Java implementation with test

.gitattributes

@@ -1 +1,3 @@
 * text eol=lf
+*.png binary
+*.bz2 binary

.github/workflows/ci.yaml

@@ -98,3 +98,17 @@ jobs:
     - name: Tests
       working-directory: Go
       run: bats test.bats
+
+  java:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v3
+    - name: Setup
+      run: |
+        sudo npm install -g bats
+    - name: Build
+      working-directory: Java
+      run: make jar
+    - name: Tests
+      working-directory: Java
+      run: bats test.bats

.gitignore

@@ -1 +1,3 @@
 semeion.data
+Java/Main.jar
+Java/out

CSharp/CSharp.csproj

@@ -1,10 +1,10 @@
-<Project Sdk="Microsoft.NET.Sdk">
-
-  <PropertyGroup>
-    <OutputType>Exe</OutputType>
-    <TargetFramework>net7.0</TargetFramework>
-    <ImplicitUsings>enable</ImplicitUsings>
-    <Nullable>enable</Nullable>
-  </PropertyGroup>
-
-</Project>
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net7.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+</Project>

CSharp/Program.cs

@@ -23,7 +23,7 @@ CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 using static Neural.Logical;
 
 Thread.CurrentThread.CurrentCulture = CultureInfo.InvariantCulture;
-if (args[0] == "--logical")
+if (args.FirstOrDefault() == "--logical")
 {
     var trainingData = Enumerable.Range(0, 2)
         .SelectMany(x => Enumerable.Range(0, 2), (l, r) => (l, r))
@@ -66,7 +66,7 @@ CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
     };
     Console.WriteLine($"network: {networkVals.ToJson()}");
 }
-else if (args[0] == "--semeion")
+else if (args.FirstOrDefault() == "--semeion")
 {
     // --semeion <file> hiddens epochs lr
     const int inputCount = 16  * 16;
@@ -128,6 +128,9 @@ CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
         Console.WriteLine();
     }
 }
+else {
+  Console.WriteLine("Specify --logical or --semeion <file>");
+}
 
 namespace Neural
 {

FSharp/FSharp.fsproj

@@ -1,13 +1,13 @@
-<Project Sdk="Microsoft.NET.Sdk">
-
-  <PropertyGroup>
-    <OutputType>Exe</OutputType>
-    <TargetFramework>net7.0</TargetFramework>
-  </PropertyGroup>
-
-  <ItemGroup>
-    <Compile Include="Neural.fs" />
-    <Compile Include="Program.fs" />
-  </ItemGroup>
-
-</Project>
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net7.0</TargetFramework>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <Compile Include="Neural.fs" />
+    <Compile Include="Program.fs" />
+  </ItemGroup>
+
+</Project>

FSharp/Program.fs

@@ -1,74 +1,74 @@
-(*
-Licensed under the MIT License given below.
-Copyright 2023 Daniel Lidstrom
-Permission is hereby granted, free of charge, to any person obtaining a copy of
-this software and associated documentation files (the “Software”), to deal in
-the Software without restriction, including without limitation the rights to
-use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
-the Software, and to permit persons to whom the Software is furnished to do so,
-subject to the following conditions:
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
-FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
-COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
-IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
-CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
-*)
-
-open Neural
-
-let randFloat =
-  let P = 2147483647u
-  let A = 16807u;
-  let mutable current = 1u
-  let inner() =
-    current <- current * A % P;
-    let result = float current / float P
-    result
-  inner
-let xor a b = a ^^^ b
-let orf (a: int) b = a ||| b
-let andf (a: int) b = a &&& b
-let xnor a b = 1 - xor a b
-let nand a b = 1 - andf a b
-let nor a b = 1 - orf a b
-
-let trainingData = [|
-  for i = 0 to 1 do
-    for j = 0 to 1 do
-      [| float i; j |],
-      [| xor i j |> float; xnor i j; orf i j; andf i j; nor i j; nand i j |]
-|]
-
-let trainer = Trainer(2, 2, 6, randFloat)
-let lr = 1.0
-let ITERS = 4000
-for e = 0 to ITERS - 1 do
-  let input, y = trainingData[e % trainingData.Length]
-  trainer.Train(input, y, lr)
-
-let network = trainer.Network
-printfn "Result after %d iterations" ITERS
-printfn "        XOR   XNOR    OR   AND   NOR   NAND"
-for i, _ in trainingData do
-  let pred = network.Predict(i)
-  printfn
-    "%.0f,%.0f = %.3f  %.3f %.3f %.3f %.3f  %.3f"
-    i[0]
-    i[1]
-    pred[0]
-    pred[1]
-    pred[2]
-    pred[3]
-    pred[4]
-    pred[5]
-
-let networkVals = {|
-  WeightsHidden = network.WeightsHidden
-  BiasesHidden = network.BiasesHidden
-  WeightsOutput = network.WeightsOutput
-  BiasesOutput = network.BiasesOutput
-|}
-printfn $"network: %A{networkVals}"
+(*
+Licensed under the MIT License given below.
+Copyright 2023 Daniel Lidstrom
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the “Software”), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+the Software, and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+*)
+
+open Neural
+
+let randFloat =
+  let P = 2147483647u
+  let A = 16807u;
+  let mutable current = 1u
+  let inner() =
+    current <- current * A % P;
+    let result = float current / float P
+    result
+  inner
+let xor a b = a ^^^ b
+let orf (a: int) b = a ||| b
+let andf (a: int) b = a &&& b
+let xnor a b = 1 - xor a b
+let nand a b = 1 - andf a b
+let nor a b = 1 - orf a b
+
+let trainingData = [|
+  for i = 0 to 1 do
+    for j = 0 to 1 do
+      [| float i; j |],
+      [| xor i j |> float; xnor i j; orf i j; andf i j; nor i j; nand i j |]
+|]
+
+let trainer = Trainer(2, 2, 6, randFloat)
+let lr = 1.0
+let ITERS = 4000
+for e = 0 to ITERS - 1 do
+  let input, y = trainingData[e % trainingData.Length]
+  trainer.Train(input, y, lr)
+
+let network = trainer.Network
+printfn "Result after %d iterations" ITERS
+printfn "        XOR   XNOR    OR   AND   NOR   NAND"
+for i, _ in trainingData do
+  let pred = network.Predict(i)
+  printfn
+    "%.0f,%.0f = %.3f  %.3f %.3f %.3f %.3f  %.3f"
+    i[0]
+    i[1]
+    pred[0]
+    pred[1]
+    pred[2]
+    pred[3]
+    pred[4]
+    pred[5]
+
+let networkVals = {|
+  WeightsHidden = network.WeightsHidden
+  BiasesHidden = network.BiasesHidden
+  WeightsOutput = network.WeightsOutput
+  BiasesOutput = network.BiasesOutput
+|}
+printfn $"network: %A{networkVals}"

Java/Makefile

@@ -0,0 +1,63 @@
+##
+# source directory
+##
+SRC_DIR := src
+
+##
+# output directory
+##
+OUT_DIR := out
+
+##
+# sources
+##
+SRCS := $(wildcard $(SRC_DIR)/*.java)
+
+##
+# classes
+##
+CLS := $(SRCS:$(SRC_DIR)/%.java=$(OUT_DIR)/%.class)
+
+##
+# compiler and compiler flags
+##
+JC := javac
+JCFLAGS := -d $(OUT_DIR)/ -cp $(SRC_DIR)/
+J := java
+
+##
+# suffixes
+##
+.SUFFIXES: .java
+
+##
+# targets that do not produce output files
+##
+.PHONY: all clean
+
+##
+# default target(s)
+##
+all: run
+
+$(CLS): $(OUT_DIR)/%.class: $(SRC_DIR)/%.java
+	$(JC) $(JCFLAGS) $<
+
+##
+# jar
+##
+jar: $(CLS)
+	jar cfe Main.jar Main -C out .
+
+##
+# run
+##
+run: jar
+	$(J) -jar Main.jar
+
+##
+# clean up any output files
+##
+clean:
+	rm -f $(OUT_DIR)/*.class
+	rm -f Main.jar

Java/src/CustomRandom.java

@@ -0,0 +1,32 @@
+/*
+Licensed under the MIT License given below.
+Copyright 2024 Daniel Lidstrom
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the “Software”), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+the Software, and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+*/
+
+import java.util.function.Supplier;
+
+public class CustomRandom implements Supplier<Double> {
+    final int P = 2147483647;
+    final int A = 16807;
+    int current = 1;
+
+    public Double get() {
+        current = Integer.remainderUnsigned(current * A, P);
+        double result = (double)current / P;
+        return result;
+    }
+}