build.gradle.kts

@@ -10,7 +10,7 @@ allprojects {
     }
 
     group = "space.kscience"
-    version = "0.3.0-dev-17"
+    version = "0.3.0-dev-18"
 }
 
 subprojects {

kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt

@@ -164,8 +164,6 @@ public open class FunctionalExpressionExtendedField<T, out A : ExtendedField<T>>
 
     override fun binaryOperationFunction(operation: String): (left: Expression<T>, right: Expression<T>) -> Expression<T> =
         super<FunctionalExpressionField>.binaryOperationFunction(operation)
-
-    override fun bindSymbol(value: String): Expression<T> = super<FunctionalExpressionField>.bindSymbol(value)
 }
 
 public inline fun <T, A : Group<T>> A.expressionInGroup(

kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/SimpleAutoDiff.kt

@@ -272,7 +272,7 @@ public fun <T : Any, F : ExtendedField<T>> SimpleAutoDiffField<T, F>.sqrt(x: Aut
 public fun <T : Any, F : ExtendedField<T>> SimpleAutoDiffField<T, F>.pow(
     x: AutoDiffValue<T>,
     y: Double,
-): AutoDiffValue<T> = derive(const { x.value.pow(y)}) { z ->
+): AutoDiffValue<T> = derive(const { x.value.pow(y) }) { z ->
     x.d += z.d * y * x.value.pow(y - 1)
 }
 
@@ -343,10 +343,7 @@ public fun <T : Any, F : ExtendedField<T>> SimpleAutoDiffField<T, F>.atanh(x: Au
 public class SimpleAutoDiffExtendedField<T : Any, F : ExtendedField<T>>(
     context: F,
     bindings: Map<Symbol, T>,
-) : ExtendedField<AutoDiffValue<T>>, ScaleOperations<AutoDiffValue<T>>,
-    SimpleAutoDiffField<T, F>(context, bindings) {
-
-    override fun bindSymbol(value: String): AutoDiffValue<T> = super<SimpleAutoDiffField>.bindSymbol(value)
+) : ExtendedField<AutoDiffValue<T>>, ScaleOperations<AutoDiffValue<T>>, SimpleAutoDiffField<T, F>(context, bindings) {
 
     override fun number(value: Number): AutoDiffValue<T> = const { number(value) }
 

kmath-tensorflow/src/main/kotlin/space/kscience/kmath/tensorflow/TensorFlowAlgebra.kt

@@ -241,6 +241,16 @@ public abstract class TensorFlowAlgebra<T, TT : TNumber, A : Ring<T>> internal c
         ops.math.argMax(asTensorFlow().output, ops.constant(dim), TInt32::class.java).output()
     ).actualTensor
 
+//    private val symbolCache = HashMap<String, TensorFlowOutput<T, TT>>()
+//
+//    override fun bindSymbolOrNull(value: String): TensorFlowOutput<T, TT>? {
+//        return symbolCache.getOrPut(value){ops.var}
+//    }
+//
+//    public fun StructureND<T>.grad(
+//
+//    )= operate { ops.gradients() }
+
     @OptIn(UnstableKMathAPI::class)
     override fun export(arg: StructureND<T>): StructureND<T> =
         if (arg is TensorFlowOutput<T, *>) arg.actualTensor else arg

kmath-tensorflow/src/main/kotlin/space/kscience/kmath/tensorflow/tfOperations.kt

@@ -20,4 +20,4 @@ public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.sin(
 
 public fun <T, TT : TNumber, A> TensorFlowAlgebra<T, TT, A>.cos(
     arg: StructureND<T>,
-): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.cos(it) }
+): TensorFlowOutput<T, TT> where A : TrigonometricOperations<T>, A : Ring<T> = arg.operate { ops.math.cos(it) }