[FIX] Fix jax and os.fork warnings

.github/workflows/ci.yml

@@ -51,9 +51,8 @@ jobs:
           cp -u _build/jupyter/*.ipynb _build/html/_notebooks
       - name: Upload Execution Reports (Download Notebooks)
         uses: actions/upload-artifact@v4
-        if: failure()
         with:
-          name: execution-reports
+          name: execution-reports-notebooks
           path: _build/jupyter/reports
       - name: Build PDF from LaTeX
         shell: bash -l {0}

lectures/back_prop.md

@@ -16,6 +16,17 @@ kernelspec:
 ```{include} _admonition/gpu.md
 ```
 
+In addition to what's included in base Anaconda, we need to install the following packages
+
+```{code-cell} ipython3
+:tags: [hide-output]
+
+!pip install -U kaleido plotly
+!conda install -y -c plotly plotly-orca
+```
+
+We also need to install JAX to run this lecture
+
 ```{code-cell} ipython3
 :tags: [skip-execution]
 
@@ -28,15 +39,6 @@ import jax
 print(f"JAX backend: {jax.devices()[0].platform}")
 ```
 
-In addition to what's included in base Anaconda, we need to install the following packages
-
-```{code-cell} ipython3
-:tags: [hide-output]
-
-!pip install kaleido
-!conda install -y -c plotly plotly plotly-orca retrying
-```
-
 ```{note}
 If you are running this on Google Colab the above cell will 
 present an error. This is because Google Colab doesn't use Anaconda to manage
@@ -521,7 +523,7 @@ predictions = vmap(compute_xδw_seq, in_axes=(None, 0))(params_ex1, grid)[0][:,
 
 ```{code-cell} ipython3
 fig = go.Figure()
-fig.add_trace(go.Scatter(x=grid, y=f_val, name=r'$-3x+2$'))
+fig.add_trace(go.Scatter(x=grid, y=f_val, name=r'-3x+2'))
 fig.add_trace(go.Scatter(x=grid, y=predictions, name='Approximation'))
 
 # Export to PNG file

lectures/status.md

@@ -33,16 +33,16 @@ and the following package versions
 !conda list
 ```
 
+This lecture series has access to the following GPU
+
+```{code-cell} ipython
+!nvidia-smi
+```
+
 You can check the backend used by JAX using:
 
 ```{code-cell} ipython3
 import jax
 # Check if JAX is using GPU
 print(f"JAX backend: {jax.devices()[0].platform}")
-```
-
-and this lecture series also has access to the following GPU
-
-```{code-cell} ipython
-!nvidia-smi
 ```