Merge pull request #1109 from AsakusaRinne/rnn-dev

feat: support training of RNN.

Author: SanftMonster

src/TensorFlowNET.Core/APIs/c_api.cs

@@ -16,6 +16,7 @@ limitations under the License.
 
 using System;
 using System.Runtime.InteropServices;
+using static Tensorflow.CppShapeInferenceResult.Types;
 
 namespace Tensorflow
 {
@@ -50,6 +51,19 @@ public static string StringPiece(IntPtr handle)
             return handle == IntPtr.Zero ? String.Empty : Marshal.PtrToStringAnsi(handle);
         }
 
+        public unsafe static byte[] ByteStringPiece(IntPtr handle)
+        {
+            byte* str_data = (byte*)handle.ToPointer();
+            List<byte> bytes = new List<byte>();
+            byte current = 255;
+            while (current != ((byte)'\0'))
+            {
+                current = *(str_data++);
+                bytes.Add(current);
+            }
+            return bytes.Take(bytes.Count - 1).ToArray();
+        }
+
         [UnmanagedFunctionPointer(CallingConvention.Winapi)]
         public delegate void Deallocator(IntPtr data, IntPtr size, ref DeallocatorArgs args);
 

src/TensorFlowNET.Core/APIs/tf.control_flow.cs

@@ -46,10 +46,10 @@ public Tensor while_loop(Func<Tensor, Tensor> cond,
             Tensor loop_vars,
             int parallel_iterations = 10)
         {
-            Func<Tensor[], Tensor> cond1 = x
+            Func<Tensors, Tensor> cond1 = x
                 => cond(x[0]);
 
-            Func<Tensor[], Tensor[]> body1 = x
+            Func<Tensors, Tensors> body1 = x
                 => new[] { body(x[0]) };
 
             var results = control_flow_ops.while_loop(cond1,
@@ -58,9 +58,9 @@ public Tensor while_loop(Func<Tensor, Tensor> cond,
             return results[0];
         }
 
-        public Tensor[] while_loop(Func<Tensor[], Tensor> cond,
-            Func<Tensor[], Tensor[]> body,
-            Tensor[] loop_vars,
+        public Tensor[] while_loop(Func<Tensors, Tensor> cond,
+            Func<Tensors, Tensors> body,
+            Tensors loop_vars,
             int parallel_iterations = 10,
             string name = null)
             => control_flow_ops.while_loop(cond, body, loop_vars,

src/TensorFlowNET.Core/APIs/tf.tensor.cs

@@ -71,15 +71,15 @@ public Tensor strided_slice<T>(Tensor input, T[] begin, T[] end, T[] strides = n
         public Tensor[] split(Tensor value, int num_split, Tensor axis, string name = null)
             => array_ops.split(
                 value: value,
-                num_split: num_split,
+                num_or_size_splits: num_split,
                 axis: axis,
                 name: name);
 
         public Tensor[] split(Tensor value, int num_split, int axis, string name = null)
             => array_ops.split(
                 value: value,
-                num_split: num_split,
-                axis: axis,
+                num_or_size_splits: num_split,
+                axis: ops.convert_to_tensor(axis),
                 name: name);
 
         public Tensor ensure_shape(Tensor x, Shape shape, string name = null)

src/TensorFlowNET.Core/Binding.Util.cs

@@ -503,7 +503,7 @@ public static TF_DataType GetDataType(this object data)
                 case Tensors tensors:
                     return tensors.dtype;
                 case IEnumerable<Tensor> tensors:
-                    return tensors.First().dtype;
+                    return tensors.Where(x => x is not null).First().dtype;
                 case RefVariable variable:
                     return variable.dtype;
                 case ResourceVariable variable:

src/TensorFlowNET.Core/Common/Extensions/LinqExtensions.cs

@@ -18,7 +18,12 @@ public static IEnumerable<T> SkipLast<T>(this IEnumerable<T> sequence, int count
             return sequence.Take(sequence.Count() - count);
         }
 #endif
-        public static Tensors ToTensors(this IEnumerable<Tensor> tensors)
+        public static Tensors ToTensors(this Tensor[] tensors)
+        {
+            return new Tensors(tensors);
+        }
+
+        public static Tensors ToTensors(this IList<Tensor> tensors)
         {
             return new Tensors(tensors);
         }

src/TensorFlowNET.Core/Common/Types/FakeTensorByTensorArray.cs

@@ -0,0 +1,20 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow.Common.Types
+{
+    /// <summary>
+    /// This is a temp solution, which should be removed after refactoring `Tensors`
+    /// </summary>
+    [Obsolete]
+    public class FakeTensorByTensorArray: Tensor
+    {
+        public TensorArray TensorArray { get; set; }
+
+        public FakeTensorByTensorArray(TensorArray array)
+        {
+            TensorArray = array;
+        }
+    }
+}

src/TensorFlowNET.Core/Common/Types/GeneralizedTensorShape.cs

@@ -5,136 +5,65 @@
 
 namespace Tensorflow.Common.Types
 {
-    public class GeneralizedTensorShape: IEnumerable<long?[]>, INestStructure<long?>, INestable<long?>
+    public class GeneralizedTensorShape: Nest<Shape>
     {
-        public TensorShapeConfig[] Shapes { get; set; }
-        /// <summary>
-        /// create a single-dim generalized Tensor shape.
-        /// </summary>
-        /// <param name="dim"></param>
-        public GeneralizedTensorShape(int dim, int size = 1)
+        public GeneralizedTensorShape(Shape value, string? name = null)
         {
-            var elem = new TensorShapeConfig() { Items = new long?[] { dim } };
-            Shapes = Enumerable.Repeat(elem, size).ToArray();
-            //Shapes = new TensorShapeConfig[size];
-            //Shapes.Initialize(new TensorShapeConfig() { Items = new long?[] { dim } });
-            //Array.Initialize(Shapes, new TensorShapeConfig() { Items = new long?[] { dim } });
-            ////Shapes = new TensorShapeConfig[] { new TensorShapeConfig() { Items = new long?[] { dim } } };
+            NodeValue = value;
+            NestType = NestType.Node;
         }
 
-        public GeneralizedTensorShape(Shape shape)
+        public GeneralizedTensorShape(IEnumerable<Shape> values, string? name = null)
         {
-            Shapes = new TensorShapeConfig[] { shape };
+            ListValue = values.Select(s => new Nest<Shape>(s) as INestStructure<Shape>).ToList();
+            Name = name;
+            NestType = NestType.List;
         }
 
-        public GeneralizedTensorShape(TensorShapeConfig shape)
+        public GeneralizedTensorShape(Dictionary<string, Shape> value, string? name = null)
         {
-            Shapes = new TensorShapeConfig[] { shape };
+            DictValue = value.ToDictionary(x => x.Key, x => new Nest<Shape>(x.Value) as INestStructure<Shape>);
+            Name = name;
+            NestType = NestType.Dictionary;
         }
 
-        public GeneralizedTensorShape(TensorShapeConfig[] shapes)
+        public GeneralizedTensorShape(Nest<Shape> other)
         {
-            Shapes = shapes;
-        }
-
-        public GeneralizedTensorShape(IEnumerable<Shape> shape)
-        {
-            Shapes = shape.Select(x => (TensorShapeConfig)x).ToArray();
+            NestType = other.NestType;
+            NodeValue = other.NodeValue;
+            DictValue = other.DictValue;
+            ListValue = other.ListValue;
+            Name = other.Name;
         }
 
         public Shape ToSingleShape()
         {
-            if (Shapes.Length != 1)
+            var shapes = Flatten().ToList();
+            if (shapes.Count != 1)
             {
                 throw new ValueError("The generalized shape contains more than 1 dim.");
             }
-            var shape_config = Shapes[0];
-            Debug.Assert(shape_config is not null);
-            return new Shape(shape_config.Items.Select(x => x is null ? -1 : x.Value).ToArray());
+            return shapes[0];
         }
 
         public long ToNumber()
         {
-            if(Shapes.Length != 1 || Shapes[0].Items.Length != 1)
+            var shapes = Flatten().ToList();
+            if (shapes.Count != 1 || shapes[0].ndim != 1)
             {
                 throw new ValueError("The generalized shape contains more than 1 dim.");
             }
-            var res = Shapes[0].Items[0];
-            return res is null ? -1 : res.Value;
-        }
-
-        public Shape[] ToShapeArray()
-        {
-            return Shapes.Select(x => new Shape(x.Items.Select(y => y is null ? -1 : y.Value).ToArray())).ToArray();
-        }
-
-        public IEnumerable<long?> Flatten()
-        {
-            List<long?> result = new List<long?>();
-            foreach(var shapeConfig in Shapes)
-            {
-                result.AddRange(shapeConfig.Items);
-            }
-            return result;
-        }
-        public INestStructure<TOut> MapStructure<TOut>(Func<long?, TOut> func)
-        {
-            List<Nest<TOut>> lists = new();
-            foreach(var shapeConfig in Shapes)
-            {
-                lists.Add(new Nest<TOut>(shapeConfig.Items.Select(x => new Nest<TOut>(func(x)))));
-            }
-            return new Nest<TOut>(lists);
+            return shapes[0].dims[0];
         }
 
-        public Nest<long?> AsNest()
+        public INestStructure<TensorShapeConfig> ToTensorShapeConfigs()
         {
-            Nest<long?> DealWithSingleShape(TensorShapeConfig config)
-            {
-                if (config.Items.Length == 0)
-                {
-                    return Nest<long?>.Empty;
-                }
-                else if (config.Items.Length == 1)
-                {
-                    return new Nest<long?>(config.Items[0]);
-                }
-                else
-                {
-                    return new Nest<long?>(config.Items.Select(x => new Nest<long?>(x)));
-                }
-            }
-
-            if(Shapes.Length == 0)
-            {
-                return Nest<long?>.Empty;
-            }
-            else if(Shapes.Length == 1)
-            {
-                return DealWithSingleShape(Shapes[0]);
-            }
-            else
-            {
-                return new Nest<long?>(Shapes.Select(s => DealWithSingleShape(s)));
-            }
-        }
-        
-
-
-        public static implicit operator GeneralizedTensorShape(int dims)
-            => new GeneralizedTensorShape(dims);
-
-        public IEnumerator<long?[]> GetEnumerator()
-        {
-            foreach (var shape in Shapes)
-            {
-                yield return shape.Items;
-            }
+            return MapStructure(s => new TensorShapeConfig() { Items = s.dims.Select<long, long?>(x => x == -1 ? null : x).ToArray() });
         }
 
-        IEnumerator IEnumerable.GetEnumerator()
+        public static implicit operator GeneralizedTensorShape(Shape shape)
         {
-            return GetEnumerator();
+            return new GeneralizedTensorShape(shape);
         }
     }
 }

src/TensorFlowNET.Core/Common/Types/INest.cs renamed to src/TensorFlowNET.Core/Common/Types/INestStructure.cs

@@ -10,6 +10,19 @@ namespace Tensorflow.Common.Types
     /// </summary>
     public interface INestStructure<T>: INestable<T>
     {
+        NestType NestType { get; }
+
+        /// <summary>
+        /// The item count of depth 1 of the nested structure.
+        /// For example, [1, 2, [3, 4, 5]] has ShallowNestedCount = 3.
+        /// </summary>
+        int ShallowNestedCount { get; }
+        /// <summary>
+        /// The total item count of depth 1 of the nested structure.
+        /// For example, [1, 2, [3, 4, 5]] has TotalNestedCount = 5.
+        /// </summary>
+        int TotalNestedCount { get; }
+
         /// <summary>
         /// Flatten the Nestable object. Node that if the object contains only one value, 
         /// it will be flattened to an enumerable with one element.

src/TensorFlowNET.Core/Common/Types/Nest.Static.cs

@@ -13,7 +13,7 @@ public static class Nest
         /// <param name="template"></param>
         /// <param name="flatItems"></param>
         /// <returns></returns>
-        public static Nest<T> PackSequenceAs<T>(INestable<T> template, T[] flatItems)
+        public static Nest<TOut> PackSequenceAs<T, TOut>(INestable<T> template, TOut[] flatItems)
         {
             return template.AsNest().PackSequence(flatItems);
         }