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comparison keras_batch_models.xml @ 17:08228c7fcf48 draft default tip

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
author bgruening
date Mon, 02 Oct 2023 08:18:30 +0000
parents 70846a2dd227
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16:967647f7bbaa 17:08228c7fcf48
174 174
175 - 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`_. 175 - 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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177 - compile parameters, are mainly composed of loss function and optimizer. 177 - compile parameters, are mainly composed of loss function and optimizer.
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179 - fit parameters, a group of variables that control the training process, referring to `galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`_ and `keras.io`_. 179 - fit parameters, a group of variables that control the training process, referring to `galaxy_ml.keras_galaxy_model.KerasGBatchClassifier`_ and Keras.
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181 - other parameters, including `class_positive_factor`, `prediction_steps`, `seed` (random seed) and so on. 181 - other parameters, including `class_positive_factor`, `prediction_steps`, `seed` (random seed) and so on.
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183 183
184 **Output** 184 **Output**
192 .. _`galaxy_ml.preprocessors.FastaRNABatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaRNABatchGenerator 192 .. _`galaxy_ml.preprocessors.FastaRNABatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaRNABatchGenerator
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194 .. _`galaxy_ml.preprocessors.FastaProteinBatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaProteinBatchGenerator 194 .. _`galaxy_ml.preprocessors.FastaProteinBatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#FastaProteinBatchGenerator
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196 .. _`galaxy_ml.preprocessors.GenomicIntervalBatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#GenomicIntervalBatchGenerator 196 .. _`galaxy_ml.preprocessors.GenomicIntervalBatchGenerator`: https://goeckslab.github.io/Galaxy-ML/APIs/keras-galaxy-models/#GenomicIntervalBatchGenerator
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198 .. _`keras.io`: https://keras.io/models/model/#fit_generator
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200 ]]> 198 ]]>
201 </help> 199 </help>
202 <citations> 200 <citations>
203 <expand macro="keras_citation" /> 201 <expand macro="keras_citation" />