HowToSD-ComfyUI-Pt-Wrapper/docs/reference/ptn_batch_norm2d.md

Ptn Batch Norm 2d

A normalization model to normalize over the batch and spatial axes for each channel.

Args: num_features (int): Specifies the size of channel axis. - For an image input of shape [8, 4, 256, 256], specify 4.

affine (bool): If `True`, applies a learnable scaling factor and bias to the normalized elements.

track_running_stats (bool): If `True`, use exponential moving average (EMA) to store mean and std to be used in eval for normalization. For training, current batch statistics are always used for mean and std irrespective of this flag.
    
momentum (float): The EMA coefficient used if track_running_stats is set to True. Higher values give more weight to the current batch statistics, while lower values retain more past statistics.

Input

Name	Data type
num_features	Int
affine	Boolean
track_running_stats	Boolean
momentum	Float

Output

Data type
Ptmodel

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Category: PyTorch wrapper - Model

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