Fixing API to use in and ReadOnly as needed (#103368)

* fixing API to use in and ReadOnly as needed

* test fixes

* API updates from Tanner's suggestion

* test fixes

* removed InPlace, changes from PR discussions

Author: michaelgsharp

src/libraries/System.Numerics.Tensors/ref/System.Numerics.Tensors.netcore.cs

@@ -225,4 +225,7 @@
   <data name="Argument_IncompatibleDimensions" xml:space="preserve">
     <value>Incompatible dimensions for provided tensors. left.Lengths[1] == {0} while right.Lengths[1] == {1}.</value>
   </data>
-</root>
+  <data name="ThrowArgument_StackShapesNotSame" xml:space="preserve">
+    <value>All tensors must have the same shape.</value>
+  </data>
+</root>

src/libraries/System.Numerics.Tensors/src/Resources/Strings.resx

@@ -23,7 +23,6 @@
     <Compile Include="System\Numerics\Tensors\netcore\ITensor.cs" />
     <Compile Include="System\Numerics\Tensors\netcore\IReadOnlyTensor.cs" />
     <Compile Include="System\Numerics\Tensors\netcore\TensorSpanDebugView.cs" />
-    <Compile Include="System\Numerics\Tensors\netcore\TensorSpanExtensions.cs" />
     <Compile Include="System\Numerics\Tensors\netcore\ReadOnlyTensorSpan.cs" />
     <Compile Include="System\Numerics\Tensors\netcore\TensorSpanHelpers.cs" />
     <Compile Include="System\Numerics\Tensors\netcore\TensorSpanHelpers.T.cs" />

src/libraries/System.Numerics.Tensors/src/System.Numerics.Tensors.csproj

@@ -775,7 +775,14 @@ public void FlattenTo(scoped Span<T> destination)
             nint copiedValues = 0;
             while (copiedValues < _flattenedLength)
             {
-                TensorSpanHelpers.Memmove(destination.Slice(checked((int)copiedValues)), ref Unsafe.Add(ref _reference, TensorSpanHelpers.ComputeLinearIndex(curIndexes, Strides, Lengths)), Lengths[Rank - 1]);
+                if (Strides[Rank - 1] == 0)
+                {
+                    destination.Slice(checked((int)copiedValues), (int)Lengths[Rank - 1]).Fill(Unsafe.Add(ref _reference, TensorSpanHelpers.ComputeLinearIndex(curIndexes, Strides, Lengths)));
+                }
+                else
+                {
+                    TensorSpanHelpers.Memmove(destination.Slice(checked((int)copiedValues)), ref Unsafe.Add(ref _reference, TensorSpanHelpers.ComputeLinearIndex(curIndexes, Strides, Lengths)), Lengths[Rank - 1]);
+                }
                 TensorSpanHelpers.AdjustIndexes(Rank - 2, 1, curIndexes, _lengths);
                 copiedValues += Lengths[Rank - 1];
             }

src/libraries/System.Numerics.Tensors/src/System/Numerics/Tensors/netcore/ReadOnlyTensorSpan.cs

@@ -3,6 +3,7 @@
 
 using System.Collections.Generic;
 using System.Linq;
+using System.Runtime.InteropServices;
 using Microsoft.VisualBasic;
 
 #pragma warning disable CS8601 // Possible null reference assignment.
@@ -19,7 +20,6 @@ public static partial class Tensor
         /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
         /// <param name="pinned">A <see cref="bool"/> whether the underlying data should be pinned or not.</param>
         public static Tensor<T> Create<T>(scoped ReadOnlySpan<nint> lengths, bool pinned = false)
-            where T : IEquatable<T>
         {
             nint linearLength = TensorSpanHelpers.CalculateTotalLength(lengths);
             T[] values = pinned ? GC.AllocateArray<T>((int)linearLength, pinned) : (new T[linearLength]);
@@ -33,7 +33,6 @@ public static Tensor<T> Create<T>(scoped ReadOnlySpan<nint> lengths, bool pinned
         /// <param name="strides">A <see cref="ReadOnlySpan{T}"/> indicating the strides of each dimension.</param>
         /// <param name="pinned">A <see cref="bool"/> whether the underlying data should be pinned or not.</param>
         public static Tensor<T> Create<T>(scoped ReadOnlySpan<nint> lengths, scoped ReadOnlySpan<nint> strides, bool pinned = false)
-            where T : IEquatable<T>
         {
             nint linearLength = TensorSpanHelpers.CalculateTotalLength(lengths);
             T[] values = pinned ? GC.AllocateArray<T>((int)linearLength, pinned) : (new T[linearLength]);
@@ -48,7 +47,7 @@ public static Tensor<T> Create<T>(scoped ReadOnlySpan<nint> lengths, scoped Read
         /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
         /// <exception cref="ArgumentOutOfRangeException"></exception>
         public static Tensor<T> Create<T>(T[] values, scoped ReadOnlySpan<nint> lengths)
-            where T : IEquatable<T> => Create(values, lengths, []);
+            => Create(values, lengths, []);
 
         /// <summary>
         /// Creates a <see cref="Tensor{T}"/> from the provided <paramref name="values"/>. If the product of the
@@ -60,51 +59,40 @@ public static Tensor<T> Create<T>(T[] values, scoped ReadOnlySpan<nint> lengths)
         /// <param name="isPinned">A <see cref="bool"/> indicating whether the <paramref name="values"/> were pinned or not.</param>
         /// <exception cref="ArgumentOutOfRangeException"></exception>
         public static Tensor<T> Create<T>(T[] values, scoped ReadOnlySpan<nint> lengths, scoped ReadOnlySpan<nint> strides, bool isPinned = false)
-            where T : IEquatable<T>
         {
             return new Tensor<T>(values, lengths, strides, isPinned);
         }
 
         /// <summary>
-        /// Creates a <see cref="Tensor{T}"/> and does not initialize it. If <paramref name="pinned"/> is true, the memory will be pinned.
-        /// </summary>
-        /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
-        /// <param name="pinned">A <see cref="bool"/> whether the underlying data should be pinned or not.</param>
-        public static Tensor<T> CreateUninitialized<T>(scoped ReadOnlySpan<nint> lengths, bool pinned = false)
-            where T : IEquatable<T> => CreateUninitialized<T>(lengths, [], pinned);
-
-
-        /// <summary>
-        /// Creates a <see cref="Tensor{T}"/> and does not initialize it. If <paramref name="pinned"/> is true, the memory will be pinned.
+        /// Creates a <see cref="Tensor{T}"/> and initializes it with the data from <paramref name="data"/>.
         /// </summary>
-        /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
-        /// <param name="strides">A <see cref="ReadOnlySpan{T}"/> indicating the strides of each dimension.</param>
-        /// <param name="pinned">A <see cref="bool"/> whether the underlying data should be pinned or not.</param>
-        public static Tensor<T> CreateUninitialized<T>(scoped ReadOnlySpan<nint> lengths, scoped ReadOnlySpan<nint> strides, bool pinned = false )
-            where T : IEquatable<T>
+        /// <param name="data">A <see cref="IEnumerable{T}"/> with the data to use for the initialization.</param>
+        /// <param name="lengths"></param>
+        public static Tensor<T> Create<T>(IEnumerable<T> data, scoped ReadOnlySpan<nint> lengths)
         {
-            nint linearLength = TensorSpanHelpers.CalculateTotalLength(lengths);
-            T[] values = GC.AllocateUninitializedArray<T>((int)linearLength, pinned);
-            return new Tensor<T>(values, lengths, strides, pinned);
+            T[] values = data.ToArray();
+            return new Tensor<T>(values, lengths.IsEmpty ? [values.Length] : lengths, false);
         }
 
         /// <summary>
         /// Creates a <see cref="Tensor{T}"/> and initializes it with the data from <paramref name="data"/>.
         /// </summary>
         /// <param name="data">A <see cref="IEnumerable{T}"/> with the data to use for the initialization.</param>
-        public static Tensor<T> CreateFromEnumerable<T>(IEnumerable<T> data)
-            where T : IEquatable<T>, IEqualityOperators<T, T, bool>
+        /// <param name="lengths"></param>
+        /// <param name="strides"></param>
+        /// <param name="isPinned"></param>
+        public static Tensor<T> Create<T>(IEnumerable<T> data, scoped ReadOnlySpan<nint> lengths, scoped ReadOnlySpan<nint> strides, bool isPinned = false)
         {
             T[] values = data.ToArray();
-            return new Tensor<T>(values, [values.Length], false);
+            return new Tensor<T>(values, lengths.IsEmpty ? [values.Length] : lengths, strides, isPinned);
         }
 
         /// <summary>
         /// Creates a <see cref="Tensor{T}"/> and initializes it with random data uniformly distributed.
         /// </summary>
         /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
         public static Tensor<T> CreateAndFillUniformDistribution<T>(params scoped ReadOnlySpan<nint> lengths)
-            where T : IEquatable<T>, IEqualityOperators<T, T, bool>, IFloatingPoint<T>
+            where T : IFloatingPoint<T>
         {
             nint linearLength = TensorSpanHelpers.CalculateTotalLength(lengths);
             T[] values = new T[linearLength];
@@ -121,16 +109,16 @@ public static Tensor<T> CreateAndFillUniformDistribution<T>(params scoped ReadOn
         /// </summary>
         /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
         public static Tensor<T> CreateAndFillGaussianNormalDistribution<T>(params scoped ReadOnlySpan<nint> lengths)
-            where T : IEquatable<T>, IEqualityOperators<T, T, bool>, IFloatingPoint<T>
+            where T : IFloatingPoint<T>
         {
             nint linearLength = TensorSpanHelpers.CalculateTotalLength(lengths);
             T[] values = new T[linearLength];
-            GaussianDistribution(ref values, linearLength);
+            GaussianDistribution<T>(values, linearLength);
             return new Tensor<T>(values, lengths, false);
         }
 
-        private static void GaussianDistribution<T>(ref T[] values, nint linearLength)
-             where T : IEquatable<T>, IEqualityOperators<T, T, bool>, IFloatingPoint<T>
+        private static void GaussianDistribution<T>(in Span<T> values, nint linearLength)
+             where T : IFloatingPoint<T>
         {
             Random rand = Random.Shared;
             for (int i = 0; i < linearLength; i++)
@@ -141,5 +129,45 @@ private static void GaussianDistribution<T>(ref T[] values, nint linearLength)
             }
         }
         #endregion
+
+        /// <summary>
+        /// Creates a <see cref="Tensor{T}"/> and does not initialize it. If <paramref name="pinned"/> is true, the memory will be pinned.
+        /// </summary>
+        /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
+        /// <param name="pinned">A <see cref="bool"/> whether the underlying data should be pinned or not.</param>
+        public static Tensor<T> CreateUninitialized<T>(scoped ReadOnlySpan<nint> lengths, bool pinned = false)
+            => CreateUninitialized<T>(lengths, [], pinned);
+
+        /// <summary>
+        /// Creates a <see cref="Tensor{T}"/> and does not initialize it. If <paramref name="pinned"/> is true, the memory will be pinned.
+        /// </summary>
+        /// <param name="lengths">A <see cref="ReadOnlySpan{T}"/> indicating the lengths of each dimension.</param>
+        /// <param name="strides">A <see cref="ReadOnlySpan{T}"/> indicating the strides of each dimension.</param>
+        /// <param name="pinned">A <see cref="bool"/> whether the underlying data should be pinned or not.</param>
+        public static Tensor<T> CreateUninitialized<T>(scoped ReadOnlySpan<nint> lengths, scoped ReadOnlySpan<nint> strides, bool pinned = false)
+        {
+            nint linearLength = TensorSpanHelpers.CalculateTotalLength(lengths);
+            T[] values = GC.AllocateUninitializedArray<T>((int)linearLength, pinned);
+            return new Tensor<T>(values, lengths, strides, pinned);
+        }
+
+        public static ref readonly TensorSpan<T> FillGaussianNormalDistribution<T>(in TensorSpan<T> destination) where T : IFloatingPoint<T>
+        {
+            Span<T> span = MemoryMarshal.CreateSpan<T>(ref destination._reference, (int)destination._flattenedLength);
+
+            GaussianDistribution<T>(span, destination._flattenedLength);
+
+            return ref destination;
+        }
+
+        public static ref readonly TensorSpan<T> FillUniformDistribution<T>(in TensorSpan<T> destination) where T : IFloatingPoint<T>
+        {
+            Span<T> span = MemoryMarshal.CreateSpan<T>(ref destination._reference, (int)destination._flattenedLength);
+
+            for (int i = 0; i < span.Length; i++)
+                span[i] = T.CreateChecked(Random.Shared.NextDouble());
+
+            return ref destination;
+        }
     }
 }