Mercurial > repos > bgruening > keras_model_builder
annotate keras_model_builder.xml @ 16:f7ecdde4b201 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 3c1e6c72303cfd8a5fd014734f18402b97f8ecb5
author | bgruening |
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date | Fri, 22 Sep 2023 17:45:38 +0000 |
parents | 624e2afa1313 |
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624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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1 <tool id="keras_model_builder" name="Create deep learning model" version="@VERSION@" profile="@PROFILE@"> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 <description>with an optimizer, loss function and fit parameters</description> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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3 <macros> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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4 <import>main_macros.xml</import> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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5 <import>keras_macros.xml</import> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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6 </macros> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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7 <expand macro="python_requirements" /> |
449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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8 <expand macro="macro_stdio" /> |
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624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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9 <version_command>echo "@VERSION@"</version_command> |
624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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10 <command> |
624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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11 <![CDATA[ |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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12 python '$__tool_directory__/keras_deep_learning.py' |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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13 --inputs '$inputs' |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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14 --tool_id 'keras_model_builder' |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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15 --outfile '$outfile' |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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16 --model_json '$mode_selection.infile_json' |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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17 ]]> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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18 </command> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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19 <configfiles> |
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449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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20 <inputs name="inputs" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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21 </configfiles> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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22 <inputs> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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23 <conditional name="mode_selection"> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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24 <param name="mode_type" type="select" label="Choose a building mode"> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 <option value="train_model" selected="true">Build a training model</option> |
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624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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26 <!--option value="prefitted">Load a pretrained model for prediction</option>--> |
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818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 </param> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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28 <when value="train_model"> |
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449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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29 <param name="infile_json" type="data" format="json" label="Select the dataset containing model configurations (JSON)" /> |
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818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 <param name="learning_type" type="select" label="Do classification or regression?"> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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31 <option value="KerasGClassifier">KerasGClassifier</option> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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32 <option value="KerasGRegressor">KerasGRegressor</option> |
818896cd2213
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 </param> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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34 <expand macro="keras_compile_params_section" /> |
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624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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35 <expand macro="keras_fit_params_section"> |
624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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36 <param name="validation_split" type="float" value="0.1" optional="true" label="The proportion of training data to set aside as validation set." help="Will be ignored if `validation_data` is set explicitly, such as in `Deep learning training and evaluation` tool." /> |
624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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37 </expand> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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38 <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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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 </when> |
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624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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40 <!--when value="prefitted"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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41 <param name="infile_json" type="data" format="json" label="Select the dataset containing model configurations (JSON)" /> |
449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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42 <param name="infile_weights" type="data" format="h5" label="Select the dataset containing keras layers weights" /> |
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624e2afa1313
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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43 </when>--> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 </conditional> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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45 </inputs> |
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46 <outputs> |
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47 <data format="h5mlm" name="outfile" label="Keras Model Builder on ${on_string}" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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48 </outputs> |
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49 <tests> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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50 <test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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51 <conditional name="mode_selection"> |
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449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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52 <param name="infile_json" value="keras01.json" ftype="json" /> |
449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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53 <param name="learning_type" value="KerasGRegressor" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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54 <section name="fit_params"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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55 <param name="epochs" value="100" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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56 </section> |
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57 </conditional> |
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58 <output name="outfile" file="keras_model01" compare="sim_size" delta="20" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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59 </test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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60 <test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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61 <conditional name="mode_selection"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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62 <param name="infile_json" value="keras02.json" ftype="json" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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63 <section name="compile_params"> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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64 <conditional name="optimizer_selection"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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65 <param name="optimizer_type" value="Adam" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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66 </conditional> |
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67 </section> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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68 <section name="fit_params"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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69 <param name="epochs" value="100" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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70 </section> |
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71 </conditional> |
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72 <output name="outfile" file="keras_model02" compare="sim_size" delta="20" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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73 </test> |
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74 <!--test> |
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75 <conditional name="mode_selection"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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76 <param name="mode_type" value="prefitted" /> |
449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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77 <param name="infile_json" value="keras03.json" ftype="json" /> |
449a757be9c9
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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78 <param name="infile_weights" value="keras_save_weights01.h5" ftype="h5" /> |
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79 </conditional> |
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80 <output name="outfile" file="keras_prefitted01.zip" compare="sim_size" delta="5" /> |
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81 </test>--> |
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82 <test> |
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83 <conditional name="mode_selection"> |
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84 <param name="infile_json" value="keras04.json" ftype="json" /> |
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85 <param name="learning_type" value="KerasGRegressor" /> |
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86 <section name="compile_params"> |
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87 <conditional name="optimizer_selection"> |
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88 <param name="optimizer_type" value="Adam" /> |
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89 </conditional> |
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90 <param name="metrics" value="mse" /> |
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91 <param name="loss" value="mean_squared_error" /> |
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92 </section> |
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93 <section name="fit_params"> |
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94 <param name="epochs" value="100" /> |
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95 </section> |
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96 <param name="random_seed" value="42" /> |
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97 </conditional> |
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98 <output name="outfile" file="keras_model04" compare="sim_size" delta="20" /> |
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99 </test> |
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100 </tests> |
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101 <help> |
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102 <![CDATA[ |
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103 **Help** |
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104 |
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105 **What it does** |
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106 |
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107 Creates an estimator object (classifier or regressor) by using the architecture JSON from 'Create architecture' tool and adding an optimizer, loss function and other fit parameters. The fit parameters include the number of training epochs and batch size. Multiple attributes of an optimizer can also be set. A pre-trained deep learning model can also be used with this tool. |
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108 |
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109 **Return** |
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110 |
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111 An estimator object which can be used to train on a dataset. |
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112 |
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113 **How to compile the architecture using this tool?** |
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114 |
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115 1. Choose the architecture building mode. For example - choose "Build a training model". |
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116 2. Attach an architecture JSON file (obtained after executing "Create architecture" tool) which contains information about multiple layers. |
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117 3. Select a loss function. For example - for classification tasks, choose 'cross entropy' losses and for regression tasks, choose 'mean squared' or 'mean absolute' losses. |
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118 4. Choose an optimizer which minimizes the loss computed by the loss function. Multiple attributes of the chosen optimizer can be modified. 'RMSProp' and 'Adam' are some of the popular optimizers. |
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119 5. Insert the number of iterations (epochs) and the size of training batches (batch_size). |
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120 6. Execute the tool to get a compiled estimator object. |
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121 |
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122 ]]> |
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123 </help> |
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124 <citations> |
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125 <expand macro="keras_citation" /> |
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126 <expand macro="tensorflow_citation" /> |
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127 </citations> |
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128 </tool> |