Mercurial > repos > bgruening > keras_batch_models
diff keras_batch_models.xml @ 15:cada91b0c1d1 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
| author | bgruening |
|---|---|
| date | Wed, 09 Aug 2023 12:20:18 +0000 (21 months ago) |
| parents | 0a3f113397b2 |
| children | 9d77b259ef27 |
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--- a/keras_batch_models.xml Thu Aug 11 09:00:13 2022 +0000 +++ b/keras_batch_models.xml Wed Aug 09 12:20:18 2023 +0000 @@ -1,153 +1,171 @@ -<tool id="keras_batch_models" name="Build Deep learning Batch Training Models" version="@KERAS_VERSION@" profile="20.05"> - <description>with online data generator for Genomic/Protein sequences and images</description> - <macros> - <import>main_macros.xml</import> - <import>keras_macros.xml</import> - </macros> - <expand macro="python_requirements" /> - <expand macro="macro_stdio" /> - <version_command>echo "@KERAS_VERSION@"</version_command> - <command> - <![CDATA[ +<tool id="keras_batch_models" name="Build Deep learning Batch Training Models" version="@VERSION@" profile="@PROFILE@"> + <description>with online data generator for Genomic/Protein sequences and images</description> + <macros> + <import>main_macros.xml</import> + <import>keras_macros.xml</import> + </macros> + <expand macro="python_requirements" /> + <expand macro="macro_stdio" /> + <version_command>echo "@VERSION@"</version_command> + <command> + <![CDATA[ python '$__tool_directory__/keras_deep_learning.py' --inputs '$inputs' --model_json '$mode_selection.infile_json' --tool_id 'keras_batch_models' --outfile '$outfile' - #if $get_params - --outfile_params '$outfile_params' - #end if ]]> - </command> - <configfiles> - <inputs name="inputs" /> - </configfiles> - <inputs> - <conditional name="mode_selection"> - <param name="mode_type" type="select" label="Choose a building mode"> - <option value="train_model" selected="true">Build a training model</option> - </param> - <when value="train_model"> - <param name="infile_json" type="data" format="json" label="Select the dataset containing model configurations (JSON)" /> - <param name="learning_type" type="select" label="Select a learning class"> - <option value="KerasGBatchClassifier">KerasGBatchClassifier -- Build a training model with batch data generator</option> - </param> - <conditional name="generator_selection"> - <param name="generator_type" type="select" label="Select a batch data generator"> - <option value="FastaDNABatchGenerator" selected="true">FastaDNABatchGenerator -- Online transformation of DNA sequences</option> - <option value="FastaRNABatchGenerator">FastaRNABatchGenerator -- Online transformation of RNA sequences</option> - <option value="FastaProteinBatchGenerator">FastaProteinBatchGenerator -- Online transformation of Protein sequences</option> - <option value="GenomicIntervalBatchGenerator">GenomicIntervalBatchGenerator - Online transformation of genomic sequences from a reference genome and intervals</option> - <option value="none">To be determined</option> - </param> - <when value="FastaDNABatchGenerator"> - <expand macro="params_fasta_dna_batch_generator" /> - </when> - <when value="FastaRNABatchGenerator"> - <expand macro="params_fasta_dna_batch_generator" /> - </when> - <when value="FastaProteinBatchGenerator"> - <expand macro="params_fasta_protein_batch_generator" /> - </when> - <when value="GenomicIntervalBatchGenerator"> - <expand macro="params_genomic_interval_batch_generator" /> - </when> - <when value="none" /> - </conditional> - <expand macro="keras_compile_params_section" /> - <expand macro="keras_fit_params_section" /> - <param name="class_positive_factor" type="float" value="1" optional="true" label="class_positive_factor" help="For binary classification only. If int, like 5, will convert to class_weight {0: 1, 1: 5}. If float, 0.2, corresponds to class_weight {0: 1/0.2, 1: 1}" /> - <param name="prediction_steps" type="integer" value="" optional="true" label="prediction_steps" help="Prediction steps. Optional. If None, it equals number of samples divided by `batch_size`." /> - <param name="random_seed" type="integer" value="" optional="true" label="Random Seed" help="Integer or blank for None. Warning: when random seed is set to an integer, training will be running in single thread mode, which may cause slowness." /> - </when> + </command> + <configfiles> + <inputs name="inputs" /> + </configfiles> + <inputs> + <conditional name="mode_selection"> + <param name="mode_type" type="select" label="Choose a building mode"> + <option value="train_model" selected="true">Build a training model</option> + </param> + <when value="train_model"> + <param name="infile_json" type="data" format="json" label="Select the dataset containing model configurations (JSON)" /> + <param name="learning_type" type="select" label="Select a learning class"> + <option value="KerasGBatchClassifier">KerasGBatchClassifier -- Build a training model with batch data generator</option> + </param> + <conditional name="generator_selection"> + <param name="generator_type" type="select" label="Select a batch data generator"> + <option value="FastaDNABatchGenerator" selected="true">FastaDNABatchGenerator -- Online transformation of DNA sequences</option> + <option value="FastaRNABatchGenerator">FastaRNABatchGenerator -- Online transformation of RNA sequences</option> + <option value="FastaProteinBatchGenerator">FastaProteinBatchGenerator -- Online transformation of Protein sequences</option> + <option value="GenomicIntervalBatchGenerator">GenomicIntervalBatchGenerator - Online transformation of genomic sequences from a reference genome and intervals</option> + <option value="none">To be determined</option> + </param> + <when value="FastaDNABatchGenerator"> + <expand macro="params_fasta_dna_batch_generator" /> + </when> + <when value="FastaRNABatchGenerator"> + <expand macro="params_fasta_dna_batch_generator" /> + </when> + <when value="FastaProteinBatchGenerator"> + <expand macro="params_fasta_protein_batch_generator" /> + </when> + <when value="GenomicIntervalBatchGenerator"> + <expand macro="params_genomic_interval_batch_generator" /> + </when> + <when value="none" /> + </conditional> + <expand macro="keras_compile_params_section" /> + <expand macro="keras_fit_params_section" /> + <param name="class_positive_factor" type="float" value="1" optional="true" label="class_positive_factor" help="For binary classification only. If int, like 5, will convert to class_weight {0: 1, 1: 5}. If float, 0.2, corresponds to class_weight {0: 1/0.2, 1: 1}" /> + <param name="prediction_steps" type="integer" value="" optional="true" label="prediction_steps" help="Prediction steps. Optional. If None, it equals number of samples divided by `batch_size`." /> + <param name="random_seed" type="integer" value="" optional="true" label="Random Seed" help="Integer or blank for None. Warning: when random seed is set to an integer, training will be running in single thread mode, which may cause slowness." /> + </when> + </conditional> + </inputs> + <outputs> + <data format="h5mlm" name="outfile" label="Keras Batch Classifier on ${on_string}" /> + </outputs> + <tests> + <test> + <conditional name="mode_selection"> + <param name="infile_json" value="keras05.json" ftype="json" /> + <param name="learning_type" value="KerasGBatchClassifier" /> + <conditional name="generator_selection"> + <param name="generator_type" value="none" /> </conditional> - <param name="get_params" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Output parameters for searchCV?" help="Optional. Tunable parameters could be obtained through `estimator_attributes` tool." /> - </inputs> - <outputs> - <data format="zip" name="outfile" label="Keras Batch Classifier on ${on_string}" /> - <data format="tabular" name="outfile_params" label="get_params for Keras Batch Classifier on ${on_string}"> - <filter>get_params</filter> - </data> - </outputs> - <tests> - <test> - <conditional name="mode_selection"> - <param name="infile_json" value="keras01.json" ftype="json" /> - <param name="learning_type" value="KerasGBatchClassifier" /> - <conditional name="generator_selection"> - <param name="generator_type" value="none" /> - </conditional> - <section name="fit_params"> - <param name="epochs" value="100" /> - <repeat name="callbacks"> - <conditional name="callback_selection"> - <param name="callback_type" value="None" /> - </conditional> - </repeat> - </section> + <section name="compile_params"> + <param name="loss" value="categorical_crossentropy" /> + <conditional name="optimizer_selection"> + <param name="optimizer_type" value="RMSprop" /> + <section name="optimizer_options"> + <param name="lr" value="0.0001" /> + <param name="decay" value="0.000001" /> + </section> + </conditional> + <param name="metrics" value="acc,categorical_accuracy" /> + </section> + <section name="fit_params"> + <param name="epochs" value="100" /> + <repeat name="callbacks"> + <conditional name="callback_selection"> + <param name="callback_type" value="None" /> </conditional> - <param name="get_params" value="true" /> - <output name="outfile" file="keras_batch_model04" compare="sim_size" delta="30" /> - <output name="outfile_params" file="keras_batch_params04.tabular" /> - </test> - <test> - <conditional name="mode_selection"> - <param name="infile_json" value="deepsear_1feature.json" ftype="json" /> - <param name="learning_type" value="KerasGBatchClassifier" /> - <conditional name="generator_selection"> - <param name="generator_type" value="GenomicIntervalBatchGenerator" /> - <param name="seed" value="999" /> - </conditional> - <section name="fit_params"> - <param name="epochs" value="100" /> - </section> + </repeat> + </section> + </conditional> + <output name="outfile" file="keras_batch_model05" compare="sim_size" delta="5" /> + </test> + <test> + <conditional name="mode_selection"> + <param name="infile_json" value="keras01.json" ftype="json" /> + <param name="learning_type" value="KerasGBatchClassifier" /> + <conditional name="generator_selection"> + <param name="generator_type" value="none" /> + </conditional> + <section name="fit_params"> + <param name="epochs" value="100" /> + <repeat name="callbacks"> + <conditional name="callback_selection"> + <param name="callback_type" value="None" /> </conditional> - <output name="outfile" file="keras_batch_model03" compare="sim_size" delta="30" /> - </test> - <test> - <conditional name="mode_selection"> - <param name="infile_json" value="keras01.json" ftype="json" /> - <param name="learning_type" value="KerasGBatchClassifier" /> - <conditional name="generator_selection"> - <param name="generator_type" value="FastaDNABatchGenerator" /> - <param name="seed" value="999" /> - </conditional> - <section name="fit_params"> - <param name="epochs" value="100" /> - <repeat name="callbacks"> - <conditional name="callback_selection"> - <param name="callback_type" value="EarlyStopping" /> - <param name="monitor" value="val_loss" /> - </conditional> - </repeat> - </section> + </repeat> + </section> + </conditional> + <output name="outfile" file="keras_batch_model04" compare="sim_size" delta="20" /> + </test> + <test> + <conditional name="mode_selection"> + <param name="infile_json" value="deepsear_1feature.json" ftype="json" /> + <param name="learning_type" value="KerasGBatchClassifier" /> + <conditional name="generator_selection"> + <param name="generator_type" value="GenomicIntervalBatchGenerator" /> + <param name="seed" value="999" /> + </conditional> + <section name="fit_params"> + <param name="epochs" value="100" /> + </section> + </conditional> + <output name="outfile" file="keras_batch_model03" compare="sim_size" delta="20" /> + </test> + <test> + <conditional name="mode_selection"> + <param name="infile_json" value="keras01.json" ftype="json" /> + <param name="learning_type" value="KerasGBatchClassifier" /> + <conditional name="generator_selection"> + <param name="generator_type" value="FastaDNABatchGenerator" /> + <param name="seed" value="999" /> + </conditional> + <section name="fit_params"> + <param name="epochs" value="100" /> + <repeat name="callbacks"> + <conditional name="callback_selection"> + <param name="callback_type" value="EarlyStopping" /> + <param name="monitor" value="val_loss" /> </conditional> - <output name="outfile" file="keras_batch_model02" compare="sim_size" delta="30" /> - </test> - <test> - <conditional name="mode_selection"> - <param name="infile_json" value="keras01.json" ftype="json" /> - <param name="learning_type" value="KerasGBatchClassifier" /> - <conditional name="generator_selection"> - <param name="generator_type" value="FastaDNABatchGenerator" /> - <param name="seed" value="999" /> - </conditional> - <section name="fit_params"> - <param name="epochs" value="100" /> - <repeat name="callbacks"> - <conditional name="callback_selection"> - <param name="callback_type" value="None" /> - </conditional> - </repeat> - </section> + </repeat> + </section> + </conditional> + <output name="outfile" file="keras_batch_model02" compare="sim_size" delta="20" /> + </test> + <test> + <conditional name="mode_selection"> + <param name="infile_json" value="keras01.json" ftype="json" /> + <param name="learning_type" value="KerasGBatchClassifier" /> + <conditional name="generator_selection"> + <param name="generator_type" value="FastaDNABatchGenerator" /> + <param name="seed" value="999" /> + </conditional> + <section name="fit_params"> + <param name="epochs" value="100" /> + <repeat name="callbacks"> + <conditional name="callback_selection"> + <param name="callback_type" value="None" /> </conditional> - <param name="get_params" value="true" /> - <output name="outfile" file="keras_batch_model01" compare="sim_size" delta="30" /> - <output name="outfile_params" file="keras_batch_params01.tabular" /> - </test> - </tests> - <help> - <![CDATA[ + </repeat> + </section> + </conditional> + <output name="outfile" file="keras_batch_model01" compare="sim_size" delta="5" /> + </test> + </tests> + <help> + <![CDATA[ **What does this tool do?** This tool builds deep learning training models using API `galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`_, which takes parameters in FIVE categories. @@ -165,7 +183,7 @@ **Output** -A zipped model file that could be used in `model_validation` tool or `hyperparameter search` tool. +A model file that could be used in `model_validation` tool or `hyperparameter search` tool. .. _`galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#kerasgbatchclassifier @@ -180,9 +198,9 @@ .. _`keras.io`: https://keras.io/models/model/#fit_generator ]]> - </help> - <citations> - <expand macro="keras_citation" /> - <expand macro="tensorflow_citation" /> - </citations> + </help> + <citations> + <expand macro="keras_citation" /> + <expand macro="tensorflow_citation" /> + </citations> </tool>