Adds sparse updates to the variable referenced by resource
.
tf.scatter_add( ref, indices, updates, use_locking=False, name=None )
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 updated value. Duplicate entries are handled correctly: if multiple indices
reference the same location, their contributions add.
Requires updates.shape = indices.shape + ref.shape[1:]
.
Args | |
---|---|
ref | A Variable . |
indices | A Tensor . Must be one of the following types: int32 , int64 . A tensor of indices into the first dimension of ref . |
updates | A Tensor . Must have the same type as ref . A tensor of updated values to store in ref . |
use_locking | An optional bool . Defaults to False . 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). |
Returns | |
---|---|
Same as ref . Returned as a convenience for operations that want to use the updated values after the update is done. |
© 2020 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/versions/r1.15/api_docs/python/tf/scatter_add