IslandOp GetDummyConstant(OpBuilder builder, ShapedType const_type,
                          Location loc) {
  DenseIntElementsAttr val = DenseIntElementsAttr::get(const_type, 1);
  auto const_op = builder.create<TF::ConstOp>(loc, val);
  auto const_island = CreateIsland(const_op, {}, builder);
  return const_island;
}

// Rewrites the while op with extra chaining operands and results. Uses a

  bool isSupportedAxis(mlir::Value value, int64_t rank) const {
    auto const_op =
        dyn_cast_or_null<mlir::arith::ConstantOp>(value.getDefiningOp());
    if (!const_op) {
      return false;
    }
    auto axes = dyn_cast<DenseIntElementsAttr>(const_op.getValueAttr());
    if (!axes || axes.getNumElements() != 1) {
      return false;
    }

  // CHECK-NEXT: %[[CAST_ZERO:.*]] = "tf.Cast"(%[[ZERO_SCALAR]]) : (tensor<i32>) -> tensor<f32>
  // CHECK-NEXT: %[[CONST10:.*]] = "tf.Const"() <{value = dense<10> : tensor<1xi32>}> : () -> tensor<1xi32>
  // CHECK-NEXT: %[[BROADCAST:.*]] = "tf.BroadcastTo"(%[[CAST_ZERO]], %[[CONST10]]) : (tensor<f32>, tensor<1xi32>) -> tensor<10xf32>
  // CHECK-NEXT: %[[BUFFER:.*]] = "tf.MlirLocalVarOp"() : () -> tensor<!tf_type.resource<tensor<10xf32>>>

  *op_header_guard = ToGuard(op_header);
  const string cc_header = strings::StrCat(
      R"include(// This file is MACHINE GENERATED! Do not edit.


#include "tensorflow/cc/ops/const_op.h"
)include",
      "#include \"", op_header, "\"\n", namespace_begin);

  const string filename = GetFilename(dot_h_fname);
  const string doxygen = strings::StrCat("/// @defgroup ", filename, " ",

#include "tensorflow/compiler/jit/partially_decluster_pass.h"

#include "absl/memory/memory.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/ops/array_ops.h"
#include "tensorflow/cc/ops/const_op.h"
#include "tensorflow/cc/ops/control_flow_ops_internal.h"
#include "tensorflow/cc/ops/function_ops.h"
#include "tensorflow/cc/ops/sendrecv_ops.h"
#include "tensorflow/cc/ops/standard_ops.h"

    }
    auto const_op =
        rewriter.create<TF::ConstOp>(loc, new_type, tensor_proto_attr);
    // Add scast op to match quantize -> composition pattern. The added scast
    // is then removed by canonicalization. ([scast - scast] -> [])
    auto scast_op = rewriter.create<quantfork::StorageCastOp>(
        loc, tensor_qtype, const_op.getOutput());
    q_op->replaceAllUsesWith(scast_op);

    %0 = tf_executor.graph {

    // CHECK: %[[CONST0:.*]] = "tf.Const"() <{value = dense<
    // CHECK-SAME: [4, 4, 2, 2, 3, 64]
    // CHECK: %[[RESHAPE0:.*]] = "tf.Reshape"(%[[BACKPROP:.*]], %[[CONST0:.*]]) : (tensor<4x4x12x64xf32>, tensor<6xi64>) -> tensor<4x4x2x2x3x64xf32>
    // CHECK: %[[CONST1:.*]] = "tf.Const"() <{value = dense<

def UndoBroadcastConvBiasAdd : Pat<
  (TFL_AddOp $lhs, (Arith_ConstantOp:$const_op $bias), TFL_AF_None),
  (TFL_AddOp $lhs, (Arith_ConstantOp (FlattenTo1D $bias)), TFL_AF_None),
  [(AnyStaticShapeTensor $lhs),
   (IsLastDimEqualToNumElements $bias, $bias),
   (HasOneUse $const_op),
   (HasRankAtMost<4> $bias),
   (HasRankAtLeast<2> $bias),
   (IsDefinedByConv2DOp $lhs)]>;

      {});
}

TEST_F(CApiFunctionTest, UsingOneOutputOfSplit) {
  /*
   *                      feed
   *                       |
   *             +---------+---+
   *             | const0  |   |
   *             |    |    |   |
   *             |    v    /   |
   *             |    split    |
   *             |   |  |  |   |
   *             |   v  |  v   |
   *             |      |      |