Description Usage Arguments Value Examples
View source: R/flexconn_conv_chain.R
FLEXCONN Convolution Chain
1 2 3 4 5 6 7 8 9 | flexconn_conv_chain(
object,
ds = 2,
num_filters = 128,
kernel_size_1 = 3,
kernel_size_2 = 5,
prefix = NULL,
ndim
)
|
object |
Model or layer object |
ds |
Some fixed number??? |
num_filters |
Nubmer of filters |
kernel_size_1 |
Size of first kernel |
kernel_size_2 |
Size of second kernel |
prefix |
output prefix for each layer |
ndim |
Number of dimensions for convolution chain |
Output model
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | user = Sys.getenv("USER")
if (user %in% c("johnmuschelli", "travis") &
Sys.info()["sysname"] == "Darwin"){
reticulate::use_python(paste0(
"/Library/Frameworks/Python.framework/Versions/3.5/bin/python3"))
} else {
python = system("which python", intern = TRUE)
print(python)
reticulate::use_python(python)
}
library(tensorflow)
library(keras)
t1_input <- layer_input(shape = shape(NULL, NULL, 1))
t1 <- t1_input %>%
flexconn_conv_chain(
prefix = "t1"
)
t1_3d_input <- layer_input(shape = shape(NULL, NULL, NULL, 1))
t1_3d <- t1_input %>%
flexconn_conv_chain(
prefix = "t1"
)
|
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