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16
appendix-A/01_optional-python-setup-preferences/README.md
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@ -2,7 +2,7 @@
There are several different ways you can install Python and set up your computing environment. Here, I am illustrating my personal preference.
There are several different ways you can install Python and set up your computing environment. Here, I am illustrating my personal preference.
(I am using computers running macOS, but this workflow is similar for Linux machines and may work for other operating systems as well.)
@ -12,9 +12,9 @@ There are several different ways you can install Python and set up your computin
Download miniforge from the GitHub repository [here](https://github.com/conda-forge/miniforge).
<img src="figures/download.png" alt="download" style="zoom:33%;" />
<img src="figures/download.png" alt="download" width="600px">
Depending on your operating system, this should download either an `.sh` (macOS, Linux) or `.exe` file (Windows).
Depending on your operating system, this should download either an `.sh` (macOS, Linux) or `.exe` file (Windows).
For the `.sh` file, open your command line terminal and execute the following command
@ -24,7 +24,7 @@ sh ~/Desktop/Miniforge3-MacOSX-arm64.sh
where `Desktop/` is the folder where the Miniforge installer was downloaded to. On your computer, you may have to replace it with `Downloads/`.
<img src="figures/miniforge-install.png" alt="miniforge-install" style="zoom:33%;" />
<img src="figures/miniforge-install.png" alt="miniforge-install" width="600px">
Next, step through the download instructions, confirming with "Enter".
@ -38,7 +38,7 @@ After the installation was successfully completed, I recommend creating a new vi
conda create -n LLMs python=3.10
```
<img src="figures/new-env.png" alt="new-env" style="zoom:33%;" />
<img src="figures/new-env.png" alt="new-env" width="600px">
> Many scientific computing libraries do not immediately support the newest version of Python. Therefore, when installing PyTorch, it's advisable to use a version of Python that is one or two releases older. For instance, if the latest version of Python is 3.13, using Python 3.10 or 3.11 is recommended.
@ -48,7 +48,7 @@ Next, activate your new virtual environment (you have to do it every time you op
conda activate dl-workshop
```
<img src="figures/activate-env.png" alt="activate-env" style="zoom:33%;" />
<img src="figures/activate-env.png" alt="activate-env" width="600px">
## Optional: styling your terminal
@ -66,13 +66,13 @@ To install new Python libraries, you can now use the `conda` package installer.
conda install jupyterlab watermark
```
<img src="figures/conda-install.png" alt="conda-install" style="zoom:33%;" />
<img src="figures/conda-install.png" alt="conda-install" width="600px">
You can also still use `pip` to install libraries. By default, `pip` should be linked to your new `LLms` conda environment:
<img src="figures/check-pip.png" alt="check-pip" style="zoom:33%;" />
<img src="figures/check-pip.png" alt="check-pip" width="600px">

10
appendix-A/02_installing-python-libraries/README.md
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@ -19,7 +19,6 @@ To install these requirements most conveniently, you can use the `requirements.t
pip install -r requirements.txt
```
![install-requirements](figures/install-requirements.png)
Then, after completing the installation, please check if all the packages are installed and are up to date using
@ -27,21 +26,20 @@ Then, after completing the installation, please check if all the packages are in
python_environment_check.py
```
![check_1](figures/check_1.jpg)
<img src="figures/check_1.jpg" width="600px">
It's also recommended to check the versions in JupyterLab by running the `jupyter_environment_check.ipynb` in this directory, which should ideally give you the same results as above.
![check_1](figures/check_2.jpg)
<img src="figures/check_2.jpg" width="500px">
If you see the following issues, it's likely that your JupyterLab instance is connected to wrong conda environment:
![jupyter-issues](figures/jupyter-issues.jpg)
<img src="figures/jupyter-issues.jpg" width="450px">
In this case, you may want to use `watermark` to check if you opened the JupyterLab instance in the right conda environment using the `--conda` flag:
![watermark](figures/watermark.jpg)
<img src="figures/watermark.jpg" width="350px">
<br>