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@@ -0,0 +1 @@ +/rouge_score-0.1.2.tar.gz diff --git a/python-rouge-score.spec b/python-rouge-score.spec new file mode 100644 index 0000000..ff1fca1 --- /dev/null +++ b/python-rouge-score.spec @@ -0,0 +1,369 @@ +%global _empty_manifest_terminate_build 0 +Name: python-rouge-score +Version: 0.1.2 +Release: 1 +Summary: Pure python implementation of ROUGE-1.5.5. +License: Apache Software License +URL: https://github.com/google-research/google-research/tree/master/rouge +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/e2/c5/9136736c37022a6ad27fea38f3111eb8f02fe75d067f9a985cc358653102/rouge_score-0.1.2.tar.gz +BuildArch: noarch + + +%description +# Python ROUGE Implementation + +## Overview + +This is a native python implementation of ROUGE, designed to replicate results +from the original perl package. + +Maintainers may be contacted at rouge-opensource@google.com. + +ROUGE was originally introduced in the paper: + +Lin, Chin-Yew. ROUGE: a Package for Automatic Evaluation of Summaries. In +Proceedings of the Workshop on Text Summarization Branches Out (WAS 2004), +Barcelona, Spain, July 25 - 26, 2004. + +## ROUGE for Python + +There are ROUGE implementations available for Python, however some are not +native python due to their dependency on the perl script, and others provide +differing results when compared with the original implementation. This makes it +difficult to directly compare with known results. + +This package is designed to replicate perl results. It implements: + +* ROUGE-N (N-gram) scoring +* ROUGE-L (Longest Common Subsequence) scoring +* Text normalization +* Bootstrap resampling for confidence interval calculation +* Optional Porter stemming to remove plurals and word suffixes such as (ing, + ion, ment). + +Note that not all options provided by the original perl ROUGE script are +supported, but the subset of options that are implemented should replicate the +original functionality. + +## Stopword removal + +The original ROUGE perl script implemented optional stopword removal (using the +-s parameter). However, there were ~600 stopwords used by ROUGE, borrowed from +another now defunct package. This word list contained many words that may not be +suited to some tasks, such as day and month names and numbers. It also has no +clear license for redistribution. Since we are unable to replicate this +functionality precisely we do not include stopword removal. + +## Two flavors of ROUGE-L +In the ROUGE paper, two flavors of ROUGE are described: + +1. sentence-level: Compute longest common subsequence (LCS) between two pieces of +text. Newlines are ignored. This is called `rougeL` in this package. +2. summary-level: Newlines in the text are interpreted as sentence boundaries, +and the LCS is computed between each pair of reference and candidate sentences, +and something called union-LCS is computed. This is called `rougeLsum` in this +package. This is the ROUGE-L reported in *[Get To The Point: Summarization with +Pointer-Generator Networks](https://arxiv.org/abs/1704.04368)*, for example. +If your references/candidates do not have newline delimiters, you can use the +--split_summaries flag (or optional argument in RougeScorer). + +## How to run + +This package compares target files (containing one example per line) with +prediction files in the same format. It can be launched as follows (from +google-research/): + +```shell +python -m rouge.rouge \ + --target_filepattern=*.targets \ + --prediction_filepattern=*.decodes \ + --output_filename=scores.csv \ + --use_stemmer=true \ + --split_summaries=true +``` + +## Using pip +``` +pip install -r rouge/requirements.txt +pip install rouge-score +``` + +Then in python: + +```python +from rouge_score import rouge_scorer + +scorer = rouge_scorer.RougeScorer(['rouge1', 'rougeL'], use_stemmer=True) +scores = scorer.score('The quick brown fox jumps over the lazy dog', + 'The quick brown dog jumps on the log.') +``` + +## License + +Licensed under the +[Apache 2.0](https://github.com/google-research/google-research/blob/master/LICENSE) +License. + +## Disclaimer + +This is not an official Google product. + + + + +%package -n python3-rouge-score +Summary: Pure python implementation of ROUGE-1.5.5. +Provides: python-rouge-score +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-rouge-score +# Python ROUGE Implementation + +## Overview + +This is a native python implementation of ROUGE, designed to replicate results +from the original perl package. + +Maintainers may be contacted at rouge-opensource@google.com. + +ROUGE was originally introduced in the paper: + +Lin, Chin-Yew. ROUGE: a Package for Automatic Evaluation of Summaries. In +Proceedings of the Workshop on Text Summarization Branches Out (WAS 2004), +Barcelona, Spain, July 25 - 26, 2004. + +## ROUGE for Python + +There are ROUGE implementations available for Python, however some are not +native python due to their dependency on the perl script, and others provide +differing results when compared with the original implementation. This makes it +difficult to directly compare with known results. + +This package is designed to replicate perl results. It implements: + +* ROUGE-N (N-gram) scoring +* ROUGE-L (Longest Common Subsequence) scoring +* Text normalization +* Bootstrap resampling for confidence interval calculation +* Optional Porter stemming to remove plurals and word suffixes such as (ing, + ion, ment). + +Note that not all options provided by the original perl ROUGE script are +supported, but the subset of options that are implemented should replicate the +original functionality. + +## Stopword removal + +The original ROUGE perl script implemented optional stopword removal (using the +-s parameter). However, there were ~600 stopwords used by ROUGE, borrowed from +another now defunct package. This word list contained many words that may not be +suited to some tasks, such as day and month names and numbers. It also has no +clear license for redistribution. Since we are unable to replicate this +functionality precisely we do not include stopword removal. + +## Two flavors of ROUGE-L +In the ROUGE paper, two flavors of ROUGE are described: + +1. sentence-level: Compute longest common subsequence (LCS) between two pieces of +text. Newlines are ignored. This is called `rougeL` in this package. +2. summary-level: Newlines in the text are interpreted as sentence boundaries, +and the LCS is computed between each pair of reference and candidate sentences, +and something called union-LCS is computed. This is called `rougeLsum` in this +package. This is the ROUGE-L reported in *[Get To The Point: Summarization with +Pointer-Generator Networks](https://arxiv.org/abs/1704.04368)*, for example. +If your references/candidates do not have newline delimiters, you can use the +--split_summaries flag (or optional argument in RougeScorer). + +## How to run + +This package compares target files (containing one example per line) with +prediction files in the same format. It can be launched as follows (from +google-research/): + +```shell +python -m rouge.rouge \ + --target_filepattern=*.targets \ + --prediction_filepattern=*.decodes \ + --output_filename=scores.csv \ + --use_stemmer=true \ + --split_summaries=true +``` + +## Using pip +``` +pip install -r rouge/requirements.txt +pip install rouge-score +``` + +Then in python: + +```python +from rouge_score import rouge_scorer + +scorer = rouge_scorer.RougeScorer(['rouge1', 'rougeL'], use_stemmer=True) +scores = scorer.score('The quick brown fox jumps over the lazy dog', + 'The quick brown dog jumps on the log.') +``` + +## License + +Licensed under the +[Apache 2.0](https://github.com/google-research/google-research/blob/master/LICENSE) +License. + +## Disclaimer + +This is not an official Google product. + + + + +%package help +Summary: Development documents and examples for rouge-score +Provides: python3-rouge-score-doc +%description help +# Python ROUGE Implementation + +## Overview + +This is a native python implementation of ROUGE, designed to replicate results +from the original perl package. + +Maintainers may be contacted at rouge-opensource@google.com. + +ROUGE was originally introduced in the paper: + +Lin, Chin-Yew. ROUGE: a Package for Automatic Evaluation of Summaries. In +Proceedings of the Workshop on Text Summarization Branches Out (WAS 2004), +Barcelona, Spain, July 25 - 26, 2004. + +## ROUGE for Python + +There are ROUGE implementations available for Python, however some are not +native python due to their dependency on the perl script, and others provide +differing results when compared with the original implementation. This makes it +difficult to directly compare with known results. + +This package is designed to replicate perl results. It implements: + +* ROUGE-N (N-gram) scoring +* ROUGE-L (Longest Common Subsequence) scoring +* Text normalization +* Bootstrap resampling for confidence interval calculation +* Optional Porter stemming to remove plurals and word suffixes such as (ing, + ion, ment). + +Note that not all options provided by the original perl ROUGE script are +supported, but the subset of options that are implemented should replicate the +original functionality. + +## Stopword removal + +The original ROUGE perl script implemented optional stopword removal (using the +-s parameter). However, there were ~600 stopwords used by ROUGE, borrowed from +another now defunct package. This word list contained many words that may not be +suited to some tasks, such as day and month names and numbers. It also has no +clear license for redistribution. Since we are unable to replicate this +functionality precisely we do not include stopword removal. + +## Two flavors of ROUGE-L +In the ROUGE paper, two flavors of ROUGE are described: + +1. sentence-level: Compute longest common subsequence (LCS) between two pieces of +text. Newlines are ignored. This is called `rougeL` in this package. +2. summary-level: Newlines in the text are interpreted as sentence boundaries, +and the LCS is computed between each pair of reference and candidate sentences, +and something called union-LCS is computed. This is called `rougeLsum` in this +package. This is the ROUGE-L reported in *[Get To The Point: Summarization with +Pointer-Generator Networks](https://arxiv.org/abs/1704.04368)*, for example. +If your references/candidates do not have newline delimiters, you can use the +--split_summaries flag (or optional argument in RougeScorer). + +## How to run + +This package compares target files (containing one example per line) with +prediction files in the same format. It can be launched as follows (from +google-research/): + +```shell +python -m rouge.rouge \ + --target_filepattern=*.targets \ + --prediction_filepattern=*.decodes \ + --output_filename=scores.csv \ + --use_stemmer=true \ + --split_summaries=true +``` + +## Using pip +``` +pip install -r rouge/requirements.txt +pip install rouge-score +``` + +Then in python: + +```python +from rouge_score import rouge_scorer + +scorer = rouge_scorer.RougeScorer(['rouge1', 'rougeL'], use_stemmer=True) +scores = scorer.score('The quick brown fox jumps over the lazy dog', + 'The quick brown dog jumps on the log.') +``` + +## License + +Licensed under the +[Apache 2.0](https://github.com/google-research/google-research/blob/master/LICENSE) +License. + +## Disclaimer + +This is not an official Google product. + + + + +%prep +%autosetup -n rouge-score-0.1.2 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-rouge-score -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.2-1 +- Package Spec generated @@ -0,0 +1 @@ +4eec4a1febf34b4a293c78cda762489b rouge_score-0.1.2.tar.gz |