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#!/bin/bash
# Sometimes you need to move your existing git repository
# to a new remote repository (/new remote origin).
# Here are a simple and quick steps that does exactly this.
#

### OPTION 1 ###########################################################################################
# Let's assume we call "old repo" the repository you wish
# to move, and "new repo" the one you wish to move to.
#

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The following are the breaking changes that were impacting the ML.NET samples (at https://github.com/dotnet/machinelearning-samples) when moving to v0.10:

1. IDataView moved to a different NuGet package: a. Error: error CS0246: The type or namespace name 'IDataView' could not be found (are you missing a using directive or an assembly reference?) b. Fix: Add using Microsoft.Data.DataView; i. The new NuGet package is added automatically when using 0.10 version

2. AsEnumerable() moved to mlContext.CreateEnumerable() a. Error: Severity Code Description Project File Line Suppression State

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using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Threading.Tasks;

namespace Microsoft.eShopOnContainers.WebMVC.Services
{
    /// <summary>
    /// When working with cloud services and Docker containers, it's very important to always catch

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        public async Task<Catalog> GetCatalogItems(int page,int take, int? brand, int? type)
        {
            _apiClient = new HttpClient();
            var itemsQs = $"items?pageIndex={page}&pageSize={take}";
            var filterQs = "";

            if (brand.HasValue || type.HasValue)
            {
                var brandQs = (brand.HasValue) ? brand.Value.ToString() : "null";
                var typeQs = (type.HasValue) ? type.Value.ToString() : "null";

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#!/bin/bash
# Sometimes you need to move your existing git repository
# to a new remote repository (/new remote origin).
# Here are a simple and quick steps that does exactly this.
#
# Let's assume we call "old repo" the repository you wish
# to move, and "new repo" the one you wish to move to.
#
### Step 1. Make sure you have a local copy of all "old repo"
### branches and tags.

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There are many more breaking changes in 0.9, but these are the ones that mostly the ML.NET samples faced when moving to v0.9:

	1. MakePredictionFunction() --> CreatePredictionEngine() --> Based on my original feedback and this [issue](https://github.com/dotnet/machinelearning/issues/1761), since it creates an object, not a function..
	
	2. The type or namespace name 'Microsoft.ML.Runtime' does not exist in the namespace 'Microsoft.ML' (Error: are you missing an assembly reference?)
		a. Data attributes are now in: using Microsoft.ML.Data; 
		b. TextLoader and other types moved to using Microsoft.ML.Data;
		c. Related, removed:
			using Microsoft.ML.Runtime.Learners;

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var dataReader = TextLoader.CreateReader(env,
                c => (
                    CustomerId: c.LoadText(0),
                    ProductId: c.LoadText(1),
                    Quantity: c.LoadFloat(2),
                    Label: c.LoadBool(3)),
                    separator: ',', hasHeader: true);
 
FieldAwareFactorizationMachinePredictor pred = null;
var ctx = new BinaryClassificationContext(env);

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  var onnxPath = GetOutputPath(subDir, "SaveModelToOnnxTest.onnx");
  var onnxAsJsonPath = GetOutputPath(subDir, "SaveModelToOnnxTest.json");

  OnnxConverter converter = new OnnxConverter()
  {
      InputsToDrop = new[] { "Label" },
      OutputsToDrop = new[] { "Label", "Features" },
      Onnx = onnxPath,
      Json = onnxAsJsonPath,
      Domain = "com.mydomain"

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pipeline.Add(new FieldAwareFactorizationMachineBinaryClassifier(){ LearningRate = 0.5f, Iter=2 });

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catalog.api:
  environment:
    - ASPNETCORE_ENVIRONMENT=Development
    - ASPNETCORE_URLS=http://0.0.0.0:80
    - ConnectionString=YOUR_VALUE
    - ... Other Environment Variables
  ports:
    - "5101:80"   # Important: In a production environment you should remove the external port (5101) kept here for microservice debugging purposes. 
                  # The API Gateway redirects and access through the internal port (80).