tf.scatter_nd_add(ref, indices, updates, use_locking=None, name=None)
See the guide: Variables > Sparse Variable Updates
Applies sparse addition between updates
and individual values or slices
within a given variable according to indices
.
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.scatter_nd_add(ref, indices, updates) with tf.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.
ref
: A mutable Tensor
. Must be one of the following types: float32
, float64
, int64
, int32
, uint8
, uint16
, int16
, int8
, complex64
, complex128
, qint8
, quint8
, qint32
, half
. A mutable Tensor. Should be from a Variable node.indices
: A Tensor
. Must be one of the following types: int32
, int64
. A Tensor. Must be one of the following types: int32, int64. A tensor of indices into ref.updates
: A Tensor
. Must have the same type as ref
. A Tensor. Must have the same type as ref. A tensor of updated values to add to ref.use_locking
: An optional bool
. Defaults to False
. An optional bool. Defaults to True. If True, the assignment will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.name
: A name for the operation (optional).A mutable Tensor
. Has the same type as ref
. Same as ref. Returned as a convenience for operations that want to use the updated values after the update is done.
Defined in tensorflow/python/ops/gen_state_ops.py
.
© 2017 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/api_docs/python/tf/scatter_nd_add