Mercurial > repos > bgruening > sklearn_model_validation
annotate keras_deep_learning.py @ 32:be4f389a95d9 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8850f42c2c3763e614f7454c9c006f3d2ff572c0
author | bgruening |
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date | Fri, 27 May 2022 11:35:43 +0000 |
parents | 4b359039f09f |
children | 1fe00785190d |
rev | line source |
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19
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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1 import argparse |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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2 import json |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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3 import pickle |
de360b57a5ab
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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4 import warnings |
de360b57a5ab
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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5 from ast import literal_eval |
de360b57a5ab
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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6 |
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efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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7 import keras |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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8 import pandas as pd |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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9 import six |
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de360b57a5ab
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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10 from galaxy_ml.utils import get_search_params, SafeEval, try_get_attr |
de360b57a5ab
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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11 from keras.models import Model, Sequential |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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12 |
5895fe0b8bde
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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13 safe_eval = SafeEval() |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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14 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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15 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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16 def _handle_shape(literal): |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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17 """ |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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18 Eval integer or list/tuple of integers from string |
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efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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19 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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20 Parameters: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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21 ----------- |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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22 literal : str. |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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23 """ |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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24 literal = literal.strip() |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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25 if not literal: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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26 return None |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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27 try: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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28 return literal_eval(literal) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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29 except NameError as e: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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30 print(e) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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31 return literal |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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32 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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33 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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34 def _handle_regularizer(literal): |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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35 """ |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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36 Construct regularizer from string literal |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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37 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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38 Parameters |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 ---------- |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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40 literal : str. E.g. '(0.1, 0)' |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 """ |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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42 literal = literal.strip() |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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43 if not literal: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 return None |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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45 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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46 l1, l2 = literal_eval(literal) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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47 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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48 if not l1 and not l2: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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49 return None |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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50 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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51 if l1 is None: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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52 l1 = 0.0 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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53 if l2 is None: |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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54 l2 = 0.0 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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55 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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56 return keras.regularizers.l1_l2(l1=l1, l2=l2) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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57 |
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58 |
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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 def _handle_constraint(config): |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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60 """ |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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61 Construct constraint from galaxy tool parameters. |
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62 Suppose correct dictionary format |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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63 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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64 Parameters |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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65 ---------- |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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66 config : dict. E.g. |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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67 "bias_constraint": |
efbec977a47d
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68 {"constraint_options": |
efbec977a47d
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69 {"max_value":1.0, |
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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 "min_value":0.0, |
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71 "axis":"[0, 1, 2]" |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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72 }, |
efbec977a47d
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73 "constraint_type": |
efbec977a47d
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74 "MinMaxNorm" |
efbec977a47d
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75 } |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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76 """ |
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77 constraint_type = config["constraint_type"] |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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78 if constraint_type in ("None", ""): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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79 return None |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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80 |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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81 klass = getattr(keras.constraints, constraint_type) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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82 options = config.get("constraint_options", {}) |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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83 if "axis" in options: |
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84 options["axis"] = literal_eval(options["axis"]) |
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85 |
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86 return klass(**options) |
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87 |
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88 |
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89 def _handle_lambda(literal): |
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90 return None |
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91 |
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92 |
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93 def _handle_layer_parameters(params): |
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94 """ |
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95 Access to handle all kinds of parameters |
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96 """ |
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97 for key, value in six.iteritems(params): |
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98 if value in ("None", ""): |
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99 params[key] = None |
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100 continue |
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101 |
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102 if type(value) in [int, float, bool] or ( |
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103 type(value) is str and value.isalpha() |
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104 ): |
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105 continue |
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106 |
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107 if ( |
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108 key |
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109 in [ |
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110 "input_shape", |
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111 "noise_shape", |
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112 "shape", |
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113 "batch_shape", |
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114 "target_shape", |
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115 "dims", |
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116 "kernel_size", |
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117 "strides", |
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118 "dilation_rate", |
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119 "output_padding", |
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120 "cropping", |
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121 "size", |
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122 "padding", |
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123 "pool_size", |
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124 "axis", |
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125 "shared_axes", |
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126 ] |
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127 and isinstance(value, str) |
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128 ): |
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129 params[key] = _handle_shape(value) |
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130 |
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131 elif key.endswith("_regularizer") and isinstance(value, dict): |
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132 params[key] = _handle_regularizer(value) |
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133 |
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134 elif key.endswith("_constraint") and isinstance(value, dict): |
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135 params[key] = _handle_constraint(value) |
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136 |
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137 elif key == "function": # No support for lambda/function eval |
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138 params.pop(key) |
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139 |
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140 return params |
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141 |
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142 |
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143 def get_sequential_model(config): |
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144 """ |
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145 Construct keras Sequential model from Galaxy tool parameters |
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146 |
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147 Parameters: |
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148 ----------- |
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149 config : dictionary, galaxy tool parameters loaded by JSON |
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150 """ |
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151 model = Sequential() |
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152 input_shape = _handle_shape(config["input_shape"]) |
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153 layers = config["layers"] |
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154 for layer in layers: |
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155 options = layer["layer_selection"] |
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156 layer_type = options.pop("layer_type") |
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157 klass = getattr(keras.layers, layer_type) |
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158 kwargs = options.pop("kwargs", "") |
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159 |
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160 # parameters needs special care |
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161 options = _handle_layer_parameters(options) |
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162 |
20
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163 if kwargs: |
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164 kwargs = safe_eval("dict(" + kwargs + ")") |
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165 options.update(kwargs) |
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166 |
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167 # add input_shape to the first layer only |
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168 if not getattr(model, "_layers") and input_shape is not None: |
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169 options["input_shape"] = input_shape |
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170 |
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171 model.add(klass(**options)) |
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172 |
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173 return model |
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174 |
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175 |
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176 def get_functional_model(config): |
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177 """ |
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178 Construct keras functional model from Galaxy tool parameters |
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179 |
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180 Parameters |
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181 ----------- |
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182 config : dictionary, galaxy tool parameters loaded by JSON |
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183 """ |
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184 layers = config["layers"] |
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185 all_layers = [] |
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186 for layer in layers: |
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187 options = layer["layer_selection"] |
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188 layer_type = options.pop("layer_type") |
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189 klass = getattr(keras.layers, layer_type) |
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190 inbound_nodes = options.pop("inbound_nodes", None) |
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191 kwargs = options.pop("kwargs", "") |
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192 |
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193 # parameters needs special care |
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194 options = _handle_layer_parameters(options) |
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195 |
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196 if kwargs: |
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197 kwargs = safe_eval("dict(" + kwargs + ")") |
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198 options.update(kwargs) |
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199 |
19
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200 # merge layers |
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201 if "merging_layers" in options: |
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202 idxs = literal_eval(options.pop("merging_layers")) |
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203 merging_layers = [all_layers[i - 1] for i in idxs] |
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204 new_layer = klass(**options)(merging_layers) |
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205 # non-input layers |
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206 elif inbound_nodes is not None: |
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207 new_layer = klass(**options)(all_layers[inbound_nodes - 1]) |
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208 # input layers |
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209 else: |
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210 new_layer = klass(**options) |
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211 |
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212 all_layers.append(new_layer) |
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213 |
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214 input_indexes = _handle_shape(config["input_layers"]) |
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215 input_layers = [all_layers[i - 1] for i in input_indexes] |
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216 |
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217 output_indexes = _handle_shape(config["output_layers"]) |
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218 output_layers = [all_layers[i - 1] for i in output_indexes] |
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219 |
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220 return Model(inputs=input_layers, outputs=output_layers) |
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221 |
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222 |
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223 def get_batch_generator(config): |
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224 """ |
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225 Construct keras online data generator from Galaxy tool parameters |
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226 |
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227 Parameters |
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228 ----------- |
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229 config : dictionary, galaxy tool parameters loaded by JSON |
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230 """ |
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231 generator_type = config.pop("generator_type") |
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232 if generator_type == "none": |
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233 return None |
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234 |
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235 klass = try_get_attr("galaxy_ml.preprocessors", generator_type) |
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236 |
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237 if generator_type == "GenomicIntervalBatchGenerator": |
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238 config["ref_genome_path"] = "to_be_determined" |
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239 config["intervals_path"] = "to_be_determined" |
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240 config["target_path"] = "to_be_determined" |
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241 config["features"] = "to_be_determined" |
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242 else: |
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243 config["fasta_path"] = "to_be_determined" |
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244 |
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245 return klass(**config) |
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246 |
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247 |
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248 def config_keras_model(inputs, outfile): |
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249 """ |
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250 config keras model layers and output JSON |
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251 |
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252 Parameters |
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253 ---------- |
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254 inputs : dict |
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255 loaded galaxy tool parameters from `keras_model_config` |
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256 tool. |
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257 outfile : str |
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258 Path to galaxy dataset containing keras model JSON. |
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259 """ |
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260 model_type = inputs["model_selection"]["model_type"] |
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261 layers_config = inputs["model_selection"] |
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262 |
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263 if model_type == "sequential": |
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264 model = get_sequential_model(layers_config) |
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265 else: |
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266 model = get_functional_model(layers_config) |
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267 |
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268 json_string = model.to_json() |
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269 |
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270 with open(outfile, "w") as f: |
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271 json.dump(json.loads(json_string), f, indent=2) |
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272 |
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273 |
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274 def build_keras_model( |
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275 inputs, |
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276 outfile, |
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277 model_json, |
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278 infile_weights=None, |
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279 batch_mode=False, |
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280 outfile_params=None, |
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281 ): |
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282 """ |
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283 for `keras_model_builder` tool |
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284 |
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285 Parameters |
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286 ---------- |
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287 inputs : dict |
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288 loaded galaxy tool parameters from `keras_model_builder` tool. |
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289 outfile : str |
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290 Path to galaxy dataset containing the keras_galaxy model output. |
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291 model_json : str |
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292 Path to dataset containing keras model JSON. |
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293 infile_weights : str or None |
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294 If string, path to dataset containing model weights. |
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295 batch_mode : bool, default=False |
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296 Whether to build online batch classifier. |
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297 outfile_params : str, default=None |
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298 File path to search parameters output. |
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299 """ |
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300 with open(model_json, "r") as f: |
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301 json_model = json.load(f) |
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302 |
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303 config = json_model["config"] |
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304 |
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305 options = {} |
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306 |
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307 if json_model["class_name"] == "Sequential": |
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308 options["model_type"] = "sequential" |
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309 klass = Sequential |
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310 elif json_model["class_name"] == "Model": |
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311 options["model_type"] = "functional" |
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312 klass = Model |
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313 else: |
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314 raise ValueError("Unknow Keras model class: %s" % json_model["class_name"]) |
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315 |
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316 # load prefitted model |
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317 if inputs["mode_selection"]["mode_type"] == "prefitted": |
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318 estimator = klass.from_config(config) |
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319 estimator.load_weights(infile_weights) |
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320 # build train model |
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321 else: |
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322 cls_name = inputs["mode_selection"]["learning_type"] |
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323 klass = try_get_attr("galaxy_ml.keras_galaxy_models", cls_name) |
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324 |
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325 options["loss"] = inputs["mode_selection"]["compile_params"]["loss"] |
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326 options["optimizer"] = ( |
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327 inputs["mode_selection"]["compile_params"]["optimizer_selection"][ |
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328 "optimizer_type" |
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329 ] |
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330 ).lower() |
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331 |
30
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332 options.update( |
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333 ( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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334 inputs["mode_selection"]["compile_params"]["optimizer_selection"][ |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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335 "optimizer_options" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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336 ] |
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337 ) |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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338 ) |
19
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339 |
30
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340 train_metrics = inputs["mode_selection"]["compile_params"]["metrics"] |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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341 if train_metrics[-1] == "none": |
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342 train_metrics = train_metrics[:-1] |
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343 options["metrics"] = train_metrics |
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344 |
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345 options.update(inputs["mode_selection"]["fit_params"]) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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346 options["seed"] = inputs["mode_selection"]["random_seed"] |
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347 |
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348 if batch_mode: |
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349 generator = get_batch_generator( |
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350 inputs["mode_selection"]["generator_selection"] |
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351 ) |
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352 options["data_batch_generator"] = generator |
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353 options["prediction_steps"] = inputs["mode_selection"]["prediction_steps"] |
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354 options["class_positive_factor"] = inputs["mode_selection"][ |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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355 "class_positive_factor" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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356 ] |
19
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357 estimator = klass(config, **options) |
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358 if outfile_params: |
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359 hyper_params = get_search_params(estimator) |
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360 # TODO: remove this after making `verbose` tunable |
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361 for h_param in hyper_params: |
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362 if h_param[1].endswith("verbose"): |
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363 h_param[0] = "@" |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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364 df = pd.DataFrame(hyper_params, columns=["", "Parameter", "Value"]) |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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365 df.to_csv(outfile_params, sep="\t", index=False) |
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366 |
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367 print(repr(estimator)) |
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368 # save model by pickle |
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369 with open(outfile, "wb") as f: |
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370 pickle.dump(estimator, f, pickle.HIGHEST_PROTOCOL) |
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371 |
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372 |
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373 if __name__ == "__main__": |
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374 warnings.simplefilter("ignore") |
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375 |
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376 aparser = argparse.ArgumentParser() |
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377 aparser.add_argument("-i", "--inputs", dest="inputs", required=True) |
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378 aparser.add_argument("-m", "--model_json", dest="model_json") |
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379 aparser.add_argument("-t", "--tool_id", dest="tool_id") |
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380 aparser.add_argument("-w", "--infile_weights", dest="infile_weights") |
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381 aparser.add_argument("-o", "--outfile", dest="outfile") |
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382 aparser.add_argument("-p", "--outfile_params", dest="outfile_params") |
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383 args = aparser.parse_args() |
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384 |
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385 input_json_path = args.inputs |
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386 with open(input_json_path, "r") as param_handler: |
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387 inputs = json.load(param_handler) |
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388 |
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389 tool_id = args.tool_id |
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390 outfile = args.outfile |
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391 outfile_params = args.outfile_params |
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392 model_json = args.model_json |
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393 infile_weights = args.infile_weights |
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394 |
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395 # for keras_model_config tool |
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396 if tool_id == "keras_model_config": |
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397 config_keras_model(inputs, outfile) |
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398 |
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399 # for keras_model_builder tool |
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400 else: |
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401 batch_mode = False |
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402 if tool_id == "keras_batch_models": |
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403 batch_mode = True |
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404 |
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405 build_keras_model( |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
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406 inputs=inputs, |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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407 model_json=model_json, |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
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diff
changeset
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408 infile_weights=infile_weights, |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
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409 batch_mode=batch_mode, |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
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410 outfile=outfile, |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
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411 outfile_params=outfile_params, |
4b359039f09f
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
bgruening
parents:
29
diff
changeset
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412 ) |