Python module

group_norm

Group Normalization implementation using the graph API.

GroupNorm

class max.nn.norm.group_norm.GroupNorm(num_groups, num_channels, eps=1e-05, affine=True, device=gpu:0)

Group normalization block.

Divides channels into groups and computes normalization stats per group. Follows the implementation pattern from PyTorch’s group_norm.

Parameters:

• num_groups (int ) – Number of groups to separate the channels into
• num_channels (int ) – Number of input channels
• eps (float ) – Small constant added to denominator for numerical stability
• affine (bool ) – If True, apply learnable affine transform parameters
• device (DeviceRef )

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