Merge branch 'JuliaLogging:master' into fix-MultilineChartContent-not-defined

Author: ldeso

.github/workflows/UnitTest.yml

@@ -13,7 +13,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [macos-latest, ubuntu-latest]
-        julia_version: ["1.3", "1", "nightly"]
+        julia_version: ["1.6", "1", "nightly"]
 
     runs-on: ${{ matrix.os }}
     env:

.gitignore

@@ -6,4 +6,4 @@ test/test_logs
 docs/Manifest.toml
 
 gen/proto
-gen/protojl
+gen/protojl

Project.toml

@@ -1,7 +1,7 @@
 name = "TensorBoardLogger"
 uuid = "899adc3e-224a-11e9-021f-63837185c80f"
 authors = ["Filippo Vicentini <[email protected]>"]
-version = "0.1.20"
+version = "0.1.23"
 
 [deps]
 CRC32c = "8bf52ea8-c179-5cab-976a-9e18b702a9bc"
@@ -14,17 +14,20 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 [compat]
 FileIO = "1.2.3"
 ImageCore = "0.8.1, 0.9"
-ProtoBuf = "0.10, 0.11"
+ProtoBuf = "1.0.11"
 Requires = "0.5, 1"
-StatsBase = "0.27, 0.28, 0.29, 0.30, 0.31, 0.32, 0.33"
-julia = "1.3"
+StatsBase = "0.27, 0.28, 0.29, 0.30, 0.31, 0.32, 0.33, 0.34"
+julia = "1.6"
 
 [extras]
-Minio = "4281f0d9-7ae0-406e-9172-b7277c1efa20"
+Cairo = "159f3aea-2a34-519c-b102-8c37f9878175"
+Fontconfig = "186bb1d3-e1f7-5a2c-a377-96d770f13627"
+Gadfly = "c91e804a-d5a3-530f-b6f0-dfbca275c004"
 ImageMagick = "6218d12a-5da1-5696-b52f-db25d2ecc6d1"
 LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
+Minio = "4281f0d9-7ae0-406e-9172-b7277c1efa20"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

README.md

@@ -39,8 +39,8 @@ logger in Julia:
 
 You can log to TensorBoard any type. Numeric types will be logged as scalar,
 arrays will be binned into histograms, images and audio will be logged as such,
-and we even support [Plots](https://github.com/JuliaPlots/Plots.jl) and
-[PyPlot](https://github.com/JuliaPlots/Plots.jl) figures!
+and we even support [Plots](https://github.com/JuliaPlots/Plots.jl),
+[PyPlot](https://github.com/JuliaPlots/Plots.jl) and [Gadfly](https://github.com/GiovineItalia/Gadfly.jl) figures!
 
 For details about how types are logged by default, or how to customize this behaviour for your custom types,
 refer to the documentation or the examples folder.
@@ -71,7 +71,7 @@ end
 ```
 
 ## Integration with third party packages
-We also support native logging of the types defined by a few third-party packages, such as `Plots` and `PyPlot` plots.
+We also support native logging of the types defined by a few third-party packages, such as `Plots`, `PyPlot` and `Gadfly` plots.
 If there are other libraries that you think we should include in the list, please open an issue.
 
 ## Roadmap

docs/make.jl

@@ -10,11 +10,13 @@ makedocs(
                 "Backends"     =>  "custom_behaviour.md",
                 "Reading back data" => "deserialization.md",
                 "Extending"    =>  "extending_behaviour.md",
-                "Explicit Interface" => "explicit_interface.md"
+                "Explicit Interface" => "explicit_interface.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(

docs/src/custom_behaviour.md

@@ -5,7 +5,7 @@ value is sent to:
 
   - `::AbstractVector{<:Real}` -> [Histogram backend](https://www.tensorflow.org/guide/tensorboard_histograms) as a vector
   - `::StatsBase.Histogram` -> [Histogram backend](https://www.tensorflow.org/guide/tensorboard_histograms)
-  - `(bin_edges, weights)::Tuple{AbstractVector,AbstractVector}` where `length(bin_edges)==length(weights)+1`, is interpreted as an histogram. (*Will be deprecated.* Please use `TBHistogram(edges, weights)` for this).
+  <!-- - `(bin_edges, weights)::Tuple{AbstractVector,AbstractVector}` where `length(bin_edges)==length(weights)+1`, is interpreted as an histogram. (*Will be deprecated.* Please use `TBHistogram(edges, weights)` for this). -->
   - `::Real` -> Scalar backend
   - `::AbstractArray{<:Colorant}` -> [Image backend](https://www.tensorflow.org/tensorboard/r2/image_summaries)
   - `::Any` -> Text Backend

docs/src/examples/hyperparameter_tuning.md

@@ -0,0 +1,53 @@
+# 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.
+
+First, import the packages we will need with:
+```julia
+using TensorBoardLogger, Logging
+using Random
+```
+Next, we will create a function which runs the experiment and logs the results, include the hyperparameters stored in the `config` dictionary.
+```julia
+function run_experiment(id, config)
+    logger = TBLogger("random_walk/run$id", tb_append)
+
+    # Specify all the metrics we want to track in a list
+    metric_names = ["scalar/position"]
+    write_hparams!(logger, config, metric_names)
+
+    epochs = config["epochs"]
+    sigma = config["sigma"]
+    bias = config["bias"]
+    with_logger(logger) do
+        x = 0.0
+        for i in 1:epochs
+            x += sigma * randn() + bias
+            @info "scalar" position = x
+        end
+    end
+    nothing
+end
+```
+Now we can write a script which runs an experiment over a set of parameter values.
+```julia
+id = 0
+for bias in LinRange(-0.1, 0.1, 11)
+    for epochs in [50, 100]
+        config = Dict(
+            "bias"=>bias,
+            "epochs"=>epochs,
+            "sigma"=>0.1
+        )
+        run_experiment(id, config)
+        id += 1
+    end
+end
+```
+
+Below is an example of the dashboard you get when you open Tensorboard with the command:
+```sh
+tensorboard --logdir=random_walk
+```
+
+![tuning plot](tuning.png)

docs/src/examples/tuning.png

@@ -44,7 +44,7 @@ See [TensorBoard Custom Scalar page](https://github.com/tensorflow/tensorboard/t
 
 For example, to combine in the same plot panel the two curves logged under tags `"Curve/1"` and `"Curve/2"` you can run once the command:
 ```julia
-layout = Dict("Cat" => Dict("Curve" => ("Multiline", ["Curve/1", "Curve/2"])))
+layout = Dict("Cat" => Dict("Curve" => (tb_multiline, ["Curve/1", "Curve/2"])))
 
 log_custom_scalar(lg, layout)
 

docs/src/explicit_interface.md

@@ -12,7 +12,7 @@ At the end of this step, every pair in `objects` will be logged to a specific
 backend, according to the following rules:
 
   - `::AbstractVector{<:Real}` -> [Histogram backend](https://www.tensorflow.org/guide/tensorboard_histograms) as a vector
-  - `::Tuple{AbstractVector,AbstractVector}` [Histogram backend](https://www.tensorflow.org/guide/tensorboard_histograms) as an histogram
+  <!-- - `::Tuple{AbstractVector,AbstractVector}` [Histogram backend](https://www.tensorflow.org/guide/tensorboard_histograms) as an histogram -->
   - `::Real` -> Scalar backend
   - `::AbstractArray{<:Colorant}` -> [Image backend](https://www.tensorflow.org/tensorboard/r2/image_summaries)
   - `::Any` -> Text Backend