tf.compat.v1.scalar

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.

TensorFlow

tf.compat / v1 / v1.scalar_mul

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tf.compat / v1 / v1.scalar_mul

Args

Returns