return "";
  }

  auto assigned_value_operand = assign_var_op.getOperand(1);
  auto const_op =
      llvm::dyn_cast<mlir::TF::ConstOp>(assigned_value_operand.getDefiningOp());
  if (!const_op) {
    assign_var_op->emitRemark(
        "Operand idx 1 is not a tf.ConstOp. The initializing tensor is not "
        "saved to checkpoint.");
    return "";
  }

  Tensor const_tensor{};

    if (func.getNumArguments() == 0) {
      return;
    }

    auto builder = OpBuilder::atBlockBegin(&func.front());

    llvm::SmallDenseMap<llvm::StringRef, TF::ConstOp> const_ops;
    llvm::BitVector arg_indexes_to_remove(func.getNumArguments());

    // Replace arguments with const ops.
    for (BlockArgument argument : func.getArguments()) {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace quant {

std::optional<TF::PartitionedCallOp> ApplyUniformQuantization(
    PatternRewriter& rewriter, TF::ConstOp op,
    tensorflow::quantization::QuantizationComponentSpec& weight_spec);

}  // namespace quant
}  // namespace mlir

    q_op->replaceAllUsesWith(new_qcast);
    return success();
  }
};

class ConvertTFConstOpToArithConstOp : public OpRewritePattern<TF::ConstOp> {
 public:
  using OpRewritePattern::OpRewritePattern;
  LogicalResult matchAndRewrite(TF::ConstOp op,
                                PatternRewriter& rewriter) const override {
    rewriter.replaceOpWithNewOp<arith::ConstantOp>(op, op.getValue());
    return success();

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace tflite {
namespace {

bool IsConst(mlir::Operation* op) {
  return llvm::isa<mlir::arith::ConstantOp, mlir::TF::ConstOp,
                   mlir::TFL::ConstOp, mlir::TFL::QConstOp>(op);
}

bool IsOpSupported(mlir::Operation* op, const std::string& hardware) {
  auto* devce_hardware = mlir::TFL::tac::GetTargetHardware(hardware);

      /*add_passes_func=*/
      [](mlir::PassManager &pm) {
        pm.addPass(mlir::quant::CreateInsertRestoreOpPass());
        pm.addPass(mlir::quant::CreateInsertSaveOpPass());
        // Initialization by `tf.ConstOp` is no longer required as there is
        // a `tf.RestoreV2Op` now.
        pm.addPass(
            mlir::quant::CreateRemoveVariableInitializationByConstPass());
      },
      ctx, module_op);
}

}

// CHECK-LABEL: func @while_test_if
// CHECK-SAME: -> !tf_mlrt.tensor
func.func @while_test_if(%cond: tensor<i1>, %x: tensor<i1>, %y: tensor<i1>) -> (tensor<i32>) {
  // CHECK: [[CONST:%.*]] = tf_mlrt.constop {tensor_proto = "\08\03\12\00"}
  %cst = "tf.Const"() {__op_key = 2: i32, device = "/device:CPU:0", value = dense<0> : tensor<i32>} : () -> tensor<i32>
  // Predicate should be inlined.
  // CHECK-NEXT: tf_mlrt.predicate

Unfortunately, Helm provides us (1) and (3) together (as .Values), making it hard to insert (2).

However, we can workaround this by placing all of (1) under a specific key (.Values.defaults).
We can then merge the profile onto the defaults, then the user settings onto that.
Finally, we can set all of that under .Values so the chart behaves without awareness.
*/}}
{{- $defaults := $.Values.defaults }}
{{- $_ := unset $.Values "defaults" }}
{{- $profile := dict }}

Unfortunately, Helm provides us (1) and (3) together (as .Values), making it hard to insert (2).

However, we can workaround this by placing all of (1) under a specific key (.Values.defaults).
We can then merge the profile onto the defaults, then the user settings onto that.
Finally, we can set all of that under .Values so the chart behaves without awareness.
*/}}
{{- $defaults := $.Values.defaults }}
{{- $_ := unset $.Values "defaults" }}
{{- $profile := dict }}

Unfortunately, Helm provides us (1) and (3) together (as .Values), making it hard to insert (2).

However, we can workaround this by placing all of (1) under a specific key (.Values.defaults).
We can then merge the profile onto the defaults, then the user settings onto that.
Finally, we can set all of that under .Values so the chart behaves without awareness.
*/}}
{{- $defaults := $.Values.defaults }}
{{- $_ := unset $.Values "defaults" }}
{{- $profile := dict }}