tf.raw_ops.RaggedCross

Generates a feature cross from a list of tensors, and returns it as a

tf.raw_ops.RaggedCross(
    ragged_values,
    ragged_row_splits,
    sparse_indices,
    sparse_values,
    sparse_shape,
    dense_inputs,
    input_order,
    hashed_output,
    num_buckets,
    hash_key,
    out_values_type,
    out_row_splits_type,
    name=None
)

RaggedTensor. See tf.ragged.cross for more details.

Args: ragged_values: A list of Tensor objects with types from: int64, string. The values tensor for each RaggedTensor input. ragged_row_splits: A list of Tensor objects with types from: int32, int64. The row_splits tensor for each RaggedTensor input. sparse_indices: A list of Tensor objects with type int64. The indices tensor for each SparseTensor input. sparse_values: A list of Tensor objects with types from: int64, string. The values tensor for each SparseTensor input. sparse_shape: A list with the same length as sparse_indices of Tensor objects with type int64. The dense_shape tensor for each SparseTensor input. dense_inputs: A list of Tensor objects with types from: int64, string. The tf.Tensor inputs. input_order: A string. String specifying the tensor type for each input. The ith character in this string specifies the type of the ith input, and is one of: 'R' (ragged), 'D' (dense), or 'S' (sparse). This attr is used to ensure that the crossed values are combined in the order of the inputs from the call to tf.ragged.cross. hashed_output: A bool. num_buckets: An int that is >= 0. hash_key: An int. out_values_type: A tf.DType from: tf.int64, tf.string. out_row_splits_type: A tf.DType from: tf.int32, tf.int64. name: A name for the operation (optional).

Returns: A tuple of Tensor objects (output_values, output_row_splits).

output_values: A `Tensor` of type `out_values_type`.
output_row_splits: A `Tensor` of type `out_row_splits_type`.