SparseToDense

tensorflow C++ API

tensorflow::ops::SparseToDense

Converts a sparse representation into a dense tensor.

Summary

Builds an arraydensewith shapeoutput_shapesuch that

``` If sparse_indices is scalar

dense[i] = (i == sparse_indices ? sparse_values : default_value)

If sparse_indices is a vector, then for each i

dense[sparse_indices[i]] = sparse_values[i]

If sparse_indices is an n by d matrix, then for each i in [0, n)

dense[sparse_indices[i][0], ..., sparse_indices[i][d-1]] = sparse_values[i] ```

Allother values indenseare set todefault_value. Ifsparse_valuesis a scalar, all sparse indices are set to this single value.

Indices should be sorted in lexicographic order, and indices must not contain any repeats. Ifvalidate_indicesis true, these properties are checked during execution.

Arguments:

• scope: AScope object
• sparse_indices: 0-D, 1-D, or 2-D.sparse_indices[i]contains the complete index wheresparse_values[i]will be placed.
• output_shape: 1-D.Shapeof the dense output tensor.
• sparse_values: 1-D. Values corresponding to each row ofsparse_indices, or a scalar value to be used for all sparse indices.
• default_value: Scalar value to set for indices not specified insparse_indices.

Optional attributes (seeAttrs):

• validate_indices: If true, indices are checked to make sure they are sorted in lexicographic order and that there are no repeats.

Returns:

• Output: Dense output tensor of shapeoutput_shape .

SparseToDense block

Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_sparse.cpp

Argument:

• Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
• Input sparse_indices: connect Input node.
• Input output_shape: connect Input node.
• Input sparse_values: connect Input node.
• Input default_value: connect Input node.
• SparseToDense::Attrs attrs : Input attrs in value. ex) validate_indices_ = true;

Return:

• Output output: Output object of SparseToDense class object.

Result:

• std::vector(Tensor) result_output : Returned object of executed result by calling session.

Using Method