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`.

tf.compat.v1.sparse_to_dense

Args

Returns