/TensorFlow 2.4


Converts a sparse representation into a dense tensor.

Builds an array dense with shape output_shape such 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]

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.

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.
name A name for the operation (optional).
A Tensor. Has the same type as sparse_values.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.