decoder_small: Network small

Description Usage Arguments Value

View source: R/architectures.R

Description

Defines decoder network architecture for scAlign.

Usage

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decoder_small(
  inputs,
  complexity,
  final_dim,
  emb_size = 32,
  l2_weight = 1e-08,
  dropout = TRUE,
  dropout_rate = 0.3,
  is_training = TRUE,
  batch_norm = TRUE,
  shared_ae = FALSE
)

Arguments

inputs

Mini-batch placeholder

complexity

Determines the depth and width of an automatically created network

final_dim

Number of features in high dimensional data

emb_size

Number of hidden nodes in final (embedding) hidden layer

l2_weight

Weight on l2_regularizer

dropout_rate

Probability for dropout.

is_training

Determines if dropout and batch norm should be include in pass through network

batch_norm

Determines if batch normalization layers should be included

Value

Neural network graph op


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