tf.data.Dataset shard() #446

src/TensorFlowNET.Core/Data/DatasetV2.cs

@@ -35,6 +35,9 @@ namespace Tensorflow
         public IDatasetV2 repeat(int count = -1)
             => new RepeatDataset(this, count: count);
 
+        public IDatasetV2 shard(int num_shards, int index)
+            => new ShardDataset(this, num_shards, index);
+
         public IDatasetV2 shuffle(int buffer_size, int? seed = null, bool reshuffle_each_iteration = true)
             => new ShuffleDataset(this, buffer_size, seed: seed, reshuffle_each_iteration: reshuffle_each_iteration);
 

src/TensorFlowNET.Core/Data/IDatasetV2.cs

@@ -24,6 +24,14 @@ namespace Tensorflow
         /// <returns></returns>
         IDatasetV2 repeat(int count = -1);
 
+        /// <summary>
+        /// Creates a `Dataset` that includes only 1/`num_shards` of this dataset.
+        /// </summary>
+        /// <param name="num_shards">The number of shards operating in parallel</param>
+        /// <param name="index">The worker index</param>
+        /// <returns></returns>
+        IDatasetV2 shard(int num_shards, int index);
+
         IDatasetV2 shuffle(int buffer_size, int? seed = null, bool reshuffle_each_iteration = true);
 
         IDatasetV2 batch(int batch_size, bool drop_remainder = false);

src/TensorFlowNET.Core/Data/ShardDataset.cs

@@ -0,0 +1,31 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using static Tensorflow.Binding;
+
+namespace Tensorflow
+{
+    /// <summary>
+    /// A `Dataset` for sharding its input.
+    /// </summary>
+    public class ShardDataset : UnaryUnchangedStructureDataset
+    {
+        Tensor _num_shards;
+        Tensor _index;
+
+        public ShardDataset(IDatasetV2 input_dataset,
+            int num_shards,
+            int index) : base(input_dataset)
+        {
+            _num_shards = tf.convert_to_tensor(num_shards, dtype: TF_DataType.TF_INT64, name: "num_shards");
+            _index = tf.convert_to_tensor(index, dtype: TF_DataType.TF_INT64, name: "index");
+
+            variant_tensor = ops.shard_dataset
+                (input_dataset.variant_tensor,
+                num_shards: _num_shards,
+                index: _index,
+                input_dataset.output_types,
+                input_dataset.output_shapes);
+        }
+    }
+}

src/TensorFlowNET.Core/Operations/dataset_ops.cs

@@ -65,6 +65,25 @@ namespace Tensorflow
             throw new NotImplementedException("");
         }
 
+        public Tensor shard_dataset(Tensor input_dataset, Tensor num_shards, Tensor index,
+            TF_DataType[] output_types, TensorShape[] output_shapes, 
+            bool require_non_empty = false, string name = null)
+        {
+            if (tf.Context.executing_eagerly())
+            {
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
+                    "ShardDataset", name,
+                    null,
+                    input_dataset, num_shards, index,
+                    "require_non_empty", require_non_empty,
+                    "output_types", output_types,
+                    "output_shapes", output_shapes);
+                return results[0];
+            }
+
+            throw new NotImplementedException("");
+        }
+
         public Tensor shuffle_dataset_v3(Tensor input_dataset, Tensor buffer_size, 
             Tensor seed, Tensor seed2, Tensor seed_generator,
             TF_DataType[] output_types, TensorShape[] output_shapes, 

test/TensorFlowNET.UnitTest/Dataset/DatasetTest.cs

@@ -61,5 +61,28 @@ namespace TensorFlowNET.UnitTest.Dataset
             }
             Assert.AreEqual(5, n);
         }
+
+        [TestMethod]
+        public void Shard()
+        {
+            long value = 0;
+
+            var dataset1 = tf.data.Dataset.range(10);
+            var dataset2 = dataset1.shard(num_shards: 3, index: 0);
+
+            foreach (var item in dataset2)
+            {
+                Assert.AreEqual(value, (long)item.Item1);
+                value += 3;
+            }
+
+            value = 1;
+            var dataset3 = dataset1.shard(num_shards: 3, index: 1);
+            foreach (var item in dataset3)
+            {
+                Assert.AreEqual(value, (long)item.Item1);
+                value += 3;
+            }
+        }
     }
 }