Simplify GPU admonition and add to all JAX lectures

lectures/aiyagari.md

@@ -22,6 +22,9 @@ kernelspec:
 
 # The Aiyagari Model
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/ak_aiyagari.md

@@ -14,6 +14,9 @@ kernelspec:
 
 # A Long-Lived, Heterogeneous Agent, Overlapping Generations Model
 
+```{include} _admonition/gpu.md
+```
+
 In addition to what's in Anaconda, this lecture will need the following library
 
 ```{code-cell} ipython3

lectures/endogenous_lake.md

@@ -22,6 +22,9 @@ kernelspec:
 
 # Lake Model with an Endogenous Job Finding Rate
 
+```{include} _admonition/gpu.md
+```
+
 ```{index} single: Lake Model, Endogenous
 ```
 

lectures/ifp_advanced.md

@@ -19,6 +19,9 @@ kernelspec:
 
 # {index}`The Income Fluctuation Problem V: Stochastic Returns on Assets <single: The Income Fluctuation Problem V: Stochastic Returns on Assets>`
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/ifp_discrete.md

@@ -13,6 +13,8 @@ kernelspec:
 
 # The Income Fluctuation Problem I: Discretization and VFI
 
+```{include} _admonition/gpu.md
+```
 
 ## Overview
 

lectures/ifp_egm.md

@@ -21,6 +21,9 @@ kernelspec:
 
 # {index}`The Income Fluctuation Problem III: The Endogenous Grid Method <single: The Income Fluctuation Problem III: The Endogenous Grid Method>`
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/ifp_egm_transient_shocks.md

@@ -21,6 +21,9 @@ kernelspec:
 
 # {index}`The Income Fluctuation Problem IV: Transient Income Shocks <single: The Income Fluctuation Problem IV: Transient Income Shocks>`
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/ifp_opi.md

@@ -13,6 +13,8 @@ kernelspec:
 
 # The Income Fluctuation Problem II: Optimistic Policy Iteration
 
+```{include} _admonition/gpu.md
+```
 
 ## Overview
 

lectures/lake_model.md

@@ -22,6 +22,9 @@ kernelspec:
 
 # A Lake Model of Employment and Unemployment
 
+```{include} _admonition/gpu.md
+```
+
 ```{index} single: Lake Model
 ```
 

lectures/mccall_fitted_vfi.md

@@ -21,6 +21,9 @@ kernelspec:
 
 # Job Search IV: Fitted Value Function Iteration
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/mccall_model.md

@@ -22,6 +22,9 @@ kernelspec:
 
 # Job Search I: The McCall Search Model
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/mccall_model_with_sep_markov.md

@@ -24,6 +24,9 @@ kernelspec:
 
 # Job Search III: Search with Separation and Markov Wages
 
+```{include} _admonition/gpu.md
+```
+
 ```{index} single: An Introduction to Job Search
 ```
 

lectures/mccall_model_with_separation.md

@@ -22,6 +22,9 @@ kernelspec:
 
 # Job Search II: Search and Separation
 
+```{include} _admonition/gpu.md
+```
+
 ```{index} single: An Introduction to Job Search
 ```
 

lectures/mccall_persist_trans.md

@@ -21,6 +21,9 @@ kernelspec:
 
 # Job Search V: Persistent and Transitory Wage Shocks
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/mle.md

@@ -21,6 +21,9 @@ kernelspec:
 
 # Maximum Likelihood Estimation
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/newton_method.md

@@ -24,6 +24,9 @@ kernelspec:
 
 # Using Newton's Method to Solve Economic Models
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```

lectures/os_egm_jax.md

@@ -19,6 +19,9 @@ kernelspec:
 
 # {index}`Optimal Savings VI: EGM with JAX <single: Optimal Savings VI: EGM with JAX>`
 
+```{include} _admonition/gpu.md
+```
+
 ```{contents} Contents
 :depth: 2
 ```