Merge pull request #54 from sk-ai-net/feature/mnist-0.0.5

Feature/mnist 0.0.5

Author: michalharakal

build.gradle.kts

@@ -10,7 +10,7 @@ plugins {
 
 allprojects {
     group = "sk.ai.net"
-    version = "0.0.5"
+    version = "0.0.7"
 }
 
 moduleGraphConfig {

core/src/commonMain/kotlin/sk/ai/net/Distribution.kt

@@ -0,0 +1,32 @@
+package sk.ai.net
+
+
+interface Distribution<T> {
+
+    /**
+     * Seed for the random number generator.
+     */
+    val seed: Long
+
+    /**
+     * Retrieves a new sample from the distribution.
+     *
+     * @return A T value.
+     */
+    fun sample(): T
+
+
+    /**
+     * Retrieves the distribution's mean.
+     *
+     * @return The mean value.
+     */
+    val mean: T
+
+    /**
+     * Retrieves the distribution's standard deviation.
+     *
+     * @return The standard deviation.
+     */
+    val deviation: T
+}

core/src/commonMain/kotlin/sk/ai/net/Shape.kt

@@ -1,5 +1,6 @@
 package sk.ai.net
 
+import sk.ai.net.impl.assert
 import sk.ai.net.impl.zipFold
 
 class Shape(vararg dimensions: Int) {
@@ -11,6 +12,22 @@ class Shape(vararg dimensions: Int) {
     val rank: Int
         get() = dimensions.size
 
+    internal fun index(indices: IntArray): Int {
+        assert(
+            { indices.size == dimensions.size },
+            { "`indices.size` must be ${dimensions.size}: ${indices.size}" })
+        return dimensions.zip(indices).fold(0) { a, x ->
+            assert(
+                { 0 <= x.second && x.second < x.first },
+                { "Illegal index: indices = ${indices}, shape = $dimensions" })
+            a * x.first + x.second
+        }
+    }
+
+    operator fun get(vararg indices: Int): Int {
+        return dimensions[index(indices)]
+    }
+
     override fun equals(other: Any?): Boolean {
         if (other !is Shape) {
             return false

core/src/commonMain/kotlin/sk/ai/net/Tensor.kt

@@ -50,7 +50,7 @@ interface Tensor {
 
     fun relu(): Tensor
 
-    fun softmax(i: Int): Tensor
+    fun softmax(dim: Int): Tensor
 
     fun softmax(): Tensor
 
@@ -63,30 +63,35 @@ interface Tensor {
     fun cos(): Tensor
 
     fun tan(): Tensor
-    
+
     fun asin(): Tensor
 
     fun acos(): Tensor
-    
+
     fun atan(): Tensor
 
-    fun sinh():Tensor
+    fun sinh(): Tensor
 
-    fun cosh():Tensor
+    fun cosh(): Tensor
 
-    fun tanh():Tensor
+    fun tanh(): Tensor
 
-    fun exp():Tensor
+    fun exp(): Tensor
 
-    fun log():Tensor
+    fun log(): Tensor
 
-    fun sqrt():Tensor
+    fun sqrt(): Tensor
 
-    fun cbrt():Tensor
+    fun cbrt(): Tensor
 
-    fun sigmoid():Tensor
+    fun sigmoid(): Tensor
 
-    fun ln():Tensor
+    fun ln(): Tensor
+
+    fun flatten(startDim: Int = 1, endDim: Int = -1): Tensor
+}
 
+fun Shape.toRanges(): Array<IntRange> {
+    return dimensions.map { 0 until it -1 }.toTypedArray()
 }
 

core/src/commonMain/kotlin/sk/ai/net/TensorFactory.kt

@@ -1,5 +1,24 @@
 package sk.ai.net
 
+import sk.ai.net.impl.BuiltInDoubleDataDescriptor
+import sk.ai.net.impl.DoublesTensor
+import kotlin.random.Random
+
 interface TensorFactory {
     fun createTensor(shape: Shape, dataDescriptor: DataDescriptor, elements: DoubleArray): Tensor
-}
+}
+
+interface DataDescriptorFactory {
+    fun createDataDescriptor(): DataDescriptor
+}
+
+
+fun rand(shape: Shape, dataDescriptor: DataDescriptor = BuiltInDoubleDataDescriptor()): Tensor {
+    val random: Random = Random.Default
+
+    return DoublesTensor(shape, DoubleArray(shape.volume) { random.nextFloat().toDouble() })
+}
+
+fun zeros(shape: Shape, dataDescriptor: DataDescriptor = BuiltInDoubleDataDescriptor()): Tensor {
+    return DoublesTensor(shape, DoubleArray(shape.volume))
+}

core/src/commonMain/kotlin/sk/ai/net/core/Slice.kt

@@ -0,0 +1,15 @@
+package sk.ai.net.core
+
+import sk.ai.net.Tensor
+
+data class Slice(val tensor: Tensor, val dimensionIndex: Int, val startIndex: Long, val endIndex: Long) {
+    fun toRange() = startIndex..endIndex
+}
+
+fun Slice.start() = startIndex
+
+fun Slice.end() = endIndex
+
+fun Slice.all() = startIndex..tensor.shape.dimensions[dimensionIndex]
+
+fun Slice.range(): LongRange = startIndex..endIndex

…ain/kotlin/sk/ai/net/impl/TypedTensor.kt …ain/kotlin/sk/ai/net/core/TypedTensor.ktcore/src/commonMain/kotlin/sk/ai/net/impl/TypedTensor.kt renamed to core/src/commonMain/kotlin/sk/ai/net/core/TypedTensor.kt core/src/commonMain/kotlin/sk/ai/net/impl/TypedTensor.kt renamed to core/src/commonMain/kotlin/sk/ai/net/core/TypedTensor.kt

@@ -1,4 +1,4 @@
-package sk.ai.net.impl
+package sk.ai.net.core
 
 import sk.ai.net.Tensor
 
@@ -11,7 +11,9 @@ interface TypedTensor<T> : Tensor {
     operator fun get(vararg indices: Int): T
 
     operator fun get(vararg ranges: IntRange): TypedTensor<T>
-}
 
+    operator fun get(vararg ranges: Slice): Tensor
 
+    val allElements: List<T>
 
+}