parameters: (index, updates, shape, name=None)
return_statement: return scatter_nd_add(zeros(shape, updates.dtype), index, updates, name)
docstring: **Scatter_nd Layer**
  
      Output is obtained by scattering the :attr:`updates` in a new tensor according
      to :attr:`index` . This op is similar to :code:`scatter_nd_add`, except the
      tensor of :attr:`shape` is zero-initialized. Correspondingly, :code:`scatter_nd(index, updates, shape)`
      is equal to :code:`scatter_nd_add(paddle.zeros(shape, updates.dtype), index, updates)` .
      If :attr:`index` has repeated elements, then the corresponding updates are accumulated.
      Because of the numerical approximation issues, the different order of repeated elements
      in :attr:`index` may cause different results. The specific calculation method can be
      seen :code:`scatter_nd_add` . This op is the inverse of the :code:`gather_nd` op.
  
      Args:
          index (Tensor): The index input with ndim > 1 and index.shape[-1] <= len(shape).
                            Its dtype should be int32 or int64 as it is used as indexes.
          updates (Tensor): The updated value of scatter_nd op. Its dtype should be float32, float64.
                              It must have the shape index.shape[:-1] + shape[index.shape[-1]:]
          shape(tuple|list): Shape of output tensor.
          name (str|None): The output Tensor name. If set None, the layer will be named automatically.
  
      Returns:
          output (Tensor): The output is a tensor with the same type as :attr:`updates` .
  
      Examples:
  
          .. code-block:: python
  
              import paddle
              import numpy as np
  
              index_data = np.array([[1, 1],
                                     [0, 1],
                                     [1, 3]]).astype(np.int64)
              index = paddle.to_tensor(index_data)
              updates = paddle.rand(shape=[3, 9, 10], dtype='float32')
              shape = [3, 5, 9, 10]
  
              output = paddle.scatter_nd(index, updates, shape)
docstring_summary: **Scatter_nd Layer**
docstring_tokens: ** Scatter_nd Layer **
function: def scatter_nd(index, updates, shape, name=None):
      """
      **Scatter_nd Layer**
  
      Output is obtained by scattering the :attr:`updates` in a new tensor according
      to :attr:`index` . This op is similar to :code:`scatter_nd_add`, except the
      tensor of :attr:`shape` is zero-initialized. Correspondingly, :code:`scatter_nd(index, updates, shape)`
      is equal to :code:`scatter_nd_add(paddle.zeros(shape, updates.dtype), index, updates)` .
      If :attr:`index` has repeated elements, then the corresponding updates are accumulated.
      Because of the numerical approximation issues, the different order of repeated elements
      in :attr:`index` may cause different results. The specific calculation method can be
      seen :code:`scatter_nd_add` . This op is the inverse of the :code:`gather_nd` op.
  
      Args:
          index (Tensor): The index input with ndim > 1 and index.shape[-1] <= len(shape).
                            Its dtype should be int32 or int64 as it is used as indexes.
          updates (Tensor): The updated value of scatter_nd op. Its dtype should be float32, float64.
                              It must have the shape index.shape[:-1] + shape[index.shape[-1]:]
          shape(tuple|list): Shape of output tensor.
          name (str|None): The output Tensor name. If set None, the layer will be named automatically.
  
      Returns:
          output (Tensor): The output is a tensor with the same type as :attr:`updates` .
  
      Examples:
  
          .. code-block:: python
  
              import paddle
              import numpy as np
  
              index_data = np.array([[1, 1],
                                     [0, 1],
                                     [1, 3]]).astype(np.int64)
              index = paddle.to_tensor(index_data)
              updates = paddle.rand(shape=[3, 9, 10], dtype='float32')
              shape = [3, 5, 9, 10]
  
              output = paddle.scatter_nd(index, updates, shape)
      """
      return scatter_nd_add(zeros(shape, updates.dtype), index, updates, name)
function_tokens: def scatter_nd ( index , updates , shape , name = None ) : return scatter_nd_add ( zeros ( shape , updates . dtype ) , index , updates , name )