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