滚动训练 这报错 该怎么解决
由bqnvfzc5创建，最终由small_q 被浏览 23 用户
-
\
Output exceeds the size limit. Open the full output data in a text editor--------------------------------------------------------------------------- KeyboardInterrupt Traceback (most recent call last) Cell In[4], line 434 429 trade = g.run(parameters) 431 return {'rollings': results, 'trade': trade} --> 434 m21 = M.hyper_rolling_train.v1( 435 run=m21_run_bigquant_run, 436 run_now=True, 437 bq_graph=g 438 ) File module2/common/modulemanagerv2.py:88, in biglearning.module2.common.modulemanagerv2.BigQuantModuleVersion.call() File module2/common/moduleinvoker.py:349, in biglearning.module2.common.moduleinvoker.module_invoke() File module2/common/moduleinvoker.py:232, in biglearning.module2.common.moduleinvoker._invoke_with_cache() File module2/common/moduleinvoker.py:189, in biglearning.module2.common.moduleinvoker._module_run() File module2/modules/hyper_rolling_train/v1/init.py:128, in biglearning.module2.modules.hyper_rolling_train.v1.init.bigquant_run() Cell In[4], line 419, in m21_run_bigquant_run(bq_graph, inputs, trading_days_market, train_instruments_mid, test_instruments_mid, predict_mid, trade_mid, start_date, end_date, train_update_days, train_update_days_for_live, train_data_min_days, train_data_max_days, rolling_count_for_live) 417 parameters[test_instruments_mid + '.end_date'] = rolling['test_end_date'] 418 # print('------ rolling_train:', parameters) --> 419 results.append(g.run(parameters)) 421 # 合并预测结果并回测 422 mx = M.cached.v3(run=merge_datasources, input_1=[[result[predict_mid].predictions, result[test_instruments_mid].data.read_pickle()['start_date']] for result in results]) File /var/app/enabled/biglearning/graphimpl/graph.py:273, in Graph.run(self, parameters, execution_class) 271 if isinstance(execution_object, GraphFAIExecution) and self.fai_cluster is not None: 272 execution_object.fai_cluster = self.fai_cluster --> 273 return execution_object.run() File /var/app/enabled/biglearning/graphimpl/graph.py:154, in GraphExecution.run(self) 152 def run(self): 153 self.build_graph() --> 154 self._exec_graph() 156 results = {} 157 for module, args in self._graph.items(): File /var/app/enabled/biglearning/graphimpl/graph.py:145, in GraphExecution._exec_graph(self) 142 i = 0 143 while i < len(queue): 144 # TODO: parallel execute --> 145 self.exec_module(queue[i]) 146 for depender in self._graph[queue[i]][GraphExecution.KEY_DEPENDERS]: 147 self._graph[depender][GraphExecution.KEY_DEPENDEES].remove(queue[i]) File /var/app/enabled/biglearning/graphimpl/graph.py:133, in GraphExecution.exec_module(self, module) 130 v = getattr(self._graph[v.module][GraphExecution.KEY_OUTPUTS], v.parameter) 131 module_args[k] = v --> 133 outputs = self.run_module(module_type, module_args) 134 args[GraphExecution.KEY_OUTPUTS] = outputs 135 globals()[module] = outputs File /var/app/enabled/biglearning/graphimpl/graph.py:119, in GraphExecution.run_module(self, module_type, args) 116 def run_module(self, module_type, args): 117 from biglearning.module2.common.modulemanagerv2 import M --> 119 return M[module_type](**args) File module2/common/modulemanagerv2.py:88, in biglearning.module2.common.modulemanagerv2.BigQuantModuleVersion.call() File module2/common/moduleinvoker.py:349, in biglearning.module2.common.moduleinvoker.module_invoke() File module2/common/moduleinvoker.py:232, in biglearning.module2.common.moduleinvoker._invoke_with_cache() File module2/common/moduleinvoker.py:191, in biglearning.module2.common.moduleinvoker._module_run() File module2/modules/derived_feature_extractor/v3/init.py:93, in biglearning.module2.modules.derived_feature_extractor.v3.init.BigQuantModule.run() File /usr/local/python3/lib/python3.8/site-packages/pandas/io/pytables.py:578, in HDFStore.getitem(self, key) 577 def getitem(self, key: str): --> 578 return self.get(key) File /usr/local/python3/lib/python3.8/site-packages/pandas/io/pytables.py:770, in HDFStore.get(self, key) 768 if group is None: 769 raise KeyError(f"No object named {key} in the file") --> 770 return self._read_group(group) File /usr/local/python3/lib/python3.8/site-packages/pandas/io/pytables.py:1764, in HDFStore._read_group(self, group) 1762 s = self._create_storer(group) 1763 s.infer_axes() -> 1764 return s.read() File /usr/local/python3/lib/python3.8/site-packages/pandas/io/pytables.py:3145, in BlockManagerFixed.read(self, where, columns, start, stop) 3142 for i in range(self.nblocks): 3144 blk_items = self.read_index(f"block{i}_items") -> 3145 values = self.read_array(f"block{i}_values", start=_start, stop=_stop) 3147 columns = items[items.get_indexer(blk_items)] 3148 df = DataFrame(values.T, columns=columns, index=axes[1]) File /usr/local/python3/lib/python3.8/site-packages/pandas/io/pytables.py:2805, in GenericFixed.read_array(self, key, start, stop) 2802 transposed = getattr(attrs, "transposed", False) 2804 if isinstance(node, tables.VLArray): -> 2805 ret = node[0][start:stop] 2806 else: 2807 dtype = _ensure_decoded(getattr(attrs, "value_type", None)) File /usr/local/python3/lib/python3.8/site-packages/tables/vlarray.py:677, in VLArray.getitem(self, key) 675 key += self.nrows 676 (start, stop, step) = self._process_range(key, key + 1, 1) --> 677 return self.read(start, stop, step)[0] 678 elif isinstance(key, slice): 679 start, stop, step = self._process_range( 680 key.start, key.stop, key.step) File /usr/local/python3/lib/python3.8/site-packages/tables/vlarray.py:821, in VLArray.read(self, start, stop, step) 819 atom = self.atom 820 if not hasattr(atom, 'size'): # it is a pseudo-atom --> 821 outlistarr = [atom.fromarray(arr) for arr in listarr] 822 else: 823 # Convert the list to the right flavor 824 flavor = self.flavor
...
1617 def load_long_binget(self): -> 1618 i, = unpack('<I', self.read(4)) 1619 self.append(self.memo[i]) File /usr/local/python3/lib/python3.8/pickle.py:289, in _Unframer.read(self, n) 287 def read(self, n): 288 if self.current_frame: --> 289 data = self.current_frame.read(n) 290 if not data and n != 0: 291 self.current_frame = None KeyboardInterrupt:
-
pytables.to_hdf(
-
[2023-10-21 18:49:42.773790] INFO: moduleinvoker:graph.py:119:run_module cached.v2 运行完成[131.403672s].
-
[2023-10-21 18:52:00.110829] INFO backtest: algo history_data=DataSource(69079ce75bc94afd8ddf42b8ba50a309T)
-
[2023-10-21 18:52:00.115400] INFO algo: TradingAlgorithm V1.8.9
-
[2023-10-21 18:52:39.936740] INFO algo: trading transform...
-
/usr/local/python3/lib/python3.8/site-packages/pandas/core/indexing.py:1124: FutureWarning: Indexing a timezone-naive DatetimeIndex with a timezone-aware datetime is deprecated and will raise KeyError in a future version. Use a timezone-naive object instead.
-
return self._get_label(key, axis=axis)
\