Mercurial > repos > bgruening > keras_batch_models

annotate keras_batch_models.xml @ 5:79efb5472c2e draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
author bgruening
date Mon, 16 Dec 2019 09:47:30 +0000
parents f59a4f7c47f9
children 8edfc7381344
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1 <tool id="keras_batch_models" name="Build Deep learning Batch Training Models" version="@KERAS_VERSION@">
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2 <description>with online data generator for Genomic/Protein sequences and images</description>
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3 <macros>
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4 <import>main_macros.xml</import>
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5 <import>keras_macros.xml</import>
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6 </macros>
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7 <expand macro="python_requirements"/>
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8 <expand macro="macro_stdio"/>
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9 <version_command>echo "@KERAS_VERSION@"</version_command>
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10 <command>
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11 <![CDATA[
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12 python '$__tool_directory__/keras_deep_learning.py'
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13 --inputs '$inputs'
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14 --model_json '$mode_selection.infile_json'
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15 --tool_id 'keras_batch_models'
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16 --outfile '$outfile'
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17 #if $get_params
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18 --outfile_params '$outfile_params'
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19 #end if
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20 ]]>
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21 </command>
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22 <configfiles>
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23 <inputs name="inputs"/>
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24 </configfiles>
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25 <inputs>
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26 <conditional name="mode_selection">
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27 <param name="mode_type" type="select" label="Choose a building mode">
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28 <option value="train_model" selected="true">Build a training model</option>
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29 </param>
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30 <when value="train_model">
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31 <param name="infile_json" type="data" format="json" label="Select the dataset containing model configurations (JSON)"/>
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32 <param name="learning_type" type="select" label="Select a learning class">
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33 <option value="KerasGBatchClassifier">KerasGBatchClassifier -- Build a training model with batch data generator</option>
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34 </param>
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35 <conditional name="generator_selection">
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36 <param name="generator_type" type="select" label="Select a batch data generator">
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37 <option value="FastaDNABatchGenerator" selected="true">FastaDNABatchGenerator -- Online transformation of DNA sequences</option>
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38 <option value="FastaRNABatchGenerator">FastaRNABatchGenerator -- Online transformation of RNA sequences</option>
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39 <option value="FastaProteinBatchGenerator">FastaProteinBatchGenerator -- Online transformation of Protein sequences</option>
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40 <option value="GenomicIntervalBatchGenerator">GenomicIntervalBatchGenerator - Online transformation of genomic sequences from a reference genome and intervals</option>
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41 <option value="none">To be determined</option>
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42 </param>
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43 <when value="FastaDNABatchGenerator">
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44 <expand macro="params_fasta_dna_batch_generator"/>
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45 </when>
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46 <when value="FastaRNABatchGenerator">
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47 <expand macro="params_fasta_dna_batch_generator"/>
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48 </when>
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49 <when value="FastaProteinBatchGenerator">
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50 <expand macro="params_fasta_protein_batch_generator"/>
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51 </when>
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52 <when value="GenomicIntervalBatchGenerator">
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53 <expand macro="params_genomic_interval_batch_generator"/>
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54 </when>
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55 <when value="none"/>
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56 </conditional>
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57 <expand macro="keras_compile_params_section"/>
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58 <expand macro="keras_fit_params_section"/>
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59 <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}"/>
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60 <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`."/>
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61 <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."/>
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62 </when>
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63 </conditional>
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64 <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."/>
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65 </inputs>
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66 <outputs>
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67 <data format="zip" name="outfile" label="Keras Batch Classifier on ${on_string}"/>
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68 <data format="tabular" name="outfile_params" label="get_params for Keras Batch Classifier on ${on_string}">
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69 <filter>get_params</filter>
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70 </data>
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71 </outputs>
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72 <tests>
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73 <test>
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74 <conditional name="mode_selection">
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75 <param name="infile_json" value="keras01.json" ftype="json"/>
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76 <param name="learning_type" value="KerasGBatchClassifier"/>
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77 <conditional name="generator_selection">
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78 <param name="generator_type" value="none"/>
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79 </conditional>
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80 <section name="fit_params">
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81 <param name="epochs" value="100"/>
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82 <repeat name="callbacks">
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83 <conditional name="callback_selection">
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84 <param name="callback_type" value="None"/>
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85 </conditional>
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86 </repeat>
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87 </section>
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88 </conditional>
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89 <param name="get_params" value="true" />
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90 <output name="outfile" file="keras_batch_model04" compare="sim_size" delta="5"/>
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91 <output name="outfile_params" file="keras_batch_params04.tabular" />
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92 </test>
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93 <test>
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94 <conditional name="mode_selection">
0
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95 <param name="infile_json" value="deepsear_1feature.json" ftype="json"/>
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96 <param name="learning_type" value="KerasGBatchClassifier"/>
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97 <conditional name="generator_selection">
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98 <param name="generator_type" value="GenomicIntervalBatchGenerator"/>
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99 <param name="seed" value="999"/>
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100 </conditional>
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101 <section name="fit_params">
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102 <param name="epochs" value="100"/>
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103 </section>
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104 </conditional>
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105 <output name="outfile" file="keras_batch_model03" compare="sim_size" delta="5"/>
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106 </test>
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107 <test>
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108 <conditional name="mode_selection">
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109 <param name="infile_json" value="keras01.json" ftype="json"/>
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110 <param name="learning_type" value="KerasGBatchClassifier"/>
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111 <conditional name="generator_selection">
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112 <param name="generator_type" value="FastaDNABatchGenerator"/>
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113 <param name="seed" value="999"/>
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114 </conditional>
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115 <section name="fit_params">
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116 <param name="epochs" value="100"/>
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117 <repeat name="callbacks">
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118 <conditional name="callback_selection">
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119 <param name="callback_type" value="EarlyStopping"/>
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120 <param name="monitor" value="val_loss"/>
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121 </conditional>
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122 </repeat>
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123 </section>
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124 </conditional>
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125 <output name="outfile" file="keras_batch_model02" compare="sim_size" delta="5"/>
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126 </test>
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127 <test>
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128 <conditional name="mode_selection">
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129 <param name="infile_json" value="keras01.json" ftype="json"/>
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130 <param name="learning_type" value="KerasGBatchClassifier"/>
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131 <conditional name="generator_selection">
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132 <param name="generator_type" value="FastaDNABatchGenerator"/>
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133 <param name="seed" value="999"/>
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134 </conditional>
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135 <section name="fit_params">
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136 <param name="epochs" value="100"/>
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137 <repeat name="callbacks">
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138 <conditional name="callback_selection">
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139 <param name="callback_type" value="None"/>
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140 </conditional>
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141 </repeat>
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142 </section>
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143 </conditional>
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144 <param name="get_params" value="true" />
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145 <output name="outfile" file="keras_batch_model01" compare="sim_size" delta="5"/>
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146 <output name="outfile_params" file="keras_batch_params01.tabular" />
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147 </test>
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148 </tests>
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149 <help>
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150 <![CDATA[
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151 **What does this tool do?**
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152
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153 This tool builds deep learning training models using API `galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`_, which takes parameters in FIVE categories.
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154
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155 - a JSON file that contains layer information for a deep learning model.
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156
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157 - a data batch generator that converts raw data, such as images and genomic sequences, into numerical data to be able to fit the deep learning model. That the cycle of `batch conversion - fitting` occur in stream mode, also called on-line transformation, guarantees the training to be CPU and memory efficient. Reference: `galaxy_ml.preprocessors.FastaDNABatchGenerator`_, `galaxy_ml.preprocessors.FastaRNABatchGenerator`_, `galaxy_ml.preprocessors.FastaProteinBatchGenerator`_, `galaxy_ml.preprocessors.GenomicIntervalBatchGenerator`_.
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158
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159 - compile parameters, are mainly composed of loss function and optimizer.
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160
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161 - fit parameters, a group of variables that control the training process, referring to `galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`_ and `keras.io`_.
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162
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163 - other parameters, including `class_positive_factor`, `prediction_steps`, `seed` (random seed) and so on.
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164
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165
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166 **Output**
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167
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168 A zipped model file that could be used in `model_validation` tool or `hyperparameter search` tool.
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170 .. _`galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#kerasgbatchclassifier
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172 .. _`galaxy_ml.preprocessors.FastaDNABatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaDNABatchGenerator
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174 .. _`galaxy_ml.preprocessors.FastaRNABatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaRNABatchGenerator
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176 .. _`galaxy_ml.preprocessors.FastaProteinBatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaProteinBatchGenerator
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178 .. _`galaxy_ml.preprocessors.GenomicIntervalBatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#GenomicIntervalBatchGenerator
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180 .. _`keras.io`: https://keras.io/models/model/#fit_generator
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181
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182 ]]>
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183 </help>
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184 <citations>
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185 <expand macro="keras_citation"/>
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186 <expand macro="tensorflow_citation"/>
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187 </citations>
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188 </tool>