Builds an array dense with shape output_shape such that
# If sparse_indices is scalardense[i]=(i==sparse_indices?sparse_values:default_value)# If sparse_indices is a vector, then for each idense[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]
All other values in dense are set to default_value. If sparse_values is 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. If validate_indices is true, these properties
are checked during execution.
Args
sparse_indices
A Tensor. Must be one of the following types: int32, int64.
0-D, 1-D, or 2-D. sparse_indices[i] contains the complete
index where sparse_values[i] will be placed.
output_shape
A Tensor. Must have the same type as sparse_indices.
1-D. Shape of the dense output tensor.
sparse_values
A Tensor.
1-D. Values corresponding to each row of sparse_indices,
or a scalar value to be used for all sparse indices.
default_value
A Tensor. Must have the same type as sparse_values.
Scalar value to set for indices not specified in
sparse_indices.
validate_indices
An optional bool. Defaults to True.
If true, indices are checked to make sure they are sorted in
lexicographic order and that there are no repeats.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-01-23 UTC."],[],[]]