decoder_small {scAlign} | R Documentation |
Defines decoder network architecture for scAlign.
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 )
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 |
Neural network graph op