parameters: (sp_input,
                               axis=None,
                               keepdims=None,
                               reduction_axes=None,
                               keep_dims=None)
return_statement: return sparse_tensor.SparseTensor(output_ind, output_val, output_shape)
docstring: Computes the sum of elements across dimensions of a SparseTensor.
  
    This Op takes a SparseTensor and is the sparse counterpart to
    `tf.reduce_sum()`.  In contrast to SparseReduceSum, this Op returns a
    SparseTensor.
  
    Note: A gradient is not defined for this function, so it can't be used
    in training models that need gradient descent.
  
    Reduces `sp_input` along the dimensions given in `reduction_axes`.  Unless
    `keepdims` is true, the rank of the tensor is reduced by 1 for each entry in
    `reduction_axes`. If `keepdims` is true, the reduced dimensions are retained
    with length 1.
  
    If `reduction_axes` has no entries, all dimensions are reduced, and a tensor
    with a single element is returned.  Additionally, the axes can be negative,
    which are interpreted according to the indexing rules in Python.
  
    Args:
      sp_input: The SparseTensor to reduce. Should have numeric type.
      axis: The dimensions to reduce; list or scalar. If `None` (the
        default), reduces all dimensions.
      keepdims: If true, retain reduced dimensions with length 1.
      reduction_axes: Deprecated name of axis.
      keep_dims: Deprecated alias for `keepdims`.
  
    Returns:
      The reduced SparseTensor.
docstring_summary: Computes the sum of elements across dimensions of a SparseTensor.
docstring_tokens: Computes the sum of elements across dimensions of a SparseTensor .
function: def sparse_reduce_sum_sparse(sp_input,
                               axis=None,
                               keepdims=None,
                               reduction_axes=None,
                               keep_dims=None):
    """Computes the sum of elements across dimensions of a SparseTensor.
  
    This Op takes a SparseTensor and is the sparse counterpart to
    `tf.reduce_sum()`.  In contrast to SparseReduceSum, this Op returns a
    SparseTensor.
  
    Note: A gradient is not defined for this function, so it can't be used
    in training models that need gradient descent.
  
    Reduces `sp_input` along the dimensions given in `reduction_axes`.  Unless
    `keepdims` is true, the rank of the tensor is reduced by 1 for each entry in
    `reduction_axes`. If `keepdims` is true, the reduced dimensions are retained
    with length 1.
  
    If `reduction_axes` has no entries, all dimensions are reduced, and a tensor
    with a single element is returned.  Additionally, the axes can be negative,
    which are interpreted according to the indexing rules in Python.
  
    Args:
      sp_input: The SparseTensor to reduce. Should have numeric type.
      axis: The dimensions to reduce; list or scalar. If `None` (the
        default), reduces all dimensions.
      keepdims: If true, retain reduced dimensions with length 1.
      reduction_axes: Deprecated name of axis.
      keep_dims: Deprecated alias for `keepdims`.
  
    Returns:
      The reduced SparseTensor.
    """
    keepdims = deprecation.deprecated_argument_lookup("keepdims", keepdims,
                                                      "keep_dims", keep_dims)
    axis = deprecation.deprecated_argument_lookup("axis", axis, "reduction_axes",
                                                  reduction_axes)
    if keepdims is None:
      keepdims = False
  
    output_ind, output_val, output_shape = (
        gen_sparse_ops.sparse_reduce_sum_sparse(
            sp_input.indices, sp_input.values, sp_input.dense_shape,
            math_ops._ReductionDims(sp_input, axis), keepdims))
  
    return sparse_tensor.SparseTensor(output_ind, output_val, output_shape)
function_tokens: def sparse_reduce_sum_sparse ( sp_input , axis = None , keepdims = None , reduction_axes = None , keep_dims = None ) : keepdims = deprecation . deprecated_argument_lookup ( "keepdims" , keepdims , "keep_dims" , keep_dims ) axis = deprecation . deprecated_argument_lookup ( "axis" , axis , "reduction_axes" , reduction_axes ) if keepdims is None : keepdims = False output_ind , output_val , output_shape = ( gen_sparse_ops . sparse_reduce_sum_sparse ( sp_input . indices , sp_input . values , sp_input . dense_shape , math_ops . _ReductionDims ( sp_input , axis ) , keepdims ) ) return sparse_tensor . SparseTensor ( output_ind , output_val , output_shape )