Martin Gabdushev
Martin Gabdushev
### 🚀 Feature Request We should delete untaged docker images because they use extra space. ### Proposal - [ ] Github workflow script on cron. - [Github docker registry api...
### 🚀 Feature Request Create runner objects for computing handling. We just pass function `func` and `args` and `kwargs` via `__call__`. - `etna.auto.runner.LocalRunner` would just call passed function with given...
### 🚀 Feature Request Create class `etna.auto.optuna.Optuna` which would handle logic around using optuna: - method `tune` runs `study.optimize` via given `runner` Copy `etna.auto.optuna.sampler.ConfigSampler` as is. ### Proposal `Optuna`: ```python...
N.B. Blocked by #854 , #853 ### 🚀 Feature Request Create `etna.auto.Auto` class which supposed to search optimal solution from defined config pool. - Config pool could be extended -...
### 🚀 Feature Request Add `MLPModel` model for etna deep model family ### Proposal * You can use [as ref](https://github.com/tinkoff-ai/etna/blob/master/etna/models/nn/rnn.py) ```python class MLPNet(DeepBaseNet): def __init__( self, input_size: int, hidden_size: List[int],...
### Preposition: We have multiple models and feature generators to use. We don't know what model or features to choose from. We have limited cpu and time resources. We have...
### 🚀 Feature Request Implement base class for probabilistic. Currently our `DeepBaseModel` can only make `raw_predict` for scalar values. It isn't possible to implement models that predict distributions. ### Proposal...
**IMPORTANT: Please do not create a Pull Request without creating an issue first.** ## Before submitting (must do checklist) - [ ] Did you read the [contribution guide](https://github.com/tinkoff-ai/etna/blob/master/CONTRIBUTING.md)? - [...
### 🚀 Feature Request We have synthetic datasets now. It's helpfull for model sanity checks and testing. But real data is more complex. ### Motivation - Performance testing of frequently...
### 🚀 Feature Request ```python class Dataset: train: TSDataset test: TSDataset dataset_path: str # url or repositary url freq: str known_future: Optional[List[Feature]] unknown_future: Optional[List[Feature]] cache_path: Optional[pathlib.Path] metadata: dict tags: List[str]...