}
    ```
  }];

  let arguments = (ins
    I32Tensor:$branch_index,
    Variadic<TF_Tensor>:$input,

    ConfinedAttr<SymbolRefArrayAttr, [ArrayMinCount<1>]>:$branches,

    // Used to map StatelessCase and Case op defined in TensorFlow to a common
    // op.
    BoolAttr:$is_stateless
  );

  let results = (outs
    Variadic<TF_Tensor>:$output
  );

    mlir::BoolAttr val = builder_.getBoolAttr(stateless);
    result.attributes.push_back(builder_.getNamedAttr("is_stateless", val));
  };

  // Map Case/If/While and StatelessCase/If/While op in TensorFlow to the common
  // Case/If/While op in MLIR and add the differentiating attribute.
  if (node.IsCaseNode()) composite_control_flow_op("Case");
  if (node.IsIfNode()) composite_control_flow_op("If");

*   Adds `tf.SparseTensor.with_values`. This returns a new SparseTensor with the
    same sparsity pattern, but with new provided values. It is similar to the
    `with_values` function of `RaggedTensor`.
*   Adds `StatelessCase` op, and uses it if none of case branches has stateful
    ops.
*   Adds `tf.config.experimental.get_memory_usage` to return total memory usage
    of the device.