scAlignOptions: Set training options

Description Usage Arguments Value Examples

View source: R/scAlignClass.R

Description

Defines parameters for optimizer and training procedure.

Usage

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scAlignOptions(
  steps = 15000,
  steps.decoder = 10000,
  batch.size = 150,
  learning.rate = 1e-04,
  log.every = 5000,
  architecture = "large",
  batch.norm.layer = FALSE,
  dropout.layer = TRUE,
  num.dim = 32,
  perplexity = 30,
  betas = 0,
  norm = TRUE,
  full.norm = FALSE,
  early.stop = FALSE,
  walker.loss = TRUE,
  reconc.loss = FALSE,
  walker.weight = 1,
  classifier.weight = 1,
  classifier.delay = NA,
  gpu.device = "0",
  seed = 1234
)

Arguments

steps

(default: 15000) Number of training iterations for neural networks.

steps.decoder

Number of training iterations for neural networks.

batch.size

(default: 150) Number of input samples per training batch.

learning.rate

(default: 1e-4) Initial learning rate for ADAM.

log.every

(default: 5000) Number of steps before saving results.

architecture

(default: "small") Network function name for scAlign.

batch.norm.layer

(default: FALSE) Include batch normalization in the network structure.

dropout.layer

(default: TRUE) Include dropout in the network.

num.dim

(default: 32) Number of dimensions for joint embedding space.

perplexity

(default: 30) Determines the neighborhood size for each sample.

betas

(default: 0) Sets the bandwidth of the gaussians to be the same if > 0. Otherwise per cell beta is computed.

norm

(default: TRUE) Normalize the data mini batches while training scAlign (repeated).

full.norm

(default: FALSE) Normalize the data matrix prior to scAlign (done once).

early.stop

(default: TRUE) Early stopping during network training.

walker.loss

(default: TRUE) Add walker loss to model.

reconc.loss

(default: FALSE) Add reconstruction loss to model during alignment.

walker.weight

(default: 1.0) Weight on walker loss component

classifier.weight

(default: 1.0) Weight on classifier loss component

classifier.delay

(default: NULL) Delay classifier component of loss function until specific training step. Defaults to (2/3)*steps.

gpu.device

(default: '0') Which gpu to use.

seed

(default: 1245) Sets graph level random seed in tensorflow.

Value

Options data.frame

Examples

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options=scAlignOptions(steps=15000,
                       log.every=5000,
                       early.stop=FALSE,
                       architecture="large")

quon-titative-biology/scAlign documentation built on Nov. 17, 2021, 9:57 a.m.