Divide value in each cell by the geometric mean of a specific row across columns and log-transform it

I would like to devide value in each cell by the geometric mean of a specific row across columns and log-transforme it (natural logarithm).

df1
      col1  col2  col3
row1  1     777   6
row2  136   1     665
row3  0     100   97

result

df_new
      col1    col2      col3
row1  -2.81   3.83     
row2           
row3              

example of the calculation for the row1

library(tidyverse)

geometric_mean <- function(x){
    exp(sum(log(x), na.rm = TRUE) / length(x))
}

yourCalculation <- function(x){
    log(x / geometric_mean(x))
}

myMatrix <- tribble(
    ~col1  ,~col2  ,~col3
    , 1     , 777   , 6
    , 136   , 1     , 665
    , 0     , 100   , 97) %>%
    as.matrix()


t(apply(myMatrix, 1, yourCalculation))

          col1      col2      col3
[1,] -2.815733  3.839707 -1.023974
[2,]  1.108508 -3.804147  2.695640
[3,]       NaN       Inf       Inf

Important about geometric means: Don't calculate them like this: prod(x)^(1/length(x)). The problem with this is, that with already medium sized vectors x you are likely to run across your type boundaries when you multiply them all and so it won't compute. The log()-and-exp() way is better.