tf.compat.v1.sparse_to_dense
Converts a sparse representation into a dense tensor. (deprecated)
tf.compat.v1.sparse_to_dense(
sparse_indices, output_shape, sparse_values, default_value=0,
validate_indices=True, name=None
)
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.
| Args | |
|---|---|
sparse_indices |
A 0-D, 1-D, or 2-D Tensor of type int32 or int64. sparse_indices[i] contains the complete index where sparse_values[i] will be placed. |
output_shape |
A 1-D Tensor of the same type as sparse_indices. Shape of the dense output tensor. |
sparse_values |
A 0-D or 1-D Tensor. Values corresponding to each row of sparse_indices, or a scalar value to be used for all sparse indices. |
default_value |
A 0-D Tensor of the same type as sparse_values. Value to set for indices not specified in sparse_indices. Defaults to zero. |
validate_indices |
A boolean value. 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). |
| Returns | |
|---|---|
Dense Tensor of shape output_shape. 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.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/sparse_to_dense