Add CacheDataset.

Author: Oceania2018

src/TensorFlowNET.Core/Data/CacheDataset.cs

@@ -0,0 +1,23 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using static Tensorflow.Binding;
+
+namespace Tensorflow
+{
+    public class CacheDataset : UnaryUnchangedStructureDataset
+    {
+        Tensor _filename;
+        public CacheDataset(IDatasetV2 input_dataset,
+            string filename = "") :
+            base(input_dataset)
+        {
+            _filename = tf.convert_to_tensor(filename, dtype: TF_DataType.TF_STRING, name: "filename");
+            variant_tensor = ops.cache_dataset_v2(input_dataset.variant_tensor,
+                _filename,
+                ops.dummy_memory_cache(),
+                output_types,
+                output_shapes);
+        }
+    }
+}

src/TensorFlowNET.Core/Data/DatasetV2.cs

@@ -23,6 +23,9 @@ public class DatasetV2 : IDatasetV2
 
         public TensorSpec[] element_spec => structure;
 
+        public IDatasetV2 cache(string filename = "")
+            => new CacheDataset(this, filename: filename);
+
         public IDatasetV2 take(int count = -1)
             => new TakeDataset(this, count: count);
 
@@ -47,6 +50,16 @@ public IDatasetV2 skip(int count)
         public IDatasetV2 optimize(string[] optimizations, string[] optimization_configs)
             => new OptimizeDataset(this, optimizations, optimization_configs: optimization_configs);
 
+        public IDatasetV2 map(Func<Tensor, Tensor> map_func,
+            bool use_inter_op_parallelism = true,
+            bool preserve_cardinality = false,
+            bool use_legacy_function = false)
+            => new MapDataset(this, 
+                map_func,
+                use_inter_op_parallelism: use_inter_op_parallelism,
+                preserve_cardinality: preserve_cardinality,
+                use_legacy_function: use_legacy_function);
+
         public IDatasetV2 model(AutotuneAlgorithm algorithm, long cpu_budget)
             => new ModelDataset(this, algorithm, cpu_budget);
 

src/TensorFlowNET.Core/Data/IDatasetV2.cs

@@ -1,5 +1,6 @@
 using System;
 using System.Collections.Generic;
+using System.Linq.Expressions;
 using System.Text;
 using Tensorflow.Framework.Models;
 
@@ -17,6 +18,13 @@ public interface IDatasetV2 : IEnumerable<(Tensor, Tensor)>
 
         TensorSpec[] structure { get; set; }
 
+        /// <summary>
+        /// Caches the elements in this dataset.
+        /// </summary>
+        /// <param name="filename"></param>
+        /// <returns></returns>
+        IDatasetV2 cache(string filename="");
+
         /// <summary>
         /// 
         /// </summary>
@@ -49,6 +57,11 @@ public interface IDatasetV2 : IEnumerable<(Tensor, Tensor)>
 
         IDatasetV2 optimize(string[] optimizations, string[] optimization_configs);
 
+        IDatasetV2 map(Func<Tensor, Tensor> map_func, 
+            bool use_inter_op_parallelism = true,
+            bool preserve_cardinality = false,
+            bool use_legacy_function = false);
+
         IDatasetV2 model(AutotuneAlgorithm algorithm, long cpu_budget);
 
         /// <summary>

src/TensorFlowNET.Core/Data/MapDataset.cs

@@ -0,0 +1,28 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Tensorflow
+{
+    /// <summary>
+    /// A `Dataset` that maps a function over elements in its input.
+    /// </summary>
+    public class MapDataset : UnaryDataset
+    {
+        public MapDataset(IDatasetV2 input_dataset,
+            Func<Tensor, Tensor> map_func,
+            bool use_inter_op_parallelism = true,
+            bool preserve_cardinality = false,
+            bool use_legacy_function = false) : base(input_dataset)
+        {
+            foreach(var input in input_dataset)
+            {
+                var data = map_func(input.Item1);
+            }
+
+            variant_tensor = ops.map_dataset(input_dataset.variant_tensor,
+                output_types,
+                output_shapes);
+        }
+    }
+}

src/TensorFlowNET.Core/Eager/EagerRunner.TFE_FastPathExecute.cs

@@ -381,6 +381,9 @@ bool SetOpAttrScalar(Context ctx, SafeOpHandle op,
                     c_api.TFE_OpSetAttrShape(op, key, dims, dims.Length, status.Handle);
                     status.Check(true);
                     break;
+                case TF_AttrType.TF_ATTR_FUNC:
+                    c_api.TFE_OpSetAttrFunctionName(op, key, value.ToString(), value.ToString().Length);
+                    break;
                 default:
                     throw new NotImplementedException($"SetOpAttrScalar for {type}");
             }

src/TensorFlowNET.Core/Eager/c_api.eager.cs

@@ -196,6 +196,9 @@ public static void TFE_Execute(SafeOpHandle op, SafeTensorHandleHandle[] retvals
         [DllImport(TensorFlowLibName)]
         public static extern void TFE_OpSetAttrBool(SafeOpHandle op, string attr_name, bool value);
 
+        [DllImport(TensorFlowLibName)]
+        public static extern void TFE_OpSetAttrFunctionName(SafeOpHandle op, string attr_name, string data, int length);
+
         /// <summary>
         /// 
         /// </summary>

src/TensorFlowNET.Core/Operations/dataset_ops.cs

@@ -155,6 +155,24 @@ public Tensor dummy_seed_generator(string name = null)
             throw new NotImplementedException("");
         }
 
+        public Tensor cache_dataset_v2(Tensor input_dataset, Tensor filename, Tensor cache,
+            TF_DataType[] output_types, TensorShape[] output_shapes,
+            string name = null)
+        {
+            if (tf.Context.executing_eagerly())
+            {
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "CacheDatasetV2", name,
+                    null,
+                    input_dataset, filename, cache,
+                    "output_types", output_types,
+                    "output_shapes", output_shapes);
+                return results[0];
+            }
+
+            throw new NotImplementedException("");
+        }
+
         /// <summary>
         /// Creates a dataset that batches `batch_size` elements from `input_dataset`.
         /// </summary>
@@ -187,6 +205,24 @@ public Tensor batch_dataset_v2(Tensor input_dataset, Tensor buffer_size,
             throw new NotImplementedException("");
         }
 
+        /// <summary>
+        /// 
+        /// </summary>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public Tensor dummy_memory_cache(string name = "")
+        {
+            if (tf.Context.executing_eagerly())
+            {
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "DummyMemoryCache", name,
+                    null);
+                return results[0];
+            }
+
+            throw new NotImplementedException("");
+        }
+
         /// <summary>
         /// Creates a dataset that asynchronously prefetches elements from `input_dataset`.
         /// </summary>
@@ -354,6 +390,33 @@ public ITensorOrOperation make_iterator(Tensor dataset, Tensor iterator, string
             throw new NotImplementedException("");
         }
 
+        /// <summary>
+        /// 
+        /// </summary>
+        /// <param name="dataset"></param>
+        /// <param name="iterator"></param>
+        /// <param name="name"></param>
+        /// <returns></returns>
+        public Tensor map_dataset(Tensor dataset, TF_DataType[] output_types, TensorShape[] output_shapes, 
+            bool use_inter_op_parallelism = true, bool preserve_cardinality = false, string name = null)
+        {
+            if (tf.Context.executing_eagerly())
+            {
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "MapDataset", name,
+                    null,
+                    dataset, new Tensor[0],
+                    "f", "MapDataset",
+                    "output_types", output_types, 
+                    "output_shapes", output_shapes,
+                    "use_inter_op_parallelism", use_inter_op_parallelism,
+                    "preserve_cardinality", preserve_cardinality);
+                return results[0];
+            }
+
+            throw new NotImplementedException("");
+        }
+
         /// <summary>
         /// A container for an iterator resource.
         /// </summary>

test/TensorFlowNET.UnitTest/Dataset/DatasetTest.cs

@@ -3,6 +3,7 @@
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;
+using Tensorflow;
 using Tensorflow.Keras;
 using Tensorflow.UnitTest;
 using static Tensorflow.Binding;
@@ -116,5 +117,35 @@ public void Skip()
                 value ++;
             }
         }
+
+        [TestMethod, Ignore]
+        public void Map()
+        {
+            long value = 0;
+
+            var dataset = tf.data.Dataset.range(3);
+            var dataset1 = dataset.map(x => x);
+
+            foreach (var item in dataset)
+            {
+                Assert.AreEqual(value, (long)item.Item1);
+                value++;
+            }
+        }
+
+        [TestMethod]
+        public void Cache()
+        {
+            long value = 0;
+
+            var dataset = tf.data.Dataset.range(5);
+            dataset = dataset.cache();
+
+            foreach (var item in dataset)
+            {
+                Assert.AreEqual(value, (long)item.Item1);
+                value++;
+            }
+        }
     }
 }