Apply suggestions from code review

Co-authored-by: Hong Ge <[email protected]>
TuringLang · Dec 9, 2023 · 0dfc064 · 0dfc064
1 parent 65fb071
commit 0dfc064
Show file tree

Hide file tree

Showing 3 changed files with 8 additions and 9 deletions.
diff --git a/src/essential/Essential.jl b/src/essential/Essential.jl
@@ -43,7 +43,6 @@ export  @model,
         AutoZygote,
         AutoReverseDiff,
         value,
-        verifygrad,
         @logprob_str,
         @prob_str
 

diff --git a/src/mcmc/hmc.jl b/src/mcmc/hmc.jl
@@ -32,7 +32,7 @@ end
 ###
 
 """
-    HMC(ϵ::Float64, n_leapfrog::Int; adtype::ADTypes.AbstractADType = ADTypes.AbstractADType=AutoForwardDiff(; chunksize=0))
+    HMC(ϵ::Float64, n_leapfrog::Int; adtype::ADTypes.AbstractADType = AutoForwardDiff(; chunksize=0))
 
 Hamiltonian Monte Carlo sampler with static trajectory.
 
@@ -41,7 +41,7 @@ Hamiltonian Monte Carlo sampler with static trajectory.
 - `ϵ`: The leapfrog step size to use.
 - `n_leapfrog`: The number of leapfrog steps to use.
 - `adtype`: The automatic differentiation (AD) backend.
-    If not specified, ForwardDiff is used with an automatically determined chunksize.
+    If not specified, `ForwardDiff` is used, with its `chunksize` automatically determined.
 
 # Usage
 
@@ -298,7 +298,7 @@ HMCDA(200, 0.65, 0.3)
 - `λ`: Target leapfrog length.
 - `ϵ`: Initial step size; 0 means automatically search by Turing.
 - `adtype`: The automatic differentiation (AD) backend.
-    If not specified, ForwardDiff is used with an automatically determined chunksize.
+    If not specified, `ForwardDiff` is used, with its `chunksize` automatically determined.
 
 # Reference
 
@@ -373,7 +373,7 @@ Arguments:
 - `Δ_max::Float64` : Maximum divergence during doubling tree.
 - `init_ϵ::Float64` : Initial step size; 0 means automatically searching using a heuristic procedure.
 - `adtype::ADTypes.AbstractADType` : The automatic differentiation (AD) backend.
-    If not specified, ForwardDiff is used with an automatically determined chunksize.
+    If not specified, `ForwardDiff` is used, with its `chunksize` automatically determined.
 
 """
 struct NUTS{AD,space,metricT<:AHMC.AbstractMetric} <: AdaptiveHamiltonian

diff --git a/src/mcmc/sghmc.jl b/src/mcmc/sghmc.jl
@@ -28,8 +28,8 @@ end
 
 Create a Stochastic Gradient Hamiltonian Monte Carlo (SGHMC) sampler.
 
-If the automatic differentiation (AD) backend `adtype` is not provided, ForwardDiff is used
-with automatically determined chunk size.
+If the automatic differentiation (AD) backend `adtype` is not provided, ForwardDiff
+with automatically determined `chunksize` is used.
 
 # Reference
 
@@ -170,8 +170,8 @@ Stochastic gradient Langevin dynamics (SGLD) sampler.
 
 By default, a polynomially decaying stepsize is used.
 
-If the automatic differentiation (AD) backend `adtype` is not provided, ForwardDiff is used
-with automatically determined chunk size.
+If the automatic differentiation (AD) backend `adtype` is not provided, ForwardDiff
+with automatically determined `chunksize` is used.
 
 # Reference