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@mayalenE mayalenE released this 22 Feb 12:16
· 27 commits to main since this release
v0.3
0c83d06

AutoDiscJax v0.3

  • New modules:

    • ClampModule: new util module to allow clamping of module outputs
    • UniformGoalGenerator: module to sample goals uniformly between a low and high value
    • RandomInterventionSelector: module to randomly select an intervention among history of prior interventions
    • NullRolloutStatisticsEncoder: module to allow users to not compute any statistics on the system outputs
    • PushPerturbationGenerator: new module to generate push perturbation parameters (separated from the NoisePerturbationGenerator)

  • Updated modules:

    • Module: each autodiscjax module now returns a log_data object

    • BaseGenerator and BaseOptimizer now inherit from the ClampModule module

    • big refacto of optimizers + BaseGCInterventionOptimizer + LearningProgressIM modules to allow save of local optim runs in imgep_experiment_pipeline

    • EAOptimizer now has a noise scheduler

    • GRNRollout: removed the vmap of grn_step (no needed anymore)

    • GRNRolloutStatisticsEncoder: added the is_converging statistic

    • WallPerturbationGenerator:

      • takes a sigma parameter allowing to tune the perpendicular vs radial repulsive forces exerted by the wall
      • positions wall based on distance travelled (instead of time travelled)

    • NoisePerturbationGenerator: added possibility to generate noise for w and c parameters

    • L2GoalAchievementLoss: added sqrt (before was squared L2) and adaptive scaling by current reached goal space extent

    • NearestNeighborInterventionSelector: added adaptive scaling by current reached goal space extent

  • New util functions:

    • create_modules.py: bunch of util functions to instantiate autodiscjax modules from a given config
    • append_to_log: util function to append the module's log_data outputs to log

  • Updated util functions:

    • is_converging: now looks if the signal amplitude has decreased (when compared to a prior phase of the signal)

  • Bug Fixes:

    • HypercubeGoalGenerator: fix hypercube center calculation
    • GRNRolloutStatisticsEncoder: stats were mixed, fixed

  • API changes:

    • big refacto of optimizers + BaseGCInterventionOptimizer + LearningProgressIM modules to allow save of local optim runs in imgep_experiment_pipeline
    • imgep_experiment_pipeline:
      • now saves local optim runs in history
    • rs_experiment_pipeline: added random search experiment pipeline
    • imgep_evaluation_pipeline was renamed into robustness_evaluation_pipeline (and run_imgep_evaluation into run_robustness_tests), and was modified with:
      • vmap vectorization of modules
      • logging
      • perturbation generator now takes raw system outputs as input (instead of just ys as this is more general)

  • jit decorators where removed/added to optimize compute time

  • Tests: renamed, updated and novel tests to test the different modules

  • Examples: updated with the new modules/pipeline

  • TODOs for next release:

    • docs
    • pip package
    • SGDOptimizer: deal with NaN values
    • IMFlowGoalGenerator bug fixes:
      • saving IM_vals into the logs can crash the code
      • can return NaN values
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