mirror of
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synced 2024-12-26 08:44:18 +00:00
Update to newer Version
This commit is contained in:
Patrick Jentsch
parent
5bd0feda5c
commit
42583fea46
@ -9,36 +9,68 @@ variables:
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stages:
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- build
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- push
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- clean
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before_script:
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- docker login -u gitlab-ci-token -p $CI_JOB_TOKEN $CI_REGISTRY
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.docker_setup:
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before_script:
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- docker login -u gitlab-ci-token -p $CI_JOB_TOKEN $CI_REGISTRY
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Build:
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.reg_setup:
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before_script:
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- apk add --no-cache curl
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- curl --fail --show-error --location "https://github.com/genuinetools/reg/releases/download/v$REG_VERSION/reg-linux-amd64" --output /usr/local/bin/reg
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- echo "$REG_SHA256 /usr/local/bin/reg" | sha256sum -c -
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- chmod a+x /usr/local/bin/reg
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variables:
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REG_SHA256: ade837fc5224acd8c34732bf54a94f579b47851cc6a7fd5899a98386b782e228
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REG_VERSION: 0.16.1
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build_image:
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extends: .docker_setup
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script:
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- docker build --pull -t $CI_REGISTRY_IMAGE:tmp .
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- docker push $CI_REGISTRY_IMAGE:tmp
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- docker build -t $INTERMEDIATE_IMAGE_TAG .
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- docker push $INTERMEDIATE_IMAGE_TAG
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stage: build
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tags:
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- docker
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- docker
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variables:
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INTERMEDIATE_IMAGE_TAG: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
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Push latest:
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push_master:
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extends:
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- .docker_setup
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- .reg_setup
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only:
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- master
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script:
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- docker pull $CI_REGISTRY_IMAGE:tmp
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- docker tag $CI_REGISTRY_IMAGE:tmp $CI_REGISTRY_IMAGE:latest
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- docker push $CI_REGISTRY_IMAGE:latest
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- docker pull $INTERMEDIATE_IMAGE_TAG
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- /usr/local/bin/reg rm -d --auth-url $CI_REGISTRY -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $INTERMEDIATE_IMAGE_TAG
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- docker tag $INTERMEDIATE_IMAGE_TAG $IMAGE_TAG
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- docker push $IMAGE_TAG
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stage: push
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tags:
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- docker
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- docker
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variables:
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IMAGE_TAG: $CI_REGISTRY_IMAGE:latest
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INTERMEDIATE_IMAGE_TAG: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
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Push tag:
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push_other:
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extends:
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- .docker_setup
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- .reg_setup
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except:
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- master
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only:
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- branches
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- tags
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script:
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- docker pull $CI_REGISTRY_IMAGE:tmp
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- docker tag $CI_REGISTRY_IMAGE:tmp $CI_REGISTRY_IMAGE:$CI_COMMIT_REF_NAME
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- docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_REF_NAME
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- docker pull $INTERMEDIATE_IMAGE_TAG
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- /usr/local/bin/reg rm -d --auth-url $CI_REGISTRY -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $INTERMEDIATE_IMAGE_TAG
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- docker tag $INTERMEDIATE_IMAGE_TAG $IMAGE_TAG
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- docker push $IMAGE_TAG
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stage: push
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tags:
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- docker
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- docker
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variables:
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IMAGE_TAG: $CI_REGISTRY_IMAGE:CI_COMMIT_REF_NAME
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INTERMEDIATE_IMAGE_TAG: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
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66
Dockerfile
66
Dockerfile
@ -1,52 +1,54 @@
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FROM debian:10-slim
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LABEL maintainer="inf_sfb1288@lists.uni-bielefeld.de"
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LABEL authors="Patrick Jentsch <p.jentsch@uni-bielefeld.de>, Stephan Porada <sporada@uni-bielefeld.de>"
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ENV LANG=C.UTF-8
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RUN apt-get update \
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RUN apt-get update
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## Install pyFlow ##
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ENV PYFLOW_RELEASE=1.1.20
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ADD "https://github.com/Illumina/pyflow/releases/download/v${PYFLOW_RELEASE}/pyflow-${PYFLOW_RELEASE}.tar.gz" .
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RUN tar -xzf "pyflow-${PYFLOW_RELEASE}.tar.gz" \
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&& cd "pyflow-${PYFLOW_RELEASE}" \
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&& apt-get install -y --no-install-recommends \
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python2.7 \
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&& python2.7 setup.py build install \
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&& cd .. \
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&& rm -r "pyflow-${PYFLOW_RELEASE}" "pyflow-${PYFLOW_RELEASE}.tar.gz"
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## Install Pipeline ##
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ENV SPACY_VERSION=2.3.2
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ENV SPACY_MODELS_VERSION=2.3.0
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RUN apt-get install -y --no-install-recommends \
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python3.7 \
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python3-pip \
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zip \
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&& pip3 install \
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chardet
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ENV PYFLOW_VERSION=1.1.20
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ADD "https://github.com/Illumina/pyflow/releases/download/v${PYFLOW_VERSION}/pyflow-${PYFLOW_VERSION}.tar.gz" .
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RUN tar -xzf "pyflow-${PYFLOW_VERSION}.tar.gz" \
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&& cd "pyflow-${PYFLOW_VERSION}" \
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&& python2.7 setup.py build install \
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&& cd .. \
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&& rm -rf \
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"pyflow-${PYFLOW_VERSION}" \
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"pyflow-${PYFLOW_VERSION}.tar.gz"
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ENV SPACY_VERSION=2.2.4
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ENV SPACY_MODELS_VERSION=2.2.5
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RUN pip3 install setuptools wheel && pip3 install "spacy==${SPACY_VERSION}" \
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&& python3 -m spacy download "de_core_news_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "el_core_news_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "en_core_web_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "es_core_news_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "fr_core_news_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "it_core_news_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "nl_core_news_sm-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "pt_core_news_sm-${SPACY_MODELS_VERSION}" --direct
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RUN rm -rf /var/lib/apt/lists/*
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chardet \
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setuptools \
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wheel \
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&& pip3 install "spacy==${SPACY_VERSION}" \
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&& python3 -m spacy download "de_core_news_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "el_core_news_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "en_core_web_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "es_core_news_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "fr_core_news_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "it_core_news_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "nl_core_news_lg-${SPACY_MODELS_VERSION}" --direct \
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&& python3 -m spacy download "pt_core_news_lg-${SPACY_MODELS_VERSION}" --direct
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COPY nlp /usr/local/bin
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COPY spacy-nlp /usr/local/bin
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## Cleanup ##
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RUN rm -r /var/lib/apt/lists/*
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ENTRYPOINT ["nlp"]
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CMD ["--help"]
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80
nlp
80
nlp
@ -5,10 +5,10 @@
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nlp
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Usage: For usage instructions run with option --help
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Author: Patrick Jentsch <p.jentsch@uni-bielefeld.de>
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Authors: Patrick Jentsch <p.jentsch@uni-bielefeld.de
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Stephan Porada <sporada@uni-bielefeld.de>
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"""
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from argparse import ArgumentParser
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from pyflow import WorkflowRunner
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import multiprocessing
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@ -34,19 +34,31 @@ def parse_args():
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parser.add_argument('-o', '--output-directory',
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help='Output directory',
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required=True)
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parser.add_argument('-l', '--language', choices=SPACY_MODELS.keys(),
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parser.add_argument('-l', '--language',
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choices=SPACY_MODELS.keys(),
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required=True)
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parser.add_argument('--check-encoding', action='store_true')
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parser.add_argument('--log-dir')
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parser.add_argument('--n-cores',
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default=min(4, multiprocessing.cpu_count()),
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help='total number of cores available', type=int)
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parser.add_argument('--zip',
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help='Zips everything into one archive.')
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parser.add_argument('--zip', help='Zips everything into one archive.')
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return parser.parse_args()
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class NLPPipelineJob:
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"""An NLP pipeline job class
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Each input file of the pipeline is represented as an NLP pipeline job,
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which holds all necessary information for the pipeline to process it.
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Arguments:
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file -- Path to the file
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output_dir -- Path to a directory, where job results a stored
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intermediate_dir -- Path to a directory, where intermediate files are
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stored.
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"""
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def __init__(self, file, output_dir):
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self.file = file
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self.name = os.path.basename(file).rsplit('.', 1)[0]
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@ -54,13 +66,23 @@ class NLPPipelineJob:
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class NLPPipeline(WorkflowRunner):
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def __init__(self, check_encoding, jobs, lang, n_cores, output_dir, zip):
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self.check_encoding = check_encoding
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self.jobs = jobs
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def __init__(self, input_dir, lang, output_dir, check_encoding, n_cores, zip):
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self.input_dir = input_dir
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self.lang = lang
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self.output_dir = output_dir
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self.check_encoding = check_encoding
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self.n_cores = n_cores
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self.output_dir = output_dir
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self.zip = zip
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if zip is None:
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self.zip = zip
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else:
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if zip.lower().endswith('.zip'):
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# Remove .zip file extension if provided
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self.zip = zip[:-4]
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self.zip = self.zip if self.zip else 'output'
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else:
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self.zip = zip
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self.jobs = collect_jobs(self.input_dir, self.output_dir)
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def workflow(self):
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if not self.jobs:
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@ -71,25 +93,24 @@ class NLPPipeline(WorkflowRunner):
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' # setup output directory #
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' ##################################################
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'''
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setup_output_directory_jobs = []
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setup_output_directory_tasks = []
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for i, job in enumerate(self.jobs):
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cmd = 'mkdir'
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cmd += ' -p'
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cmd += ' "{}"'.format(job.output_dir)
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lbl = 'setup_output_directory_-_{}'.format(i)
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setup_output_directory_jobs.append(self.addTask(command=cmd,
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label=lbl))
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task = self.addTask(command=cmd, label=lbl)
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setup_output_directory_tasks.append(task)
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'''
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' ##################################################
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' # nlp #
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' ##################################################
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'''
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nlp_jobs = []
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nlp_tasks = []
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n_cores = min(self.n_cores, max(1, int(self.n_cores / len(self.jobs))))
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for i, job in enumerate(self.jobs):
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output_file = os.path.join(job.output_dir,
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'{}.vrt'.format(job.name))
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output_file = os.path.join(job.output_dir, '{}.vrt'.format(job.name)) # noqa
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cmd = 'spacy-nlp'
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cmd += ' -i "{}"'.format(job.file)
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cmd += ' -l "{}"'.format(self.lang)
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@ -98,36 +119,29 @@ class NLPPipeline(WorkflowRunner):
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cmd += ' --check-encoding'
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deps = 'setup_output_directory_-_{}'.format(i)
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lbl = 'nlp_-_{}'.format(i)
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nlp_jobs.append(self.addTask(command=cmd,
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dependencies=deps,
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label=lbl,
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nCores=n_cores))
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task = self.addTask(command=cmd, dependencies=deps, label=lbl, nCores=n_cores) # noqa
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nlp_tasks.append(task)
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'''
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' ##################################################
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' # zip creation #
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' ##################################################
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'''
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zip_creation_jobs = []
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zip_creation_tasks = []
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if self.zip is not None:
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# Remove .zip file extension if provided
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if self.zip.endswith('.zip'):
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self.zip = self.zip[:-4]
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self.zip = self.zip if self.zip else 'output'
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cmd = 'cd "{}"'.format(self.output_dir)
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cmd += ' && '
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cmd += 'zip'
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cmd += ' -r'
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cmd += ' "{}".zip .'.format(self.zip)
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cmd += ' "{}.zip" .'.format(self.zip)
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cmd += ' -x "pyflow.data*"'
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cmd += ' -i "*.vrt"'
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cmd += ' && '
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cmd += 'cd -'
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deps = nlp_jobs
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deps = nlp_tasks
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lbl = 'zip_creation'
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zip_creation_jobs.append(self.addTask(command=cmd,
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dependencies=deps,
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label=lbl))
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task = self.addTask(command=cmd, dependencies=deps, label=lbl)
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zip_creation_tasks.append(task)
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|
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def collect_jobs(input_dir, output_dir):
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@ -136,7 +150,7 @@ def collect_jobs(input_dir, output_dir):
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if os.path.isdir(os.path.join(input_dir, file)):
|
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jobs += collect_jobs(os.path.join(input_dir, file),
|
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os.path.join(output_dir, file))
|
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elif file.endswith('.txt'):
|
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elif file.lower().endswith('.txt'):
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jobs.append(NLPPipelineJob(os.path.join(input_dir, file),
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os.path.join(output_dir, file)))
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return jobs
|
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@ -144,9 +158,9 @@ def collect_jobs(input_dir, output_dir):
|
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|
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def main():
|
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args = parse_args()
|
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jobs = collect_jobs(args.input_directory, args.output_directory)
|
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nlp_pipeline = NLPPipeline(args.check_encoding, jobs, args.language,
|
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args.n_cores, args.output_directory, args.zip)
|
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nlp_pipeline = NLPPipeline(args.input_directory, args.language,
|
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args.output_directory, args.check_encoding,
|
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args.n_cores, args.zip)
|
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retval = nlp_pipeline.run(
|
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dataDirRoot=(args.log_dir or args.output_directory),
|
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nCores=args.n_cores
|
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|
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46
spacy-nlp
46
spacy-nlp
@ -4,29 +4,28 @@
|
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from argparse import ArgumentParser
|
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from xml.sax.saxutils import escape
|
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import chardet
|
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import hashlib
|
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import os
|
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import spacy
|
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import textwrap
|
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import hashlib
|
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|
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|
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SPACY_MODELS = {'de': 'de_core_news_sm',
|
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'el': 'el_core_news_sm',
|
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'en': 'en_core_web_sm',
|
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'es': 'es_core_news_sm',
|
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'fr': 'fr_core_news_sm',
|
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'it': 'it_core_news_sm',
|
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'nl': 'nl_core_news_sm',
|
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'pt': 'pt_core_news_sm'}
|
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|
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SPACY_MODELS = {'de': 'de_core_news_lg',
|
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'el': 'el_core_news_lg',
|
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'en': 'en_core_web_lg',
|
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'es': 'es_core_news_lg',
|
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'fr': 'fr_core_news_lg',
|
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'it': 'it_core_news_lg',
|
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'nl': 'nl_core_news_lg',
|
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'pt': 'pt_core_news_lg'}
|
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SPACY_MODELS_VERSION = os.environ.get('SPACY_MODELS_VERSION')
|
||||
SPACY_VERSION = os.environ.get('SPACY_VERSION')
|
||||
|
||||
# Parse the given arguments
|
||||
parser = ArgumentParser(description=('Tag a text file with spaCy and save it '
|
||||
'as a verticalized text file.'))
|
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parser.add_argument('-i', '--input', metavar='txt-sourcefile', required=True)
|
||||
parser.add_argument('-o', '--output', metavar='vrt-destfile', required=True)
|
||||
parser.add_argument('-l', '--language',
|
||||
choices=SPACY_MODELS.keys(),
|
||||
required=True)
|
||||
parser.add_argument('-l', '--language', choices=SPACY_MODELS.keys(), required=True) # noqa
|
||||
parser.add_argument('--check-encoding', action='store_true')
|
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args = parser.parse_args()
|
||||
|
||||
@ -43,10 +42,10 @@ else:
|
||||
|
||||
# hashing in chunks to avoid full RAM with huge files.
|
||||
with open(args.input, 'rb') as input_file:
|
||||
md5_hash = hashlib.md5()
|
||||
for chunk in iter(lambda: input_file.read(128 * md5_hash.block_size), b''):
|
||||
md5_hash.update(chunk)
|
||||
md5_hash = md5_hash.hexdigest()
|
||||
source_md5 = hashlib.md5()
|
||||
for chunk in iter(lambda: input_file.read(128 * source_md5.block_size), b''):
|
||||
source_md5.update(chunk)
|
||||
source_md5 = source_md5.hexdigest()
|
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|
||||
# Load the text contents from the input file
|
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with open(args.input, encoding=encoding) as input_file:
|
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@ -60,7 +59,8 @@ with open(args.input, encoding=encoding) as input_file:
|
||||
|
||||
|
||||
# Setup the spaCy toolkit by loading the chosen language model
|
||||
nlp = spacy.load(SPACY_MODELS[args.language])
|
||||
model = SPACY_MODELS[args.language]
|
||||
nlp = spacy.load(model)
|
||||
|
||||
|
||||
# Create the output file in verticalized text format
|
||||
@ -70,11 +70,9 @@ output_file_stand_off_filename = args.output.replace('.vrt', '.stand-off.vrt')
|
||||
common_xml = ('<?xml version="1.0" encoding="UTF-8" standalone="yes"?>\n'
|
||||
+ '<corpus>\n'
|
||||
+ '<text>\n'
|
||||
+ '<nlp name="spaCy"\n'
|
||||
+ ' version="{}"\n'.format(spacy.__version__)
|
||||
+ ' model="{}"\n'.format(SPACY_MODELS[args.language])
|
||||
+ ' model_version="{}"\n'.format(nlp.meta['version'])
|
||||
+ ' md5_hash_of_input="{}" />\n'.format(md5_hash))
|
||||
+ '<nlp name="spaCy:{}"\n'.format(SPACY_VERSION)
|
||||
+ ' model="{}:{}"\n'.format(model, SPACY_MODELS_VERSION)
|
||||
+ ' source-md5="{}" />\n'.format(source_md5))
|
||||
|
||||
with open(output_file_original_filename, 'w+') as output_file_original, \
|
||||
open(output_file_stand_off_filename, 'w+') as output_file_stand_off:
|
||||
|
||||
Loading…
Reference in New Issue
Block a user