classes.py#

class mlui.types.classes.LayerParams[source]#

Bases: TypedDict

Base type annotation class for the parameters of the layer.

class mlui.types.classes.InputParams[source]#

Bases: dict

Type annotation class for the Input layer.

shape: tuple[int]#

class mlui.types.classes.DenseParams[source]#

Bases: dict

Type annotation class for the Dense layer.

units: int#

activation: Callable[[...], Tensor]#

class mlui.types.classes.BatchNormalizationParams[source]#

Bases: dict

Type annotation class for the BatchNormalization layer.

momentum: float#

epsilon: float#

class mlui.types.classes.DropoutParams[source]#

Bases: dict

Type annotation class for the Dropout layer.

rate: float#

class mlui.types.classes.OptimizerParams[source]#

Bases: TypedDict

Base type annotation class for the parameters of the optimizer.

class mlui.types.classes.AdamParams[source]#

Bases: dict

Type annotation class for the Adam optimizer.

learning_rate: float#

beta_1: float#

beta_2: float#

class mlui.types.classes.RMSpropParams[source]#

Bases: dict

Type annotation class for the RMSprop optimizer.

learning_rate: float#

rho: float#

momentum: float#

class mlui.types.classes.SGDParams[source]#

Bases: dict

Type annotation class for the SGD optimizer.

learning_rate: float#

momentum: float#

class mlui.types.classes.CallbackParams[source]#

Bases: TypedDict

Base type annotation class for the parameters of the callback.

class mlui.types.classes.EarlyStoppingParams[source]#

Bases: dict

Type annotation class for the EarlyStopping callback.

min_delta: float#

patience: int#