tf.linalg.einsum #885

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

@@ -26,6 +26,9 @@ namespace Tensorflow
         {
             linalg_ops ops = new linalg_ops();
 
+            public Tensor einsum(string equation, Tensors inputs, string name = null)
+                => math_ops.einsum(equation, inputs, name: name);
+
             public Tensor eye(int num_rows,
                 int num_columns = -1,
                 Shape batch_shape = null,

src/TensorFlowNET.Core/Contexts/ExecuteOpArgs.cs

@@ -11,7 +11,11 @@ namespace Tensorflow
         public Func<Operation, object> GetGradientAttrs { get; set; }
         public object[] OpInputArgs { get; set; }
         public Dictionary<string, object> OpAttrs { get; set; }
-        
+
+        /// <summary>
+        /// 
+        /// </summary>
+        /// <param name="inputArgs">For array: OpInputArgs = new object[]{ }</param>
         [DebuggerStepThrough]
         public ExecuteOpArgs(params object[] inputArgs)
         {

src/TensorFlowNET.Core/Operations/math_ops.cs

@@ -230,6 +230,27 @@ namespace Tensorflow
             });
         }
 
+        public static Tensor einsum(string equation, Tensors inputs, string name = null)
+        {
+            return tf_with(ops.name_scope(name, "einsum", inputs), scope =>
+            {
+                name = scope;
+                return tf.Context.ExecuteOp("Einsum", name, new ExecuteOpArgs
+                {
+                    OpInputArgs = new object[] { inputs.ToArray() },
+                    GetGradientAttrs = (op) => new
+                    {
+                        equation = op.get_attr<string>("equation"),
+                        N = op.get_attr<int>("N"),
+                        T = op.get_attr<TF_DataType>("T")
+                    }
+                }.SetAttributes(new
+                {
+                    equation = equation
+                }));
+            });
+        }
+
         public static Tensor greater_equal<Tx, Ty>(Tx x, Ty y, string name = null)
             => gen_math_ops.greater_equal<Tx, Ty>(x, y, name: name);
         public static Tensor equal<Tx, Ty>(Tx x, Ty y, string name = null)

test/TensorFlowNET.UnitTest/ManagedAPI/LinalgTest.cs

@@ -45,5 +45,14 @@ namespace TensorFlowNET.UnitTest.ManagedAPI
             Assert.AreEqual(x_under_reg.shape, (4, 1));
             AssetSequenceEqual(x_under_reg.ToArray<float>(), new float[] { -0.04763567f, -1.214508f, 0.62748903f, 1.299031f });*/
         }
+
+        [TestMethod]
+        public void Einsum()
+        {
+            var m0 = tf.random.normal((2, 3));
+            var m1 = tf.random.normal((3, 5));
+            var e = tf.linalg.einsum("ij,jk->ik", (m0, m1));
+            Assert.AreEqual(e.shape, (2, 5));
+        }
     }
 }