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ENH: Upgrade docker with anaconda==2023.03 (#327)
* ENH: Upgrade docker with anaconda==2023.02 * update matplotlib project='3d' * change matplotlib syntax * update env * remove jax install from github actions * TST: full build * upgrade to cuda12 + jax
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.github/workflows/ci.yml

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@@ -24,19 +24,12 @@ jobs:
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needs: deploy-runner
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runs-on: [self-hosted, cml-gpu]
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container:
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image: docker://mmcky/quantecon-lecture-python:py39-anaconda-2022-10-jb-0.15.1
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image: docker://mmcky/quantecon-lecture-python:cuda-12.1.0-anaconda-2023-03-py310
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options: --gpus all
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steps:
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- uses: actions/checkout@v3
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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# Install Hardware Dependant Libraries
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- name: Install Jax and Upgrade CUDA
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shell: bash -l {0}
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run: |
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pip install --upgrade "jax[cuda]==0.4.2" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
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pip install --upgrade "numpyro[cuda]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
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nvidia-smi
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# Check nvidia drivers
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- name: nvidia Drivers
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shell: bash -l {0}
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- name: Display Pip Versions
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shell: bash -l {0}
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run: pip list
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- name: Download "build" folder (cache)
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uses: dawidd6/action-download-artifact@v2
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with:
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workflow: cache.yml
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branch: main
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name: build-cache
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path: _build
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# - name: Download "build" folder (cache)
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# uses: dawidd6/action-download-artifact@v2
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# with:
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# workflow: cache.yml
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# branch: main
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# name: build-cache
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# path: _build
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# Build Assets (Download Notebooks and PDF via LaTeX)
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- name: Build Download Notebooks (sphinx-tojupyter)
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shell: bash -l {0}

environment.yml

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@@ -11,9 +11,9 @@ dependencies:
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- sphinx-tojupyter==0.3.0
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- sphinxext-rediraffe==0.2.7
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- sphinx-exercise==0.4.1
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- ghp-import==1.1.0
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- sphinxcontrib-youtube==1.1.0
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- sphinx-togglebutton==0.3.1
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- ghp-import==2.1.0
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- sphinxcontrib-youtube==1.2.0
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- sphinx-togglebutton==0.3.2
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- arviz==0.13.0
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- kaleido
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# Docker Requirements

lectures/linear_algebra.md

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@@ -288,8 +288,7 @@ The span is a two-dimensional plane passing through these two points and the ori
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---
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tags: [output_scroll]
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---
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fig = plt.figure(figsize=(10, 8))
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ax = fig.gca(projection='3d')
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ax = plt.figure(figsize=(10, 8)).add_subplot(projection='3d')
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x_min, x_max = -5, 5
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y_min, y_max = -5, 5

lectures/lln_clt.md

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@@ -478,8 +478,7 @@ S = Z.cumsum(axis=1)
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Y = (1 / np.sqrt(ns)) * S
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# Plot
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fig = plt.figure(figsize = (10, 6))
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ax = fig.gca(projection='3d')
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ax = plt.figure(figsize = (10, 6)).add_subplot(projection='3d')
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a, b = -3, 3
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gs = 100

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