BuildDivisorTransitions application added.

EvenPerfectBitScanner/MLModel1.consumption.cs

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+// This file was auto-generated by ML.NET Model Builder.
+using Microsoft.ML;
+using Microsoft.ML.Data;
+using System;
+using System.Linq;
+using System.IO;
+using System.Collections.Generic;
+namespace EvenPerfectBitScanner
+{
+    public partial class MLModel1
+    {
+        /// <summary>
+        /// model input class for MLModel1.
+        /// </summary>
+        #region model input class
+        public class ModelInput
+        {
+            [LoadColumn(0)]
+            [ColumnName(@"p")]
+            public float P { get; set; }
+
+            [LoadColumn(1)]
+            [ColumnName(@"divisor")]
+            public float Divisor { get; set; }
+
+            [LoadColumn(2)]
+            [ColumnName(@"lastDigit")]
+            public float LastDigit { get; set; }
+
+            [LoadColumn(3)]
+            [ColumnName(@"k")]
+            public float K { get; set; }
+
+            [LoadColumn(4)]
+            [ColumnName(@"lastMersenneDigit")]
+            public float LastMersenneDigit { get; set; }
+
+            [LoadColumn(5)]
+            [ColumnName(@"isNextKHigher")]
+            public float IsNextKHigher { get; set; }
+
+        }
+
+        #endregion
+
+        /// <summary>
+        /// model output class for MLModel1.
+        /// </summary>
+        #region model output class
+        public class ModelOutput
+        {
+            [ColumnName(@"p")]
+            public float P { get; set; }
+
+            [ColumnName(@"divisor")]
+            public float Divisor { get; set; }
+
+            [ColumnName(@"lastDigit")]
+            public float LastDigit { get; set; }
+
+            [ColumnName(@"k")]
+            public float K { get; set; }
+
+            [ColumnName(@"lastMersenneDigit")]
+            public float LastMersenneDigit { get; set; }
+
+            [ColumnName(@"isNextKHigher")]
+            public float IsNextKHigher { get; set; }
+
+            [ColumnName(@"Features")]
+            public float[] Features { get; set; }
+
+            [ColumnName(@"Score")]
+            public float Score { get; set; }
+
+        }
+
+        #endregion
+
+        private static string MLNetModelPath = Path.GetFullPath("MLModel1.mlnet");
+
+        public static readonly Lazy<PredictionEngine<ModelInput, ModelOutput>> PredictEngine = new Lazy<PredictionEngine<ModelInput, ModelOutput>>(() => CreatePredictEngine(), true);
+
+
+        private static PredictionEngine<ModelInput, ModelOutput> CreatePredictEngine()
+        {
+            var mlContext = new MLContext();
+            ITransformer mlModel = mlContext.Model.Load(MLNetModelPath, out var _);
+            return mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(mlModel);
+        }
+
+        /// <summary>
+        /// Use this method to predict on <see cref="ModelInput"/>.
+        /// </summary>
+        /// <param name="input">model input.</param>
+        /// <returns><seealso cref=" ModelOutput"/></returns>
+        public static ModelOutput Predict(ModelInput input)
+        {
+            var predEngine = PredictEngine.Value;
+            return predEngine.Predict(input);
+        }
+    }
+}