langml.layers.layer_norm

Module Contents

Classes

LayerNorm

class langml.layers.layer_norm.LayerNorm(center: bool = True, scale: bool = True, epsilon: float = 1e-07, gamma_initializer: langml.tensor_typing.Initializer = 'ones', gamma_regularizer: Optional[langml.tensor_typing.Regularizer] = None, gamma_constraint: Optional[langml.tensor_typing.Constraint] = None, beta_initializer: langml.tensor_typing.Initializer = 'zeros', beta_regularizer: Optional[langml.tensor_typing.Regularizer] = None, beta_constraint: Optional[langml.tensor_typing.Constraint] = None, **kwargs)[source]

Bases: tensorflow.keras.layers.Layer

get_config(self) → dict[source]
build(self, input_shape: langml.tensor_typing.Tensors)[source]
call(self, inputs: langml.tensor_typing.Tensors, **kwargs) → langml.tensor_typing.Tensors[source]
compute_mask(self, inputs: langml.tensor_typing.Tensors, mask: Optional[langml.tensor_typing.Tensors] = None) → Union[langml.tensor_typing.Tensors, None][source]
static get_custom_objects() → dict[source]
compute_output_shape(self, input_shape: langml.tensor_typing.Tensors) → langml.tensor_typing.Tensors[source]