Applies sparse subtraction to individual values or slices in a Variable.
`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]]
ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8], use_resource=True)
indices = tf.constant([[4], [3], [1], [7]])
updates = tf.constant([9, 10, 11, 12])
sub = tf.scatter_nd_sub(ref, indices, updates)
with tf.Session() as sess:
print sess.run(sub)
[1, -9, 3, -6, -4, 6, 7, -4]
See tf.scatter_nd
for more details about how to make updates to
slices.
Nested Classes
class | ResourceScatterNdSub.Options | Optional attributes for ResourceScatterNdSub
|
Public Methods
static <T extends Number, U> ResourceScatterNdSub | |
static ResourceScatterNdSub.Options |
useLocking(Boolean useLocking)
|
Inherited Methods
Public Methods
public static ResourceScatterNdSub create (Scope scope, Operand<?> ref, Operand<T> indices, Operand<U> updates, Options... options)
Factory method to create a class wrapping a new ResourceScatterNdSub operation.
Parameters
scope | current scope |
---|---|
ref | A resource handle. Must be from a VarHandleOp. |
indices | 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 of values to add to ref. |
options | carries optional attributes values |
Returns
- a new instance of ResourceScatterNdSub
public static ResourceScatterNdSub.Options useLocking (Boolean useLocking)
Parameters
useLocking | 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. |
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