TensorOf<[TF_Qint8]>:$rhs,
    TF_Float32Tensor:$lhs_scales,
    TF_Int32Tensor:$lhs_zps,
    TF_Float32Tensor:$rhs_scales,
    TF_Int32Tensor:$rhs_zps,
    TF_Float32Tensor:$output_scales,
    TF_Int32Tensor:$output_zps,

    StrAttr:$dimension_numbers,
    DefaultValuedOptionalAttr<I64Attr, "-1">:$lhs_quantization_axis,
    DefaultValuedOptionalAttr<I64Attr, "-128">:$lhs_quantization_min_val,

    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> unconditionally_use_set_output_shapes(
    "tf-enable-unconditionally-use-set-output-shapes-on-import",
    llvm::cl::desc("Enable using the _output_shapes unconditionally on import "
                   "(temporary)"),
    llvm::cl::init(false));

// NOLINTNEXTLINE
opt<bool> enable_soft_placement(
    "tf-enable-soft-placement-on-import",

  bool restrict_functionalization_to_compiled_nodes = false;
  // If true, enables shape inference on input.
  // TODO(jpienaar): This will be removed shortly.
  bool enable_shape_inference = true;
  // _output_shapes is an unregistered attribute which is used during
  // GraphConstructor::ConvertGraph to override shapes. It is unfortunately
  // not always set correctly (which is undesirable and should be addressed)

  // Create a bad output shape attr.
  AttrValue shape_attr;
  TensorShapeProto* shape_proto = shape_attr.mutable_list()->add_shape();
  shape_proto->add_dim()->set_size(1);
  builder.Attr("_output_shapes", shape_attr);

  TF_RETURN_IF_ERROR(builder.Finalize(&node));

  return CreateSingleOpGraph(node, {}, {DataType::DT_INT32});
}

absl::Status BuildHloFromGraph(Graph& graph, bool use_output_shapes) {