[Draft] Github CI, DSL Builder, Seperate logging factory

.github/workflows/gradle.yml

@@ -0,0 +1,60 @@
+name: Build
+
+on: [ push, pull_request ]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Set up JDK(16)
+        uses: actions/setup-java@v1
+        with:
+          java-version: 16
+
+      - name: CheckOut
+        uses: actions/checkout@v2
+
+      - name: Gradle wrapper validation
+        uses: gradle/wrapper-validation-action@v1
+
+
+      - name: Gradle cache
+        uses: actions/cache@v2
+        with:
+          path: |
+            ~/.gradle/caches
+            ~/.gradle/wrapper
+          key: ${{ runner.os }}-gradle-${{ hashFiles('**/*.gradle*') }}
+          restore-keys: |
+            ${{ runner.os }}-gradle-
+
+
+      - name: Gradle Build
+        #        Test takes too long on ci with github, maybe manually trigger with teamcity?
+        run: ./gradlew build -x test
+
+
+      - name: 'Upload API artifacts'
+        uses: actions/upload-artifact@v2
+        with:
+          name: 'API Jars'
+          path: api/build/libs/*.jar
+
+      - name: 'Upload DataSet artifacts'
+        uses: actions/upload-artifact@v2
+        with:
+          name: 'DataSet Jars'
+          path: dataset/build/libs/*.jar
+
+      - name: 'Upload Example artifacts'
+        uses: actions/upload-artifact@v2
+        with:
+          name: 'Example Jars'
+          path: examples/build/libs/*.jar
+
+      - name: 'Upload ONNX artifacts'
+        uses: actions/upload-artifact@v2
+        with:
+          name: 'ONNX Jars'
+          path: onnx/build/libs/*.jar

api/build.gradle

@@ -1,13 +1,17 @@
 project.setDescription("This module contains the Kotlin API for building, training, and evaluating the Deep Learning models.")
 
 dependencies {
+    implementation 'org.jetbrains.kotlin:kotlin-stdlib-jdk8:1.6.10'
+
+
     api project(":dataset")
-    implementation 'org.jetbrains.kotlin:kotlin-stdlib-jdk8:1.6.0'
     api group: 'org.tensorflow', name: 'tensorflow', version: '1.15.0'
     api 'com.github.doyaaaaaken:kotlin-csv-jvm:0.7.3' // for csv parsing
-    api 'io.github.microutils:kotlin-logging:2.0.4' // for logging
     api 'io.jhdf:jhdf:0.5.7' // for hdf5 parsing
     api 'com.beust:klaxon:5.5'
+    api project(":logging:logging-api")
+
+
     testImplementation 'ch.qos.logback:logback-classic:1.2.7'
     testImplementation 'org.junit.jupiter:junit-jupiter-api:5.8.2'
     testImplementation 'org.junit.jupiter:junit-jupiter-engine:5.8.2'

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/Functional.kt

@@ -8,6 +8,7 @@ package org.jetbrains.kotlinx.dl.api.core
 import org.jetbrains.kotlinx.dl.api.core.layer.Layer
 import org.jetbrains.kotlinx.dl.api.core.layer.core.Input
 import org.jetbrains.kotlinx.dl.api.inference.keras.*
+import org.jetbrains.kotlinx.dl.logging.api.debug
 import org.tensorflow.Operand
 import java.io.File
 import java.io.FileNotFoundException

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/Sequential.kt

@@ -12,6 +12,7 @@ import org.jetbrains.kotlinx.dl.api.inference.keras.deserializeSequentialModel
 import org.jetbrains.kotlinx.dl.api.inference.keras.loadSequentialModelLayers
 import org.jetbrains.kotlinx.dl.api.inference.keras.loadSerializedModel
 import org.jetbrains.kotlinx.dl.api.inference.keras.serializeModel
+import org.jetbrains.kotlinx.dl.logging.api.debug
 import org.tensorflow.Operand
 import org.tensorflow.Shape
 import java.io.File

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/callback/EarlyStopping.kt

@@ -7,6 +7,8 @@ package org.jetbrains.kotlinx.dl.api.core.callback
 
 import org.jetbrains.kotlinx.dl.api.core.history.EpochTrainingEvent
 import org.jetbrains.kotlinx.dl.api.core.history.TrainingHistory
+import org.jetbrains.kotlinx.dl.logging.api.info
+import org.jetbrains.kotlinx.dl.logging.api.warn
 import java.util.function.BiFunction
 import kotlin.reflect.KProperty1
 

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/callback/TerminateOnNaN.kt

@@ -7,6 +7,7 @@ package org.jetbrains.kotlinx.dl.api.core.callback
 
 import org.jetbrains.kotlinx.dl.api.core.history.BatchTrainingEvent
 import org.jetbrains.kotlinx.dl.api.core.history.TrainingHistory
+import org.jetbrains.kotlinx.dl.logging.api.info
 
 /**
  * This callback is used to stop the training if loss is not a number (NaN or INFINITY).

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/callback/TimeStopping.kt

@@ -7,6 +7,7 @@ package org.jetbrains.kotlinx.dl.api.core.callback
 
 import org.jetbrains.kotlinx.dl.api.core.history.EpochTrainingEvent
 import org.jetbrains.kotlinx.dl.api.core.history.TrainingHistory
+import org.jetbrains.kotlinx.dl.logging.api.info
 
 /**
  * Callback for stopping training of a model when a specified amount of time has passed.

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/layer/merge/Dot.kt

@@ -80,7 +80,7 @@ public fun batchDot(scope: Scope?, x: Operand<Float>, y: Operand<Float>, axis: I
     val xDim = x.asOutput().shape().numDimensions()
     val yDim = y.asOutput().shape().numDimensions()
     val diff: Int
-    var x2: Operand<Float> = x;
+    var x2: Operand<Float> = x
     var y2: Operand<Float> = y
     if (xDim > yDim) {
         diff = xDim - yDim

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/core/summary/Helpers.kt

@@ -1,15 +1,16 @@
 package org.jetbrains.kotlinx.dl.api.core.summary
 
-import mu.KLogging
+
 import org.jetbrains.kotlinx.dl.api.core.TrainableModel
-import org.slf4j.Logger
+import org.jetbrains.kotlinx.dl.logging.api.GlobalLogFactory
+import org.jetbrains.kotlinx.dl.logging.api.Logger
 import java.io.PrintStream
 
 private data class SummaryRow(
     val layerName: String,
     val outputShape: String,
     val paramsCount: String,
-    val inboundLayers: List<String>
+    val inboundLayers: List<String>,
 )
 
 /**
@@ -33,7 +34,7 @@ public fun ModelSummary.format(
     columnSeparator: String = " ",
     lineSeparator: Char = '_',
     thickLineSeparator: Char = '=',
-    withConnectionsColumn: Boolean = layersSummaries.any { it.inboundLayers.size > 1 }
+    withConnectionsColumn: Boolean = layersSummaries.any { it.inboundLayers.size > 1 },
 ): List<String> {
     // Prepare string data for resulting table
     val table = layersSummaries.map { layer ->
@@ -121,7 +122,9 @@ public fun ModelSummary.print(out: PrintStream = System.out): Unit =
 public fun TrainableModel.printSummary(out: PrintStream = System.out): Unit =
     summary().print(out)
 
-private object ModelSummaryLogger : KLogging()
+private object ModelSummaryLogger {
+    val logger = GlobalLogFactory.newLogger(ModelSummaryLogger::class.java)
+}
 
 /**
  * Formats and log model summary to logger

api/src/main/kotlin/org/jetbrains/kotlinx/dl/api/extension/dsl/GraphTrainableModelDsl.kt

@@ -0,0 +1,71 @@
+package org.jetbrains.kotlinx.dl.api.extension.dsl
+
+import org.jetbrains.kotlinx.dl.api.core.Functional
+import org.jetbrains.kotlinx.dl.api.core.GraphTrainableModel
+import org.jetbrains.kotlinx.dl.api.core.Sequential
+import org.jetbrains.kotlinx.dl.api.core.layer.Layer
+
+@DslMarker
+@Retention(AnnotationRetention.SOURCE)
+internal annotation class BuilderDsl
+
+@DslMarker
+@Retention(AnnotationRetention.SOURCE)
+internal annotation class EntryDsl
+
+public class GraphTrainableModelDsl<T : GraphTrainableModel>(private val initializer: (Array<Layer>) -> T) {
+
+    private var handler: T.() -> Unit = {}
+    private var layerProvider: LayerBuilder.() -> Unit = {}
+    private var use: ((T) -> Unit)? = null
+
+    @BuilderDsl
+    public fun model(builder: T.() -> Unit) {
+        this.handler = builder
+    }
+
+    @BuilderDsl
+    public fun layers(builder: LayerBuilder.() -> Unit) {
+        this.layerProvider = builder
+    }
+
+    @BuilderDsl
+    public fun use(builder: T.() -> Unit) {
+        use = builder
+    }
+
+    public fun build(): T = initializer.invoke(LayerBuilder().apply(layerProvider).toArray()).apply(handler).apply {
+        use?.let { use(it) }
+    }
+}
+
+@JvmInline
+public value class LayerBuilder(private val list: MutableList<Layer> = mutableListOf()) {
+
+    public operator fun Layer.unaryPlus(): Layer {
+        list.add(this)
+        return this
+    }
+
+    public fun toArray(): Array<Layer> = list.toTypedArray()
+
+    public inline operator fun <T : Layer> T.invoke(builder: T.() -> Unit) {
+        this.apply(builder)
+    }
+}
+
+
+@EntryDsl
+public fun sequential(builder: GraphTrainableModelDsl<Sequential>.() -> Unit): Sequential {
+    return GraphTrainableModelDsl(Sequential.Companion::of).apply(builder).build()
+}
+
+@EntryDsl
+public fun functional(builder: GraphTrainableModelDsl<Functional>.() -> Unit): Functional {
+    return GraphTrainableModelDsl(Functional.Companion::of).apply(builder).build()
+}
+
+@EntryDsl
+public operator fun <T : GraphTrainableModel> ((Array<Layer>) -> T).invoke(builder: GraphTrainableModelDsl<T>.() -> Unit): T {
+    return GraphTrainableModelDsl(this).apply(builder).build()
+}