Expand description
Optimizers module.
Modules§
- grad_
clipping - Gradient clipping module.
- lr_
scheduler - Learning rate scheduler module.
- optim
- Optimizer module.
Structs§
- AdaGrad
- AdaGrad optimizer
- AdaGrad
Config - AdaGrad configuration.
- AdaGrad
State - AdaGrad state.
- AdaGrad
State Item - The record item type for the module.
- Adam
- Adam optimizer as described in the paper Adam: A Method for Stochastic Optimization.
- Adam
Config - Adam configuration.
- Adam
State - Adam state.
- Adam
State Item - The record item type for the module.
- AdamW
- AdamW optimizer.
- AdamW
Config AdamWConfiguration.- AdamW
State - AdamW state.
- AdamW
State Item - The record item type for the module.
- Adaptive
Momentum State - Adaptive momentum state.
- Adaptive
Momentum State Item - The record item type for the module.
- Centered
State - CenteredState is to store and pass optimizer step params.
- Centered
State Item - The record item type for the module.
- Gradients
Accumulator - Accumulate gradients into a single Gradients object.
- Gradients
Params - Data type that contains gradients for parameters.
- LrDecay
State - Learning rate decay state (also includes sum state).
- LrDecay
State Item - The record item type for the module.
- RmsProp
- Optimizer that implements stochastic gradient descent with momentum. The optimizer can be configured with RmsPropConfig.
- RmsProp
Config - Configuration to create the RmsProp optimizer.
- RmsProp
Momentum - RmsPropMomentum is to store config status for optimizer.
(, which is stored in optimizer itself and not passed in during
step()calculation) - RmsProp
Momentum State - RmsPropMomentumState is to store and pass optimizer step params.
- RmsProp
Momentum State Item - The record item type for the module.
- RmsProp
State - State of RmsProp
- RmsProp
State Item - The record item type for the module.
- Sgd
- Optimizer that implements stochastic gradient descent with momentum.
- SgdConfig
- Configuration to create the Sgd optimizer.
- SgdState
- State of Sgd.
- SgdState
Item - The record item type for the module.
- Square
AvgState - SquareAvgState is to store and pass optimizer step params.
- Square
AvgState Item - The record item type for the module.
Traits§
- Optimizer
- General trait to optimize module.
- Simple
Optimizer - Simple optimizer is an opinionated trait to simplify the process of implementing an optimizer.
Type Aliases§
- Learning
Rate - Type alias for the learning rate.