tensorflow::ops::SparseConcat

#include <sparse_ops.h>

Concatenates a list of SparseTensor along the specified dimension.

Summary

Concatenation is with respect to the dense versions of these sparse tensors. It is assumed that each input is a SparseTensor whose elements are ordered along increasing dimension number.

All inputs' shapes must match, except for the concat dimension. The indices, values, and shapes lists must have the same length.

The output shape is identical to the inputs', except along the concat dimension, where it is the sum of the inputs' sizes along that dimension.

The output elements will be resorted to preserve the sort order along increasing dimension number.

This op runs in O(M log M) time, where M is the total number of non-empty values across all inputs. This is due to the need for an internal sort in order to concatenate efficiently across an arbitrary dimension.

For example, if concat_dim = 1 and the inputs are

sp_inputs[0]: shape = [2, 3]
[0, 2]: "a"
[1, 0]: "b"
[1, 1]: "c"

sp_inputs[1]: shape = [2, 4]
[0, 1]: "d"
[0, 2]: "e"

then the output will be

shape = [2, 7]
[0, 2]: "a"
[0, 4]: "d"
[0, 5]: "e"
[1, 0]: "b"
[1, 1]: "c"

Graphically this is equivalent to doing

[    a] concat [  d e  ] = [    a   d e  ]
[b c  ]        [       ]   [b c          ]

Arguments:

• scope: A Scope object
• indices: 2-D. Indices of each input SparseTensor.
• values: 1-D. Non-empty values of each SparseTensor.
• shapes: 1-D. Shapes of each SparseTensor.
• concat_dim: Dimension to concatenate along. Must be in range [-rank, rank), where rank is the number of dimensions in each input SparseTensor.

Returns:

• Output output_indices: 2-D. Indices of the concatenated SparseTensor.
• Output output_values: 1-D. Non-empty values of the concatenated SparseTensor.
• Output output_shape: 1-D. Shape of the concatenated SparseTensor.

Public attributes

Operation operation

::tensorflow::Output output_indices

::tensorflow::Output output_shape

::tensorflow::Output output_values

Public functions

 SparseConcat(
  const ::tensorflow::Scope & scope,
  ::tensorflow::InputList indices,
  ::tensorflow::InputList values,
  ::tensorflow::InputList shapes,
  int64 concat_dim
)