Completed the documentation for the feature

JamieMair · JamieMair · commit f6f9ca9e2558 · 2023-07-17T16:17:32.000+01:00
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "TensorBoardLogger"
 uuid = "899adc3e-224a-11e9-021f-63837185c80f"
 authors = ["Filippo Vicentini <filippovicentini@gmail.com>"]
-version = "0.1.20"
+version = "0.1.21"
 
 [deps]
 CRC32c = "8bf52ea8-c179-5cab-976a-9e18b702a9bc"
diff --git a/docs/make.jl b/docs/make.jl
@@ -11,11 +11,12 @@ makedocs(
                 "Reading back data" => "deserialization.md",
                 "Extending"    =>  "extending_behaviour.md",
                 "Explicit Interface" => "explicit_interface.md",
-                "Hyperparameter API" => "hyperparameter_api.md"
+                "Hyperparameter logging" => "hyperparameters.md"
             ],
             "Examples"      => Any[
                 "Flux.jl"  => "examples/flux.md"
                 "Optim.jl"  => "examples/optim.md"
+                "Hyperparameter tuning"  => "examples/hyperparameter_tuning.md"
             ]
     ],
     format    = Documenter.HTML(
diff --git a/docs/src/examples/hyperparameter_tuning.md b/docs/src/examples/hyperparameter_tuning.md
@@ -1,4 +1,4 @@
-# Hyperparameter Tuning
+# Hyperparameter tuning
 
 We will start this example by setting up a simple random walk experiment, and seeing the effect of the hyperparameter `bias` on the results.
 
diff --git a/docs/src/hyperparameters.md b/docs/src/hyperparameters.md
@@ -1,12 +1,10 @@
-# Hyperparameter Experiments
+# Hyperparameter logging
 
 In additition to logging the experiments, you may wish to also visualise the effect of hyperparameters on some plotted metrics. This can be done by logging the hyperparameters via the `write_hparams!` function, which takes a dictionary mapping hyperparameter names to their values (currently limited to `Real`, `Bool` or `String` types), along with the names of any metrics that you want to view the effects of. 
 
 You can see how the HParams dashboard in Tensorboard can be used to tune hyperparameters on the [tensorboard website](https://www.tensorflow.org/tensorboard/hyperparameter_tuning_with_hparams).
 
-![hparams dashboard view](https://www.tensorflow.org/tensorboard/images/hparams_parallel_coordinates.png?raw=1)
-
-## HParams API
+## API
 ```@docs
 write_hparams!
 ```
diff --git a/docs/src/index.md b/docs/src/index.md
@@ -121,5 +121,5 @@ As an alternative, you can also log data to TensorBoard through its functional i
 
 ## Hyperparameter tuning
 
-Many experiments rely on hyperparameters, which can be difficult to tune. Tensorboard allows you to visualise the effect of your hyperparameters on your metrics, giving you an intuition for the correct hyperparameters for your task. For information on this API, see the [Hyperparameter API](@ref).
+Many experiments rely on hyperparameters, which can be difficult to tune. Tensorboard allows you to visualise the effect of your hyperparameters on your metrics, giving you an intuition for the correct hyperparameters for your task. For information on this API, see the [Hyperparameter logging](@ref) manual page.
 

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-# Hyperparameter Tuning`
	`1`	`+# Hyperparameter tuning`
`2`	`2`
`3`	`3`	We will start this example by setting up a simple random walk experiment, and seeing the effect of the hyperparameter `bias` on the results.
`4`	`4`
Original file line number	Diff line number	Diff line change
`@@ -121,5 +121,5 @@ As an alternative, you can also log data to TensorBoard through its functional i`
`121`	`121`
`122`	`122`	`## Hyperparameter tuning`
`123`	`123`
`124`		`-Many experiments rely on hyperparameters, which can be difficult to tune. Tensorboard allows you to visualise the effect of your hyperparameters on your metrics, giving you an intuition for the correct hyperparameters for your task. For information on this API, see the [Hyperparameter API](@ref).`
	`124`	`+Many experiments rely on hyperparameters, which can be difficult to tune. Tensorboard allows you to visualise the effect of your hyperparameters on your metrics, giving you an intuition for the correct hyperparameters for your task. For information on this API, see the [Hyperparameter logging](@ref) manual page.`
`125`	`125`