Enable software version checking

.github/workflows/ci.yml

@@ -4,7 +4,7 @@ jobs:
  preview:
  runs-on: quantecon-gpu
  container:
- image: ghcr.io/quantecon/lecture-python-container:cuda-12.6.0-anaconda-2024-10-py312-b
+ image: ghcr.io/quantecon/lecture-python-container:cuda-12.8.1-anaconda-2024-10-py312
  options: --gpus all
  steps:
  - uses: actions/checkout@v4
@@ -24,13 +24,13 @@ jobs:
  - name: Display Pip Versions
  shell: bash -l {0}
  run: pip list
- - name: Download "build" folder (cache)
- uses: dawidd6/action-download-artifact@v3
- with:
- workflow: cache.yml
- branch: main
- name: build-cache
- path: _build
+ # - name: Download "build" folder (cache)
+ #  uses: dawidd6/action-download-artifact@v3
+ #  with:
+ #  workflow: cache.yml
+ #  branch: main
+ #  name: build-cache
+ #  path: _build
  # Build Assets (Download Notebooks and PDF via LaTeX)
  - name: Build Download Notebooks (sphinx-tojupyter)
  shell: bash -l {0}

lectures/status.md

@@ -21,6 +21,19 @@ This table contains the latest execution statistics.
 These lectures are built on `linux` instances through `github actions` that has 
 access to a `gpu`. These lectures make use of the nvidia `T4` card.
 
+These lectures are using the following python version
+
+```{code-cell} ipython
+!python --version
+```
+
+and the following package versions
+
+```{code-cell} ipython
+:tags: [hide-output]
+!conda list
+```
+
 You can check the backend used by JAX using:
 
 ```{code-cell} ipython3
@@ -33,4 +46,5 @@ and the hardware we are running on:
 
 ```{code-cell} ipython3
 !nvidia-smi
-```
+```
+