Adds sparse updates to the variable referenced by resource.
tf.compat.v1.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 ofref. | 
| updates | A Tensor. Must have the same type asref. A tensor of updated values to store inref. | 
| use_locking | An optional bool. Defaults toFalse. 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. | 
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/compat/v1/scatter_add