using NumSharp.Core; using System; using System.Collections.Generic; using System.Text; using Tensorflow; namespace TensorFlowNET.Examples { /// /// Basic Operations example using TensorFlow library. /// https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1_Introduction/basic_operations.py /// public class BasicOperations : IExample { private Session sess; public void Run() { // Basic constant operations // The value returned by the constructor represents the output // of the Constant op. var a = tf.constant(2); var b = tf.constant(3); // Launch the default graph. using (sess = tf.Session()) { Console.WriteLine("a=2, b=3"); Console.WriteLine($"Addition with constants: {sess.run(a + b)}"); Console.WriteLine($"Multiplication with constants: {sess.run(a * b)}"); } // Basic Operations with variable as graph input // The value returned by the constructor represents the output // of the Variable op. (define as input when running session) // tf Graph input a = tf.placeholder(tf.int16); b = tf.placeholder(tf.int16); // Define some operations var add = tf.add(a, b); var mul = tf.multiply(a, b); // Launch the default graph. using(sess = tf.Session()) { var feed_dict = new Dictionary(); feed_dict.Add(a, (short)2); feed_dict.Add(b, (short)3); // Run every operation with variable input Console.WriteLine($"Addition with variables: {sess.run(add, feed_dict)}"); Console.WriteLine($"Multiplication with variables: {sess.run(mul, feed_dict)}"); } // ---------------- // More in details: // Matrix Multiplication from TensorFlow official tutorial // Create a Constant op that produces a 1x2 matrix. The op is // added as a node to the default graph. // // The value returned by the constructor represents the output // of the Constant op. } } }