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Mojo function
reduce_group_norm_shape
def reduce_group_norm_shape(input: T, gamma: T, beta: T, epsilon: Float32, num_groups: Int32) -> IndexList[T.rank]
Computes the output shape for the mo.reduce.group_norm graph op.
Args:
- input (
T): Input tensor normalized across grouped channels. - gamma (
T): Per-channel scale weights applied after normalization. - beta (
T): Per-channel shift weights applied after scaling. - epsilon (
Float32): Small constant added inside the normalization variance for numerical stability. - num_groups (
Int32): Number of groups the channel dimension is split into for computing mean and variance.
Returns:
IndexList[T.rank]: The output shape, which matches the input shape.