---
title: "Extended Installation Guide"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Extended Installation Guide}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

*Text* enables users access to HuggingFace Transformers in R through the R-package [reticulate](https://rstudio.github.io/reticulate/) as an interface to [Python](https://www.python.org/), and the python packages [torch](https://pytorch.org/) and [transformers](https://huggingface.co/docs/transformers/index). So it's important to install both the text-package and a python environment with the text required python packages that the text-package can use. </br></br> The recommended way is to use `textrpp_install()` to install a conda environment with text required python packages, and `textrpp_initialize` to initialize it.

## Conda environment

```{r extended_installation_condaenv, eval = FALSE}
library(text)
library(reticulate)

# Install text required python packages in a conda environment (with defaults).
text::textrpp_install()

# Show available conda environments.
reticulate::conda_list()

# Initialize the installed conda environment.
# save_profile = TRUE saves the settings so that you don't have to run textrpp_initialize() after restarting R. 
text::textrpp_initialize(save_profile = TRUE)

# Test so that the text package work.
textEmbed("hello")

```


## Solving OMP errors and R/Rstudio crashes
Recently some text users (mainly on Mac), have experienced OMP errors - and that RStudio and R crashes. When this is happening we have found the following solutions for now:


```         
Sys.setenv(OMP_NUM_THREADS = "1") #Limit the number of threads to prevent conflicts.

Sys.setenv(OMP_MAX_ACTIVE_LEVELS = "1") 

# Also might have to restart R
.rs.restartR()

# If above does not work, you can also try this; although this solution might have some risks assocaited with it (for more information see https://github.com/dmlc/xgboost/issues/1715)
Sys.setenv(KMP_DUPLICATE_LIB_OK = "TRUE") #Temporarily allows execution despite duplicate OpenMP libraries.

### This is how you can unset the settings
Sys.unsetenv("OMP_NUM_THREADS")
Sys.unsetenv("OMP_MAX_ACTIVE_LEVELS")
Sys.unsetenv("KMP_DUPLICATE_LIB_OK")

# This is how you can verify the settings
print(Sys.getenv("DYLD_LIBRARY_PATH"))


# Please let us know if you find any other solutions. 
```



## Solving Mac OS errors

### Failed to build tokenizers

if running: textrpp_install()

results in this error:

```         
Failed to build tokenizers
ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects
```

In the terminal run:

```{r extended_installation_condaenvE1, eval = FALSE}
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```

### Rust compiler

Error:

```         
"Error: Error installing package(s): ..." 
including: "error: can't find Rust compiler"
```

In the terminal run:

```{r extended_installation_condaenvE2, eval = FALSE}
brew install rust
```

## Recommended versions for conda

The success of the installation is dependent on using conda, python and package versions that work together. The installation of the text-package with text required python packages is tested on Linux, Mac OS, and Windows using github actions. The installation procedure and details can be seen at [github actions](https://github.com/OscarKjell/text/actions) (look at workflow runs called System specific installation NoPy).

The table below show various combination of python and package versions that have worked (it is not an exhaustive list).

```{r conda_tabble_short, echo=FALSE, results='asis'}
library(magrittr)

os <- c("'Mac OS'", "'Linux'", "'Windows'",
  "'Windows'", 
        "'Mac OS'", "'Linux'", "'Windows'",
        "'Mac OS'", "'Linux'",  "'Windows'",
        "'Mac OS'", "'Linux'", "'Windows'")
mini_conda <- c("'-'", "'-'", "'-'","'4.10.1'", 
                "'4.10.3'", "'4.10.3'", "'4.10.3'",
                "'4.10.3'", "'4.10.3'", "'4.10.3'",
                "'4.10.3'", "'4.10.3'", "'4.10.3'")
python <- c("'3.9.0'", "'3.9.0'", "'3.9.0'", "'3.9.0'",
                   "'3.9.0'", "'3.9.0'", "'3.9.0'",
                   "'3.8.10'", "'3.8.10'", "'3.8.10'",
                   "'3.7.0'", "'3.7.0'", "'3.6.13'"
                )

torch <- c("'torch==1.11.0'", "'torch==1.11.0'", "'torch==1.11.0'","'torch==1.7.1'", 
           "'torch==1.7.1'", "'torch==1.7.1'", "'torch==1.7.1'", 
           "'torch==1.7.1'", "'torch==1.7.1'", "'torch==1.7.1'", 
           "'torch==0.4.1'", "'torch==0.4.1'", "'torch==1.10'")

transformers <- c("'transformers==4.19.2'", "'transformers==4.19.2'", "'transformers==4.19.2'", "'transformers==4.12.5'", 
                  "'transformers==4.12.5'", "'transformers==4.12.5'", "'transformers==4.12.5'",
                  "'transformers==4.12.5'", "'transformers==4.12.5'", "'transformers==4.12.5'", 
                  "'transformers==3.3.1'", "'transformers==3.3.1'", "'transformers==3.3.1'")

success <- c("Pass", "Pass","Pass", 
             "FAIL", 
             "Pass", "Pass","Pass",
             "Pass","Pass","Pass",
             "Pass","Pass","Pass")

mini_conda_table <- tibble::tibble(os, mini_conda, python, torch, transformers, success)

knitr::kable(mini_conda_table, caption="", bootstrap_options = c("hover"), full_width = T)
```

## Virtual environments

It is also possible to use virtual environments (although it is currently only tested on MacOS).

```{r extended_installation_venv, eval = FALSE}
# Create a virtual environment with text required python packages.
# Note that you have to provide a python path.
text::textrpp_install_virtualenv(rpp_version = c("torch==1.7.1", "transformers==4.12.5", "numpy", "nltk"),
                                 python_path = "/usr/local/bin/python3.9",
                                 envname = "textrpp_virtualenv")

# Initialize the virtual environment.
text::textrpp_initialize(virtualenv = "textrpp_virtualenv",
                         condaenv = NULL,
                         save_profile = TRUE)

```

## Versions tested for virtual environment

Virtual environments works for MacOS, whereas github actions does not currently work for Linux and Windows. At [gihub actions](https://github.com/OscarKjell/text/actions) look for a workflow run called: Virtual environment for more information.

```{r venv_tabble_short, echo=FALSE, results='asis'}
library(magrittr)

OS <- c("'Mac OS'", "'Linux'", "'Mac OS'", "'Linux'", "'Windows'")

Python_version <- c("'3.9.8'", "'3.9.8'", "'3.9.8'", "-", "-")

torch <- c("'torch==1.11.0'", "'torch==1.11.0'", "'torch==1.7.1'", "-", "-")

transformers <- c("'transformers==4.19.2'", "'transformers==4.19.2'", "'transformers==4.12.5'", "-", "-")

Success <- c("Pass", "Pass", "Pass", "-", "-")

venv_conda_table <- tibble::tibble(OS, Python_version, torch, transformers, Success)

knitr::kable(venv_conda_table, caption="", bootstrap_options = c("hover"), full_width = T)
```

## Installation instructions for text 0.9.10

Below is the instructions for installing earlier versions of text (0.9.10 and before); these should work for newer versions of text as long as a correct versions of python and required packages are used.

```{r extended_installation_old, eval = FALSE}
library(text)

# To install the python packages torch, transformers, numpy and nltk through R, run: 
library(reticulate)
install_miniconda()

conda_install(envname = 'r-reticulate', c('torch==0.4.1', 'transformers==3.3.1', 'numpy', 'nltk'), pip = TRUE)

# Windows 10
conda_install(envname = 'r-reticulate', c('torch==0.4.1', 'transformers==3.3.1', 'numpy', 'nltk'))

```

## Checking your versions

If something isn't working right, it is a good start to examine what is installed and running on your system. For example to make sure that you have R and Python versions that are up to date.

```{r extended_installation_checking_system, eval = FALSE}

# First check R-version and which packages that are attached and loaded.  
sessionInfo()

# Second check out python version; and make sure you at least have version 3.6.10
library(reticulate)
py_config()
```

### Issue: RStudio craches during textEmbed

After a new install/update of *text*, RStudio crashed (Abort session) when running functions that fetches word embeddings (i.e., `textEmbedLayersOutput` or `textEmbed`).

### Solution: Reinstall reticulate and r-miniconda

To solve the issue re-install reticulate (development version) and uninstall and install r-miniconda.

Uninstall r-miniconda by removing its entire folder (which by default [in Mac] is at `Users/YOUR_USER_NAME/Library/r-miniconda`).

(Note that [in Mac] the Library folder is hidden, so to make it visible go to Finder and the path Users/YOUR_USER_NAME/ and press the three keys: `COMMAND + SHIFT + .` . Then the Library-folder should appear, and you can find and remove r-miniconda.

```{r extended_REinstallation, eval = FALSE}
library(text)

# To re-install packages start with a fresh session by restarting R and RStudio

# Install development of reticulate (might not be necessary)
devtools::install_github("rstudio/reticulate")

# After having manually removed the r-miniconda folder, install it again: 
library(reticulate)
install_miniconda()

# Subsequently re-install torch, transformers, numpy and nltk by running: 
conda_install(envname = 'r-reticulate', c('torch==0.4.1', 'transformers==3.3.1', 'numpy', 'nltk'), pip = TRUE)

```

The exact way to install these packages may differ across systems. Please see:\
[Python](https://www.python.org/)\
[torch](https://pytorch.org/)\
[transformers](https://huggingface.co/docs/transformers/index)

## Share advise

*If you find a good solution please feel free to email oscar [ d_o t] kjell [a_t] psy [DOT] lu [d_o_t]se so that we can update above instructions.*
>>>>>>> e368e8b (documentation updates)
