Merge pull request #704 from stan-dev/extra-pathfinder-config

Document new pathfinder config
stan-dev · Jan 16, 2024 · 9071597 · 9071597
2 parents 090ea49 + 37aafdf
commit 9071597
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diff --git a/src/cmdstan-guide/pathfinder_config.Rmd b/src/cmdstan-guide/pathfinder_config.Rmd
@@ -25,6 +25,8 @@ method = pathfinder
     history_size = 5 (Default)
     num_psis_draws = 1000 (Default)
     num_paths = 4 (Default)
+    psis_resample = 1 (Default)
+    calculate_lp = 1 (Default)
     save_single_paths = 0 (Default)
     max_lbfgs_iters = 1000 (Default)
     num_draws = 1000 (Default)
@@ -53,6 +55,18 @@ Can differ from `num_psis_draws`.
 - `num_elbo_draws` - Number of Monte Carlo draws to evaluate ELBO.
 Must be a positive integer.  Default value is $25$.
 
+- `psis_resample` - If True ($1$), perform psis resampling on samples returned
+from individual pathfinders. If False ($0$), returns all `num_paths * num_draws samples` draws
+from the individual pathfinders.
+Valid values: $\{0, 1\}$. Default is $1$ (True).
+
+- `calculate_lp` - If True ($1$), log probabilities of the approximate draws
+are calculated and returned with the output. If False ($0$), each pathfinder
+will only  calculate the lp values needed for the ELBO calculation.
+If False, psis resampling cannot be performed and the algorithm returns
+`num_paths * num_draws samples`. The output will still contain any lp values
+used when calculating ELBO scores within L-BFGS iterations.
+Valid values: $\{0, 1\}$. Default is $1$ (True).
 
 
 ## L-BFGS Configuration

diff --git a/src/cmdstan-guide/pathfinder_intro.Rmd b/src/cmdstan-guide/pathfinder_intro.Rmd
@@ -50,6 +50,8 @@ method = pathfinder
     history_size = 5 (Default)
     num_psis_draws = 1000 (Default)
     num_paths = 4 (Default)
+    psis_resample = 1 (Default)
+    calculate_lp = 1 (Default)
     save_single_paths = 0 (Default)
     max_lbfgs_iters = 1000 (Default)
     num_draws = 1000 (Default)
@@ -75,20 +77,20 @@ parallel, the uses importance resampling on the set of returned draws
 to produce the specified number of draws.
 ```
 Path [1] :Initial log joint density = -11.543343
-Path [1] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes 
-              5      -6.748e+00      1.070e-03   1.707e-05    1.000e+00  1.000e+00       126 -6.220e+00 -6.220e+00                  
+Path [1] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes
+              5      -6.748e+00      1.070e-03   1.707e-05    1.000e+00  1.000e+00       126 -6.220e+00 -6.220e+00
 Path [1] :Best Iter: [5] ELBO (-6.219833) evaluations: (126)
 Path [2] :Initial log joint density = -7.443345
-Path [2] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes 
-              5      -6.748e+00      9.936e-05   3.738e-07    1.000e+00  1.000e+00       126 -6.164e+00 -6.164e+00                  
+Path [2] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes
+              5      -6.748e+00      9.936e-05   3.738e-07    1.000e+00  1.000e+00       126 -6.164e+00 -6.164e+00
 Path [2] :Best Iter: [5] ELBO (-6.164015) evaluations: (126)
 Path [3] :Initial log joint density = -18.986308
-Path [3] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes 
-              5      -6.748e+00      2.996e-04   4.018e-06    1.000e+00  1.000e+00       126 -6.201e+00 -6.201e+00                  
+Path [3] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes
+              5      -6.748e+00      2.996e-04   4.018e-06    1.000e+00  1.000e+00       126 -6.201e+00 -6.201e+00
 Path [3] :Best Iter: [5] ELBO (-6.200559) evaluations: (126)
 Path [4] :Initial log joint density = -8.304453
-Path [4] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes 
-              5      -6.748e+00      2.814e-04   2.034e-06    1.000e+00  1.000e+00       126 -6.221e+00 -6.221e+00                  
+Path [4] : Iter      log prob        ||dx||      ||grad||     alpha      alpha0      # evals       ELBO    Best ELBO        Notes
+              5      -6.748e+00      2.814e-04   2.034e-06    1.000e+00  1.000e+00       126 -6.221e+00 -6.221e+00
 Path [4] :Best Iter: [3] ELBO (-6.161276) evaluations: (126)
 Total log probability function evaluations:8404
 ```