romeokienzler

romeokienzler

Member Since 8 years ago

CTO and Chief Data Scientist, STSM, IBM CODAIT, Associate Professor for Artificial Intelligence at FH Berne - IBM Academy of Technology, Switzerland

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356 contributions in the last year

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⚡ Project containig related material for my TensorFlow articles
⚡ Sample application from Discover IoT
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Activity
Aug
19
1 month ago
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issue

romeokienzler issue elyra-ai/elyra

romeokienzler
romeokienzler

Pipeline Editor: Render ("galaxy inspired") component configuration UI

Is your feature request related to a problem? Please describe. Currently, notebooks only support rendering text fields based on parsed environment variables. Also, KFP pipeline components only support rudimentary parameter descriptions (e.g. type)

This way a complex component like a DL model can't be properly parameterized - especially if parameter visibility is dependent on the choice of other parameters (e.g. kernel type is only a valid option if kernalized regression is chosen)

Describe the solution you'd like Please have a look at this "galaxy tool" - a galaxy tool is a component for the galaxy pipeline tool. In this part of the XML the actual behavior of the property editing UI is expressed (including UI components only visible under certain circumstances)

I'd like to see something similar for Elyra. The configuration could be included in a cell in the notebook so that a citizen data scientist can edit it as well

Either the XML can be used 1:1 or an equivalent can be used. If should be evaluated if the code base from Galaxy could be used (either by proposing the Galaxy team to externalize this functionality so that it becomes a dependency for Galaxy and Elyra) or just copying the code.

Describe alternatives you've considered There are not alternatives

Additional context Example of the component configuration dialog in galaxy image

Activity icon
issue

romeokienzler issue comment elyra-ai/elyra

romeokienzler
romeokienzler

Pipeline Editor: Render ("galaxy inspired") component configuration UI

Is your feature request related to a problem? Please describe. Currently, notebooks only support rendering text fields based on parsed environment variables. Also, KFP pipeline components only support rudimentary parameter descriptions (e.g. type)

This way a complex component like a DL model can't be properly parameterized - especially if parameter visibility is dependent on the choice of other parameters (e.g. kernel type is only a valid option if kernalized regression is chosen)

Describe the solution you'd like Please have a look at this "galaxy tool" - a galaxy tool is a component for the galaxy pipeline tool. In this part of the XML the actual behavior of the property editing UI is expressed (including UI components only visible under certain circumstances)

I'd like to see something similar for Elyra. The configuration could be included in a cell in the notebook so that a citizen data scientist can edit it as well

Either the XML can be used 1:1 or an equivalent can be used. If should be evaluated if the code base from Galaxy could be used (either by proposing the Galaxy team to externalize this functionality so that it becomes a dependency for Galaxy and Elyra) or just copying the code.

Describe alternatives you've considered There are not alternatives

Additional context Example of the component configuration dialog in galaxy image

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romeokienzler push IBM/claimed

romeokienzler
romeokienzler

commit sha: aa48af7990d8b75471807abba985c12525a6ca8a

push time in 1 month ago
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1 month ago
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2 months ago
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romeokienzler push romeokienzler/c3

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romeokienzler

add support for parsing description and data type

commit sha: 6ff1149db694ac0a5427b00caada1aad8f6deeff

push time in 2 months ago
Aug
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2 months ago
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10
2 months ago
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romeokienzler push IBM/claimed

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romeokienzler

commit sha: e34071e5dd5b9858139b89cfd085167f22e7f708

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romeokienzler push romeokienzler/component-library

romeokienzler
romeokienzler

support spark on different python versions

commit sha: 348dc9f342a96d52cfc2656e1f778cc49b5718ac

push time in 2 months ago
Aug
9
2 months ago