tf.scatter_add

tf.scatter_add(
    ref,
    indices,
    updates,
    use_locking=False,
    name=None
)

Defined in tensorflow/python/ops/state_ops.py.

Adds sparse updates to the variable referenced by resource.

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.