Cannot mutate grouping columns with across

[eutwt]

If a table is grouped by a column x, I can still alter the column with mutate using mutate(x = 2*x). However, if I try to do the same thing using across, I get an error saying that "Column x doesn't exist".

Is the fact that across cannot access grouping columns intentional?

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
df <- tibble(x = rep(1:2, 2:3)) %>% group_by(x)

df %>%
  mutate(x = x*2)
#> # A tibble: 5 × 1
#> # Groups:   x [2]
#>       x
#>   <dbl>
#> 1     2
#> 2     2
#> 3     4
#> 4     4
#> 5     4

df %>%
  mutate(across(x, ~ . * 2))
#> Error: Problem with `mutate()` input `..1`.
#> ℹ `..1 = across(x, ~. * 2)`.
#> x Can't subset columns that don't exist.
#> x Column `x` doesn't exist.
#> ℹ The error occurred in group 1: x = 1.

^{Created on 2021-07-30 by the reprex package (v2.0.0)}

[eutwt]

Nevermind, should have checked the across documentation`:

"Because across() is used within functions like summarise() and mutate(), you can't select or compute upon grouping variables."