Comments (18)
juliasilge
commented on June 25, 2024
That sounds frustrating! Can you create a reprex, a small reproducible example, so that we can find the source of your problem? If you haven't created a reprex before, this is a helpful introduction.
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quantumlinguist
commented on June 25, 2024
library(recipes)
#> Loading required package: 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
#>
#> Attaching package: 'recipes'
#> The following object is masked from 'package:stats':
#>
#> step
library(embed)
rec <- recipe(Case~AnimacyObj+ Participants+ AgencySubj, data=causee)%>%
step_embed(Participants,
outcome=vars(Case),
num_terms=1,
hidden_units=10,
options = embed_control(epochs = 25, validation_split=0.2)) %>%
prep()
#> Error in is_tibble(data): object 'causee' not foundCreated on 2020-07-05 by the reprex package (v0.3.0)
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quantumlinguist
commented on June 25, 2024
I see now it says my dataset is not a tibble? So I should just transform it?
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juliasilge
commented on June 25, 2024
No, in that reprex, you haven't loaded any data at all, so that's an error for not finding causee. Check out this section and this section about possibilities for getting some example data into the reprex.
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quantumlinguist
commented on June 25, 2024
I can't get my dataset to be found. It certainly is loaded.
library(recipes)
#> Loading required package: 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
#>
#> Attaching package: 'recipes'
#> The following object is masked from 'package:stats':
#>
#> step
library(embed)
library(datapasta)
dpasta(causee)
#> Error in is_tibble(input): object 'causee' not found
rec <- recipe(Case~AnimacyObj+ Participants+ AgencySubj, data=causee)%>%
step_embed(Participants,
outcome=vars(Case),
num_terms=1,
hidden_units=10,
options = embed_control(epochs = 25, validation_split=0.2)) %>%
prep()
#> Error in is_tibble(data): object 'causee' not foundCreated on 2020-07-05 by the reprex package (v0.3.0)
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juliasilge
commented on June 25, 2024
Take a look at the animated GIF in this section, and notice when you get out some output that can be pasted into a reprex (the wings object).
The idea here, which this explains really well if you can take some time to look through the slides, is to create a self-contained, rigorous example (including containing insides it a hopefully small dataset that reproduces your problem) so that others can understand your problem.
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quantumlinguist
commented on June 25, 2024
Thanks, here is what I got now.
library(recipes)
#> Loading required package: 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
#>
#> Attaching package: 'recipes'
#> The following object is masked from 'package:stats':
#>
#> step
library(embed)
library(datapasta)
str(mini_df)
#> Error in str(mini_df): object 'mini_df' not found
dpasta(mini_df)
#> Error in is_tibble(input): object 'mini_df' not found
mini_df=tibble::tribble(
~Case.Participants.AnimacyObj.AgencySubj,
"1 DAT 1 1 1",
"2 DAT 1 1 0",
"3 ACC 1 1 1",
"4 ACC 1 1 0",
"5 ACC 1 1 0",
"6 ACC 0 1 0"
)
head(mini_df)
#> # A tibble: 6 x 1
#> Case.Participants.AnimacyObj.AgencySubj
#> <chr>
#> 1 1 DAT 1 1 1
#> 2 2 DAT 1 1 0
#> 3 3 ACC 1 1 1
#> 4 4 ACC 1 1 0
#> 5 5 ACC 1 1 0
#> 6 6 ACC 0 1 0
rec <- recipe(Case~AnimacyObj+ Participants+ AgencySubj, data=mini_df)%>%
step_embed(Participants,
outcome=vars(Case),
num_terms=3,
hidden_units=10,
options = embed_control(epochs = 25, validation_split=0.2)) %>%
prep()
#> Error in eval(predvars, data, env): object 'Case' not foundCreated on 2020-07-05 by the reprex package (v0.3.0)
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topepo
commented on June 25, 2024
Can you run sessioninfo::session_info() after one of the failures (or use reprex::reprex(si = TRUE))?
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quantumlinguist
commented on June 25, 2024
Here it is
library(recipes)
#> Loading required package: 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
#>
#> Attaching package: 'recipes'
#> The following object is masked from 'package:stats':
#>
#> step
library(embed)
library(datapasta)
causee= read.csv("causee_only_data.csv", sep=";")
#> Warning in file(file, "rt"): cannot open file 'causee_only_data.csv': No such
#> file or directory
#> Error in file(file, "rt"): cannot open the connection
mini_df= select(causee,Case, Participants, AnimacyObj, AgencySubj)%>%
mutate_if(is.character, factor)
#> Error in select(causee, Case, Participants, AnimacyObj, AgencySubj): object 'causee' not found
rec <- recipe(Case~., data=mini_df)%>%
step_embed(Participants,
outcome=vars(Case),
num_terms=3,
hidden_units=10,
options = embed_control(epochs = 25, validation_split=0.2)) %>%
prep(training=mini_df)
#> Error in is_tibble(data): object 'mini_df' not foundCreated on 2020-07-05 by the reprex package (v0.3.0)
Session info
devtools::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 3.6.3 (2020-02-29)
#> os macOS Mojave 10.14.6
#> system x86_64, darwin15.6.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Oslo
#> date 2020-07-05
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
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#> pkgbuild 1.0.8 2020-05-07 [1] CRAN (R 3.6.2)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 3.6.0)
#> pkgload 1.1.0 2020-05-29 [1] CRAN (R 3.6.2)
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#> recipes * 0.1.13 2020-06-23 [1] CRAN (R 3.6.2)
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#>
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#> [2] /Library/Frameworks/R.framework/Versions/3.6/Resources/libraryfrom embed.
topepo
commented on June 25, 2024
Can you execute this code and send the output?
library(tidymodels)
library(embed)
library(modeldata)
data(ames, package = "modeldata")
rec <-
recipe(Sale_Price ~ MS_SubClass + Neighborhood, data = ames) %>%
step_log(Sale_Price, base = 10) %>%
step_embed(all_predictors(), outcome = vars(Sale_Price))
rec %>% prep()
tensorflow::tf_version()
rec %>% prep()from embed.
quantumlinguist
commented on June 25, 2024
Yes, thanks for your help by the way.
library(tidymodels)
#> ── Attaching packages ────────────────────────────────────── tidymodels 0.1.0 ──
#> ✓ broom 0.5.6 ✓ recipes 0.1.13
#> ✓ dials 0.0.7 ✓ rsample 0.0.7
#> ✓ dplyr 1.0.0 ✓ tibble 3.0.1
#> ✓ ggplot2 3.3.2 ✓ tune 0.1.0
#> ✓ infer 0.5.2 ✓ workflows 0.1.1
#> ✓ parsnip 0.1.1 ✓ yardstick 0.0.6
#> ✓ purrr 0.3.4
#> ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
#> x purrr::discard() masks scales::discard()
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()
#> x recipes::step() masks stats::step()
library(embed)
library(modeldata)
data(ames, package = "modeldata")
rec <-
recipe(Sale_Price ~ MS_SubClass + Neighborhood, data = ames) %>%
step_log(Sale_Price, base = 10) %>%
step_embed(all_predictors(), outcome = vars(Sale_Price))
rec %>% prep()
#> Error in if (is.na(b)) return(1L): argument is of length zero
tensorflow::tf_version()
#> NULL
rec %>% prep()
#> Error in if (is.na(b)) return(1L): argument is of length zeroCreated on 2020-07-06 by the reprex package (v0.3.0)
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topepo
commented on June 25, 2024
Can you run this command twice and send the results?
tensorflow::tf_config()from embed.
quantumlinguist
commented on June 25, 2024
tensorflow::tf_config()
#> Installation of TensorFlow not found.
#>
#> Python environments searched for 'tensorflow' package:
#> /Users/ggu020/Library/r-miniconda/envs/r-reticulate/bin/python3.6
#>
#> You can install TensorFlow using the install_tensorflow() function.
#> Created on 2020-07-06 by the reprex package (v0.3.0)
tensorflow::tf_config()
#> Installation of TensorFlow not found.
#>
#> Python environments searched for 'tensorflow' package:
#> /Users/ggu020/Library/r-miniconda/envs/r-reticulate/bin/python3.6
#>
#> You can install TensorFlow using the install_tensorflow() function.
#> Created on 2020-07-06 by the reprex package (v0.3.0)
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topepo
commented on June 25, 2024
You can install TensorFlow using the install_tensorflow() function... so give that a try and let us know if it works.
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quantumlinguist
commented on June 25, 2024
I followed the step of installing tensor flow and it works now. I had installed it via install.packages(), I didn't know it required a different method. Thanks for your help!
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topepo
commented on June 25, 2024
Sooo... here's why this is confusing (for everyone). There is a bug in the CRAN version of reticulate that will not find the python install the first time you ask for it. That is fixed in the devel version.
For some reason, this does work in a reprex. I should have been more clear; it needed to be run (without reprex) in a new R session twice.
The overall solution is to install the version of reticulate that is on Github.
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quantumlinguist
commented on June 25, 2024
Ohh I see! Ok, thanks for the clarification!
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github-actions
commented on June 25, 2024
This issue has been automatically locked. If you believe you have found a related problem, please file a new issue (with a reprex: https://reprex.tidyverse.org) and link to this issue.
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