Kilian/online offline adaptation

[KilianFt]

@CodiumAI-Agent /review

[CodiumAI-Agent]

PR Analysis

• 🎯 Main theme: Implementing offline adaptation for the model and integrating wandb for hyperparameter tuning.

• 📝 PR summary: This PR introduces offline adaptation for the model, which is explored in the newly added 'offline_adaptation_sweep.py'. The PR also integrates wandb for hyperparameter tuning and implements a sweep configuration. Additionally, the PR refactors the code by moving some functions to a new file 'training.py' and modifies the 'pretrain_model.py' to use the wandb configuration.

• 📌 Type of PR: Enhancement

• 🧪 Relevant tests added: No

• ⏱️ Estimated effort to review [1-5]: 4, due to the significant amount of new code added, and the complexity of the changes, including the integration of a new library (wandb) and the implementation of a new feature (offline adaptation).

• 🔒 Security concerns: No security concerns found

  PR Feedback

• 💡 General suggestions: The PR introduces significant changes and new features, including offline adaptation and wandb integration. It would be beneficial to include unit tests for these new features to ensure they work as expected and prevent future regressions. Additionally, it's recommended to add error handling for the new external calls, especially for the wandb calls.

• 🤖 Code feedback:

  • relevant file: offline_adaptation_sweep.py suggestion: It's recommended to move the hardcoded 'episode_filenames' to a configuration file or make it a parameter. This would make the code more flexible and easier to maintain. [important] relevant line: [episode_filenames =

  • relevant file: pretrain_model.py suggestion: The 'train_emg_decoder' function has a 'use_ninapro' parameter that changes the behavior of the function significantly. It's recommended to split this function into two separate functions, one for each behavior. This would improve the readability and maintainability of the code. [medium] relevant line: def train_emg_decoder(use_ninapro = False):

  • relevant file: adaptive_hci/training.py suggestion: The 'train_model' function is quite long and does multiple things. It's recommended to split this function into smaller ones, each with a single responsibility. This would make the code easier to read, test, and maintain. [medium] relevant line: def train_model(model,

How to use

Tag me in a comment '@CodiumAI-Agent' and add one of the following commands: /review [-i]: Request a review of your Pull Request. For an incremental review, which only considers changes since the last review, include the '-i' option. /describe: Modify the PR title and description based on the contents of the PR. /improve [--extended]: Suggest improvements to the code in the PR. Extended mode employs several calls, and provides a more thorough feedback. /ask \<QUESTION>: Pose a question about the PR. /update_changelog: Update the changelog based on the PR's contents.

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[manuel-delverme]

The AI made some good points

[KilianFt]

@CodiumAI-Agent /review

[CodiumAI-Agent]

PR Analysis

• 🎯 Main theme: This PR mainly focuses on integrating online and offline adaptation for an adaptive HCI system. It includes changes in dataset handling, model training, and environment setup. It also introduces new scripts for continuous training and general model training.
• 📝 PR summary: This PR introduces significant changes to the adaptive HCI system. It includes the addition of new scripts for continuous training and general model training, changes in dataset handling to accommodate online and offline adaptation, and modifications in the environment setup. The PR also includes refactoring and code improvements.
• 📌 Type of PR: Enhancement
• 🧪 Relevant tests added: No

How to use

Tag me in a comment '@CodiumAI-Agent' and add one of the following commands: /review [-i]: Request a review of your Pull Request. For an incremental review, which only considers changes since the last review, include the '-i' option. /describe: Modify the PR title and description based on the contents of the PR. /improve [--extended]: Suggest improvements to the code in the PR. Extended mode employs several calls, and provides a more thorough feedback. /ask \<QUESTION>: Pose a question about the PR. /update_changelog: Update the changelog based on the PR's contents.

To edit any configuration parameter from configuration.toml, add --config_path=new_value For example: /review --pr_reviewer.extra_instructions="focus on the file: ..." To list the possible configuration parameters, use the /config command.

[KilianFt]

@CodiumAI-Agent /improve --extended