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2 changes: 1 addition & 1 deletion .github/workflows/cache.yml
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Expand Up @@ -24,7 +24,7 @@ jobs:
auto-update-conda: true
auto-activate-base: true
miniconda-version: 'latest'
python-version: "3.12"
python-version: "3.13"
environment-file: environment.yml
activate-environment: quantecon
- name: Install jax (and install checks for GPU)
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2 changes: 1 addition & 1 deletion .github/workflows/ci.yml
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Expand Up @@ -20,7 +20,7 @@ jobs:
auto-update-conda: true
auto-activate-base: true
miniconda-version: 'latest'
python-version: "3.12"
python-version: "3.13"
environment-file: environment.yml
activate-environment: quantecon
- name: Install jax (and install checks for GPU)
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2 changes: 1 addition & 1 deletion .github/workflows/publish.yml
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Expand Up @@ -23,7 +23,7 @@ jobs:
auto-update-conda: true
auto-activate-base: true
miniconda-version: 'latest'
python-version: "3.12"
python-version: "3.13"
environment-file: environment.yml
activate-environment: quantecon
- name: Install jax (and install checks for GPU)
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21 changes: 9 additions & 12 deletions environment.yml
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Expand Up @@ -2,21 +2,18 @@ name: quantecon
channels:
- default
dependencies:
- python=3.12
- anaconda=2024.10
- python=3.13
- anaconda=2025.06
- pip
- pip:
- jupyter-book==1.0.3
- quantecon-book-theme==0.7.6
- sphinx-tojupyter==0.3.0
- jupyter-book==1.0.4post1
- quantecon-book-theme==0.8.3
- sphinx-tojupyter==0.3.1
- sphinxext-rediraffe==0.2.7
- sphinx-reredirects==0.1.4
- sphinx-exercise==1.0.1
- sphinx-proof==0.2.0
- ghp-import==1.1.0
- sphinxcontrib-youtube==1.3.0 #Version 1.3.0 is required as quantecon-book-theme is only compatible with sphinx<=5
- sphinx-proof==0.2.1
- sphinxcontrib-youtube==1.4.1
- sphinx-togglebutton==0.3.2
- kaleido # generating static images support
# Docker Requirements
- pytz
- sphinx-reredirects==0.1.4


13 changes: 13 additions & 0 deletions lectures/status.md
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Expand Up @@ -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
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