Update lectures requiring GPU access

Author: mmcky

lectures/_admonition/gpu.md

@@ -0,0 +1,9 @@
+```{admonition} GPU
+:class: warning
+
+This lecture was built using a machine with the latest CUDA and CUDANN frameworks installed with access to a GPU.
+
+To run this lecture on [Google Colab](https://colab.research.google.com/), click on the "play" icon top right, select Colab, and set the runtime environment to include a GPU.
+
+To run this lecture on your own machine, you need to install the software listed following this notice.
+```

lectures/ar1_bayes.md

@@ -13,15 +13,17 @@ kernelspec:
 
 # Posterior Distributions for  AR(1) Parameters
 
-We'll begin with some Python imports.
-
+```{include} _admonition/gpu.md
+```
 
 ```{code-cell} ipython3
-:tags: [hide-output, skip-execution]
+:tags: [skip-execution]
 
 !pip install arviz pymc numpyro jax
 ```
 
+We'll begin with some Python imports.
+
 ```{code-cell} ipython3
 
 import arviz as az

lectures/back_prop.md

@@ -13,6 +13,9 @@ kernelspec:
 
 # Introduction to Artificial Neural Networks
 
+```{include} _admonition/gpu.md
+```
+
 ```{code-cell} ipython3
 :tags: [skip-execution]
 

lectures/bayes_nonconj.md

@@ -13,6 +13,15 @@ kernelspec:
 
 # Non-Conjugate Priors
 
+```{include} _admonition/gpu.md
+```
+
+```{code-cell} ipython3
+:tags: [skip-execution]
+
+!pip install numpyro pyro-ppl torch jax
+```
+
 This lecture is a sequel to the {doc}`quantecon lecture <prob_meaning>`.
 
 That lecture offers a Bayesian interpretation of probability in a setting in which the likelihood function and the prior distribution
@@ -43,13 +52,6 @@ The two Python modules are
 
 As usual, we begin by importing some Python code.
 
-```{code-cell} ipython3
-:tags: [hide-output, skip-execution]
-
-# install dependencies
-!pip install numpyro pyro-ppl torch jax
-```
-
 ```{code-cell} ipython3
 import numpy as np
 import seaborn as sns

lectures/mix_model.md

@@ -14,12 +14,12 @@ kernelspec:
 (likelihood-ratio-process)=
 # Incorrect Models
 
-In addition to what's in Anaconda, this lecture will need the following libraries:
+```{include} _admonition/gpu.md
+```
 
 ```{code-cell} ipython
----
-tags: [hide-output, skip-execution]
----
+:tags: [skip-execution]
+
 !pip install numpyro jax
 ```