Revert "resnet"

This reverts commit 206c8f7.

docs/src/tutorials/allen_cahn.md

@@ -26,7 +26,7 @@ bcs = [u(x,0) ~ x^2 * cospi(x),
 
 Then we define the neural net, the sampler, and the training strategy.
 ```@example allen
-chain = ResNet(2, 1, tanh; hidden_dims=16, num_layers=4)
+chain = FullyConnected(2, 1, tanh; hidden_dims=16, num_layers=4)
 pinn = PINN(chain)
 sampler = QuasiRandomSampler(500, (300, 100))
 strategy = NonAdaptiveTraining(1, (50, 1))

docs/src/tutorials/ode.md

@@ -33,8 +33,8 @@ In this part of the tutorial, we will employ [`BetaRandomSampler`](@ref) to gene
 
 ```@example ODE
 # Constructing the physics-informed neural network (PINN)
-pinn = PINN(x = ResNet(1, 1, sin; hidden_dims=8, num_layers=3),
-            y = ResNet(1, 1, sin; hidden_dims=8, num_layers=3))
+pinn = PINN(x = FullyConnected(1, 1, sin; hidden_dims=8, num_layers=3),
+            y = FullyConnected(1, 1, sin; hidden_dims=8, num_layers=3))
 
 # Setting up the sampler, training strategy and problem
 sampler = BetaRandomSampler(200, 1)

docs/src/tutorials/sod.md

@@ -38,9 +38,9 @@ domains = [t ∈ Interval(t_min, t_max), x ∈ Interval(x_min, x_max)]
 ```
 
 ```@example SOD
-pinn = PINN(u=ResNet(2, 1, tanh; num_layers=4, hidden_dims=16),
-            ρ=ResNet(2, 1, tanh; num_layers=4, hidden_dims=16),
-            p=ResNet(2, 1, tanh; num_layers=4, hidden_dims=16))
+pinn = PINN(u=FullyConnected(2, 1, tanh; num_layers=4, hidden_dims=16),
+            ρ=FullyConnected(2, 1, tanh; num_layers=4, hidden_dims=16),
+            p=FullyConnected(2, 1, tanh; num_layers=4, hidden_dims=16))
 
 sampler = QuasiRandomSampler(1000, 400)