<jupyter_start><jupyter_text>아래와 같이 ENTRYPOINT 지정하면 해당 docker가 싫행시에 해당 스크립트를 무조건 실행 함.```ENTRYPOINT ["python", "pca_byoc_train.py"]```<jupyter_code>%%writefile docker/Dockerfile

FROM 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:0.20.0-cpu-py3
    
# install python package
RUN pip install joblib


ENV PYTHONUNBUFFERED=TRUE
ENV PYTHONDONTWRITEBYTECODE=TRUE

ENV PATH="/opt/ml/code:${PATH}"

# Copy training code
COPY code/* /opt/ml/code/
 
WORKDIR /opt/ml/code

# ENTRYPOINT ["python", "pca_byoc_train.py"]
# In order to use SageMaker Env varaibles, use the statement below
ENV SAGEMAKER_PROGRAM pca_byoc_train.py<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11607142857142858, 'fraction_numerical': 0.026785714285714284, 'mean_word_length': 5.598039215686274, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '215679', 'license': 'MIT', 'n_tokens_mistral': 309, 'n_tokens_neox': 320, 'n_words': 55, 'path': 'working/ref-Dockerfile.ipynb', 'repo_name': 'gonsoomoon-ml/churn-prediction-workshop2', 'size': '672'}