Fix extra_model_workflow

Author: SCiarella

benchmark.jl

@@ -18,7 +18,11 @@ ispath(compdir) || mkpath(compdir)
 
 # List configurations files
 using Glob
-list_confs = glob("*.yaml", confdir)
+exclude_patterns = ["att", "cno"]
+exclude_patterns = ["cno"]
+@warn "Excluding configurations with patterns: $(exclude_patterns)"
+all_confs = glob("*.yaml", confdir)
+list_confs = filter(conf -> all(!occursin(pat, conf) for pat in exclude_patterns), all_confs)
 if isempty(list_confs)
     @error "No configuration files found in $confdir"
 end

cnn_model_workflow.jl

@@ -357,7 +357,6 @@ let
         postseed = seeds.post,
         dns_seeds_train,
         dns_seeds_valid,
-        dns_seeds_test,
         nunroll = conf["posteriori"]["nunroll"],
         nsamples = conf["posteriori"]["nsamples"],
         dt = T(conf["posteriori"]["dt"]),

configs/snellius/att_1.yaml

@@ -11,7 +11,7 @@ params:
   tsim: 5.0
   savefreq: 50
   ndns: 4096
-  nles: [128]
+  nles: [64]
   filters: ["FaceAverage()"]
   icfunc: "(setup, psolver, rng) -> random_field(setup, T(0); kp=20, psolver, rng)"
   method: "RKMethods.Wray3(; T)"
@@ -33,8 +33,10 @@ closure:
   use_bias: [true, true, true, true, false]
   use_attention: [true, false, false, false, false]
   emb_sizes: [124, 124, 124, 124, 124]
-  Ns: [148, 144, 140, 136, 132]
-  patch_sizes: [37, 36, 35, 34, 33]
+#  Ns: [148, 144, 140, 136, 132]
+  Ns: [ 84,  80,  76,  72,  68]
+#  patch_sizes: [37, 36, 35, 34, 33]
+  patch_sizes: [21, 20, 19, 18, 17]
   n_heads: [4, 4, 4, 4, 4]
   sum_attention: [false, false, false, false, false]
   rng: "Xoshiro(seeds.θ_start)"

extra_model_workflow.jl

@@ -175,7 +175,7 @@ dns_seeds_test = dns_seeds[ntrajectory:ntrajectory]
 docreatedata = conf["docreatedata"]
 for i = 1:ntrajectory
 	if i%numtasks == taskid - 1
-		docreatedata && createdata(; params, seed = dns_seeds[i], outdir, backend)
+		docreatedata && createdata(; params, seed = dns_seeds[i], outdir, backend, dataproj = conf["dataproj"])
 	end
 end
 @info "Data generated"
@@ -283,6 +283,7 @@ let
         do_plot = conf["priori"]["do_plot"],
         plot_train = conf["priori"]["plot_train"],
         nepoch,
+        dataproj = conf["dataproj"],
     )
 end
 end
@@ -380,6 +381,7 @@ let
         do_plot = conf["posteriori"]["do_plot"],
         plot_train = conf["posteriori"]["plot_train"],
         sensealg = haskey(conf["posteriori"],:sensealg) ? eval(Meta.parse(conf["posteriori"]["sensealg"])) : nothing,
+        dataproj = conf["dataproj"],
     )
 end
 end
@@ -470,11 +472,11 @@ let
             eprior.model_post[ig, ifil, iorder] = compute_eprior(closure, device(θ_cnn_post[ig, ifil, iorder]), st, testset...)
         end
     end
-    jldsave(joinpath(outdir_model, "eprior.jld2"); eprior...)
+    jldsave(joinpath(outdir_model, "eprior_nles=$(params.nles[1]).jld2"); eprior...)
 end
 clean()
 
-eprior = namedtupleload(joinpath(outdir_model, "eprior.jld2"))
+eprior = namedtupleload(joinpath(outdir_model, "eprior_nles=$(params.nles[1]).jld2"))
 
 ########################################################################## #src
 
@@ -533,10 +535,10 @@ let
         @info "Epost model_post" epost.model_post[I, :]
         clean()
     end
-    jldsave(joinpath(outdir_model, "epost.jld2"); epost...)
+    jldsave(joinpath(outdir_model, "epost_nles=$(params.nles[1]).jld2"); epost...)
 end
 
-epost = namedtupleload(joinpath(outdir_model, "epost.jld2"))
+epost = namedtupleload(joinpath(outdir_model, "epost_nles=$(params.nles[1]).jld2"))
 
 
 ########################################################################## #src
@@ -724,12 +726,12 @@ let
             push!(energyhistory[:model_post][I], Point2f(t, e))
         end
     end
-    jldsave(joinpath(outdir_model, "history.jld2"); energyhistory, divergencehistory)
+    jldsave(joinpath(outdir_model, "history_nles=$(params.nles[1]).jld2"); energyhistory, divergencehistory)
     clean()
 end
 end
 
-(; divergencehistory, energyhistory) = namedtupleload(joinpath(outdir_model, "history.jld2"));
+(; divergencehistory, energyhistory) = namedtupleload(joinpath(outdir_model, "history_nles=$(params.nles[1]).jld2"));
 
 ########################################################################## #src
 
@@ -1009,11 +1011,11 @@ let
         end
         clean()
     end
-    jldsave("$outdir_model/solutions.jld2"; u = utimes, t = times_exact, itime_max_DIF)
+    jldsave("$outdir_model/solutions_nles=$(params.nles[1]).jld2"; u = utimes, t = times_exact, itime_max_DIF)
 end;
 
 # Load solution
-solutions = namedtupleload("$outdir_model/solutions.jld2");
+solutions = namedtupleload("$outdir_model/solutions_nles=$(params.nles[1]).jld2");
 
 ########################################################################## #src
 

src/train.jl

@@ -239,7 +239,6 @@ function trainpost(;
     postseed,
     dns_seeds_train,
     dns_seeds_valid,
-    dns_seeds_test,
     nunroll,
     nsamples = 1,
     closure,
@@ -335,7 +334,7 @@ function trainpost(;
 
 
         # For the callback I am going to use the a-posteriori error estimator
-        sample = namedtupleload(getdatafile(outdir, nles, Φ, dns_seeds_test[1]))
+        sample = namedtupleload(getdatafile(outdir, nles, Φ, dns_seeds_valid[1]))
         it = 1:(nunroll_valid+1)
         data_cb = (;
             u = selectdim(sample.u, ndims(sample.u), it) |> collect |> device,