diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorCasts.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorCasts.kt
index 921bcf97e..4e43ed1e1 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorCasts.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/tensorCasts.kt
@@ -9,17 +9,17 @@ import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.internal.tensor
 
 /**
- * Casts [Tensor<Double>] to [DoubleTensor]
+ * Casts [Tensor] iof [Double] to [DoubleTensor]
  */
 public fun Tensor<Double>.toDoubleTensor(): DoubleTensor = this.tensor
 
 /**
- * Casts [Tensor<Int>] to [IntTensor]
+ * Casts [Tensor] iof [Int] to [IntTensor]
  */
 public fun Tensor<Int>.toIntTensor(): IntTensor = this.tensor
 
 /**
- * @return [DoubleArray] of tensor elements
+ * Returns [DoubleArray] of tensor elements
  */
 public fun DoubleTensor.toDoubleArray(): DoubleArray {
     return DoubleArray(numElements) { i ->
@@ -28,42 +28,10 @@ public fun DoubleTensor.toDoubleArray(): DoubleArray {
 }
 
 /**
- * @return [IntArray] of tensor elements
+ * Returns [IntArray] of tensor elements
  */
 public fun IntTensor.toIntArray(): IntArray {
     return IntArray(numElements) { i ->
         mutableBuffer[bufferStart + i]
     }
 }
-
-/**
- * Casts [Array<DoubleArray>] to [DoubleTensor]
- */
-public fun Array<DoubleArray>.toDoubleTensor(): DoubleTensor {
-    val n = size
-    check(n > 0) { "An empty array cannot be casted to tensor" }
-    val m = first().size
-    check(m > 0) { "Inner arrays must have at least 1 argument" }
-    check(all { size == m }) { "Inner arrays must be the same size" }
-
-    val shape = intArrayOf(n, m)
-    val buffer = this.flatMap { arr -> arr.map { it } }.toDoubleArray()
-
-    return DoubleTensor(shape, buffer, 0)
-}
-
-/**
- * Casts [Array<IntArray>] to [IntTensor]
- */
-public fun Array<IntArray>.toIntTensor(): IntTensor {
-    val n = size
-    check(n > 0) { "An empty array cannot be casted to tensor" }
-    val m = first().size
-    check(m > 0) { "Inner arrays must have at least 1 argument" }
-    check(all { size == m }) { "Inner arrays must be the same size" }
-
-    val shape = intArrayOf(n, m)
-    val buffer = this.flatMap { arr -> arr.map { it } }.toIntArray()
-
-    return IntTensor(shape, buffer, 0)
-}