From 2540027d05631789fcf1a9c82441c5eb80403ee9 Mon Sep 17 00:00:00 2001
From: Logan Kilpatrick <23kilpatrick23@gmail.com>
Date: Fri, 26 Nov 2021 07:24:13 -0800
Subject: [PATCH 1/6] Update functor.jl

---
 src/functor.jl | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/functor.jl b/src/functor.jl
index ee9eb1d543..4c253280cc 100644
--- a/src/functor.jl
+++ b/src/functor.jl
@@ -48,6 +48,12 @@ function params!(p::Params, x, seen = IdSet())
   end
 end
 
+"""
+    params(model)
+
+Given a model or specific layers from a model, return the trainable parameters
+such that they can be used as input to the `train!` function.
+"""
 function params(m...)
   ps = Params()
   params!(ps, m)

From a12569aff690802f66b50742fe14aa38e4226902 Mon Sep 17 00:00:00 2001
From: Logan Kilpatrick <23kilpatrick23@gmail.com>
Date: Fri, 26 Nov 2021 08:27:55 -0800
Subject: [PATCH 2/6] Update src/functor.jl

Co-authored-by: Michael Abbott <32575566+mcabbott@users.noreply.github.com>
---
 src/functor.jl | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/src/functor.jl b/src/functor.jl
index 4c253280cc..28eb472c24 100644
--- a/src/functor.jl
+++ b/src/functor.jl
@@ -51,8 +51,18 @@ end
 """
     params(model)
 
-Given a model or specific layers from a model, return the trainable parameters
-such that they can be used as input to the `train!` function.
+Given a model or specific layers from a model, create a `Params` object pointing to its trainable parameters.
+
+This can be used with [`gradient`](@ref), or as input to the [`Flux.train!`](@ref Flux.train!) function.
+
+# Examples
+```jldoctest
+julia> params(Chain(Dense(ones(2,3))), softmax)
+Params([[1.0 1.0 1.0; 1.0 1.0 1.0], [0.0, 0.0]])
+
+julia> params(BatchNorm(2, relu))
+Params([Float32[0.0, 0.0], Float32[1.0, 1.0]])
+```
 """
 function params(m...)
   ps = Params()

From 4d56e755aba58197f6fde946ef3de4ed9666b892 Mon Sep 17 00:00:00 2001
From: Logan Kilpatrick <23kilpatrick23@gmail.com>
Date: Fri, 26 Nov 2021 09:03:51 -0800
Subject: [PATCH 3/6] Add note on custom behavior

---
 src/functor.jl | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/functor.jl b/src/functor.jl
index 28eb472c24..25565d0bed 100644
--- a/src/functor.jl
+++ b/src/functor.jl
@@ -55,6 +55,8 @@ Given a model or specific layers from a model, create a `Params` object pointing
 
 This can be used with [`gradient`](@ref), or as input to the [`Flux.train!`](@ref Flux.train!) function.
 
+The behaviour of `params` on custom types can be customized using [`Functor.@functor`](@ref) or [`Flux.trainable`](@ref).
+
 # Examples
 ```jldoctest
 julia> params(Chain(Dense(ones(2,3))), softmax)

From be50da058f8c057536e71bcaf88a96d22229bf39 Mon Sep 17 00:00:00 2001
From: Logan Kilpatrick <23kilpatrick23@gmail.com>
Date: Fri, 26 Nov 2021 20:44:49 -0800
Subject: [PATCH 4/6] Update src/functor.jl

Co-authored-by: Brian Chen <ToucheSir@users.noreply.github.com>
---
 src/functor.jl | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/functor.jl b/src/functor.jl
index 25565d0bed..c4ccd5924b 100644
--- a/src/functor.jl
+++ b/src/functor.jl
@@ -50,6 +50,7 @@ end
 
 """
     params(model)
+    params(layers...)
 
 Given a model or specific layers from a model, create a `Params` object pointing to its trainable parameters.
 

From 428b1d9ea7feda2a5ffd95ae53c783d3e7fff5fc Mon Sep 17 00:00:00 2001
From: Logan Kilpatrick <23kilpatrick23@gmail.com>
Date: Sat, 27 Nov 2021 08:46:34 -0800
Subject: [PATCH 5/6] Add params to the Model parameters section

---
 docs/src/training/training.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/docs/src/training/training.md b/docs/src/training/training.md
index fa8573d6a6..845a22d8a6 100644
--- a/docs/src/training/training.md
+++ b/docs/src/training/training.md
@@ -70,6 +70,10 @@ Such an object contains a reference to the model's parameters, not a copy, such
 
 Handling all the parameters on a layer by layer basis is explained in the [Layer Helpers](../models/basics.md) section. Also, for freezing model parameters, see the [Advanced Usage Guide](../models/advanced.md).
 
+```@docs
+Flux.params
+```
+
 ## Datasets
 
 The `data` argument of `train!` provides a collection of data to train with (usually a set of inputs `x` and target outputs `y`). For example, here's a dummy dataset with only one data point:

From e21b094ab60fc5ebc6b511ce11c5f4cfba766430 Mon Sep 17 00:00:00 2001
From: Logan Kilpatrick <23kilpatrick23@gmail.com>
Date: Sat, 27 Nov 2021 09:12:53 -0800
Subject: [PATCH 6/6] Fix link to Gradient

---
 src/functor.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/functor.jl b/src/functor.jl
index c4ccd5924b..179259a3c6 100644
--- a/src/functor.jl
+++ b/src/functor.jl
@@ -54,7 +54,7 @@ end
 
 Given a model or specific layers from a model, create a `Params` object pointing to its trainable parameters.
 
-This can be used with [`gradient`](@ref), or as input to the [`Flux.train!`](@ref Flux.train!) function.
+This can be used with the `gradient` function, see [Taking Gradients](@ref), or as input to the [`Flux.train!`](@ref Flux.train!) function.
 
 The behaviour of `params` on custom types can be customized using [`Functor.@functor`](@ref) or [`Flux.trainable`](@ref).