using System; | |
using System.Collections.Generic; | |
using System.IO; | |
using System.Linq; | |
using System.Text; | |
using System.Threading.Tasks; | |
using TensorFlow; | |
namespace MachineLearning | |
{ | |
class Program | |
{ | |
private static string _modelPath; | |
static void Main(string[] args) | |
{ | |
// Path of the Frozen model | |
_modelPath = "D:\\net_Repos\\net\\MachineLearning\\Model\\frozen_model.pb"; | |
string modelFile = _modelPath; | |
float[,] data = {{3, 10, 7, 20, 5, 9, 7, 9, 4, 3}, | |
{ 3, 5, 7, 4, 5, 9, 7, 9, 4, 3}, | |
{ 2, 8, 8, 7, 8, 5, 5, 9, 7, 2}}; | |
// TensorflowSharp Session | |
using (var graph = new TFGraph()){ | |
var model = File.ReadAllBytes(modelFile); | |
graph.Import(model); | |
Console.Write("reached here"); | |
var session = new TFSession(graph); | |
var runner = session.GetRunner(); | |
Console.Write("reached here"); | |
// AddInput is the input node and Fetch is the output node in Tensorflow graph | |
runner.AddInput (graph ["Placeholder/inputs_placeholder"] [0], data).Fetch (graph ["Accuracy/predictions"] [0]); | |
var output = runner.Run(); | |
var result = output[0]; | |
var se = (Boolean[,])result.GetValue(jagged: false); | |
Console.WriteLine ("{0}[1]", result); | |
for (int i = 0; i < se.GetLength(0); i++){ | |
for (int j = 0; j < se.GetLength(1); j++){ | |
Console.WriteLine("{0}", se[i, j]); | |
} | |
} | |
} | |
Console.ReadLine(); | |
} | |
} | |
} |
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