diff train_test_eval.xml @ 14:0edcdeaad6f4 draft default tip

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a

--- a/train_test_eval.xml	Thu Aug 11 07:51:41 2022 +0000
+++ b/train_test_eval.xml	Mon Oct 02 09:12:23 2023 +0000
@@ -1,4 +1,4 @@
-<tool id="sklearn_train_test_eval" name="Train, Test and Evaluation" version="@VERSION@" profile="20.05">
+<tool id="sklearn_train_test_eval" name="Train, Test and Evaluation" version="@VERSION@" profile="@PROFILE@">
     <description>fit a model using part of dataset and evaluate using the rest</description>
     <macros>
         <import>main_macros.xml</import>
@@ -85,7 +85,7 @@
     </inputs>
     <outputs>
         <data format="tabular" name="outfile_result" />
-        <data format="zip" name="outfile_object" label="Fitted estimator or estimator skeleton on ${on_string}">
+        <data format="h5mlm" name="outfile_object" label="Fitted estimator or estimator skeleton on ${on_string}">
             <filter>save != 'nope'</filter>
         </data>
         <data format="h5" name="outfile_weights" label="Weights trained on ${on_string}">
@@ -96,20 +96,20 @@
         <test>
             <conditional name="experiment_schemes">
                 <param name="selected_exp_scheme" value="train_val_test" />
-                <param name="infile_estimator" value="keras_model04" ftype="zip" />
+                <param name="infile_estimator" value="keras_model04" ftype="h5mlm" />
                 <section name="hyperparams_swapping">
                     <param name="infile_params" value="keras_params04.tabular" ftype="tabular" />
                     <repeat name="param_set">
                         <param name="sp_value" value="999" />
-                        <param name="sp_name" value="layers_0_Dense__config__kernel_initializer__config__seed" />
+                        <param name="sp_name" value="layers_1_Dense__config__kernel_initializer__config__seed" />
                     </repeat>
                     <repeat name="param_set">
                         <param name="sp_value" value="999" />
-                        <param name="sp_name" value="layers_2_Dense__config__kernel_initializer__config__seed" />
+                        <param name="sp_name" value="layers_3_Dense__config__kernel_initializer__config__seed" />
                     </repeat>
                     <repeat name="param_set">
                         <param name="sp_value" value="0.1" />
-                        <param name="sp_name" value="lr" />
+                        <param name="sp_name" value="learning_rate" />
                     </repeat>
                     <repeat name="param_set">
                         <param name="sp_value" value="'adamax'" />
@@ -147,30 +147,27 @@
             <output name="outfile_result">
                 <assert_contents>
                     <has_n_columns n="2" />
-                    <has_text text="0.6384" />
-                    <has_text text="-6.072" />
                 </assert_contents>
             </output>
-            <output name="outfile_object" file="train_test_eval_model01" compare="sim_size" delta="5" />
             <output name="outfile_weights" file="train_test_eval_weights01.h5" compare="sim_size" delta="5" />
         </test>
         <test>
             <conditional name="experiment_schemes">
                 <param name="selected_exp_scheme" value="train_val_test" />
-                <param name="infile_estimator" value="keras_model04" ftype="zip" />
+                <param name="infile_estimator" value="keras_model04" ftype="h5mlm" />
                 <section name="hyperparams_swapping">
                     <param name="infile_params" value="keras_params04.tabular" ftype="tabular" />
                     <repeat name="param_set">
                         <param name="sp_value" value="999" />
-                        <param name="sp_name" value="layers_0_Dense__config__kernel_initializer__config__seed" />
+                        <param name="sp_name" value="layers_1_Dense__config__kernel_initializer__config__seed" />
                     </repeat>
                     <repeat name="param_set">
                         <param name="sp_value" value="999" />
-                        <param name="sp_name" value="layers_2_Dense__config__kernel_initializer__config__seed" />
+                        <param name="sp_name" value="layers_3_Dense__config__kernel_initializer__config__seed" />
                     </repeat>
                     <repeat name="param_set">
                         <param name="sp_value" value="0.1" />
-                        <param name="sp_name" value="lr" />
+                        <param name="sp_name" value="learning_rate" />
                     </repeat>
                     <repeat name="param_set">
                         <param name="sp_value" value="'adamax'" />
@@ -214,8 +211,6 @@
             <output name="outfile_result">
                 <assert_contents>
                     <has_n_columns n="2" />
-                    <has_text text="0.627" />
-                    <has_text text="-6.012" />
                 </assert_contents>
             </output>
             <output name="outfile_weights" file="train_test_eval_weights02.h5" compare="sim_size" delta="5" />
@@ -223,7 +218,7 @@
         <test>
             <conditional name="experiment_schemes">
                 <param name="selected_exp_scheme" value="train_test" />
-                <param name="infile_estimator" value="pipeline10" ftype="zip" />
+                <param name="infile_estimator" value="pipeline10" ftype="h5mlm" />
                 <section name="hyperparams_swapping">
                     <param name="infile_params" value="get_params10.tabular" ftype="tabular" />
                     <repeat name="param_set">
@@ -242,13 +237,6 @@
                         <param name="random_state" value="123" />
                     </conditional>
                 </section>
-                <section name="val_split">
-                    <conditional name="split_algos">
-                        <param name="shuffle" value="simple" />
-                        <param name="test_size" value="0.2" />
-                        <param name="random_state" value="456" />
-                    </conditional>
-                </section>
                 <section name="metrics">
                     <conditional name="scoring">
                         <param name="primary_scoring" value="r2" />