}];

  let arguments = (ins
    AnyType:$data,
    TensorOf<[I32]>:$index,
    // Optional extra control inputs.
    Variadic<TfeControlType>:$controlInputs,
    I64Attr:$num_outs
  );

  let results = (outs
    Variadic<AnyType>:$outputs,
    TfeControlType: $control
  );
}

def TfExecutor_MergeOp : TfExecutor_Op<"Merge",

    Set a tensor in resource array.

    arg: the tensor to be set in the resource array.
    index: the index in the resource array
  }];

  let arguments = (ins
    TFTensorType:$arg,
    I64Attr:$index
  );

  let results = (outs);

  let assemblyFormat = "operands attr-dict";
}

def GetResourceOp : TensorflowMlrt_Op<"get_resource", []> {
  let summary = "get a tensor in resource array";

def ValueToVariadic: NativeCodeCall<"SmallVector<Value, 1>{$0}">;
def : Pat<(TF_AllToAllOp AnyRankedTensor:$input, (ConstantLikeMatcher ElementsAttr:$group_assignment), I64Attr:$concat_dimension, $split_dimension, $split_count),
          (MHLO_AllToAllOp (ValueToVariadic $input), $split_dimension, $concat_dimension, $split_count, (CastElementsToI64Elements $group_assignment), (NullChannelHandleAttr))>;

lower bound 0 is included in the range, while the upper bound 1 is excluded.
  }];

  let arguments = (ins
    TFL_I32Tensor:$shape,
    DefaultValuedOptionalAttr<I64Attr, "0">:$seed,
    DefaultValuedOptionalAttr<I64Attr, "0">:$seed2
  );

   let results = (outs
    TFL_TensorOf<[F32]>:$out);
  let hasOptions = 1;
  let customOption = "RandomOptions";
}

}

// I32Attr already returns an int as required by flatbuffer builders.
static int ConvertI32AttrForOptionWriter(
    int i, flatbuffers::FlatBufferBuilder* builder) {
  return i;
}

// I64Attr already returns a int64_t as required by flatbuffer builders.
static int64_t ConvertI64AttrForOptionWriter(
    int64_t i, flatbuffers::FlatBufferBuilder* builder) {
  return i;
}