Turn off parallel processing for NMF, do not load pkgs

[juliasilge]

Closes #681

This PR turns off the parallelization that NMF has on by default, which allows us to use NMF and dimRed without fully loading them as before. This solves the problem with fit():

library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#>   method                   from   
#>   required_pkgs.model_spec parsnip
data(biomass)

rec <- recipe(HHV ~ ., data = biomass) %>%
  update_role(sample, new_role = "id var") %>%
  update_role(dataset, new_role = "split variable") %>%
  step_nnmf(all_numeric_predictors(), num_comp = 2, seed = 473, num_run = 2) %>%
  prep(training = biomass)

linear_reg() %>% fit(mpg ~ ., data = mtcars)
#> Warning: Engine set to `lm`.
#> parsnip model object
#> 
#> Fit time:  3ms 
#> 
#> Call:
#> stats::lm(formula = mpg ~ ., data = data)
#> 
#> Coefficients:
#> (Intercept)          cyl         disp           hp         drat           wt  
#>    12.30337     -0.11144      0.01334     -0.02148      0.78711     -3.71530  
#>        qsec           vs           am         gear         carb  
#>     0.82104      0.31776      2.52023      0.65541     -0.19942

^{Created on 2021-04-14 by the reprex package (v2.0.0)}

In the future, we could consider exposing some kind of parallel option for step_nnmf() for folks who use it outside of our tuning infrastructure and want to run it in parallel.

[DavisVaughan]

Yay!

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