}];

  let arguments = (ins
    Arg<TF_Int32Tensor, [{int32 `Tensor`.}]>:$arr,
    Arg<TF_Int32Tensor, [{non-negative int32 scalar `Tensor`.}]>:$size,
    Arg<TensorOf<[TF_Float32, TF_Float64, TF_Int32, TF_Int64]>, [{is an int32, int64, float32, or float64 `Tensor` with the same
shape as `arr`, or a length-0 `Tensor`, in which case it acts as all weights
equal to 1.}]>:$weights
  );

        `strategy.scope()`.
*   `TensorRT`
    *   [TensorRT 6.0](https://developer.nvidia.com/tensorrt#tensorrt-whats-new)
        is now supported and enabled by default. This adds support for more
        TensorFlow ops including Conv3D, Conv3DBackpropInputV2, AvgPool3D,
        MaxPool3D, ResizeBilinear, and ResizeNearestNeighbor. In addition, the
        TensorFlow-TensorRT python conversion API is exported as

          name: "tensor_names"
          type: DT_STRING
        }
        input_arg {
          name: "shape_and_slices"
          type: DT_STRING
        }
        output_arg {
          name: "tensors"
          type_list_attr: "dtypes"
        }
        attr {
          name: "dtypes"
          type: "list(type)"
          has_minimum: true
          minimum: 1
        }
        is_stateful: true