DataPredict Neural [Release 1.5] - PyTorch-like Deep Learning Library Meets Roblox!

Release Version 1.0 / Beta Version 0.6.0

Added

  • Shape Transformation Blocks:

    • Permute
  • Attention Blocks:

    • BaseAttentionBlock

    • ScaledDotProductAttention

  • Deep Reinforcement Models:

    • DeepQLearning

    • DeepDoubleQLearningV1

    • DeepDoubleQLearningV2

    • DeepClippedDoubleQLearning

    • DeepStateActionRewardStateAction

    • DeepDoubleStateActionRewardStateActionV1

    • DeepDoubleStateActionRewardStateActionV2

    • DeepExpectedStateActionRewardStateAction

    • DeepDoubleExpectedStateActionRewardStateActionV1

    • DeepDoubleExpectedStateActionRewardStateActionV2

    • ActorCritic

    • AdvantageActorCritic

    • ProximalPolicyOptimization

    • ProximalPolicyOptimizationClip

    • REINFORCE

    • VanillaPolicyGradient

  • Value Schedulers:

    • BaseValueScheduler

    • TimeDecay

    • StepDecay

Changes

  • setClassesList() function and getClassesList() function are added to Sequential Container.

  • Removed ā€œnumberOfDataā€ parameter from the BaseCostFunctionā€™s calculateCostValue() function and calculateLossTensor() function.

  • setLearningRateScheduler() function and getLearningRateScheduler() function are added to the BaseOptimizer

Side Notes

Please update your TensorL library for bug fixes.

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Release Version 1.1 / Beta Version 0.7.0

Added

  • Expansion Blocks:

    • BaseExpansionBlock

    • ExpandNumberOfDimensions

    • ExpandDimensionSizes

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(post deleted by author)

Release Version 1.2 / Beta Version 0.8.0

Changes

  • Moved InputHolder to Holder Blocks

  • Changed all the Shape Transformation Blocks settings so that it saves the transformed tensor.

Added

  • Holder Blocks:

    • BaseHolderBlock

    • VariableHolder

    • NullaryFunctionHolder

2 Likes

Release Version 1.3 / Beta Version 0.9.0

Changes

  • If any of the input tensors have its number of dimensions or dimension sizes expanded, it will collapse the partial first derivative tensor to the input tensorā€™s number of dimensions and dimension sizes.

Added

  • Operator Blocks:

    • Clamp

    • Maximum

    • Minimum

Release Version 1.4 / Beta Version 1.0.0

Changes

  • Everything related to ā€œFirstDerivativeā€ is renamed to ā€œChainRuleFirstDerivativeā€.

  • Everything related to ā€œSecondStepFirstDerivativeā€ is renamed to ā€œFirstDerivativeā€.

  • Calculations for first derivative tensors inside the FunctionBlocks are now more efficient.

Fixes

  • Replaced forgotten TensorLā€™s getSize() functions to getDimensionSizeArray().

  • Fixed a bug where MaxUnpooling FunctionBlocks requires incorrect input tensors dimension sizes.

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Release Version 1.5 / Beta Version 1.1.0

Added

  • Added RandomNetworkDistillation under ā€œModelsā€.
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Which would be the best module for a self-learning AI out of your two modules and if they are equally as good, what is the best one to start on as someone who has never stepped into anything related to this?

Start with the other library, DataPredict. It has a lot more tutorials and simpler to set up.

Come back to this library if you want more specialized neural networks to build your self-learning AIs with it.

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