tf.raw_ops.RaggedGather

Gather ragged slices from params axis 0 according to indices.

tf.raw_ops.RaggedGather(
    params_nested_splits,
    params_dense_values,
    indices,
    OUTPUT_RAGGED_RANK,
    name=None
)

Outputs a RaggedTensor output composed from output_dense_values and output_nested_splits, such that:

output.shape = indices.shape + params.shape[1:]
output.ragged_rank = indices.shape.ndims + params.ragged_rank
output[i...j, d0...dn] = params[indices[i...j], d0...dn]

where

  • params = ragged.from_nested_row_splits(params_dense_values, params_nested_splits) provides the values that should be gathered.
  • indices ia a dense tensor with dtype int32 or int64, indicating which values should be gathered.
  • output = ragged.from_nested_row_splits(output_dense_values, output_nested_splits) is the output tensor.

(Note: This c++ op is used to implement the higher-level python tf.ragged.gather op, which also supports ragged indices.)

params_nested_splits A list of at least 1 Tensor objects with the same type in: int32, int64. The nested_row_splits tensors that define the row-partitioning for the params RaggedTensor input.
params_dense_values A Tensor. The flat_values for the params RaggedTensor. There was a terminology change at the python level from dense_values to flat_values, so dense_values is the deprecated name.
indices A Tensor. Must be one of the following types: int32, int64. Indices in the outermost dimension of params of the values that should be gathered.
OUTPUT_RAGGED_RANK An int that is >= 0. The ragged rank of the output RaggedTensor. output_nested_splits will contain this number of row_splits tensors. This value should equal indices.shape.ndims + params.ragged_rank - 1.
name A name for the operation (optional).

A tuple of Tensor objects (output_nested_splits, output_dense_values).
output_nested_splits A list of OUTPUT_RAGGED_RANK Tensor objects with the same type as params_nested_splits.
output_dense_values A Tensor. Has the same type as params_dense_values.