tensorflow::
   
  
   #include <state_ops.h>
  
  Applies sparse addition to individual values or slices in a Variable .
Summary
   
    ref
   
   is a
   
    
     Tensor
    
   
   with rank
   
    P
   
   and
   
    indices
   
   is a
   
    
     Tensor
    
   
   of rank
   
    Q
   
   .
  
   
    indices
   
   must be integer tensor, containing indices into
   
    ref
   
   . It must be shape
   
    [d_0, ..., d_{Q-2}, K]
   
   where
   
    0 < K <= P
   
   .
  
   The innermost dimension of
   
    indices
   
   (with length
   
    K
   
   ) corresponds to indices into elements (if
   
    K = P
   
   ) or slices (if
   
    K < P
   
   ) along the
   
    K
   
   th dimension of
   
    ref
   
   .
  
   
    updates
   
   is
   
    
     Tensor
    
   
   of rank
   
    Q-1+P-K
   
   with shape:
  
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]]
For example, say we want to add 4 scattered elements to a rank-1 tensor to 8 elements. In Python, that addition would look like this:
ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8]) indices = tf.constant([[4], [3], [1], [7]]) updates = tf.constant([9, 10, 11, 12]) add = tf.scatter_nd_add(ref, indices, updates) with tf.Session() as sess: print sess.run(add)
The resulting update to ref would look like this:
[1, 13, 3, 14, 14, 6, 7, 20]
   See
   
    tf.scatter_nd
   
   for more details about how to make updates to slices.
  
Args:
- scope: A Scope object
- ref: A mutable Tensor . Should be from a Variable node.
- indices: A Tensor . Must be one of the following types: int32, int64. A tensor of indices into ref.
- updates: A Tensor . Must have the same type as ref. A tensor of updated values to add to ref.
   Optional attributes (see
   
    
     Attrs
    
   
   ):
   
- use_locking: An optional bool. Defaults to True. If True, the assignment 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.
| Constructors and Destructors | |
|---|---|
| 
      
       ScatterNdAdd
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::Input
      
      ref, ::
      
       tensorflow::Input
      
      indices, ::
      
       tensorflow::Input
      
      updates)
      | |
| 
      
       ScatterNdAdd
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::Input
      
      ref, ::
      
       tensorflow::Input
      
      indices, ::
      
       tensorflow::Input
      
      updates, const
      
       ScatterNdAdd::Attrs
      
      & attrs)
      | 
| Public attributes | |
|---|---|
| 
      
       operation
      
      | |
| 
      
       output_ref
      
      | |
| Public functions | |
|---|---|
| 
      
       node
      
      () const
      | 
       ::tensorflow::Node *
       | 
| 
      
       operator::tensorflow::Input
      
      () const
      | 
       | 
| 
      
       operator::tensorflow::Output
      
      () const
      | 
       | 
| Public static functions | |
|---|---|
| 
      
       UseLocking
      
      (bool x)
      | |
| Structs | |
|---|---|
| tensorflow:: | Optional attribute setters for ScatterNdAdd . | 
Public attributes
Public functions
ScatterNdAdd
ScatterNdAdd( const ::tensorflow::Scope & scope, ::tensorflow::Input ref, ::tensorflow::Input indices, ::tensorflow::Input updates )
ScatterNdAdd
ScatterNdAdd( const ::tensorflow::Scope & scope, ::tensorflow::Input ref, ::tensorflow::Input indices, ::tensorflow::Input updates, const ScatterNdAdd::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const