Question

看到错误

TypeError：+不支持的操作数类型：“ NoneType”和“ unicode”

当尝试使用gridsearch在h2o中训练模型并且无法解释原因时。

以下是在错误发生之前打印的输出：

drf Grid Build progress: |████████████████████████████████████████████████| 100%
Errors/Warnings building gridsearch model

Hyper-parameter: col_sample_rate_per_tree, 0.75
Hyper-parameter: max_depth, 5
Hyper-parameter: min_rows, 4096.0
Hyper-parameter: min_split_improvement, 1e-08
Hyper-parameter: mtries, 8
Hyper-parameter: nbins, 8
Hyper-parameter: nbins_cats, 64
Hyper-parameter: ntrees, 96
Hyper-parameter: sample_rate, 0.6320000291
failure_details: None
failure_stack_traces: java.lang.NullPointerException
    at hex.tree.SharedTree.init(SharedTree.java:164)
    at hex.tree.drf.DRF.init(DRF.java:53)
    at hex.tree.SharedTree$Driver.computeImpl(SharedTree.java:207)
    at hex.ModelBuilder$Driver.compute2(ModelBuilder.java:222)
    at hex.ModelBuilder.trainModelNested(ModelBuilder.java:348)
    at hex.ModelBuilder$TrainModelNestedRunnable.run(ModelBuilder.java:383)
    at water.H2O.runOnH2ONode(H2O.java:1304)
    at water.H2O.runOnH2ONode(H2O.java:1297)
    at hex.ModelBuilder.trainModelNested(ModelBuilder.java:364)
    at hex.grid.GridSearch.buildModel(GridSearch.java:343)
    at hex.grid.GridSearch.gridSearch(GridSearch.java:220)
    at hex.grid.GridSearch.access$000(GridSearch.java:71)
    at hex.grid.GridSearch$1.compute2(GridSearch.java:138)
    at water.H2O$H2OCountedCompleter.compute(H2O.java:1416)
    at jsr166y.CountedCompleter.exec(CountedCompleter.java:468)
    at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263)
    at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:974)
    at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477)
    at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)

以及用于创建gridsearch对象的代码

model = h2o.h2o.H2ORandomForestEstimator(
                response_column=configs['RESPONSE'],
                keep_cross_validation_models=False,
                keep_cross_validation_predictions=False
            )

random_forest_grid = h2o.h2o.H2OGridSearch(model=model, 
                     hyper_params=configs['HYPERPARAMETER_RANGES'], 
                     search_criteria=configs['SEARCH_CRITERIA'])
.
.
.

max_train_time_hrs = 8
# here is where the ERROR is thrown
random_forest_grid.train(x=training_features, y=training_response,
                         weights_column='weight',
                         training_frame=train_u, validation_frame=test_u,
                         max_runtime_secs=max_train_time_hrs * 60 * 60)

其中引用的configs是像...这样的字典。

configs = {
.
.
.
 'HYPERPARAMETER_RANGES': {
        'ntrees': [32, 64, 96, 128],  # default 50
        'nbins_cats': [16, 32, 64, 128, 512, 1024],  # default is 1024
        'nbins': [8, 13, 21, 34],  # default is 20
        'max_depth': [5, 8, 13],  # default is 20
        'mtries': [-1, 5, 8, 13],  # default is -1 for the square root of number of features
        'min_split_improvement': [1 * 10 ** -8,
                                  1 * 10 ** -5,
                                  1 * 10 ** -3],
        'min_rows': [16, 64, 256, 1024, 4096],  # this option specifies the number of observations for a split
        'col_sample_rate_per_tree': [0.75, 0.9, 1],  # default is 1
        'sample_rate': [0.5, 0.6320000291, 0.75]  # default is 0.6320000291
},
'SEARCH_CRITERIA': {
    'strategy': 'RandomDiscrete',
    'max_models': 24,
    'seed': 64,
    'stopping_metric': 'AUTO',  # log-loss
 }

}

请注意，gridsearch适用于我正在训练的其他一些DRF模型（具有完全相同的gridsearch超参数和标准范围），并且似乎找不到这些工作版本与此错误版本之间的任何显着差异。为什么可能会在h2o中引发此类错误？任何理论或进一步的调试建议将不胜感激。

Answer 1

通过检查h2o Flow UI中的日志找到了错误的原因（我通常会说这是一个很好的h2o调试技巧（因为看起来有些错误只在此打印而不是标准错误输出））。

06-20 12:39:02.188 172.18.4.64:54321     27694  FJ-1-11   INFO: Building H2O DRF model with these parameters:
06-20 12:39:02.188 172.18.4.64:54321     27694  FJ-1-11   INFO: {"_train":{"name":"py_9_sid_827e","type":"Key"},"_valid":{"name":"py_10_sid_827e","type":"Key"},"_nfolds":0,"_keep_cross_validation_models":false,"_keep_cross_validation_predictions":false,"_keep_cross_validation_fold_assignment":false,"_parallelize_cross_validation":true,"_auto_rebalance":true,"_seed":111,"_fold_assignment":"AUTO","_categorical_encoding":"AUTO","_max_categorical_levels":10,"_distribution":"AUTO","_tweedie_power":1.5,"_quantile_alpha":0.5,"_huber_alpha":0.9,"_ignored_columns":null,"_ignore_const_cols":true,"_weights_column":"weight","_offset_column":null,"_fold_column":null,"_check_constant_response":true,"_is_cv_model":false,"_score_each_iteration":false,"_max_runtime_secs":28800.0,"_stopping_rounds":0,"_stopping_metric":"AUTO","_stopping_tolerance":0.001,"_response_column":"DENIAL","_balance_classes":false,"_max_after_balance_size":5.0,"_class_sampling_factors":null,"_max_confusion_matrix_size":20,"_checkpoint":null,"_pretrained_autoencoder":null,"_custom_metric_func":null,"_export_checkpoints_dir":null,"_ntrees":96,"_max_depth":13,"_min_rows":64.0,"_nbins":13,"_nbins_cats":16,"_min_split_improvement":1.0E-5,"_histogram_type":"AUTO","_r2_stopping":1.7976931348623157E308,"_nbins_top_level":1024,"_build_tree_one_node":false,"_score_tree_interval":0,"_initial_score_interval":4000,"_score_interval":4000,"_sample_rate":0.6320000291,"_sample_rate_per_class":null,"_calibrate_model":false,"_calibration_frame":null,"_col_sample_rate_change_per_level":1.0,"_col_sample_rate_per_tree":1.0,"_binomial_double_trees":true,"_mtries":5}
06-20 12:39:02.189 172.18.4.64:54321     27694  FJ-1-11   ERRR: _weights_column: Weights column 'weight' not found in the training frame
06-20 12:39:02.189 172.18.4.64:54321     27694  FJ-1-11   ERRR: _weights_column: Weights column 'weight' not found in the training frame

事实证明，该问题是由于以下事实造成的：在所使用的H2OFrame中，在网格搜索中分配为用作weights_column参数的列实际上并不存在。

将尝试减少问题的发帖范围，以便对可能仅根据标题找到此问题的其他人更加敏感（因为控制台中显示的标准错误没有表明具体问题）。

h2o gridsearch“ TypeError：不支持的操作数”错误

1 个答案: