Gather ragged slices from `params` axis `0` according to `indices`.
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.
Public Methods
static <T extends Number, U, V extends Number> RaggedGather<T, U> | |
Output<U> |
outputDenseValues()
The `flat_values` for the returned RaggedTensor.
|
List<Output<T>> |
outputNestedSplits()
The `nested_row_splits` tensors that define the row-partitioning for the
returned RaggedTensor.
|
Inherited Methods
Public Methods
public static RaggedGather<T, U> create (Scope scope, Iterable<Operand<T>> paramsNestedSplits, Operand<U> paramsDenseValues, Operand<V> indices, Long OUTPUTRAGGEDRANK)
Factory method to create a class wrapping a new RaggedGather operation.
Parameters
scope | current scope |
---|---|
paramsNestedSplits | The `nested_row_splits` tensors that define the row-partitioning for the `params` RaggedTensor input. |
paramsDenseValues | 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 | Indices in the outermost dimension of `params` of the values that should be gathered. |
OUTPUTRAGGEDRANK | 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`. |
Returns
- a new instance of RaggedGather
public List<Output<T>> outputNestedSplits ()
The `nested_row_splits` tensors that define the row-partitioning for the returned RaggedTensor.