torch: nnf_batch_norm – R documentation

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torch

nnf_batch_norm

Batch_norm

Description

Applies Batch Normalization for each channel across a batch of data.

Usage

nnf_batch_norm(
  input,
  running_mean,
  running_var,
  weight = NULL,
  bias = NULL,
  training = FALSE,
  momentum = 0.1,
  eps = 1e-05
)

Arguments

`input`	input tensor
`running_mean`	the running_mean tensor
`running_var`	the running_var tensor
`weight`	the weight tensor
`bias`	the bias tensor
`training`	bool wether it's training. Default: FALSE
`momentum`	the value used for the `running_mean` and `running_var` computation. Can be set to None for cumulative moving average (i.e. simple average). Default: 0.1
`eps`	a value added to the denominator for numerical stability. Default: 1e-5

torch

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0

MIT + file LICENSE

Authors

Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]

Initial release

nnf_batch_norm

Description

Usage

Arguments

torch

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