EmbeddedMontiArc issueshttps://git.rwth-aachen.de/groups/monticore/EmbeddedMontiArc/-/issues2023-06-07T18:30:30+02:00https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/110Documentation of AutoML techniques2023-06-07T18:30:30+02:00aixaiDocumentation of AutoML techniquesExtend the Readme of EMADL2CPP.
Copy AutoML explainations from our thesisExtend the Readme of EMADL2CPP.
Copy AutoML explainations from our thesisTobias HörnschemeyerNazish QamarHiroshi HamanoAkashKumarDSTobias Hörnschemeyerhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/gans/3d-gan/-/issues/23D Gan Training fails due to configuration errors2023-03-02T17:55:58+01:00Martin Fitzke3D Gan Training fails due to configuration errors`Train3D-GAN` pipeline fails due to configuration errors in `Generator.conf` file.`Train3D-GAN` pipeline fails due to configuration errors in `Generator.conf` file.aixaiaixaihttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/gans/3d-gan/-/issues/1JAR not generated because of MXNET error2023-03-02T17:54:18+01:00Martin FitzkeJAR not generated because of MXNET errorJAR pipeline fails with this
```
mxnet.base.MXNetError: MXNetError: Error in operator conv5_deconvolution0: [16:46:17] ../src/operator/nn/deconvolution.cc:105: If not using CUDNN, only 1D or 2D Deconvolution is supported
```
C++ Library ...JAR pipeline fails with this
```
mxnet.base.MXNetError: MXNetError: Error in operator conv5_deconvolution0: [16:46:17] ../src/operator/nn/deconvolution.cc:105: If not using CUDNN, only 1D or 2D Deconvolution is supported
```
C++ Library is probably in the wrong versionaixaiaixaihttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/109Open to-dos MA Mulhem2023-02-12T17:37:21+01:00Feras MulhemOpen to-dos MA MulhemOpen to-dos derived from Mulhem's Master thesis
- #108
- #107
- #106Open to-dos derived from Mulhem's Master thesis
- #108
- #107
- #106aixaiaixaihttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/108Workflow adjustment for multiple networks2023-02-12T17:37:21+01:00Feras MulhemWorkflow adjustment for multiple networks**Current situation**
The current workflow assumes one EMADL component representing a neural network. For applications like the MNISTCalculator we need to deal with multiple networks, possibly trained with different training configurati...**Current situation**
The current workflow assumes one EMADL component representing a neural network. For applications like the MNISTCalculator we need to deal with multiple networks, possibly trained with different training configurations.
**Tasks**
- [ ] When an EMADL model is given, iterate the model looking up all networks.
**Notes**
- The [EMADLGenerator] implemented (https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/main/java/de/monticore/lang/monticar/emadl/generator/EMADLGenerator.java#L988) this functionality
- An example of how to resolve a neural network in an emadl model is given [here](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/main/java/de/monticore/mlpipelines/workflow/AbstractWorkflow.java#L100)https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/107Naming conventions for emadl network components2023-02-12T17:37:21+01:00Feras MulhemNaming conventions for emadl network components**Current situation**
- A [naming convention](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/main/java/de/monticore/mlpipelines/workflow/AbstractWorkflow.java#L67) is followed to resolve conf...**Current situation**
- A [naming convention](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/main/java/de/monticore/mlpipelines/workflow/AbstractWorkflow.java#L67) is followed to resolve configuration such that these are assumed to have the _full name_ of a to-be-trained neural network.
**Tasks**
- [ ] Adjust the naming conventions to exclude the _package name_ from the network full name
- [ ] Adjust the names of the corresponding configurations accordingly. The configurations need also to have package information explicitly ( i.e. _package MyPackage_)https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/106Link pipeline configurations to their reference model2023-04-25T19:50:07+02:00Feras MulhemLink pipeline configurations to their reference modelThis issue aims to enable the toolchain to resolve the correct pipeline reference model based on the pipeline configuration. This mechanism is similar to resolving the training-time architectures using training configuration.
**Tasks**
...This issue aims to enable the toolchain to resolve the correct pipeline reference model based on the pipeline configuration. This mechanism is similar to resolving the training-time architectures using training configuration.
**Tasks**
- [ ] Add a schema definition that contains an entry for the desired reference model
- [ ] in the pipeline configuration add an entry that determines which schema shall be used ( for example _learning method_)
- [ ] Resolve the corresponding schema definitions for the given pipeline configuration
- [ ] Validate the pipeline configuration (similar to [training configurations](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/main/java/de/monticore/mlpipelines/workflow/AbstractWorkflow.java#L139))
**Notes**
- The above-mentioneed steps shall be added as part of the commen [workflow ](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/main/java/de/monticore/mlpipelines/workflow/AbstractWorkflow.java#L139 ) for ML pipelines.
- Currently, the workflow resolves a default pipeline reference modelTobias HörnschemeyerNazish QamarHiroshi HamanoAkashKumarDSTobias Hörnschemeyerhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/47Merge the branch ma_sc to new emadl2cpp2022-11-16T15:56:28+01:00Sonam Raju ChughMerge the branch ma_sc to new emadl2cppOnce new emadl2cpp is created-
Merge the test cases (GenerationTest.java, CustomLayerTest.java)(test cases for mnist, loadnetwork, custom layer)
Merge the Backend.java (which has new backend pytorch)
related branch: [ma_sc](https://git....Once new emadl2cpp is created-
Merge the test cases (GenerationTest.java, CustomLayerTest.java)(test cases for mnist, loadnetwork, custom layer)
Merge the Backend.java (which has new backend pytorch)
related branch: [ma_sc](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/tree/ma_sc)
**Tasks**
- [ ] perform a health check on the testsTobias HörnschemeyerFeras MulhemTobias Hörnschemeyerhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/46Please create a PyTorch docker image2022-11-09T09:25:16+01:00Evgeny KusmenkoPlease create a PyTorch docker image- under test/resources/pytorch
- create a CI pipeline building and pushing the image to the registry- under test/resources/pytorch
- create a CI pipeline building and pushing the image to the registrySonam Raju ChughSonam Raju Chughhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMAM2Middleware/-/issues/34Extend ROS topics to accept integer arrays for state representation2022-11-11T19:39:14+01:00Anis Abdollahi-SissanExtend ROS topics to accept integer arrays for state representationWhen using the EMAM2Middleware to generate a reinforcement learning agent, which is connected via ros-gym to python, defining the state as an integer array in python leads to an error, because the middleware initializes the state topic i...When using the EMAM2Middleware to generate a reinforcement learning agent, which is connected via ros-gym to python, defining the state as an integer array in python leads to an error, because the middleware initializes the state topic in ROS as Float32MultiArray, regardless of the definition in the python files.
[This](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/reinforcement_learning/topologyoptimizer/-/blob/main/additional_files/Middleware/Environment.ftl) file implements Int32MultiArray as the default topic type for the state.
To resolve this issue, it would be necessary to automatically switch between the Float- and Integer-representation for the ROS state topic.
This can be implemented in the template file for the environment of the agent.Lukas BramThilo MetzlaffLukas Bramhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/reinforcement_learning/coopmontisimautopilot/-/issues/2Update Readme.md2022-10-06T17:52:03+02:00Evgeny KusmenkoUpdate Readme.md- mention in readme.md:
- problem with GPU training on cluster
-- mention in readme.md:
- problem with GPU training on cluster
-Rodion PrikhodovskyTil MohrRodion Prikhodovskyhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/reinforcement_learning/coopmontisimautopilot/-/issues/1Move to emadl-maven-plugin2022-09-21T15:00:10+02:00Evgeny KusmenkoMove to emadl-maven-plugin- please use emadl-maven-plugin instead of shell based build in CI
- please add streamtests- please use emadl-maven-plugin instead of shell based build in CI
- please add streamtestsRodion PrikhodovskyTil MohrRodion Prikhodovskyhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/reinforcement_learning/roboschoolhalfcheetah/-/issues/1Move CI to emadl-maven-plugin2022-09-21T14:49:42+02:00Evgeny KusmenkoMove CI to emadl-maven-plugin- Please use emadl-maven-plugin in CI
- please remove shell based CI
- please add stream tests- Please use emadl-maven-plugin in CI
- please remove shell based CI
- please add stream testsYuyuan LiuYuyuan Liuhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/reinforcement_learning/ataripong/-/issues/1Create maven-based CI2022-09-23T20:00:11+02:00Evgeny KusmenkoCreate maven-based CI- please create emadl-maven-plugin based CI
- please remove shell script based build
- please add stream tests- please create emadl-maven-plugin based CI
- please remove shell script based build
- please add stream testsYuyuan LiuYuyuan Liuhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/45Explicit input and output shape required2022-09-02T17:30:04+02:00Luis LaasExplicit input and output shape requiredA component currently requires explicit input and output shapes to be successfully parsed.
This works:
package rangePrediction;
component MLPL{
ports in Q(0:100)^{1} data,
out Q(-oo:+oo)^{1} prediction;
...A component currently requires explicit input and output shapes to be successfully parsed.
This works:
package rangePrediction;
component MLPL{
ports in Q(0:100)^{1} data,
out Q(-oo:+oo)^{1} prediction;
implementation CNN {
data -> prediction;
}
}
However this does not work:
package rangePrediction;
component MLPL{
ports in Q(0:100) data,
out Q(-oo:+oo) prediction;
implementation CNN {
data -> prediction;
}
}
Generating code terminates with this Exception:
Exception in thread "main" java.lang.IllegalStateException: Unknown port type
The expected behavior is that both versions work.
generator-version: 0.5.3
environment: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/generators/emadl2cpp/mxnet/190https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/mnistcalculator/-/issues/18Design a streamtest template for MNISTCalculator2022-07-25T17:10:09+02:00Yuyuan LiuDesign a streamtest template for MNISTCalculatorTo implement:
- A generator for EMADL `streamtest` in `EMADL-Generator`
- (If necessary) An Expansion of grammar in `languagecommon` project.To implement:
- A generator for EMADL `streamtest` in `EMADL-Generator`
- (If necessary) An Expansion of grammar in `languagecommon` project.Yuyuan LiuYuyuan Liuhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/mnistcalculator/-/issues/17Add a cpp unittest2022-07-15T17:00:09+02:00Yuyuan LiuAdd a cpp unittestInstead of calling a executable with the images as parameters, implement a cpp file to run the unittests.Instead of calling a executable with the images as parameters, implement a cpp file to run the unittests.Yuyuan LiuYuyuan Liuhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/37Add CustomLayerTest to CI2022-11-09T10:19:04+01:00Evgeny KusmenkoAdd CustomLayerTest to CIhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Caffe2/-/issues/7move train routine to a dedicated trainer2022-05-04T14:01:28+02:00Jonas Ritzmove train routine to a dedicated trainerin the other backends, the train(...) routine is implemented in specific trainers, e.g. CNNSupervisedTrainer, while here, it is implemented in the CNNCreator, but does not really belong therein the other backends, the train(...) routine is implemented in specific trainers, e.g. CNNSupervisedTrainer, while here, it is implemented in the CNNCreator, but does not really belong therehttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Caffe2/-/issues/6Data Loading of hdf5 files2022-05-04T13:59:48+02:00Jonas RitzData Loading of hdf5 filesright now, this backend just supports loading lmdb files, there is no such thin as an extra dedicated dataloader compared to the other backends where one could implement cleaningright now, this backend just supports loading lmdb files, there is no such thin as an extra dedicated dataloader compared to the other backends where one could implement cleaning