ag_batch_norm: Create a Batch Normalisation layer
In ggmlR: 'GGML' Tensor Operations for Machine Learning
ag_batch_norm R Documentation
Create a Batch Normalisation layer
Description
Normalises each feature (row) over the batch dimension.
Learnable scale gamma [F,1] and shift beta [F,1].
Usage
ag_batch_norm(num_features, eps = 1e-05, momentum = 0.1)
Arguments
num_features
Number of features (rows of input)
eps
Numerical stability constant (default 1e-5)
momentum
Running-stats momentum (default 0.1)
Details
Training mode: use batch statistics; update running mean/var.
Eval mode: use stored running statistics.
Value
An ag_batch_norm environment
Examples
bn <- ag_batch_norm(16L)
x <- ag_tensor(matrix(rnorm(16 * 32), 16, 32))
out <- bn$forward(x)
ggmlR documentation built on July 14, 2026, 1:08 a.m.
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| ag_batch_norm | R Documentation |
Create a Batch Normalisation layer
Description
Normalises each feature (row) over the batch dimension.
Learnable scale gamma [F,1] and shift beta [F,1].
Usage
ag_batch_norm(num_features, eps = 1e-05, momentum = 0.1)
Arguments
num_features |
Number of features (rows of input) |
eps |
Numerical stability constant (default 1e-5) |
momentum |
Running-stats momentum (default 0.1) |
Details
Training mode: use batch statistics; update running mean/var. Eval mode: use stored running statistics.
Value
An ag_batch_norm environment
Examples
bn <- ag_batch_norm(16L)
x <- ag_tensor(matrix(rnorm(16 * 32), 16, 32))
out <- bn$forward(x)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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