brief documentation for Dist <: GenFn

probcomp · georgematheos · May 17, 2020 · May 17, 2020 · May 17, 2020 · May 18, 2020
commit 61673a46cef1af989b003e226e762fc21c1814eb
diff --git a/docs/src/ref/distributions.md b/docs/src/ref/distributions.md
@@ -1,5 +1,11 @@
 # Probability Distributions
 
+In Gen, a probability distribution is a generative function which makes a single random choice
+and returns the value of this choice.  The choicemap for a probability distribution
+is always a [`ValueChoiceMap`](@ref).  In addition to supporting the regular `GFI` methods,
+every distribution supports the methods [`random`](@ref) and [`logpdf`](@ref), described 
+in the [Distribution API](@ref custom_distributions).
+
 Gen provides a library of built-in probability distributions, and two ways of
 writing custom distributions, both of which are explained below:
 

diff --git a/docs/src/ref/extending.md b/docs/src/ref/extending.md
@@ -110,7 +110,7 @@ Gen's Distribution interface directly, as defined below.
 Probability distributions are singleton types whose supertype is `Distribution{T}`, where `T` indicates the data type of the random sample.
 
 ```julia
-abstract type Distribution{T} end
+abstract type Distribution{T} <: GenerativeFunction{T, DistributionTrace} end
 ```
 
 A new Distribution type must implement the following methods:
@@ -146,6 +146,9 @@ has_output_grad
 logpdf_grad
 ```
 
+Any custom distribution will automatically be a `GenerativeFunction` since `Distribution <: GenerativeFunction`;
+implementations of all GFI methods are automatically provided in terms of `random` and `logpdf`.
+
 ## Custom generative functions
 
 We recommend the following steps for implementing a new type of generative function, and also looking at the implementation for the [`DynamicDSLFunction`](@ref) type as an example.