Merge pull request #514 from SciML/smalls

don't rebuild things if you're not doing anything fancy

Author: ChrisRackauckas

Project.toml

@@ -1,7 +1,7 @@
 name = "DiffEqBase"
 uuid = "2b5f629d-d688-5b77-993f-72d75c75574e"
 authors = ["Chris Rackauckas <[email protected]>"]
-version = "6.34.0"
+version = "6.34.1"
 
 [deps]
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"

src/init.jl

@@ -3,6 +3,7 @@ cuify(x) = error("To use LinSolveGPUFactorize, you must do `using CuArrays`")
 promote_u0(u0,p,t0) = u0
 promote_tspan(u0,p,tspan,prob,kwargs) = tspan
 get_tmp(x) = nothing
+isdistribution(u0) = false
 
 if VERSION < v"1.4.0-DEV.635"
   # Piracy, should get upstreamed
@@ -18,6 +19,7 @@ function __init__()
 
   @require Distributions="31c24e10-a181-5473-b8eb-7969acd0382f" begin
     handle_distribution_u0(_u0::Distributions.Sampleable) = rand(_u0)
+    isdistribution(_u0::Distributions.Sampleable) = true
   end
 
   @require ForwardDiff="f6369f11-7733-5829-9624-2563aa707210" begin
@@ -54,7 +56,7 @@ function __init__()
 
     @inline ODE_DEFAULT_NORM(u::AbstractArray{<:ForwardDiff.Dual{<:Any,<:ForwardDiff.Dual}},::ForwardDiff.Dual) = sqrt(sum(UNITLESS_ABS2∘value,u) / length(u))
     @inline ODE_DEFAULT_NORM(u::ForwardDiff.Dual{<:Any,ForwardDiff.Dual},::ForwardDiff.Dual) = abs(value(u))
-    
+
     @inline ODE_DEFAULT_NORM(u::AbstractArray{<:ForwardDiff.Dual{<:Any,<:ForwardDiff.Dual}},::ForwardDiff.Dual{<:Any,ForwardDiff.Dual}) = sqrt(sum(UNITLESS_ABS2,u) / length(u))
     @inline ODE_DEFAULT_NORM(u::ForwardDiff.Dual{<:Any,ForwardDiff.Dual},::ForwardDiff.Dual{<:Any,ForwardDiff.Dual}) = abs(u)
 

src/solve.jl

@@ -44,7 +44,7 @@ function solve_call(_prob,args...;merge_callbacks = true, kwargs...)
       callbacks = NamedTuple{(:callback,)}( [DiffEqBase.CallbackSet(_prob.kwargs[:callback], values(kwargs).callback )] )
       kwargs = merge(kwargs_temp, callbacks)
     end
-    kwargs = merge(values(_prob.kwargs), kwargs)
+    kwargs = isempty(_prob.kwargs) ? kwargs : merge(values(_prob.kwargs), kwargs)
   end
 
   T = Core.Compiler.return_type(__solve,Tuple{typeof(_prob),map(typeof, args)...})
@@ -121,9 +121,14 @@ function discretize end
 function get_concrete_problem(prob, kwargs)
   tspan = get_concrete_tspan(prob, kwargs)
   u0 = get_concrete_u0(prob, tspan[1], kwargs)
-  u0 = promote_u0(u0, prob.p, tspan[1])
-  tspan = promote_tspan(u0, prob.p, tspan, prob, kwargs)
-  remake(prob; u0 = u0, tspan = tspan)
+  u0_promote = promote_u0(u0, prob.p, tspan[1])
+  tspan_promote = promote_tspan(u0, prob.p, tspan, prob, kwargs)
+  if isconcreteu0(prob, tspan[1], kwargs) && typeof(u0_promote) === typeof(u0) &&
+                  prob.tspan == tspan && typeof(tspan) === typeof(tspan_promote)
+    return prob
+  else
+    return remake(prob; u0 = u0_promote, tspan = tspan_promote)
+  end
 end
 
 function get_concrete_problem(prob::DDEProblem, kwargs)
@@ -159,6 +164,10 @@ function get_concrete_tspan(prob, kwargs)
   tspan
 end
 
+function isconcreteu0(prob, t0, kwargs)
+  !eval_u0(prob.u0) && prob.u0 !== nothing && !isdistribution(prob.u0)
+end
+
 function get_concrete_u0(prob, t0, kwargs)
   if eval_u0(prob.u0)
     u0 = prob.u0(prob.p, t0)

test/downstream/inference.jl

@@ -44,3 +44,13 @@ function solve_ode(f::F, p::P) where {F,P}
   return sol
 end
 @test_broken @inferred solve_ode(f, (a = 1, b = 1))
+
+using StochasticDiffEq, Test
+u0=1/2
+ff(u,p,t) = u
+gg(u,p,t) = u
+dt = 1//2^(4)
+tspan = (0.0,1.0)
+prob = SDEProblem(ff,gg,u0,(0.0,1.0))
+sol = solve(prob,EM(),dt=dt)
+@inferred solve(prob,EM(),dt=dt)