diff --git a/src/cuda/cudnn.jl b/src/cuda/cudnn.jl
index a15637f77f..3414939853 100644
--- a/src/cuda/cudnn.jl
+++ b/src/cuda/cudnn.jl
@@ -5,7 +5,7 @@ function (BN::Flux.BatchNorm)(x::Union{CuArray{T,2},CuArray{T,4},CuArray{T,5}},
   
   @assert BN.affine "BatchNorm: only affine=true supported on gpu"
   @assert BN.track_stats "BatchNorm: only track_stats=true supported on gpu"
-  @assert length(BN.β) == size(x, ndims(x)-1) "BatchNorm: input has wronng number of channels"
+  @assert length(BN.β) == size(x, ndims(x)-1) "BatchNorm: input has wrong number of channels"
   return BN.λ.(batchnorm(BN.γ, BN.β, x, BN.μ, BN.σ², BN.momentum; 
                   cache=cache, alpha=1, beta=0, eps=BN.ϵ, 
                   training=Flux._isactive(BN)))
diff --git a/src/layers/normalise.jl b/src/layers/normalise.jl
index 446575f355..0f2696a50a 100644
--- a/src/layers/normalise.jl
+++ b/src/layers/normalise.jl
@@ -431,6 +431,10 @@ function InstanceNorm(chs::Int, λ=identity;
                     affine=false, track_stats=false,
                     ϵ=1f-5, momentum=0.1f0)
 
+  if track_stats
+    Base.depwarn("`track_stats=true` will be removed from InstanceNorm in Flux 0.14. The default value is `track_stats=false`, which will work as before.", :InstanceNorm)
+  end
+
   β = affine ? initβ(chs) : nothing
   γ = affine ? initγ(chs) : nothing
   μ = track_stats ? zeros32(chs) : nothing
@@ -529,6 +533,10 @@ function GroupNorm(chs::Int, G::Int, λ=identity;
               affine=true, track_stats=false,
               ϵ=1f-5, momentum=0.1f0)
 
+if track_stats
+  Base.depwarn("`track_stats=true` will be removed from GroupNorm in Flux 0.14. The default value is `track_stats=false`, which will work as before.", :GroupNorm)
+end
+
   chs % G == 0 || error("The number of groups ($(G)) must divide the number of channels ($chs)")
 
   β = affine ? initβ(chs) : nothing
diff --git a/src/optimise/train.jl b/src/optimise/train.jl
index dac294cb19..b6d6986285 100644
--- a/src/optimise/train.jl
+++ b/src/optimise/train.jl
@@ -38,6 +38,9 @@ struct SkipException <: Exception end
 Call `Flux.skip()` in a callback to indicate when a callback condition is met.
 This will trigger the train loop to skip the current data point and not update with the calculated gradient.
 
+!!! note
+    `Flux.skip()` will be removed from Flux 0.14
+
 # Examples
 ```julia
 cb = function ()
@@ -46,6 +49,8 @@ end
 ```
 """
 function skip()
+  Base.depwarn("""Flux.skip() will be removed from Flux 0.14.
+                  and should be replaced with `continue` in an ordinary `for` loop.""", :skip)
   throw(SkipException())
 end
 
@@ -58,6 +63,9 @@ struct StopException <: Exception end
 Call `Flux.stop()` in a callback to indicate when a callback condition is met.
 This will trigger the train loop to stop and exit.
 
+!!! note
+    `Flux.stop()` will be removed from Flux 0.14. It should be replaced with `break` in an ordinary `for` loop.
+
 # Examples
 ```julia
 cb = function ()
@@ -66,6 +74,8 @@ end
 ```
 """
 function stop()
+  Base.depwarn("""Flux.stop() will be removed from Flux 0.14.
+                  It should be replaced with `break` in an ordinary `for` loop.""", :stop)
   throw(StopException())
 end
 
@@ -140,8 +150,11 @@ end
 Run `body` `N` times. Mainly useful for quickly doing multiple epochs of
 training in a REPL.
 
+!!! note
+    The macro `@epochs` will be removed from Flux 0.14. Please just write an ordinary `for` loop.
+
 # Examples
-```jldoctest
+```julia
 julia> Flux.@epochs 2 println("hello")
 [ Info: Epoch 1
 hello
@@ -150,6 +163,8 @@ hello
 ```
 """
 macro epochs(n, ex)
+  Base.depwarn("""The macro `@epochs` will be removed from Flux 0.14.
+                  As an alternative, you can write a simple `for i in 1:epochs` loop.""", Symbol("@epochs"), force=true)
   :(@progress for i = 1:$(esc(n))
       @info "Epoch $i"
       $(esc(ex))
diff --git a/src/utils.jl b/src/utils.jl
index ad963d5ed6..83ae222aa5 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -648,7 +648,8 @@ julia> loss() = rand();
 julia> trigger = Flux.patience(() -> loss() < 1, 3);
 
 
-julia> Flux.@epochs 10 begin
+julia> for i in 1:10
+         @info "Epoch \$i"
          trigger() && break
        end
 [ Info: Epoch 1
@@ -685,7 +686,8 @@ julia> loss = let l = 0
 julia> es = Flux.early_stopping(loss, 3);
 
 
-julia> Flux.@epochs 10 begin
+julia> for i in 1:10
+         @info "Epoch \$i"
          es() && break
        end
 [ Info: Epoch 1
@@ -726,7 +728,8 @@ julia> f = let v = 10
 julia> trigger = Flux.plateau(f, 3; init_score=10, min_dist=18);
 
 
-julia> Flux.@epochs 10 begin
+julia> for i in 1:10
+         @info "Epoch \$i"
          trigger() && break
        end
 [ Info: Epoch 1