tf.sparse_add( a, b, thresh=0 )
Adds two tensors, at least one of each is a
SparseTensor and one
Tensor are passed in, returns a
both arguments are
SparseTensors, this returns a
SparseTensor. The order
of arguments does not matter. Use vanilla
tf.add() for adding two dense
The shapes of the two operands must match: broadcasting is not supported.
The indices of any input
SparseTensor are assumed ordered in standard
lexicographic order. If this is not the case, before this step run
SparseReorder to restore index ordering.
If both arguments are sparse, we perform "clipping" as follows. By default,
if two values sum to zero at some index, the output
SparseTensor would still
include that particular location in its index, storing a zero in the
corresponding value slot. To override this, callers can specify
indicating that if the sum has a magnitude strictly smaller than
corresponding value and index would then not be included. In particular,
thresh == 0.0 (default) means everything is kept and actual thresholding
happens only for a positive value.
For example, suppose the logical sum of two sparse operands is (densified):
[ 2] [.1 0] [ 6 -.2]
* `thresh == 0` (the default): all 5 index/value pairs will be returned. * `thresh == 0.11`: only .1 and 0 will vanish, and the remaining three index/value pairs will be returned. * `thresh == 0.21`: .1, 0, and -.2 will vanish.
a: The first operand;
b: The second operand;
Tensor. At least one operand must be sparse.
thresh: A 0-D
Tensor. The magnitude threshold that determines if an output value/index pair takes space. Its dtype should match that of the values if they are real; if the latter are complex64/complex128, then the dtype should be float32/float64, correspondingly.
SparseTensor or a
Tensor, representing the sum.
TypeError: If both