// Set dimension sizes specified by broadcast_dimensions.
  ArrayRef<int64_t> input_shape =
      mlir::cast<ShapedType>(input.getType()).getShape();
  for (auto x : llvm::enumerate(broadcast_dimensions)) {
    expanded_shape[x.value().getSExtValue()] =
        rewriter.getI64IntegerAttr(input_shape[x.index()]);
  }

  // Create the expanded type wrapped in a arith::ConstantOp.
  auto attr_type =

  %paddings = "tf.Const"() {value = dense<[[1, 2], [1, 2]]> : tensor<2x2xi64>} : () -> tensor<2x2xi64>
  // expected-error @+1 {{requires block_shape[i] divides input_shape[i + 1] + paddings[i, 0] + paddings[i, 1]; failed for i=1}}
  %1 = "tf.SpaceToBatchND"(%input, %block_shape, %paddings) : (tensor<3x5x7x10xf32>, tensor<2xi64>, tensor<2x2xi64>) -> tensor<36x2x3x10xf32>