tf.raw_ops.TakeManySparseFromTensorsMap

Read SparseTensors from a SparseTensorsMap and concatenate them.

tf.raw_ops.TakeManySparseFromTensorsMap(
    sparse_handles, dtype, container='', shared_name='', name=None
)

The input sparse_handles must be an int64 matrix of shape [N, 1] where N is the minibatch size and the rows correspond to the output handles of AddSparseToTensorsMap or AddManySparseToTensorsMap. The ranks of the original SparseTensor objects that went into the given input ops must all match. When the final SparseTensor is created, it has rank one higher than the ranks of the incoming SparseTensor objects (they have been concatenated along a new row dimension on the left).

The output SparseTensor object's shape values for all dimensions but the first are the max across the input SparseTensor objects' shape values for the corresponding dimensions. Its first shape value is N, the minibatch size.

The input SparseTensor objects' indices are assumed ordered in standard lexicographic order. If this is not the case, after this step run SparseReorder to restore index ordering.

For example, if the handles represent an input, which is a [2, 3] matrix representing two original SparseTensor objects:

    index = [ 0]
            [10]
            [20]
    values = [1, 2, 3]
    shape = [50]

and

    index = [ 2]
            [10]
    values = [4, 5]
    shape = [30]

then the final SparseTensor will be:

    index = [0  0]
            [0 10]
            [0 20]
            [1  2]
            [1 10]
    values = [1, 2, 3, 4, 5]
    shape = [2 50]

Args:

  • sparse_handles: A Tensor of type int64. 1-D, The N serialized SparseTensor objects. Shape: [N].
  • dtype: A tf.DType. The dtype of the SparseTensor objects stored in the SparseTensorsMap.
  • container: An optional string. Defaults to "". The container name for the SparseTensorsMap read by this op.
  • shared_name: An optional string. Defaults to "". The shared name for the SparseTensorsMap read by this op. It should not be blank; rather the shared_name or unique Operation name of the Op that created the original SparseTensorsMap should be used.
  • name: A name for the operation (optional).

Returns:

A tuple of Tensor objects (sparse_indices, sparse_values, sparse_shape).

  • sparse_indices: A Tensor of type int64.
  • sparse_values: A Tensor of type dtype.
  • sparse_shape: A Tensor of type int64.