next_values_to_visit.push_back(
              while_op.getCond().front().getArgument(operand_number));
          next_values_to_visit.push_back(
              while_op.getBody().front().getArgument(operand_number));
          continue;
        }

        if (llvm::isa<mlir::TF::IdentityOp, mlir::TF::CastOp,
                      mlir::TF::ReadVariableOp>(owner)) {

                              ArrayRef<Type> dataset_types) {
  const Location loc = reduce_dataset.getLoc();
  auto while_input_types = dataset_while.getOperandTypes();
  auto& body_region = dataset_while.getBody();
  Block* body_block = builder.createBlock(&body_region);
  auto body_arguments = body_block->addArguments(
      while_input_types, SmallVector<Location>(while_input_types.size(), loc));

// the function body.
std::optional<llvm::StringMap<FunctionMetadata>> GetFunctionMetadatas(
    func::FuncOp func_op) {
  llvm::StringMap<FunctionMetadata> metadatas;
  WalkResult result = func_op.getBody().walk([&](Operation *op) {
    std::string op_host = GetHost(op);
    FunctionMetadata &func_metadata = metadatas[op_host];
    func_metadata.original_name = func_op.getName();

		MethodDelete,
		MethodOptions,
		MethodTrace,
	} {
		req.Method = method
		_, body := getBody(t, method, req, c)
		if !bytes.Equal(body, file) {
			t.Fatalf("body mismatch for %v request: got %q, want %q", method, body, file)
		}
	}

	// HEAD request.
	req.Method = MethodHead
	resp, body := getBody(t, "HEAD", req, c)
	if len(body) != 0 {
		t.Fatalf("body mismatch for HEAD request: got %q, want empty", body)

  void runOnOperation() override;
};

// TODO(fengliuai): migrate to use modify_io_nodes pass.
void RemoveQuantizationAdaptorOps(func::FuncOp func) {
  mlir::OpBuilder builder(func.getBody());
  auto& bb = func.front();
  auto loc = func.getLoc();

  int num_args = bb.getNumArguments();
  llvm::SmallVector<Type, 4> input_types;
  input_types.reserve(num_args);

		return req, nil // nothing to rewind
	}
	if !req.Body.(*readTrackingBody).didClose {
		req.closeBody()
	}
	if req.GetBody == nil {
		return nil, errCannotRewind
	}
	body, err := req.GetBody()
	if err != nil {
		return nil, err
	}
	newReq := *req
	newReq.Body = &readTrackingBody{ReadCloser: body}
	return &newReq, nil
}

      (*buffer_to_size)[region.getArgument(i)] = {size_arg,
                                                  it->getSecond().fixed};
    }
  };

  // Rewrite body.
  Region& body_region = while_op.getBody();
  modify_region_arguments(body_region);
  if (failed(DecomposeTensorListOpsInternal(
          &body_region.front(), module, buffer_to_size,
          decomposed_partitioned_call_callees))) {
    return failure();

    auto guard = OpBuilder::InsertionGuard(*rewriter);
    auto inputs = branch_func.getFunctionType().getInputs();
    Block *block = rewriter->createBlock(
        &branch_func.getBody(), branch_func.begin(), inputs,
        SmallVector<Location>(inputs.size(), branch_func.getLoc()));

    auto input_shape = block->getArgument(1);
    auto size_diff = block->getArgument(2);

      llvm::ArrayRef<std::pair<mlir::ValueRange, mlir::Type>>{},
      mlir::ValueRange{}, mlir::TypeRange{});
  builder.setInsertionPoint(&replicate.getBody().front(),
                            replicate.getBody().front().begin());

  llvm::SmallVector<mlir::Type, 8> result_types;
  auto cluster = builder.create<mlir::tf_device::ClusterOp>(
      mlir::UnknownLoc::get(&context), result_types);

    wrap_func->setAttr(TF::kFromXlaCallModuleAttrName, builder.getUnitAttr());
  }
  wrap_func->setAttr(kFusedFunctionAttr, builder.getUnitAttr());
  builder.createBlock(&wrap_func.getBody(), wrap_func.begin(), arg_types,
                      arg_locs);

  IRMapping mapping;
  for (int32_t i : llvm::seq<int32_t>(0, arguments.size())) {
    mapping.map(arguments[i], wrap_func.getArgument(i));
  }