tf.scatter_update( ref, indices, updates, use_locking=True, name=None )
See the guide: Variables > Sparse Variable Updates
Applies sparse updates to a variable reference.
This operation computes
# Scalar indices ref[indices, ...] = updates[...] # Vector indices (for each i) ref[indices[i], ...] = updates[i, ...] # High rank indices (for each i, ..., j) ref[indices[i, ..., j], ...] = updates[i, ..., j, ...]
This operation outputs
ref after the update is done.
This makes it easier to chain operations that need to use the reset value.
If values in
ref is to be updated more than once, because there are
duplicate entries in
indices, the order at which the updates happen
for each value is undefined.
updates.shape = indices.shape + ref.shape[1:].
Tensor. Must be one of the following types:
int64. A tensor of indices into the first dimension of
Tensor. Must have the same type as
ref. A tensor of updated values to store in
use_locking: 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).
ref. Returned as a convenience for operations that want
to use the updated values after the update is done.