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op {
graph_op_name: "ScatterAdd"
in_arg {
name: "ref"
description: <<END
Should be from a `Variable` node.
END
}
in_arg {
name: "indices"
description: <<END
A tensor of indices into the first dimension of `ref`.
END
}
in_arg {
name: "updates"
description: <<END
A tensor of updated values to add to `ref`.
END
}
out_arg {
name: "output_ref"
description: <<END
= Same as `ref`. Returned as a convenience for operations that want
to use the updated values after the update is done.
END
}
attr {
name: "use_locking"
description: <<END
If True, the addition will be protected by a lock;
otherwise the behavior is undefined, but may exhibit less contention.
END
}
summary: "Adds sparse updates to a variable reference."
description: <<END
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.
Duplicate entries are handled correctly: if multiple `indices` reference
the same location, their contributions add.
Requires `updates.shape = indices.shape + ref.shape[1:]`.
<div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
<img style="width:100%" src="https://www.tensorflow.org/images/ScatterAdd.png" alt>
</div>
END
}
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