tf.compat.v1.scatter_mul

Multiplies sparse updates into a variable reference.

tf.compat.v1.scatter_mul(
    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 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:] or updates.shape = [].

Args
`ref`	A mutable `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. Should be from a `Variable` node.
`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 multiply to `ref`.
`use_locking`	An optional `bool`. Defaults to `False`. If True, the operation will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
`name`	A name for the operation (optional).

Returns
A mutable `Tensor`. Has the same type as `ref`.

tf.compat.v1.scatter_mul

Args

Returns