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Adaptado para que agrupe los datos

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This commit is contained in:
Miguel Á M.S.
2023-01-19 10:55:47 +01:00
parent 105e2e471e
commit 8b128ceb46
2 changed files with 85 additions and 42 deletions
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34
testML/DictionaryToObjectConverter.cs
View File

@@ -10,14 +10,18 @@ using System.Linq;
using System.Reflection;
using System.Runtime.CompilerServices;
using System.Text;
using System.Text.RegularExpressions;
using System.Threading.Tasks;
namespace testML
{
public static class DictionaryToObjectConverter
{
public static IEnumerable<object> Convert(List<Dictionary<string, object>> data, string toPredict, out Type classType, out Type classPredictionType, out DataViewSchema schema)
public static IEnumerable<object> Convert(List<Dictionary<string, object>> data, string toPredict, string objectFilename, out Type classType, out Type classPredictionType, out DataViewSchema schema)
{
var regexCR = new Regex(@"_CR\d+");
var currentCR = regexCR.Match(toPredict).Groups[0].Value;
var schemaBuilder = new DataViewSchema.Builder();
var definition = new Dictionary<string, Type>();
@@ -27,6 +31,11 @@ namespace testML
{
foreach (var key in sample.Keys)
{
if (!key.Contains(currentCR))
{
continue;
}
//Buscamos el tipo
var sampleValue = (from x in data where x.ContainsKey(key) && x[key] != null select x[key]).FirstOrDefault();
if (sampleValue != null)
@@ -58,22 +67,34 @@ namespace testML
}
}
var className = "OBJ"+ Path.GetFileNameWithoutExtension(objectFilename).Replace(".", "_");
Assembly dllAssembly = null;
if (File.Exists(Path.Combine(Environment.CurrentDirectory, objectFilename)))
{
dllAssembly = Assembly.LoadFrom(Path.Combine(Environment.CurrentDirectory, objectFilename));
}
else
{
var converter = new DictionaryToObjectConverterClass()
{
ClassName = "OBJ" + Guid.NewGuid().ToString("N").ToUpper(),
ClassName = className,
ToPredict = toPredict,
Definition = definition
};
var classCode = converter.TransformText();
File.WriteAllText(Path.Combine(Environment.CurrentDirectory, objectFilename + ".cs"), classCode, Encoding.UTF8);
string exDir = System.Runtime.InteropServices.RuntimeEnvironment.GetRuntimeDirectory().Trim(Path.DirectorySeparatorChar);
CompilerParameters compilerParameters = new CompilerParameters
{
GenerateExecutable = false,
GenerateInMemory = true,
GenerateInMemory = false,
IncludeDebugInformation = true,
TreatWarningsAsErrors = false,
OutputAssembly = Path.Combine(Environment.CurrentDirectory, objectFilename),
CompilerOptions = string.Format("/target:library /lib:{0}", exDir)
};
@@ -92,10 +113,11 @@ namespace testML
new string[] { classCode }
);
var dllAssembly = compilerResults.CompiledAssembly;
dllAssembly = compilerResults.CompiledAssembly;
}
classType = dllAssembly.GetType("DictionaryToObjectConverterNamespace." + converter.ClassName);
classPredictionType = dllAssembly.GetType("DictionaryToObjectConverterNamespace." + converter.ClassName + "Prediction");
classType = dllAssembly.GetType("DictionaryToObjectConverterNamespace." + className);
classPredictionType = dllAssembly.GetType("DictionaryToObjectConverterNamespace." + className + "Prediction");
Type listType = typeof(List<>);
Type genericType = listType.MakeGenericType(classType);

31
testML/Program.cs
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@@ -16,6 +16,7 @@ using System.Reflection;
using System.Security.AccessControl;
using System.Security.Cryptography;
using System.Text;
using System.Text.RegularExpressions;
using System.Threading.Tasks;
using System.Xml.Linq;
using static TorchSharp.torch.utils;
@@ -30,21 +31,23 @@ namespace testML
{
XSSFWorkbook wb;
//using (FileStream file = new FileStream(@"C:\Users\miguel.maldonado\Downloads\entrenar_IAMenos.xlsx", FileMode.Open, FileAccess.Read))
using (FileStream file = new FileStream(@"C:\Users\miguel.maldonado\Downloads\entrenar_IA.xlsx", FileMode.Open, FileAccess.Read))
using (FileStream file = new FileStream(@"entrenar_IA (1).xlsx", FileMode.Open, FileAccess.Read))
{
wb = new XSSFWorkbook(file);
}
var sheet = wb.GetSheetAt(0);
var headerRow = sheet.GetRow(0);
var CRRow = sheet.GetRow(0);
var headerRow = sheet.GetRow(1);
#region Preparamos los datos de entrenamiento
var tmpData = new List<Dictionary<string, object>>();
for (var r = 1; r < sheet.LastRowNum - 1; r++)
for (var r = headerRow.RowNum + 1; r < sheet.LastRowNum - 1; r++)
{
//if (r == 50) break;
Console.WriteLine(string.Format("{0} / {1}", r, sheet.LastRowNum - 1));
@@ -58,6 +61,7 @@ namespace testML
{
var usePrefix = true;
var columnName = headerRow.GetCell(c)?.StringCellValue;
var crCell = CRRow.GetCell(c)?.NumericCellValue;
columnName = FixColumnName(columnName);
@@ -93,6 +97,12 @@ namespace testML
}
var finalColumnName = (usePrefix ? prefix : string.Empty) + columnName;
if (crCell != null)
{
finalColumnName = finalColumnName + "_CR" + crCell.Value.ToString();
}
if (value is string)
{
rowData.Add(finalColumnName, valuePrefix + value);
@@ -164,11 +174,21 @@ namespace testML
private static void MakePrediction(List<Dictionary<string, object>> tmpData, string columnToPredict)
{
var regexCR = new Regex(@"_CR\d+");
var currentCR = regexCR.Match(columnToPredict).Groups[0].Value;
var firstRow = tmpData[0] as IDictionary<string, object>;
var hashKey = new StringBuilder();
foreach (var key in firstRow.Keys.Where(x => !x.StartsWith("DESCENDIENTE_") && (x.Contains("_S4i") || x.Contains("_SNP"))).OrderBy(x => x))
{
if(!key.Contains(currentCR))
{
continue;
}
if (hashKey.Length > 0) { hashKey.Append("+"); }
hashKey.Append(key);
}
@@ -177,6 +197,7 @@ namespace testML
var hash = string.Join("", md5.ComputeHash(new MemoryStream(new UTF8Encoding(false).GetBytes(hashKey.ToString()))).Select(x => x.ToString("X2").ToUpper()).ToArray());
var modelFilename = columnToPredict + "." + hash + ".zip";
var objectFilename = columnToPredict + "." + hash + ".dll";
#endregion
@@ -185,7 +206,6 @@ namespace testML
MLContext mlContext = new MLContext();
mlContext.Log += (_, e) =>
{
if (e.Kind == Microsoft.ML.Runtime.ChannelMessageKind.Trace && e.Source.EndsWith(" Cursor")) { return; }
@@ -203,7 +223,7 @@ namespace testML
};
var dataConverted = DictionaryToObjectConverter.Convert(tmpData, columnToPredict, out Type classType, out Type classPredictionType, out DataViewSchema schema);
var dataConverted = DictionaryToObjectConverter.Convert(tmpData, columnToPredict, objectFilename, out Type classType, out Type classPredictionType, out DataViewSchema schema);
ITransformer _trainedModel;
if (!File.Exists(modelFilename))
@@ -236,6 +256,7 @@ namespace testML
var trainingPipeline = BuildAndTrainModel(mlContext, trainData, pipeline, classType, classPredictionType);
Console.WriteLine("Training...");
_trainedModel = trainingPipeline.Fit(trainData);
mlContext.Model.Save(_trainedModel, data.Schema, modelFilename);