在 MacOS(Monterey、Apple M1)上使用 H2O(来自 Python 3.9.10)和 XGBoost 后端时出错

发布于 2025-01-15 05:13:38 字数 2432 浏览 2 评论 0原文

我目前正在尝试从 Python 使用 H2O,并且在 Mac 操作系统上使用 XGBoost 时遇到了一些问题。 H2O 似乎在任何地方都找不到它。

更准确地说,下一个简单的片段

import pandas as pd
import h2o

data = [['2015-01-01', '2490.925806' , '-0.41'],
        ['2015-01-02', '2412.623113' , '-0.48'],
        ['2015-01-03', '2365.611276' , '-0.55']]
df = pd.DataFrame(data, columns=["time", "base", "target"]).set_index("time", drop=True)

h2o.init(nthreads=-1)
estimator = h2o.estimators.H2OXGBoostEstimator()
training_frame = h2o.H2OFrame(df) 
estimator.train(["base"], "target", training_frame)

给了我错误:

H2OResponseError: Server error water.exceptions.H2ONotFoundArgumentException:
  Error: POST /3/ModelBuilders/xgboost not found
  Request: POST /3/ModelBuilders/xgboost
    data: {'training_frame': 'Key_Frame__upload_893634781f588299bbd20d51c98d43a9.hex', 'nfolds': '0', 'keep_cross_validation_models': 'True', 'keep_cross_validation_predictions': 'False', 'keep_cross_validation_fold_assignment': 'False', 'score_each_iteration': 'False', 'fold_assignment': 'auto', 'response_column': 'target', 'ignore_const_cols': 'True', 'stopping_rounds': '0', 'stopping_metric': 'auto', 'stopping_tolerance': '0.001', 'max_runtime_secs': '0.0', 'seed': '-1', 'distribution': 'auto', 'tweedie_power': '1.5', 'categorical_encoding': 'auto', 'quiet_mode': 'True', 'ntrees': '50', 'max_depth': '6', 'min_rows': '1.0', 'min_child_weight': '1.0', 'learn_rate': '0.3', 'eta': '0.3', 'sample_rate': '1.0', 'subsample': '1.0', 'col_sample_rate': '1.0', 'colsample_bylevel': '1.0', 'col_sample_rate_per_tree': '1.0', 'colsample_bytree': '1.0', 'colsample_bynode': '1.0', 'max_abs_leafnode_pred': '0.0', 'max_delta_step': '0.0', 'score_tree_interval': '0', 'min_split_improvement': '0.0', 'gamma': '0.0', 'nthread': '-1', 'build_tree_one_node': 'False', 'calibrate_model': 'False', 'max_bins': '256', 'max_leaves': '0', 'sample_type': 'uniform', 'normalize_type': 'tree', 'rate_drop': '0.0', 'one_drop': 'False', 'skip_drop': '0.0', 'tree_method': 'auto', 'grow_policy': 'depthwise', 'booster': 'gbtree', 'reg_lambda': '1.0', 'reg_alpha': '0.0', 'dmatrix_type': 'auto', 'backend': 'auto', 'gainslift_bins': '-1', 'auc_type': 'auto', 'scale_pos_weight': '1.0'}

有关我的发行版的更多信息:

  • 操作系统:Monterey 12.3
  • 处理器:Apple M1
  • Python:3.9.10
  • H2O:3.36.0.3

我怀疑Apple M1是错误的原因,但是真的是这样吗?

I am currently trying to use H2O from Python, and I encounter some problems on my Mac OS with XGBoost.
It seems like H2O does not find it anywhere.

More precisely, the next simple snippet

import pandas as pd
import h2o

data = [['2015-01-01', '2490.925806' , '-0.41'],
        ['2015-01-02', '2412.623113' , '-0.48'],
        ['2015-01-03', '2365.611276' , '-0.55']]
df = pd.DataFrame(data, columns=["time", "base", "target"]).set_index("time", drop=True)

h2o.init(nthreads=-1)
estimator = h2o.estimators.H2OXGBoostEstimator()
training_frame = h2o.H2OFrame(df) 
estimator.train(["base"], "target", training_frame)

gives me the error :

H2OResponseError: Server error water.exceptions.H2ONotFoundArgumentException:
  Error: POST /3/ModelBuilders/xgboost not found
  Request: POST /3/ModelBuilders/xgboost
    data: {'training_frame': 'Key_Frame__upload_893634781f588299bbd20d51c98d43a9.hex', 'nfolds': '0', 'keep_cross_validation_models': 'True', 'keep_cross_validation_predictions': 'False', 'keep_cross_validation_fold_assignment': 'False', 'score_each_iteration': 'False', 'fold_assignment': 'auto', 'response_column': 'target', 'ignore_const_cols': 'True', 'stopping_rounds': '0', 'stopping_metric': 'auto', 'stopping_tolerance': '0.001', 'max_runtime_secs': '0.0', 'seed': '-1', 'distribution': 'auto', 'tweedie_power': '1.5', 'categorical_encoding': 'auto', 'quiet_mode': 'True', 'ntrees': '50', 'max_depth': '6', 'min_rows': '1.0', 'min_child_weight': '1.0', 'learn_rate': '0.3', 'eta': '0.3', 'sample_rate': '1.0', 'subsample': '1.0', 'col_sample_rate': '1.0', 'colsample_bylevel': '1.0', 'col_sample_rate_per_tree': '1.0', 'colsample_bytree': '1.0', 'colsample_bynode': '1.0', 'max_abs_leafnode_pred': '0.0', 'max_delta_step': '0.0', 'score_tree_interval': '0', 'min_split_improvement': '0.0', 'gamma': '0.0', 'nthread': '-1', 'build_tree_one_node': 'False', 'calibrate_model': 'False', 'max_bins': '256', 'max_leaves': '0', 'sample_type': 'uniform', 'normalize_type': 'tree', 'rate_drop': '0.0', 'one_drop': 'False', 'skip_drop': '0.0', 'tree_method': 'auto', 'grow_policy': 'depthwise', 'booster': 'gbtree', 'reg_lambda': '1.0', 'reg_alpha': '0.0', 'dmatrix_type': 'auto', 'backend': 'auto', 'gainslift_bins': '-1', 'auc_type': 'auto', 'scale_pos_weight': '1.0'}

For more information about my distribution:

  • OS: Monterey 12.3
  • Processor: Apple M1
  • Python: 3.9.10
  • H2O: 3.36.0.3

I suspect Apple M1 to be the cause of the error, but is that really the case ?

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亣腦蒛氧 2025-01-22 05:13:38

抱歉,Apple M1 处理器尚不支持 XGBoost。

https://h2oai.atlassian.net/browse/PUBDEV-8482

I am sorry, the XGBoost is not supported on Apple M1 processor yet.

https://h2oai.atlassian.net/browse/PUBDEV-8482

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