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vpuri3 · Jul 26, 2023 · f1be38c · f1be38c
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Showing 6 changed files with 30 additions and 30 deletions.
diff --git a/examples/diffusion_fourier/exp_2d/exp_FNO_linear_nonlinear/plt_training.png b/examples/diffusion_fourier/exp_2d/exp_FNO_linear_nonlinear/plt_training.png
diff --git a/examples/diffusion_fourier/exp_2d/exp_FNO_linear_nonlinear/statistics.txt b/examples/diffusion_fourier/exp_2d/exp_FNO_linear_nonlinear/statistics.txt
@@ -1,19 +1,19 @@
-TRAIN LOSS: 0.03994172 TEST LOSS: 0.04135022 
+TRAIN LOSS: 0.03871075 TEST LOSS: 0.04123595 
 #======================#
 TRAIN STATS
-R² score:       0.8439697
-mean SQR error: 0.03994172
-mean ABS error: 0.16075909
-max  ABS error: 1.0566008
-mean REL error: 6.9465413
-max  REL error: 4.3865045e6
+R² score:       0.8487784
+mean SQR error: 0.03871075
+mean ABS error: 0.15822649
+max  ABS error: 0.9419304
+mean REL error: 5.270242
+max  REL error: 2.634915e6
 #======================#
 #======================#
 TEST  STATS
-R² score:       0.86031735
-mean SQR error: 0.04135022
-mean ABS error: 0.15992492
-max  ABS error: 1.2126786
-mean REL error: 3.2685025
-max  REL error: 290475.8
+R² score:       0.86070335
+mean SQR error: 0.04123595
+mean ABS error: 0.15992007
+max  ABS error: 1.1729906
+mean REL error: 3.6967828
+max  REL error: 392784.5
 #======================#
diff --git a/examples/diffusion_fourier/exp_2d/exp_FNO_nonlin/plt_training.png b/examples/diffusion_fourier/exp_2d/exp_FNO_nonlin/plt_training.png
diff --git a/examples/diffusion_fourier/exp_2d/exp_FNO_nonlin/statistics.txt b/examples/diffusion_fourier/exp_2d/exp_FNO_nonlin/statistics.txt
@@ -1,19 +1,19 @@
-TRAIN LOSS: 0.00067307 TEST LOSS: 0.061007 
+TRAIN LOSS: 0.00059043 TEST LOSS: 0.05867297 
 #======================#
 TRAIN STATS
-R² score:       0.99737066
-mean SQR error: 0.00067307
-mean ABS error: 0.0196111
-max  ABS error: 0.3286597
-mean REL error: 1.7440374
-max  REL error: 1.518056e6
+R² score:       0.99769354
+mean SQR error: 0.00059043
+mean ABS error: 0.01852134
+max  ABS error: 0.28291965
+mean REL error: 0.38249248
+max  REL error: 88166.45
 #======================#
 #======================#
 TEST  STATS
-R² score:       0.793916
-mean SQR error: 0.061007
-mean ABS error: 0.19505797
-max  ABS error: 1.4256942
-mean REL error: 5.497858
-max  REL error: 1.4715734e6
+R² score:       0.8018004
+mean SQR error: 0.05867297
+mean ABS error: 0.19184159
+max  ABS error: 1.4140823
+mean REL error: 7.0414925
+max  REL error: 2.8188798e6
 #======================#
diff --git a/examples/diffusion_fourier/exp_2d/model.jl b/examples/diffusion_fourier/exp_2d/model.jl
@@ -50,7 +50,7 @@ Random.seed!(rng, 201)
 ###
 # FNO model
 ###
-if false
+if true
 
 __data = combine_data2D(_data, K)
 data__ = combine_data2D(data_, K)
@@ -104,8 +104,8 @@ nonlin = Chain(
     )
 linear = Chain(
         Dense(c2, w2, use_bias = false),
-        OpKernel(w1, w1, m),
-        OpKernel(w1, w1, m),
+        OpKernel(w2, w2, m),
+        # OpKernel(w2, w2, m),
     )
 # linear = Dense(c2, w2, use_bias = false)
 bilin  = OpConvBilinear(w1, w2, o, m)

diff --git a/src/train.jl b/src/train.jl
@@ -130,11 +130,11 @@ function train_model(
     # visualization
     if make_plots
         plt_train = plot_training(ITER, _LOSS, LOSS_)
+        png(plt_train, joinpath(dir, "plt_training"))
 
         if ndims(V) == 1
             plts = visualize(V, _data, data_, NN, p, st; nsamples)
 
-            png(plt_train, joinpath(dir, "plt_training"))
             png(plts[1],   joinpath(dir, "plt_traj_train"))
             png(plts[2],   joinpath(dir, "plt_traj_test"))
             png(plts[3],   joinpath(dir, "plt_r2_train"))