<tool id="wine_quality_predict" name="wine_quality_predict" version="1.0.0">

  <description>wine_quality_predict</description>

  <requirements>

    <!-- singularity -->
    <container type="singularity">oras://registry.forgemia.inra.fr/nathalie.rousse/use/dnn_fidlemore:1906137478520a9f71a4d8996c0a8827f27aed16</container>

    <!-- image locale
    <container type="singularity">/home/nrousse/workspace_git/SIWAA_regroup/USE_branch_dnn/use/DNN/containers/fidlemore.simg</container -->

  </requirements>

  <environment_variables>
  </environment_variables>
  <command detect_errors="aggressive">
    <![CDATA[

    bash -e -c "source /fidle-tp/fidle-env/bin/activate &&
    mkdir datasets-fidle &&
    export FIDLE_DATASETS_DIR=\$(realpath -s datasets-fidle) &&
    mkdir ipython_dir &&
    export IPYTHONDIR=\$(realpath -s ipython_dir) &&
    ipython profile create default &&
    mkdir cache_dir &&
    export TRANSFORMERS_CACHE=\$(realpath -s cache_dir) &&
    mkdir mpl_dir &&
    export MPLCONFIGDIR=\$(realpath -s mpl_dir) &&
    python3 /fidlemore/model_wine_lightning/wine_quality_predict.py -model_ckpt_filepath ${model_ckpt} -norm_config_json_filepath ${norm_config_json} -data_json_filepath ${data_json} &&
    cp OUTPUTS/report.json ${report_json}"
    ]]>
  </command>

  <inputs>
    <param name="data_json" optional="false" type="data" format="json"
           label="File of data of wine whose quality to be predicted (.json)"/>
    <param name="model_ckpt" optional="false" type="data" format="ckpt" 
           label="model_ckpt model file (.ckpt)"/>
    <param name="norm_config_json" optional="false" type="data" format="json" 
           label="norm_config normalization configuration (.json)"/>
  </inputs>

  <outputs>
    <data format="json" name="report_json" label="report (.json)"/>
  </outputs>

  <tests>
  </tests>

  <help><![CDATA[

wine_quality_predict.xml

===========================

Code:

----

- wine_quality_predict.py

Inputs:

-------

- data file (.json) :
  File containing data of wine for which quality is going to be predicted.

- Model file (.ckpt)

- Normalization configuration file (.json)

Outputs:

--------

- Report file (.json)

Credits:

--------

-  Author: Nathalie Rousse nathalie.rousse@inrae.fr
-  Copyright: INRAE

  ]]>
  </help>

</tool>