don't use such a high tolerance

SciML · Jun 26, 2021 · 65601fe · 65601fe
1 parent 8a27810
commit 65601fe
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Showing 2 changed files with 3 additions and 3 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "DiffEqFlux"
 uuid = "aae7a2af-3d4f-5e19-a356-7da93b79d9d0"
 authors = ["Chris Rackauckas <[email protected]>"]
-version = "1.40.0"
+version = "1.40.1"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

diff --git a/test/multiple_shoot.jl b/test/multiple_shoot.jl
@@ -1,4 +1,4 @@
-using DiffEqFlux, DiffEqSensitivity, OrdinaryDiffEq, Flux, Optim, Test
+using DiffEqFlux, DiffEqSensitivity, OrdinaryDiffEq, Test
 using DiffEqFlux: group_ranges
 
 ## Test group partitioning helper function
@@ -61,7 +61,7 @@ continuity_term = 200
 function loss_multiple_shooting(p)
     return multiple_shoot(p, ode_data, tsteps, prob_node, loss_function, Tsit5(),
                           group_size; continuity_term,
-                          abstol=1e-3, reltol=1e-3) # test solver kwargs
+                          abstol=1e-8, reltol=1e-6) # test solver kwargs
 end
 
 res_ms = DiffEqFlux.sciml_train(loss_multiple_shooting, neuralode.p,