new_operands[index] = builder.create<TF::ReadVariableOp>(
        caller->getLoc(), ArrayRef<Type>{new_type}, ArrayRef<Value>{operand});
    caller->setOperand(index, new_operands[index]);
    if (updated_index < 0) continue;
    builder.setInsertionPointAfter(caller);
    builder.create<TF::AssignVariableOp>(
        caller->getLoc(), ArrayRef<Type>{},
        ArrayRef<Value>{operand, caller->getResult(updated_index)});
  }

    for (const auto& arg : func_op.getArguments()) {
      arg_locs.push_back(arg.getLoc());
    }
  }

  // Creates a new main function.
  auto func_type = FunctionType::get(context, arg_types, result_types);
  auto main_func = builder.create<func::FuncOp>(
      module_op.getLoc(), kImportModelDefaultGraphFuncName, func_type);
  builder.createBlock(&main_func.getBody(), main_func.begin(), arg_types,

    // and its users.
    auto quantize = rewriter.create<quantfork::QuantizeCastOp>(
        tf_op.getLoc(), qtype.getValue(), input);
    auto dequantize = rewriter.create<quantfork::DequantizeCastOp>(
        tf_op.getLoc(), res_type, quantize.getResult());
    tf_op.getOutputs().replaceAllUsesWith(dequantize);

    return success();
  }

  bool use_fake_quant_num_bits_;

      ++num_unscheduled_ops;
    }
  }
  emitRemark(func.getLoc(), func.getName())
      << ": " << num_part_ops << " ops delegated out of " << num_all_ops
      << " ops with " << num_partitions_after
      << " partitions (originally: " << num_partitions_before << ")";
  if (!scheduled_everything) {
    emitError(func.getLoc(), func.getName())

    if (variable_name.empty()) {
      return signalPassFailure();
    }
    VarHandleOp var_handle_op = builder.create<VarHandleOp>(
        variable_v2_op.getLoc(),
        ArrayRef<Type>{RankedTensorType::get(
            {}, TF::ResourceType::get(ArrayRef<TensorType>{tensor_type},
                                      builder.getContext()))},
        ArrayRef<Value>{},

  if (IsKVCacheCompositeOp(composite)) {
    return builder.create<TFL::CustomOp>(
        composite->getLoc(), composite->getResultTypes(),
        composite->getOperands().slice(2, 3), composite.getName(),
        CustomOption(&builder, custom_option_buffer));
  }
  return builder.create<TFL::CustomOp>(
      composite->getLoc(), composite->getResultTypes(),
      composite->getOperands(), composite.getName(),

    // and its users.
    Value value = tf_op.getOutputs();
    auto quantize = rewriter.create<TFL::QuantizeOp>(
        tf_op.getLoc(), qtype.getValue(), value, qtype);
    auto dequantize = rewriter.create<TFL::DequantizeOp>(
        tf_op.getLoc(), res_type, quantize.getOutput());
    value.replaceAllUsesWith(dequantize);
    quantize.getOperation()->replaceUsesOfWith(dequantize, value);

func (c *sigctxt) sigcode() uint32 { return uint32(c.info.si_code) }
func (c *sigctxt) sigaddr() uint32 {
	return *(*uint32)(add(unsafe.Pointer(c.info), 16))
}

func (c *sigctxt) set_pc(x uint32)  { c.regs().sc_pc = x }
func (c *sigctxt) set_sp(x uint32)  { c.regs().sc_usr_sp = x }
func (c *sigctxt) set_lr(x uint32)  { c.regs().sc_usr_lr = x }
func (c *sigctxt) set_r10(x uint32) { c.regs().sc_r10 = x }

      if (!dict_attr) continue;

      OpBuilder builder(func.getContext());
      builder.setInsertionPointToStart(&func.getBlocks().front());
      builder.create<TFL::CallOnceOp>(func.getLoc(), init_func_op.getName());
    }
  }
}

}  // namespace

// Inserts a TFL::CallOnce op when tf_saved_model's session initializer is
// given.
std::unique_ptr<OperationPass<ModuleOp>>

              operand.getDefiningOp<corert::ConstDenseTensorOp>()) {
        new_values.push_back(
            rewriter.create<fallback_async::ConstDenseTensorOp>(
                op.getLoc(), rewriter.getType<fallback::TFTensorType>(),
                corert_const_dense_tensor_op.getValue()));
        should_rewrite = true;
        continue;
      }
      if (auto corert_const_string_tensor_op =