public async Task MlProcessing_ModelTraining_ModelPersisted()
{
var models = Harness.GetDependentFilesExcept(FolderId, FileType.Image, FileType.Tabular, FileType.Pdf);
var modelResponse = await JohnApi.GetModelEntityById(models.First());
modelResponse.EnsureSuccessStatusCode();
var modelJson = JToken.Parse(await modelResponse.Content.ReadAsStringAsync());
modelJson.Should().ContainsJson($@"
{{
'id': '{modelJson["id"].ToObject<Guid>()}',
'blob': *EXIST*,
'ownedBy': '{JohnId}',
'createdBy': '{JohnId}',
'createdDateTime': *EXIST*,
'updatedBy': '{JohnId}',
'updatedDateTime': *EXIST*,
'parentId': '{FolderId}',
'name': 'Naive Bayes',
'status': 'Processed',
'version': 11,
'method': 'NaiveBayes',
'className': 'ClassName',
'subSampleSize': '0.2',
'kFold': 4,
'fingerprints': [
{{
'type': '1',
'size': 1024,
'radius': 3
}}],
'images': *EXIST*
}}", new List <string> {
"testDatasetSize"
});
var modelNodeResponse = await JohnApi.GetNodeById(models.First());
modelNodeResponse.EnsureSuccessStatusCode();
var nodeJson = JToken.Parse(await modelNodeResponse.Content.ReadAsStringAsync());
nodeJson.Should().ContainsJson($@"
{{
'id': '{modelJson["id"].ToObject<Guid>()}',
'blob': *EXIST*,
'type': 'Model',
'ownedBy': '{JohnId}',
'createdBy': '{JohnId}',
'createdDateTime': *EXIST*,
'updatedBy': '{JohnId}',
'updatedDateTime': *EXIST*,
'parentId': '{FolderId}',
'name': 'Naive Bayes',
'status': 'Processed',
'version': 11,
'images': *EXIST*
}}");
}
public async Task MlProcessing_ModelTraining_ModelProcessed()
{
var models = Harness.GetDependentFilesExcept(FolderId, FileType.Image, FileType.Tabular, FileType.Pdf);
var modelResponse = await JohnApi.GetModelEntityById(models.First());
modelResponse.EnsureSuccessStatusCode();
var modelJson = JToken.Parse(await modelResponse.Content.ReadAsStringAsync());
modelJson["status"].ToObject <string>().ShouldBeEquivalentTo("Processed");
}
