pytagi.nn.layer_norm

pytagi.nn.layer_norm#

Classes#

LayerNorm

Implements Layer Normalization by normalizing the inputs across the

Module Contents#

class pytagi.nn.layer_norm.LayerNorm(normalized_shape: List[int], eps: float = 0.0001, bias: bool = True)[source]#

Bases: pytagi.nn.base_layer.BaseLayer

Implements Layer Normalization by normalizing the inputs across the features dimension. It inherits from BaseLayer.

Initializes the LayerNorm layer.

Parameters:

  • normalized_shape – The shape of the input to normalize over (e.g., the size of the feature dimension). Expected to be a list of integers.

  • eps – A small value added to the denominator for numerical stability to prevent division by zero. Defaults to 1e-4.

  • bias – If True, the layer will use an additive bias (beta) during normalization. Defaults to True.

get_layer_info() → str[source]#

Retrieves a descriptive string containing information about the layer’s configuration (e.g., its shape and parameters) from the C++ backend.

get_layer_name() → str[source]#

Retrieves the name of the layer (e.g., ‘LayerNorm’) from the C++ backend.

init_weight_bias()[source]#

Initializes the layer’s internal parameters, specifically the learnable scale (gamma) and, if ‘bias’ is True, the learnable offset (beta). This task is delegated to the C++ backend.

Contents