// CHECK: "tfl.batch_to_space_nd"
}

func.func @space_to_batch_nd(%arg0: tensor<1x4x4x3xf32>, %arg1: tensor<2xi32>, %arg2: tensor<2x2xi32>) -> tensor<*xf32> {
  %0 = "tf.SpaceToBatchND"(%arg0, %arg1, %arg2) : (tensor<1x4x4x3xf32>, tensor<2xi32>, tensor<2x2xi32>) -> tensor<*xf32>
  func.return %0 : tensor<*xf32>
  // CHECK-LABEL: space_to_batch_nd

// -----

// CHECK-LABEL: testSpaceToBatchND
func.func @testSpaceToBatchND(%arg0 : tensor<1x4x4x3xf32>, %arg1 : tensor<2xi32>, %arg2 : tensor<2x2xi32>) -> tensor<?xf32> {
  // CHECK: "tfl.space_to_batch_nd"(%arg0, %arg1, %arg2)
  %0 = "tfl.space_to_batch_nd"(%arg0, %arg1, %arg2) : (tensor<1x4x4x3xf32>, tensor<2xi32>, tensor<2x2xi32>) -> tensor<?xf32>
  func.return %0 : tensor<?xf32>
}

// -----

    TFL_TensorOf<[I32]>:$indices
  );

  let results = (outs
    TFL_TensorOf<[F32, I16, I32, I64, UI8, QI8, QUI8, QI16]>:$output
  );
}

def TFL_SpaceToBatchNdOp: TFL_Op<"space_to_batch_nd", [
    Pure,
    QuantizableResult,
    SameOperandsAndResultsScale,
    TFL_OperandHasRankRange<0, 3, 4>,
    PredOpTrait<"input and output must have same element type",