Merge pull request dotnet#41 from dotnet/master

Update live with master

Author: JRAlexander

dotnet/xml/Microsoft.ML.Models/OnnxConverter.xml

@@ -55,53 +55,7 @@
       <Docs>
         <param name="model">Model that needs to be converted to ONNX format.</param>
         <summary>
-          <a href="https://onnx.ai/">ONNX</a> is an intermediate representation format
-             for machine learning models. It is used to make models portable such that you can
-             train a model using a toolkit and run it in another tookit's runtime, for example,
-             you can create a model using ML.NET, export it to an ONNX-ML model file,
-             then load and run that ONNX-ML model in Windows ML, on an UWP Windows 10 app.
-            
-             This API converts an ML.NET model to ONNX-ML format by inspecting the transform pipeline
-             from the end, checking for components that know how to save themselves as ONNX.
-             The first item in the transform pipeline that does not know how to save itself
-             as ONNX, is considered the "input" to the ONNX pipeline. (Ideally this would be the
-             original loader itself, but this may not be possible if the user used unsavable
-             transforms in defining the pipe.) All the columns in the source that are a type the
-             ONNX knows how to deal with will be tracked. Intermediate transformations of the
-             data appearing as new columns will appear in the output block of the ONNX, with names
-             derived from the corresponding column names. The ONNX JSON will be serialized to a
-             path defined through the Json option.
-            
-             This API supports the following arguments:
-             <see cref="P:Microsoft.ML.Models.OnnxConverter.Onnx" /> indicates the file to write the ONNX protocol buffer file to. This is optional.
-             <see cref="P:Microsoft.ML.Models.OnnxConverter.Json" /> indicates the file to write the JSON representation of the ONNX model. This is optional.
-             <see cref="P:Microsoft.ML.Models.OnnxConverter.Name" /> indicates the name property in the ONNX model. If left unspecified, it will
-             be the extension-less name of the file specified in the onnx indicates the protocol buffer file
-             to write the ONNX representation to.
-             <see cref="P:Microsoft.ML.Models.OnnxConverter.Domain" /> indicates the domain name of the model. ONNX uses reverse domain name space indicators.
-             For example com.microsoft.cognitiveservices. This is a required field.
-             <see cref="P:Microsoft.ML.Models.OnnxConverter.InputsToDrop" /> is a string array of input column names to omit from the input mapping.
-             A common scenario might be to drop the label column, for instance, since it may not be practically
-             useful for the pipeline. Note that any columns depending on these naturally cannot be saved.
-             <see cref="P:Microsoft.ML.Models.OnnxConverter.OutputsToDrop" /> is similar, except for the output schema. Note that the pipeline handler
-             is currently not intelligent enough to drop intermediate calculations that produce this value: this will
-             merely omit that value from the actual output.
-            
-             Transforms that can be exported to ONNX
-             1. Concat
-             2. KeyToVector
-             3. NAReplace
-             4. Normalize
-             5. Term
-             6. Categorical
-            
-             Learners that can be exported to ONNX
-             1. FastTree
-             2. LightGBM
-             3. Logistic Regression
-            
-             See <a href="https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/OnnxTests.cs" />
-             for an example on how to train a model and then convert that model to ONNX.
+          Converts an ML.NET model to ONNX-ML format.
              </summary>
         <remarks>
           <para>
@@ -297,4 +251,4 @@
       </Docs>
     </Member>
   </Members>
-</Type>
+</Type>