tf.raw_ops.DenseToSparseSetOperation

Applies set operation along last dimension of Tensor and SparseTensor.

tf.raw_ops.DenseToSparseSetOperation(
    set1, set2_indices, set2_values, set2_shape, set_operation,
    validate_indices=True, name=None
)

See SetOperationOp::SetOperationFromContext for values of set_operation.

Input set2 is a SparseTensor represented by set2_indices, set2_values, and set2_shape. For set2 ranked n, 1st n-1 dimensions must be the same as set1. Dimension n contains values in a set, duplicates are allowed but ignored.

If validate_indices is True, this op validates the order and range of set2 indices.

Output result is a SparseTensor represented by result_indices, result_values, and result_shape. For set1 and set2 ranked n, this has rank n and the same 1st n-1 dimensions as set1 and set2. The nth dimension contains the result of set_operation applied to the corresponding [0...n-1] dimension of set.

Args:

  • set1: A Tensor. Must be one of the following types: int8, int16, int32, int64, uint8, uint16, string. Tensor with rank n. 1st n-1 dimensions must be the same as set2. Dimension n contains values in a set, duplicates are allowed but ignored.
  • set2_indices: A Tensor of type int64. 2D Tensor, indices of a SparseTensor. Must be in row-major order.
  • set2_values: A Tensor. Must have the same type as set1. 1D Tensor, values of a SparseTensor. Must be in row-major order.
  • set2_shape: A Tensor of type int64. 1D Tensor, shape of a SparseTensor. set2_shape[0...n-1] must be the same as the 1st n-1 dimensions of set1, result_shape[n] is the max set size across n-1 dimensions.
  • set_operation: A string.
  • validate_indices: An optional bool. Defaults to True.
  • name: A name for the operation (optional).

Returns:

A tuple of Tensor objects (result_indices, result_values, result_shape).

  • result_indices: A Tensor of type int64.
  • result_values: A Tensor. Has the same type as set1.
  • result_shape: A Tensor of type int64.