a b/man/merge_models.Rd
1
% Generated by roxygen2: do not edit by hand
2
% Please edit documentation in R/create_model_utils.R
3
\name{merge_models}
4
\alias{merge_models}
5
\title{Merge two models}
6
\usage{
7
merge_models(
8
  models,
9
  layer_names,
10
  layer_dense,
11
  solver = "adam",
12
  learning_rate = 1e-04,
13
  freeze_base_model = c(FALSE, FALSE),
14
  model_seed = NULL
15
)
16
}
17
\arguments{
18
\item{models}{List of two models.}
19
20
\item{layer_names}{Vector of length 2 with names of layers to merge.}
21
22
\item{layer_dense}{Vector specifying number of neurons per dense layer after last LSTM or CNN layer (if no LSTM used).}
23
24
\item{solver}{Optimization method, options are \verb{"adam", "adagrad", "rmsprop"} or \code{"sgd"}.}
25
26
\item{learning_rate}{Learning rate for optimizer.}
27
28
\item{freeze_base_model}{Boolean vector of length 2. Whether to freeze weights of individual models.}
29
30
\item{model_seed}{Set seed for model parameters in tensorflow if not \code{NULL}.}
31
}
32
\value{
33
A keras model merging two input models.
34
}
35
\description{
36
Combine two models at certain layers and add dense layer(s) afterwards.
37
}
38
\examples{
39
\dontshow{if (reticulate::py_module_available("tensorflow")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
40
model_1 <- create_model_lstm_cnn(layer_lstm = c(64, 64), maxlen = 50, layer_dense = c(32, 4),
41
                                 verbose = FALSE)
42
model_2 <- create_model_lstm_cnn(layer_lstm = c(32), maxlen = 40, 
43
                                 layer_dense = c(8, 2), verbose = FALSE)
44
# get names of second to last layers
45
num_layers_1 <- length(model_1$get_config()$layers)
46
layer_name_1 <- model_1$get_config()$layers[[num_layers_1 - 1]]$name
47
num_layers_2 <- length(model_2$get_config()$layers)
48
layer_name_2 <- model_2$get_config()$layers[[num_layers_2 - 1]]$name
49
# merge models
50
model <- merge_models(models = list(model_1, model_2),
51
                      layer_names = c(layer_name_1, layer_name_2),
52
                      layer_dense = c(6, 2), 
53
                      freeze_base_model = c(FALSE, FALSE)) 
54
\dontshow{\}) # examplesIf}
55
}