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# TensorScatterNdSub

public final class TensorScatterNdSub

Subtracts sparse `updates` from an existing tensor according to `indices`.

This operation creates a new tensor by subtracting sparse `updates` from the passed in `tensor`. This operation is very similar to `tf.scatter_nd_sub`, except that the updates are subtracted from an existing tensor (as opposed to a variable). If the memory for the existing tensor cannot be re-used, a copy is made and updated.

`indices` is an integer tensor containing indices into a new tensor of shape `shape`. The last dimension of `indices` can be at most the rank of `shape`:

indices.shape[-1] <= shape.rank

The last dimension of `indices` corresponds to indices into elements (if `indices.shape[-1] = shape.rank`) or slices (if `indices.shape[-1] < shape.rank`) along dimension `indices.shape[-1]` of `shape`. `updates` is a tensor with shape

indices.shape[:-1] + shape[indices.shape[-1]:]

The simplest form of tensor_scatter_sub is to subtract individual elements from a tensor by index. For example, say we want to insert 4 scattered elements in a rank-1 tensor with 8 elements.

In Python, this scatter subtract operation would look like this:

``````indices = tf.constant([[4], [3], [1], [7]])
updates = tf.constant([9, 10, 11, 12])
tensor = tf.ones([8], dtype=tf.int32)
print(updated)
``````
The resulting tensor would look like this:

[1, -10, 1, -9, -8, 1, 1, -11]

We can also, insert entire slices of a higher rank tensor all at once. For example, if we wanted to insert two slices in the first dimension of a rank-3 tensor with two matrices of new values.

In Python, this scatter add operation would look like this:

``````indices = tf.constant([[0], [2]])
updates = tf.constant([[[5, 5, 5, 5], [6, 6, 6, 6],
[7, 7, 7, 7], [8, 8, 8, 8]],
[[5, 5, 5, 5], [6, 6, 6, 6],
[7, 7, 7, 7], [8, 8, 8, 8]]])
tensor = tf.ones([4, 4, 4],dtype=tf.int32)
print(updated)
``````
The resulting tensor would look like this:

[[[-4, -4, -4, -4], [-5, -5, -5, -5], [-6, -6, -6, -6], [-7, -7, -7, -7]], [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]], [[-4, -4, -4, -4], [-5, -5, -5, -5], [-6, -6, -6, -6], [-7, -7, -7, -7]], [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]]

Note that on CPU, if an out of bound index is found, an error is returned. On GPU, if an out of bound index is found, the index is ignored.

### Constants

 String OP_NAME The name of this op, as known by TensorFlow core engine

### Public Methods

 Output () Returns the symbolic handle of the tensor. static TensorScatterNdSub ( Scope scope, Operand tensor, Operand indices, Operand updates) Factory method to create a class wrapping a new TensorScatterNdSub operation. Output () A new tensor copied from tensor and updates subtracted according to the indices.

## Constants

#### public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "TensorScatterSub"

## Public Methods

#### public Output <T> asOutput ()

Returns the symbolic handle of the 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 TensorScatterNdSub <T> create ( Scope scope, Operand <T> tensor, Operand <? extends TNumber > indices, Operand <T> updates)

Factory method to create a class wrapping a new TensorScatterNdSub operation.

##### Parameters
 scope current scope Tensor to copy/update. Index tensor. Updates to scatter into output.
##### Returns
• a new instance of TensorScatterNdSub

#### public Output <T> output ()

A new tensor copied from tensor and updates subtracted according to the indices.

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