如何通过joblib向/从S3存储桶写入/加载机器学习模型? [英] How to write/load machine learning model to/from S3 bucket through joblib?
问题描述
我有一个 ml 模型,我想将其保存在 S3 存储桶中.
I have an ml model which I want to save on an S3 bucket.
from lightgbm.sklearn import LGBMClassifier
# Initialize model
mdl_lightgbm = LGBMClassifier(boosting_type='rf', objective='binary')
# Fit data
mdl_lightgbm.fit(X,Y)
# Save model to dictionary
mdl_dict = {'mdl_fitted':mdl_lightgbm}
出于某些原因,我将拟合模型存储在字典中.这个想法是通过 joblib 向/从 S3 存储桶转储/加载模型.
For some reasons, I'm storing the fitted model in a dictionary. The idea is to dump/load the model through joblib to/from an S3 bucket.
推荐答案
将模型保存到 S3
基于这个问题的想法,下面的函数让你将模型保存到s3桶或通过joblib本地保存:
Save model to S3
Based on the idea of this question, the following function let you save the model to an s3 bucket or locally through joblib:
import boto3
from io import BytesIO
def write_joblib(file, path):
'''
Function to write a joblib file to an s3 bucket or local directory.
Arguments:
* file: The file that you want to save
* path: an s3 bucket or local directory path.
'''
# Path is an s3 bucket
if path[:5] == 's3://':
s3_bucket, s3_key = path.split('/')[2], path.split('/')[3:]
s3_key = '/'.join(s3_key)
with BytesIO() as f:
joblib.dump(file, f)
f.seek(0)
boto3.client("s3").upload_fileobj(Bucket=s3_bucket, Key=s3_key, Fileobj=f)
# Path is a local directory
else:
with open(path, 'wb') as f:
joblib.dump(file, f)
在您的示例中,如果您想将模型保存到 s3 存储桶,只需输入
In your example, if you want to save your model to an s3 bucket, just type
write_joblib(mdl_dict, 's3://bucket_name/mdl_dict.joblib')
此外,遵循这个问题的想法,下面的函数让你从s3存储桶或本地文件加载模型
Additionaly, following the idea on this question, the following function let's you load the model from an s3 bucket or a local file
def read_joblib(path):
'''
Function to load a joblib file from an s3 bucket or local directory.
Arguments:
* path: an s3 bucket or local directory path where the file is stored
Outputs:
* file: Joblib file loaded
'''
# Path is an s3 bucket
if path[:5] == 's3://':
s3_bucket, s3_key = path.split('/')[2], path.split('/')[3:]
s3_key = '/'.join(s3_key)
with BytesIO() as f:
boto3.client("s3").download_fileobj(Bucket=s3_bucket, Key=s3_key, Fileobj=f)
f.seek(0)
file = joblib.load(f)
# Path is a local directory
else:
with open(path, 'rb') as f:
file = joblib.load(f)
return file
在您的情况下,要从同一个 s3 存储桶加载文件,请使用以下代码行
In your case, to load the file from the same s3 bucket use the following line of code
mdl_lightgbm = read_joblib('s3://bucket_name/mdl_dict.joblib')
mdl_lightgbm = mdl_lightgbm['mdl_fitted']
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