tf.compat.v1.scatter_add
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 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/r2.3/api_docs/python/tf/compat/v1/scatter_add