeserializeSparse sparse_indices(tensorflow.Output sparse_indices)
@ByRef public tensorflow.Output sparse_values()
public tensorflow.DeserializeSparse sparse_values(tensorflow.Output sparse_values)
@ByRef public tensorflow.Output sparse_shape()
public tensorflow.DeserializeSparse sparse_shape(tensorflow.Output sparse_shape)
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