Merge pull request #65 from AtelierArith/increase-epoch-500-to-1000

Increase epoch 500 to 1000

cfgs/example3d_broken.toml

@@ -21,7 +21,7 @@ device_id = 0
 [training]
 seed = 12345
 batchsize = 64
-epochs = 500
+epochs = 1000
 iterations = 100
 base_lr = 0.0015
 opt = "ADAM"

cfgs/example3d_broken_prior_potential.toml

@@ -21,7 +21,7 @@ device_id = 0
 [training]
 seed = 12345
 batchsize = 64
-epochs = 500
+epochs = 1000
 iterations = 100
 base_lr = 0.0015
 opt = "ADAM"

cfgs/example3d_broken_prior_potential_lr_low.toml

@@ -0,0 +1,53 @@
+# setup DeviceParams for example
+# device_id = -1 # <--- train with CPU
+# device_id = 0 # <--- train with GPU its Device ID is 0
+# device_id = 1 # <--- train with GPU its Device ID is 1
+
+device_id = 0
+
+
+# setup TrainingParams
+#
+# for _ in 1:epochs
+#    for _ in 1:iterations
+#       # extract batchsize data
+#       z = rand(prior, lattice_shape..., batchsize)
+#       gs = Flux.gradient(ps) do
+#                do something
+#       end
+#       Flux.Optimise.update!(opt(base_lr), ps, gs)
+#    end
+# end
+[training]
+seed = 12345
+batchsize = 64
+epochs = 1000
+iterations = 100
+base_lr = 0.0005
+opt = "ADAM"
+prior = "Potential{Float32}(; m²=-4f0, λ=8f0)"
+pretrained = ""
+
+# setup PhysicalParams
+#
+# lattice_shape = (L, L) if Nd = 2
+# lattice_shape = (L, L, L) if Nd = 3
+# action = ScalarPhi4Action(M2, lam)
+[physical]
+L = 8
+Nd = 3
+M2 = -4.0 # m²
+lam = 8.0 # λ
+
+
+# setup ModelParams
+#
+[model]
+seed = 2021
+n_layers = 16
+hidden_sizes = [8, 8]
+kernel_size = 3
+inC = 1
+outC = 2
+use_final_tanh = true
+use_bn = false