New biobb_pytorch Molecular dynamics autoencoder wrapper

tools/biobb_pytorch/.shed.yml

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+name: biobb_pytorch
+owner: chemteam
+description: "biobb_pytorch is the Biobb module collection to create and train ML & DL models using the popular [PyTorch](https://pytorch.org/) Python library."
+homepage_url: https://github.com/bioexcel/biobb_pytorch
+long_description: |
+    biobb_pytorch is the Biobb module collection to create and train ML & DL models using the popular [PyTorch](https://pytorch.org/) Python library.
+    Biobb (BioExcel building blocks) packages are Python building blocks that
+    create new layer of compatibility and interoperability over popular
+    bioinformatics tools.
+    The latest documentation of this package can be found in our readthedocs site:
+    [latest API documentation](http://biobb-pytorch.readthedocs.io/en/latest/).
+remote_repository_url: https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/tree/master/tools/biobb_pytorch
+type: unrestricted
+categories:
+  - biobb
+maintainers:
+  - PauAndrio
+  - gbayarri
+  - adamhospital

tools/biobb_pytorch/biobb_apply_mdae.xml

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+<tool id="biobb_pytorch_apply_mdae" name="ApplyMdae" version="@TOOL_VERSION@" profile="22.05">
+    <description>Apply a Molecular Dynamics AutoEncoder (MDAE) PyTorch model.</description>
+    <macros>
+      <token name="@TOOL_VERSION@">4.2.1</token>
+    </macros>
+
+    <requirements>
+      <requirement type="package" version="@TOOL_VERSION@">biobb_pytorch</requirement>
+    </requirements>
+
+    <command detect_errors="exit_code"><![CDATA[
+
+      ln -s '$input_data_npy_path' ./input_data_npy_path.$input_data_npy_path.ext &&
+      ln -s '$input_model_pth_path' ./input_model_pth_path.$input_model_pth_path.ext &&
+      #if $config_json:
+        ln -s '$config_json' ./config_json.$config_json.ext &&
+      #end if
+
+      apply_mdae
+
+      #if $config_json:
+        --config ./config_json.$config_json.ext
+      #end if
+
+      --input_data_npy_path ./input_data_npy_path.$input_data_npy_path.ext
+      --input_model_pth_path ./input_model_pth_path.$input_model_pth_path.ext
+      --output_reconstructed_data_npy_path $outname_output_reconstructed_data_npy_path
+      #if $outname_output_latent_space_npy_path:
+        --output_latent_space_npy_path $outname_output_latent_space_npy_path
+      #end if
+      ;
+
+      mv '$outname_output_reconstructed_data_npy_path' '$output_reconstructed_data_npy_path' &&
+      if test -f '$outname_output_latent_space_npy_path'; then mv '$outname_output_latent_space_npy_path' '$output_latent_space_npy_path'; fi;
+
+      ]]>
+    </command>
+
+    <inputs>
+      <param name="input_data_npy_path"  type="data" format="npy"  optional="False" label="Input NPY file" help="Input data file"/>
+      <param name="input_model_pth_path" type="data" format="pth"  optional="False" label="input PTH file" help="Path to the input model file. Format: [input].pth"/>
+      <param name="outname_output_reconstructed_data_npy_path" type="text" value="myapply_mdae.npy" optional="False" label="output NPY name" help="Path to the output reconstructed data file Format: [output].npy "/>
+      <param name="outname_output_latent_space_npy_path" type="text" value="myapply_mdae.npy" optional="True" label="output NPY name" help="Path to the reduced dimensionality file Format: [output].npy "/>
+      <param name="config_json" type="data" format="json" optional="True" label="Configuration file" help="File containing tool settings. See below for the syntax"/>
+    </inputs>
+
+    <outputs>
+      <data name="output_reconstructed_data_npy_path" format="npy" />
+      <data name="output_latent_space_npy_path"       format="npy" />
+    </outputs>
+
+    <tests>
+        <test>
+          <param name="config_json" value="config_apply_mdae.json" ftype="json" />
+          <param name="input_data_npy_path"  value="train_mdae_traj.npy" ftype="npy" />
+          <param name="input_model_pth_path" value="ref_output_model.pth" />
+          <param name="outname_output_reconstructed_data_npy_path" value="output_reconstructed_data.npy" />
+          <param name="outname_output_latent_space_npy_path" value="output_latent_space.npy" />
+          <output name="output_reconstructed_data_npy_path" ftype="npy">
+            <assert_contents>
+              <has_size value="123k" delta="50k"/>
+            </assert_contents>
+          </output>
+          <output name="output_latent_space_npy_path" ftype="npy">
+            <assert_contents>
+              <has_size value="928" delta="200"/>
+            </assert_contents>
+          </output>
+        </test>
+    </tests>
+
+    <help>
+.. class:: infomark
+
+Check the syntax for the tool parameters at the original library documentation: https://biobb-pytorch.readthedocs.io/en/latest
+
+-----
+
+.. image:: http://mmb.irbbarcelona.org/biobb/assets/layouts/layout3/img/logo.png
+    :width: 150
+
+**https://mmb.irbbarcelona.org/biobb**
+
+.. image:: https://bioexcel.eu/wp-content/uploads/2019/08/Bioexcel_logo_no_subheading_660px.png
+        :width: 150
+
+**https://bioexcel.eu**
+   </help>
+
+    <citations>
+        <citation type="bibtex">
+            @misc{githubbiobb,
+            author = {Andrio P, Bayarri, G., Hospital A, Gelpi JL},
+            year = {2019-21},
+            title = {biobb: BioExcel building blocks },
+            publisher = {GitHub},
+            journal = {GitHub repository},
+            url = {https://github.com/bioexcel/biobb_pytorch},
+            }
+        </citation>
+        <citation type="doi">10.1038/s41597-019-0177-4</citation>
+    </citations>
+</tool>

tools/biobb_pytorch/biobb_train_mdae.xml

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+<tool id="biobb_pytorch_train_mdae" name="TrainMdae" version="@TOOL_VERSION@" profile="22.05">
+    <description>Train a Molecular Dynamics AutoEncoder (MDAE) PyTorch model.</description>
+    <macros>
+      <token name="@TOOL_VERSION@">4.2.1</token>
+    </macros>
+
+    <requirements>
+      <requirement type="package" version="@TOOL_VERSION@">biobb_pytorch</requirement>
+    </requirements>
+
+    <command detect_errors="exit_code"><![CDATA[
+
+      ln -s '$input_train_npy_path' ./input_train_npy_path.$input_train_npy_path.ext &&
+      #if $input_model_pth_path:
+        ln -s '$input_model_pth_path' ./input_model_pth_path.$input_model_pth_path.ext &&
+      #end if
+      #if $config_json:
+        ln -s '$config_json' ./config_json.$config_json.ext &&
+      #end if
+
+      train_mdae
+
+      #if $config_json:
+        --config ./config_json.$config_json.ext
+      #end if
+
+      --input_train_npy_path ./input_train_npy_path.$input_train_npy_path.ext
+      #if $input_model_pth_path:
+        --input_model_pth_path ./input_model_pth_path.$input_model_pth_path.ext
+      #end if
+      --output_model_pth_path $outname_output_model_pth_path
+      #if $outname_output_train_data_npz_path:
+        --output_train_data_npz_path $outname_output_train_data_npz_path
+      #end if
+      #if $outname_output_performance_npz_path:
+        --output_performance_npz_path $outname_output_performance_npz_path
+      #end if
+      ;
+
+      mv '$outname_output_model_pth_path' '$output_model_pth_path' &&
+      if test -f '$outname_output_train_data_npz_path'; then mv '$outname_output_train_data_npz_path' '$output_train_data_npz_path'; fi;
+      if test -f '$outname_output_performance_npz_path'; then mv '$outname_output_performance_npz_path' '$output_performance_npz_path'; fi;
+
+      ]]>
+    </command>
+
+    <inputs>
+      <param name="input_train_npy_path" type="data" format="npy"  optional="False" label="input NPY file" help="Path to the input train data file. Format: [input].npy"/>
+      <param name="input_model_pth_path" type="data" format="pth"  optional="True" label="input PTH file" help="Path to the input model file. Format: [input].pth"/>
+      <param name="outname_output_model_pth_path" type="text" value="mytrain_mdae.pth" optional="False" label="output PTH name" help="Path to the output model file Format: [output].pth "/>
+      <param name="outname_output_train_data_npz_path" type="text" value="mytrain_mdae.npz" optional="True" label="output train data NPZ name" help="Path to the output train data file Format: [output].npz "/>
+      <param name="outname_output_performance_npz_path" type="text" value="mytrain_mdae.npz" optional="True" label="output performance NPZ name" help="Path to the output performance file Format: [output].npz "/>
+      <param name="config_json" type="data" format="json" optional="True" label="Configuration file" help="File containing tool settings. See below for the syntax"/>
+    </inputs>
+
+    <outputs>
+      <data name="output_model_pth_path" />
+      <data name="output_train_data_npz_path"  format="npz" />
+      <data name="output_performance_npz_path" format="npz" />
+    </outputs>
+
+    <tests>
+      <test>
+        <param name="config_json" value="config_train_mdae.json" ftype="json" />
+        <param name="input_train_npy_path" value="train_mdae_traj.npy" ftype="npy" />
+        <param name="outname_output_model_pth_path" value="output_model.pth" />
+        <param name="outname_output_train_data_npz_path" value="output_train_data.npz" />
+        <param name="outname_output_performance_npz_path" value="output_performance.npz" />
+        <output name="output_model_pth_path"       file="ref_output_model.pth" compare="sim_size" />
+        <output name="output_train_data_npz_path">
+          <assert_contents>
+            <has_size value="1k" delta="500"/>
+          </assert_contents>
+        </output>
+        <output name="output_performance_npz_path">
+          <assert_contents>
+            <has_size value="124k" delta="50k"/>
+          </assert_contents>
+        </output>
+      </test>
+    </tests>
+
+    <help>
+.. class:: infomark
+
+Check the syntax for the tool parameters at the original library documentation: https://biobb-pytorch.readthedocs.io/en/latest
+
+-----
+
+.. image:: http://mmb.irbbarcelona.org/biobb/assets/layouts/layout3/img/logo.png
+    :width: 150
+
+**https://mmb.irbbarcelona.org/biobb**
+
+.. image:: https://bioexcel.eu/wp-content/uploads/2019/08/Bioexcel_logo_no_subheading_660px.png
+        :width: 150
+
+**https://bioexcel.eu**
+   </help>
+
+    <citations>
+        <citation type="bibtex">
+            @misc{githubbiobb,
+            author = {Andrio P, Bayarri, G., Hospital A, Gelpi JL},
+            year = {2019-21},
+            title = {biobb: BioExcel building blocks },
+            publisher = {GitHub},
+            journal = {GitHub repository},
+            url = {https://github.com/bioexcel/biobb_pytorch},
+            }
+        </citation>
+        <citation type="doi">10.1038/s41597-019-0177-4</citation>
+    </citations>
+</tool>

tools/biobb_pytorch/test-data/config_apply_mdae.json

@@ -0,0 +1,5 @@
+{
+  "properties": {
+    "batch_size": 1
+  }
+}

tools/biobb_pytorch/test-data/config_train_mdae.json

@@ -0,0 +1,6 @@
+{
+  "properties": {
+    "num_epochs": 50,
+    "seed": 1
+  }
+}