For the complete documentation index, see llms.txt. Markdown versions of all pages are available by appending .md to any URL (e.g. /max/get-started.md).
Python class
LayerNorm
LayerNorm
class max.experimental.nn.norm.LayerNorm(dim, eps=1e-05, *, keep_dtype=True, elementwise_affine=True, use_bias=True)
Bases: Module
Layer normalization over the last dimension.
Initialize LayerNorm.
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Parameters:
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- dim (int) – Size of the last dimension to normalize.
- eps (float) – Numerical stability constant.
- keep_dtype (bool) – Whether to preserve input dtype in computation.
- elementwise_affine (bool) – Whether to apply learned scale.
- use_bias (bool) – Whether to apply a bias. It’s only effective if elementwise_affine is True.
bias
forward()
forward(x)
Applies layer normalization to the input.
weight
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