Multiplies sparse updates into a variable reference.
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 = []`.
Nested Classes
class | ScatterMul.Options |
Optional attributes for
ScatterMul
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Public Methods
Output <T> |
asOutput
()
Returns the symbolic handle of a tensor.
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static <T, U extends Number> ScatterMul <T> | |
Output <T> |
outputRef
()
= Same as `ref`.
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static ScatterMul.Options |
useLocking
(Boolean useLocking)
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Inherited Methods
Public Methods
public Output <T> asOutput ()
Returns the symbolic handle of a tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static ScatterMul <T> create ( Scope scope, Operand <T> ref, Operand <U> indices, Operand <T> updates, Options... options)
Factory method to create a class wrapping a new ScatterMul operation.
Parameters
scope | current scope |
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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`. |
options | carries optional attributes values |
Returns
- a new instance of ScatterMul
public Output <T> outputRef ()
= Same as `ref`. Returned as a convenience for operations that want to use the updated values after the update is done.
public static ScatterMul.Options useLocking (Boolean useLocking)
Parameters
useLocking | If True, the operation will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention. |
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