--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ludwig_predict.xml	Tue Jan 07 22:45:18 2025 +0000
@@ -0,0 +1,111 @@
+<tool id="ludwig_predict" name="Ludwig Predict" version="@VERSION@" profile="@PROFILE@">
+    <description>loads a pretrained model to do prediction</description>
+    <macros>
+        <import>ludwig_macros.xml</import>
+    </macros>
+    <expand macro="python_requirements_gpu" />
+    <expand macro="macro_stdio" />
+    <version_command>echo "@VERSION@"</version_command>
+    <command>
+        <![CDATA[
+            #import re
+            mkdir -p outputs &&
+            #if $dataset
+            #set $sanitized_dataset = re.sub('[^\w\-_\.]', '_', $dataset.element_identifier.strip())
+            ln -sf '$dataset' "./${sanitized_dataset}";
+            #end if
+
+            #if $raw_data
+                unzip -o -q '$raw_data' -d ./;
+            #end if
+
+            python '$__tool_directory__/ludwig_predict.py'
+                #if $model_path
+                --model_path '$model_path.extra_files_path'
+                #end if
+                #if $dataset
+                --dataset "./${sanitized_dataset}"
+                #end if
+                #if $disable_parallel_threads
+                --disable_parallel_threads
+                #end if
+                --output_directory "./outputs"
+                --data_format '$data_format'
+                --split '$split'
+                --backend local
+                --skip_save_unprocessed_output &&
+            echo "Prediction is done!"
+
+        ]]>
+    </command>
+    <configfiles>
+        <inputs name="inputs" />
+    </configfiles>
+    <inputs>
+        <param name="model_path" type="data" format="ludwig_model" label="Load the pretrained model" />
+        <param name="dataset" type="data" format="tabular,csv,h5,json,txt" label="Input dataset" />
+        <param name="data_format" type="select" label="Data format">
+            <option value="auto" selected="true">auto</option>
+            <option value="tsv">tsv</option>
+            <option value="csv">csv</option>
+            <option value="h5">h5</option>
+            <option value="json">json</option>
+        </param>
+        <param name="split" type="select" label="Select the split portion to test the model on">
+            <option value="training">training</option>
+            <option value="validation">validation</option>
+            <option value="test">test</option>
+            <option value="full" selected="true">full</option>
+        </param>
+        <param name="batch_size" type="integer" value="128" optional="true" label="Batch size" min="1" max="4096" />
+        <param name="disable_parallel_threads" type="boolean" checked="false" label="Whether to disable parallel threads for reproducibility?" />
+        <param name="raw_data" type="data" format="zip" optional="true" label="Raw data" help="Optional. Needed for images."/>
+    </inputs>       
+    <outputs>
+        <collection type="list" name="output_csv" label="${tool.name} CSV on ${on_string}" >
+            <discover_datasets pattern="(?P&lt;designation&gt;predictions_parquet\.csv)" format="csv" directory="outputs" />
+            <discover_datasets pattern="(?P&lt;designation&gt;.+)\.json" format="json" directory="outputs" />
+        </collection>
+        <!-- <data format="html" name="output_report" from_work_dir="outputs/smart_report.html" label="${tool.name} report on ${on_string}" /> -->
+        <!-- <data format="csv" name="output_top_k" label="${tool.name} top K predictions on ${on_string}" /> -->
+    </outputs>
+    <tests>
+        <test>
+            <param name="model_path" value="" ftype="ludwig_model">
+                <composite_data value="temp_model01/model_hyperparameters.json" />
+                <composite_data value="temp_model01/model_weights" />
+                <composite_data value="temp_model01/training_set_metadata.json" />
+                <composite_data value="temp_model01/training_progress.json" />
+            </param>
+            <param name="dataset" value="temperature_la.csv" ftype="csv" />
+            <param name="split" value="test" />
+            <output_collection name="output_csv">
+                <element name="predictions_parquet.csv">
+                    <assert_contents>
+                        <has_n_columns n="1" />
+                    </assert_contents>
+                </element>
+            </output_collection>
+        </test>
+    </tests>
+    <help>
+        <![CDATA[
+**What it does**
+This tool conducts `ludwig predict`.
+
+
+**Input**
+- a trained ludwig model.
+- dataset to be evaluate.
+
+
+**Output**
+- report in html.
+- a collection of prediction results.
+
+
+
+        ]]>
+    </help>
+    <expand macro="macro_citations" />
+</tool>