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diff --git a/python-jury.spec b/python-jury.spec new file mode 100644 index 0000000..d232ca5 --- /dev/null +++ b/python-jury.spec @@ -0,0 +1,937 @@ +%global _empty_manifest_terminate_build 0 +Name: python-jury +Version: 2.2.3 +Release: 1 +Summary: Evaluation toolkit for neural language generation. +License: MIT +URL: https://github.com/obss/jury +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/82/cb/2cc74d1c798d175573becbcf91eebb0e4bc797ea48b6a183360cdf53783f/jury-2.2.3.tar.gz +BuildArch: noarch + +Requires: python3-click +Requires: python3-evaluate +Requires: python3-fire +Requires: python3-nltk +Requires: python3-rouge-score +Requires: python3-scikit-learn +Requires: python3-tqdm +Requires: python3-validators +Requires: python3-black +Requires: python3-deepdiff +Requires: python3-flake8 +Requires: python3-isort +Requires: python3-pytest +Requires: python3-pytest-cov +Requires: python3-pytest-timeout +Requires: python3-sacrebleu +Requires: python3-bert-score +Requires: python3-jiwer +Requires: python3-seqeval +Requires: python3-sentencepiece +Requires: python3-unbabel-comet +Requires: python3-fairseq +Requires: python3-importlib-metadata +Requires: python3-numpy +Requires: python3-numpy +Requires: python3-sacrebleu +Requires: python3-bert-score +Requires: python3-jiwer +Requires: python3-seqeval +Requires: python3-sentencepiece +Requires: python3-unbabel-comet +Requires: python3-fairseq +Requires: python3-numpy +Requires: python3-numpy +Requires: python3-fairseq +Requires: python3-numpy +Requires: python3-numpy + +%description +<h1 align="center">Jury</h1> + +<p align="center"> +<a href="https://pypi.org/project/jury"><img src="https://img.shields.io/pypi/pyversions/jury" alt="Python versions"></a> +<a href="https://pepy.tech/project/jury"><img src="https://pepy.tech/badge/jury" alt="downloads"></a> +<a href="https://pypi.org/project/jury"><img src="https://img.shields.io/pypi/v/jury?color=blue" alt="PyPI version"></a> +<a href="https://github.com/obss/jury/releases/latest"><img alt="Latest Release" src="https://img.shields.io/github/release-date/obss/jury"></a> +<a href="https://colab.research.google.com/github/obss/jury/blob/main/examples/jury_evaluate.ipynb"><img alt="Open in Colab" src="https://colab.research.google.com/assets/colab-badge.svg"></a> +<br> +<a href="https://github.com/obss/jury/actions"><img alt="Build status" src="https://github.com/obss/jury/actions/workflows/ci.yml/badge.svg"></a> +<a href="https://libraries.io/pypi/jury"><img alt="Dependencies" src="https://img.shields.io/librariesio/github/obss/jury"></a> +<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> +<a href="https://github.com/obss/jury/blob/main/LICENSE"><img alt="License: MIT" src="https://img.shields.io/pypi/l/jury"></a> +<br> +<a href="https://doi.org/10.5281/zenodo.6109838"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.6109838.svg" alt="DOI"></a> +</p> + +A comprehensive toolkit for evaluating NLP experiments offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses a more advanced version of [evaluate](https://github.com/huggingface/evaluate/) design for underlying metric computation, so that adding custom metric is easy as extending proper class. + +Main advantages that Jury offers are: + +- Easy to use for any NLP project. +- Unified structure for computation input across all metrics. +- Calculate many metrics at once. +- Metrics calculations can be handled concurrently to save processing time. +- It seamlessly supports evaluation for multiple predictions/multiple references. + +To see more, check the [official Jury blog post](https://medium.com/codable/jury-evaluating-performance-of-nlg-models-730eb9c9999f). + +# Available Metrics + +The table below shows the current support status for available metrics. + +| Metric | Jury Support | HF/evaluate Support | +|-------------------------------------------------------------------------------|--------------------|---------------------| +| Accuracy-Numeric | :heavy_check_mark: | :white_check_mark: | +| Accuracy-Text | :heavy_check_mark: | :x: | +| Bartscore | :heavy_check_mark: | :x: | +| Bertscore | :heavy_check_mark: | :white_check_mark: | +| Bleu | :heavy_check_mark: | :white_check_mark: | +| Bleurt | :heavy_check_mark: | :white_check_mark: | +| CER | :heavy_check_mark: | :white_check_mark: | +| CHRF | :heavy_check_mark: | :white_check_mark: | +| COMET | :heavy_check_mark: | :white_check_mark: | +| F1-Numeric | :heavy_check_mark: | :white_check_mark: | +| F1-Text | :heavy_check_mark: | :x: | +| METEOR | :heavy_check_mark: | :white_check_mark: | +| Precision-Numeric | :heavy_check_mark: | :white_check_mark: | +| Precision-Text | :heavy_check_mark: | :x: | +| Prism | :heavy_check_mark: | :x: | +| Recall-Numeric | :heavy_check_mark: | :white_check_mark: | +| Recall-Text | :heavy_check_mark: | :x: | +| ROUGE | :heavy_check_mark: | :white_check_mark: | +| SacreBleu | :heavy_check_mark: | :white_check_mark: | +| Seqeval | :heavy_check_mark: | :white_check_mark: | +| Squad | :heavy_check_mark: | :white_check_mark: | +| TER | :heavy_check_mark: | :white_check_mark: | +| WER | :heavy_check_mark: | :white_check_mark: | +| [Other metrics](https://github.com/huggingface/evaluate/tree/master/metrics)* | :white_check_mark: | :white_check_mark: | + +_*_ Placeholder for the rest of the metrics available in `evaluate` package apart from those which are present in the +table. + +**Notes** + +* The entry :heavy_check_mark: represents that full Jury support is available meaning that all combinations of input +types (single prediction & single reference, single prediction & multiple references, multiple predictions & multiple +references) are supported + +* The entry :white_check_mark: means that this metric is supported (for Jury through the `evaluate`), so that it +can (and should) be used just like the `evaluate` metric as instructed in `evaluate` implementation although +unfortunately full Jury support for those metrics are not yet available. + +## Request for a New Metric + +For the request of a new metric please [open an issue](https://github.com/obss/jury/issues/new?assignees=&labels=&template=new-metric.md&title=) providing the minimum information. Also, PRs addressing new metric +supports are welcomed :). + +## <div align="center"> Installation </div> + +Through pip, + + pip install jury + +or build from source, + + git clone https://github.com/obss/jury.git + cd jury + python setup.py install + +**NOTE:** There may be malfunctions of some metrics depending on `sacrebleu` package on Windows machines which is +mainly due to the package `pywin32`. For this, we fixed pywin32 version on our setup config for Windows platforms. +However, if pywin32 causes trouble in your environment we strongly recommend using `conda` manager install the package +as `conda install pywin32`. + +## <div align="center"> Usage </div> + +### API Usage + +It is only two lines of code to evaluate generated outputs. + +```python +from jury import Jury + +scorer = Jury() +predictions = [ + ["the cat is on the mat", "There is cat playing on the mat"], + ["Look! a wonderful day."] +] +references = [ + ["the cat is playing on the mat.", "The cat plays on the mat."], + ["Today is a wonderful day", "The weather outside is wonderful."] +] +scores = scorer(predictions=predictions, references=references) +``` + +Specify metrics you want to use on instantiation. + +```python +scorer = Jury(metrics=["bleu", "meteor"]) +scores = scorer(predictions, references) +``` + +#### Use of Metrics standalone + +You can directly import metrics from `jury.metrics` as classes, and then instantiate and use as desired. + +```python +from jury.metrics import Bleu + +bleu = Bleu.construct() +score = bleu.compute(predictions=predictions, references=references) +``` + +The additional parameters can either be specified on `compute()` + +```python +from jury.metrics import Bleu + +bleu = Bleu.construct() +score = bleu.compute(predictions=predictions, references=references, max_order=4) +``` + +, or alternatively on instantiation + +```python +from jury.metrics import Bleu +bleu = Bleu.construct(compute_kwargs={"max_order": 1}) +score = bleu.compute(predictions=predictions, references=references) +``` + +Note that you can seemlessly access both `jury` and `evaluate` metrics through `jury.load_metric`. + +```python +import jury + +bleu = jury.load_metric("bleu") +bleu_1 = jury.load_metric("bleu", resulting_name="bleu_1", compute_kwargs={"max_order": 1}) +# metrics not available in `jury` but in `evaluate` +wer = jury.load_metric("competition_math") # It falls back to `evaluate` package with a warning +``` + +### CLI Usage + +You can specify predictions file and references file paths and get the resulting scores. Each line should be paired in both files. You can optionally provide reduce function and an export path for results to be written. + + jury eval --predictions /path/to/predictions.txt --references /path/to/references.txt --reduce_fn max --export /path/to/export.txt + +You can also provide prediction folders and reference folders to evaluate multiple experiments. In this set up, however, it is required that the prediction and references files you need to evaluate as a pair have the same file name. These common names are paired together for prediction and reference. + + jury eval --predictions /path/to/predictions_folder --references /path/to/references_folder --reduce_fn max --export /path/to/export.txt + +If you want to specify metrics, and do not want to use default, specify it in config file (json) in `metrics` key. + +```json +{ + "predictions": "/path/to/predictions.txt", + "references": "/path/to/references.txt", + "reduce_fn": "max", + "metrics": [ + "bleu", + "meteor" + ] +} +``` + +Then, you can call jury eval with `config` argument. + + jury eval --config path/to/config.json + +### Custom Metrics + +You can use custom metrics with inheriting `jury.metrics.Metric`, you can see current metrics implemented on Jury from [jury/metrics](https://github.com/obss/jury/tree/master/jury/metrics). Jury falls back to `evaluate` implementation of metrics for the ones that are currently not supported by Jury, you can see the metrics available for `evaluate` on [evaluate/metrics](https://github.com/huggingface/evaluate/tree/master/metrics). + +Jury itself uses `evaluate.Metric` as a base class to drive its own base class as `jury.metrics.Metric`. The interface is similar; however, Jury makes the metrics to take a unified input type by handling the inputs for each metrics, and allows supporting several input types as; + +- single prediction & single reference +- single prediction & multiple reference +- multiple prediction & multiple reference + +As a custom metric both base classes can be used; however, we strongly recommend using `jury.metrics.Metric` as it has several advantages such as supporting computations for the input types above or unifying the type of the input. + +```python +from jury.metrics import MetricForTask + +class CustomMetric(MetricForTask): + def _compute_single_pred_single_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError + + def _compute_single_pred_multi_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError + + def _compute_multi_pred_multi_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError +``` + +For more details, have a look at base metric implementation [jury.metrics.Metric](./jury/metrics/_base.py) + +## <div align="center"> Contributing </div> + +PRs are welcomed as always :) + +### Installation + + git clone https://github.com/obss/jury.git + cd jury + pip install -e .[dev] + +Also, you need to install the packages which are available through a git source separately with the following command. +For the folks who are curious about "why?"; a short explaination is that PYPI does not allow indexing a package which +are directly dependent on non-pypi packages due to security reasons. The file `requirements-dev.txt` includes packages +which are currently only available through a git source, or they are PYPI packages with no recent release or +incompatible with Jury, so that they are added as git sources or pointing to specific commits. + + pip install -r requirements-dev.txt + +### Tests + +To tests simply run. + + python tests/run_tests.py + +### Code Style + +To check code style, + + python tests/run_code_style.py check + +To format codebase, + + python tests/run_code_style.py format + + +## <div align="center"> Citation </div> + +If you use this package in your work, please cite it as: + + @software{obss2021jury, + author = {Cavusoglu, Devrim and Akyon, Fatih Cagatay and Sert, Ulas and Cengiz, Cemil}, + title = {{Jury: Comprehensive NLP Evaluation toolkit}}, + month = {feb}, + year = {2022}, + publisher = {Zenodo}, + doi = {10.5281/zenodo.6108229}, + url = {https://doi.org/10.5281/zenodo.6108229} + } + +## <div align="center"> License </div> + +Licensed under the [MIT](LICENSE) License. + + +%package -n python3-jury +Summary: Evaluation toolkit for neural language generation. +Provides: python-jury +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-jury +<h1 align="center">Jury</h1> + +<p align="center"> +<a href="https://pypi.org/project/jury"><img src="https://img.shields.io/pypi/pyversions/jury" alt="Python versions"></a> +<a href="https://pepy.tech/project/jury"><img src="https://pepy.tech/badge/jury" alt="downloads"></a> +<a href="https://pypi.org/project/jury"><img src="https://img.shields.io/pypi/v/jury?color=blue" alt="PyPI version"></a> +<a href="https://github.com/obss/jury/releases/latest"><img alt="Latest Release" src="https://img.shields.io/github/release-date/obss/jury"></a> +<a href="https://colab.research.google.com/github/obss/jury/blob/main/examples/jury_evaluate.ipynb"><img alt="Open in Colab" src="https://colab.research.google.com/assets/colab-badge.svg"></a> +<br> +<a href="https://github.com/obss/jury/actions"><img alt="Build status" src="https://github.com/obss/jury/actions/workflows/ci.yml/badge.svg"></a> +<a href="https://libraries.io/pypi/jury"><img alt="Dependencies" src="https://img.shields.io/librariesio/github/obss/jury"></a> +<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> +<a href="https://github.com/obss/jury/blob/main/LICENSE"><img alt="License: MIT" src="https://img.shields.io/pypi/l/jury"></a> +<br> +<a href="https://doi.org/10.5281/zenodo.6109838"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.6109838.svg" alt="DOI"></a> +</p> + +A comprehensive toolkit for evaluating NLP experiments offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses a more advanced version of [evaluate](https://github.com/huggingface/evaluate/) design for underlying metric computation, so that adding custom metric is easy as extending proper class. + +Main advantages that Jury offers are: + +- Easy to use for any NLP project. +- Unified structure for computation input across all metrics. +- Calculate many metrics at once. +- Metrics calculations can be handled concurrently to save processing time. +- It seamlessly supports evaluation for multiple predictions/multiple references. + +To see more, check the [official Jury blog post](https://medium.com/codable/jury-evaluating-performance-of-nlg-models-730eb9c9999f). + +# Available Metrics + +The table below shows the current support status for available metrics. + +| Metric | Jury Support | HF/evaluate Support | +|-------------------------------------------------------------------------------|--------------------|---------------------| +| Accuracy-Numeric | :heavy_check_mark: | :white_check_mark: | +| Accuracy-Text | :heavy_check_mark: | :x: | +| Bartscore | :heavy_check_mark: | :x: | +| Bertscore | :heavy_check_mark: | :white_check_mark: | +| Bleu | :heavy_check_mark: | :white_check_mark: | +| Bleurt | :heavy_check_mark: | :white_check_mark: | +| CER | :heavy_check_mark: | :white_check_mark: | +| CHRF | :heavy_check_mark: | :white_check_mark: | +| COMET | :heavy_check_mark: | :white_check_mark: | +| F1-Numeric | :heavy_check_mark: | :white_check_mark: | +| F1-Text | :heavy_check_mark: | :x: | +| METEOR | :heavy_check_mark: | :white_check_mark: | +| Precision-Numeric | :heavy_check_mark: | :white_check_mark: | +| Precision-Text | :heavy_check_mark: | :x: | +| Prism | :heavy_check_mark: | :x: | +| Recall-Numeric | :heavy_check_mark: | :white_check_mark: | +| Recall-Text | :heavy_check_mark: | :x: | +| ROUGE | :heavy_check_mark: | :white_check_mark: | +| SacreBleu | :heavy_check_mark: | :white_check_mark: | +| Seqeval | :heavy_check_mark: | :white_check_mark: | +| Squad | :heavy_check_mark: | :white_check_mark: | +| TER | :heavy_check_mark: | :white_check_mark: | +| WER | :heavy_check_mark: | :white_check_mark: | +| [Other metrics](https://github.com/huggingface/evaluate/tree/master/metrics)* | :white_check_mark: | :white_check_mark: | + +_*_ Placeholder for the rest of the metrics available in `evaluate` package apart from those which are present in the +table. + +**Notes** + +* The entry :heavy_check_mark: represents that full Jury support is available meaning that all combinations of input +types (single prediction & single reference, single prediction & multiple references, multiple predictions & multiple +references) are supported + +* The entry :white_check_mark: means that this metric is supported (for Jury through the `evaluate`), so that it +can (and should) be used just like the `evaluate` metric as instructed in `evaluate` implementation although +unfortunately full Jury support for those metrics are not yet available. + +## Request for a New Metric + +For the request of a new metric please [open an issue](https://github.com/obss/jury/issues/new?assignees=&labels=&template=new-metric.md&title=) providing the minimum information. Also, PRs addressing new metric +supports are welcomed :). + +## <div align="center"> Installation </div> + +Through pip, + + pip install jury + +or build from source, + + git clone https://github.com/obss/jury.git + cd jury + python setup.py install + +**NOTE:** There may be malfunctions of some metrics depending on `sacrebleu` package on Windows machines which is +mainly due to the package `pywin32`. For this, we fixed pywin32 version on our setup config for Windows platforms. +However, if pywin32 causes trouble in your environment we strongly recommend using `conda` manager install the package +as `conda install pywin32`. + +## <div align="center"> Usage </div> + +### API Usage + +It is only two lines of code to evaluate generated outputs. + +```python +from jury import Jury + +scorer = Jury() +predictions = [ + ["the cat is on the mat", "There is cat playing on the mat"], + ["Look! a wonderful day."] +] +references = [ + ["the cat is playing on the mat.", "The cat plays on the mat."], + ["Today is a wonderful day", "The weather outside is wonderful."] +] +scores = scorer(predictions=predictions, references=references) +``` + +Specify metrics you want to use on instantiation. + +```python +scorer = Jury(metrics=["bleu", "meteor"]) +scores = scorer(predictions, references) +``` + +#### Use of Metrics standalone + +You can directly import metrics from `jury.metrics` as classes, and then instantiate and use as desired. + +```python +from jury.metrics import Bleu + +bleu = Bleu.construct() +score = bleu.compute(predictions=predictions, references=references) +``` + +The additional parameters can either be specified on `compute()` + +```python +from jury.metrics import Bleu + +bleu = Bleu.construct() +score = bleu.compute(predictions=predictions, references=references, max_order=4) +``` + +, or alternatively on instantiation + +```python +from jury.metrics import Bleu +bleu = Bleu.construct(compute_kwargs={"max_order": 1}) +score = bleu.compute(predictions=predictions, references=references) +``` + +Note that you can seemlessly access both `jury` and `evaluate` metrics through `jury.load_metric`. + +```python +import jury + +bleu = jury.load_metric("bleu") +bleu_1 = jury.load_metric("bleu", resulting_name="bleu_1", compute_kwargs={"max_order": 1}) +# metrics not available in `jury` but in `evaluate` +wer = jury.load_metric("competition_math") # It falls back to `evaluate` package with a warning +``` + +### CLI Usage + +You can specify predictions file and references file paths and get the resulting scores. Each line should be paired in both files. You can optionally provide reduce function and an export path for results to be written. + + jury eval --predictions /path/to/predictions.txt --references /path/to/references.txt --reduce_fn max --export /path/to/export.txt + +You can also provide prediction folders and reference folders to evaluate multiple experiments. In this set up, however, it is required that the prediction and references files you need to evaluate as a pair have the same file name. These common names are paired together for prediction and reference. + + jury eval --predictions /path/to/predictions_folder --references /path/to/references_folder --reduce_fn max --export /path/to/export.txt + +If you want to specify metrics, and do not want to use default, specify it in config file (json) in `metrics` key. + +```json +{ + "predictions": "/path/to/predictions.txt", + "references": "/path/to/references.txt", + "reduce_fn": "max", + "metrics": [ + "bleu", + "meteor" + ] +} +``` + +Then, you can call jury eval with `config` argument. + + jury eval --config path/to/config.json + +### Custom Metrics + +You can use custom metrics with inheriting `jury.metrics.Metric`, you can see current metrics implemented on Jury from [jury/metrics](https://github.com/obss/jury/tree/master/jury/metrics). Jury falls back to `evaluate` implementation of metrics for the ones that are currently not supported by Jury, you can see the metrics available for `evaluate` on [evaluate/metrics](https://github.com/huggingface/evaluate/tree/master/metrics). + +Jury itself uses `evaluate.Metric` as a base class to drive its own base class as `jury.metrics.Metric`. The interface is similar; however, Jury makes the metrics to take a unified input type by handling the inputs for each metrics, and allows supporting several input types as; + +- single prediction & single reference +- single prediction & multiple reference +- multiple prediction & multiple reference + +As a custom metric both base classes can be used; however, we strongly recommend using `jury.metrics.Metric` as it has several advantages such as supporting computations for the input types above or unifying the type of the input. + +```python +from jury.metrics import MetricForTask + +class CustomMetric(MetricForTask): + def _compute_single_pred_single_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError + + def _compute_single_pred_multi_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError + + def _compute_multi_pred_multi_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError +``` + +For more details, have a look at base metric implementation [jury.metrics.Metric](./jury/metrics/_base.py) + +## <div align="center"> Contributing </div> + +PRs are welcomed as always :) + +### Installation + + git clone https://github.com/obss/jury.git + cd jury + pip install -e .[dev] + +Also, you need to install the packages which are available through a git source separately with the following command. +For the folks who are curious about "why?"; a short explaination is that PYPI does not allow indexing a package which +are directly dependent on non-pypi packages due to security reasons. The file `requirements-dev.txt` includes packages +which are currently only available through a git source, or they are PYPI packages with no recent release or +incompatible with Jury, so that they are added as git sources or pointing to specific commits. + + pip install -r requirements-dev.txt + +### Tests + +To tests simply run. + + python tests/run_tests.py + +### Code Style + +To check code style, + + python tests/run_code_style.py check + +To format codebase, + + python tests/run_code_style.py format + + +## <div align="center"> Citation </div> + +If you use this package in your work, please cite it as: + + @software{obss2021jury, + author = {Cavusoglu, Devrim and Akyon, Fatih Cagatay and Sert, Ulas and Cengiz, Cemil}, + title = {{Jury: Comprehensive NLP Evaluation toolkit}}, + month = {feb}, + year = {2022}, + publisher = {Zenodo}, + doi = {10.5281/zenodo.6108229}, + url = {https://doi.org/10.5281/zenodo.6108229} + } + +## <div align="center"> License </div> + +Licensed under the [MIT](LICENSE) License. + + +%package help +Summary: Development documents and examples for jury +Provides: python3-jury-doc +%description help +<h1 align="center">Jury</h1> + +<p align="center"> +<a href="https://pypi.org/project/jury"><img src="https://img.shields.io/pypi/pyversions/jury" alt="Python versions"></a> +<a href="https://pepy.tech/project/jury"><img src="https://pepy.tech/badge/jury" alt="downloads"></a> +<a href="https://pypi.org/project/jury"><img src="https://img.shields.io/pypi/v/jury?color=blue" alt="PyPI version"></a> +<a href="https://github.com/obss/jury/releases/latest"><img alt="Latest Release" src="https://img.shields.io/github/release-date/obss/jury"></a> +<a href="https://colab.research.google.com/github/obss/jury/blob/main/examples/jury_evaluate.ipynb"><img alt="Open in Colab" src="https://colab.research.google.com/assets/colab-badge.svg"></a> +<br> +<a href="https://github.com/obss/jury/actions"><img alt="Build status" src="https://github.com/obss/jury/actions/workflows/ci.yml/badge.svg"></a> +<a href="https://libraries.io/pypi/jury"><img alt="Dependencies" src="https://img.shields.io/librariesio/github/obss/jury"></a> +<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> +<a href="https://github.com/obss/jury/blob/main/LICENSE"><img alt="License: MIT" src="https://img.shields.io/pypi/l/jury"></a> +<br> +<a href="https://doi.org/10.5281/zenodo.6109838"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.6109838.svg" alt="DOI"></a> +</p> + +A comprehensive toolkit for evaluating NLP experiments offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses a more advanced version of [evaluate](https://github.com/huggingface/evaluate/) design for underlying metric computation, so that adding custom metric is easy as extending proper class. + +Main advantages that Jury offers are: + +- Easy to use for any NLP project. +- Unified structure for computation input across all metrics. +- Calculate many metrics at once. +- Metrics calculations can be handled concurrently to save processing time. +- It seamlessly supports evaluation for multiple predictions/multiple references. + +To see more, check the [official Jury blog post](https://medium.com/codable/jury-evaluating-performance-of-nlg-models-730eb9c9999f). + +# Available Metrics + +The table below shows the current support status for available metrics. + +| Metric | Jury Support | HF/evaluate Support | +|-------------------------------------------------------------------------------|--------------------|---------------------| +| Accuracy-Numeric | :heavy_check_mark: | :white_check_mark: | +| Accuracy-Text | :heavy_check_mark: | :x: | +| Bartscore | :heavy_check_mark: | :x: | +| Bertscore | :heavy_check_mark: | :white_check_mark: | +| Bleu | :heavy_check_mark: | :white_check_mark: | +| Bleurt | :heavy_check_mark: | :white_check_mark: | +| CER | :heavy_check_mark: | :white_check_mark: | +| CHRF | :heavy_check_mark: | :white_check_mark: | +| COMET | :heavy_check_mark: | :white_check_mark: | +| F1-Numeric | :heavy_check_mark: | :white_check_mark: | +| F1-Text | :heavy_check_mark: | :x: | +| METEOR | :heavy_check_mark: | :white_check_mark: | +| Precision-Numeric | :heavy_check_mark: | :white_check_mark: | +| Precision-Text | :heavy_check_mark: | :x: | +| Prism | :heavy_check_mark: | :x: | +| Recall-Numeric | :heavy_check_mark: | :white_check_mark: | +| Recall-Text | :heavy_check_mark: | :x: | +| ROUGE | :heavy_check_mark: | :white_check_mark: | +| SacreBleu | :heavy_check_mark: | :white_check_mark: | +| Seqeval | :heavy_check_mark: | :white_check_mark: | +| Squad | :heavy_check_mark: | :white_check_mark: | +| TER | :heavy_check_mark: | :white_check_mark: | +| WER | :heavy_check_mark: | :white_check_mark: | +| [Other metrics](https://github.com/huggingface/evaluate/tree/master/metrics)* | :white_check_mark: | :white_check_mark: | + +_*_ Placeholder for the rest of the metrics available in `evaluate` package apart from those which are present in the +table. + +**Notes** + +* The entry :heavy_check_mark: represents that full Jury support is available meaning that all combinations of input +types (single prediction & single reference, single prediction & multiple references, multiple predictions & multiple +references) are supported + +* The entry :white_check_mark: means that this metric is supported (for Jury through the `evaluate`), so that it +can (and should) be used just like the `evaluate` metric as instructed in `evaluate` implementation although +unfortunately full Jury support for those metrics are not yet available. + +## Request for a New Metric + +For the request of a new metric please [open an issue](https://github.com/obss/jury/issues/new?assignees=&labels=&template=new-metric.md&title=) providing the minimum information. Also, PRs addressing new metric +supports are welcomed :). + +## <div align="center"> Installation </div> + +Through pip, + + pip install jury + +or build from source, + + git clone https://github.com/obss/jury.git + cd jury + python setup.py install + +**NOTE:** There may be malfunctions of some metrics depending on `sacrebleu` package on Windows machines which is +mainly due to the package `pywin32`. For this, we fixed pywin32 version on our setup config for Windows platforms. +However, if pywin32 causes trouble in your environment we strongly recommend using `conda` manager install the package +as `conda install pywin32`. + +## <div align="center"> Usage </div> + +### API Usage + +It is only two lines of code to evaluate generated outputs. + +```python +from jury import Jury + +scorer = Jury() +predictions = [ + ["the cat is on the mat", "There is cat playing on the mat"], + ["Look! a wonderful day."] +] +references = [ + ["the cat is playing on the mat.", "The cat plays on the mat."], + ["Today is a wonderful day", "The weather outside is wonderful."] +] +scores = scorer(predictions=predictions, references=references) +``` + +Specify metrics you want to use on instantiation. + +```python +scorer = Jury(metrics=["bleu", "meteor"]) +scores = scorer(predictions, references) +``` + +#### Use of Metrics standalone + +You can directly import metrics from `jury.metrics` as classes, and then instantiate and use as desired. + +```python +from jury.metrics import Bleu + +bleu = Bleu.construct() +score = bleu.compute(predictions=predictions, references=references) +``` + +The additional parameters can either be specified on `compute()` + +```python +from jury.metrics import Bleu + +bleu = Bleu.construct() +score = bleu.compute(predictions=predictions, references=references, max_order=4) +``` + +, or alternatively on instantiation + +```python +from jury.metrics import Bleu +bleu = Bleu.construct(compute_kwargs={"max_order": 1}) +score = bleu.compute(predictions=predictions, references=references) +``` + +Note that you can seemlessly access both `jury` and `evaluate` metrics through `jury.load_metric`. + +```python +import jury + +bleu = jury.load_metric("bleu") +bleu_1 = jury.load_metric("bleu", resulting_name="bleu_1", compute_kwargs={"max_order": 1}) +# metrics not available in `jury` but in `evaluate` +wer = jury.load_metric("competition_math") # It falls back to `evaluate` package with a warning +``` + +### CLI Usage + +You can specify predictions file and references file paths and get the resulting scores. Each line should be paired in both files. You can optionally provide reduce function and an export path for results to be written. + + jury eval --predictions /path/to/predictions.txt --references /path/to/references.txt --reduce_fn max --export /path/to/export.txt + +You can also provide prediction folders and reference folders to evaluate multiple experiments. In this set up, however, it is required that the prediction and references files you need to evaluate as a pair have the same file name. These common names are paired together for prediction and reference. + + jury eval --predictions /path/to/predictions_folder --references /path/to/references_folder --reduce_fn max --export /path/to/export.txt + +If you want to specify metrics, and do not want to use default, specify it in config file (json) in `metrics` key. + +```json +{ + "predictions": "/path/to/predictions.txt", + "references": "/path/to/references.txt", + "reduce_fn": "max", + "metrics": [ + "bleu", + "meteor" + ] +} +``` + +Then, you can call jury eval with `config` argument. + + jury eval --config path/to/config.json + +### Custom Metrics + +You can use custom metrics with inheriting `jury.metrics.Metric`, you can see current metrics implemented on Jury from [jury/metrics](https://github.com/obss/jury/tree/master/jury/metrics). Jury falls back to `evaluate` implementation of metrics for the ones that are currently not supported by Jury, you can see the metrics available for `evaluate` on [evaluate/metrics](https://github.com/huggingface/evaluate/tree/master/metrics). + +Jury itself uses `evaluate.Metric` as a base class to drive its own base class as `jury.metrics.Metric`. The interface is similar; however, Jury makes the metrics to take a unified input type by handling the inputs for each metrics, and allows supporting several input types as; + +- single prediction & single reference +- single prediction & multiple reference +- multiple prediction & multiple reference + +As a custom metric both base classes can be used; however, we strongly recommend using `jury.metrics.Metric` as it has several advantages such as supporting computations for the input types above or unifying the type of the input. + +```python +from jury.metrics import MetricForTask + +class CustomMetric(MetricForTask): + def _compute_single_pred_single_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError + + def _compute_single_pred_multi_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError + + def _compute_multi_pred_multi_ref( + self, predictions, references, reduce_fn = None, **kwargs + ): + raise NotImplementedError +``` + +For more details, have a look at base metric implementation [jury.metrics.Metric](./jury/metrics/_base.py) + +## <div align="center"> Contributing </div> + +PRs are welcomed as always :) + +### Installation + + git clone https://github.com/obss/jury.git + cd jury + pip install -e .[dev] + +Also, you need to install the packages which are available through a git source separately with the following command. +For the folks who are curious about "why?"; a short explaination is that PYPI does not allow indexing a package which +are directly dependent on non-pypi packages due to security reasons. The file `requirements-dev.txt` includes packages +which are currently only available through a git source, or they are PYPI packages with no recent release or +incompatible with Jury, so that they are added as git sources or pointing to specific commits. + + pip install -r requirements-dev.txt + +### Tests + +To tests simply run. + + python tests/run_tests.py + +### Code Style + +To check code style, + + python tests/run_code_style.py check + +To format codebase, + + python tests/run_code_style.py format + + +## <div align="center"> Citation </div> + +If you use this package in your work, please cite it as: + + @software{obss2021jury, + author = {Cavusoglu, Devrim and Akyon, Fatih Cagatay and Sert, Ulas and Cengiz, Cemil}, + title = {{Jury: Comprehensive NLP Evaluation toolkit}}, + month = {feb}, + year = {2022}, + publisher = {Zenodo}, + doi = {10.5281/zenodo.6108229}, + url = {https://doi.org/10.5281/zenodo.6108229} + } + +## <div align="center"> License </div> + +Licensed under the [MIT](LICENSE) License. + + +%prep +%autosetup -n jury-2.2.3 + +%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-jury -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.3-1 +- Package Spec generated |