generators issueshttps://git.rwth-aachen.de/groups/monticore/EmbeddedMontiArc/generators/-/issues2022-11-27T11:35:22+01:00https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/52Create parser for MontiAnna languages2022-11-27T11:35:22+01:00Feras MulhemCreate parser for MontiAnna languagesDifferent ways can be observed that are used to parse EMADL models and their related models. The goal of this issue is to modularise und unify the parsing interface.
**Included languages**
- ConfLang
- SchemaLang
- EmbeddedMontiArc (EMA...Different ways can be observed that are used to parse EMADL models and their related models. The goal of this issue is to modularise und unify the parsing interface.
**Included languages**
- ConfLang
- SchemaLang
- EmbeddedMontiArc (EMA)
**Tasks**
- [x] create parsing classes
- [x] parse a ConfLang configuration and return symbol-augmented AST
- [x] parse a SchemaLang schema and return symbol-augmented AST
- [x] parse an EMA model and return symbol-augmented AST
- [x] parse EMADL model with CNN architecture into symbol-augmented AST
- [x] test it on [LeNetNetwork](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/blob/master/src/test/resources/models/mnist/LeNetNetwork.emadl)
**Notes**
- The lenet network is crucial for the [evaluation ](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/mnistpredictor) part and has priorityTobias HörnschemeyerFeras MulhemTobias Hörnschemeyer2022-11-28https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/51Create EfficientNet algorithm2022-11-25T12:44:31+01:00Evgeny KusmenkoCreate EfficientNet algorithmTobias HörnschemeyerNazish QamarTobias Hörnschemeyer2022-11-21https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/50Create AdaNet algorithm2022-11-16T16:07:55+01:00Evgeny KusmenkoCreate AdaNet algorithmTobias HörnschemeyerNazish QamarTobias Hörnschemeyer2022-11-21https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/49Create Workflow for Autonomous Pipeline Execution2023-01-28T22:17:41+01:00Evgeny KusmenkoCreate Workflow for Autonomous Pipeline ExecutionIn montipipes#1 a python script was generated to execute a python pipeline. In this issue **minimal** workflow shall be created to test functionality integration into the framework
**Tasks**
- [x] dedicated classes to execute the follow...In montipipes#1 a python script was generated to execute a python pipeline. In this issue **minimal** workflow shall be created to test functionality integration into the framework
**Tasks**
- [x] dedicated classes to execute the following steps
- [x] parsing
- [x] parse appropriate pipeline model
- [x] parse pipeline configuration
- [x] parse training configuration
- [x] symbol table for EMA pipeline
- [x] symbol table for training and pipeline configurations
- [x] check CoCos
- [x] inter-model validations (schemas / configurations):
- [x] generate backend-related artefacts
- [x] wrap EMADLGenerator with new main generator (MontiAnnaGenerator)
- [x] refactor MontiAnnaGenerator using EMADLGenerator functionality
- [x] provide python training configuration
- [x] use default if not generated
- [x] generate the configuration
- [x] choose the appropriate schema API
- [x] calculate execution semantic
- [x] generate pipeline script
- [x] execute pipeline
- [x] read results
- [x] Discuss TODOS
**Issues**
- [x] Problem with parsing LeNet model with generic parameters
**Notes**
- EMADLGenerator for inspiration
- Defaults are to be used to create quick demonstration
- Only PyTorch is supported as backend for nowTobias HörnschemeyerFeras MulhemNazish QamarTobias Hörnschemeyer2022-12-30https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/48Extend Conf Schema for Network Optimizers2022-11-07T10:24:57+01:00Evgeny KusmenkoExtend Conf Schema for Network Optimizerssimilarly to `optimizer:sgd {...}` we want to allow the definition of `network_optimizer` parameters. Since depending on the concrete optimizer it might have varying parameters, e.g. alpha, beta in the case of efficient net, it should be...similarly to `optimizer:sgd {...}` we want to allow the definition of `network_optimizer` parameters. Since depending on the concrete optimizer it might have varying parameters, e.g. alpha, beta in the case of efficient net, it should be written in a nested way similarly to the optimizer example as `network_optimizer:efficientnet {efficientnet specific params come here}` or `network_optimizer:adanet{adanetspecific params come here}`Hiroshi HamanoAkashKumarDSHiroshi Hamano2022-10-18https://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/EMADL2CPP/-/issues/44Custom Layers2022-08-31T14:53:38+02:00Evgeny KusmenkoCustom LayersPlease implement custom layers for the PyTorch backendPlease implement custom layers for the PyTorch backendSonam Raju ChughSonam Raju Chugh2022-08-24https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/42AutoML: Architecture Search2023-05-29T13:29:06+02:00Evgeny KusmenkoAutoML: Architecture Search- Please extend the framework to optimize the MontiAnna neural architecture for a given learning problem
- create tests for your framework
- create a model in the MNISTCalculator project X
- create a CI experiment in the MNISTCalculator ...- Please extend the framework to optimize the MontiAnna neural architecture for a given learning problem
- create tests for your framework
- create a model in the MNISTCalculator project X
- create a CI experiment in the MNISTCalculator project
- please create an AutoML pipelineTobias HörnschemeyerNazish QamarTobias Hörnschemeyer2023-05-01https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/41Implement LoadNetwork layer for PyTorch backend2022-10-11T11:19:12+02:00Evgeny KusmenkoImplement LoadNetwork layer for PyTorch backendSonam Raju ChughSonam Raju Chugh2022-09-22https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/40Execution Order2022-10-11T11:24:01+02:00Evgeny KusmenkoExecution OrderUse Execution Semantics to determine the correct order of the component executionUse Execution Semantics to determine the correct order of the component executionFeras MulhemFeras Mulhem2022-10-05https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/39Introduce String types in EMA2022-10-11T11:39:44+02:00Evgeny KusmenkoIntroduce String types in EMA- make it possible to use String as a type for ports and component parameters
- write tests
- This [reference model](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/mnistcalculator/-/blob/16-pytorch/pytorch/predefined-...- make it possible to use String as a type for ports and component parameters
- write tests
- This [reference model](https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/applications/mnistcalculator/-/blob/16-pytorch/pytorch/predefined-pipeline/src/test/resources/schemas/referencemodels/Training_Pipeline.ema) of a machine learning pipeline would parse when trying to provide String parameters in component definitions, even though no explicit support for Strings seems to take place. However, trying to instantiate the corresponding component, here `instance Data_Access ("path.to.datasource") data_access_step;` would lead to a parsing error. To reproduce this, it is sufficient to try to parse the model with the parsing API provided by the EMA language.Nazish QamarAkashKumarDSNazish Qamar2022-09-27https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/38Validation Mechanism for Components2022-10-11T11:40:17+02:00Evgeny KusmenkoValidation Mechanism for Componentsallow parameterizable components in conflang based on the components of a reference modelallow parameterizable components in conflang based on the components of a reference modelFeras MulhemFeras Mulhem2022-09-24https://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/cnnarch2x/-/issues/3Schema Python API2023-01-19T13:41:39+01:00Feras MulhemSchema Python APIFeras MulhemFeras Mulhem2022-11-30https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Gluon/-/issues/8Issues with CNNAutoencodeTrainer.ftl2022-02-08T23:52:53+01:00Nils BaumannIssues with CNNAutoencodeTrainer.ftlWhen trying to run my project with emadl:train and dependency:resolve I get an Error in the CNNAutoencerTrainer.ftl file in line 216 and 323. I uploaded the stack trace for one of those. (It shows 322 because I tried removing line 216)
[...When trying to run my project with emadl:train and dependency:resolve I get an Error in the CNNAutoencerTrainer.ftl file in line 216 and 323. I uploaded the stack trace for one of those. (It shows 322 because I tried removing line 216)
[FTLStackTrace](/uploads/04d53805e6c2f67207ea487d28d0da1c/FTLStackTrace)Furkan CelikFurkan Celikhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/35Generation Test fails2022-07-08T15:51:43+02:00Evgeny KusmenkoGeneration Test fails@nils_baumann the generation test fails in master, please fix the expected target code@nils_baumann the generation test fails in master, please fix the expected target codeNils BaumannNils Baumannhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Gluon/-/issues/7Generalize classification specific code to be able to tackle regression tasks...2022-05-04T14:02:01+02:00Jonas RitzGeneralize classification specific code to be able to tackle regression tasks as wellhttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Gluon/-/blob/master/src/main/resources/templates/gluon/CNNSupervisedTrainer.ftl#L608
This code line e.g. will cause a termination when training a regression task n...https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/CNNArch2Gluon/-/blob/master/src/main/resources/templates/gluon/CNNSupervisedTrainer.ftl#L608
This code line e.g. will cause a termination when training a regression task network.https://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/34MXNet Docker Build fails2022-07-08T15:52:15+02:00Evgeny KusmenkoMXNet Docker Build failsEvgeny KusmenkoEvgeny Kusmenkohttps://git.rwth-aachen.de/monticore/EmbeddedMontiArc/generators/EMADL2CPP/-/issues/28link to docker files not working2021-11-10T11:05:51+01:00Jonas Ritzlink to docker files not workingThe link to the docker files in the first line of subsection Prerequisites in readme.md does not seem to work properly. (404)The link to the docker files in the first line of subsection Prerequisites in readme.md does not seem to work properly. (404)