无法打开腌制Sagemaker XGBoost型号

Question

我正试图打开我在AWS Sagemaker中创建的一个经过腌制的XGBoost模型，以查看模型中的功能重要性。我正试着按照这篇文章中的答案去做。然而，我得到了一个如下所示的错误。当我尝试调用Booster.save_model时，我得到一个错误，说'Estimator' object has no attribute 'save_model'。我该如何解决此问题？

# Build initial model
sess = sagemaker.Session()
s3_input_train = sagemaker.s3_input(s3_data='s3://{}/{}/train/'.format(bucket, prefix), content_type='csv')
xgb_cont = get_image_uri(region, 'xgboost', repo_version='0.90-1')
xgb = sagemaker.estimator.Estimator(xgb_cont, role, train_instance_count=1, train_instance_type='ml.m4.4xlarge',
output_path='s3://{}/{}'.format(bucket, prefix), sagemaker_session=sess)
xgb.set_hyperparameters(eval_metric='rmse', objective='reg:squarederror', num_round=100)
ts = strftime("%Y-%m-%d-%H-%M-%S", gmtime())
xgb_name = 'xgb-initial-' + ts
xgb.set_hyperparameters(eta=0.1, alpha=0.5, max_depth=10)
xgb.fit({'train': s3_input_train}, job_name=xgb_name)
# Load model to get feature importances
model_path = 's3://{}/{}//output/model.tar.gz'.format(bucket, prefix, xgb_name)
fs = s3fs.S3FileSystem()
with fs.open(model_path, 'rb') as f:
with tarfile.open(fileobj=f, mode='r') as tar_f:
with tar_f.extractfile('xgboost-model') as extracted_f:
model = pickle.load(extracted_f)
XGBoostError: [19:16:42] /workspace/src/learner.cc:682: Check failed: header == serialisation_header_: 
If you are loading a serialized model (like pickle in Python) generated by older
XGBoost, please export the model by calling `Booster.save_model` from that version
first, then load it back in current version.  There's a simple script for helping
the process. See:
https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html
for reference to the script, and more details about differences between saving model and
serializing.

Answer 1

您在笔记本电脑中使用的是哪个版本的XGBoost？XGBoost 1.0中的模型格式发生了更改。看见https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html.短版本：如果你在笔记本中使用1.0，你就不能加载一个腌制的模型。

下面是一个在脚本模式下使用XGBoost的工作示例(它比内置的算法灵活得多(：

• https://gitlab.com/juliensimon/dlnotebooks/-/blob/master/sagemaker/09-XGBoost-script-mode.ipynb
• https://gitlab.com/juliensimon/dlnotebooks/-/blob/master/sagemaker/xgb.py

Answer 2

如果您绝对需要使用Pickle加载XGBoost模型，并且您遇到了与最新版本XGBoost的兼容性问题，降级到特定版本可能是一个可行的解决方案：

pip uninstall xgboost
pip install xgboost==0.90

然后以下将正常工作

import pickle
with open("model.dat", "rb") as file:
loaded_model = pickle.load(file)