encoder_small {scAlign} | R Documentation

## Network small

### Description

Defines network architecture for scAlign.

### Usage

    encoder_small(
      inputs,
      input_size = NULL,
      complexity = 3,
      emb_size = 32,
      l2_weight = 1e-04,
      dropout = TRUE,
      dropout_rate = 0.3,
      is_training = TRUE,
      batch_norm = TRUE
    )

### Arguments

`inputs` | Mini-batch placeholder
`input_size` | Number of features per cell
`complexity` | Determines the depth and width of an automatically created network
`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

[Package scAlign version 1.8.0 Index]