tensorflow::ops::ScatterMul

#include <state_ops.h>

Multiplies sparse updates into a variable reference.

Summary

This operation computes

```python 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 multiply.

Requires updates.shape = indices.shape + ref.shape[1:].

Arguments:

• scope: A Scope object
• ref: Should be from a Variable node.
• indices: A tensor of indices into the first dimension of ref.
• updates: A tensor of updated values to multiply to ref.

Optional attributes (see Attrs):

• use_locking: If True, the operation will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.

Returns:

• Output: = Same as ref. Returned as a convenience for operations that want to use the updated values after the update is done.

Public attributes

::tensorflow::Output output_ref

Public functions

 ScatterMul(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input ref,
  ::tensorflow::Input indices,
  ::tensorflow::Input updates
)

 ScatterMul(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input ref,
  ::tensorflow::Input indices,
  ::tensorflow::Input updates,
  const ScatterMul::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs UseLocking(
  bool x
)