LinearRegression

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

@@ -11,6 +11,11 @@ namespace Tensorflow
             return gen_math_ops.add(a, b);
         }
 
+        public static unsafe Tensor add(Tensor a, RefVariable b)
+        {
+            return gen_math_ops.add(a, b);
+        }
+
         public static unsafe Tensor multiply(Tensor x, Tensor y)
         {
             return gen_math_ops.mul(x, y);

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -20,6 +20,17 @@ namespace Tensorflow
             return new Tensor(_op, 0, _op.OutputType(0));
         }
 
+        public static Tensor add(Tensor a, RefVariable b)
+        {
+            var keywords = new Dictionary<string, object>();
+            keywords.Add("x", a);
+            keywords.Add("y", b);
+
+            var _op = _op_def_lib._apply_op_helper("Add", name: "add", keywords: keywords);
+
+            return new Tensor(_op, 0, _op.OutputType(0));
+        }
+
         public static Tensor mul(Tensor x, Tensor y)
         {
             var keywords = new Dictionary<string, object>();

test/TensorFlowNET.Examples/LinearRegression.cs

@@ -36,7 +36,11 @@ namespace TensorFlowNET.Examples
             var W = tf.Variable(rng.randn<double>(), name: "weight");
             var b = tf.Variable(rng.randn<double>(), name: "bias");
 
-            var aa = tf.multiply(X, W);
+            var part1 = tf.multiply(X, W);
+            var pred = tf.add(part1, b);
+
+            // Mean squared error
+            var cost = tf.reduce_sum(tf.pow(pred - Y, 2)) / (2 * n_samples);
         }
     }
 }