Implement low level XXXArray classes holding custom types. Uses with TensordataFactory.

Related-To: #97, #95

Author: michalharakal

gradle.properties

@@ -1,5 +1,5 @@
 GROUP=sk.ainet.core
-VERSION_NAME=0.0.1.1
+VERSION_NAME=0.0.1.2
 
 POM_DESCRIPTION=SKaiNET
 

skainet-lang/skainet-lang-api/src/commonMain/kotlin/sk/ainet/lang/tensor/Shape.kt

@@ -8,7 +8,7 @@ public data class Shape(val dimensions: IntArray) {
     }
 
     val volume: Int
-        get() = dimensions.fold(1) { a, x -> a * x }
+        get() = dimensions.fold(if (dimensions.isNotEmpty()) 1 else 0) { a, x -> a * x }
 
     val rank: Int
         get() = dimensions.size

skainet-lang/skainet-lang-api/src/commonMain/kotlin/sk/ainet/lang/tensor/data/TensorData.kt

@@ -7,14 +7,14 @@ import sk.ainet.lang.types.DType
  * A fundamental data structure interface that provides indexed access to elements.
  * 
  * This interface serves as the base for all data structures that need to provide
- * element access through multi-dimensional indexing. It is designed to support
+ * element access through multidimensional indexing. It is designed to support
  * efficient access patterns commonly used in neural network computations.
  * 
  * @param T the type of elements that can be accessed
  */
 public interface ItemsAccessor<T> {
     /**
-     * Retrieves an element at the specified multi-dimensional indices.
+     * Retrieves an element at the specified multidimensional indices.
      * 
      * This operator function allows accessing elements using bracket notation
      * with variable number of indices, supporting tensors of any dimensionality.
@@ -24,6 +24,12 @@ public interface ItemsAccessor<T> {
      * @throws IndexOutOfBoundsException if any index is out of bounds
      */
     public operator fun get(vararg indices: Int): T
+
+
+    /**
+     * Setter
+     */
+    public operator fun set(vararg indices: Int, value: T)
 }
 
 /**
@@ -61,4 +67,6 @@ public interface TensorData<T : DType, V> : ItemsAccessor<V> {
      * @return the Shape object describing this tensor's dimensional structure
      */
     public val shape: Shape
+
+    public companion object
 }

skainet-lang/skainet-lang-api/src/commonMain/kotlin/sk/ainet/lang/tensor/data/pprint.kt

@@ -0,0 +1,63 @@
+package sk.ainet.lang.tensor.data
+
+import sk.ainet.lang.types.DType
+
+
+public fun <T: DType,V> TensorData<T,V>.pprint(): String {
+    return when (this.shape.rank) {
+        0 -> {
+            // Scalar - single value
+            this.toString()
+        }
+        1 -> {
+            // Vector - horizontal representation with parentheses
+            val sb = StringBuilder()
+            sb.append("[ ")
+            for (i in 0 until this.shape[0]) {
+                if (i > 0) sb.append(", ")
+                sb.append(this[i].toString())
+            }
+            sb.append(" ]")
+            sb.toString()
+        }
+        2 -> {
+            // Matrix - vertical representation with Unicode brackets
+            val sb = StringBuilder()
+            val rows = this.shape[0]
+            val cols = this.shape[1]
+
+            for (i in 0 until rows) {
+                // Left bracket
+                val leftBracket = when {
+                    rows == 1 -> "( "
+                    i == 0 -> "⎛ "
+                    i == rows - 1 -> "⎝ "
+                    else -> "⎜ "
+                }
+                sb.append(leftBracket)
+
+                // Matrix elements
+                for (j in 0 until cols) {
+                    if (j > 0) sb.append(", ")
+                    sb.append(this[i, j].toString())
+                }
+
+                // Right bracket
+                val rightBracket = when {
+                    rows == 1 -> " )"
+                    i == 0 -> " ⎞"
+                    i == rows - 1 -> " ⎠"
+                    else -> " ⎟"
+                }
+                sb.append(rightBracket)
+
+                if (i < rows - 1) sb.append("\n")
+            }
+            sb.toString()
+        }
+        else -> {
+            // Higher rank tensors - use toString
+            this.toString()
+        }
+    }
+}

skainet-lang/skainet-lang-memory/Module.md

@@ -0,0 +1,15 @@
+# skainet-lang-memory
+
+## Overview
+
+## memory layout
+
+row major **BCWH**
+
+$$
+\text{stride}[i] = \prod_{j=i+1}^{n-1} \text{dims}[j]
+$$
+
+## Classes
+
+DenseXXXTensorDataMemory implement dense linear memoty holding tensors data.