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tensorflow::
ops::
DeserializeManySparse
#include <sparse_ops.h>
Deserialize and concatenate
SparseTensors
from a serialized minibatch.
Summary
The input
serialized_sparse
must be a string matrix of shape
[N x 3]
where
N
is the minibatch size and the rows correspond to packed outputs of
SerializeSparse
. The ranks of the original
SparseTensor
objects must all match. When the final
SparseTensor
is created, it has rank one higher than the ranks of the incoming
SparseTensor
objects (they have been concatenated along a new row dimension).
The output
SparseTensor
object's shape values for all dimensions but the first are the max across the input
SparseTensor
objects' shape values for the corresponding dimensions. Its first shape value is
N
, the minibatch size.
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]
Args:
-
scope: A
Scope
object
-
serialized_sparse: 2-D, The
N
serialized
SparseTensor
objects. Must have 3 columns.
-
dtype: The
dtype
of the serialized
SparseTensor
objects.
Returns:
Public attributes
Public functions
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Last updated 2021-05-14 UTC.
[null,null,["Last updated 2021-05-14 UTC."],[],[],null,["# tensorflow::ops::DeserializeManySparse Class Reference\n\ntensorflow::\nops::\nDeserializeManySparse\n========================================\n\n`\n#include \u003csparse_ops.h\u003e\n`\n\n\nDeserialize and concatenate\n`\nSparseTensors\n`\nfrom a serialized minibatch.\n\nSummary\n-------\n\n\nThe input\n`\nserialized_sparse\n`\nmust be a string matrix of shape\n`\n[N x 3]\n`\nwhere\n`\nN\n`\nis the minibatch size and the rows correspond to packed outputs of\n`\n`[SerializeSparse](/versions/r2.5/api_docs/cc/class/tensorflow/ops/serialize-sparse#classtensorflow_1_1ops_1_1_serialize_sparse)`\n`\n. The ranks of the original\n`\nSparseTensor\n`\nobjects must all match. When the final\n`\nSparseTensor\n`\nis created, it has rank one higher than the ranks of the incoming\n`\nSparseTensor\n`\nobjects (they have been concatenated along a new row dimension).\n\n\nThe output\n`\nSparseTensor\n`\nobject's shape values for all dimensions but the first are the max across the input\n`\nSparseTensor\n`\nobjects' shape values for the corresponding dimensions. Its first shape value is\n`\nN\n`\n, the minibatch size.\n\n\nThe input\n`\nSparseTensor\n`\nobjects' indices are assumed ordered in standard lexicographic order. If this is not the case, after this step run\n`\n`[SparseReorder](/versions/r2.5/api_docs/cc/class/tensorflow/ops/sparse-reorder#classtensorflow_1_1ops_1_1_sparse_reorder)`\n`\nto restore index ordering.\n\n\nFor example, if the serialized input is a\n`\n[2 x 3]\n`\nmatrix representing two original\n`\nSparseTensor\n`\nobjects: \n\n```text\nindex = [ 0]\n [10]\n [20]\nvalues = [1, 2, 3]\nshape = [50]\n```\n\n\u003cbr /\u003e\n\n\nand \n\n```text\nindex = [ 2]\n [10]\nvalues = [4, 5]\nshape = [30]\n```\n\n\u003cbr /\u003e\n\n\nthen the final deserialized\n`\nSparseTensor\n`\nwill be: \n\n```text\nindex = [0 0]\n [0 10]\n [0 20]\n [1 2]\n [1 10]\nvalues = [1, 2, 3, 4, 5]\nshape = [2 50]\n```\n\n\u003cbr /\u003e\n\n\nArgs:\n\n- scope: A [Scope](/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- serialized_sparse: 2-D, The `\n N\n ` serialized `\n SparseTensor\n ` objects. Must have 3 columns.\n- dtype: The `\n dtype\n ` of the serialized `\n SparseTensor\n ` objects.\n\n\u003cbr /\u003e\n\n\nReturns:\n\n- `\n `[Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` sparse_indices\n- `\n `[Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` sparse_values\n- `\n `[Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)`\n ` sparse_shape\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| ` `[DeserializeManySparse](#classtensorflow_1_1ops_1_1_deserialize_many_sparse_1ab7cf9797d35b97c6d82e4000573b7839)` (const :: `[tensorflow::Scope](/versions/r2.5/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, :: `[tensorflow::Input](/versions/r2.5/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` serialized_sparse, DataType dtype) ` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|\n| ` `[operation](#classtensorflow_1_1ops_1_1_deserialize_many_sparse_1ac7cd19536afb9e162240583e49e59e8d)` ` | ` `[Operation](/versions/r2.5/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)` ` |\n| ` `[sparse_indices](#classtensorflow_1_1ops_1_1_deserialize_many_sparse_1a047caae64f0cea6d6dc1659d15bfe4b9)` ` | ` :: `[tensorflow::Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n| ` `[sparse_shape](#classtensorflow_1_1ops_1_1_deserialize_many_sparse_1a248aaedf66a2ba1733b1f2e541c4d3e2)` ` | ` :: `[tensorflow::Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n| ` `[sparse_values](#classtensorflow_1_1ops_1_1_deserialize_many_sparse_1a1047d48275c3140bedd5e8737af534f2)` ` | ` :: `[tensorflow::Output](/versions/r2.5/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output)` ` |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### sparse_indices\n\n```scdoc\n::tensorflow::Output sparse_indices\n``` \n\n### sparse_shape\n\n```scdoc\n::tensorflow::Output sparse_shape\n``` \n\n### sparse_values\n\n```scdoc\n::tensorflow::Output sparse_values\n``` \n\nPublic functions\n----------------\n\n### DeserializeManySparse\n\n```gdscript\n DeserializeManySparse(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input serialized_sparse,\n DataType dtype\n)\n```"]]