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Applies sparse addition to individual values or slices in a Variable.
tf.compat.v1.scatter_nd_add(
ref, indices, updates, use_locking=False, name=None
)
ref
is a Tensor
with rank P
and indices
is a Tensor
of rank Q
.
indices
must be integer tensor, containing indices into ref
.
It must be shape [d_0, ..., d_{Q-2}, K]
where 0 < K <= P
.
The innermost dimension of indices
(with length K
) corresponds to
indices into elements (if K = P
) or slices (if K < P
) along the K
th
dimension of ref
.
updates
is Tensor
of rank Q-1+P-K
with shape:
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]]
For example, say we want to add 4 scattered elements to a rank-1 tensor to 8 elements. In Python, that addition would look like this:
ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
indices = tf.constant([[4], [3], [1], [7]])
updates = tf.constant([9, 10, 11, 12])
add = tf.compat.v1.scatter_nd_add(ref, indices, updates)
with tf.compat.v1.Session() as sess:
print sess.run(add)
The resulting update to ref would look like this:
[1, 13, 3, 14, 14, 6, 7, 20]
See tf.scatter_nd
for more details about how to make updates to
slices.
Returns | |
---|---|
A mutable Tensor . Has the same type as ref .
|