code: def generate_trade_decision(self, execute_result=None):
      # get the number of trading step finished, trade_step can be [0, 1, 2, ..., trade_len - 1]
      trade_step = self.trade_calendar.get_trade_step()
      # get the total count of trading step
      trade_len = self.trade_calendar.get_trade_len()
  
      # update the order amount
      if execute_result is not None:
          for order, _, _, _ in execute_result:
              self.trade_amount[order.stock_id] -= order.deal_amount
  
      (
          trade_start_time,
          trade_end_time,
      ) = self.trade_calendar.get_step_time(trade_step)
      (
          pred_start_time,
          pred_end_time,
      ) = self.trade_calendar.get_step_time(trade_step, shift=1)
      order_list = []
      for order in self.outer_trade_decision.get_decision():
          # if not tradable, continue
          if not self.trade_exchange.is_stock_tradable(
              stock_id=order.stock_id,
              start_time=trade_start_time,
              end_time=trade_end_time,
          ):
              continue
          _order_amount = None
          # considering trade unit
  
          sig_sam = (
              resam_ts_data(
                  self.signal[order.stock_id],
                  pred_start_time,
                  pred_end_time,
                  method=ts_data_last,
              )
              if order.stock_id in self.signal
              else None
          )
  
          if sig_sam is None or np.isnan(sig_sam):
              # no signal, TWAP
              _amount_trade_unit = (
                  self.trade_exchange.get_amount_of_trade_unit(
                      stock_id=order.stock_id,
                      start_time=order.start_time,
                      end_time=order.end_time,
                  )
              )
              if _amount_trade_unit is None:
                  # divide the order into equal parts, and trade one part
                  _order_amount = self.trade_amount[order.stock_id] / (
                      trade_len - trade_step
                  )
              else:
                  # divide the order into equal parts, and trade one part
                  # calculate the total count of trade units to trade
                  trade_unit_cnt = int(
                      self.trade_amount[order.stock_id]
                      // _amount_trade_unit
                  )
                  # calculate the amount of one part, ceil the amount
                  # floor((trade_unit_cnt + trade_len - trade_step - 1) / (trade_len - trade_step)) == ceil(trade_unit_cnt / (trade_len - trade_step))
                  _order_amount = (
                      (trade_unit_cnt + trade_len - trade_step - 1)
                      // (trade_len - trade_step)
                      * _amount_trade_unit
                  )
          else:
              # VA strategy
              kappa_tild = self.lamb / self.eta * sig_sam * sig_sam
              kappa = np.arccosh(kappa_tild / 2 + 1)
              amount_ratio = (
                  np.sinh(kappa * (trade_len - trade_step))
                  - np.sinh(kappa * (trade_len - trade_step - 1))
              ) / np.sinh(kappa * trade_len)
              _order_amount = order.amount * amount_ratio
              _order_amount = (
                  self.trade_exchange.round_amount_by_trade_unit(
                      _order_amount,
                      stock_id=order.stock_id,
                      start_time=order.start_time,
                      end_time=order.end_time,
                  )
              )
  
          if order.direction == order.SELL:
              # sell all amount at last
              if self.trade_amount[order.stock_id] > 1e-5 and (
                  _order_amount < 1e-5 or trade_step == trade_len - 1
              ):
                  _order_amount = self.trade_amount[order.stock_id]
  
          _order_amount = min(
              _order_amount, self.trade_amount[order.stock_id]
          )
  
          if _order_amount > 1e-5:
              _order = Order(
                  stock_id=order.stock_id,
                  amount=_order_amount,
                  start_time=trade_start_time,
                  end_time=trade_end_time,
                  direction=order.direction,  # 1 for buy
                  factor=order.factor,
              )
              order_list.append(_order)
      return TradeDecisionWO(order_list, self)
  
imports: from pathlib import Path
  import warnings
  import numpy
  import pandas
  from typing import IO, List, Tuple, Union
  from qlib.data.dataset.utils import convert_index_format
  from qlib.utils import lazy_sort_index
  from ...utils.resam import resam_ts_data, ts_data_last
  from ...data.data import D
  from ...strategy.base import BaseStrategy
  from ...backtest.decision import BaseTradeDecision, Order, TradeDecisionWO, TradeRange
  from ...backtest.exchange import Exchange, OrderHelper
  from ...backtest.utils import CommonInfrastructure, LevelInfrastructure
  from qlib.utils.file import get_io_object
  from qlib.backtest.utils import get_start_end_idx
label_desc: Use image node_id 5 for calling the ACStrategy obj's underlying member method code with example usage: obj.generate_trade_decision(execute_result) and returns: TradeDecisionWO