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For training and tuning, you provide the train_features.csv file
to the container through the input channel when you call the .fit() method. The file is downloaded from S3 and put into the /opt/ml/input/data/train/train_features.csv
location. After training is completed, only /opt/ml/model will be exported to S3 as model artificats.
During model deployment, a brand new host is provisioned and model artifacts are downloaded to /opt/ml/model
. However, your train_features.csv file
will not be available to the host because it does not know about it. You will need to get it from S3 and put in the expected location /opt/ml/input/data/train/train_features.csv
. You can use an inference.py
script to write a function that downloads the file from S3 before your model is loaded. Please have a look at this example for XGBoost.
Hope it helps.
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