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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.
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